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The boundedness and compactness of weighted composition operators on the logarithmic Bloch-Orlicz space [Formula: see text] are investigated in this paper.The boundedness and compactness of weighted composition operators on the logarithmic Bloch-Orlicz space [Formula: see text] are investigated in this paper.

Alcohol use disorder (AUD) is a prominent contributor to global morbidity and mortality. Its complex etiology involves genetics, epigenetics, and environmental factors. We review progress in understanding the genetics and epigenetics of AUD, summarizing the key findings. Advancements in technology over the decades have elevated research from early candidate gene studies to present-day genome-wide scans, unveiling numerous genetic and epigenetic risk factors for AUD. The latest GWAS on more than one million participants identified more than 100 genetic variants, and the largest epigenome-wide association studies (EWAS) in blood and brain samples have revealed tissue-specific epigenetic changes. Downstream analyses revealed enriched pathways, genetic correlations with other traits, transcriptome-wide association in brain tissues, and drug-gene interactions for AUD. We also discuss limitations and future directions, including increasing the power of GWAS and EWAS studies as well as expanding the diversity of populations included in these analyses. Larger samples, novel technologies, and analytic approaches are essential; these include whole-genome sequencing, multiomics, single-cell sequencing, spatial transcriptomics, deep-learning prediction of variant function, and integrated methods for disease risk prediction.

Inadvertent intraoperative hypothermia is frequent during open surgeries; however, few studies on hypothermia during laparoscopic abdominal surgery have been reported. We aimed to investigate the incidence and risk factors for hypothermia in patients undergoing laparoscopic abdominal surgery. This single-center prospective cohort observational study involved patients undergoing laparoscopic surgery between October 2018 and June 2019. Data on core body temperature and potential variables were collected. A multivariate logistic regression analysis was performed to identify the risk factors associated with hypothermia. A Cox regression analysis was used to verify the sensitivity of the results. In total, 690 patients were included in the analysis, of whom 200 (29.0%, 95% CI: 26%-32%) had a core temperature < 36°C. The core temperature decreased over time, and the incident hypothermia increased gradually. In the multivariate logistic regression analysis, age (OR = 1.017, 95% CI: 1.000-1.034, P = 0.050), BMI (OR = 0.938, 95% CI: 0.880-1.000; P = 0.049), baseline body temperature (OR = 0.025, 95% CI: 0.010-0.060; P < 0.001), volume of irrigation fluids (OR = 1.001, 95% CI: 1.000-1.001, P = 0.001), volume of urine (OR = 1.001, 95% CI: 1.000-1.003, P = 0.070), and duration of surgery (OR = 1.010, 95% CI: 1.006-1.015, P < 0.001) were significantly associated with hypothermia. In the Cox analysis, variables in the final model were age, BMI, baseline body temperature, volume of irrigation fluids, blood loss, and duration of surgery. Inadvertent intraoperative hypothermia is evident in patients undergoing laparoscopic surgeries. Age, BMI, baseline body temperature, volume of irrigation fluids, and duration of surgery are significantly associated with intraoperative hypothermia.

Ischemic stroke (IS) is a common neurological disorder associated with high disability rates and mortality rates. At present, recombinant tissue plasminogen activator (r-tPA) is the only US(FDA)-approved drug for IS. However, due to the narrow therapeutic window and risk of intracerebral hemorrhage, r-tPA is currently used in less than 5% of stroke patients. Natural compounds have been widely used in the treatment of IS in China and have a wide range of therapeutic effects on IS by regulating multiple targets and signaling pathways. The keywords “ischemia stroke, traditional Chinese Medicine, Chinese herbal medicine, natural compounds” were used to search the relevant literature in PubMed and other databases over the past five years. The results showed that JAK/STAT, NF-κB, MAPK, Notch, Nrf2, and PI3K/Akt are the key pathways, and SIRT1, MMP9, TLR4, HIF-α are the key targets for the natural compounds from traditional Chinese medicine in treating IS. This study aims to update and summarize the signaling pathways and targets of natural compounds in the treatment of IS, and provide a base of information for the future development of effective treatments for IS.

Objective We analyzed the impact of mind mapping on the critical thinking ability of clinical nursing students and its use as a teaching application. This study provides reference information for clinical teaching. Methods We selected 64 nursing students using convenience sampling. Participants received basic knowledge training of mind mapping in three sessions during the intervention. Questionnaires on critical thinking ability were designed by the researchers, adopting the Chinese version of the Critical Thinking Disposition Inventory. Data collected using the questionnaires included learning strategy function and clinical skill improvement with mind mapping, as well as students’ degree of adaptability to mind mapping. Participants’ critical thinking ability before and after the intervention was analyzed using a paired t-test. Results The critical thinking inclination of nursing students was significantly improved after intervention compared with that before the intervention (t = −0.74). The four dimensions of open-mindedness, inquisitiveness, cognitive maturity, and systematicity among nursing students after the intervention were also significantly improved compared with before the intervention. Conclusion Mind mapping is conducive to improving the critical thinking ability of clinical nursing students.

Background PTH plays a crucial role in bone remodelling by regulating bone formation. Pre-collagen type 1 N-terminal peptide (P1NP) is a key biomarker indicative of new bone formation. However, the relationship between PTH levels and P1NP levels in patients with osteoporotic fractures (OPFs) has not been fully elucidated. Methods This study analyzed data from 588 OPFs patients hospitalized between January 2015 and March 2022. Serum P1NP concentration serve as the dependent variable, while PTH level serve as the exposure variable. Covariates included age, gender; Charlson comorbidity index (CCI), body mass index (BMI), lymphocyte, neutrophil, monocyte, low-density lipoprotein (LDL), platelet, triglyceride, albumin, hemoglobin. Generalized estimating equations were used to assess the independent association between PTH and P1NP levels, adjusting for covariates. Non-linear relationships were evaluated using generalized additive models. Results This study found a positive association between PTH level and P1NP level in patients with OPFs (β = 0.59; 95% CI [confident interval] = 0.22 to 0.96; P  = 0.0018). This association remained significant after multivariate adjustment. Moreover, the nonlinear model showed a threshold effect, with PTH level below 16.63 (pg/mL) being positively correlated with P1NP (β = 1.69; 95% CI = 0.90 to 2.47; P  < 0.0001). However, this correlation did not hold true for PTH level above 16.63 (pg/mL) (β = 0.37; 95% CI = -0.34 to 1.07; P  = 0.3091). Conclusion This study identified an inflection point and a nonlinear, threshold effect in the relationship between PTH and P1NP levels. Further research is needed to confirm these findings.

Background It is crucial to investigate protein functions in specific subcellular environments. Cross-linking mass spectrometry is a powerful tool to map the direct interactome of proteins by identifying inter-protein cross-links. However, it is challenging to identify inter-protein cross-linked peptides due to their low abundance. Results We chemically synthesize the cross-linkers ePDES1 and ePDES2 with an alkyne group and a compound with azide linked to a phosphate group to enrich for cross-linked peptides. Conclusion Based on the high-quality cross-linking spectra of ePDES1 and ePDES2, our methods achieve the identification of hundreds of directly interacting proteins or substrates of thioredoxins in the nucleus and mitochondria.

Diabetic nephropathy (DN) is the primary cause of end-stage renal disease, but existing therapeutics are limited. Therefore, novel molecular pathways that contribute to DN therapy and diagnostics are urgently needed. Based on the Gene Expression Omnibus (GEO) database and Limma R package, we identified differentially expressed genes of DN and downloaded oxidative stress-related genes based on the Genecard database. Then, immune and oxidative stress-related hub genes were screened by combined WGCNA, machine learning, and protein-protein interaction (PPI) networks and validated by external validation sets. We conducted ROC analysis to assess the diagnostic efficacy of hub genes. The correlation of hub genes with clinical characteristics was analyzed by the Nephroseq v5 database. To understand the cellular clustering of hub genes in DN, we performed single nucleus RNA sequencing through the KIT database. Ultimately, we screened three hub genes, namely CD36, ITGB2, and SLC1A3, which were all up-regulated. According to ROC analysis, all three demonstrated excellent diagnostic efficacy. Correlation analysis revealed that the expression of hub genes was significantly correlated with the deterioration of renal function, and the results of single nucleus RNA sequencing showed that hub genes were mainly clustered in endothelial cells and leukocyte clusters. By combining three machine learning algorithms with WGCNA analysis, this research identified three hub genes that could serve as novel targets for the diagnosis and therapy of DN.

Retinal vessel segmentation in fundus images is critical for diagnosing microvascular and ophthalmologic diseases. However, the task remains challenging due to significant vessel width variation and low vessel-to-background contrast. To address these limitations, we propose WDM-UNet, a novel spatial-wavelet dual-domain fusion architecture that integrates spatial and wavelet-domain representations to simultaneously enhance the local detail and global context. The encoder combines a Deformable Convolution Encoder (DCE), which adaptively models complex vascular structures through dynamic receptive fields, and a Wavelet Convolution Encoder (WCE), which captures the semantic and structural contexts through low-frequency components and hierarchical wavelet convolution. These features are further refined by a Gated Fusion Transformer (GFT), which employs gated attention to enhance multi-scale feature integration. In the decoder, depthwise separable convolutions are used to reduce the computational overhead without compromising the representational capacity. To preserve fine structural details and facilitate contextual information flow across layers, the model incorporates skip connections with a hierarchical fusion strategy, enabling the effective integration of shallow and deep features. We evaluated WDM-UNet in three public datasets: DRIVE, STARE, and CHASE_DB1. The quantitative evaluations demonstrate that WDM-UNet consistently outperforms state-of-the-art methods, achieving 96.92% accuracy, 83.61% sensitivity, and an 82.87% F1-score in the DRIVE dataset, with superior performance across all the benchmark datasets in both segmentation accuracy and robustness, particularly in complex vascular scenarios.

Although many efforts have been devoted to the adsorptive removal of phosphate from aqueous solutions and eutrophic water, it is still highly desirable to develop novel adsorbents with high adsorption capacities. In this study, Fe-based metal-organic frameworks (MOFs), MIL-101 and NH 2 -MIL-101, are fabricated through a general facile strategy. Their performance as an adsorbent for phosphate removal is investigated. Experiments are performed to study the effects of various factors on the phosphate adsorption, including adsorbent dosage, contact time and co-existing ions. Both MIL-101(Fe) and NH 2 -MIL-101(Fe) show highly effective removal of phosphates from aqueous solutions, and the concentration of phosphates decrease sharply from the initial 0.60 mg·L −1 to 0.045 and 0.032 mg·L −1 , respectively, within just 30 min of exposure. The adsorption kinetics and adsorption isotherms reveal that NH 2 -MIL-101(Fe) has higher adsorption capacity than MIL-101(Fe) possibly due to the amine group. Furthermore, the Fe-based MOFs also exhibit a high selectivity towards phosphate over other anions such as chloride, bromide, nitrate and sulfate. Particularly, the prepared Fe-based MIL-101 materials are also capable of adsorbing phosphate in an actual eutrophic water sample and display better removal effect.