Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription.

Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.

Extraocular muscle stem cells exhibit distinct cellular properties associated with non-muscle molecular signatures.

Skeletal muscle stem cells (MuSCs) are recognised as functionally heterogeneous. Cranial MuSCs are reported to have greater proliferative and regenerative capacity when compared with those in the limb. A comprehensive understanding of the mechanisms underlying this functional heterogeneity is lacking. Here, we have used clonal analysis, live imaging and single cell transcriptomic analysis to identify crucial features that distinguish extraocular muscle (EOM) from limb muscle stem cell populations. A MyogeninntdTom reporter showed that the increased proliferation capacity of EOM MuSCs correlates with deferred differentiation and lower expression of the myogenic commitment gene Myod. Unexpectedly, EOM MuSCs activated in vitro expressed a large array of extracellular matrix components typical of mesenchymal non-muscle cells. Computational analysis underscored a distinct co-regulatory module, which is absent in limb MuSCs, as driver of these features. The EOM transcription factor network, with Foxc1 as key player, appears to be hardwired to EOM identity as it persists during growth, disease and in vitro after several passages. Our findings shed light on how high-performing MuSCs regulate myogenic commitment by remodelling their local environment and adopting properties not generally associated with myogenic cells.

Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data.

Non-coding variants associated with complex traits can alter the motifs of transcription factor (TF)-deoxyribonucleic acid binding. Although many computational models have been developed to predict the effects of non-coding variants on TF binding, their predictive power lacks systematic evaluation. Here we have evaluated 14 different models built on position weight matrices (PWMs), support vector machines, ordinary least squares and deep neural networks (DNNs), using large-scale in vitro (i.e. SNP-SELEX) and in vivo (i.e. allele-specific binding, ASB) TF binding data. Our results show that the accuracy of each model in predicting SNP effects in vitro significantly exceeds that achieved in vivo. For in vitro variant impact prediction, kmer/gkm-based machine learning methods (deltaSVM_HT-SELEX, QBiC-Pred) trained on in vitro datasets exhibit the best performance. For in vivo ASB variant prediction, DNN-based multitask models (DeepSEA, Sei, Enformer) trained on the ChIP-seq dataset exhibit relatively superior performance. Among the PWM-based methods, tRap demonstrates better performance in both in vitro and in vivo evaluations. In addition, we find that TF classes such as basic leucine zipper factors could be predicted more accurately, whereas those such as C2H2 zinc finger factors are predicted less accurately, aligning with the evolutionary conservation of these TF classes. We also underscore the significance of non-sequence factors such as cis-regulatory element type, TF expression, interactions and post-translational modifications in influencing the in vivo predictive performance of TFs. Our research provides valuable insights into selecting prioritization methods for non-coding variants and further optimizing such models.

ABI transcription factors and PROTEIN L-ISOASPARTYL METHYLTRANSFERASE module mediate seed desiccation tolerance and longevity in Oryza sativa.

In contrast to desiccation-tolerant orthodox seeds, recalcitrant seeds are desiccation sensitive and are unable to survive for a prolonged time. Here, our analyses of Oryza species with contrasting seed desiccation tolerance reveals that PROTEIN L-ISOASPARTYL METHYLTRANSFERASE (PIMT), an enzyme that repairs abnormal isoaspartyl (isoAsp) residues in proteins, acts as a key player that governs seed desiccation tolerance to orthodox seeds but is ineffective in recalcitrant seeds. We observe that, unlike the orthodox seed of Oryza sativa, desiccation intolerance of the recalcitrant seeds of Oryza coarctata are linked to reduced PIMT activity and increased isoAsp accumulation due to the lack of coordinated action of ABA and ABI transcription factors to upregulate PIMT during maturation. We show that suppression of PIMT reduces, and its overexpression increases, seed desiccation tolerance and seed longevity in O. sativa. Our analyses further reveal that the ABI transcription factors undergo isoAsp formation that affect their functional competence; however, PIMT interacts with and repairs isoAsp residues and facilitates their functions. Our results thus illustrate a new insight into the mechanisms of acquisition of seed desiccation tolerance and longevity by ABI transcription factors and the PIMT module.

Regulators of early maize leaf development inferred from transcriptomes of laser capture microdissection (LCM)-isolated embryonic leaf cells.

The superior photosynthetic efficiency of C4 leaves over C3 leaves is owing to their unique Kranz anatomy, in which the vein is surrounded by one layer of bundle sheath (BS) cells and one layer of mesophyll (M) cells. Kranz anatomy development starts from three contiguous ground meristem (GM) cells, but its regulators and underlying molecular mechanism are largely unknown. To identify the regulators, we obtained the transcriptomes of 11 maize embryonic leaf cell types from five stages of pre-Kranz cells starting from median GM cells and six stages of pre-M cells starting from undifferentiated cells. Principal component and clustering analyses of transcriptomic data revealed rapid pre-Kranz cell differentiation in the first two stages but slow differentiation in the last three stages, suggesting early Kranz cell fate determination. In contrast, pre-M cells exhibit a more prolonged transcriptional differentiation process. Differential gene expression and coexpression analyses identified gene coexpression modules, one of which included 3 auxin transporter and 18 transcription factor (TF) genes, including known regulators of Kranz anatomy and/or vascular development. In situ hybridization of 11 TF genes validated their expression in early Kranz development. We determined the binding motifs of 15 TFs, predicted TF target gene relationships among the 18 TF and 3 auxin transporter genes, and validated 67 predictions by electrophoresis mobility shift assay. From these data, we constructed a gene regulatory network for Kranz development. Our study sheds light on the regulation of early maize leaf development and provides candidate leaf development regulators for future study.

A role for partial epithelial-to-mesenchymal transition in enabling stemness in homeostasis and cancer.

Stem cells have self-renewal capacities and the ability to give rise to differentiated cells thereby sustaining tissues during homeostasis and injury. This structural hierarchy extends to tumours which harbor stem-like cells deemed cancer stem cells that propagate the tumour and drive metastasis and relapse. The process of epithelial-to-mesenchymal transition (EMT), which plays an important role in development and cancer cell migration, was shown to be correlated with stemness in both homeostasis and cancer indicating that stemness can be acquired and is not necessarily an intrinsic trait. Nowadays it is experimentally proven that the activation of an EMT program does not necessarily drive cells towards a fully mesenchymal phenotype but rather to hybrid E/M states. This review offers the latest advances in connecting the EMT status and stem-cell state of both non-transformed and cancer cells. Recent literature clearly shows that hybrid EMT states have a higher probability of acquiring stem cell traits. The position of a cell along the EMT-axis which coincides with a stem cell-like state is known as the stemness window. We show how the original EMT-state of a cell dictates the EMT/MET inducing programmes required to reach stemness. Lastly we present the mechanism of stemness regulation and the regulatory feedback loops which position cells at a certain EMT state along the EMT axis.

The TF/Nrf2/GSTP1 pathway is involved in stress-induced hepatocellular injury through ferroptosis.

Stress triggers a comprehensive pathophysiological cascade in organisms. However, there is a substantial gap in the research regarding the effects of stress on liver function. This study aimed to investigate the impact of restraint stress on hepatocellular damage and elucidate the underlying molecular mechanisms. An effective mouse restraint stress model was successfully developed, and liver function analysis was performed using laser speckle imaging, metabolomics and serum testing. Alterations in hepatocyte morphology were assessed using haematoxylin and eosin staining and transmission electron microscopy. Oxidative stress in hepatocytes was assessed using lipid reactive oxygen species and malondialdehyde. The methylation status and expression of GSTP1 were analysed using DNA sequencing and, real-time PCR, and the expression levels of GPX4, TF and Nrf2 were evaluated using real-time quantitative PCR, western blotting, and immunohistochemical staining. A stress-induced model was established in vitro by using dexamethasone-treated AML-12 cells. To investigate the underlying mechanisms, GSTP1 overexpression, small interfering RNA, ferroptosis and Nrf2 inhibitors were used. GSTP1 methylation contributes to stress-induced hepatocellular damage and dysfunction. GSTP1 is involved in ferroptosis-mediated hepatocellular injury induced by restraint stress via the TF/Nrf2 pathway. These findings suggest that stress-induced hepatocellular injury is associated with ferroptosis, which is regulated by TF/Nrf2/GSTP1.

Identification of common stria vascularis cellular alteration in sensorineural hearing loss based on ScRNA-seq.

BACKGROUND: The stria vascularis (SV), located in the lateral wall of the cochlea, maintains cochlear fluid homeostasis and mechanoelectrical transduction (MET) activity required for sound wave conduction. The pathogenesis of a number of human inheritable deafness syndromes, age related hearing loss, drug-induced ototoxicity and noise-induced hearing loss results from the morphological changes and functional impairments in the development of the SV. In this study, we investigate the implications of intercellular communication within the SV in the pathogenesis of sensorineural hearing loss (SNHL). We aim to identify commonly regulated signaling pathways using publicly available single-cell transcriptomic sequencing (scRNA-seq) datasets. METHODS: We analyzed scRNA-seq data, which was derived from studying the cochlear SV in mice with SNHL compared to normal adult mice. After quality control and filtering, we obtained the major cellular components of the mouse cochlear SV and integrated the data. Using Seurat's FindAllMarkers and FindMarkers packages, we searched for novel conservative genes and differential genes. We employed KEGG and GSEA to identify molecular pathways that are commonly altered among different types of SNHL. We utilized pySCENIC to discover new specific regulatory factors in SV subpopulation cells. With the help of CellChat, we identified changes in subpopulation cells showing similar trends across different SNHL types and their alterations in intercellular communication pathways. RESULTS: Through the analysis of the integrated data, we discovered new conserved genes to SV specific cells and identified common downregulated pathways in three types of SNHL. The enriched genes for these pathways showing similar trends are primarily associated with the Electron Transport Chain, related to mitochondrial energy metabolism. Using the CellChat package, we further found that there are shared pathways in the incoming signaling of specific intermediate cells in SNHL, and these pathways have common upstream regulatory transcription factor of Nfe2l2. Combining the results from pySCENIC and CellChat, we predicted the transcription factor Nfe2l2 as an upstream regulatory factor for multiple shared cellular pathways in IC. Additionally, it serves as an upstream factor for several genes within the Electron Transport Chain. CONCLUSION: Our bioinformatics analysis has revealed that downregulation of the mitochondrial electron transport chain have been observed in various conditions of SNHL. E2f1, Esrrb, Runx1, Yy1, and Gata2 could serve as novel important common TFs regulating the electron transport chain. Adm has emerged as a potential new marker gene for intermediate cells, while Itgb5 and Tesc show promise as potential new marker genes for marginal cells in the SV. These findings offer a new perspective on SV lesions in SNHL and provide additional theoretical evidence for the same drug treatment and prevention of different pathologies of SNHL.

Genome-wide characterization and expression profiling of E2F/DP gene family members in response to abiotic stress in tomato (Solanum lycopersicum L.).

BACKGROUND: E2F/DP (Eukaryotic 2 transcription factor/dimerization partner) family proteins play an essential function in the cell cycle development of higher organisms. E2F/DP family genes have been reported only in a few plant species. However, comprehensive genome-wide characterization analysis of the E2F/DP gene family of Solanum lycopersicum has not been reported so far. RESULTS: This study identified eight nonredundant SlE2F/DP genes that were classified into seven groups in the phylogenetic analysis. All eight genes had a single E2F-TDP domain and few genes had additional domains. Two segmental duplication gene pairs were observed within tomato, in addition to cis-regulatory elements, miRNA target sites and phosphorylation sites which play an important role in plant development and stress response in tomato. To explore the three-dimensional (3D) models and gene ontology (GO) annotations of SlE2F/DP proteins, we pointed to their putative transporter activity and their interaction with several putative ligands. The localization of SlE2F/DP-GFP fused proteins in the nucleus and endoplasmic reticulum suggested that they may act in other biological functions. Expression studies revealed the differential expression pattern of most of the SlE2F/DP genes in various organs. Moreover, the expression of E2F/DP genes against abiotic stress, particularly SlE2F/DP2 and/or SlE2F/DP7, was upregulated in response to heat, salt, cold and ABA treatment. Furthermore, the co-expression analysis of SlE2F/DP genes with multiple metabolic pathways was co-expressed with defence genes, transcription factors and so on, suggested their crucial role in various biological processes. CONCLUSIONS: Overall, our findings provide a way to understand the structure and function of SlE2F/DP genes; it might be helpful to improve fruit development and tolerance against abiotic stress through marker-assisted selection or transgenic approaches.

Identifying and characterizing drug sensitivity-related lncRNA-TF-gene regulatory triplets.

Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient's expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment.

Comprehensive characterization genetic regulation and chromatin landscape of enhancer-associated long non-coding RNAs and their implication in human cancer.

Long non-coding RNAs (lncRNAs) that emanate from enhancer regions (defined as enhancer-associated lncRNAs, or elncRNAs) are emerging as critical regulators in disease progression. However, their biological characteristics and clinical relevance have not been fully portrayed. Here, based on the traditional expression quantitative loci (eQTL) and our optimized residual eQTL method, we comprehensively described the genetic effect on elncRNA expression in more than 300 lymphoblastoid cell lines. Meanwhile, a chromatin atlas of elncRNAs relative to the genetic regulation state was depicted. By applying the maximum likelihood estimate method, we successfully identified causal elncRNAs for protein-coding gene expression reprogramming and showed their associated single nucleotide polymorphisms (SNPs) favor binding of transcription factors. Further epigenome analysis revealed two immune-associated elncRNAs AL662844.4 and LINC01215 possess high levels of H3K27ac and H3K4me1 in human cancer. Besides, pan-cancer analysis of 3D genome, transcriptome, and regulatome data showed they potentially regulate tumor-immune cell interaction through affecting MHC class I genes and CD47, respectively. Moreover, our study showed there exist associations between elncRNA and patient survival. Finally, we made a user-friendly web interface available for exploring the regulatory relationship of SNP-elncRNA-protein-coding gene triplets (http://bio-bigdata.hrbmu.edu.cn/elncVarReg). Our study provides critical mechanistic insights for elncRNA function and illustrates their implications in human cancer.

A deep learning model to identify gene expression level using cobinding transcription factor signals.

Gene expression is directly controlled by transcription factors (TFs) in a complex combination manner. It remains a challenging task to systematically infer how the cooperative binding of TFs drives gene activity. Here, we quantitatively analyzed the correlation between TFs and surveyed the TF interaction networks associated with gene expression in GM12878 and K562 cell lines. We identified six TF modules associated with gene expression in each cell line. Furthermore, according to the enrichment characteristics of TFs in these TF modules around a target gene, a convolutional neural network model, called TFCNN, was constructed to identify gene expression level. Results showed that the TFCNN model achieved a good prediction performance for gene expression. The average of the area under receiver operating characteristics curve (AUC) can reach up to 0.975 and 0.976, respectively in GM12878 and K562 cell lines. By comparison, we found that the TFCNN model outperformed the prediction models based on SVM and LDA. This is due to the TFCNN model could better extract the combinatorial interaction among TFs. Further analysis indicated that the abundant binding of regulatory TFs dominates expression of target genes, while the cooperative interaction between TFs has a subtle regulatory effects. And gene expression could be regulated by different TF combinations in a nonlinear way. These results are helpful for deciphering the mechanism of TF combination regulating gene expression.

Assessing deep learning methods in cis-regulatory motif finding based on genomic sequencing data.

Identifying cis-regulatory motifs from genomic sequencing data (e.g. ChIP-seq and CLIP-seq) is crucial in identifying transcription factor (TF) binding sites and inferring gene regulatory mechanisms for any organism. Since 2015, deep learning (DL) methods have been widely applied to identify TF binding sites and predict motif patterns, with the strengths of offering a scalable, flexible and unified computational approach for highly accurate predictions. As far as we know, 20 DL methods have been developed. However, without a clear and systematic assessment, users will struggle to choose the most appropriate tool for their specific studies. In this manuscript, we evaluated 20 DL methods for cis-regulatory motif prediction using 690 ENCODE ChIP-seq, 126 cancer ChIP-seq and 55 RNA CLIP-seq data. Four metrics were investigated, including the accuracy of motif finding, the performance of DNA/RNA sequence classification, algorithm scalability and tool usability. The assessment results demonstrated the high complementarity of the existing DL methods. It was determined that the most suitable model should primarily depend on the data size and type and the method's outputs.

Involvement of nr2f genes in brain regionalization and eye development during early zebrafish development.

Nuclear receptor subfamily 2 group F (Nr2f) proteins are essential for brain development in mice, but little is known about their precise roles and their evolutionary diversification. In the present study, the expression patterns of major nr2f genes (nr2f1a, nr2f1b, and nr2f2) during early brain development were investigated in zebrafish. Comparisons of their expression patterns revealed similar but temporally and spatially distinct patterns after early somite stages in the brain. Frameshift mutations in the three nr2f genes, achieved using the CRISPR/Cas9 method, resulted in a smaller telencephalon and smaller eyes in the nr2f1a mutants; milder forms of those defects were present in the nr2f1b and nr2f2 mutants. Acridine orange staining revealed enhanced cell death in the brain and/or eyes in all nr2f homozygous mutants. The expression of regional markers in the brain did not suggest global defects in brain regionalization; however, shha expression in the preoptic area and hypothalamus, as well as fgf8a expression in the anterior telencephalon, was disturbed in nr2f1a and nr2f1b mutants, potentially leading to a defective telencephalon. Specification of the retina and optic stalk was also significantly affected. The overexpression of nr2f1b by injection of mRNA disrupted the anterior brain at a high dose, and the expression of pax6a in the eyes and fgf8a in the telencephalon at a low dose. The results of these loss- and gain-of-function approaches showed that nr2f genes regulate the development of the telencephalon and eyes in zebrafish embryos.

Transcription factors-related molecular subtypes and risk prognostic model: exploring the immunogenicity landscape and potential drug targets in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, with a high mortality rate and poor prognosis. Mutated or dysregulated transcription factors (TFs) are significantly associated with carcinogenesis. The aim of this study was to develop a TF-related prognostic risk model to predict the prognosis and guide the treatment of HCC patients. METHODS: RNA sequencing data were obtained from the TCGA database. The ICGC and GEO databases were used as validation datasets. The consensus clustering algorithm was used to classify the molecular subtypes of TFs. Kaplan‒Meier survival analysis and receiver operating characteristic (ROC) analysis were applied to evaluate the prognostic value of the model. The immunogenic landscape differences of molecular subtypes were evaluated by the TIMER and xCell algorithms. Autodock analysis was used to predict possible binding sites of trametinib to TFs. RT‒PCR was used to verify the effect of trametinib on the expression of core TFs. RESULTS: According to the differential expression of TFs, HCC samples were divided into two clusters (C1 and C2). The survival time, signaling pathways, abundance of immune cell infiltration and responses to chemotherapy and immunotherapy were significantly different between C1 and C2. Nine TFs with potential prognostic value, including HMGB2, ESR1, HMGA1, MYBL2, TCF19, E2F1, FOXM1, CENPA and ZIC2, were identified by Cox regression analysis. HCC patients in the high-risk group had a poor prognosis compared with those in the low-risk group (p < 0.001). Moreover, the area under the ROC curve (AUC) values of the 1-year, 2-year and 3-year survival rates were 0.792, 0.71 and 0.695, respectively. The risk model was validated in the ICGC database. Notably, trametinib sensitivity was highly correlated with the expression of core TFs, and molecular docking predicted the possible binding sites of trametinib with these TFs. More importantly, the expression of core TFs was downregulated under trametinib treatment. CONCLUSIONS: A prognostic signature with 9 TFs performed well in predicting the survival rate and chemotherapy/immunotherapy effect of HCC patients. Trimetinib has potential application value in HCC by targeting TFs.

A novel optimization-assisted multi-scale and dilated adaptive hybrid deep learning network with feature fusion for event detection from social media.

Social media networks become an active communication medium for connecting people and delivering new messages. Social media can perform as the primary channel, where the globalized events or instances can be explored. Earlier models are facing the pitfall of noticing the temporal and spatial resolution for enhancing the efficacy. Therefore, in this proposed model, a new event detection approach from social media data is presented. Firstly, the essential data is collected and undergone for pre-processing stage. Further, the Bidirectional Encoder Representations from Transformers (BERT) and Term Frequency Inverse Document Frequency (TF-IDF) are employed for extracting features. Subsequently, the two resultant features are given to the multi-scale and dilated layer present in the detection network of GRU and Res-Bi-LSTM, named as Multi-scale and Dilated Adaptive Hybrid Deep Learning (MDA-HDL) for event detection. Moreover, the MDA-HDL network's parameters are tuned by Improved Gannet Optimization Algorithm (IGOA) to enhance the performance. Finally, the execution of the system is done over the Python platform, where the system is validated and compared with baseline methodologies. The accuracy findings of model acquire as 94.96 for dataset 1 and 96.42 for dataset 2. Hence, the recommended model outperforms with the superior results while detecting the social events.

'School-based screen-and-treat': An effective blueprint for expediating access to care in children experiencing PTSD following disasters.

OBJECTIVES: While 5%-10% of children exposed to natural disasters develop PTSD, few children access support. This paper reports on the proactive 'screen-and-treat' approach deployed following devastating floods in Queensland, Australia, in 2011 and presents results for children in the Lockyer Valley (the most impacted community). DESIGN: Open treatment study (2011-2012) within a government-funded post-disaster service response. METHODS: One hundred and fifty children (7-12 years) completed pencil-and-paper screening (PTSD, anxiety and depression) at school. Eighty children endorsing either clinical levels of PTSD, or moderate levels of PTSD and clinical levels of either anxiety or depression, and their parents, completed a structured diagnostic interview. Forty-eight children were offered a free trauma-focused CBT intervention. The parents of 19 children accepted this offer. Most clinicians were clinical psychology trainees from local universities. All measures were repeated at post-treatment, 6- and 12-month follow-up. Note: The term 'parents' is used to refer to the wide variety of people serving as a child's primary caregiver. RESULTS: Pre-treatment, all children met diagnostic criteria for full (N = 17) or sub-clinical PTSD. By post-treatment, 10.5% met criteria for PTSD, with 0% meeting criteria at the 12-month follow-up. The incidence of anxiety and depressive disorders also reduced significantly. There were no differences in outcomes for children seen by trainees compared to experienced clinicians. CONCLUSIONS: A school-based screen-and-treat approach offers potential as a means of identifying and treating children following natural disaster exposure. However, engagement of families at the outset, and when offering intervention was challenging. Postgraduate trainees represent an effective potential workforce in a post-disaster environment.

Bbhox2 is a key regulator for conidiation and virulence in Beauveria bassiana.

Beauveria bassiana, a well-known filamentous biocontrol fungus, is the main pathogen of numerous field and forest pests. To explore the potential factors involved in the fungal pathogenicity, Bbhox2, an important and conserved functional transcription factor containing homeodomain was carried out by functional analysis. Homologous recombination was used to disrupt the Bbhox2 gene in B.bassiana. The conidia yield of the deletant fungal strain was significantly reduced. The conidial germination was faster, and stress tolerance to Congo red and high osmotic agents were decreased compared with that in the wildtype. Additionally, ΔBbhox2 showed a dramatic reduction in virulence no matter in topical inoculations or in intra-hemolymph injections against Galleria mellonella larvae, which is likely due to the failure of appressorium formation and the defect in producing hyphal body. These results indicate that the Bbhox2 gene markedly contributes to conidiation and pathogenicity in B. bassiana.

Toxicity factors to assess the ecological risk for soil microbial communities.

The toxicity factor (TF), a critical parameter within the potential ecological risk index (RI), is determined without accounting for microbial factors. It is considerable uncertainty exists concerning its validity for quantitatively assessing the influence of metal(loid)s on microorganisms. To evaluate the suitability of TF, we constructed microcosm experiments with varying RI levels (RI = 100, 200, 300, 500, and 700) by externally adding zinc (Zn), chromium (Cr), copper (Cu), lead (Pb), nickel (Ni), cadmium (Cd), and mercury (Hg) to uncontaminated soil (CK). Quantitative real-time PCR (qPCR) and high-throughput sequencing techniques were employed to measure the abundance and community of bacteria and fungi, and high-throughput qPCR was utilised to quantify functional genes associated with CNPS cycles. The results demonstrated that microbial diversity and function exhibited significant alterations (p < 0.05) in response to increasing RI levels, and the influences on microbial community structure, enzyme activity, and functional gene abundances were different due to the types of metal(loid)s treatments. At the same RI level, significant differences (p < 0.05) were discerned in microbial diversity and function across metal(loid) treatments, and these differences became more pronounced (p < 0.001) at higher levels. These findings suggest that TF may not be suitable for the quantitative assessment of microbial ecological risk. Therefore, we adjusted the TF by following three steps (1) determining the adjustment criteria, (2) deriving the initial TF, and (3) adjusting and optimizing the TF. Ultimately, the optimal adjusted TF was established as Zn = 1.5, Cr = 4.5, Cu = 6, Pb = 4.5, Ni = 5, Cd = 22, and Hg = 34. Our results provide a new reference for quantitatively assessing the ecological risks caused by metal(loid)s to microorganisms.

Effect of 1,4-Dioxane Solvent on ß-Glucuronidation Using Methyl 1,2,3,4-Tetra-O-acetyl-ß-D-glucuronate as the Glycosyl Donor.

A facile and selective ß-D-glucuronidation of alcohols, such as (-)-menthol, cholestanol, (+)- and (-)-borneols, and 2-adamantanol, using commercially available methyl 1,2,3,4-tetra-O-acetyl-ß-D-glucuronate as the glycosyl donor and trimethylsilyl bis(trifluoromethanesulfonyl)imide (Tf2NTMS) (0.5 equivalent) as the activator in 1,4-dioxane at 60 °C gave products in moderate yields. The addition of MS4A increased the ß : α ratios of D-glucuronides when cholestanol, (+)-borneol, and 2-adamantanol were used as the acceptor substrate.