Crystal structure of (S)-5,7-diphenyl-4,7-dihydrotetrazolo[1,5-a]pyrimidine

Acknowledgements The authors thank Christopher Daley, A. Rheingold and C. Moore (UCSD) for the data collection. Funding for this work was provided by the University of California, Merced and the National Science Foundation (CHE-1300686)Peer reviewedPublisher PD

Extraterrestrial Amino Acids Identified in Metal-Rich CH and CB Carbonaceous Chondrites from Antarctica

Carbonaceous chondrites contain numerous indigenous organic compounds and could have been an important source of prebiotic compounds required for the origin of life on Earth or elsewhere. Extraterrestrial amino acids have been reported in five of the eight groups of carbonaceous chondrites and are most abundant in CI, CM, and CR chondritesbut are also present in the more thermally altered CV and CO chondrites. We report the abundance, distribution, and enantiomeric and isotopic compositions of simple primary amino acids in six metal-rich CH and CB carbonaceous chondrites that have not previously been investigated for amino acids: Allan Hills (ALH) 85085 (CH3), Pecora Escarpment(PCA) 91467 (CH3), Patuxent Range (PAT) 91546 (CH3), MacAlpine Hills (MAC) 02675(CBb), Miller Range (MIL) 05082 (CB), and Miller Range (MIL) 07411 (CB). Amino acid abundances and carbon isotopic values were obtained by using both liquid chromatography time-of-flight mass spectrometry and fluorescence, and gas chromatography isotope ratiomass spectrometry. The (delta D, delta C-13, delta N-15) ratios of multiple amino acids fall outside of the terrestrial range and support their extraterrestrial origin. Extracts of CH chondrites were found to be particularly rich in amino acids (1316 parts per million, ppm) while CB chondrite extracts had much lower abundances (0.22 ppm). The amino acid distributions of the CH and CB chondrites were distinct from the distributions observed in type 2 and 3 CM and CR chondrites and contained elevated levels of beta-, gamma-, and delta-amino acids compared to the corresponding alpha-amino acids, providing evidence that multiple amino acid formation mechanisms were important in CH and CB chondrites

Artificial Intelligence-Enabled Optimization of Battery-Grade Lithium Carbonate Production

By 2035, the need for battery-grade lithium is expected to quadruple. About half of this lithium is currently sourced from brines and must be converted from a chloride into lithium carbonate (Li2CO3) through a process called softening. Conventional softening methods using sodium or potassium salts contribute to carbon emissions during reagent mining and battery manufacturing, exacerbating global warming. This study introduces an alternative approach using carbon dioxide (CO2(g)) as the carbonating reagent in the lithium softening process, offering a carbon capture solution. We employed an active learning-driven high-throughput method to rapidly capture CO2(g) and convert it to lithium carbonate. The model was simplified by focusing on the elemental concentrations of C, Li, and N for practical measurement and tracking, avoiding the complexities of ion speciation equilibria. This approach led to an optimized lithium carbonate process that capitalizes on CO2(g) capture and improves the battery metal supply chain's carbon efficiency

Summary: Combating Climate Change with Section 115 of the Clean Air Act

The scale and scope of the climate crisis calls for comprehensive nationwide efforts to reduce greenhouse gas emissions. New legislation, passed by Congress and signed by the President, is the first and best option for climate action at the federal level. This could be a version of the Green New Deal, a carbon tax, sectoral limits, an emissions cap with compliance trading, or another approach. What matters most is that the legislation effectively cut the greenhouse gas emissions driving the world’s temperatures ever higher. Unfortunately, the prospect for federal legislation is uncertain, while strong and decisive action is needed now. A president committed to tackling climate change will need a backup plan in case Congress remains gridlocked, one that relies on existing statutes to achieve the deep emission reductions the science says we need

Iterative in situ click chemistry creates antibody-like protein-capture agents

Iterative in situ click chemistry (see scheme for the tertiary ligand screen) and the one-bead-one-compound method for the creation of a peptide library enable the fragment-based assembly of selective high-affinity protein-capture agents. The resulting ligands are water-soluble and stable chemically, biochemically, and thermally. They can be produced in gram quantities through copper (I)-catalyzed cycloaddition

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among Men of African Descent: A case-control study

<p>Abstract</p> <p>Background</p> <p>Polymorphisms in <it>glutathione S-transferase </it>(GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected <it>GST </it>genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic <it>GSTs </it>(<it>M1</it>, <it>T1</it>, and <it>P1</it>) alone and combined with cigarette smoking on PCA susceptibility.</p> <p>Methods</p> <p>In order to evaluate the effects of <it>GST </it>polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of <it>GSTM1 </it>and <it>GSTT1 </it>gene deletions, <it>GSTP1 </it>105 Val and cigarette smoking on PCA risk.</p> <p>Results</p> <p>We observed a moderately significant association between risk among men possessing at least one variant <it>GSTP1 </it>105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among <it>GSTM1 </it>(OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and <it>GSTT1 </it>(OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the <it>GSTM1</it>-<it>GSTP1 </it>pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the <it>GSTP1 </it>Val marker. Notably, the <it>GSTM1</it>-<it>GSTP1 </it>axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the <it>GST </it>SNPs and PCA.</p> <p>Conclusion</p> <p>A moderately significant association was observed between PCA risk and men possessing at least one variant <it>GSTP1 </it>105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the <it>GSTP1 </it>(Val/Val) and <it>GSTM1 </it>(*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting <it>GSTP1 </it>105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility.</p

Data from a pre-publication independent replication initiative examining ten moral judgement effects

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science

The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had “in the pipeline” as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed