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Autosomal-recessive cutis laxa type 2 (ARCL2) is a rare genetic disorder caused by pyrroline-5-carboxylate reductase 1 (PYCR1) mutations and characterized by loose and sagging skin, typical facial features, intrauterine growth retardation, and developmental delay. To study the effect of PYCR1 mutations on protein function and clinical features, we identified a homozygous missense mutation c.559G > A (p.Ala187Thr) in PYCR1 in a Chinese child with typical clinical features, especially severe developmental delays. The three-dimensional (3D) model showed the modification of the hydrogen bonds produce a misfolding in the mutant PYCR1 protein. Mutagenesis and enzyme assay study revealed decreased activity of the mutant protein in vitro, indicating that this mutation impairs PYCR1 function. Our findings confirmed abnormal enzymatic activity and neurodevelopmental trajectory of this PYCR1 mutation. [ABSTRACT FROM AUTHOR]

The combined use of multiple medications is common in treatment, which may lead to severe drug–drug interactions (DDIs). Deep learning methods have been widely used to predict DDIs in recent years. However, current models need help to fully understand the characteristics of drugs and the relationships between these characteristics, resulting in inaccurate and inefficient feature representations. Beyond that, existing studies predominantly focus on analyzing a single DDIs, failing to explore multiple similar DDIs simultaneously, thus limiting the discovery of common mechanisms underlying DDIs. To address these limitations, this research proposes a method based on M-Transformer and knowledge graph for predicting DDIs, comprising a dual-pathway approach and neural network. In the first pathway, we leverage the interpretability of the transformer to capture the intricate relationships between drug features using the multi-head attention mechanism, identifying and discarding redundant information to obtain a more refined and information-dense drug representation. However, due to the potential difficulty for a single transformer model to understand features from multiple semantic spaces, we adopted M-Transformer to understand the structural and pharmacological information of the drug as well as the connections between them. In the second pathway, we constructed a drug–drug interaction knowledge graph (DDIKG) using drug representation vectors obtained from M-Transformer as nodes and DDI types as edges. Subsequently, drug edges with similar interactions were aggregated using a graph neural network (GNN). This facilitates the exploration and extraction of shared mechanisms underlying drug–drug interactions. Extensive experiments demonstrate that our MTrans model accurately predicts DDIs and outperforms state-of-the-art models. [ABSTRACT FROM AUTHOR]

Developing durable electrocatalysts with high performance for hydrogen evolution reaction (HER) in acid conditions is of prime challenge for hydrogen production. Durability is of important prerequisite for catalyst application. Herein, this work constructs the Co‐doped WO3 loaded with Pt nanoparticles under ammonia treatment (Pt/N‐CoWO3) with the Pt‐N/O‐W interaction, which shows excellent activity and stability for acidic hydrogen production at industrial current density. The electronic structure of Pt species is modulated with enhanced Pt‐N/O bonding by Co doping, hence reinforcing the metal‐support interaction, and greatly enhancing the stability of the catalyst under high current density in acidic media. The resultant Pt/N‐CoWO3 catalyst exhibits the overpotentials of only 94 and 108 mV at high current densities of 1 and 2 A cm−2, respectively. More impressively, Pt/N‐CoWO3 delivers a record operation for acid electrocatalytic hydrogen evolution over 2000 h at 1 A cm−2, denoting its potential for catalyst applications at the industrial current density. This work opens a new avenue for developing Pt‐loading acidic HER catalysts for long‐term operation at ampere‐level current densities in acid conditions. [ABSTRACT FROM AUTHOR]

Background: Prostatic fibrosis, characterized by the accumulation of myofibroblasts and collagen deposition, is closely associated with LUTS and may lead to mechanical obstruction of the urethra. Additionally, Metabolic Syndrome (MetS), characterized by central obesity, high blood sugar, lipid metabolism disorders, and hypertension, is increasingly recognized as a proinflammatory condition linked to prostate inflammation. Methods: Clinical data from 108 subjects who underwent transurethral resection of the prostate or bipolar plasmakinetic enucleation of the prostate were prospectively collected between June 2021 and August 2022. Patients were divided in two groups according to whether or not they had a diagnosis of MetS. Specimens were stained with Masson trichrome and the periurethral prostatic fibrosis extent was evaluated using quantitative morphometry. Results: Forty-three patients (39.8%) were diagnosed with MetS. Patients with MetS showed a significantly greater extent of prostatic fibrosis than the others (68.1 ± 17.1% vs. 42.5 ± 18.2%, P < 0.001), and there was a positive correlation between the number of positive MetS parameters and the extent of prostatic fibrosis (R2 = 0.4436, P < 0.001). Multivariate regression analysis revealed that central obesity (B = 2.941, 95% confidence interval, 1.700–3.283), elevated fasting glucose (B = 1.036, 95% confidence interval, 0.293–1.780), reduced HDL cholesterol (B = 0.910, 95% confidence interval, 0.183–1.636) and elevated triglycerides (B = 1.666, 95% confidence interval, 0.824–2.508) were positively correlated to prostatic fibrosis. Elevated blood pressure, however, was unrelated to prostatic fibrosis (B = 0.009, 95% confidence interval, -0.664–0.683). Conclusions: The present findings suggest that prostatic fibrosis is positively correlated with MetS and its components including central obesity, elevated fasting glucose, reduced high density lipoprotein cholesterol and elevated triglycerides. [ABSTRACT FROM AUTHOR]

Abandoned cropland is a great waste of land resources, which not only affects the stability of food production, but also wastes limited cropland resources. China has large areas of abandoned cropland, and accurately extracting the large-scale abandoned cropland is a prerequisite for the government to implement reclamation policies and estimate the food production potential of abandoned cropland. China has implemented the Grain for Green Project (GGP) since 1980, but most research has not considered its impact on the extraction of abandoned cropland. Therefore, a method was proposed to identify abandoned cropland excluding the regions of GGP, and to analyze the spatio-temporal characteristics and potential of abandoned cropland in China from 1991 to 2018. GGP potential and food production potential of abandoned cropland were discussed. The results showed that 26.47 million hectares of cropland has been abandoned in the past 28 years (including cropland that has been reclaimed). Under the positive influence of the government's food security policy, the abandoned cropland has decreased in recent years, but the total area is still high. The abandonment mainly occurred in the Jiangnan Hills, the Hilly Regions of Fujian and Guangdong Province, the North China Mountains, and Eastern Inner Mongolia. The higher the elevation and the steeper the slope, the higher the abandonment rate. In addition, the urban-rural income gap significantly affected the abandonment rate. This study drew the spatial and temporal distribution map of abandoned cropland in China with a spatial resolution of 30 m considering GGP. It provides an important basis for formulating reclamation and GGP policy. [ABSTRACT FROM AUTHOR]

Introduction: For locally advanced, inoperable esophageal cancer, concurrent chemoradiotherapy (CCRT) becomes the norm. Combining immunotherapy with radiotherapy has been shown to improve efficacy. Circulating tumor DNA (ctDNA) is a strong predictor of effectiveness and tumor recurrence and is indicative of minimal residual disease (MRD). Patients with inoperable stage II-III esophageal squamous cell carcinoma (ESCC) are enrolled in the ECMRD-001 trial to evaluate changes in MRD status before and after CCRT combined with immunotherapy and adjuvant immunotherapy following neoadjuvant immunochemotherapy., Methods and Analysis: The ECMRD-001 trial is a prospective cohort study. Eligible patients will receive radical concurrent chemoradiotherapy combined with immunotherapy after neoadjuvant immunochemotherapy, followed by adjuvant immunotherapy for at least one year. Follow-up will be up to three years. MRD-related blood and tissue samples and T-cell immunohistobank related blood and tissue samples collected before, during and after treatment and follow-up will be grouped into sample collection time points. The relationship between MRD status at different time points and treatment efficacy is the primary outcome. Correlation between MRD status and immune microenvironment, radiotherapy dose, and tumor recurrence are the secondary outcomes. Examination of ctDNA mutations is the exploratory outcome., Discussion: ctDNA-based MRD may be a potential predictive marker for the efficacy and tumor recurrence of inoperable ESCC patients. Elevated ctDNA-MRD may predict tumor recurrence earlier than imaging. ctDNA-based MRD analysis and ctDNA-based MRD guided diagnosis and treatment should be implemented into clinical practice to improve efficacy and reduce tumor recurrence of inoperable stage II-III ESCC., Trial Registration: The ECMRD-001 study has been registered at ClinicalTrials.gov as NCT05952661 (July 19, 2023), https://classic.clinicaltrials.gov/ct2/show/NCT05952661., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Zhang, Zhao, Song, Deng and Shen.)

Non-ST-segment elevation acute myocardial infarction (NSTEMI) is a life-threatening clinical emergency with a poor prognosis. However, there are no individualized nomogram models to identify patients at high risk of NSTEMI who may undergo death. The aim of this study was to develop a nomogram for in-hospital mortality in patients with NSTEMI to facilitate rapid risk stratification of patients. A total of 774 non-diabetic patients with NSTEMI were included in this study. Least Absolute Shrinkage and Selection Operator regression was used to initially screen potential predictors. Univariate and multivariate logistic regression (backward stepwise selection) analyses were performed to identify the optimal predictors for the prediction model. The corresponding nomogram was constructed based on those predictors. The receiver operating characteristic curve, GiViTI calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. The nomogram model consisting of six predictors: age (OR = 1.10; 95% CI: 1.05-1.15), blood urea nitrogen (OR = 1.06; 95% CI: 1.00-1.12), albumin (OR = 0.93; 95% CI: 0.87-1.00), triglyceride (OR = 1.41; 95% CI: 1.09-2.00), D-dimer (OR = 1.39; 95% CI: 1.06-1.80), and aspirin (OR = 0.16; 95% CI: 0.06-0.42). The nomogram had good discrimination (area under the curve (AUC) = 0.89, 95% CI: 0.84-0.94), calibration, and clinical usefulness. In this study, we developed a nomogram model to predict in-hospital mortality in patients with NSTEMI based on common clinical indicators. The proposed nomogram has good performance, allowing rapid risk stratification of patients with NSTEMI., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Prusogliptin is a potent and selective DPP-4 inhibitor. In different animal models, Prusogliptin showed potential efficacy in the treatment of type 2 diabetes. However, the knowledge of its pharmacokinetics and safety in patients with liver dysfunction is limited., Objectives: The present study evaluated the pharmacokinetics and safety of Prusogliptin in subjects with mild or moderate hepatic impairment compared with healthy subjects., Methods: According to the liver function of the subjects, we divided them into a mild liver dysfunction group, a moderate liver dysfunction group and a normal liver function group. All subjects in three groups received a single oral dose of Prusogliptin 100-mg tablets. Pharmacokinetics and safety index collection was carried out before and after taking the drug. Plasma pharmacokinetics of Prusogliptin were evaluated, and geometric least- -squares mean (GLSM) and associated 90% confidence intervals for insufficient groups versus the control group were calculated for plasma exposures., Results: After a single oral administration of 100 mg of Prusogliptin tablets, the exposure level of Prusogliptin in subjects with mild liver dysfunction was slightly higher than that in healthy subjects. The exposure level of Prusogliptin was significantly increased in subjects with moderate liver dysfunction. There were no adverse events in this study., Conclusion: The exposure level of Prusogliptin in subjects with liver dysfunction was higher than that in healthy subjects. No participant was observed of adverse events. Prusogliptin tablets were safe and well tolerated in Chinese subjects with mild to moderate liver dysfunction and normal liver function., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)