Urinary heavy metals and overall survival of advanced high-grade serous ovarian cancer: A nested case-control study in China.

BACKGROUND: Environmental pollution has emerged as a significant determinant in ovarian cancer prognosis. However, limited evidence exists regarding the correlations between heavy metals and ovarian cancer prognosis. OBJECTIVE: To elucidate the relationship between urinary heavy metals and their mixtures with overall survival (OS) of advanced high-grade serous ovarian cancer (HGSOC). METHODS: Within the Ovarian Cancer Follow-Up Study, we conducted a nested case-control study. A sum of 159 deceased patients and an equal number of alive patients were included, matched by sample date, body mass index, and age at diagnosis. Urinary concentrations of five heavy metals were quantified: arsenic (As), cadmium (Cd), chromium (Cr), mercury (Hg), and lead (Pb). Conditional logistic regression models were employed to calculate odds ratios (ORs) and their 95 % confidence intervals (CIs). To elucidate joint effects, we utilized quantile g-computation and Bayesian kernel machine regression models. RESULTS: For the multivariable adjusted conditional logistic regression model, significant associations were found between high urinary levels of As (OR=1.99, 95 %CI: 1.05-3.79), Cd (OR=2.56, 95 %CI: 1.29-5.05), Hg (OR=2.24, 95 %CI: 1.09-4.62), and Pb (OR=3.80, 95 %CI: 1.75-8.27) and worse OS of HGSOC, comparing the highest tertile to the lowest. Analysis of joint effects showed that elevated concentrations of heavy metal mixtures were related to poor OS of HGSOC. Pb exhibited the highest contribution to the overall association within the metal mixtures. CONCLUSIONS: High urinary heavy metal concentrations were linked to worse OS of HGSOC. Future research is necessary to validate our findings.

Integrating Multi-Omics Data to Uncover Prostate Tissue DNA Methylation Biomarkers and Target Genes for Prostate Cancer Risk.

Previous studies have indicated that specific CpG sites may be linked to the risk of prostate cancer (PCa) by regulating the expression of PCa target genes. However, most existing studies aim to identify DNA methylation (DNAm) biomarkers through blood tissue genetic instruments, which impedes the identification of relevant biomarkers in prostate tissue. To identify PCa risk-associated CpG sites in prostate tissue, we established genetic prediction models of DNAm levels using data from normal prostate samples in the GTEx (N = 108) and assessed associations between genetically predicted DNAm in prostate and PCa risk by studying 122,188 cases and 604,640 controls. We observed significant associations for 3879 CpG sites, including 926 at novel genomic loci. Among them, DNAm levels of 80 CpG sites located at novel loci are significantly associated with expression levels of 45 neighboring genes in normal prostate tissue. Of these genes, 11 further exhibit significant associations with PCa risk for their predicted expression levels in prostate tissue. Intriguingly, a total of 31 CpG sites demonstrate consistent association patterns across the methylation-gene expression-PCa risk pathway. Our findings suggest that specific CpG sites may be related to PCa risk by modulating the expression of nearby target genes.

Associations between peripheral whole blood cell counts derived indexes and cancer prognosis: An umbrella review of meta-analyses of cohort studies.

Meta-analyses have reported conflicting data on the whole blood cell count (WBCC) derived indexes (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], and lymphocyte-to-monocyte ratio [LMR]) and cancer prognosis. However, the strength and quality of this evidence has not been quantified in aggregate. To grade the evidence from published meta-analyses of cohort studies that investigated the associations between NLR, PLR, and LMR and cancer prognosis. A total of 694 associations from 224 articles were included. And 219 (97.8%) articles rated as moderate-to-high quality according to AMSTAR. There were four associations supported by convincing evidence. Meanwhile, 165 and 164 associations were supported by highly suggestive and suggestive evidence, respectively. In this umbrella review, we summarized the existing evidence on the WBCC-derived indexes and cancer prognosis. Due to the direction of effect sizes is not completely consistent between studies, further research is needed to assess causality and provide firm evidence.

Adverse pregnancy outcomes and multiple cancers risk in both mother and offspring: an umbrella review of systematic reviews with meta-analyses of observational studies.

BACKGROUND: Adverse pregnancy outcomes have reached epidemic proportions in recent years with serious health ramifications, especially for diverse cancers risk. Therefore, we carried out an umbrella review to systematically evaluate the validity and strength of the data and the extent of potential biases of the established association between adverse pregnancy outcomes and cancers risk in both mother and offspring. METHODS: PubMed, Embase, and Web of Science databases were searched from inception until 18 January 2024. Meta-analyses of observational studies investigating the relationship between adverse pregnancy outcomes and multiple cancers risk in both mother and offspring were included. Evidence certainty was assessed using Grading of Recommendations, Assessment, Development, and Evaluation. The protocol for this umbrella review was prospectively registered in PROSPERO (CRD42023470544). RESULTS: The search identified 129 meta-analyses of observational studies and 42 types of cancer. Moderate certainty of evidence, exhibiting statistical significance, has been observed linking per kilogram increase in birth weight to a heightened risk of breast cancer (OR = 1.07, 95% CI = 1.02-1.12), prostate cancer (OR = 1.02, 95% CI = 1.00-1.05), leukemia (OR = 1.18, 95% CI = 1.13-1.23), and acute lymphoblastic leukemia in offspring (OR = 1.18, 95% CI = 1.12-1.23); rubella infection during pregnancy to an increased risk of leukemia in offspring (OR = 2.79, 95% CI = 1.16-6.71); and a linear dose-response association between an increase in the proportion of optimal birth weight and an elevated risk of acute lymphoblastic leukemia in offspring (OR = 1.16, 95% CI = 1.09-1.24), respectively. CONCLUSIONS: Although some adverse pregnancy outcomes have clinically promising associations with risk of several cancers in both mother and offspring, it is essential to conduct additional research to solidify the evidence, evaluate causality, and ascertain clinical utility.

Fine Mapping Regulatory Variants by Characterizing Native CpG Methylation with Nanopore Long-Read Sequencing.

5-methylcytosine (5mC) is the most common chemical modification occurring on the CpG sites across the human genome. Bisulfite conversion combined with short-read whole genome sequencing can capture and quantify the modification at single nucleotide resolution. However, the PCR amplification process could lead to duplicative methylation patterns and introduce 5mC detection bias. Additionally, the limited read length also restricts co-methylation analysis between distant CpG sites. The bisulfite conversion process presents a significant challenge for detecting variant-specific methylation due to the destruction of allele information in the sequencing reads. To address these issues, we sought to characterize the human methylation profiling with the nanopore long-read sequencing, aiming to demonstrate its potential for long-range co-methylation analysis with native modification call and intact allele information retained. In this regard, we first analyzed the nanopore demo data in the adaptive sampling sequencing run targeting all human CpG islands. We applied the linkage disequilibrium (LD) R2 to calculate the co-methylation in nanopore data, and further identified 27,875, 50,481, 26,542 and 51,189 methylation haplotype blocks (MHB) in COLO829, COLO829BL, HCC1395 and HCC1395BL cell lines, respectively. Interestingly, while we found that majority of the co-methylation were in a short range (≤200bp), a small portion (1~3%) showed long distance (≥1,000bp), suggesting potential remote regulatory mechanisms across the genome. To further characterize the epigenetic changes related to transcription factor binding, we profiled the 5mC percentage changes surrounding various motif sites in JASPAR collection and found that CTCF and KLF5 binding sites showed reduced methylation, while FOXE1 and ZNF354A sites showed increased methylation. To further investigate the allele-specific 5mCG in the prostate genome, we designed a target region covering methylation quantitative trait loci (mQTL) and genome-wide association study (GWAS) risk germline variants and generated long reads with adaptive sampling run in the 22Rv1 cell line. To identify the allele-specific methylation in the 22Rv1 cell line, we performed long-read based phasing and compared the 5mCG signals between the two haplotypes. As a result, we identified 6,390 haplotype-specific methylated regions in the 22Rv1 cell line (p-MWU ≤ 1e-5 and delta ≥ 50%). By examining haplotype-specific methylated regions near the phasing variants, we identified examples of allele-specific methylated regions that showed allelespecific accessibility in the ATAC-seq data. By further integrating the ATAC-seq data of 22Rv1, we found that methylation levels were negatively correlated with chromatin accessibility at the genome-wide scale. Our study has revealed native methylome profiling while preserving haplotype information, offering a novel approach to uncovering the regulatory mechanisms of the human prostate genome.

Natural Products-Based Anticancer Agents: Synthesis and Anticancer Activities of Funtumine Amide/sulfonamide Derivatives.

Funtumine is a pregnene-type steroidal alkaloid exhibiting moderate anticancer activity. To discover novel natural product-based anticancer drugs, a series of novel funtumine amide/sulfonamide derivatives were papered and identified using spectroscopic techniques. Additionally, the structures of compounds 2j, 3a, and 4k were further confirmed through X-ray diffraction analysis. Biological activity experiments conducted against three cancer cell lines revealed that several of the synthesized compounds demonstrated inhibition activities comparable to or exceeding those of the commercial anticancer agent, 5-Fluorouracil. Especially compound 4i demonstrated a notably strong growth inhibitory effect on HePG2 (IC50 = 14.89 µM) and HCT116 (IC50 = 15.67 µM) cell lines, while exhibiting minimal cytotoxicity towards human normal BEAS-2B cells. Preliminary structure-activity relationships (SARs) analysis indicated that the conversion of the carbonyl group at the C-20 position of funtumine to a hydroxyl group could yield more potent compounds.

A truncated B-box zinc finger transcription factor confers drought sensitivity in modern cultivated tomatoes.

Enhancing drought tolerance in crops and understanding the underlying mechanisms have been subject of intense research. The precise function and molecular mechanisms of B-box zinc finger proteins (BBX) remain elusive. Here, we report a natural allele of BBX18 (BBX18TT) that encodes a C-terminal truncated protein. While most wild tomato germplasms contain the BBX18CC allele and show more drought tolerant, modern cultivated tomatoes mostly carry BBX18TT allele and are more drought sensitive. Knockout of BBX18 leads to improved drought tolerance in transgenic plants of cultivated tomato. Ascorbate peroxidase 1 (APX1) is identified as a BBX18-interacting protein that acts as a positive regulator of drought resistance in tomato. Chromatin immunoprecipitation sequencing analyses reveal that BBX18 binds to a unique cis-acting element of the APX1 promoter and represses its gene expression. This study provides insights into the molecular mechanism underlying drought resistance mediated by the BBX18-APX1 module in plants.

Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations.

AIMS/HYPOTHESIS: Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European. METHODS: Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations. RESULTS: We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development. CONCLUSIONS/INTERPRETATION: Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations. DATA AVAILABILITY: The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https://github.com/Arthur1021/MESA-1K-PWAS ).

Association between pre-diagnosis and post-diagnosis Alternate Mediterranean Diet and ovarian cancer survival: evidence from a prospective cohort study.

BACKGROUND: There is currently a lack of comprehensive evidence regarding the correlation between Alternate Mediterranean Diet (AMED) and the survival of patients with ovarian cancer (OC). This prospective cohort study first assessed the association of AMED, not only pre-diagnosis and post-diagnosis but also the change from pre-diagnosis to post-diagnosis with OC survival. METHODS: A total of 560 OC patients were included in the study, and their dietary intake was assessed using a reliable 111-item food frequency questionnaire. The overall survival (OS) of the patients was monitored through active follow-up and review of medical records until February 16th, 2023. Cox proportional hazard regression models were utilized to compute the hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs). RESULTS: Out of the total 560 patients with OC, 211 (37.68%) succumbed during a median follow-up period of 44.40 months (interquartile range: 26.97-61.37). Comparative analysis indicated a significant association between the highest tertiles of pre-diagnosis (HR = 0.59; 95% CI 0.38-0.90; Ptrend < 0.05) and post-diagnosis (HR = 0.61; 95% CI 0.41-0.91; Ptrend < 0.05) AMED intake and improved OS as opposed to the lowest tertile. Additionally, a significant linear trend was observed for AMED and OC survival. Notably, decreased intake (more than 5% change) and significantly increased intake (more than 15% change) of AMED from pre-diagnosis to post-diagnosis were linked to worse and better OS, respectively, when compared to the stable intake group (change within 5%). Furthermore, patients displaying consistently higher AMED intake both before and after diagnosis experienced enhanced OS in comparison to those with consistently low AMED intake (HRHigh-High vs. Low-Low = 0.47; 95% CI 0.31-0.70). CONCLUSION: High pre-diagnosis and post-diagnosis AMED was associated with an improved OS in patients with OC, suggesting that maintaining a consistently high intake of AMED could potentially benefit the prognosis of OC.

Application of three-dimensional visualization technology in early surgical repair of bile duct injury during laparoscopic cholecystectomy.

OBJECTIVE: This study aimed to explore the application value of three-dimensional (3D) visualization technology in the early surgical repair of bile duct injury during laparoscopic cholecystectomy (LC). METHODS: A retrospective analysis was conducted on the clinical data of 15 patients who underwent early surgical repair of bile duct injury during LC with the assistance of 3D visualization technology at the Hepatobiliary Surgery Department of Ningxia Hui Autonomous Region People's Hospital from January 2019 to December 2022. Postoperative efficacy and long-term follow-up outcomes were summarized. RESULTS: Before the repair surgery, 15 cases of bile duct injury during LC were evaluated using 3D visualization technology according to the Strasberg-Bismuth classification: 2 cases of type C, 4 of type E1, 3 of type E2, 3 of type E3, and 3 of type E4. Intraoperative findings were consistent with the 3D visualization reconstruction results, and all patients successfully underwent hepaticojejunostomy using Roux-en-Y anastomosis guided by the 3D visualization navigation. The time interval between LC and bile duct repair surgery ranged from 5 to 28 (14.2 ± 9.7) days. The surgical time was between 120 and 190 (156.40 ± 23.92) min, and estimated blood loss ranged from 80 to 250 (119.66 ± 47.60) mL. The length of hospital stay ranged from 12 to 25 days (median: 16 days). One patient experienced mild bile leakage after the operation, which healed with conservative treatment. All patients were followed up for 12-56 months (median: 34 months) without any loss to follow-up. During the follow-up period, no complications, such as anastomotic stricture or stone formation, were observed. CONCLUSION: The application of 3D visualization technology for preoperative evaluation and intraoperative navigation can accurately and effectively facilitate early surgical repair of bile duct injury during LC and has clinical value for promotion and application.

Prognosis Analysis of Rat Liver Transplantation Under Direct Vision of Single Operator.

OBJECTIVE: This study aims to investigate the impact of surgical experimental variables on the prognosis of orthotopic liver transplantation (OLT) in rats, with the goal of enhancing the efficacy of modeling techniques. METHODS: Using Kamada's "two-cuff method" of rat orthotopic liver transplantation, 76 pairs of SD-Wistar rats were performed orthotopic liver transplantation from March to September 2023. Thirteen experimental factors during the perioperative period and the survival time of recipient rats were collected and recorded. To explore the surgical factors affecting the prognosis of rat liver transplantation and summarize the surgical techniques. RESULTS: The success rate of orthotopic liver transplantation in SD-Wistar rats was 68.4%, with 24 recipients surviving within 3-7 days and 28 recipients surviving more than 1 week. Donor liver perfusion, recipient blood loss, recipient liver blood expulsion, anhepatic phase, suprahepatic inferior vena cava anastomosis time and anesthesia recovery time are related to the survival of recipient rats after liver transplantation. Donor liver perfusion, eliminating blood in recipient liver and intraoperative blood loss of recipient are surgical factors affecting the prognosis of liver transplantation in rats. The survival time of recipient rats with liver perfusion through abdominal aorta, eliminating blood in recipient liver was relatively prolonged after operation. CONCLUSION: Under the condition of reasonable control of the anhepatic phase, the perfusion method of the donor liver, whether to eliminate blood in recipient liver, and intraoperative blood loss of recipient are important surgical factors affecting the prognosis of liver transplantation in rats.

Benchmarking DNA Foundation Models for Genomic Sequence Classification.

The rapid advancement of DNA foundation language models has revolutionized the field of genomics, enabling the decoding of complex patterns and regulatory mechanisms within DNA sequences. However, the current evaluation of these models often relies on fine-tuning and limited datasets, which introduces biases and limits the assessment of their true potential. Here, we present a benchmarking study of three recent DNA foundation language models, including DNABERT-2, Nucleotide Transformer version-2 (NT-v2), and HyenaDNA, focusing on the quality of their zero-shot embeddings across a diverse range of genomic tasks and species through analyses of 57 real datasets. We found that DNABERT-2 exhibits the most consistent performance across human genome-related tasks, while NT-v2 excels in epigenetic modification detection. HyenaDNA stands out for its exceptional runtime scalability and ability to handle long input sequences. Importantly, we demonstrate that using mean token embedding consistently improves the performance of all three models compared to the default setting of sentence-level summary token embedding, with average AUC improvements ranging from 4.3% to 9.7% for different DNA foundation models. Furthermore, the performance differences between these models are significantly reduced when using mean token embedding. Our findings provide a framework for selecting and optimizing DNA language models, guiding researchers in applying these tools effectively in genomic studies.

Genetic Architecture and Analysis Practices of Circulating Metabolites in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.

Circulating metabolite levels partly reflect the state of human health and diseases, and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single study analyses. Leveraging the rich metabolomics resources generated by the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally-diverse samples. We provided recommendations for outlier and imputation handling to process metabolite data, as well as a general analytical framework. We further performed a pooled analysis following our practical recommendations and discovered 1,778 independent loci associated with 667 metabolites. Among 108 novel locus - metabolite pairs, we detected not only novel loci within previously implicated metabolite associated genes, but also novel genes (such as GAB3 and VSIG4 located in the X chromosome) that have putative roles in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, including well-known metabolic genes such as FADS2 , D2HGDH , SUGP1 , UTG2B17 , strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

The Causal Effect of Intrapancreatic Fat Deposition on Acute and Chronic Pancreatitis: A Mendelian Randomization Study.

INTRODUCTION: Recent associative studies have linked intrapancreatic fat deposition (IPFD) with risk of pancreatitis, but the causal relationship remains unclear. METHODS: Using Mendelian randomization, we evaluated the causal association between genetically predicted IPFD and pancreatitis. This approach used genetic variants from genomewide association studies of IPFD (n = 25,617), acute pancreatitis (n = 6,787 cases/361,641 controls), and chronic pancreatitis (n = 3,875 cases/361,641 controls). RESULTS: Genetically predicted IPFD was significantly associated with acute pancreatitis (odds ratio per 1-SD increase: 1.40 [95% CI: 1.12-1.76], P = 0.0032) and chronic pancreatitis (odds ratio: 1.64 [95% CI: 1.13-2.39], P = 0.0097). DISCUSSION: Our findings support a causal role of IPFD in pancreatitis, suggesting that reducing IPFD could lower the risk of pancreatitis.

An atlas of genetic effects on the monocyte methylome across European and African populations.

Elucidating the genetic architecture of DNA methylation (DNAm) is crucial for decoding the etiology of complex diseases. However, current epigenomic studies often suffer from incomplete coverage of methylation sites and the use of tissues containing heterogeneous cell populations. To address these challenges, we present a comprehensive human methylome atlas based on deep whole-genome bisulfite sequencing (WGBS) and whole-genome sequencing (WGS) of purified monocytes from 298 European Americans (EA) and 160 African Americans (AA) in the Louisiana Osteoporosis Study. Our atlas enables the analysis of over 25 million DNAm sites. We identified 1,383,250 and 1,721,167 methylation quantitative trait loci (meQTLs) in cis -regions for EA and AA populations, respectively, with 880,108 sites shared between ancestries. While cis -meQTLs exhibited population-specific patterns, primarily due to differences in minor allele frequencies, shared cis -meQTLs showed high concordance across ancestries. Notably, cis -heritability estimates revealed significantly higher mean values in the AA population (0.09) compared to the EA population (0.04). Furthermore, we developed population-specific DNAm imputation models using Elastic Net, enabling methylome-wide association studies (MWAS) for 1,976,046 and 2,657,581 methylation sites in EA and AA, respectively. The performance of our MWAS models was validated through a systematic multi-ancestry analysis of 41 complex traits from the Million Veteran Program. Our findings bridge the gap between genomics and the monocyte methylome, uncovering novel methylation-phenotype associations and their transferability across diverse ancestries. The identified meQTLs, MWAS models, and data resources are freely available at www.gcbhub.org and https://osf.io/gct57/ .

Validation of candidate protein biomarkers previously identified by genetic instruments for prostate cancer risk: A prospective cohort analysis of directly measured protein levels in the ARIC study.

BACKGROUND: Multiple novel protein biomarkers have been shown to be associated with prostate cancer risk using genetic instruments. This study aimed to externally validate the associations of 30 genetically predicted candidate proteins with prostate cancer risk using aptamer-based levels in US Black and White men in the Atherosclerosis Risk in Communities (ARIC) study. Plasma protein levels were previously measured by SomaScan® using the blood collected in 1990-1992. METHODS: Among 4864 eligible participants, we ascertained 667 first primary prostate cancer cases through 2015. Hazard ratios (HRs) of prostate cancer and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression for tertiles of each protein. We adjusted for age, race, and other risk factors. RESULTS: Of the 30 proteins and considering a nominal p trend < 0.05, two were positively associated with prostate cancer risk-RF1ML (tertile 3 vs. 1: HR = 1.23; 95% CI 1.02-1.48; p trend = 0.037) and TPST1 (1.28, 95% CI 1.06-1.55; p trend = 0.0087); two were inversely associated-ATF6A (HR = 0.80, 95% CI 0.65-0.98; p trend = 0.028) and SPINT2 (HR = 0.74, 95% CI 0.61-0.90; p trend = 0.0025). One protein, KDEL2, which was nonlinearly associated (test-for-linearity: p < 0.01) showed a statistically significant lower risk in the second tertile (HR = 0.79, 95% CI 0.65-0.95). Of these five, four proteins-ATF6A, KDEL2, RF1ML, and TPST1-were consistent in the direction of association with the discovery studies. CONCLUSION: This study validated some pre-diagnostic protein biomarkers of the risk of prostate cancer.

Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells.

While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations (p-value ≤ 0.05, gene abundance percentage ≥ 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants (p = 0.0055). Among these findings were previously reported regulatory variants including rs60464856-RUVBL1 (multiome p-value = 0.0099 in BPH1) and rs7247241-SPINT2 (multiome p-value = 0.0002- 0.0004 in 22Rv1). We also functionally validated a new regulatory SNP and its target gene rs2474694-VPS53 (multiome p-value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.

Binder-Responsive DNA Strand Displacement Enables High-Throughput and High-Fidelity Discovering of Small Molecular DNA Binders.

High-throughput screening (HTS) is pivotal in the discovery of small molecules that bind to DNA, yet there are limited sensing mechanisms available for designing HTS assays for DNA binders. Herein, we introduce a binder-responsive toehold-mediated DNA strand displacement (BR-TMSD) technique featuring programmable reaction kinetics in response to DNA-binder interactions. When two DNA binders are used, BR-TMSD is initiated through a rapid binder displacement, followed by the DNA strand displacement. The orthogonal displacement reactions of BR-TMSD enables a high-fidelity, dual-channel HTS assay, returning 19 new DNA binders from a library of 1,170 compounds.

Enhancement of Cu2ZnSn(S, Se)4 device performance using an IPA/MOE hybrid solvent system in ambient air.

In this work, a mixed precursor solvent system comprising isopropyl alcohol (IPA) and 2-methoxy ethanol (MOE) is introduced for the fabrication of Cu2ZnSn(S, Se)4 (CZTSSe) thin films under ambient conditions. The effects of different IPA/(MOE + IPA) ratios on the characteristics of CZTSSe films and the corresponding devices were investigated. Our research results indicate that the addition of IPA enhances the wettability of Cu-Zn-Sn-S precursor solution on the substrate, reduces Sn loss in the film during high-temperature annealing, and diminishes band tail states. Additionally, adding IPA leads to effective enlargement of grain size, improved crystallinity, and enhanced light absorption. However, excessive content of IPA negatively impacts CZTSSe film properties and the device's performance. Notably, when substituting 20% of MOE with IPA, the short-circuit current density (JSC) increased from 30.84 mA cm-2 to 35.55 mA cm-2 in the resulting CZTSSe device, and the efficiency improved from 9.19% to 10.63%. This work provides a new method of a solvent system for preparing efficient kesterite-based solar cells.