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News Article | February 21, 2017
Site: www.theenergycollective.com

NucNet: Private companies have invested over $1bn in the development of small modular reactors (SMRs), but more investment through public-private partnerships is needed to assure that SMRs are a viable option in the mid-2020s, the US-based SMR Start industry consortium said in a policy statement. SMR Start is urging Congress to authorize sufficient funds for an SMR commercial deployment program and called for the continuation and expansion of the existing licensing technical support program to include the design and engineering, regulatory review and approval of SMR technologies and facilities. The statement said that in addition to accomplishing the public benefit from SMR deployment, the federal government would receive a return on investment through taxes associated with investment, job creation and economic output over the lifetime of the SMR facilities that would otherwise not exist without federal investment. It also called for continuation of the loan guarantee program to support financing for the design and construction of SMR facilities and SMR component manufacturing facilities. The policy statement is online: http://bit.ly/2kQM1vG Members of the consortium include AREVA, Bechtel, BWXT, Dominion, Duke Energy, Energy Northwest, Fluor, Holtec International, NuScale Power, Ontario Power Generation, PSEG Nuclear, Southern Nuclear, TVA, and UAMPS Plant Vogtle could use new fuel when MOX is complete Augusta Chronicle: Proponents of the Savannah River Site’s mixed-oxide (MOX) fuel fabrication facility are touting the possibility that once in production, its output, PWR type fuel assemblies in the form of MOX fuel, could be used at Units 3 and 4 at Southern Nuclear’s Plant Vogtle. According to Areva Nuclear Materials LLC, one of the companies involved in MOX design and construction, the Energy Department planned for a subsidized cost structure to make the MOX fuel more attractive. Plant Vogtle, which could have four operating reactor units when the MOX plant is finished, could make the switch to the mixed-oxide fuel. Up to one-third of the reactor’s fuel assemblies could be MOX fuel. The advantage of the fuel is that there are longer periods between fuel outages during which time the reactor is not generating electricity nor making any money for its investors. “In order to accommodate the potential use of MOX fuel, modifications would be required for the plant’s physical structure, as well as the processes and procedures used to operate the facility.” He might have also added that the plant would have to modify the NRC license for each reactor based on the change in fuel type. The agency has no experience with this kind of modification of a license. AP: A federal appeals court has rejected a Virginia company’s bid to end the state’s decades-long ban on uranium mining. A panel of the 4th U.S. Circuit Court of Appeals in Richmond has upheld the ruling of a district judge who threw out a lawsuit from Virginia Uranium Inc. challenging the ban. The Pittsylvania County company wants to mine a 119-million-pound deposit of the radioactive ore. It argued that a federal law should pre-empt state regulations, but the courts disagreed. Does India still want the Westinghouse reactors despite Toshiba meltdown? Reuters, PTI: In a burst of what can charitably be characterized as wishful thinking, an Indian government official said he does not expect fallout from the financial meltdown at Toshiba Corp to halt plans to buy six nuclear reactors from the Japanese company’s U.S. nuclear unit Westinghouse. Indian wire services added details to the report. This statement was not made by NPCIL which is the main actor in all matters related to building new nuclear power plants. This raises a question of how credible the statement is as an expression of the Indian’s government’s views on Toshiba’s financial troubles. India has been in talks for years to build six Westinghouse AP1000 reactors in the southern state of Andhra Pradesh under its drive to expand nuclear generation and to move the economy off polluting fuels like coal. “As for the technical execution of the project, I do not see many problems,” Sekhar Basu, secretary of the Department of Atomic Energy that reports directly to Modi, told Reuters in a short telephone interview. The wire service reported that negotiations on the technical and commercial terms of the reactor deal have reached an advanced stage. Not mentioned in the report is any measure of relief from the terms of the supplier liability law that has kept U.S. firms out of the Indian market. Industry experts said that, if the project is still at all viable, the main logistical challenge would be to locate civil engineering contractors since Westinghouse would only provide the reactors. India has not yet signed a contract with Westinghouse, nor has cash changed hands. Basu said that talks on financing had not yet begun in earnest. Significantly, he also said the state-owned Nuclear Power Corporation of India (NPCIL) had yet to be updated by Westinghouse on recent developments. Westinghouse and NPCIL did not respond to requests for comment from wire service reporters. Separately, there is considerable pressure within India’s nuclear industdry to abandon the Westinghouse reactor project and build 700 MW PHWR reactors based on an Indian adaptation of the CANDU technology. Further, an amendment to the enabling legislation for NPCIL allows it to do joint development efforts with heavy industry such as steel and petrochemicals and even provide electricity for India’s vast electrified rail network. This is seen as an advantage and would build domestic capabilities, supply chains, and not have India relying on western technology. Albuquerque Journal: WIPP said it expects to begin accepting shipments of nuclear waste from storage sites around the country in April. Feb 14th marked three years since a radiation accident contaminated the Waste Isolation Pilot Plant outside Carlsbad. After struggling to clean up the deep underground repository, WIPP commenced waste emplacement last month. WIPP has been moving waste drums underground from an above-ground warehouse, where waste was being temporarily held when a drum of radioactive material burst underground on Feb. 14, 2014, and WIPP was shut down. WIPP has started off slowly, making just two emplacements per week from the waste handling building, according to a spokesman. When shipments begin, the facility is aiming to make about four emplacements per week by the end of the year compared with an average of 17 per week before the accident. Los Alamos National Laboratory is on the list of those sites expected to begin shipping in April, along with Department of Energy facilities at Idaho, Oak Ridge and Savannah River. LANL faced its own issues after investigators discovered that the drum that burst at WIPP had been improperly packed by a LANL subcontractor. The Idaho Falls Post Register reported that the Idaho Cleanup Project will send an estimated 61 shipments of radioactive waste to New Mexico’s Waste Isolation Pilot Plant over the next year, more than any other site, U.S. Department of Energy officials said. While Idaho cleanup contractor Fluor Idaho will send more than twice the number of shipments of any other site, it will not be nearly enough to make the necessary progress toward meeting a Dec. 31, 1995, Settlement Agreement deadline with the state of Idaho. Idaho has more than 900 shipments — or more than 20,000 individual containers — of transuranic waste that are supposed to leave by the end of next year.


No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. Male heterozygous ythdf2+/− fish in the *AB background were custom made by ZGeneBio. TALEN mutagenesis was performed to mutate ythdf2 (Ensembl ENSDART00000127043) with L1 recognition sequence 5′-GGACCTGGCCAATCCCC-3′, R1 recognition sequence 5′-GGCACAGTAATGCCACC-3′, and spacer sequence 5′-TCCCAATTCAGGAATG-3′. Purchased fish were outcrossed to in-house wild-type *AB fish. Embryos were obtained from natural crosses, were raised under standard conditions, and were staged according to literature26. Embryos were reared at 28.5 °C and all experiments and observations were performed as close to this temperature as possible. Fish lines were maintained in accordance with AAALAC research guidelines, under a protocol approved by the University of Chicago IACUC (Institutional Animal Care & Use Committee). The open reading frame of zebrafish ythdf2 was purchased from Open Biosystems (clone 5601005) and subcloned into a pCS2+ vector using restriction enzyme sites of BamHI and XhoI. The resulting vector was linearized by HindIII and used as a template for ythdf2 probe preparation. Antisense digoxigenin (DIG) RNA probes were generated by in vitro transcription using standard reagents and methods. In situ hybridization protocol was followed essentially as previously reported27. All experiments were repeated at least once from biological samples. Control and ythdf2 morpholinos (5′-TGGCTGACATTTCTCACTCCCCGGT-3′) were obtained from Gene Tools (Oregon). 3 ng of either control or gene-specific morpholino was injected into *AB wild-type embryos at the one-cell stage. GFP and mCherry were subcloned into pCS2+ vectors and linearized by NotI. GFP-m6A, GFP-A, and mCherry-capped and polyadenylated mRNA was generated by in vitro transcription using mMessage mMachine SP6 kit (Thermo Fisher) and Poly(A) tailing kit (Thermo Fisher) according to the manufacturer’s protocol. Products were purified with the MEGAclear transcription clean-up kit (Thermo Fisher) and used for injections directly. For GFP-m6A, we spiked 6 nmol m6ATP into the 100 nmol ATP supplied in the transcription reaction, in order to ensure that less than 0.3% of GFP mRNAs are without m6A on average. (GFP mRNA is 942 nt; each mRNA has 1.89 m6A on average.) 35 pg of either GFP reporter mRNA and 10 pg of mCherry mRNA were injected together in 1.25 nl into embryos at the one-cell stage. ythdf2 mRNA containing the ythdf2 5′ UTR and a 3′ Flag tag, which was used to rescue the mutant phenotype and validate the knockdown efficiency of ythdf2 MO, was constructed in pCS2+ vector (forward primer: 5′-CGTACGGATCCTGTCTGATCTGCAGCTGTAG-3′; reverse primer: 5′-CGATGCTCGAGTTACTTGTCATCGTCGTCCTTGTAATCTATTCCAGATGGAGCAAGGC-3′) and prepared in the same way as mCherry mRNAs. Antibodies used in this study are listed below in the format of name (application; catalogue number; supplier): mouse anti-Flag HRP conjugate (Western; A5892; Sigma), rabbit anti-m6A (m6A-seq and m6A-CLIP-seq; 202003; Synaptic Systems), rabbit anti-histone H3 (IF; ab5176; Abcam), and anti-rabbit Alexa Fluor 488 (IF; ab150077; Abcam). All images were observed with a Leica MZFLIII microscope and captured with a Nikon D5000 digital camera using Camera Control Pro (Nikon) software. For fluorescent microscopy, standard ET-GFP and TXR LP filters (Leica) were used. For bright field imaging of live embryos, only saturation was adjusted and was adjusted identically for all images. For fluorescent imaging of live embryos, no image processing was performed. For fluorescent imaging of fixed embryos, contrast and exposure were adjusted for all to obtain the lowest amount of background while preserving the morphology of all visible nuclei. All experiments were repeated at least once from biological samples. To compare the total amount of DNA in wild-type and mutant embryos at different time points during the MZT, 10 embryos per time point per condition were dechorionated and pipetted into standard DNA lysis buffer. The number of embryos in each tube was counted twice to ensure uniformity. Proteinase K was added to 100 μg ml−1 and the embryos were incubated for 4 h at ~55 °C with occasional mixing. Proteinase K was inactivated by a 10-min incubation at 95 °C and the DNA was then phenol-chloroform-extracted, ethanol-precipitated, and resuspended in 100 μl Tris (pH 8.5) and 1 mM EDTA using standard procedures. Double-stranded DNA content was measured with NanoDrop. Three biological replicates (comprised of the offspring of three different fish mating pairs of the appropriate genotype) were measured for each time point for both the control and experimental samples. Biological replicates were averaged together to determine the average DNA amount per time point per genotype and to compute standard errors of the mean. All DNA values were normalized to that of wild-type embryos at 2.5 h.p.f. Embryos were collected into standard 2× protein sample buffer with added β-mercaptoethanol and protease inhibitors and immediately put on ice for a few minutes. The embryo mixtures were carefully but thoroughly pipetted up and down to dissolve and homogenize the embryos, and then samples were heated at 95 °C for 5 min and frozen at −80 °C. Before use, samples were again heated for 5 min and then centrifuged at 12,000 r.p.m. to remove debris. Supernatants were loaded into a 10-well, 1.5 mm Novex 4–20% Tris-Glycine Mini Protein Gel (Thermo Fisher) with 6 embryos per well. The gel was transferred onto a nitrocellulose membrane using iBlot2 gel transfer system (Thermo Fisher) set to P3 for 7 min with iBlot2 mini gel transfer stacks (Thermo Fisher). Membranes were blocked in 5% BSA, 0.05% Tween-20 in PBS for 1 h, and then incubated overnight at 4 °C with anti-Flag–HRP conjugate (Sigma) diluted 1:10,000 in 3% BSA. Proteins were visualized using the SuperSignal West Pico Luminol/Enhancer solution (Thermo Fisher) in FluorChem M system (ProteinSimple). mRNA isolation for LC-MS/MS: total RNA was isolated from zebrafish embryos with TRIzol reagent (Invitrogen) and Direct-zol RNA MiniPrep kit (Zymo). mRNA was extracted by removal of contaminating rRNA using RiboMinus Eukaryote Kit v2 (Thermo Fisher) for two rounds. Total RNA isolation for RT–qPCR: we followed the instruction of Direct-zol RNA MiniPrep kit (Zymo) with DNase I digestion step. Total RNA was eluted with RNase-free water and used for RT–qPCR directly. 100–200 ng of mRNA was digested by nuclease P1 (2 U) in 25 μl of buffer containing 10 mM of NH OAc (pH 5.3) at 42 °C for 2 h, followed by the addition of NH HCO (1 M, 3 μl, freshly made) and alkaline phosphatase (0.5 U). After an additional incubation at 37 °C for 2 h, the sample was diluted to 50 μl and filtered (0.22 μm pore size, 4 mm diameter, Millipore), and 5 μl of the solution was injected into LC-MS/MS. Nucleosides were separated by reverse-phase ultra-performance liquid chromatography on a C18 column with on-line mass spectrometry detection using an Agilent 6410 QQQ triple-quadrupole LC mass spectrometer in positive electrospray ionization mode. The nucleosides were quantified by using the nucleoside to base ion mass transitions of 282 to 150 (m6A), and 268 to 136 (A). Quantification was performed in comparison with the standard curve obtained from pure nucleoside standards running on the same batch of samples. The ratio of m6A to A was calculated on the basis of the calibrated concentrations9. Total RNA was isolated from fish embryos collected at different time points with TRIzol reagent and Direct-zol RNA MiniPrep kit. For each time point, ~200 embryos were collected to ensure RNA yield and that samples were representative. mRNA was further purified using RiboMinus Eukaryote Kit v2. RNA fragmentation was performed by sonication at 10 ng μl−1 in 100 μl RNase-free water using Bioruptor Pico (Diagenode) with 30 s on/off for 30 cycles. m6A-immunoprecipitation (IP) and library preparation were performed according to the previous protocol17. Sequencing was carried out on Illumina HiSeq 2000 according to the manufacturer’s instructions. Additional high-throughput sequencing of zebrafish methylome was carried out using a modified m6A-seq method, which is similar to previously reported methods19, 20. Briefly, total RNA and mRNA were purified as previously described for m6A-seq. Purified mRNA (1 μg) was mixed with 2.5 μg of affinity purified anti-m6A polyclonal antibody (Synaptic Systems) in IPP buffer (150 mM NaCl, 0.1% NP-40, 10 mM Tris-HCl (pH 7.4)) and incubated for 2 h at 4 °C. The mixture was subjected to UV-crosslinking in a clear flat-bottom 96-well plate (Nalgene) on ice at 254 nm with 0.15 J for 3 times. The mixture was then digested with 1 U μl−1 RNase T1 at 22 °C for 6 min followed by quenching on ice. Next, the mixture was immunoprecipitated by incubation with protein-A beads (Invitrogen) at 4 °C for 1 h. After extensive washing, the mixture was digested again with 10 U μl−1 RNase T1 at 22 °C for 6 min followed by quenching on ice. After additional washing and on-bead end-repair, the bound RNA fragments were eluted from the beads by proteinase K digestion twice at 55 °C for 20 and 10 min, respectively. The eluate was further purified using RNA clean and concentrator kit (Zymo Research). RNA was used for library generation with NEBNext multiplex small RNA library prep kit (NEB). Sequencing was carried out on Illumina HiSeq 2000 according to the manufacturer’s instructions. Total RNA was isolated from wild-type and mutant fish embryos collected at different time points with TRIzol reagent and Direct-zol RNA MiniPrep kit. For each time points, ~20 embryos were collected to ensure RNA yield and that samples were representative. mRNA was further purified using RiboMinus Eukaryote Kit v2. RNA fragmentation was performed using Bioruptor Pico as described previously. Fragmented mRNA was used for library construction using TruSeq stranded mRNA library prep kit (Illumina) according to manufacturer’s protocol. Sequencing was carried out on Illumina HiSeq 2000 according to the manufacturer’s instructions. All samples were sequenced by Illumina Hiseq 2000 with single-end 50-bp read length. The deep-sequencing data were mapped to zebrafish genome version 10 (GRCz10). (1) For m6A-seq, reads were aligned to the reference genome (danRer10) using Tophat v2.0.14 (ref. 28) with parameter -g 1–library-type = fr-firststrand. RefSeq Gene structure annotations were downloaded from UCSC Table Browser. The longest isoform was used if the gene had multiple isoforms. Aligned reads were extended to 150 bp (average fragments size) and converted from genome-based coordinates to isoform-based coordinates, in order to eliminate the interference from introns in peak calling. The peak-calling method was modified from published work18. To call m6A peaks, the longest isoform of each gene was scanned using a 100 bp sliding window with 10 bp step. To reduce bias from potential inaccurate gene structure annotation and the arbitrary usage of the longest isoform, windows with read counts less than 1 out of 20 of the top window in both m6A-IP and input sample were excluded. For each gene, the read counts in each window were normalized by the median count of all windows of that gene. A Fisher exact test was used to identify the differential windows between IP and input samples. The window was called as positive if the FDR < 0.01 and log (enrichment score) ≥ 1. Overlapping positive windows were merged. The following four numbers were calculated to obtain the enrichment score of each peak (or window): (a) reads count of the IP samples in the current peak or window, (b) median read counts of the IP sample in all 100 bp windows on the current mRNA, (c) reads count of the input sample in the current peak/window, and (d) median read counts of the input sample in all 100 bp windows on the current mRNA. The enrichment score of each window was calculated as (a × d)/(b × c). (2) For m6A-CLIP-seq, after removing the adaptor sequence, the reads were mapped to the reference genome (danRer10) using Bowtie2. Peak calling method was similar to the previous study19. Briefly, mutations were considered as signal and all mapped reads were treated as background. A Gaussian Kernel density estimation was used to identify the binding regions. The motif analysis was performed using HOMER29 to search motifs in each set of m6A peaks. The longest isoform of all genes was used as background. (3) For mRNA-seq, reads were mapped with Tophat and Cufflink (v2.2.1) was used to calculate the FPKM of each gene to represent their mRNA expression level30. (4) For fish gene group categorization, we used the input mRNA-seq data from m6A-seq. FPKM of all genes were first normalized to the highest value of five time points, with only genes with FPKM >1 analysed. Then Cluster3.0 (ref. 31) was used to divide all genes into six clusters, with the parameters: adjust data – normalize genes; k-means cluster – organize genes, 6 clusters, 100 number; k-means – Euclidean distance. The result clustered file with clustered number was merged with original FPKM values, imported and processed in R, and plotted in Excel. (5) For GO analysis, the list of target genes was first uploaded into DAVID32, 33 and analysed with functional annotation clustering. The resulting file was downloaded and extracted with GO terms and corresponding P values. The new list (contains GO terms with P < 0.01) was imported into REVIGO34 and visualized with the interactive graph, which was used as the final output figures. Methylated genes (at each time point) were defined as overlapped gene targets between m6A-seq and m6A-CLIP-seq. Ythdf2-regulated genes were defined as overlapped gene targets between the lists of the top 20% upregulated genes in both ythdf2 knockout and MO-injected samples. The most stringent Ythdf2 target genes at 4 h.p.f. (135) were defined in the main text, as overlapped genes of methylated genes at 4 h.p.f. (3,237) and Ythdf2-regulated genes at 4 h.p.f. (876). All the raw data and processed files have been deposited in the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) and accessible under GSE79213. A summary of sequenced samples and processed FPKM data are included as Supplementary Data 2. One set of representative experiment results from at least two independent experiments were shown where applicable. Quantitative reverse-transcription PCR (RT–qPCR) was performed to assess the relative abundance of mRNA. All RNA templates used for RT–qPCR were pre-treated with on-column DNase I digestion in the purification step. RT–qPCR primers were designed to span exon-exon junctions to only detect mature mRNA. RT–qPCR was performed by using SuperScript III one-step RT–PCR system (Thermo Fisher) with 50–100 ng total RNA template. Actb1 was used as an internal control as it showed relative invariant expression during the studied time period according to pilot RT–qPCR data. P values were determined using two-sided Student’s t-test for two samples with equal variance. *P < 0.05; **P < 0.01; ***P < 0.001. The sequences of primers used in this study are listed below: actb1: forward 5′-CGAGCAGGAGATGGGAACC-3′, reverse 5′-CAACGGAAACGCTCATTGC-3′; buc: forward 5′-CAAGTTACTGGACCTCAGGATC-3′, reverse 5′-GGCAGTAGGTAAATTCGGTCTC-3′; zgc:162879: forward 5′-TCCTGAATGTCCGTGAATGG-3′, reverse 5′-CCCTCAGATCCACCTTGTTC-3′; mylipa: forward 5′-CCAAACCAGACAACCATCAAC-3′, reverse 5′-CACTCCACCCCATAATGCTC-3′; vps26a: forward 5′-AAATGACAGGAATAGGGCCG-3′, reverse 5′-CAGCCAGGAAAAGTCGGATAG-3′; tdrd1: forward 5′-TACTTCAACACCCGACACTG-3′, reverse 5′-TCACAAGCAGGAGAACCAAC-3′; setdb1a: forward 5′-CTTCTCAACCCAAAACACTGC-3′, reverse 5′-CTATCTGAAGAGACGGGTGAAAC-3′; mtus1a: forward 5′-TGGAGTATTACAAGGCTCAGTG-3′, reverse 5′-TTATGACCACAGCGACAGC-3′; GFP: forward 5′-TGACATTCTCACCACCGTGT-3′, reverse 5′-AGTCGTCCACACCCTTCATC-3′. High-throughput sequencing data that support the findings of this study have been deposited at GEO under the accession number GSE79213. All the other data generated or analysed during this study are included in the article and Supplementary Information.


News Article | February 15, 2017
Site: www.24-7pressrelease.com

HOUSTON, TX, February 14, 2017-- Leslie Peter Antalffy has been included in Marquis Who's Who. As in all Marquis Who's Who biographical volumes, individuals profiled are selected on the basis of current reference value. Factors such as position, noteworthy accomplishments, visibility, and prominence in a field are all taken into account during the selection process.A registered professional engineer originally from Budapest, Hungary, Mr. Antalffy began working as a mechanical engineer for T. O'Connor & Sons during his final years while studying at the University of Adelaide in Australia. He earned a Baccalaureate degree in mechanical engineering in 1970 and became a chartered professional engineer through the Institution of Engineers, Australia. Mr. Antalffy then relocated to Toronto, Canada, where he started accruing professional experience as a vessel engineer for Lummus Company, Canada and A.G. McKee & Company.In 1973, Mr. Antalffy moved to Houston, Texas to become a senior vessel engineer for the multinational engineering and construction firm, Fluor Engineers and Constructors. He has remained with the company ever since in various roles, including principal engineer, supervising mechanical engineer, mechanical engineering director, senior mechanical engineering director, and presently executive director process technology and engineering. Furthermore, Mr. Antalffy continued his education, earning an MBA from Sam Houston State University in 1980. He also became a registered professional engineer in the state of Texas. Since 1995, he has been a senior technical fellow with the company.Aside from his education and professional positions, Mr. Antalffy had remained active as a Life Fellow of the American Society of Mechanical Engineers; he has been a member of several of the organization's technical code committees as well. Additionally, Mr. Antalffy is noted for obtaining 12 U.S. patents in the field of delayed cooking. He has contributed over 110 articles to professional journals and/or has presented technical papers at conferences around the world. His accomplishments have been featured in the 25th through 27th editions of Who's Who in the South and Southwest, as well as multiple editions of Who's Who in Finance and Industry, Who's Who in Science and Engineering, Who's Who in America and Who's Who in the World.About Marquis Who's Who :Since 1899, when A. N. Marquis printed the First Edition of Who's Who in America , Marquis Who's Who has chronicled the lives of the most accomplished individuals and innovators from every significant field of endeavor, including politics, business, medicine, law, education, art, religion and entertainment. Today, Who's Who in America remains an essential biographical source for thousands of researchers, journalists, librarians and executive search firms around the world. Marquis now publishes many Who's Who titles, including Who's Who in America , Who's Who in the World , Who's Who in American Law , Who's Who in Medicine and Healthcare , Who's Who in Science and Engineering , and Who's Who in Asia . Marquis publications may be visited at the official Marquis Who's Who website at www.marquiswhoswho.com


News Article | February 22, 2017
Site: www.nature.com

All animal procedures adhered to the laws governing animal experimentation issued by the German Government. For all experiments, we used 3- to 12-week-old C57Bl/6 (n = 3), Chattm2(cre)Lowl (n = 34; ChAT:Cre, JAX 006410, The Jackson Laboratory), and Tg(Pcp2-cre)1Amc (n = 5; Pcp2, JAX 006207) mice of either sex. The transgenic lines were cross-bred with the Cre-dependent red fluorescence reporter line Gt(ROSA)26Sortm9(CAG-tdTomato)Hze (Ai9tdTomato, JAX 007905) for a subset of experiments. Owing to the explanatory nature of our study, we did not use randomization and blinding. No statistical methods were used to predetermine sample size. Animals were housed under a standard 12-h day–night rhythm. For recordings, animals were dark-adapted for ≥ 1 h, then anaesthetized with isoflurane (Baxter) and killed by cervical dislocation. The eyes were removed and hemisected in carboxygenated (95% O , 5% CO ) artificial cerebral spinal fluid (ACSF) solution containing (in mM): 125 NaCl, 2.5 KCl, 2 CaCl , 1 MgCl , 1.25 NaH PO , 26 NaHCO , 20 glucose, and 0.5 l-glutamine (pH 7.4). Then, the tissue was moved to the recording chamber of the microscope, where it was continuously perfused with carboxygenated ACSF at ~37 °C. The ACSF contained ~0.1 μM sulforhodamine-101 (SR101, Invitrogen) to reveal blood vessels and any damaged cells in the red fluorescence channel. All procedures were carried out under very dim red (>650 nm) light. A volume of 1 μl of the viral construct (AAV9.hSyn.iGluSnFR.WPRE.SV40 or AAV9.CAG.Flex.iGluSnFR.WPRE.SV40 (AAV9.iGluSnFR) or AAV9.Syn.Flex.GCaMP6f.WPRE.SV40, Penn Vector Core) was injected into the vitreous humour of 3- to 8-week-old mice anaesthetized with 10% ketamine (Bela-Pharm GmbH & Co. KG) and 2% xylazine (Rompun, Bayer Vital GmbH) in 0.9% NaCl (Fresenius). For the injections, we used a micromanipulator (World Precision Instruments) and a Hamilton injection system (syringe: 7634-01, needles: 207434, point style 3, length 51 mm, Hamilton Messtechnik GmbH). Owing to the fixed angle of the injection needle (15°), the virus was applied to the ventronasal retina. Imaging experiments were performed 3–4 weeks after injection. Sharp electrodes were pulled on a P-1000 micropipette puller (Sutter Instruments) with resistances >100 MΩ. Single cells in the inner nuclear layer were dye-filled with 10 mM Alexa Fluor 555 (Life Technologies) in a 200 mM potassium gluconate (Sigma-Aldrich) solution using the buzz function (50-ms pulse) of the MultiClamp 700B software (Molecular Devices). Pipettes were carefully retracted as soon as the cell began to fill. Approximately 20 min were allowed for the dye to diffuse throughout the cell before imaging started. After recording, an image stack was acquired to document the cell’s morphology, which was then traced semi-automatically using the Simple Neurite Tracer plugin implemented in Fiji (https://imagej.net/Simple_Neurite_Tracer). All drugs were bath applied for at least 10 min before recordings. The following drug concentrations were used (in μM): 10 gabazine (Tocris Bioscience)50, 75 TPMPA (Tocris Bioscience)50, 50 l-AP4 (l-(+)-2-amino-4-phosphonobutyric acid, Tocris Bioscience) and 0.5 strychnine (Sigma-Aldrich)51. Drug solutions were carboxygenated and warmed to ~37 °C before application. Pharmacological experiments were exclusively performed in the On and Off ChAT-immunoreactive bands, which are labelled in red fluorescence in ChAT:Cre × Ai9tdTomato crossbred animals. We used a MOM-type two-photon microscope (designed by W. Denk, MPI, Heidelberg; purchased from Sutter Instruments/Science Products). The design and procedures have been described previously52. In brief, the system was equipped with a mode-locked Ti:Sapphire laser (MaiTai-HP DeepSee, Newport Spectra-Physics), two fluorescence detection channels for iGluSnFR or GCaMP6f (HQ 510/84, AHF/Chroma) and SR101/tdTomato (HQ 630/60, AHF), and a water immersion objective (W Plan-Apochromat 20×/1.0 DIC M27, Zeiss). The laser was tuned to 927 nm for imaging iGluSnFR, GCaMP6f or SR101, and to 1,000 nm for imaging tdTomato. For image acquisition, we used custom-made software (ScanM by M. Müller and T.E.) running under IGOR Pro 6.3 for Windows (Wavemetrics), taking time-lapsed 64 × 16 pixel image scans (at 31.25 Hz) for glutamate and 32 × 32 pixel image scans (at 15.625 Hz) for calcium imaging. For visualizing morphology, 512 × 512 pixel images were acquired. For light stimulation, we focused a DLP projector (K11, Acer) through the objective, fitted with band-pass-filtered light-emitting diodes (LEDs) (green, 578 BP 10; and blue, HC 405 BP 10, AHF/Croma) to match the spectral sensitivity of mouse M- and S-opsins. LEDs were synchronized with the microscope’s scan retrace. Stimulator intensity (as photoisomerization rate, 103 P* per s per cone) was calibrated as described previously52 to range from 0.6 and 0.7 (black image) to 18.8 and 20.3 for M- and S-opsins, respectively. Owing to technical limitations, intensity modulations were weakly rectified below 20% brightness. An additional, steady illumination component of ~104 P* per s per cone was present during the recordings because of two-photon excitation of photopigments (for detailed discussion, see refs 52 and 53). The light stimulus was centred before every experiment, such that its centre corresponded to the centre of the recording field. For all experiments, the tissue was kept at a constant mean stimulator intensity level for at least 15 s after the laser scanning started and before light stimuli were presented. Because the stimulus was projected though the objective lens, the stimulus projection plane shifted when focusing at different IPL levels. We therefore quantified the resulting blur of the stimulus at the level of photoreceptor outer segments. We found that a vertical shift of the imaging plane by 50 μm blurred the image only slightly (2% change in pixel width), indicating that different IPL levels (total IPL thickness = 41.6 ± 4.8 μm, mean ± s.d., n = 20 scans) can be imaged without substantial change in stimulus quality. Four types of light stimuli were used (Fig. 1): (i) full-field (600 × 800 μm) and (ii) local (100 μm in diameter) chirp stimuli consisting of a bright step and two sinusoidal intensity modulations, one with increasing frequency (0.5–8 Hz) and one with increasing contrast; (iii) 1-Hz light flashes (500 μm in diameter, 50% duty cycle); and (iv) binary dense noise (20 × 15 matrix of 20 × 20 μm pixels; each pixel displayed an independent, balanced random sequence at 5 Hz for 5 min) for space–time receptive field mapping. In a subset of experiments, we used three additional stimuli: (v) a ring noise stimulus (10 annuli with increasing diameter, each annulus 25 μm wide), with each ring’s intensity determined independently by a balanced 68-s random sequence at 60 Hz repeated four times; (vi) a surround chirp stimulus (annulus; full-field chirp sparing the central 100 μm corresponding to the local chirp); and (vii) a spot noise stimulus (100 or 500 μm in diameter; intensity modulation like ring noise) flickering at 60 Hz. For all drug experiments, we showed in addition: (viii) a stimulus consisting of alternating 2-s full-field and local light flashes (500 and 100 μm in diameter, respectively). All stimuli were achromatic, with matched photo-isomerization rates for mouse M- and S-opsins. For each scan field, we used the relative positions of the inner (ganglion cell layer) and outer (inner nuclear layer) blood vessel plexus to estimate IPL depth. To relate these blood vessel plexi to the ChAT bands, we performed separate experiments in ChAT:Cre × Ai9tdTomato mice. High-resolution stacks throughout the inner retina were recorded in the ventronasal retina. The stacks were then first corrected for warping of the IPL using custom-written scripts in IGOR Pro. In brief, a raster of markers (7 × 7) was projected in the x–y plane of the stack and for each marker the z positions of the On ChAT band were manually determined. The point raster was used to calculate a smoothed surface, which provided a z offset correction for each pixel beam in the stack. For each corrected stack, the z profiles of tdTomato and SR101 labelling were extracted by manually drawing ROIs in regions where only blood vessel plexi or the ChAT bands were visible. The two profiles were then matched such that 0 corresponded to the inner vessel peak and 1 corresponded to the outer vessel peak. We averaged the profiles of n = 9 stacks from three mice and determined the IPL depth of the On and Off ChAT bands to be 0.48 ± 0.011 and 0.77 ± 0.014 AU (mean ± s.d.), respectively. The s.d. corresponds to an error of 0.45 and 0.63 μm for the On and Off ChAT bands, respectively. In the following, recording depths relative to blood vessel plexi were transformed into IPL depths relative to ChAT bands for all scan fields (Fig. 1b), with 0 corresponding to the On ChAT band and 1 corresponding to the Off ChAT band. Data analysis was performed using Matlab 2014b/2015a (Mathworks Inc.) and IGOR Pro. Data were organized in a custom written schema using the DataJoint for Matlab framework (github.com/datajoint/datajoint-matlab)54. Regions-of-interest (ROIs) were defined automatically by a custom correlation-based algorithm in IGOR Pro. First, the activity stack in response to the dense noise stimulus (64 × 16 × 10,000 pixels) was de-trended by high-pass filtering the trace of each individual pixel above ~0.1 Hz. For the 100 best-responding pixels in each recording field (highest s.d. over time), the trace of each pixel was correlated with the trace of every other pixel in the field. Then, the correlation coefficient (ρ) was plotted against the distance between the two pixels and the average across ROIs was computed (Extended Data Fig. 1a). A scan field-specific correlation threshold (ρ ) was determined by fitting an exponential between the smallest distance and 5 μm (Extended Data Fig. 1b). ρ was defined as the correlation coefficient at λ, where λ is the exponential decay constant (space constant; Extended Data Fig. 1b). Next, we grouped neighbouring pixels with ρ > ρ into one ROI (Extended Data Fig. 1c–e). To match ROI sizes with the sizes of BC axon terminals, we restricted ROI diameters (estimated as effective diameter of area-equivalent circle) to range between 0.75 and 4 μm (Extended Data Fig. 1b, g). For validation, the number of ROIs covering single axon terminals was quantified manually for n = 31 terminals from n = 5 GCaMP6-expressing BCs (Extended Data Figs 1g, 2a–c). The glutamate (or calcium) traces for each ROI were extracted (as ΔF/F) using the image analysis toolbox SARFIA for IGOR Pro55 and resampled at 500 Hz. A stimulus time marker embedded in the recorded data served to align the traces relative to the visual stimulus with 2 ms precision. For this, the timing for each ROI was corrected for sub-frame time-offsets related to the scanning. Stimulus-aligned traces for each ROI were imported into Matlab for further analysis. For the chirp and step stimuli, we down-sampled to 64 Hz for further processing, subtracted the baseline (median of first 20–64 samples), computed the median activity r(t) across stimulus repetitions (5 repetitions for chirp, >30 repetitions for step) and normalized it such that . For dye-injected BCs, axon terminals were labelled manually using the image analysis toolbox SARFIA for IGOR Pro. Then, ROIs were estimated as described above and assigned to the reconstructed cell, if at least two pixels overlapped with the cell´s axon terminals. We mapped the receptive field from the dense noise stimulus and the response kernel to the ring noise stimulus by computing the glutamate/calcium transient-triggered average. To this end, we used Matlab’s findpeaks function to detect the times t at which transients occurred. We set the minimum peak height to 1 s.d., where the s.d. was robustly estimated using: We then computed the glutamate/calcium transient-triggered average stimulus, weighting each sample by the steepness of the transient: Here, is the stimulus, τ is the time lag and M is the number of glutamate/calcium events. For the receptive field from the dense noise stimulus, we smoothed this raw receptive field estimate using a 3 × 3-pixel Gaussian window for each time lag separately and used singular value decomposition (SVD) to extract temporal and spatial receptive field kernels. To extract the receptive field’s position and scale, we fitted it with a 2D Gaussian function using Matlab’s lsqcurvefit. Receptive field quality (Qi ) was measured as one minus the fraction of residual variance not explained by the Gaussian fit , Response quality index. To measure how well a cell responded to a stimulus (local and full-field chirp, flashes), we computed the signal-to-noise ratio where C is the T by R response matrix (time samples by stimulus repetitions), while and denote the mean and variance across the indicated dimension, respectively2. For further analysis, we used only cells that responded well to the local chirp stimulus (Qi  > 0.3) and resulted in good receptive fields (Qi  > 0.2). Polarity index. To distinguish between On and Off BCs, we calculated the polarity index (POi) from the step response to local and full-field chirp, respectively, as where b = 2 s (62 samples). For cells responding solely during the On-phase of a step of light POi = 1, while for cells only responding during the step’s Off-phase POi = −1. Opposite polarity index. The number of opposite polarity events (OPi) was estimated from individual trials of local and full-field chirp step responses (first 6 s) using IGOR Pro’s FindPeak function. Specifically, we counted the number of events that occurred during the first 2 s after the step onset and offset for Off and On BCs, respectively. For each trial the total number of events was divided by the number of stimulus trials. If OPi = 1, there was on average one opposite polarity event per trial. High frequency index. The high frequency index (HFi) was used to quantify spiking (compare with ref. 28) and was calculated from responses to individual trials of the local and full-field chirps. For the first 6 s of each trial, the frequency spectrum was calculated by fast Fourier transform (FFT) and spectra were averaged across trials for individual ROIs. Then, HFi = log(F /F ), where F and F are the mean power between 0.5–1 Hz and 2–16 Hz, respectively. Response transience index. The step response (first 6 s) of local and full-field chirps was used to calculate the response transience (RTi). Traces were up-sampled to 500 Hz and the response transience was calculated as where α = 400 ms is the read-out time following the peak response t . For a transient cell with complete decay back to baseline RTi = 1, whereas for a sustained cell with no decay RTi = 0. Response plateau index. Local and full-field chirp responses were up-sampled to 500 Hz and the plateau index (RPi) was determined as: with the read-out time α = 2 s. A cell showing a sustained plateau has an RPi = 1, while for a transient cell RPi = 0. Tonic release index. Local chirp frequency and contrast responses were up-sampled to 500 Hz and the baseline (response to 50% contrast step) was subtracted. Then, the glutamate traces were separated into responses above (r ) and below (r ) baseline and the tonic release index (TRi) was determined as: For a cell with no tonic release TRi = 0, whereas for a cell with maximal tonic release TRi = 1. Response delay. The response delay (t ) was defined as the time from stimulus onset/offset until response onset and was calculated from the up-sampled local chirp step response. Response onset (t ) and delay (t ) were defined as and , respectively. We used sparse principal component analysis, as implemented in the SpaSM toolbox by K. Sjöstrang et al. (http://www2.imm.dtu.dk/projects/spasm/), to extract sparse response features from the mean responses across trials to the full-field (12 features) and local chirp (6 features), and the step stimulus (6 features) (as described in ref. 2; see Extended Data Fig. 4b). Before clustering, we standardized each feature separately across the population of cells. BC-terminal volume profiles were obtained from electron microscopic reconstructions of the inner retina6, 10. To isolate synaptic terminals, we removed those parts of the volume profiles that probably corresponded to axons. We estimated the median axon density for each type from the upper 0.06 units of the IPL and subtracted twice that estimate from the profiles, clipping at zero. Profiles were smoothed with a Gaussian kernel (s.d. = 0.14 units IPL depth) to account for jitter in depth measurements of two-photon data. For the GluMI cell, we assumed the average profile of CBC types 1 and 2. We used a modified mixture of Gaussian model56 to incorporate the prior knowledge from the anatomical BC profiles. For each ROI i with IPL depth , we define a prior over anatomical types c as Where IPL(d,c) is the IPL terminal density profile as a function of depth and anatomical cell type. For example, all ROIs of a scan field taken at an IPL depth of 1.7 were likely to be sorted into clusters for CBC types 1 and 2, while a scan field taken at a depth of 0 received a bias for CBC types 5–7 (Extended Data Fig. 4a). The parameters of the mixture of Gaussian model are estimated as usual, with the exception of estimating the posterior over clusters. Here, the mixing coefficients are replaced by the prior over anatomical types, resulting in a modified update formula for the posterior: All other updates remain the same as for the standard mixture of Gaussians algorithm57. We constrained the covariance matrix for each component to be diagonal, resulting in 48 parameters per component (24 for the mean, 24 for the variances). We further regularized the covariance matrix by adding a constant (10−5) to the diagonal. The clustering was based on a subset (~83%) of the data (the first 11,101 recorded cells). The remaining ROIs were then automatically allocated to the established clustering (n = 2,210 ROIs). For each pair of clusters, we computed the direction in feature space that optimally separated the clusters , where are the cluster means in feature space and is the pooled covariance matrix. We projected all data on this axis and standardized the projected data according to cluster 1 (that is, subtracted the projected mean of cluster 1 and divided by its s.d.). We computed d′ as a measure of the separation between the clusters: , where are the means of the two clusters in the projected, normalized space. We also performed a more constrained clustering in which we divided the IPL into five portions without overlap based on stratification profiles. We then clustered each zone independently using a standard mixture of Gaussian approach and a cluster number determined by the number of BC types expected in each portion. The correlation between the cluster means of our clustering and the more constrained clustering was 0.97 for the full-field chirp traces, indicating high agreement. Field entropy. Field entropy (S ) was used as a measure of cluster heterogeneity within single recording fields and was defined as  , where i is the number of clusters in one recording field and p corresponds to the number of ROIs assigned to the ith cluster. S  = 0 if all ROIs of one recording field are assigned to one cluster and S increases if ROIs are equally distributed across multiple clusters. In general, high field-entropy indicates high cluster heterogeneity within a single field. Analysis of response diversity. To investigate the similarity of local and full-field chirp responses across clusters (Fig. 3), we determined the linear correlation coefficient between any two cluster pairs. The analysis was performed on cluster means. For every cluster, correlation coefficients were averaged across clusters with the same and opposite response polarity, respectively. We used principal component analysis (using Matlab’s pca function) to obtain a 2D embedding of the mean cluster responses. The principal component analysis was computed on all 14 local and 14 full-field cluster means. If not stated otherwise, the non-parametric Wilcoxon signed-rank test was used for statistical testing. Pharmacology. To analyse drug-induced effects on BC clusters (Fig. 4, Extended Data Figs 7, 8), response traces and receptive fields of ROIs in one recording field belonging to the same cluster were averaged if there were at least 5 ROIs assigned to this cluster. Spatial receptive fields were aligned relative to the pixel with the highest s.d. before averaging. Centre-surround properties. To estimate the signal-to-noise ratio of ring maps of single ROIs, we extracted temporal centre and surround kernels and normalized the respective kernel to the s.d. of its baseline (first 50 samples). For further analysis, we included only ROIs with |Peak | > 12 s.d. and |Peak | > 7 s.d. Ring maps of individual ROIs were then aligned relative to its peak centre activation and averaged across ROIs assigned to one cluster. To isolate the BC surround, the centre rings (first two rings) were cut and the surround time and space components were extracted by singular value decomposition (SVD). The surround space component was then extrapolated across the centre by fitting a Gaussian and an extrapolated surround map was generated. To isolate the BC centre, the estimated surround map was subtracted from the average map and centre time and space components were extracted by SVD. The estimated centre and surround maps were summed to obtain a complete description of the centre–surround structure of BC receptive fields. Across clusters, the estimated centre–surround maps captured 92.5 ± 1.9% of the variance of the original map. Owing to the low signal-to-noise ratio, the temporal centre–surround properties of individual ROIs were extracted as described above using the centre and surround space kernels obtained from the respective cluster average. The 1D Gaussian fits of centre and surround space activation were used to calculate centre and surround ratios (CSRs) for various stimulus sizes. Specifically, the CSR was defined as where S corresponds to the stimulus radius and ranged from 10 to 500 μm, with a step size dx of 1 μm. Time kernels for different stimulus sizes were generated by linearly mixing centre and surround time kernels, weighted by the respective CSR. BC spectra. The temporal spectra of BC clusters were calculated by Fourier transform of the time kernels estimated for a local (100 μm in diameter) and full-field (500 μm in diameter) light stimulus (see centre–surround properties). Owing to the lower SNR of time kernels estimated for the full-field stimulus, kernels were cut 100 ms before and at the time point of response, still capturing 86.7 ± 14.7% of the variance of the original kernel. The centre of mass (Centroid) was used to characterize spectra of different stimulus sizes and was determined as where x(n) corresponds to the magnitude and f(n) represents the centre frequency of the nth bin. Surround chirp and spot noise data. To investigate the effects of surround-only activation and stimulus size on temporal encoding properties across BC clusters, response traces and estimated kernels of ROIs in one recording field belonging to the same cluster were averaged if there were at least five ROIs assigned to this cluster. The spectra for kernels estimated from local and full-field spot noise stimuli were calculated as described above. Time kernel correlation. To analyse the similarity of temporal kernels estimated for a specific stimulus size (Fig. 5i, j), we computed the linear correlation coefficient of each kernel pair from clusters with the same response polarity. We then calculated the average correlation coefficient for every cluster (Fig. 5i) and across all cluster averages (Fig. 5j). Data (original data and clustering results) as well as Matlab code are available from http://www.retinal-functomics.org.


Adult male C57BL/6J mice (Jackson Laboratories) or Ai9 reporter mice (Cg-Gt(ROSA)26Sortm9(CAG-tdTomato)HzeIJ; Jackson Laboratories) were group housed (25–35 g; 6–8 weeks old) with littermates until surgery. For all experiments, mice underwent surgery during which they were anaesthetized with 0.8–1.5% isoflurane vaporized in pure oxygen (1 l min−1) and placed within a stereotactic frame (David Kopf Instruments). Ophthalmic ointment (Akorn) and a topical anaesthetic (2% lidocaine; Akorn) were applied during surgeries, and subcutaneous injections of sterile saline (0.9% NaCl in water) were administered to prevent dehydration. During surgeries, virus injections were administered unilaterally (for two-photon microscopy experiments) or bilaterally (for optogenetics or anatomical experiments) targeting dorsal medial PFC (specifically prelimbic cortex; 500 nl per side; relative to bregma: AP, +1.85 mm; ML, ±0.60 mm; DV, −2.50 mm), bilaterally targeting NAc (500 nl per side; relative to bregma: AP, +1.42 mm; ML ±0.73 mm; DV, −4.80 mm), and/or on the midline targeting PVT (300 nl; relative to bregma: AP, −1.46 mm; ML, −1.13 mm; DV, −3.30 mm; 20° angle). The UNC Vector Core packaged all viruses except canine adenovirus 2 encoding Cre (Cav2-Cre; Institut de Génétique Moléculaire de Montpellier). For two-photon imaging experiments, an optical cannula (Inscopix) was implanted above the PFC injection site (relative to bregma: AP, +1.85 mm; ML, −0.8 mm; DV, −2.2 mm; see ref. 29 for details of using similar surgical protocols for imaging experiments). For optogenetic experiments, custom-made optical fibres30 were implanted bilaterally approximately 0.5 mm above the PFC injection sites (relative to bregma: AP, +1.85 mm; ML, ±0.83 mm; DV, −1.93 mm; 10° angle). For experiments involving head-fixed behaviour, a custom-made ring (stainless steel; 5 mm ID, 11 mm OD) was attached to the skull during surgery to allow head fixation (see Fig. 1a). Following surgeries, mice received acetaminophen in their drinking water for two days, and were allowed to recover with access to food and water ad libitum for at least 21 days. After recovery, mice were water restricted (water bottles taken out of the cage), and 0.6 ml of water was delivered every day to a dish placed within each home cage. Behavioural experiments began when mice weighed less than 90% of free drinking weight (around 10 days for all experiments). To ensure good health and weight maintenance, mice were weighed and handled daily. This protocol resulted in weight stabilization between 85–90% of free-drinking weight during each experiment. No mouse was given more or less than 0.6 ml of water for weight concerns during water restriction procedures, nor did any health problems related to dehydration arise at any point from these protocols. All experimental procedures were performed in accordance with the Guide for the Care and Use of Laboratory Animals (National Institutes of Health), and were approved by the Institutional Animal Care and Use Committee at the University of North Carolina prior to experiments commencing. Following recovery from surgery, mice were habituated to head fixation for 3 days, during which unpredictable drops of sucrose (10% sucrose in water; 2.0–2.5 μl) were delivered intermittently for one hour (approximately 60 drops per hour) through a gravity-driven, solenoid-controlled lick tube. Once the mice displayed sufficient licking (>1,000 licks per session), they underwent Pavlovian conditioning. During each conditioning session, two cues (3 kHz pulsing or 12 kHz constant tones, 2 s, 70 dB) were randomly presented 50 times before the delivery of sucrose (CS+, 10% sucrose in water; 2.0–2.5 μl) or no sucrose (CS−), such that there was a one second trace interval between delivery of the CS+ and sucrose (see Fig. 1b). The cue contingencies were counterbalanced across cohorts of mice to ensure that mice acquired conditioned licking in response to either tone when paired with sucrose. The inter-trial interval between the previous reward delivery (CS+) or withholding time (CS−) and the next cue was chosen as a random sample from a uniform distribution bounded by 40 s and 80 s. Cue discrimination was quantified using the area under a receiver operating characteristic (auROC) formed by the number of baseline-subtracted licks during the CS+ versus CS− trace intervals. For both two-photon and optogenetic behavioural experiments, we classified sessions as ‘early’ or ‘late’ in learning, defined by both behavioural performance (early, auROC < 0.65; late, auROC > 0.66) and session number (early, sessions 1–5; late, sessions 7 or later). These criteria were used as post hoc analysis revealed that an auROC > 0.66 approximates high performance in a phase space formed by behavioural performance across sessions. Finally, behavioural data are displayed and analysed throughout the manuscript as the change in lick rate between each 3-s cue period and 1-s baseline period (baseline period is immediately before each cue). In addition, we show raw lick rates during both the cue and baseline periods for all imaging experiments (see Extended Data Fig. 1). Baseline lick rates remained relatively low across all experiments, and therefore for optogenetic studies only the change in lick rate is shown and analysed (see Figs 4, 5 and Extended Data Figs 8 and 9). Experimental design. Two-photon microscopy was used to visualize activity dynamics of PFC neurons in vivo. A virus encoding the calcium indicator GCaMP6s18 (AAVdj-CaMK2a-GCaMP6s; 5.3 × 1012 infectious units per ml) was injected into PFC (see Subjects and surgery). For imaging projection-specific neurons, a virus encoding the Cre-dependent calcium indicator GCaMP6s (AAVdj-ef1α-DIO-GCaMP6s; 3.1 × 1012 infectious units per ml; from Karl Deisseroth) was injected into PFC, and the retrogradely transported canine adenovirus encoding Cre-recombinase31, 32 was injected into either NAc or PVT (Cav2-Cre; 4.2 × 1012 infectious units per ml). After a minimum of 8 weeks to allow virus transport and infection, mice underwent Pavlovian conditioning, during which GCaMP6s-expressing neurons were visualized using two-photon microscopy. Data acquisition, signal extraction, and analysis. A two-photon microscope (FVMPE-RS) was equipped with the following to allow imaging of PFC in vivo: a hybrid scanning core set with galvanometers and fast resonant scanners (allows up to 30 Hz frame-rate acquisition; set to 2.5 Hz), multi-alkali PMT and GaAsP-PMT photo detectors with adjustable voltage, gain, and offset features, a single green/red NDD filter cube, a long working distance 20× air objective designed for optical transmission at infrared wavelengths (Olympus, LCPLN20XIR, 0.45 NA, 8.3 mm WD), a software-controlled modular xy stage loaded on a manual z-deck, and a tunable Mai-Tai Deep See laser system (Spectra Physics, laser set to 955 nm, ~100 fs pulse width) with automated four-axis alignment. Before each conditioning session, a particular field of view (FOV) was selected by adjusting the imaging plane (z-axis), and each FOV was spaced at least 50 μm from one another to prevent visualization of the same cells across multiple FOVs. During each conditioning session, two-photon scanning was triggered for each trial 7 s before cue delivery, and a 20 s video was then collected for each trial. Data were both acquired and processed using a computer equipped with FluoView (Olympus, FV1200) and cellSens (Olympus) software packages. Following data acquisition, videos were motion corrected using a planar hidden Markov model (SIMA v1.3)33 and regions of interest (ROIs) were hand drawn around each cell using the standard deviation projection of the motion-corrected video using ImageJ. Next, calcium transient time series data were extracted with SIMA and analysed using custom Python data analysis pipelines written in the laboratory (by V.M.K.N.). For analysis, data were split into two groups (early and late) that were defined based on behavioural performance and the day of conditioning (see Head-fixed behaviour). Next, each recorded neuron was defined as having an excitatory response, inhibitory response, or no response. Significant responses represent significant two-tailed auROC comparing average fluorescence (Δf/f) of the trace interval (1 s after CS offset) versus baseline (1 s before CS onset) where P < 0.05 after Benjamini–Hochberg false discovery rate correction. Each P value for auROC was defined by calculating the P values for the corresponding Mann–Whitney U statistic. χ2 tests were then used to compare the number of CS+ responders to CS− responders for each group. For additional decoding analysis (for example, Fig. 2f, l), we tested whether the identity of the cue on any given trial could be decoded from the mean trace interval response on that trial using support vector machines. To this end, we used the Python module, scikitlearn, with GridSearchCV and a support vector classification (SVC) estimator with a radial basis function kernel, optimizing across the following parameters: γ: {10−2, 10−1, 100, 101, 102}, C: {10−2, 10−1, 100, 101, 102}. Quantification of performance was done using tenfold validation34. For each neuron, the highest accuracy score across these parameters was used as the metric of accuracy. In order to determine whether the population of accuracy scores across all neurons was significantly different from that expected by chance, we performed a single shuffle per neuron by randomizing the cue identity on every trial. The population of shuffled accuracy scores across one shuffle was then compared to the population of unshuffled accuracy scores using a two-tailed Welch’s t-test. Note that since the metric of accuracy was optimized across parameters, the mean accuracy score expected by chance is not 0.5, but is instead closer to 0.55 (Fig. 2f, l and Extended Data Fig. 4d). We also further tested whether the mean activity during the trace interval on a given trial for one neuron could be used to decode the number of licks in the trace interval. This was performed using support vector regression (SVR) in scikitlearn with GridSearchCV with a radial basis function kernel, optimizing across the following parameters: C: 5 logarithmically equidistant points between 10−3 and 103 {10−3, 3.16 × 10−2, 100, 3.16 × 102, 103}, ε: 5 logarithmically equidistant points between 10−3 and 103 {10−3, 3.16 × 10−2, 100, 3.16 × 102, 103}, γ: 10 logarithmically equidistant points between 10−6 and 106 {10−6, 2.15 × 10−5, 4.64 × 10−4, 10−2, 2.15 × 10−1, 4.64, 102, 2.15 × 103, 4.64 × 104, 106}. Quantification of performance was done using tenfold validation of the R2 metric (note that this metric can be infinitely negative, indicating arbitrarily poor performance, but is bounded on the positive end at 1, indicating perfect decoding). We found that as a population, the number of anticipatory licks during the trace interval could not be decoded in the late sessions in CaMK2a-expressing neurons (mean R2 = −1.21), PFC–NAc neurons (mean R2 = −0.92) or PFC–PVT neurons (mean R2 = −0.39). These negative numbers reflect the absence of a relationship between licking and calcium activity in each cell population. Behavioural optogenetics were performed as described in detail previously30. In brief, during surgery a virus encoding Cre-inducible channelrhodopsin-2 (AAV5-ef1α-DIO-hChR2(H134R)-eYFP; 5.0 × 1012 infectious units per ml), halorhodopsin (AAV5-ef1α-eNpHR3.0-eYFP; 8.0 × 1012 infectious units per ml), or control (AAV5-ef1α-eYFP; 6.0 × 1012 infectious units per ml) was injected into PFC; and Cav2-Cre (refs 31, 32) (4.2 × 1012 infectious units per ml) was injected into either NAc or PVT. After a minimum of 8 weeks to allow sufficient virus transport and infection, mice underwent Pavlovian conditioning. For acquisition experiments (for example, Fig. 4), mice underwent eight daily conditioning sessions with laser followed by a test session (no laser). For photoactivation manipulations in ChR2 or control mice, the laser (473 nm; 8–10 mW) was turned on for 5-ms pulses (20 Hz) during 80% of the cue trials, starting at the cue onset and ending at the reward delivery. For photoinhibition manipulations in eNpHR3.0 or control mice, the laser (532 nm; 8–10 mW) did not pulse. Because the laser had no effect in the control mice, these data were collapsed across PFC–NAc and PFC–PVT groups. For expression experiments (for example, Fig. 5), after mice reached high performance criterion (late, auROC > 0.66), they underwent six daily conditioning sessions. Furthermore, every other session was selected for optogenetic manipulations, during which the laser was presented for 3 s during either the cue and trace interval or at random time epochs outside of cue or reward delivery. Because there was no effect of laser in the ChR2 or eNpHR3.0 control mice, these data were collapsed for PFC–NAc groups and PFC–PVT groups. In addition, for expression experiments subsets of control mice were used twice, once as ChR2 controls (blue light), and again as eNpHR3.0 controls (green light). Following experiments, histological verification of fluorescence and optical fibre placements were performed as described previously35. Behavioural data (change in lick rate, see above) was analysed based on a priori comparisons of interest (effect of laser on ChR2/eNpHR3.0 animals versus effect of laser in eYFP animals). For acquisition experiments (Fig. 4; Extended Data Fig. 8a–f), we analysed data from the no-laser test day only, and specifically compared the change in lick rate between the ChR2 or eNpHR3.0 groups versus the eYFP group. To correct for the double comparison (ChR2 or eNpHR3.0 versus eYFP), we performed a Benjamini–Hochberg multiple comparisons correction. For expression experiments (Fig. 5; Extended Data Figs 8 g–l and 9), in each pair of sessions (no laser, laser) we calculated the difference in mean lick rate between the two in order to obtain a statistical measure of the ‘effect of laser’ per session pair. Next, we compared the effects of laser from the ChR2 or eNpHR3.0 groups versus the corresponding effect of laser in the eYFP group. To correct for the double comparison (ChR2 or eNpHR3.0 versus eYFP), we again performed a Benjamini–Hochberg multiple comparisons correction. Considering this, for optogenetic experiments all P values (which are two-tailed throughout the manuscript) have been corrected for multiple comparisons. The anatomy and electrophysiological properties of PFC–NAc and PFC–PVT neurons were evaluated through retrograde tracing36. Specifically, during surgeries the retrograde tracer cholera toxin subunit B conjugated to Alexa Fluor (CtB-488, CtB-594; Molecular Probes) was injected bilaterally into NAc (500 nl per side) and on the midline in PVT (300 nl; colour counterbalanced across mice). Ten days following surgery, animals were killed for histology (n = 3 mice) or slice electrophysiology (n = 3 mice). For anatomical experiments, a student blind to all experiments (E.P.M.) and conditions counted the number of CtB-488 positive, CtB-594 positive, and double-positive neurons in prelimbic medial prefrontal cortex (a subregion of dorsal medial PFC). The distance of each cell from the midline and the layer specificity of each cell were then measured using ImageJ. For electrophysiological experiments, mice were euthanized ten days following surgery for patch-clamp recordings ex vivo (see below for details). The monosynaptic afferents to PFC–NAc and PFC–PVT neurons were identified using a glycoprotein-deleted rabies strategy37 in combination with Cav2-Cre targeting of projection-specific neuron populations. Specifically, during the first surgery a cocktail containing the Cre-dependent starter viruses encoding the G-protein and TVA were injected into PFC (3:1 of AAV5-FLEX-RG and AAV5-FLEX-TVA-mCherry; 300 nl per side), and Cav2-Cre was injected into either NAc (500 nl per side) or PVT (300 nl). Five weeks later, mice were given a second surgery in which the G-deleted rabies virus was injected into PFC (1:5 diluted EnvA-rabies-GFP). Finally, 8 days after the rabies injection each mouse (n = 3 per group) was euthanized for histology and cell quantification. Our rabies protocol led to sparse labelling of PFC-projection neurons, allowing quantification of individual cells in each brain section (40 μm thick). Each ROI was selected based on previous PFC tracing experiments38, as well as the fluorescence intensity observed in our experiments. Next, out of all tissue collected for each ROI in each mouse, we selected the three sections containing the most cells per region, and used confocal microscopy to get cellular-resolution images of all cells in each of those sections. For each section, we quantified all individual input neurons (GFP+) and starter cells (both GFP+ and mCherry+). Considering that the anterior cingulate cortex (ACC) was close to the PFC injection site, some sections containing ACC also had starter cell labelling. Thus, because we were interested in long-range inputs from ACC only, only sections that did not have mCherry labelling were used for ACC input quantification. Finally, rabies-tracing data were analysed by comparing the number of cells in each section across groups (raw neuron count), and by comparing the percentage of input neurons per starter cell for each particular mouse. Mice were anaesthetized with pentobarbital (50 mg kg−1) before transcardial perfusion with ice-cold sucrose cutting solution containing the following (in mM): 225 sucrose, 119 NaCl, 1.0 NaH PO , 4.9 MgCl , 0.1 CaCl , 26.2 NaHCO , 1.25 glucose, 305 mOsm. Brains were then rapidly removed, and coronal sections 300 μm thick were made using a vibratome (Leica, VT 1200). Sections were then incubated in aCSF (32 °C) containing the following (in mM): 119 NaCl, 2.5 KCl, 1.0 NaH PO , 1.3 MgCl, 2.5 CaCl , 26.2 NaHCO , 15 glucose, approximately 306 mOsm. After an hour of recovery, slices were constantly perfused with aCSF (32 °C) and visualized using differential interference contrast through a 40× water-immersion objective mounted on an upright microscope (Olympus BX51WI). Whole-cell recordings were obtained using borosilicate pipettes (3–5 MΩ) back-filled with internal solution containing the following (in mM): 130 K gluconate, 10 KCl, 10 HEPES, 10 EGTA, 2 MgCl , 2 ATP, 0.2 GTP (pH 7.35, 270–285 mOsm). Current-clamp recordings were obtained from GCaMP6s-expressing neurons to identify how action potential frequency correlated with GCaMP6s fluorescence. Specifically, to determine how elevations in action potential frequency influence GCaMP6s fluorescence, a 1 s train of depolarizing pulses (2 nA, 2 ms) was applied at a frequency of 1, 2, 5, 10 or 20 Hz. To determine how attenuations in action potential frequency influence GCaMP6s fluorescence, a 3 s pause was applied after a 10 s baseline train of depolarizing pulses (2 nA, 2 ms; 1, 2, 5, 10 or 20 Hz). Finally, to determine if hyperpolarization influences GCaMP6s fluorescence in the absence of action potential frequency modulation, a 3 s hyperpolarizing step (150 pA) was applied in neurons that were held either below or above resting membrane potential. During electrophysiological recordings, GCaMP6s fluorescence dynamics were visualized using a mercury lamp (Olympus, U-RFL-T) and microscope-mounted camera (QImaging, optiMOS). Imaging data were acquired using Micro-Manager, and extracted through hand-drawn ROIs for each recorded neuron using ImageJ. Current-clamp recordings were also obtained to identify the intrinsic properties of PFC–NAc and PFC–PVT neurons in retrograde tracing experiments, as previously described39. First, action potential firing was examined by applying a series of long depolarizing sweeps (800 ms) at +25 pA steps (0–450 pA). Next, rheobase (the minimum amount of current required for an action potential to fire) was measured by applying a series of short depolarizing sweeps (50 ms) at +10 pA steps (starting at 0 pA) until the recorded neuron fired an action potential. For all patch-clamp experiments, data acquisition occurred at 1 kHz sampling rate through a MultiClamp 700B amplifier connected to a Digidata 1440A digitizer (Molecular Devices). Data were analysed using Clampfit 10.3 (Molecular Devices). The nature of all imaging and behavioural experiments yields high-power datasets, as we can test responses to reward-predictive cues hundreds of times within a single session. Thus, although the experiments themselves require rigorous experimentation, the number of mice that are required for each experiment is generally 3–6 per group, depending on the effect size (which was not predetermined for these experiments). Mice were randomly picked for each group in each experiment, by alternating the surgery for each mouse in a cage. During data collection, investigators were only blind to the conditions for rabies tracing cell counting and CtB cell counting. The only mice excluded from final analysis were those that died before or during the experiments (n = 3). For optogenetic experiments, mice were excluded if histology confirmed ectopic virus expression outside of PFC (n = 1), or if optical-fibre placements were not in dorsomedial PFC (n = 0). For data analysis, equal variance was not assumed for behavioural optogenetics or imaging datasets. Equal variance was assumed for cell counting experiments and electrophysiological experiments. We used Python (codes written by V.M.K.N.) to analyse imaging and optogenetic datasets included in this manuscript (see Figs 1, 2, 3, 4, 5). That data, as well as the codes used for analysis, are openly available online (https://github.com/stuberlab). All other data are available upon request from the corresponding author.


News Article | February 22, 2017
Site: www.nature.com

The study was approved by the ethics committee of the medical faculty and the university clinics of the University of Tübingen and strictly adhered to Good Clinical Practice and the principles of the Declaration of Helsinki. The study is registered at ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT02115516) and in the EudraCT database, number 2013-003900-38. The study was carried out under FDA IND 15862 and with approval of the Paul-Ehrlich-Institute. Volunteers were healthy, 18–45 years old, malaria-naive adults. The full list of inclusion and exclusion criteria is given in the clinical trial protocol (Supplementary Information). All volunteers, except those in the second part who received the every 5-day regimen, received 10 mg kg−1 or 620 mg chloroquine base (Resochin, Bayer) loading dose 2 days before the first dose of PfSPZ Challenge, whichever dose was less, followed by weekly doses of 5 mg kg−1 or 310 mg through 5 days after the last dose of PfSPZ Challenge. Volunteers who were immunized on days 0, 5, and 10 received chloroquine on days 0 (loading dose), 5, 10, and 15. Randomization was performed on the day of first immunization by an independent party through provision of sealed envelopes to the syringe preparation team members, who diluted PfSPZ Challenge12, 13, 34 or loaded placebo (normal saline) into syringes at an allocation ratio of 9:5, PfSPZ:placebo. Only the syringe preparation team was aware of allocation to the intervention and had no other role in the trial. The rest of the team remained blinded until completion of CHMI of group III. PfSPZ Challenge dose escalation for groups I, II, and III was staggered by at least four weeks and in each group three sentinel volunteers (PfSPZ:placebo, 2:1) received injections one to seven days before the main group. For group I, II, and III the three immunizations were given at 28-day intervals and CHMI by DVI of 3.2 × 103 PfSPZ was done 8–10 weeks following the last immunization. In the second part the three immunizations were administered at 14-day and 5-day intervals and CHMI was done at 10 weeks post immunization. Chloroquine concentrations were measured by mass spectrometry in the blood of selected volunteers on the day before CHMI to exclude carry-over from the immunization period. Following CHMI volunteers were regularly visited for 20 weeks. The primary efficacy endpoint was the proportion of volunteers with thick blood smears positive for Pf within 21 days of CHMI, primary safety endpoint was occurrence of related grade 3 or serious adverse events from first chloroquine dose until the end of the follow-up. We performed a randomized, placebo-controlled, double-blind trial in healthy, malaria-naive, 18–45 year olds (TÜCHMI-002; ClinicalTrials.gov ID: NCT02115516). Between 1 May and 4 July 2014, 42 volunteers were randomized to receive either three doses of normal saline (placebo) or 3.2 × 103 PfSPZ (PfSPZ Challenge12, 13, 34) (group I), 1.28 × 104 PfSPZ (group II), or 5.12 × 104 PfSPZ (group III) by DVI12, 13 at four-week intervals (Extended Data Fig. 2). All volunteers received oral chemoprophylaxis with chloroquine starting with a loading dose (10 mg kg−1 chloroquine base or 620 mg, whichever dose was less) two days before first PfSPZ inoculation followed by weekly maintenance doses (5 mg kg−1) through five days after last PfSPZ inoculation; total of 10 doses. Chloroquine is not active against SPZ or liver-stage parasites35 and Pf asexual blood-stage parasites leave the liver between days 5 and 6 following inoculation36; hence dosing five days following inoculation ensured high drug levels upon liver egress. Dose-escalation was staggered in four-week intervals and at each dose escalation the ratio of placebo-immunized to PfSPZ-CVac-immunized subjects was 5:9. Following PfSPZ dose escalation, accelerated regimens (14- and 5-day intervals) were assessed using essentially the same procedures. A full report will be published separately. Eight to ten weeks after last vaccine or placebo dose (51–67 days after last chloroquine dose), protective efficacy was assessed by CHMI using DVI with PfSPZ Challenge12, 13. Daily thick blood smears were performed as previously described37 from day 6 to 21, following each DVI for immunization and CHMI, during antimalarial treatment and at each late follow-up visit. Slides were considered positive when at least two readers detected two unambiguous parasites, each. A negative slide was defined as no observed parasites in the volume of blood required to detect with 95% probability less than 10 parasites per μl (~0.5 μl). In case of discordance, a third reading was performed. In addition, 1.2 ml blood was sampled in EDTA tubes (Sarstedt) for nucleic acid extraction at the same time-points. DNA extraction control 610 (Bioline) was added and total nucleic acid (DNA and RNA) was isolated from 0.5 ml blood using the QIAamp DNA blood mini kit (Qiagen) according to the manufacturer’s specifications but without addition of RNase. Parasitaemia was calculated from a standard curve generated from serially diluted (2–20,000 parasites per ml) Pf 3D7 ring-stage synchronized cultured parasites, counted by microscopy and cytometry. All purified nucleic acid samples were stored at –20 °C until time of use. Reverse transcription quantitative polymerase chain reaction (RT–qPCR) was performed using TaqMan RNA-to-CT 1-Step Kit using published primers and probes38, with a different fluorophore and addition of a minor groove binder (probe: VIC-ATGGCCGTTTTTAGTTCGTG-NFQMGB; primers: 5′-GCTCTTTCTTGATTTCTTGGATG-3′ and 5′-AGCAGGTTAAGATCTCGTTCG-3′). Reactions were done in 384 wells at 48 °C for 20 min (reverse transcription), 96 °C for 10 min (enzyme activation), and 45 cycles of 95 °C for 15 s, 62 °C 1 min. Samples were run as triplicates with no-template control, no-RT control and positive controls in the same plate. Amplification controls were assessed manually and cycle values (C ) were calculated with the second derivative maximum method (LightCycler 480 software; version 1.5.1.62). The assay was validated in accordance to MIQE guidelines38, 39 and had a lower limit of quantification of 3 parasites per ml. qPCR results were not reported to the clinical and microscopy teams during the study period to maintain blinding of the study. Sample size was calculated with the intention to show, with a power of 80% and a two-tailed alpha of 5%, a difference in proportion of infected volunteers of 25% or less of immunized volunteers and 99% in controls, allocated in a 2:1 ratio (8 PfSPZ:4 controls), allowing for one dropout in each group (9:5). Clinical data were captured on paper case report forms and transferred to an electronic database (OpenClinica; version 3.2) by double data entry. Efficacy data were reported as proportions (primary) and time to parasitaemia. Safety and tolerability data were listed and reported as summary statistics. Results of immunological assays were explored by post hoc analyses and used to generate hypotheses about correlates and immunological mechanisms of protection. Analyses were coded in R (version 3.2.3)40 when not otherwise stated. Where possible, estimate and 95% confidence interval are given. Box plots display median (middle line), 25th (lower hinge) and 75th (upper hinge) quartile. Whiskers extend to values within 1.5× the inter-quartile ranges of the lower and upper hinges, respectively. A two-sided P value less than 5% was considered statistically significant. Flow cytometry data were analysed with Pestle v1.7, SPICE v5.3 (ref. 41) and Prism 6 (GraphPad). Graphs were rendered in FlowJo, SPICE, and Prism. For vaccine immunogenicity, comparisons to pre-vaccine were performed using Wilcoxon signed rank test with Bonferroni correction for multiple comparisons or two-way ANOVA with Bonferroni correction, as specified in the text. Immune responses assessed at baseline, two weeks after final immunization, and at the time of CHMI were compared to outcome (parasitaemia or no parasitaemia) after CHMI. Assessment of immune responses that correlated with sterile protection was made using a stratified Wilcoxon test controlling for vaccine dose group as a covariate. Sera were assessed for vaccine-induced antibodies by ELISA (enzyme-linked immunosorbent assay), immunofluorescence assay, inhibition of sporozoite invasion assay and protein arrays representing 91% of the Pf proteome. ELISAs were performed for antigens first expressed in PfSPZ (PfCSP, PfSSP2/TRAP, PfCelTOS, PfMSP5, PfAMA1), early liver stages (PfEXP1 and PfLSA1) and late liver stages (PfMSP1 and PfEBA175). The ELISA methods for each antigen are described below. Recombinant (r) proteins used in ELISA assays are listed in Supplementary Table 7. 96-well plates (Nunc Maxisorp Immuno Plate) were coated overnight at 4 °C with 0.5 μg to 2.0 μg recombinant proteins (Supplementary Table 7) in 50 μl per well in coating buffer (KPL). Plates were washed three times with 2 mM imidazole, 160 mM NaCl, 0.02% Tween 20, 0.5 mM EDTA and blocked with 1% Bovine Serum Albumin (BSA) blocking buffer (KPL) containing 1% or 5% non-fat dry milk (Supplementary Table 7) for 1 h at 37 °C. Plates were washed three times and serially diluted serum samples (in triplicates) were added and incubated at 37 °C for 1 h. After three washes, peroxidase labelled goat anti-human IgG (KPL) was added at a dilution of 0.05 μg ml−1 to 0.2 μg ml−1 (Supplementary Table 7) and incubated at 37 °C for 1 h. Plates were washed three times, ABTS peroxidase substrate was added for plate development, and the plates were incubated for defined periods at 22 °C room temperature (Supplementary Table 7). The plates were read with a Spectramax Plus384 microplate reader (Molecular Devices) at 405 nm. The data were collected using Softmax Pro GXP v5 and fit to a 4-parameter logistic curve, to calculate the serum dilution at OD 1.0. A negative control (pooled serum from non-immune individuals from malaria free area) was included in all assays. The following positive control sera were used for the different antigens: serum from an individual with anti-PfCSP antibodies for PfCSP; pooled sera from individuals immunized with PfLSA-1 and PfEBA-175 subunit vaccines respectively for PfLSA1 and PfEBA175; pooled sera from volunteers from a malaria-endemic area (acquired from a blood bank in Kenya) for PfAMA1, PfEXP1, and PfMSP1. No positive control sera were available for PfMSP5, PfSSP2/TRAP or PfCelTOS. Samples were considered positive if the difference between the post-immunization OD 1.0 and the pre-immunization OD 1.0 (net OD 1.0) was ≥50 and the ratio of post-immunization OD 1.0 to pre-immunization OD 1.0 (ratio) was ≥3. Purified PfSPZ (NF54 strain) from aseptic Anopheles stephensi mosquitoes produced by Sanaria were resuspended in phosphate buffered saline (PBS (pH 7.4)) to obtain 5 × 103 PfSPZ per 40 μl. 40 μl (5 × 103 PfSPZ) were added to each well of Greiner cellstar clear-bottom black 96-well plates (Sigma-Aldrich). After addition of the suspension, plates were left at room temperature for 12–18 h for air-drying. 50 μl of sera diluted in PBS with 2% BSA were added to each well of the 96-well plate containing air-dried PfSPZ. Sera samples were added at twofold dilutions starting at 1:50. After adding samples, plates were incubated at 37 °C for 1 h. Plates were washed in PBS three times on an Aquamax Microplate washer. Alexa Fluor 488 conjugated goat anti-human IgG (Molecular Probes) was diluted to 1:250 in PBS with 2% BSA and 50 μl was added to each well. The plates were then incubated for 1 h at 37 °C. Plates were washed three times with PBS on an Aquamax Microplate washer. 100 μl PBS was added to each well. The plates were sealed using a plate sealer and stored in the dark at 4 °C until data acquisition. Samples were assessed by scanning the plates using an Acumen eX3 laser scanning imaging cytometer. The positive control was pooled human serum taken two weeks after the last immunization from 12 uninfected volunteers immunized 4 or 5 times with 1.35 × 105 PfSPZ Vaccine5. The Acumen image cytometer scans the entire surface area of each well in a 96-well plate and the fluorescence intensity values (arbitrary units) therefore represent the signal from all 5 × 103 PfSPZ that were seeded in each well. The data obtained from the Acumen image cytometer were plotted to fit a 4-parameter sigmoidal curve in GraphPad Prism software using serum dilution (log transformed) as the x axis variable and arbitrary fluorescence units (AFU) on the y axis. Over many iterations during development of this assay we have determined that sera from naive volunteers in the USA and Europe, including pre-immune sera, always register an arbitrary fluorescence value less than 2 × 105 even at the highest concentration (1:50 dilution, see above) used in this assay. Moreover, for sera that react to PfSPZ, 2 × 105 AFU falls in the exponential portion of their sigmoidal curves. Therefore, 2 × 105 was chosen as a threshold in the automated immunofluorescence assay and the results for each volunteer for antibodies to PfSPZ are reported as the reciprocal serum dilution at which fluorescence intensity was equal to 2 × 105 AFU. HC-04 (1F9) (ref. 42) cells (hepatocytes) were obtained from the Naval Medical Research Center. Master and working cell banks were produced, and after establishing they were free of mycoplasma, were quality control released. For the assay they were cultured in complete medium (10% FBS in DMEM/F12 with 100 units per ml penicillin and 100 μg per ml streptomycin; Gibco by Life Technologies) in Entactic-Collagen IV-Laminin (ECL)-coated 96-well clear bottom black well plates (Greiner Bio-One North America) at a density of 2.5 × 104 cells per well, and incubated for 24 h at 37 °C, 5% CO with 85% relative humidity. Twenty-four hours later cells were infected with 104 aseptic, purified, cryopreserved PfSPZ per well, without or with sera diluted in a 12-point series from subjects immunized with PfSPZ Vaccine. The assay control included PfSPZ added with media alone. All subjects were assessed at pre-immunization (baseline), post-immunization and pre-CHMI time points. Three hours later, PfSPZ that had not invaded the HC-04 cells were removed by washing three times with Dulbecco’s phosphate-buffered saline (DPBS), and the cultures were fixed using 4% paraformaldehyde for 15 min at room temperature. Differential immunostaining was performed to differentiate between PfSPZ inside the hepatocytes versus PfSPZ outside the hepatocytes. PfSPZ outside the hepatocytes were stained with an anti-PfCSP mAb (2A10, 6.86 μg ml−1) (Protein Potential LLC, with permission from New York University School of Medicine) conjugated with Alexa Fluor 633 (far-red) (1 μg ml−1; custom-conjugated at GenScript). The hepatocytes were then permeabilized with 0.1% Triton X-100 for 10 min at room temperature, and the PfSPZ inside the hepatocytes were stained with the anti-PfCSP mAb (2A10, 6.86 μg ml−1) conjugated with Alexa Fluor 488 (green; 1 μg ml−1, conjugated from Genscript). The numbers and intensity of infected hepatocytes (green only) were counted by scanning the plates using an Acumen eX3 laser scanning imaging cytometer. The data obtained from the Acumen image cytometer were plotted to fit a 4-parameter sigmoidal curve in GraphPad Prism software using serum dilution (log transformed) as the x axis variable and arbitrary fluorescence units on the y axis. 75% inhibition was interpolated from the sigmoidal curves as the reciprocal serum dilution at which the fluorescent intensity of infected wells with serum was 25% of the negative control without serum. The number of invaded PfSPZ scored in this assay in the absence of sera ranged from 400–600 (intensity of 1–3 × 106 fluorescence units) (4% to 6% of those added to the wells). A whole-proteome microarray with 91% coverage of the Pf proteome (PfWPM) was produced by Antigen Discovery, Inc. (ADI). Proteins were expressed as previously described43 from a library of Pf partial or complete open reading frames (ORFs) cloned into a T7 expression vector pXI using an in vitro transcription and translation (IVTT) system, the Escherichia coli cell-free Rapid Translation System (RTS) kit (5 Prime). The library was created through an in vivo recombination cloning process with PCR-amplified Pf ORFs, and a complementary linearized expressed vector transformed into chemically competent E. coli was amplified by PCR and cloned into pXI vector using a high-throughput PCR recombination cloning method described elsewhere44. Each expressed protein includes a 5′ polyhistidine (HIS) epitope and 3′ haemagglutinin (HA) epitope. After expressing the proteins according to manufacturer’s instructions, translated proteins were printed onto nitrocellulose-coated glass AVID slides (Grace Bio-Labs) using an Omni Grid Accent robotic microarray printer (Digilabs, Inc.). Microarray chip printing and protein expression were quality checked by probing random slides with anti-HIS and anti-HA monoclonal antibodies with fluorescent labelling. PfWPM chips contained 7,455 Pf peptide fragments, representing proteins from 4,805 unique genes, 302 IgG positive control spots and 192 spotted IVTT reactions without Pf ORFs (IVTT controls). For each PfWPM chip, 3 replicates were printed per microarray slide on 3 nitrocellulose pads. IgG-positive control spots were included as an assay control, whereas IVTT control spots were included as a sample-level normalization factor. Serum samples were diluted 1:100 in a 3 mg ml−1 E. coli lysate solution in protein arraying buffer (Maine Manufacturing) and incubated at room temperature for 30 min. Chips were rehydrated in blocking buffer for 30 min. Blocking buffer was removed, and chips were probed with pre-incubated serum samples using sealed, fitted slide chambers to ensure no cross-contamination of sample between pads. Chips were incubated overnight at 4 °C with agitation. Chips were washed five times with TBS-0.05% Tween 20, followed by incubation with biotin-conjugated goat anti-human IgG (Jackson ImmunoResearch) diluted 1:200 in blocking buffer at room temperature. Chips were washed three times with TBS-0.05% Tween 20, followed by incubation with streptavidin-conjugated SureLight P-3 (Columbia Biosciences) at room temperature protected from light. Chips were washed three times with TBS-0.05% Tween 20, three times with TBS, and once with water. Chips were air dried by centrifugation at 1,000g for 4 min and scanned on a ScanArray Express HT spectral scanner (Perkin-Elmer), and spot and background intensities were measured using an annotated grid file (.GAL). Data were exported and normalized using the IVTT control spots for statistical analysis in R40. Raw spot and local background fluorescence intensities, spot annotations and sample phenotypes were imported and merged in R, where all subsequent procedures were performed40. Foreground spot intensities were adjusted by local background by subtraction, and negative values were converted to 1. Next, all foreground values were transformed using the base 2 logarithm (log ). The dataset was normalized to remove systematic effects by subtracting the median signal intensity of the IVTT controls for each sample. As the IVTT control spots carry the chip, sample and batch-level systematic effects, but also antibody background activity to the IVTT system, this procedure normalizes the data and provides a relative measure of the specific antibody binding to the non-specific antibody binding to the IVTT controls (a.k.a. background). With the normalized data, a value of 0.0 means that the intensity is no different than the background and a value of 1.0 indicates a doubling with respect to background. A seropositivity threshold was established for each protein on the chip using the top 2.5th percentile of the pre-immunization samples for each protein. Reactive antigens were defined as those that had seropositive responses after immunization and before CHMI, but which did not show seropositive responses in the mock-immunization group. PBMCs were isolated by density-gradient centrifugation from heparinized whole blood. Assessment of cellular immune responses using multi-parameter flow cytometry was performed on PBMCs from cryopreserved samples at the completion of the study, as described6. In brief, PBMCs were thawed and rested in complete RPMI for 8 h followed by stimulation for 17 h with: (1) 1.5 × 105 viable, irradiated, aseptic, purified, cryopreserved PfSPZ from a single production lot; (2) PfSPZ Vaccine diluent (1% human serum albumin, HSA, CSL Behring); (3) 2 × 105 lysed RBC, >90% infected with late-stage schizonts (PfRBC) from a single production lot; or (4) 2 × 105 donor-matched uninfected erythrocytes from a single production lot. For the last 5 h of the stimulation, 10 μg ml−1 Brefeldin A (BD) was added to the culture. After stimulation, cells were stained as previously described45. The staining panels are shown in Supplementary Table 8 and the antibody clones and manufacturers are shown in Supplementary Table 9. Briefly, cells were surface stained with CCR7 at 37 °C for 20 min. Dead cells were identified by Aqua Live-Dead dye (Invitrogen), as per manufacturer’s instructions. This was followed by 15 min surface staining at room temperature for CD4, CD8, CD14, CD38, CD45RA, CD56, CD57, CD127, CD161, TCR-γδ, TCR-Vδ1, TCR-Vδ2, TCR-Vγ9, TCR-Vα7.2, CXCR6, or PD-1. Cells were washed, fixed, and permeabilized using Cytofix/Cytoperm kit (BD) and stained intracellularly for CD3, IFN-γ, IL-2, TNF-α, IL-4, IL-10, perforin, or Ki-67. Cells were washed, fixed in 0.5% paraformaldehyde, and measured on a modified LSR II (BD). Flow cytometry data were analysed using FlowJo v9.9 (Tree Star) blinded to vaccination group and CHMI outcome. All antigen-specific cytokine frequencies are reported after background subtraction of identical gates from the same sample incubated with the control antigen stimulation (HSA or uninfected erythrocytes). The data that support the findings of these studies are available in part on request from the corresponding author (S.L.H.) subject to restrictions. Some data are not publicly available, as they contain information that could compromise research participant privacy/consent.


News Article | February 15, 2017
Site: www.prweb.com

The Structural Engineers Association of Southern California Foundation is pleased to announce that it will award eight scholarships to outstanding Southern California engineering students at the 2017 Structural Engineers Association of Southern California (SEAOSC) Annual Job Fair and Student Scholarship Awards Night held Wednesday, February 1, in Los Angeles, California. The call for scholarship award applications went out to many civil and structural engineering colleges and universities throughout Southern California including: California Polytechnic University San Luis Obispo, California Polytechnic University Pomona, California State University Northridge, California State University Los Angeles, California State University Fullerton, California State University Long Beach, , California Institute of Technology, Loyola Marymount University, University of California Los Angeles, University of California Irvine, and the University of Southern California. A total of $12,500 in scholarships will be awarded this year. Scholarships will be awarded at the SEAOSC Job Fair and Student Scholarship Awards Night which will take place from 3:30 p.m. to 9 p.m. at Luminarias, 3500 Ramona Boulevard, Monterey Park. Click the following links to register or for more information on becoming a sponsor. “It is an important annual tradition for SEAOSC and the SEAOSC Foundation to recognize and support talented and hard-working student engineers in order to promote the high standards of our profession as well as its value,” said SEAOSC President Jeff Ellis, S.E. “The Structural Engineers Association of Southern California, founded in 1929, is the oldest structural engineering association in the world. SEAOSC and the SEAOSC Foundation have given out many tens of thousands of dollars in student scholarships over the years.” “The SEAOSC Foundation is proud to award scholarships to these deserving civil and structural engineering students from southern California.” said SEAOSC Foundation Chairman Kevin O’Connell, S.E. “Through generous funding by engineering firms, industry supporters, and individuals, the SEAOSC Foundation will continue its purpose and advance the study of the scientific principles of structural engineering.” This year’s scholarships were funded in part through the generous donations of sponsors, including significant donations from longtime annual supported the David and Margaret Narver Family, and Optimum Seismic, a locally based earthquake retrofit engineering and construction firm. Other companies giving donations include Fluor, Hilti, Miyamoto International, Simpson Strong-Tie Company Inc., STB Structural Engineers, Structural Focus, and Vulcan Materials Company. ABOUT THE SEAOSC FOUNDATION: The Structural Engineers Association of Southern California Foundation (SEAOSC Foundation) is a non-profit, 501(c)(3) corporation started in 2007. The SEAOSC Foundation, in its goals to further the development of the structural engineering profession, looks for partners, be it individuals, companies or corporations, to pursue structural engineering innovation and research for use in the public domain. The SEAOSC Foundation can assist in the development process of specific structural engineering research projects and publishing of any findings. The SEAOSC Foundation is dependent upon donations for its operation and funding of research.


News Article | February 17, 2017
Site: www.businesswire.com

IRVING, Texas--(BUSINESS WIRE)--Fluor Corporation (NYSE: FLR) announced today that it has signed an agreement with JGC America, Inc. (JGC) to provide construction-related support to the front-end engineering and design (FEED) services for the Woodfibre Liquefied Natural Gas (LNG) project in the District of Squamish near Vancouver, British Columbia, Canada. Fluor booked the undisclosed contract value in the fourth quarter of 2016. Under the subcontract, Fluor will provide construction planning and design services to support the FEED package and engineering, procurement and construction proposal development. JGC is a FEED contractor for the proposed 2.1 million-tonnes-per-year natural gas Woodfibre liquefaction plant and export facility. “With our industry-leading modular design and construction approach, Fluor will work closely with JGC to develop a project execution strategy that delivers capital efficiency and schedule certainty to Woodfibre LNG,” said Pierre Bechelany, senior vice president of pipelines and LNG for Fluor. “Leveraging JGC’s extensive LNG experience and Fluor’s project execution and construction expertise, we look forward to helping Woodfibre LNG advance this project for the community and British Columbia.” The proposed facility will be powered with electricity from BC Hydro, which generates more than 90 percent clean renewable energy and will help create one of the cleanest LNG facilities in the world. Fluor Corporation (NYSE: FLR) is a global engineering, procurement, fabrication, construction and maintenance company that designs, builds and maintains capital-efficient facilities for its clients on six continents. For more than a century, Fluor has served our clients by delivering innovative and integrated solutions across the globe. With headquarters in Irving, Texas, Fluor ranks 155 on the FORTUNE 500 list with revenue of $18.1 billion in 2015 and has more than 60,000 employees worldwide. For more information, please visit www.fluor.com or follow us on Twitter @FluorCorp.


News Article | February 27, 2017
Site: www.businesswire.com

IRVING, Texas--(BUSINESS WIRE)--Fluor Corporation (NYSE: FLR) announced today that SunCoke Energy, Inc. (SunCoke) has awarded Fluor a contract to provide certain maintenance support and capital project services at SunCoke coke facilities in the United States. Fluor will book the undisclosed contract value in the first quarter of 2017. Under the five-year contract, Fluor will provide maintenance and capital project services at SunCoke’s U.S. domestic coke facilities, which produce high-quality coke for use in steelmaking. Fluor will transition onto the sites in early March 2017 and work alongside SunCoke employees. “With a detailed transition plan, we are partnering with SunCoke on a seamless transition to the sites with no disruption to current operations,” said Dale Barnard, vice president of North American maintenance, modification and asset integrity operations for Fluor. “We will implement our asset performance management process and identify specific opportunities to reduce SunCoke’s total ownership costs.” Fluor, along with its Stork division, delivers maintenance, modification and asset integrity services at more than 200 sites in North America, with extensive experience in multi-site execution. Fluor Corporation (NYSE: FLR) is a global engineering, procurement, fabrication, construction and maintenance company that designs, builds and maintains capital-efficient facilities for its clients on six continents. For more than a century, Fluor has served our clients by delivering innovative and integrated solutions across the globe. With headquarters in Irving, Texas, Fluor ranks 155 on the FORTUNE 500 list with revenue of $19 billion in 2016 and has more than 60,000 employees worldwide. For more information, please visit www.fluor.com or follow us on Twitter @FluorCorp.


News Article | February 17, 2017
Site: www.24-7pressrelease.com

HOUSTON, TX, February 17, 2017-- Leslie Antalffy is a celebrated Marquis Who's Who biographee. As in all Marquis Who's Who biographical volumes, individuals profiled are selected on the basis of current reference value. Factors such as position, noteworthy accomplishments, visibility, and prominence in a field are all taken into account during the selection process.Marquis Who's Who, the world's premier publisher of biographical profiles, is proud to name Leslie Antalffy a Lifetime Achiever. An accomplished listee, Leslie Antalffy celebrates many years' experience in his professional network, and has been noted for achievements, leadership qualities, and the credentials and successes he has accrued in his field.Mr. Antalffy is the executive director of process technology and engineering for Fluor Enterprises, Inc., a publicly traded engineering, procurement, construction, maintenance, and project management company.Mr. Antalffy has achieved 12 US patents in the field of delayed coking and was named as a Life Fellow of the American Society of Mechanical Engineers. Marquis Who's Who has recognized Mr. Antalffy in Who's Who in Finance and Industry, Who's Who in America, Who's Who in Science and Engineering, Who's Who in the South and Southwest, and Who's Who in the World.In recognition of outstanding contributions to his profession and the Marquis Who's Who community, Leslie Antalffy has been featured on the Marquis Who's Who Lifetime Achievers website. Please visit https://wwlifetimeachievement.com/2016/12/13/leslie-peter-antalffy/ to view this distinguished honor.About Marquis Who's Who :Since 1899, when A. N. Marquis printed the First Edition of Who's Who in America , Marquis Who's Who has chronicled the lives of the most accomplished individuals and innovators from every significant field of endeavor, including politics, business, medicine, law, education, art, religion and entertainment. Today, Who's Who in America remains an essential biographical source for thousands of researchers, journalists, librarians and executive search firms around the world. Marquis publications may be visited at the official Marquis Who's Who website at www.marquiswhoswho.com

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