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Epigallocatechin-3-gallate mitigates cerebral ischemia-reperfusion injury by promoting microglia toward M2 phenotype via Nrf2/HO-1 pathway
Abstract Ischemic stroke remains the leading disease in terms of global disability and fatality rates. Cerebral ischemia-reperfusion injury (CIRI) and neuroinflammation induced by CIRI represents a challenge for clinical therapy of ischemic stroke. Epigallocatechin-3-gallate (EGCG), the predominant catechin in green tea, is known to mitigate ischemic stroke and inflammation, while its role in regulating neuroinflammation post-recanalization remains unclear. This study aimed to explore the effect and mechanism of EGCG on the regulation of CIRI. The CIRI in vivo model was established by middle cerebral artery occlusion/reperfusion (MCAO/R) in rats and EGCG was administered via intracerebroventricular injection before MCAO/R. The neurological scores, infarct volume, neuronal injury, and microglial biomarkers were evaluated. BV2 cells subjected to oxygen–glucose deprivation/reoxygenation (OGD/R) were used to establish an in vitro CIRI model. After pretreatment with EGCG and/or ML385, OGD/R, cell viability, microglial biomarkers, pro-inflammatory and anti-inflammatory factors, and transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) and hemeoxygenase-1 (HO-1) were detected. Different conditioned media collected from BV2 cells were used for culturing the neuronal mimic cell line SH-SY5Y. EGCG administration in vivo significantly improved neurological deficits, infarct volume, and neuronal damage. Moreover, pretreatment with EGCG significantly increased BV2 cells viability and anti-inflammatory factors, and reduced toxicity and ferroptosis in SH-SY5Y cells. Furthermore, the upregulation of M2 markers was consistent with in vivo experiments. However, this protective effect was abolished by ML385, an Nrf2 inhibitor. EGCG upregulated Nrf2 and HO-1 protein expression, thus promoting microglial polarization toward the M2 phenotype. EGCG has a protective effect on CIRI by promoting the polarization of microglia toward the M2 phenotype via the Nrf2/HO-1 pathway to inhibit ferroptosis of neuron, which may provide a novel target for ischemic stroke treatment.
Acoustic-vibration characteristics of steel-spring floating-slab track based on acoustic wave superposition method
Clinical crown height changes in mandibular anterior teeth retained with two types of fixed retainers over two years: findings from a randomized clinical trial
Abstract This study aimed to assess longitudinal changes in lingual clinical crown height (CCH) in patients treated with two types of fixed mandibular retainers bonded to all six anterior teeth. This is a secondary analysis of a randomized, parallel-group clinical trial conducted in a single center, including 133 orthodontic patients (median age 24.6 years; interquartile range: 17.2–32.4 years). Participants were allocated in a 1:1 ratio to receive either a three-strand round twisted (RT) wire or an eight-strand rectangular braided (RB) wire retainer. The primary outcome in this analysis was the change in CCH, defined as the vertical distance from the incisal edge (or canine cusp tip) to the most apical point of the gingival margin on the lingual surface. Measurements were obtained from dental casts at baseline (T0), at retainer placement (T1), and at 3, 6, 12, 18, and 24 months thereafter. Measurement reproducibility was high, with intra- and inter-examiner agreement exceeding 0.89 (ICC). Across the observation period, CCH values showed minimal variation, with differences between consecutive time points remaining below 0.3 mm. Regression analysis indicated that retainer design was not a significant predictor of CCH changes. No adverse effects were observed during follow-up. Within the limits of this study, fixed retention bonded to all mandibular anterior teeth does not appear to influence lingual clinical crown height over a 24-month period. Trial registration : The trial was registered in ClinicalTrials.gov (NCT07476950).
Distributed Nash equilibrium seeking for second-order systems with finite/fixed-time convergence in the absence of velocity measurement
An adaptive modified Newton–Raphson-based optimizer for efficient optimal power flow performance under multiple operating conditions
Pangenome analysis of salmonella Paratyphi a reveals genetic diversity, antimicrobial resistance determinants, and public health implications
Searching for BBB permeable phytochemical inhibitors for targeting brain cancer associated HER2 protein through free energy calculations and pharmacokinetic analysis
Indoor PM2.5 levels and self-reported health symptoms in office workers during the haze seasons in Chiang Mai Thailand
Abstract This study investigated the impact of fluctuating indoor air-conditioned environments and seasonal air pollution on physical symptoms among office workers in Chiang Mai, Thailand. Using a longitudinal repeated measures design, the same cohort of 27 office workers was monitored over an 8-week period to capture variations between seasons. Indoor air quality parameters, including indoor PM2.5, CO 2 , temperature, and humidity, were monitored continuously during office hours. The multivariable binary logistic regression analysis, adjusted for age, gender, and office location, demonstrated that indoor PM2.5 concentrations were significantly associated with an increased likelihood of nasal symptoms (adjusted OR = 3.99, 95% CI: 1.48–10.76, p = 0.01). Furthermore, significant associations were observed with relative humidity and temperature, while no other statistically significant associations were found for ocular, respiratory, or skin symptoms in the balanced 25-participant cohort. These findings highlight that indoor fine particulate matter is a primary environmental factor related to health complaints in air-conditioned office settings, underscoring the need for targeted workplace policies during seasonal pollution episodes.
Explainable and clinically audited hybrid self-supervised framework for multi-class DFU classification and mobile deployment
Groundwater quality and health risks for drinking and irrigation in densely populated Qalyubia, Egypt
Abstract This study comprehensively assesses groundwater suitability for drinking and irrigation and evaluates the associated non-carcinogenic health risks for children and adults in the urban, densely populated Qalyubia Governorate, South Nile Delta, Egypt. Groundwater samples from ten sites were analyzed for thirteen chemical parameters. An integrated approach to water quality assessment was applied, using the Water Quality Index (WQI), multiple irrigation indices, the Metal Index (MI), and the Heavy Metal Pollution Index (HPI) against World Health Organization (WHO) and Egyptian water quality standards. Key findings reveal an apparent yet explainable divergence between the indices: while the WQI (22–36) and irrigation indices indicated good overall water quality for both drinking and irrigation, the Metal Index (MI: 0.81–3.29) signaled a “moderately affected” status. This contrast underscores that the WQI, which integrates a broad suite of physicochemical parameters, can reflect generally good conditions, whereas the MI is specifically sensitive to the presence of even low concentrations of potentially toxic elements (PTEs) such as Fe, Mn, Cd, As, Cr, Pb, Hg, Ni, and Zn. The HPI values (≤ 15) indicated minimal pollution from PTEs. No significant non-carcinogenic health risks were identified for the analyzed metals, though children were more susceptible than adults. The study concludes that although the groundwater is generally suitable for use, the MI results provide a critical early warning of moderate metal pollution, necessitating regular monitoring and preemptive measures to safeguard public health and water resources.
Postoperative dynamics of inflammatory markers in patients with uncomplicated recovery after colorectal cancer surgery: a preliminary inflammatory benchmarks study
Abstract Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide, with surgical resection as the cornerstone of curative therapy for localized disease. Surgery triggers a profound systemic inflammatory response that influences recovery, complications, and oncologic outcomes. While elevated NLR, PLR, and SII pre- or postoperatively predict adverse events like anastomotic leakage and poor survival, their normal temporal trajectories in uncomplicated cases remain poorly defined, hindering clinical interpretation. This preliminary study was conducted at two tertiary centers, screening 88 consecutive adults (≥ 18 years) undergoing elective curative (R0) CRC resection (stages I–III, open/laparoscopic). Inclusion required Clavien-Dindo grade ≤ I recovery (no intervention beyond symptomatic treatment; ERAS discharge criteria met) and complete blood counts (preop baseline ≤ 7 days, POD1/15/30). Exclusions: emergencies, immunosuppression, severe comorbidities (e.g., eGFR < 30, HbA1c > 10), neoadjuvant < 4 weeks prior, grade ≥ II complications (e.g., leak, sepsis, readmission). Only the uncomplicated cohort ( n = 47; median age 50 years; 62% female) was finally analyzed. EDTA-blood analyzed via automated hematology (neutrophils/lymphocytes/platelets); markers calculated; trajectories via Friedman test; 5th–95th percentile intervals. All markers declined significantly ( P < 0.001). NLR medians: POD1 12.5 (IQR 5.6–26.1), POD15 3.4 (2.5–6.4), POD30 2.6 (1.7–5.1); 95th percentiles 49.0 to 11.9. PLR: POD1 366.1 (223–682), POD15 244.9 (173–330), POD30 194.5 (129–319); 95th 1455 to 658.5. SII: POD1 3520 (1473–8806), POD15 1244 (757–2223), POD30 789 (470–1389); 95th 17,063 to 3311. Neutrophils fell (8.99 to 4.4 × 10^9/L), lymphocytes rose (0.71 to 1.25 × 10^9/L). Uncomplicated CRC resection recovery features rapid normalization of NLR, PLR, and SII over 30 days, providing preliminary time-specific percentile-based benchmarks for describing expected postoperative inflammatory trajectories. These findings should be interpreted as exploratory and require validation in larger multicenter cohorts before clinical application.
Prevalence of elevated liver enzymes and its associated factors among people living with HIV on dolutegravir-based ART at Debre Markos Comprehensive Specialized Hospital, Ethiopia
CASE-GANet : Context-aware and semantic-enhanced generative adversarial network for infrared and visible image fusion
Exploring feature limitations in antimicrobial resistance prediction: machine learning and deep learning in A. baumannii
A hazard assessment framework for landslide-induced impulse waves in high-dam reservoir
Secure multi-party biometric verification using QKD assisted quantum oblivious transfer
Modeling the impact of prevalence-driven public awareness on dengue dynamics and optimizing multi-intervention control strategies
Comparative analysis of CNN–LSTM and CNN–BiLSTM hybrid deep learning models for solar radiation prediction
Abstract Solar radiation forecasting is a complex task since the radiation signal is nonlinear, intermittent and is significantly influenced by meteorological variability, which makes it vital for PV planning, renewable energy planning and stability of the smart grid. In this work, a replicable comparison between CNN–LSTM and CNN–BiLSTM models for one-step ahead solar clearness-index forecasting based on multivariate climate variables from NASA POWER dataset for Delhi, India, is presented. Under identical preprocessing, windowing, chronological splitting, and training conditions, CNN–LSTM achieved MAE = 0.0880, RMSE = 0.1100, R2 = 0.3100, EVS = 0.3154, WI = 0.6317, and APB = 1.89%, whereas CNN–BiLSTM obtained MAE = 0.1015, RMSE = 0.1224, R2 = 0.1456, EVS = 0.1998, WI = 0.5261, and APB = 5.98%. The Skill Scores shown and the negative values for direct clearness-index prediction do not imply that the persistence reference was unattainable, but rather reveal that the results are a controlled model-to-model comparison and not evidence of state-of-the-art superiority. Reconstructed all-sky irradiance produced stronger agreement with observations (MAE = 0.4353, RMSE = 0.5417, R2 = 0.7884, EVS = 0.7965, WI = 0.9299, and APB = 3.90%). The main task of CNN–LSTM is to provide a practical balance between accuracy and efficiency in this experimental context, and further testing with other locations, more powerful baselines and probabilistic forecasting techniques is needed.