Enrichment Tests Research Articles

Edukasi Pajak Kaum Millenial Berbasis Web Games

WEB GAMES-BASED MİLLENNİAL TAX EDUCATİON. This Community Service Activity (PkM) aims to provide solutions for the Subject Teachers' Conference (MGMP) on: 1). declining interest in learning for high school students during the pandemic; 2). lack of attractive tax teaching support facilities and infrastructure at the high school level; 3). lack of knowledge and skills of teachers in technology-based learning, especially taxation subjects. In addition, to support partner programs as well as the government's national program in creating a tax-aware golden generation in 2045, the PkM team utilizes research on tax assistance activities, tax education, and the use of tax technology that has been done previously by: (1) formulating two types of easy games and already known by students, namely Snakes & Ladders and Tax Uno Cards, have become web-based games to make them more attractive; (2) direct introduction of the two web games to accounting teachers and develop input from teachers, in order to improve the program including facilities and infrastructure; (3) direct socialization to students in a series of Web games for the Tax Awareness Gold Generation which were made interactive, competitive and interesting. The results show an increase in the learning interest of 100 students involved, obtaining support for facilities and infrastructure, and increasing teacher knowledge and skills in technology-based learning in taxation subjects by more than 70%. Participants feel that web games-based tax learning is more fun as enrichment material and test preparation activities are more fun and more competitive than the usual practice questions.

Extraction of gold from low-sulfide gold-bearing ores by beneficiating method using a pressure generator for pulp microaeration

Research results on the study of the material composition of low-sulfide gold-bearing ore from the East Kazakhstan deposit are presented. The main non-metallic minerals of the original sample and beneficiation products include quartz, chlorite (clinochlore), carbonates (calcite and dolomite). Pyrite is present predominantly in the form of cubic crystals, sometimes in the form of clusters. The grain size is from 0.03 to 0.40.5 mm, the size of the clusters reaches several mm. Iron oxides (goethite, hydrogoethite) were formed on pyrite, possibly magnetite and ilmenite. The assay test found that the test sample contains 6.04 g/t Au and 7.9 g/t Ag. The content of sulfide minerals is 11.81%. A significant part of gold (85.51%) is in a finely disseminated state in sulfides, as well as in rock-forming minerals 1.22%. The paper presents the results of laboratory studies of the gold- ore beneficiation ability using gravity concentration processes. Gravity enrichment tests were performed on laboratory equipment: Knelson KS-MD 3 centrifugal concentrator, SKO-05 concentration table, and a two-chamber diaphragm jig (OML TsNIGRI type (jig of Central Geological Research Institute for Nonferrous and Precious Metals)). The obtained results of ore beneficiation on the concentration table show the possibility of obtaining a gravity concentrate with a gold grade of 48.9 g/t with a gold recovery of 40.08%. When separating the gravity concentrate on a jig, the gold extraction was 31.6% at a content of 51.4 g/t. It was found that that according to a single-stage beneficiation scheme in a centrifugal concentrator, a gold-bearing concentrate with a gold content of 58.3 g/t was obtained with a recovery of 80.6%. The dependence of the gold extraction and its content in the gravity concentrate on the output at the Knelson centrifugal concentrator is shown. The results of ore flotation beneficiation show the possibility of obtaining waste grade flotation tailings with a gold grade of 0.8 g/t. The extraction of gold into the combined concentrate, with a gold content of 49.7 g/t, is 88.88%.

303 The role of rare variants in male-pattern hair loss: Analysis of whole exome sequencing data in the UK Biobank

Male-pattern hair loss (MPHL) is a highly heritable and prevalent form of hair loss. While genome-wide association studies (GWAS) have provided insights into the contribution of common genetic variants to MPHL etiology, the relevance of rare variants is unclear. In this study, we tested for a contribution of rare coding variants to MPHL etiology based on exome data of 72,469 men from the UK Biobank. We performed SKAT-O and GenRisk gene-based association analyses as well as single-variant tests, followed by interpretation, risk prediction modelling and enrichment testing.

Current Testing Practices for t(11;14) Rearrangements in Patients with Newly Diagnosed Multiple Myeloma in the United States

Background: Despite an improvement in the awareness and use of precision medicine and molecular testing in hematological cancers, there are still significant disparities in biomarker testing. This ultimately leads to inequality in molecular testing access and can lead to suboptimal medical care for some patients, who do not receive the most appropriate and effective therapy. Venetoclax is a selective BCL-2 inhibitor and has shown promising antimyeloma activity in patients with t(11;14) multiple myeloma (MM). t(11;14) is the most frequent chromosomal translocation in MM reported in approximately 15-20% of newly diagnosed MM patients (NDMM) (Kumar et al. Blood 2017). In this study, we assessed current t(11;14)(q13;q32) testing practices in patients with NDMM in the United States (US) to gain insights on challenges for biomarker testing and equitable access to precision medicine. Methods: A retrospective, real-world evidence study was conducted between January and December 2021 using the Diaceutics DXRX Data Repository database. DXRX is a patient-level claims- and laboratory-linked dataset covering more than 4000 laboratories and 360 million patient lives between 2011 and 2022 in the US. Eligible patients were identified using International Classification of Disease (ICD) codes for NDMM (ICD-10 code C90.0). A 2-year lookback was utilized to ensure patients were not in remission or relapse (ICD-10 codes C90.01, C90.02). Percentages were used to describe study population characteristics. t(11;14) and plasma cell enrichment (PCE) testing rates were estimated using descriptive statistics for the entire cohort as well as for race/ethnicity subgroups. PCE testing was considered as it contributes to increasing sensitivity of testing. Results: We identified 27,586 eligible patients with NDMM. The median age at diagnosis was 70 years (interquartile range: 65-75) and 45% were female. Among the eligible patients, 69% (n=19,034) specifically received t(11;14) testing, within 1 month from diagnosis to testing. Fluorescence in situ hybridization (FISH; dual color, dual fusion probe and immunoglobin [IG] break apart) was the most commonly utilized technology (89%; n=16,940) for detecting t(11;14); next-generation sequencing panels were limited (<1%) in utilization. Confirmatory reflex testing with a t(11;14) dual probe following positive IG break apart was not performed in 17% (n=3235) of patients. In patients who were tested with the t(11;14) dual probe FISH assay, less than half (40.9%) were tested for t(11;14) with PCE. Results of the FISH assay were available for 4941 patients. A lower positivity rate was observed with non-PCE testing (13.1%; n=647) compared with those utilizing PCE (16.8%; n=830), p=0.494. Testing rates of t(11;14) in an academic setting were 72% (n=10,659) vs 64% (n=8374) in the community setting, p<0.0001. PCE was performed on only 24.9% (n=2093) of patients in a community setting vs 61% (n=6502) of samples in an academic setting, p<0.0001. For the subgroup analysis, race/ethnicity data were available for 9245 patients with NDMM; 75.7% were White, 15.9% were Black, 2.6% were Asian, 2% were Hispanic, and 3.2% were classified as other. t(11;14) testing rates were higher for patients who were White (72.8%) compared with the minority groups (66.9% for patients who were Black, 68.8% for patients who were Asian, and 65.7% for patients who were Hispanic). The t(11;14) testing setting for minority group patients was community (62%) vs academic (38%). Conclusions: Notable variations in t(11;14) testing patterns were observed among patients with NDMM in different care settings and racial/ethnic groups. There is a clear unmet need for standardization across academic and community settings to mitigate suboptimal testing methodologies that could impact treatment decision-making and patient outcomes. From our study, there is a clear need to improve t(11;14) testing rates as the clinical utility changes from a prognostic to predictive biomarker with the availability of personalized healthcare options. Education of PCE utilization for physicians, especially community-based pathologists and laboratories, will be essential to reduce false negatives and inequalities in optimal testing, especially PCE in ethnic minorities in the US.

Capsular inflammation after immediate breast reconstruction – Gene expression patterns and inflammatory cell infiltration in irradiated and non-irradiated breasts

Capsular contracture following post-mastectomy radiotherapy (PMRT) is commonly seen in patients undergoing implant-based immediate breast reconstruction (IBR). Further understanding of the underlying biology is needed for the development of preventive or therapeutic strategies. Therefore, we conducted a comparative study of gene expression patterns in capsular tissue from breast cancer patients who had received versus those who had not received PMRT after implant-based IBR. Biopsies from irradiated and healthy non-irradiated capsular tissue were harvested during implant exchange following IBR. Biopsies from irradiated (n=13) and non-irradiated (n=12) capsules were compared using Affymetrix microarrays to identify the most differentially regulated genes. Further analysis using immunohistochemistry was performed in a subset of materials to compare the presence of T cells, B cells, and macrophages. Enrichment testing using Gene Ontology (GO) analysis revealed that the 227 most differentially expressed genes were mainly involved in an inflammatory response. Twenty-one GO biological processes were identified [p < 0.05, false discovery rate (FDR) < 5%], several with B-cell-associated inflammation. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) analysis identified macrophages as the most common inflammatory cell type in both groups, further supported by immunostaining of CD68. Radiation remarkably increased B-cell infiltration in the capsular region of biopsies, as quantified by immunostaining of CD20 (p=0.016). Transcript analysis and immunohistochemistry revealed inflammatory responses in capsular biopsies regardless of radiotherapy. However, the radiation response specifically involved B-cell-associated inflammatory responses.

Fusion Separation of Vanadium-Titanium Magnetite and Enrichment Test of Ti Element in Slag.

In view of the problem that the enrichment and migration law of the Ti element in the slag of vanadium-titanium magnetite during the melting process is not clear, the phase transformation is not clear and the enrichment effect is not obvious, the single factor experiment and orthogonal experiment are used to optimize the melting conditions of Ti enrichment. Through XRD, SEM and EDS analysis, the effects of melting temperature, alkalinity and carbon content on the Ti phase in the slag are studied, and the occurrence form and migration law of the Ti element in the slag system under different melting conditions are clarified. The results demonstrate that increasing the basicity and melting temperature is beneficial to the enrichment of Ti, but it is too high it will lead to the formation of pyroxene, diopside and magnesia-alumina spinel, affecting the enrichment of Ti. The increase in carbon content can make Ti occur in slag in the form of titanium oxides such as TiO, TiO2, Ti2O3 and Ti3O5, but excessive carbon content leads to the excessive reduction of Ti compounds to TiCN and TiC. After optimization, under the melting conditions of alkalinity 1.2, the melting temperature 1500 °C and carbon content 15%, the content of Ti in slag can reach 18.84%, and the recovery rate is 93.54%. By detecting the content of Fe and V in molten iron, the recovery rates are 99.86% and 95.64%, respectively.

Air pollution, metabolomic response, and bone mineral density among Women’s Health Initiative participants

BACKGROUND: Ambient air pollution has been associated with bone damage. However, no studies have evaluated the metabolomic changes linked to air pollutants and their potential influence on bone damage in postmenopausal women. METHODS: We analyzed data available among Woman’s Health Initiative (WHI) participants. We used log-normal, ordinary kriging to estimate daily mean concentrations of PM10 (&amp;#x3bc;g/m3) and NOx, NO2, and SO2 (ppm) at their geocoded addresses. We averaged the means over 1-, 3-, and 5-year periods before metabolomic assessments. We measured whole-body, total hip, femoral neck, and spine bone mineral density (BMD) via dual-energy X-ray absorptiometry. We processed 2,129 plasma samples using liquid chromatography-tandem mass spectrometry (LC-MS) to estimate the concentration of approximately 500 metabolites. We used multivariable linear models adjusted for age, body mass index, ethnicity, education, and coronary heart disease to identify metabolome-wide significant cross-sectional associations between air pollutants, metabolites, and BMD at an FDR-corrected threshold of 0.05. We then used a hypergeometric enrichment test hosted on Metaboanalyst to conduct pathway analysis with the KEGG metabolic map as reference. RESULTS: The mean (standard deviation) age of participants was 67.0 (7.1) years. Air pollutants were associated with several metabolite concentrations. For example, 1-year mean NOx exposure was associated with 104 metabolites after adjusting for multiple comparisons, including homoarginine, sphingosine-1-phosphate, uridine diphosphate glucose (UDP), UDP-galactose, alpha-glycerophosphate, kynurenine, cytidine monophosphate, malonylcarnitine, docosatrienoic acid, carboxybuprofen, and others. These NOx-associated metabolites enriched the arachidonic acid, purine, glycerophospholipid, and arginine metabolic pathways. Likewise, 17 metabolites were significantly associated with BMD, particularly total hip and whole body. Homoarginine was associated with both NOx and BMD. CONCLUSIONS: This initial study of air pollutant-associated metabolites and bone mineral density in the Women’s Health Initiative highlights potential metabolomic mechanisms by which air pollution may negatively affect bone health among postmenopausal women. KEYWORDS: Air pollution, Metabolomics, BMD, Postmenopausal, Women.

Systematic assessment of pathway databases, based on a diverse collection of user-submitted experiments.

A knowledge-based grouping of genes into pathways or functional units is essential for describing and understanding cellular complexity. However, it is not always clear a priori how and at what level of specificity functionally interconnected genes should be partitioned into pathways, for a given application. Here, we assess and compare nine existing and two conceptually novel functional classification systems, with respect to their discovery power and generality in gene set enrichment testing. We base our assessment on a collection of nearly 2000 functional genomics datasets provided by users of the STRING database. With these real-life and diverse queries, we assess which systems typically provide the most specific and complete enrichment results. We find many structural and performance differences between classification systems. Overall, the well-established, hierarchically organized pathway annotation systems yield the best enrichment performance, despite covering substantial parts of the human genome in general terms only. On the other hand, the more recent unsupervised annotation systems perform strongest in understudied areas and organisms, and in detecting more specific pathways, albeit with less informative labels.

MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data

The discovery of cancer subtypes based on unsupervised clustering helps in providing a precise diagnosis, guide treatment, and improve patients’ prognoses. Instead of single-omics data, multi-omics data can improve the clustering performance because it obtains a comprehensive landscape for understanding biological systems and mechanisms. However, heterogeneous data from multiple sources raises high complexity and different kinds of noise, which are detrimental to the extraction of clustering information. We propose an end-to-end deep learning based method, called Multi-omics Clustering Variational Autoencoders (MCluster-VAEs), that can extract cluster-friendly representations on multi-omics data. First, a unified network architecture with an attention mechanism was developed for accurately modeling multi-omics data. Then, using a novel objective function built from the Variational Bayes technique, the model was trained to effectively obtain the posterior estimation of the clustering assignments. Compared with 12 other state-of-the-art multi-omics clustering methods, MCluster-VAEs achieved an outstanding performance on benchmark datasets from the TCGA database. On the Pan Cancer dataset, MCluster-VAEs achieved an adjusted Rand index of approximately 0.78 for cancer category recognition, an increase of more than 18% compared with other methods. Furthermore, a survival analysis and clinical parameter enrichment tests conducted on 10 cancer datasets demonstrated that MCluster-VAEs provides comparable and even better results than many common integrative approaches. These results demonstrate that MCluster-VAEs are a powerful new tool for dissecting complex multi-omics relationships and providing new insights for cancer subtype discovery.

Comparative Transcriptome Analysis Reveals the Mechanisms Underlying Differential Seed Vigor in Two Contrasting Peanut Genotypes

Seed vigor is an important agronomic trait, and wide variation exists among peanut accessions. However, the detailed regulatory mechanisms underlying differences in seed vigor between varieties are not known in peanut yet. Here, we performed a comparative transcriptome analysis of germinating seeds in two contrasting peanut accessions, namely A86 (high-vigor variety) and A279 (low-vigor variety). A total of 583 and 860 differentially expressed genes (DEGs) were identified at two imbibition stages between A86 and A279, respectively. Pathway enrichment tests highlighted the cell wall remodeling-, hormone signaling-, transcriptional regulation-, and oxidative stress-related DEGs, which may explain to a certain extent the difference in seed vigor between the two cultivars. Among them, the largest number of cell wall remodeling-related DEGs were extensions followed by cellulose synthases, fasciclin-like arabinogalactan proteins, polygalacturonases, expansins, and pectinesterases and the hormone signaling-related DEGs belonged mainly to the auxin and ethylene signaling pathway. The majority of transcriptional regulation-related DEGs were MYB, FAR1, and bHLH transcription factors, and the oxidative stress-related DEGs were mainly peroxidases. Further physiological analyses indicated that differences in seed vigor between A86 and A279 may be associated with differences in the ROS-scavenging abilities mediated by peroxidases. Moreover, we identified 16 DEGs homologous to known Arabidopsis regulators of seed dormancy and germination, suggesting that these DEGs would play similar functional roles during peanut seed germination. Our results not only provide important insights into the difference in seed vigor between varieties, but offer candidate genes that are worth investigating in future studies.

Detection of Salmonella spp. by Traditional and PCR Assays in Raw Milk, Maysan, Iraq.

Salmonella spp are characterized as rod- shaped, motile, gram- negative bacteria which has the ability to infect animals and human. Salmonella spp occasionally causes sickness while in most cases not lead to severe symptoms. Analyzing milk for Salmonella spp. is not routine but traditional culture methods are used to evaluate the health condition of the dairy products. However, the antibody-based and nucleic-acid- based methods are practical for identifying Salmonella spp. Therefore, this research was designed to evaluate the use of traditional culture methods and PCR in detection of the presence of Salmonella spp. in raw milk samples in, Maysan Iraq. A total number of 130 raw milk samples collected from Maysan Iraq. All the samples were analyzed for the presence of Salmonella spp. using traditional culture method and polymerase chain reaction (PCR). The culture method used in this experiment were done by using pre-enrichment, enrichment, selective plating and biochemical tests. The results of this traditional technique were compared with the results obtained from PCR method. The PCR was performed using a 284bp sequence of the invA gene. The results showed that 8 (7.07%) of samples were identified as salmonella positive using traditional culture technique but 14 (12.3%) samples were detected as salmonella positive by PCR method. The results of the current research revealed that the traditional culture based methods are generally time costuming and labor intensive but the development of new rapid methods including DNA based methods such as PCR are more sensitive and have dramatically decreased the time necessary for the detection of bacteria.

Acoustofluidic bubble-driven micromixers for the rational engineering of multifunctional ZnO nanoarray

Acoustofluidics that combines acoustics with microfluidics represents an emerging and promising technology for the efficient mixing of fluids and synthesis of functional nanomaterials. However, it remains a great challenge to the controllable synthesis of three-dimensional functional nanostructures in a confined space. Herein, we introduce a robust acoustofluidic bubble-driven micromixer for the controllable synthesis of functional nanoarray inside the glass capillary toward efficient photodegradation and metal ion enrichment. The acoustofluidic micromixer functions with microbubbles-induced acoustic streaming from arrow-patterned microchannels. The morphology, density, and size of ZnO nanorods and nanosheets array can be precisely adjusted by reactant type, seeding phase, and reaction time. ZnO nanorod array exhibits approximately 90% degradation efficiency of R6G even after ten cycles, which are significantly better than ZnO nanosheet array and blank control groups. Enrichment tests of heavy metal ions show that ZnO nanoarray performs better enrichment performance of Cu2+ than that of Ag+. In addition, both photodegradation and enrichment capabilities can be well regulated by tuning the flow rates (i.e., the residence time). These findings provide important guidelines for the rational design of functional nanomaterials and shed new light on the fabrication of advanced lab-on-a-chip devices.

Refining bulk segregant analyses: ontology-mediated discovery of flowering time genes in Brassica oleracea

BackgroundBulk segregant analysis (BSA) can help identify quantitative trait loci (QTLs), but this may result in substantial bycatch of functionally irrelevant genes.ResultsHere we develop a Gene Ontology-mediated approach to zoom in on specific genes located inside QTLs identified by BSA as implicated in a continuous trait. We apply this to a novel experimental system: flowering time in the giant woody Jersey kale, which we phenotyped in four bulks of flowering onset. Our inferred QTLs yielded tens of thousands of candidate genes. We reduced this by two orders of magnitude by focusing on genes annotated with terms contained within relevant subgraphs of the Gene Ontology. A pathway enrichment test then led to the circadian rhythm pathway. The genes that enriched this pathway are attested from previous research as regulating flowering time. Within that pathway, the genes CCA1, FT, and TSF were identified as having functionally significant variation compared to Arabidopsis. We validated and confirmed our ontology-mediated results through genome sequencing and homology-based SNP analysis. However, our ontology-mediated approach produced additional genes of putative importance, showing that the approach aids in exploration and discovery.ConclusionsOur method is potentially applicable to the study of other complex traits and we therefore make our workflows available as open-source code and a reusable Docker container.

KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

As an alternative to one drug-one target approaches, systems biology methods can provide a deeper insight into the holistic effects of drugs. Network-based approaches are tools of systems biology, that can represent valuable methods for visualizing and analysing drug-protein and protein–protein interactions. In this study, a KNIME workflow is presented which connects drugs to causal target proteins and target proteins to their causal protein interactors. With the collected data, networks can be constructed for visualizing and interpreting the connections. The last part of the workflow provides a topological enrichment test for identifying relevant pathways and processes connected to the submitted data. The workflow is based on openly available databases and their web services. As a case study, compounds of DILIRank were analysed. DILIRank is the benchmark dataset for Drug-Induced Liver Injury by the FDA, where compounds are categorized by their likeliness of causing DILI. The study includes the drugs that are most likely to cause DILI (“mostDILI”) and the ones that are not likely to cause DILI (“noDILI”). After selecting the compounds of interest, down- and upregulated proteins connected to the mostDILI group were identified; furthermore, a liver-specific subset of those was created. The downregulated sub-list had considerably more entries, therefore, network and causal interactome were constructed and topological pathway enrichment analysis was performed with this list. The workflow identified proteins such as Prostaglandin G7H synthase 1 and UDP-glucuronosyltransferase 1A9 as key participants in the potential toxic events disclosing the possible mode of action. The topological network analysis resulted in pathways such as recycling of bile acids and salts and glucuronidation, indicating their involvement in DILI. The KNIME pipeline was built to support target and network-based approaches to analyse any sets of drug data and identify their target proteins, mode of actions and processes they are involved in. The fragments of the pipeline can be used separately or can be combined as required.

EnrichMiR predicts functionally relevant microRNAs based on target collections.

MicroRNAs (miRNAs) are small non-coding RNAs that are among the main post-transcriptional regulators of gene expression. A number of data collections and prediction tools have gathered putative or confirmed targets of these regulators. It is often useful, for discovery and validation, to harness such collections to perform target enrichment analysis in given transcriptional signatures or gene-sets in order to predict involved miRNAs. While several methods have been proposed to this end, a flexible and user-friendly interface for such analyses using various approaches and collections is lacking. enrichMiR (https://ethz-ins.org/enrichMiR/) addresses this gap by enabling users to perform a series of enrichment tests, based on several target collections, to rank miRNAs according to their likely involvement in the control of a given transcriptional signature or gene-set. enrichMiR results can furthermore be visualised through interactive and publication-ready plots. To guide the choice of the appropriate analysis method, we benchmarked various tests across a panel of experiments involving the perturbation of known miRNAs. Finally, we showcase enrichMiR functionalities in a pair of use cases.

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data

BackgroundRevealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1860 human genome-wide distal enhancer-to-target gene definitions (EnTDefs). To evaluate performance, we used gene set enrichment (GSE) testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology annotations, and other benchmarks.ResultsThe top ranked 741 (40%) EnTDefs significantly outperform the common, naïve approach of linking distal regions to the nearest genes, and the top 10 EnTDefs perform well when applied to ChIP-seq data of other cell types. The GSE-based ranking of EnTDefs is highly concordant with ranking based on overlap with curated benchmarks of enhancer-gene interactions. Both our top general EnTDef and cell-type-specific EnTDefs significantly outperform seven independent computational and experiment-based enhancer-gene pair datasets. We show that using our top EnTDefs for GSE with either genome-wide DNA methylation or ATAC-seq data is able to better recapitulate the biological processes changed in gene expression data performed in parallel for the same experiment than our lower-ranked EnTDefs.ConclusionsOur findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.

ANANASTRA: annotation and enrichment analysis of allele-specific transcription factor binding at SNPs.

We present ANANASTRA, https://ananastra.autosome.org, a web server for the identification and annotation of regulatory single-nucleotide polymorphisms (SNPs) with allele-specific binding events. ANANASTRA accepts a list of dbSNP IDs or a VCF file and reports allele-specific binding (ASB) sites of particular transcription factors or in specific cell types, highlighting those with ASBs significantly enriched at SNPs in the query list. ANANASTRA is built on top of a systematic analysis of allelic imbalance in ChIP-Seq experiments and performs the ASB enrichment test against background sets of SNPs found in the same source experiments as ASB sites but not displaying significant allelic imbalance. We illustrate ANANASTRA usage with selected case studies and expect that ANANASTRA will help to conduct the follow-up of GWAS in terms of establishing functional hypotheses and designing experimental verification.

Rapid, Quantitative Nuclear Magnetic Resonance Test for Oxygen-17 Enrichment in Water.

Nuclear magnetic resonance (NMR) studies involving 17O are increasingly important in molecular biology, material science, and other disciplines. A large number of these studies employ H217O as a source of 17O, and this reliance can be limiting because the high cost of H217O. To overcome this constraint, a recent study proposed a distillation scheme capable of producing significant quantities of H217O at a low cost. Although this method is reported to be effective, the reactions proposed to quantify percent of 17O enrichment are either time intensive or have a risk of errors due to the isotope effect. Here, an alternative reaction scheme is described to measure 17O water that ultimately creates methyl benzoate as the sole 17O-containing product. The proposed reaction is completed in a matter of minutes at room temperature, produces only one 17O product, and requires no clean-up step. The large isotope shift observed in solution NMR between the 13C═16O and 13C═17O resonances allows for integration of the individual peaks. This 13C NMR analysis is found to be highly accurate over a wide enrichment range and is accessible to most NMR spectroscopists.

Hydroxyl group-enriched microporous organic network for high-performance solid-phase extraction of triazine herbicides: Experiment and DFT calculation on adsorption behavior

High-efficiency monitoring of triazine herbicides residues is vital in the evaluation of environmental and agro-food safety. Herein, we fabricated a spherical hydroxylated microporous organic network (OH–MON) with high surface area, high stability and rich hydrogen-bonding affinity sites suitable as an advanced solid-phase extraction (SPE) adsorbent for efficient adsorption of triazine herbicides. Density–functional theory calculations and competitive enrichment tests confirmed that hydrogen bonding played a vital role to the enrichment of triazine herbicides by OH–MON. This OH–MON SPE cartridge showed satisfactory reproducibility, maintaining its adsorption capacity after 10 adsorption–desorption cycles. Furthermore, we developed a sensitive analytical approach for determining triazine herbicides residues in water and fruit juice samples. Desirable linear correlations within 0.50–250 ng⋅L-1, an ultra-low detection limit (0.03–0.15 ng⋅L-1 for water; 0.04–0.21 ng⋅L-1 for fruit juice), good precision and high enrichment factor for triazine herbicides were achieved. A preliminary practical application of the developed method was proved by the efficient detection of triazine herbicides in water and fruit samples with good recoveries (72.8%−100.4% and 72.0%−97.7% for water and juice samples, respectively). This study serves as a good reference for designing the high-functionalized MON to capture contaminants and address environmental and agro-food safety issues.

Inflammation and Brain Structure in Schizophrenia and Other Neuropsychiatric Disorders

Previous in vitro and postmortem research suggests that inflammation may lead to structural brain changes via activation of microglia and/or astrocytic dysfunction in a range of neuropsychiatric disorders. To investigate the relationship between inflammation and changes in brain structures in vivo and to explore a transcriptome-driven functional basis with relevance to mental illness. This study used multistage linked analyses, including mendelian randomization (MR), gene expression correlation, and connectivity analyses. A total of 20 688 participants in the UK Biobank, which includes clinical, genomic, and neuroimaging data, and 6 postmortem brains from neurotypical individuals in the Allen Human Brain Atlas (AHBA), including RNA microarray data. Data were extracted in February 2021 and analyzed between March and October 2021. Genetic variants regulating levels and activity of circulating interleukin 1 (IL-1), IL-2, IL-6, C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF) were used as exposures in MR analyses. Brain imaging measures, including gray matter volume (GMV) and cortical thickness (CT), were used as outcomes. Associations were considered significant at a multiple testing-corrected threshold of P < 1.1 × 10-4. Differential gene expression in AHBA data was modeled in brain regions mapped to areas significant in MR analyses; genes were tested for biological and disease overrepresentation in annotation databases and for connectivity in protein-protein interaction networks. Of 20 688 participants in the UK Biobank sample, 10 828 (52.3%) were female, and the mean (SD) age was 55.5 (7.5) years. In the UK Biobank sample, genetically predicted levels of IL-6 were associated with GMV in the middle temporal cortex (z score, 5.76; P = 8.39 × 10-9), inferior temporal (z score, 3.38; P = 7.20 × 10-5), fusiform (z score, 4.70; P = 2.60 × 10-7), and frontal (z score, -3.59; P = 3.30 × 10-5) cortex together with CT in the superior frontal region (z score, -5.11; P = 3.22 × 10-7). No significant associations were found for IL-1, IL-2, CRP, or BDNF after correction for multiple comparison. In the AHBA sample, 5 of 6 participants (83%) were male, and the mean (SD) age was 42.5 (13.4) years. Brain-wide coexpression analysis showed a highly interconnected network of genes preferentially expressed in the middle temporal gyrus (MTG), which further formed a highly connected protein-protein interaction network with IL-6 (enrichment test of expected vs observed network given the prevalence and degree of interactions in the STRING database: 43 nodes/30 edges observed vs 8 edges expected; mean node degree, 1.4; genome-wide significance, P = 4.54 × 10-9). MTG differentially expressed genes that were functionally enriched for biological processes in schizophrenia, autism spectrum disorder, and epilepsy. In this study, genetically determined IL-6 was associated with brain structure and potentially affects areas implicated in developmental neuropsychiatric disorders, including schizophrenia and autism.