The Development of a Counseling Service Questionnaire: Study of Validation and Reliability

The study developed items of a counseling service questionnaire to aid counselors and universities in supporting students’ mental health. The participants of this study were 1,022 Chinese college students from three universities in Thailand. The questionnaire included development items and content validity and reliability testing. The questionnaire contained 17 items covering four aspects: (1) developmental counseling; (2) adaptive counseling; (3) disorder counseling; and (4) intervention in psychological crises. The results showed that the counseling services questionnaire is a valid and reliable instrument that can be used to determine students’ mental health

LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs

In this work, we leverage pre-trained Large Language Models (LLMs) to enhance time-series forecasting. Mirroring the growing interest in unifying models for Natural Language Processing and Computer Vision, we envision creating an analogous model for long-term time-series forecasting. Due to limited large-scale time-series data for building robust foundation models, our approach LLM4TS focuses on leveraging the strengths of pre-trained LLMs. By combining time-series patching with temporal encoding, we have enhanced the capability of LLMs to handle time-series data effectively. Inspired by the supervised fine-tuning in chatbot domains, we prioritize a two-stage fine-tuning process: first conducting supervised fine-tuning to orient the LLM towards time-series data, followed by task-specific downstream fine-tuning. Furthermore, to unlock the flexibility of pre-trained LLMs without extensive parameter adjustments, we adopt several Parameter-Efficient Fine-Tuning (PEFT) techniques. Drawing on these innovations, LLM4TS has yielded state-of-the-art results in long-term forecasting. Our model has also shown exceptional capabilities as both a robust representation learner and an effective few-shot learner, thanks to the knowledge transferred from the pre-trained LLM

Mechanisms of and obstacles to iron cardiomyopathy in thalassemia

[[abstract]]Thalassemia is anemia of variable severity, arising from mutations of genes encoding the hemoglobin alpha and beta chains. Severe thalassemia is associated with iron overload, tissue lesions, and high risk for cardiovascular complications, and iron-mediated cardiomyopathy is the main cause of death in this condition. Thalassemia major (TM) patients exhibit cardiovascular abnormalities consistent with chronic anemia; these include enlargement of the ventricular chambers, increased cardiac output, and reduced total vascular resistance. Cardiac iron overload in TM patients due to long-term transfusion can cause further chamber dilation, decreased contractility, and arrhythmia. Paradoxically, many such patients remain asymptomatic until decompensation occurs. For decades, magnetic resonance imaging and echocardiography have been performed to detect advanced cardiac dysfunction; however, reliable evaluation tools for the early detection of cardiac abnormalities are currently in demand. This article reviews the mechanisms underlying the development of heart disease in thalassemia and strategies for therapeutic intervention in TM patients with congestive heart failure

Endothelial toll-like receptor 4 maintains lung integrity via epigenetic suppression of p16INK4a.

We previously reported that the canonical innate immune receptor toll-like receptor 4 (TLR4) is critical in maintaining lung integrity. However, the molecular mechanisms via which TLR4 mediates its effect remained unclear. In the present study, we identified distinct contributions of lung endothelial cells (Ec) and epithelial cells TLR4 to pulmonary homeostasis using genetic-specific, lung- and cell-targeted in vivo methods. Emphysema was significantly prevented via the reconstituting of human TLR4 expression in the lung Ec of TLR4-/- mice. Lung Ec-silencing of TLR4 in wild-type mice induced emphysema, highlighting the specific and distinct role of Ec-expressed TLR4 in maintaining lung integrity. We also identified a previously unrecognized role of TLR4 in preventing expression of p16INK4a , a senescence-associated gene. Lung Ec-p16INK4a -silencing prevented TLR4-/- induced emphysema, revealing a new functional role for p16INK4a in lungs. TLR4 suppressed endogenous p16INK4a expression via HDAC2-mediated deacetylation of histone H4. These findings suggest a novel role for TLR4 in maintaining of lung homeostasis via epigenetic regulation of senescence-related gene expression

Structural basis for tetraspanin functions as revealed by the cryo-EM structure of uroplakin complexes at 6-Å resolution

Tetraspanin uroplakins (UPs) Ia and Ib, together with their single-spanning transmembrane protein partners UP II and IIIa, form a unique crystalline 2D array of 16-nm particles covering almost the entire urothelial surface. A 6 Å–resolution cryo-EM structure of the UP particle revealed that the UP tetraspanins have a rod-shaped structure consisting of four closely packed transmembrane helices that extend into the extracellular loops, capped by a disulfide-stabilized head domain. The UP tetraspanins form the primary complexes with their partners through tight interactions of the transmembrane domains as well as the extracellular domains, so that the head domains of their tall partners can bridge each other at the top of the heterotetramer. The secondary interactions between the primary complexes and the tertiary interaction between the 16-nm particles contribute to the formation of the UP tetraspanin network. The rod-shaped tetraspanin structure allows it to serve as stable pilings in the lipid sea, ideal for docking partner proteins to form structural/signaling networks

Real value prediction of protein solvent accessibility using enhanced PSSM features

<p>Abstract</p> <p>Background</p> <p>Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from one-dimensional sequences. Traditionally, predicting solvent accessibility is regarded as either a two- (exposed or buried) or three-state (exposed, intermediate or buried) classification problem. However, the states of solvent accessibility are not well-defined in real protein structures. Thus, a number of methods have been developed to directly predict the real value ASA based on evolutionary information such as position specific scoring matrix (PSSM).</p> <p>Results</p> <p>This study enhances the PSSM-based features for real value ASA prediction by considering the physicochemical properties and solvent propensities of amino acid types. We propose a systematic method for identifying residue groups with respect to protein solvent accessibility. The amino acid columns in the PSSM profile that belong to a certain residue group are merged to generate novel features. Finally, support vector regression (SVR) is adopted to construct a real value ASA predictor. Experimental results demonstrate that the features produced by the proposed selection process are informative for ASA prediction.</p> <p>Conclusion</p> <p>Experimental results based on a widely used benchmark reveal that the proposed method performs best among several of existing packages for performing ASA prediction. Furthermore, the feature selection mechanism incorporated in this study can be applied to other regression problems using the PSSM. The program and data are available from the authors upon request.</p

MicroRNA-146a-5p Mediates High Glucose-Induced Endothelial Inflammation via Targeting Interleukin-1 Receptor-Associated Kinase 1 Expression

Background and Aims: Interleukin-1 receptor-associated kinase-1 (IRAK-1) is critical for mediating toll-like receptor and interleukin-1 receptor signaling. In this study, we have examined whether IRAK-1 expression is altered in high glucose (HG)-stimulated human aortic endothelial cells (HAECs), and whether microRNAs (miRs) target IRAK-1 to regulate HG-induced endothelial inflammation.Methods: HAECs were treated with HG for 24 and 48 h. Real-time PCR, Western blot, monocyte adhesion assay, bioinformatics analysis, TaqMan® arrays, microRNA mimic or inhibitor transfection, luciferase reporter assay and siRNA IRAK-1 transfection were performed. The aortic tissues from db/db type 2 diabetic mice were examined by immunohistochemistry staining.Results: HG time-dependently increased IRAK-1 mRNA and protein levels in HAECs, and was associated with increased VCAM-1/ICAM-1 gene expression and monocyte adhesion. Bioinformatic analysis, TaqMan® arrays, and real-time PCR were used to confirm that miR-146a-5p, miR-339-5p, and miR-874-3p were significantly downregulated in HG-stimulated HAECs, suggesting impaired feedback restraints on HG-induced endothelial inflammation via IRAK-1. However, only miR-146a-5p mimic transfection reduced the HG-induced upregulation of IRAK-1 expression, VCAM-1/ICAM-1 expression, and monocyte adhesion. Additionally, IRAK-1 depletion reduced HG-induced VCAM-1/ICAM-1 gene expression, and monocyte adhesion, indicating that HG-induced endothelial inflammation was mediated partially through IRAK-1. In vivo, intravenous injections of miR-146a-5p mimic prevented endothelial IRAK-1 and ICAM-1 expression in db/db mice.Conclusion: These results suggest that miR-146a-5p is involved in the regulation of HG-induced endothelial inflammation via modulation of IRAK-1; indicating that miR-146a-5p may be a novel target for the treatment of diabetic vascular complications