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.

Establishment of a Mitochondrial Metabolism-Related Diagnostic Model in Schizophrenia Based on LASSO Algorithm.

OBJECTIVE: Schizophrenia is a common mental disorder, and mitochondrial function represents a potential therapeutic target for psychiatric diseases. The role of mitochondrial metabolism-related genes (MRGs) in the diagnosis of schizophrenia remains unknown. This study aimed to identify candidate genes that may influence the diagnosis and treatment of schizophrenia based on MRGs. METHODS: Three schizophrenia datasets were obtained from the Gene Expression Omnibus database. MRGs were collected from relevant literature. The differentially expressed genes between normal samples and schizophrenia samples were screened using the limma package. Venn analysis was performed to identify differentially expressed MRGs (DEMRGs) in schizophrenia. Based on the STRING database, hub genes in DEMRGs were identified using the MCODE algorithm in Cytoscape. A diagnostic model containing hub genes was constructed using LASSO regression and logistic regression analysis. The relationship between hub genes and drug sensitivity was explored using the DSigDB database. An interaction network between miRNA-transcription factor (TF)-hub genes was created using the Network-Analyst website. RESULTS: A total of 1,234 MRGs, 172 DEMRGs, and 6 hub genes with good diagnostic performance were identified. Ten potential candidate drugs (rifampicin, fulvestrant, pentadecafluorooctanoic acid, etc.) were selected. Thirty-four miRNAs targeting genes in the diagnostic model (ANGPTL4, CPT2, GLUD1, MED1, and MED20), as well as 137 TFs, were identified. CONCLUSION: Six potential candidate genes showed promising diagnostic significance. rifampicin, fulvestrant, and pentadecafluorooctanoic acid were potential drugs for future research in the treatment of schizophrenia. These findings provided valuable evidence for the understanding of schizophrenia pathogenesis, diagnosis, and drug treatment.

Genome-Wide Identification of the Alfin-like Gene Family in Cotton (Gossypium hirsutum) and the GhAL19 Gene Negatively Regulated Drought and Salt Tolerance.

Alfin-like (AL) is a small plant-specific gene family characterized by a PHD-finger-like structural domain at the C-terminus and a DUF3594 structural domain at the N-terminus, and these genes play prominent roles in plant development and abiotic stress response. In this study, we conducted genome-wide identification and analyzed the AL protein family in Gossypium hirsutum cv. NDM8 to assess their response to various abiotic stresses for the first time. A total of 26 AL genes were identified in NDM8 and classified into four groups based on a phylogenetic tree. Moreover, cis-acting element analysis revealed that multiple phytohormone response and abiotic stress response elements were highly prevalent in AL gene promoters. Further, we discovered that the GhAL19 gene could negatively regulate drought and salt stresses via physiological and biochemical changes, gene expression, and the VIGS assay. The study found there was a significant increase in POD and SOD activity, as well as a significant change in MDA in VIGS-NaCl and VIGS-PEG plants. Transcriptome analysis demonstrated that the expression levels of the ABA biosynthesis gene (GhNCED1), signaling genes (GhABI1, GhABI2, and GhABI5), responsive genes (GhCOR47, GhRD22, and GhERFs), and the stress-related marker gene GhLEA14 were regulated in VIGS lines under drought and NaCl treatment. In summary, GhAL19 as an AL TF may negatively regulate tolerance to drought and salt by regulating the antioxidant capacity and ABA-mediated pathway.

Identification of DNA motif pairs on paired sequences based on composite heterogeneous graph.

Motivation: The interaction between DNA motifs (DNA motif pairs) influences gene expression through partnership or competition in the process of gene regulation. Potential chromatin interactions between different DNA motifs have been implicated in various diseases. However, current methods for identifying DNA motif pairs rely on the recognition of single DNA motifs or probabilities, which may result in local optimal solutions and can be sensitive to the choice of initial values. A method for precisely identifying DNA motif pairs is still lacking. Results: Here, we propose a novel computational method for predicting DNA Motif Pairs based on Composite Heterogeneous Graph (MPCHG). This approach leverages a composite heterogeneous graph model to identify DNA motif pairs on paired sequences. Compared with the existing methods, MPCHG has greatly improved the accuracy of motifs prediction. Furthermore, the predicted DNA motifs demonstrate heightened DNase accessibility than the background sequences. Notably, the two DNA motifs forming a pair exhibit functional consistency. Importantly, the interacting TF pairs obtained by predicted DNA motif pairs were significantly enriched with known interacting TF pairs, suggesting their potential contribution to chromatin interactions. Collectively, we believe that these identified DNA motif pairs held substantial implications for revealing gene transcriptional regulation under long-range chromatin interactions.

A community-based study of the impact of trauma exposure on school-aged children's self-concept and improvements following TF-CBT.

BACKGROUND: Experiencing trauma in childhood has been associated with more severe psychopathology and a greater risk of engaging in harmful behavior later in life. Traumatic exposure can also erode a child's self-concept. Negative self-concept has been associated with shame, self-doubt, and helplessness in the face of adverse experiences. Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) is an evidence-based model for children; however, research on its effectiveness in improving children's self-concept is limited. OBJECTIVE: To investigate the impact of trauma on school-aged children's self-concept and improvements following TF-CBT. PARTICIPANTS AND SETTING: A demographically diverse sample of trauma-exposed school-aged children referred to community-based agencies in Canada and a normative sample of school-aged children randomly selected from the general population in the United States. METHOD: A longitudinal design was used to assess trauma-exposed children's self-reported self-concept using the short-form Tennessee Self-Concept Scale - Second Edition (TSCS:2; Fitts & Warren, 1996) prior to and following TF-CBT. RESULTS: Trauma-exposed children had a significantly more negative mean self-concept compared to that of the normative sample. Improvements following TF-CBT - and not the passage of time alone - were found with gains maintained six months post-therapy. CONCLUSIONS: School-aged children awaiting treatment at community-based agencies are likely to hold clinically concerning negative views of themselves. TF-CBT was effective in significantly improving their self-concept with continued and lasting improvements observed after the therapy had been completed.

2-Site versus 3-site models of ATP hydrolysis by F1-ATPase: definitive mathematical proof using combinatorics and conservation equations.

The F1-ATPase enzyme is the smallest-known molecular motor that rotates in 120° steps, driven by the hydrolysis of ATP. It is a multi-subunit enzyme that contains three catalytic sites. A central question is how the elementary chemical reactions that occur in the three sites are coupled to mechanical rotation. Various models and coupling schemes have been formulated in an attempt to answer this question. They can be classified as 2-site (bi-site) models, exemplified by Boyer's binding change mechanism first proposed 50 years ago, and 3-site (tri-site) models such as Nath's torsional mechanism, first postulated 25 years ago and embellished 1 year back. Experimental data collated using diverse approaches have conclusively shown that steady-state ATP hydrolysis by F1-ATPase occurs in tri-site mode. Hence older models have been continually modified to make them conform to the new facts. Here, we have developed a pure mathematical approach based on combinatorics and conservation laws to test if proposed models are 2-site or 3-site. Based on this novel combinatorial approach, we have proved that older and modified models are effectively bi‒site models in that catalysis and rotation in F1-ATPase occurs in these models with only two catalytic sites occupied by bound nucleotide. Hence these models contradict consensus experimental data. The recent 2023 model of ATP hydrolysis by F1-ATPase has been proved to be a true tri-site model based on our novel mathematical approach. Such pure mathematical proofs constitute an important step forward for ATP mechanism. However, in what must be considered an aspect with great scientific potential, the power of such mathematical proofs has not been fully exploited to solve molecular biological problems, in our opinion. We believe that the creative application of pure mathematical proofs (for another example see Nath in Theory Biosci 141:249-260, 2022) can help resolve with finality various longstanding molecular-level issues that arise as a matter of course in the analysis of fundamental biological problems. Such issues have proved extraordinarily difficult to resolve by standard experimental, theoretical, or computational approaches.

TFTF: An R-Based Integrative Tool for Decoding Human Transcription Factor-Target Interactions.

Transcription factors (TFs) are crucial in modulating gene expression and sculpting cellular and organismal phenotypes. The identification of TF-target gene interactions is pivotal for comprehending molecular pathways and disease etiologies but has been hindered by the demanding nature of traditional experimental approaches. This paper introduces a novel web application and package utilizing the R program, which predicts TF-target gene relationships and vice versa. Our application integrates the predictive power of various bioinformatic tools, leveraging their combined strengths to provide robust predictions. It merges databases for enhanced precision, incorporates gene expression correlation for accuracy, and employs pan-tissue correlation analysis for context-specific insights. The application also enables the integration of user data with established resources to analyze TF-target gene networks. Despite its current limitation to human data, it provides a platform to explore gene regulatory mechanisms comprehensively. This integrated, systematic approach offers researchers an invaluable tool for dissecting the complexities of gene regulation, with the potential for future expansions to include a broader range of species.

Psychological intervention in women victims of childhood sexual abuse: a randomized controlled clinical trial comparing EMDR psychotherapy and trauma-focused cognitive behavioral therapy.

Introduction: Childhood sexual abuse persists as a painful societal reality, necessitating responses from institutions and healthcare professionals to prevent and address its severe long-term consequences in victims. This study implements an intervention comprising two psychotherapeutic approaches recommended by the WHO and international clinical guidelines for addressing short-, medium-, and long-term posttraumatic symptomatology: Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) and Eye Movement Desensitization and Reprocessing (EMDR). Both approaches are adapted from group formats for implementation in small online groups via Zoom. Methods: The impact of both therapeutic approaches on trauma improvement was assessed in a sample of 19 women who were victims of childhood sexual abuse through a Randomized Clinical Trial comparing EMDR Psychotherapy and Trauma-Focused Cognitive Behavioral Therapy after a baseline period. Intra and inter comparison were made using statistics appropriate to the sample. Results: Both therapeutic approaches significantly reduced symptomatology across various evaluated variables, suggesting their efficacy in improving the quality of life for these individuals. Following CBT-FT treatment, patients exhibited enhanced emotional regulation, reduced reexperiencing, and avoidance. The EMDR group, utilizing the G-TEP group protocol, significantly improved dissociation, along with other crucial clinical variables and the perception of quality of life. Discussion: Although the limitations of this study must be taken into account due to the size of the sample and the lack of long-term follow-up, the results align with existing scientific literature, underscoring the benefits of trauma-focused psychological treatments. The online group format appears promising for enhancing the accessibility of psychological treatment for these women. Furthermore, the differential outcomes of each treatment support recent research advocating for the inclusion of both approaches for individuals with trauma-related symptomatology. Ethics and dissemination: The study has been approved by the Ethics Committee of the Valencian International University (VIU) (Valencia, Spain) (Ref. CEID2021_07). The results will be submitted for publication in peer-reviewed journals and disseminated to the scientific community. Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT04813224, identifier NCT04813224.

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.

Automatic text classification of drug-induced liver injury using document-term matrix and XGBoost.

Introduction: Regulatory agencies generate a vast amount of textual data in the review process. For example, drug labeling serves as a valuable resource for regulatory agencies, such as U.S. Food and Drug Administration (FDA) and Europe Medical Agency (EMA), to communicate drug safety and effectiveness information to healthcare professionals and patients. Drug labeling also serves as a resource for pharmacovigilance and drug safety research. Automated text classification would significantly improve the analysis of drug labeling documents and conserve reviewer resources. Methods: We utilized artificial intelligence in this study to classify drug-induced liver injury (DILI)-related content from drug labeling documents based on FDA's DILIrank dataset. We employed text mining and XGBoost models and utilized the Preferred Terms of Medical queries for adverse event standards to simplify the elimination of common words and phrases while retaining medical standard terms for FDA and EMA drug label datasets. Then, we constructed a document term matrix using weights computed by Term Frequency-Inverse Document Frequency (TF-IDF) for each included word/term/token. Results: The automatic text classification model exhibited robust performance in predicting DILI, achieving cross-validation AUC scores exceeding 0.90 for both drug labels from FDA and EMA and literature abstracts from the Critical Assessment of Massive Data Analysis (CAMDA). Discussion: Moreover, the text mining and XGBoost functions demonstrated in this study can be applied to other text processing and classification tasks.

Screening and Treatment of Posttraumatic Stress Disorder in Wildfire Evacuees: A Cost-Utility Analysis.

Background. Global climate change is resulting in dramatic increases in wildfires. Individuals exposed to wildfires experience a high burden of posttraumatic stress disorder (PTSD), and the cost-effectiveness of the treatment options to address PTSD from wildfires has not been studied. The objective of this study was to conduct a cost-utility analysis comparing screening followed by treatment with paroxetine or trauma-focused cognitive behavioral therapy (TF-CBT) versus no screening in Canadian adult wildfire evacuees. Methods. Using a Markov model, quality-adjusted life-years (QALYs) and costs were evaluated over a 5-y time horizon using health care and societal perspectives. All costs and utilities in the model were discounted at 1.5%. Probabilistic and deterministic sensitivity analyses examined the uncertainty in the incremental net monetary benefit (INMB) under a willingness-to-pay threshold of $50,000. Results. From a societal perspective, no screening (NMB = $177,641) was dominated by screening followed by treatment with paroxetine (NMB = $180,733) and TF-CBT (NMB = $181,787), with TF-CBT having the highest likelihood of being cost-effective at a willingness-to-pay threshold of $50,000 per QALY (probability = 0.649). The initial prevalence of PTSD, probability of acceptance of treatment, and costs of productivity had the largest impact on the INMB of both paroxetine or TF-CBT versus no screening. Neither intervention was cost-effective at a willingness-to-pay threshold of $50,000 per QALY from a health care perspective. Interpretation. Screening followed by treatment with paroxetine or TF-CBT compared with no screening was found to be cost-saving while providing additional QALYs in wildfire evacuees. Governments should consider funding screening programs for PTSD followed by treatment with TF-CBT for wildfire evacuees. Highlights: Two prior studies examined the cost-effectiveness of screening followed by treatment for PTSD among individuals exposed to other disaster-type events (i.e., terrorist attack and Hurricane Sandy) and found screening followed by treatment (i.e., cognitive behavioral therapy [CBT]) to be highly cost-effective.Among wildfire evacuees, screening followed by treatment with paroxetine or trauma-focused (TF)-CBT provides additional quality-adjusted life-years (QALYs) and is cost-saving from a societal perspective. TF-CBT was the treatment option found most likely to be cost-effective.Neither treatment option was cost-effective at a willingness-to-pay threshold of $50,000 per QALY from a health care perspective.Screening programs for PTSD should be considered for wildfire evacuees, and individuals diagnosed with PTSD could be prescribed either TF-CBT or paroxetine depending on their preference and resources availability.

Neointimal hyperplasia after endoluminal injury in mice is dependent on tissue factor- and angiopoietin-2 dependent interferon gamma production by fibrocytes and macrophages.

Background: The intimal hyperplasia (IH) and vascular remodelling that follows endovascular injury, for instance after post-angioplasty re-stenosis, results in downstream ischaemia and progressive end organ damage. Interferon gamma (IFNγ) is known to play a critical role in this process. In mouse models we have previously shown that fibrocytes expressing tissue factor (TF) are recruited early to the site of injury. Through thrombin generation and protease activated receptor-1 (PAR-1) activation, fibrocytes secrete angiopoietin-2, stimulate neointimal cell proliferation, inhibit apoptosis and induce CXCL-12 production, all of which contribute to the progressive IH that then develops. In this study we investigated the relationship between TF, angiopoietin-2 and IFNγ. Methods and results: IH developing in carotid arteries of wild-type mice 4 weeks after endoluminal injury contained a significant proportion of IFNγ+ fibrocytes and macrophages, which we show, using a previously defined adoptive transfer model, were derived from circulating CD34+ cells. IH did not develop after injury in IFNγ-deficient mice, except after transplantation of WT bone marrow or adoptive transfer of WT CD34+ cells. In vitro, CD34+ cells isolated from post-injury mice did not express IFNγ, but this was induced when provided with FVIIa and FX, and enhanced when prothrombin was also provided: In both cases IFNγ secretion was TF-dependent and mediated mainly through protease activated PAR-1. IFNγ was predominantly expressed by fibrocytes. In vivo, all IFNγ+ neointimal cells in WT mice co-expressed angiopoietin-2, as did the small numbers of neointimal cells recruited in IFNγ-/- mice. Adoptively transferred WT CD34+ cells treated with either an anti-TIE-2 antibody, or with siRNA against angiopoetin-2 inhibited the expression of IFNγ and the development of IH. Conclusion: TF-dependent angiopoietin-2 production by newly recruited fibrocytes, and to a lesser extent macrophages, switches on IFNγ expression, and this is necessary for the IH to develop. These novel findings enhance our understanding of the pathophysiology of IH and expose potential targets for therapeutic intervention.

Calpain Small Subunit Mediated Secretion of Galectin-3 Regulates Traction Stress.

The complex regulation of traction forces (TF) produced during cellular migration remains poorly understood. We have previously found that calpain 4 (Capn4), the small non-catalytic subunit of the calpain 1 and 2 proteases, regulates the production of TF independent of the proteolytic activity of the larger subunits. Capn4 was later found to facilitate tyrosine phosphorylation and secretion of the lectin-binding protein galectin-3 (Gal3). In this study, recombinant Gal3 (rGal3) was added to the media-enhanced TF generated by capn4-/- mouse embryonic fibroblasts (MEFs). Extracellular Gal3 also rescued defects in the distribution, morphology, and adhesive strength of focal adhesions present in capn4-/- MEF cells. Surprisingly, extracellular Gal3 does not influence mechanosensing. c-Abl kinase was found to affect Gal3 secretion and the production of TF through phosphorylation of Y107 on Gal3. Our study also suggests that Gal3-mediated regulation of TF occurs through signaling pathways triggered by ß1 integrin but not by focal adhesion kinase (FAK) Y397 autophosphorylation. Our findings provide insights into the signaling mechanism by which Capn4 and secreted Gal3 regulate cell migration through the modulation of TF distinctly independent from a mechanosensing mechanism.

A robust deep learning system for screening of obstructive sleep apnea using T-F spectrum of ECG signals.

Obstructive sleep apnea (OSA) is a non-communicable sleep-related medical condition marked by repeated disruptions in breathing during sleep. It may induce various cardiovascular and neurocognitive complications. Electrocardiography (ECG) is a useful method for detecting numerous health-related disorders. ECG signals provide a less complex and non-invasive solution for the screening of OSA. Automated and accurate detection of OSA may enhance diagnostic performance and reduce the clinician's workload. Traditional machine learning methods typically involve several labor-intensive manual procedures, including signal decomposition, feature evaluation, selection, and categorization. This article presents the time-frequency (T-F) spectrum classification of de-noised ECG data for the automatic screening of OSA patients using deep convolutional neural networks (DCNNs). At first, a filter-fusion algorithm is used to eliminate the artifacts from the raw ECG data. Stock-well transform (S-T) is employed to change filtered time-domain ECG into T-F spectrums. To discriminate between apnea and normal ECG signals, the obtained T-F spectrums are categorized using benchmark Alex-Net and Squeeze-Net, along with a less complex DCNN. The superiority of the presented system is measured by computing the sensitivity, specificity, accuracy, negative predicted value, precision, F1-score, and Fowlkes-Mallows index. The results of comparing all three utilized DCNNs reveal that the proposed DCNN requires fewer learning parameters and provides higher accuracy. An average accuracy of 95.31% is yielded using the proposed system. The presented deep learning system is lightweight and faster than Alex-Net and Squeeze-Net as it utilizes fewer learnable parameters, making it simple and reliable.

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.

'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.

Efficient production of human interleukin-3 from Escherichia coli using protein disulfide isomerase b'a' domain.

Human interleukin-3 (IL3) is a multifunctional cytokine essential for both clinical and biomedical research endeavors. However, its production in Escherichia coli has historically been challenging due to its aggregation into inclusion bodies, requiring intricate solubilization and refolding procedures. This study introduces an innovative approach employing two chaperone proteins, maltose binding protein (MBP) and protein disulfide isomerase b'a' domain (PDIb'a'), as N-terminal fusion tags. Histidine tag (H) was added at the beginning of each chaperone protein gene for easy purification. This fusion of chaperone proteins significantly improved IL3 solubility across various E. coli strains and temperature conditions, eliminating the need for laborious refolding procedures. Following expression optimization, H-PDIb'a'-IL3 was purified using two chromatographic methods, and the subsequent removal of the H-PDIb'a' tag yielded high-purity IL3. The identity of the purified protein was confirmed through liquid chromatography coupled with tandem mass spectrometry analysis. Biological activity assays using human erythroleukemia TF-1 cells revealed a unique two-step stimulation pattern for both purified IL3 and the H-PDIb'a'-IL3 fusion protein, underscoring the protein's functional integrity and revealing novel insights into its cellular interactions. This study advances the understanding of IL3 expression and activity while introducing novel considerations for protein fusion strategies.

OsBBP1, a newly identified protein containing DUF630 and DUF632 domains confers drought tolerance in rice.

Domain of unknown function (DUF) protein families, which are uncharacterized and numerous within the Pfam database. Recently, studies have demonstrated that DUFs played crucial roles in plant development, but whether, or how, they function in drought resistance remain unclear. In this study, we identified the Os03g0321500 gene, encoding OsbZIP72 binding protein 1 (OsBBP1), as a target of OsbZIP72 using chromatin immunoprecipitation sequencing in rice. OsBBP1 is a novel member of DUFs, which localize both in the nuclei and cytoplasm of rice protoplasts. Furthermore, yeast one-hybrid and electrophoretic mobility shift assays confirmed the specific binding between OsbZIP72 and OsBBP1. Additionally, a luciferase reporter analysis illustrated that OsbZIP72 activated the expression of OsBBP1. Drought tolerance experiments demonstrate that the OsBBP1 CRISPER-CAS9 transgenic mutants were sensitive to drought stress, but the transgenic OsBBP1 over-expressing rice plants showed enhanced drought resistance. Moreover, drought tolerance experiments in a paddy field suggested that OsBBP1 contributed to less yield or yield-related losses under drought conditions. Mechanistically, OsBBP1 might confer drought resistance by inducing more efficient reactive oxygen species (ROS) scavenging. Several ROS scavenging-related genes showed increased expression levels in OsBBP1 overexpression lines and decreased expression levels in OsBBP1 CRISPER-CAS9 mutants under drought conditions. Thus, OsBBP1, acting downstream of OsbZIP72, contributes to drought resistance and causes less yield or yield-related losses under drought conditions.

Prediction of novel biomarkers for gastric intestinal metaplasia and gastric adenocarcinoma using bioinformatics analysis.

Background & aim: The histologic and molecular changes from intestinal metaplasia (IM) to gastric cancer (GC) have not been fully characterized. The present study sought to identify potential alterations in signaling pathways in IM and GC to predict disease progression; these alterations can be considered therapeutic targets. Materials & methods: Seven gene expression profiles were selected from the GEO database. Discriminate differentially expressed genes (DEGs) were analyzed by EnrichR. The STRING database, Cytoscape, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, NetworkAnalyst, MirWalk database, OncomiR, and bipartite miRNA‒mRNA correlation network was used for downstream analyses of selected module genes. Results: Analyses revealed that extracellular matrix-receptor interactions (ITGB1, COL1A1, COL1A2, COL4A1, FN1, COL6A3, and THBS2) in GC and PPAR signaling pathway interactions (FABP1, APOC3, APOA1, HMGCS2, and PPARA and PCK1) in IM may play key roles in both the carcinogenesis and progression of underlying GC from intestinal metaplasia. IM enrichment indicated that this is closely related to digestion and absorption. The TF-hub gene regulatory network revealed that AR, TCF4, SALL4, and ESR1 were more important for hub gene expression. It was revealed that the development and prediction of GC may be affected by hsa-miR-29. It was found that PTGR1, C1orf115, CRYL1, ALDOB, and SULT1B1 were downregulated in GC and upregulated in IM. Therefore, they might have tumor suppressor activity in GC progression. Conclusion: New potential biomarkers and pathways involved in GC and IM were identified that are important for the transformation of GC from IM to adenocarcinoma and can be therapeutic targets for GC.

RUNX1-induced upregulation of PTGS2 enhances cell growth, migration and invasion in colorectal cancer cells.

Colorectal cancer (CRC) arises via the progressive accumulation of dysregulation in key genes including oncogenes and tumor-suppressor genes. Prostaglandin-endoperoxide synthase 2 (PTGS2, also called COX2) acts as an oncogenic driver in CRC. Here, we explored the upstream transcription factors (TFs) responsible for elevating PTGS2 expression in CRC cells. The results showed that PTGS2 silencing repressed cell growth, migration and invasion in HCT116 and SW480 CRC cells. The two fragments (499-981 bp) and (1053-1434 bp) were confirmed as the core TF binding profiles of the PTGS2 promoter. PTGS2 expression positively correlated with RUNX1 level in colon adenocarcinoma (COAD) samples using the TCGA-COAD dataset. Furthermore, RUNX1 acted as a positive regulator of PTGS2 expression by promoting transcriptional activation of the PTGS2 promoter via the 1086-1096 bp binding motif. In conclusion, our study demonstrates that PTGS2 upregulation induced by the TF RUNX1 promotes CRC cell growth, migration and invasion, providing an increased rationale for the use of PTGS2 inhibitors in CRC prevention and treatment.