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Incidence of intracerebral hemorrhage in Shangdong province, East China, 2012-2021: a population-based study
Mismatched Nucleotide Rejections at the Open and Ajar States of DNA Polymerase I Ensure High Fidelity
Integrating CAD, BIM, immersive technology, and 3D Gaussian Splatting for construction model coordination with ISO 19650
Annual flu vaccines are far from ideal — this is why
Study on hydrothermal coupling and frost heave characteristics of trapezoidal concrete-lined canals with gradient sand-gravel replacement in cold regions
Dynamic network models reveal personalized patterns of well-being in young adult daily lives
Could tracking animals’ health help to avert the next pandemic?
Machine learning prognosis model for locally recurrent rectal cancer patients after radioactive 125I seed implantation
Optimization design and experimental verification of magnetic pulse spot welding system of dissimilar metal sheets based on a field shaper
Environmental DNA reveals the distinct genetic diversity and evolutionary pathways of the Chinese Minnow Rhynchocypris oxycephalus in Korean freshwater systems
Comparative cohort study of pregabalin nortriptyline and pregabalin duloxetine in the management of diabetic peripheral neuropathic pain
Abstract Diabetic Peripheral Neuropathic Pain (DPNP) is a chronic complication affecting nearly half of individuals with diabetes. While monotherapies like pregabalin, duloxetine, and nortriptyline are frequently used, combination regimens may offer enhanced efficacy. Comparative studies of pregabalin–nortriptyline (PG-NT) and pregabalin–duloxetine (PG-DLX), especially in Indian populations, remain limited. A retrospective–prospective cohort study was conducted over five months at a tertiary care centre in South India. Sixty adults with DPNP, treated for at least two months with PG-NT or PG-DLX, were followed for nine weeks. Participants received either pregabalin–nortriptyline (dosed 150–300 mg/day and 10–75 mg/day, respectively) or pregabalin 150–300 mg/day with duloxetine 60 mg/day, for nine weeks. Efficacy was assessed using the Visual Analogue Scale (VAS), Insomnia Severity Index (ISI), and Hospital Anxiety and Depression Scale (HADS). Adverse events were documented. Both regimens significantly reduced pain scores. PG-DLX showed greater reductions in VAS (-2.23 vs. -1.35), ISI (-2.87 vs. -1.14), and HADS-A (-2.00 vs. -1.41). PG-DLX also significantly improved HADS-D scores (-1.70; p < 0.001), while PG-NT did not ( p = 0.076). Adverse events were mild but more frequent with PG-DLX (30% vs. 16.67%). Both combinations are effective for managing DPNP. However, PG-DLX demonstrated superior benefits in pain relief, sleep quality, and mood symptoms, with a modest increase in mild adverse events.
Celastrol suppresses bone destruction in rheumatoid arthritis by inhibiting ALOX5 expression in macrophages via the NF-κB pathway
Abstract Rheumatoid arthritis (RA) is a complex and highly disabling chronic autoimmune disease. As the disease progresses, patients often develop complications such as joint destruction and cardiovascular diseases, posing significant threats to human health. Celastrol, a major bioactive compound extracted from the traditional Chinese herb Tripterygium wilfordii Hook. f., exhibits potent immunomodulatory and anti-inflammatory properties. However, the specific mechanisms underlying its protective effects against bone destruction in RA remain poorly understood. To elucidate its potential therapeutic mechanisms, this study retrieved three gene expression datasets—GSE55235, GSE93777, and GSE200815—from the Gene Expression Omnibus (GEO) database. The primary molecular targets of celastrol were obtained from the HERB and TCMSP platforms. Functional mechanisms associated with these targets were explored using gene set variation analysis (GSVA) and weighted gene co-expression network analysis (WGCNA). Furthermore, molecular docking, immune infiltration analysis, and single-cell RNA sequencing analysis were employed to investigate the role of key target genes. In this study, thirteen potential target genes of celastrol in RA have been identified, including ADAMTS5 , AGTR1 , ALOX5 , CTSB , MMP3 , MMP9 , MYC , TNF , ITGA4 , ITGB7 , MMP1 , MMP13 , and PPARG . Among these, ALOX5 was found to significantly promote MMP3 protein expression, based on which a regulatory model with high predictive power was constructed. GSVA analysis revealed that the TNF-NFκB pathway was significantly activated in RA and exhibited a strong positive correlation with ALOX5 expression. Further experimental analysis demonstrated that knockdown of ALOX5 and its shared transcription factor with MMP2 resulted in a significant downregulation of both genes and inhibition of TNF-NFκB pathway activity. Single-cell transcriptomic analysis showed that ALOX5 was predominantly expressed in macrophages, and the AddModuleScore of celastrol-targeted genes in this cell type was significantly higher than in other cell types, suggesting that macrophages may serve as key effector cells in celastrol-mediated treatment of RA. Celastrol might attenuate RA bone destruction by inhibiting the expression of the ALOX5 gene in macrophages, thereby suppressing the activation of the NF-κB pathway and subsequently reducing the production of matrix metalloproteinases.
The hidden cost of video-call glitches
Hedyotis diffusae herba -Scutellaria Barbata herba drug pair suppresses prostate cancer by inducing apoptosis
Simulation study on the impact of check dams on water and sand in Xiliugou Basin and inner Mongolia section of the Yellow River
Molecular dynamics simulation of Sunset Yellow dye removal from water using hydrochar adsorbent
Abstract Water pollution by synthetic dyes poses a serious environmental threat, necessitating effective and sustainable remediation technologies. This study explores the molecular mechanisms of Sunset Yellow (SSY) dye removal using hydrochar adsorbents via molecular dynamics simulations. Three hydrochar models were designed representing standard (with mixed functional groups), pure aromatic, and hydroxyl-enriched. All exhibited high SSY adsorption, with the standard model achieving adsorption capacities of 74–460 mg/g depending on SSY concentration, and 90% average efficiency. Adsorption increased with hydroxyl group density and decreased in their absence. Molecular analysis revealed that van der Waals interactions and $$\pi$$ - $$\pi$$ stacking are the dominant mechanisms, with van der Waals forces being the strongest and scaling linearly with concentration. Hydroxyl functionalization enhanced adsorption by 35% compared to non-functionalized surfaces, while mixed functional groups offered the best balance of capacity and efficiency. The results demonstrate that functional group engineering critically influences adsorption performance, offering quantitative design principles for optimized hydrochar materials. These findings provide molecular-level insights to guide the development of advanced, sustainable adsorbents for water treatment.