Investigating gene functions and single-cell expression profiles of de novo variants in orofacial clefts.

Orofacial clefts (OFCs) are common congenital birth defects with various etiologies, including genetic variants. Online Mendelian Inheritance in Man (OMIM) annotated several hundred genes involving OFCs. Furthermore, several hundreds of de novo variants (DNVs) have been identified from individuals with OFCs. Some DNVs are related to known OFC genes or pathways, but there are still many DNVs whose relevance to OFC development is unknown. To explore novel gene functions and their cellular expression profiles, we focused on DNVs in genes that were not listed in OMIM. We collected 960 DNVs in 853 genes from published studies and curated these genes, based on the DNVs' deleteriousness, into 230 and 23 genes related to cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO), respectively. For comparison, we curated 178 CL/P and 277 CPO genes from OMIM. In CL/P, the pathways enriched in DNV and OMIM genes were significantly overlapped (p = 0.002). Single-cell RNA sequencing (scRNA-seq) analysis of mouse lip development revealed that both gene sets had abundant expression in the ectoderm (DNV genes: adjusted p = 0.032, OMIM genes: adjusted p < 0.0002), while only DNV genes were enriched in the endothelium (adjusted p = 0.032). Although we did not achieve significant findings using CPO gene sets, which was mainly due to the limited number of DNV genes, scRNA-seq analysis implicated various expression patterns among DNV and OMIM genes. Our results suggest that combinatory pathway and scRNA-seq data analyses are helpful for contextualizing genes in OFC development.

Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach.

Alzheimer's Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD's pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10-12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.

Ba6RE2Ti4O17 (RE = Nd, Sm, Gd, Dy-Yb): A Family of Rare-Earth-Based Layered Triangular Lattice Magnets.

The exploration of new rare-earth (RE)-based triangular-lattice materials plays a significant role in motivating the discovery of exotic magnetic states. Herein, we report a family of hexagonal perovskite compounds Ba6RE2Ti4O17 (RE = Nd, Sm, Gd, Dy-Yb) with a space group of P63/mmc, where magnetic RE3+ ions are distributed on the parallel triangular-lattice layers within the ab-plane and stacked in an 'AA'-type fashion along the c-axis. The low-temperature magnetic characterizations indicate that all synthesized Ba6RE2Ti4O17 compounds exhibit dominant antiferromagnetic (AFM) interactions and the absence of magnetic order down to 1.8 K. The isothermal magnetization and electron spin resonance results reveal the distinct magnetic anisotropy for the compounds with different RE ions. Moreover, the as-grown Ba6Nd2Ti4O17 single crystals exhibit Ising-like magnetic anisotropy with a magnetic easy-axis perpendicular to the triangle-lattice plane and no long-range magnetic order down to 80 mK, as the quantum spin liquid candidate with dominant Ising-type interactions.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach.

Background: The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points. Objective: To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach. Methods: We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results: We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Conclusions: Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

Unraveling the intercellular communication disruption and key pathways in Alzheimer's disease: an integrative study of single-nucleus transcriptomes and genetic association.

BACKGROUND: Recently, single-nucleus RNA-seq (snRNA-seq) analyses have revealed important cellular and functional features of Alzheimer's disease (AD), a prevalent neurodegenerative disease. However, our knowledge regarding intercellular communication mediated by dysregulated ligand-receptor (LR) interactions remains very limited in AD brains. METHODS: We systematically assessed the intercellular communication networks by using a discovery snRNA-seq dataset comprising 69,499 nuclei from 48 human postmortem prefrontal cortex (PFC) samples. We replicated the findings using an independent snRNA-seq dataset of 56,440 nuclei from 18 PFC samples. By integrating genetic signals from AD genome-wide association studies (GWAS) summary statistics and whole genome sequencing (WGS) data, we prioritized AD-associated Gene Ontology (GO) terms containing dysregulated LR interactions. We further explored drug repurposing for the prioritized LR pairs using the Therapeutic Targets Database. RESULTS: We identified 190 dysregulated LR interactions across six major cell types in AD PFC, of which 107 pairs were replicated. Among the replicated LR signals, we found globally downregulated communications in the astrocytes-to-neurons signaling axis, characterized, for instance, by the downregulation of APOE-related and Calmodulin (CALM)-related LR interactions and their potential regulatory connections to target genes. Pathway analyses revealed 44 GO terms significantly linked to AD, highlighting Biological Processes such as 'amyloid precursor protein processing' and 'ion transmembrane transport,' among others. We prioritized several drug repurposing candidates, such as cromoglicate, targeting the identified dysregulated LR pairs. CONCLUSIONS: Our integrative analysis identified key dysregulated LR interactions in a cell type-specific manner and the associated GO terms in AD, offering novel insights into potential therapeutic targets involved in disrupted cell-cell communication in AD.

Unraveling the intercellular communication disruption and key pathways in Alzheimer's disease: An integrative study of single-nucleus transcriptomes and genetic association.

Background: Recently, single-nucleus RNA-seq (snRNA-seq) analyses have revealed important cellular and functional features of Alzheimer's disease (AD), a prevalent neurodegenerative disease. However, our knowledge regarding intercellular communication mediated by dysregulated ligand-receptor (LR) interactions remains very limited in AD brains. Methods: We systematically assessed the intercellular communication networks by using a discovery snRNA-seq dataset comprising 69,499 nuclei from 48 human postmortem prefrontal cortex (PFC) samples. We replicated the findings using an independent snRNA-seq dataset of 56,440 nuclei from 18 PFC samples. By integrating genetic signals from AD genome-wide association studies (GWAS) summary statistics and whole genome sequencing (WGS) data, we prioritized AD-associated Gene Ontology (GO) terms containing dysregulated LR interactions. We further explored drug repurposing for the prioritized LR pairs using the Therapeutic Targets Database. Results: We identified 316 dysregulated LR interactions across six major cell types in AD PFC, of which 210 pairs were replicated. Among the replicated LR signals, we found globally downregulated communications in astrocytes-to-neurons signaling axis, characterized, for instance, by the downregulation of APOE-related and Calmodulin (CALM)-related LR interactions and their potential regulatory connections to target genes. Pathway analyses revealed 60 GO terms significantly linked to AD, highlighting Biological Processes such as 'amyloid precursor protein processing' and 'ion transmembrane transport', among others. We prioritized several drug repurposing candidates, such as cromoglicate, targeting the identified dysregulated LR pairs. Conclusions: Our integrative analysis identified key dysregulated LR interactions in a cell type-specific manner and the associated GO terms in AD, offering novel insights into potential therapeutic targets involved in disrupted cell-cell communication in AD.

Genetic manipulation of Patescibacteria provides mechanistic insights into microbial dark matter and the epibiotic lifestyle.

Patescibacteria, also known as the candidate phyla radiation (CPR), are a diverse group of bacteria that constitute a disproportionately large fraction of microbial dark matter. Its few cultivated members, belonging mostly to Saccharibacteria, grow as epibionts on host Actinobacteria. Due to a lack of suitable tools, the genetic basis of this lifestyle and other unique features of Patescibacteira remain unexplored. Here, we show that Saccharibacteria exhibit natural competence, and we exploit this property for their genetic manipulation. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth, and a transposon-insertion sequencing (Tn-seq) genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii, as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.

Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach.

Background: The progressive cognitive decline that is an integral component of AD unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and Alzheimer's disease between different chronological points. Methods: We developed a deep-learning framework based on dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results: We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G>T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neuron and plays a role in controlling cell growth and differentiation. In addition, MUC7 and PROL1/OPRPNon chromosome 4 were significant at the gene level. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Furthermore, we found that the cognitive decline slope GWAS was positively correlated with previous AD GWAS. Conclusion: Our deep learning model was demonstrated effective on extracting relevant neuroimaging features and predicting individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene. Our approach has the potential to disentangle accelerated cognitive decline from the normal aging process and to determine its related genetic factors, leveraging opportunities for early intervention.

Ba9RE2(SiO4)6 (RE = Ho-Yb): A Family of Rare-Earth-Based Honeycomb-Lattice Magnets.

Rare-earth (RE)-based honeycomb-lattice materials with strong spin-orbit coupled Jeff = 1/2 moments have attracted great interest as a platform to realize the Kitaev quantum spin liquid (QSL) state. Herein, we report the discovery of a family of RE-based honeycomb-lattice magnets Ba9RE2(SiO4)6 (RE = Ho-Yb), which crystallize into the rhombohedral structure with the space group R3̅. In these serial compounds, magnetic RE3+ ions are arranged on a perfect honeycomb lattice within the ab-plane and stacked in the "ABCABC"-type fashion along the c-axis. All synthesized Ba9RE2(SiO4)6 (RE = Ho-Yb) polycrystals exhibit the dominant antiferromagnetic interaction and absence of magnetic order down to 2 K. In combination with the magnetization and electron spin resonance results, magnetic behaviors are discussed for the compounds with different RE ions. Moreover, the as-grown Ba9Yb2(SiO4)6 single crystals show large magnetic frustration with frustration index f = θCW/TN > 8 and no long-range magnetic ordering down to 0.15 K, being a possible QSL candidate material. These series of compounds are attractive for exploring the exotic magnetic phases of Kitaev materials with 4f electrons.

Genetically-regulated pathway-polygenic risk score (GRPa-PRS): A risk stratification method to identify genetically regulated pathways in polygenic diseases.

Background: Alzheimer's disease (AD) is a common neurodegenerative disease in the elderly population, with genetic factors playing an important role. A considerable proportion of elderly people carry a high genetic AD risk but evade AD. On the other hand, some individuals with a low risk for AD eventually develop AD. We hypothesized that unknown counterfactors might be involved in reversing the polygenic risk scores (PRS) prediction, which might provide insights into AD pathogenesis, prevention, and early clinical intervention. Methods: We built a novel computational framework to identify genetically-regulated pathways (GRPa) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery and the replication dataset include 2722 and 2492 individuals, respectively. First, we calculated the optimized PRS model based on the three latest AD GWAS summary statistics for each cohort. Then, we sub-grouped the individuals by their PRS and clinical diagnosis into groups such as cognitively normal (CN) with high PRS for AD (resilient group), AD cases with low PRS (susceptible group), and AD/CNs participants with similar PRS backgrounds. Lastly, we imputed the individual genetically-regulated expression (GReX) and identified the differential GRPas between subgroups with gene-set enrichment analysis and gene-set variational analysis in 2 models with and without the effect of APOE. Results: For each subgroup, we conducted the same procedures in both the discovery and replication datasets across three PRS models for comparison. In Model 1 with the APOE region, we identified well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocytes response to oxidative stress. In Model 2 without the APOE region, synapse function, microglia function, histidine metabolism, and thiolester hydrolase activity were significant, suggesting that they are pathways independent of the effect of APOE. Finally, our GRPa-PRS method reduces the false discovery rate in detecting differential pathways compared to another variants-based pathway PRS method. Conclusions: We developed a framework, GRPa-PRS, to systematically explore the differential GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those groups unveiled new insights into the pathways associated with AD risk and resilience. Our framework can be extended to other polygenic complex diseases.

Genetic manipulation of candidate phyla radiation bacteria provides functional insights into microbial dark matter.

The study of bacteria has yielded fundamental insights into cellular biology and physiology, biotechnological advances and many therapeutics. Yet due to a lack of suitable tools, the significant portion of bacterial diversity held within the candidate phyla radiation (CPR) remains inaccessible to such pursuits. Here we show that CPR bacteria belonging to the phylum Saccharibacteria exhibit natural competence. We exploit this property to develop methods for their genetic manipulation, including the insertion of heterologous sequences and the construction of targeted gene deletions. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth and a transposon insertion sequencing genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their Actinobacteria hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii , as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.

Efficient degradation of 2,4-dichlorophenol in water by sequential electrocatalytic reduction and oxidation with a Pd-MWCNTs/Ni-foam electrode.

Our previous study indicated excellent dechlorination efficiency and phenol conversion rate in the electrocatalytic reduction of 2,4-dichlorophenol (2,4-DCP) with a Pd-MWCNTs/Ni-foam electrode; it is deserved to investigate whether this electrode can efficiently degrade phenol in electro-Fenton oxidation (EFO) process and realize the effective mineralization of 2,4-DCP in aqueous solution. In this work, the sequential electrocatalytic reduction and oxidation of 2,4-DCP were studied after examining phenol degradation in the EFO process. The results showed that the removal efficiency of 0.31 mM phenol could reach 96.76% after 90-min degradation with the rate constant of 0.0367 min-1, and hydroxy radicals (·OH) were the main active species in the EFO process. In the sequential electrocatalytic reduction and oxidation processes, the removal efficiencies of 2,4-DCP, phenol, and total organic carbon (TOC) reached 99.72%, 97.07%, and 61.45%, respectively. The possible degradation mechanism of 2,4-DCP was proposed through monitoring the reaction products, and the stability and reusability of the electrode were also examined. This study suggested that 2,4-DCP in wastewater can be effectively mineralized to realize its efficient degradation through the sequential electrocatalytic reduction and oxidation.

Interactions and quantification of multiple influencing factors on cadmium accumulation in soil-rice systems at a large region.

The accumulation of Cd in soil-rice systems at a large region is often extremely complicated due to environmental heterogeneity and the interactions of multiple influencing factors. However, the interactive effects and quantification of the contributions of influencing factors on Cd accumulation in large regions remain unclear. In this study, conditional inference trees and random forest analysis were used to identify the interactions of various factors (soil properties, topography and demographic-economic), and quantify their contributions to Cd accumulation in soil-rice systems of Sichuan-Chongqing region, China. The results showed that Cd content in the soil was the most significant influencing factor on Cd accumulation in soil-rice systems, especially bioavailable Cd in soil contributed to 35.73 % and 54.78 % for soil total Cd (Cdsoil) and brown rice Cd (Cdrice), respectively. Population density (PD) and elevation contributed 31.16 % and 27.40 % to Cdsoil content, respectively, and their interaction promoted the increase in Cdsoil content. Moreover, PD played a leading role in Cdsoil content when the elevation exceeded 324 m. The relative importances of slope and elevation for Cdrice content were 16.81 % and 8.49 %, respectively, and their interaction facilitated the increment of Cdrice content. As soil pH, gross domestic product (GDP) and slope decreased, the interaction of soil pH with GDP led to the increase of bioavailability factor (BAF), and that with slope enhanced the bioaccumulation factor (BCF). In addition, soil pH, PD and elevation were of considerable importance for the migration and transformation of Cd, with contributions of 22.11 %, 12.90 % and 12.52 % to BAF, and 5.05 %, 5.62 % and 5.50 % to BCF, respectively. This study is hopeful to provide a scientific insight into the prevention and control of Cd contamination in soil-rice systems at a large region.

Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments.

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein-protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 drugs. Immune cell membrane receptors, the downstream cellular signaling cascade, and severe COVID-19 symptom risk were significantly enriched for the core subnetwork genes. The lung mast cell was most enriched for the target genes among 1355 human tissue-cell types. Human bronchoalveolar lavage fluid COVID-19 single-cell RNA-Seq data highlighted the fact that T cells and macrophages have the most overlapping genes from the core subnetwork. Overall, we constructed an actionable human target-protein module that mainly involved anti-inflammatory/antiviral entry functions and highly overlapped with COVID-19-severity-related genes. Our findings could serve as a knowledge base for guiding drug discovery or drug repurposing to confront the fast-evolving SARS-CoV-2 virus and other severe infectious diseases.

A Visible-Light-Promoted C-H Arylation and Heteroarylation of Uracil Derivatives with Diazoniums in Aqueous Conditions.

The photoredox synthesis of C-5 (hetero)arylated uracil and uridine substrates with the corresponding diazonium salts is described. The coupling proceeds efficiently without protection of the hydroxyls at the ribose or pre-functionalization of the C5 position at the nucleobase. No transition-metal catalyst is used in this transformation, thereby avoiding metal contamination in the final products. The use of water as the medium also eliminates the impurities caused by the use of organic solvents. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Synthesis of 5-aryl and 5-heteroaryl uracil derivatives Basic Protocol 2: Synthesis of 5-aryl uridine and deoxyuridine uridine derivatives.

Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.

BACKGROUND: Multiple sclerosis (MS) is a debilitating immune-mediated disease of the central nervous system that affects over 2 million people worldwide, resulting in a heavy burden to families and entire communities. Understanding the genetic basis underlying MS could help decipher the pathogenesis and shed light on MS treatment. We refined a recently developed Bayesian framework, Integrative Risk Gene Selector (iRIGS), to prioritize risk genes associated with MS by integrating the summary statistics from the largest GWAS to date (n = 115,803), various genomic features, and gene-gene closeness. RESULTS: We identified 163 MS-associated prioritized risk genes (MS-PRGenes) through the Bayesian framework. We replicated 35 MS-PRGenes through two-sample Mendelian randomization (2SMR) approach by integrating data from GWAS and Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) of 19 tissues. We demonstrated that MS-PRGenes had more substantial deleterious effects and disease risk. Moreover, single-cell enrichment analysis indicated MS-PRGenes were more enriched in activated macrophages and microglia macrophages than non-activated ones in control samples. Biological and drug enrichment analyses highlighted inflammatory signaling pathways. CONCLUSIONS: In summary, we predicted and validated a high-confidence MS risk gene set from diverse genomic, epigenomic, eQTL, single-cell, and drug data. The MS-PRGenes could further serve as a benchmark of MS GWAS risk genes for future validation or genetic studies.

WebCSEA: web-based cell-type-specific enrichment analysis of genes.

Human complex traits and common diseases show tissue- and cell-type- specificity. Recently, single-cell RNA sequencing (scRNA-seq) technology has successfully depicted cellular heterogeneity in human tissue, providing an unprecedented opportunity to understand the context-specific expression of complex trait-associated genes in human tissue-cell types (TCs). Here, we present the first web-based application to quickly assess the cell-type-specificity of genes, named Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA, available at https://bioinfo.uth.edu/webcsea/). Specifically, we curated a total of 111 scRNA-seq panels of human tissues and 1,355 TCs from 61 different general tissues across 11 human organ systems. We adapted our previous decoding tissue-specificity (deTS) algorithm to measure the enrichment for each tissue-cell type (TC). To overcome the potential bias from the number of signature genes between different TCs, we further developed a permutation-based method that accurately estimates the TC-specificity of a given inquiry gene list. WebCSEA also provides an interactive heatmap that displays the cell-type specificity across 1355 human TCs, and other interactive and static visualizations of cell-type specificity by human organ system, developmental stage, and top-ranked tissues and cell types. In short, WebCSEA is a one-click application that provides a comprehensive exploration of the TC-specificity of genes among human major TC map.

Identifying candidate genes and drug targets for Alzheimer's disease by an integrative network approach using genetic and brain region-specific proteomic data.

Genome-wide association studies (GWAS) have identified more than 75 genetic variants associated with Alzheimer's disease (ad). However, how these variants function and impact protein expression in brain regions remain elusive. Large-scale proteomic datasets of ad postmortem brain tissues have become available recently. In this study, we used these datasets to investigate brain region-specific molecular pathways underlying ad pathogenesis and explore their potential drug targets. We applied our new network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS), to integrate ad GWAS statistics of 472 868 individuals with proteomic profiles from two brain regions from two large-scale ad cohorts [parahippocampal gyrus (PHG), sample size n = 190; dorsolateral prefrontal cortex (DLPFC), n = 192]. The resulting network modules were evaluated using a scale-free network index, followed by a cross-region consistency evaluation. Our EW_dmGWAS analyses prioritized 52 top module genes (TMGs) specific in PHG and 58 TMGs in DLPFC, of which four genes (CLU, PICALM, PRRC2A and NDUFS3) overlapped. Those four genes were significantly associated with ad (GWAS gene-level false discovery rate < 0.05). To explore the impact of these genetic components on TMGs, we further examined their differentially co-expressed genes at the proteomic level and compared them with investigational drug targets. We pinpointed three potential drug target genes, APP, SNCA and VCAM1, specifically in PHG. Gene set enrichment analyses of TMGs in PHG and DLPFC revealed region-specific biological processes, tissue-cell type signatures and enriched drug signatures, suggesting potential region-specific drug repurposing targets for ad.

Aqueous and Visible-Light-Promoted C-H (Hetero)arylation of Uracil Derivatives with Diazoniums.

Direct C5 (hetero)arylation of uracil and uridine substrates with (hetero)aryl diazonium salts under photoredox catalysis with blue light was reported. The coupling proceeds efficiently with diazonium salts and heterocycles in good functional group tolerance at room temperature in aqueous solution without transition-metal components. A plausible radical mechanism has been proposed.

[Cd Pollution and Safe Planting Zoning in Paddy Soils: A Case Study in a District of Chongqing].

Rice has a strong ability to accumulate Cd in soil, and it is of great significance to study Cd pollution and safe planting zoning in paddy soils. In this work, 300 sets of paddy soil-rice samples were simultaneously collected in 22 towns in a District of Chongqing, and soil pH, soil total and available Cd contents, and brown rice Cd contents were determined. Soil Cd pollution was assessed using the geoaccumulation index, bioconcentration factor, and the single-factor pollution index. Based on the Cd pollution indices of soil and brown rice, safe planting zoning for rice was determined. The results showed that the paddy soils were generally acidic, and total Cd contents ranged from 0.09 mg·kg-1 to 1.60 mg·kg-1, with 35.0% of sites exceeding the risk screening value. The Cd contents of the brown rice ranged from 0.002 mg·kg-1 to 0.808 mg·kg-1 and exceeded the food safety limit in 13.7% of cases. Pearson correlation analysis showed that the Cd content of brown rice was significantly positively correlated with soil total and available Cd (P<0.01). The pollution evaluation indicated that significant Cd accumulation occurred in the paddy soils, with some areas showing light-to-moderate pollution levels. The enrichment coefficients of rice to soil Cd ranged from 0.004 to 1.72. Overall, the paddy soils in the studied area were considered generally safe with respect to Cd pollution, with low-risk areas distributed in the south, west, and east, whereas some medium-high risk areas were detected in eight towns.