Search Results (7,155)

Objectives: Neuroinflammation is recognized as a significant characteristic of Alzheimer’s disease (AD). Currently, there is a notable absence of effective pharmacological agents to prevent or treat neuroinflammatory processes associated with AD. Heat shock protein 70 (HSP70) is pivotal in the progression of neuroinflammation. In this study, we explored the potential of maltol, a Maillard reaction product derived from red ginseng, as a therapeutic agent for neuroinflammation. Methods: In vitro, HMC3 microglial cell models were developed to examine the regulatory effects of gradient concentrations of maltol (12.5, 25, 50 μM) on the TLR4/MyD88/NF-κB p65 signaling pathway, neuroinflammation, and pyroptosis. Analyses of the GEO database and Gene Set Enrichment Analysis (GSEA) were performed to identify the core targets of maltol, followed by HSP70 gene silencing experiments to validate the targeted regulatory mechanism. Results: Maltol significantly mitigated LPS-induced neuronal damage and cognitive deficits in mice. It effectively suppressed microglia-mediated neuroinflammation and pyroptosis, reversed oxidative stress-induced neuronal ferroptosis, and inhibited neuronal apoptosis. In vitro experiments demonstrated that maltol obstructed TLR4/MyD88 binding, thereby inhibiting NF-κB p65-mediated neuroinflammation and pyroptosis, while also alleviating excessive ROS accumulation to enhance oxidative stress and ferroptosis. Bioinformatics analysis identified HSP70 as a crucial target for the anti-inflammatory and antioxidant effects of maltol. Subsequent gene silencing experiments confirmed that maltol exerted its inhibitory effects on LPS-induced neuroinflammation and pyroptosis in an HSP70-dependent manner. Conclusions: Maltol exhibits significant protective effects against Alzheimer’s disease-related neuroinflammation, oxidative stress, pyroptosis, and ferroptosis through the targeting of HSP70. This study elucidates the molecular mechanisms by which maltol improves neuroinflammatory injury and provides a novel theoretical foundation and therapeutic strategy for the intervention of Alzheimer’s disease neuroinflammation using traditional Chinese medicine. Full article

Background and Objectives: ABO and Rh blood group systems represent clinically relevant genetic polymorphisms with established associations beyond transfusion medicine, including thrombotic risk. We investigated the prevalence of ABO and Rh blood group phenotypes in hemodialysis patients and their associations with documented vascular access thrombosis and all-cause mortality. Materials and Methods: This retrospective cohort study analyzed 3027 patients receiving maintenance hemodialysis in Hatay province, Türkiye, between January 2010 and April 2025. Data included ABO and Rh blood group determination, demographics, comorbidities, dialysis vintage, vascular access type, vascular access thrombosis events, and mortality. Multivariable binary logistic regression was used to identify independent factors associated with documented vascular access thrombosis. Multivariable Cox proportional hazards regression with vascular access thrombosis modeled as a time-dependent covariate was used to identify independent predictors of all-cause mortality. Results: Mean patient age was 63.95 ± 13.74 years; 58.3% were men. Blood group A was most prevalent (41.4%), followed by O (35.8%), B (15.9%), and AB (6.9%); 92.7% were Rh-positive. Documented vascular access thrombosis differed significantly by ABO group (p = 0.027), with the highest rate in group A (14.1%). In multivariable logistic regression, non-O blood group (OR 1.34, 95% CI 1.06–1.70; p = 0.014) and longer dialysis vintage (OR 1.01 per month, 95% CI 1.00–1.01; p < 0.001) were independently associated with documented vascular access thrombosis. In multivariable Cox regression, time-dependent vascular access thrombosis was independently associated with higher all-cause mortality (HR 1.33, 95% CI 1.12–1.59; p = 0.002), as were age (HR 1.02; p < 0.001), diabetes mellitus (HR 1.49; p < 0.001), coronary artery disease (HR 1.34; p < 0.001), and hypertension (HR 1.19; p < 0.001). Arteriovenous fistula was associated with lower mortality compared with temporary catheter (HR 0.46, 95% CI 0.37–0.58; p < 0.001). Blood group phenotype was not independently associated with all-cause mortality (all p > 0.5 vs. group O). Conclusions: In hemodialysis patients, non-O blood groups were modestly but independently associated with documented vascular access thrombosis, and vascular access thrombosis was independently associated with increased mortality when modeled as a time-dependent exposure. Blood group phenotype was not independently associated with mortality after adjustment for established risk factors. Blood group may contribute incrementally to vascular access risk awareness alongside established clinical risk factors, but its modest absolute risk difference limits standalone clinical utility. Full article

Background/Objectives: Artificial Intelligence (AI) integration in healthcare promises improved diagnostic accuracy, patient safety, and operational efficiency. However, AI acceptance among healthcare workers remains limited due to knowledge gaps, risk concerns, and governance challenges, particularly in developing countries like Saudi Arabia, where rapid healthcare modernization faces unique infrastructure, organizational, and cultural challenges. This research investigates the factors influencing AI acceptance among medical practitioners, nurses, administrators, and students in Saudi Arabian hospitals to identify key determinants and barriers to adoption. Methods: This cross-sectional study employed an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework integrated with ethical considerations from the Model for Ethical Assessment and Analysis of AI in Medicine (MEAAM). A structured bilingual questionnaire was administered to 119 healthcare professionals and students across Saudi Arabia, measuring constructs including Awareness and Knowledge, Performance Expectancy, Effort Expectancy, Facilitating Conditions, Social Influence, Trust, Perceived Risk, Ethical Governance, and Price Value. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for quantitative analysis, supplemented by thematic analysis of open-ended qualitative responses. Results: The PLS-SEM analysis explained 59.8% of variance in behavioral intention to adopt AI (R² = 0.598). Awareness and Knowledge emerged as the strongest predictor (β = +0.505, p < 0.001), followed by Performance Expectancy (β = +0.229, p < 0.05) and Social Influence (β = +0.123). Perceived Risk functioned as the primary barrier (β = −0.185, p < 0.05). Qualitative findings identified infrastructure gaps, regulatory ambiguities, and training deficiencies as major implementation barriers, while emphasizing opportunities in diagnostic accuracy and remote monitoring. Conclusions: AI acceptance in Saudi healthcare is primarily driven by knowledge, with perceived usefulness and peer support as secondary facilitators, while safety and accountability concerns remain substantial obstacles. Successful AI integration requires coordinated efforts in education, transparent governance frameworks, and institutional support. This study contributes theoretically by validating extended UTAUT in a non-Western healthcare context and practically by providing evidence-based strategies for sustainable AI adoption that enhance healthcare quality while respecting professional roles and ethical principles. Full article

Background: Artificial intelligence in medicine has largely relied on supervised training of disease-specific models, limiting scalability in conditions where labeled data are scarce. Large language models (LLMs), which encode broad medical knowledge through large-scale pretraining, offer an alternative paradigm in which structured physiological measurements can be interpreted directly without task-specific model training. Objective: To evaluate whether smartphone-derived ocular motor biomarkers can be translated into clinically meaningful probabilistic assessments of Huntington’s disease (HD) using general-purpose LLMs operating as inference engines. Methods: In this prospective proof-of-concept study, 26 participants (13 with genetically confirmed HD and 13 age-matched controls) completed a standardized ocular motor assessment using a custom smartphone application. Quantitative eye-movement metrics were validated against expert neurologist ratings. Structured physiological features were then provided to four general-purpose LLMs without task-specific training or diagnostic labels, and the models generated an AI-Assigned HD Probability Score (HAIPS). Discriminative performance and associations with clinical severity measures were evaluated. Results: Smartphone-derived ocular motor metrics showed strong agreement with clinician assessments (Spearman ρ = 0.76–0.95; all p < 0.001), confirming preservation of clinically meaningful physiological signals. LLM-derived HAIPS distinguished HD from controls with high accuracy (AUC 0.879–0.944), with no significant differences across models. Discrimination was statistically equivalent to a supervised logistic regression model trained on the same features. HAIPS correlated strongly with established measures of disease severity, including cognitive (MoCA, ρ = −0.86), functional (TFC, ρ = −0.74), and motor impairment (UHDRS, ρ = 0.85) (all p ≤ 0.003). Conclusions: Structured ocular motor biomarkers acquired using a consumer smartphone can be translated into clinically meaningful probabilistic assessments of HD by general-purpose LLMs without disease-specific model training. These findings support a framework in which physiologically grounded digital biomarkers are coupled with general-purpose inference models, potentially enabling scalable assessment in rare neurological diseases where labeled data are limited. Full article

Background: Pain is a prominent and disabling manifestation of inflammatory bowel disease (IBD), including abdominal, pelvic, musculoskeletal, axial, and neuropathic pain phenotypes. Patients referred to pain clinics represent a selected subgroup with clinically meaningful, persistent, refractory, or diagnostically complex pain. Objective: To characterize pain phenotypes, treatment patterns, interventional pain-care exposure, and utilization burden among patients with IBD evaluated in tertiary pain-clinic settings and to explore differences between Crohn’s disease and ulcerative colitis patients. Methods: We performed a retrospective electronic medical-record cohort study of patients with documented IBD who were evaluated in pain-clinic settings between 24 October 2010 and 14 May 2026. Repeated clinical entries were aggregated into unique visit dates and patient-level variables. IBD diagnosis, pain phenotypes, treatment documentation, interventional procedures, and pain-clinic utilization were summarized descriptively using counts, percentages, means, medians, interquartile ranges, and ranges as appropriate. Crohn’s disease and ulcerative colitis subgroups were compared using univariable odds ratios with 95% confidence intervals and two-sided p-values. Because repeated clinical entries could belong to the same patient, the primary analytic unit was the patient rather than the individual note. Results: The source dataset included 19,615 clinical entries representing 7053 unique pain-clinic visits among 596 unique patients with IBD. The cohort included 314 patients with Crohn’s disease (52.7%), 247 with ulcerative colitis (41.4%), and 35 with IBD-unclassified (5.9%). The mean number of pain-clinic visits per patient was 11.8, with a median of four visits (interquartile range, 1–11). The dominant patient-level pain phenotypes were limb or peripheral joint pain (395/596, 66.3%), back or axial spine pain (358/596, 60.1%), and abdominal or pelvic pain (246/596, 41.3%). Overall, 437 patients (73.3%) had documentation of at least one interventional pain procedure. Compared with ulcerative colitis, Crohn’s disease was associated with higher documentation of abdominal or pelvic pain (148/314, 47.1% vs. 82/247, 33.2%; odds ratio, 1.79; 95% confidence interval, 1.27–2.53; p = 0.001) and fibromyalgia-like or widespread pain (83/314, 26.4% vs. 39/247, 15.8%; odds ratio, 1.92; 95% confidence interval, 1.25–2.93; p = 0.0027). In contrast, radiofrequency procedures (59/314, 18.8% vs. 78/247, 31.6%; odds ratio, 0.50; 95% confidence interval, 0.34–0.74; p = 0.0005) and facet or medial branch procedures (79/314, 25.2% vs. 87/247, 35.2%; odds ratio, 0.62; 95% confidence interval, 0.43–0.89; p = 0.012) were less frequently documented in Crohn’s disease than in ulcerative colitis. Conclusions: Among patients with IBD referred to tertiary pain-clinic evaluation, pain was heterogeneous and predominantly musculoskeletal, axial, neuropathic, and procedurally targetable rather than exclusively visceral. These findings support structured, mechanism-based pain assessment integrated with gastroenterology, rheumatology, and pain-medicine care. Full article

Background: Recovery after major head-and-neck reconstruction extends beyond flap survival and wound closure, involving swallowing, psychological adaptation, body image, and overall quality of life. Integrated multidimensional assessments remain limited in routine reconstructive outcomes research. Aim: The aim of this study was to characterize and compare six-month multidimensional recovery—clinical, functional, nutritional, psychological, and body-image outcomes—between microvascular free-flap and regional pedicled-flap reconstruction and to identify factors that stratify risk for persistent functional and psychosocial impairment. Methods: We conducted a single-center prospective cohort study at the “Victor Babeș” University of Medicine and Pharmacy, Timișoara, Romania, enrolling 87 adults undergoing major reconstructive surgery after ablative treatment of head-and-neck defects (52 microvascular free flaps; 35 regional pedicled flaps). Patients were assessed at baseline and 6 months using the SF-36, WHOQOL-BREF, Body Image Scale (BIS), HADS, PHQ-9, GAD-7, Functional Oral Intake Scale (FOIS), speech intelligibility, and PEG/tracheostomy dependence. Results: At 6 months, most SF-36 and WHOQOL-BREF domains improved with moderate effect sizes (d = 0.3–0.7; all p ≤ 0.009), and body image distress decreased significantly (ΔBIS −2.9 ± 4.6; p < 0.001), whereas social functioning showed no robust gain (p = 0.098; not surviving false-discovery-rate correction). Pedicled reconstruction was associated with higher PEG dependence (37.1% vs. 9.6%; p = 0.005) and worse FOIS (4.7 ± 1.4 vs. 5.6 ± 1.2; p = 0.003). Major complications were linked to blunted or worsening psychological trajectories and a threefold higher rate of clinically significant depression (HADS-D ≥ 11: 66.7% vs. 18.7%; p = 0.001). In a reduced four-predictor multivariable model, pedicled flap (aOR 4.6), adjuvant radiotherapy (aOR 2.8), major complication (aOR 3.3), and lower baseline FOIS (aOR 0.5 per point) were independently associated with PEG dependence (optimism-corrected AUC 0.79). Clustering identified three recovery phenotypes—functional/emotional responders, psychological/body-image responders, and global slow recovery—with significantly different PEG rates (5.9%, 21.4%, 40.0%; p = 0.006). Exploratory mediation analysis suggested that the association between reconstruction technique and mental quality-of-life recovery was partly statistically accounted for by swallowing and body-image improvement. Conclusions: Recovery after major head-and-neck reconstruction is multidimensional and heterogeneous. Baseline swallowing function, reconstruction technique, radiotherapy, and major complications jointly stratify risk for persistent functional and psychosocial impairment, supporting risk-adapted multidisciplinary rehabilitation and early psycho-oncologic screening. Full article

Background: The management of diabetic foot disease and knee osteoarthritis (OA) with smart orthotics holds significant importance during the early stages of these conditions, given their potential consequences, including functional impairment, chronic pain, and economic burden. Real-time monitoring of plantar foot pressure enables early detection of abnormal force distribution and gait biomechanics, allowing for the redirection of forces away from affected ulcers or arthritic joints. This is the first systematic review to synthesise clinical evidence for smart orthotics technology with real-time plantar pressure sensor biofeedback across both diabetic foot ulcer prevention and knee osteoarthritis management simultaneously. A search of the PROSPERO register confirmed no existing registration covers this specific combination. Objectives: To examine the clinical evidence for the use of standard and smart orthotics in the prevention and management of diabetic foot ulcers (DFUs) and knee OA, and to evaluate their impact on plantar pressure redistribution, ulcer recurrence, pain, biomechanics, and economic burden. Eligibility criteria: Studies published in English involving human adult participants (≥18 years) with a clinical diagnosis of diabetes mellitus (at risk of DFU or with peripheral neuropathy) or knee OA, where the intervention involved any orthotic device or smart/intelligent insole with clinical outcomes reported, were included. Studies on healthy individuals only, those not reporting participant age, and non-weight-bearing protocols not differentiated from weight-bearing were excluded. Information sources: Five databases were searched: CINAHL (EBSCO Information Services, Ipswich, MA, USA), PubMed Advanced (National Library of Medicine, Bethesda, MD, USA), Wiley Online Library (John Wiley & Sons, Hoboken, NJ, USA), Cochrane Library (Cochrane Collaboration, London, UK), and Google Scholar (Google LLC, Mountain View, CA, USA). Searches were completed in May 2026. Methods: We conducted a comprehensive literature review. This review was structured and reported with reference to the PRISMA 2020 statement (Preferred Reporting Items for Systematic Reviews and Meta-Analysis; University of Ottawa, Ottawa, ON, Canada) to guide transparency of reporting. It does not constitute a full Cochrane-style systematic review; risk of bias assessment was applied to key included studies and GRADE (Grading of Recommendations Assessment, Development and Evaluation; McMaster University, Hamilton, ON, Canada) certainty ratings were applied informally and narratively rather than as formal per-outcome evidence profiles. Five databases were searched yielding 92,637 records. After removal of 398 duplicates by Rayyan, 92,239 records remained. A subsequent automated keyword-based relevance filter applied within Rayyan (Rayyan AI, Doha, Qatar), prior to human screening, excluded 84,572 records that did not contain any terms related to orthotics, diabetic foot, or knee osteoarthritis, yielding 7667 records for human title/abstract screening. A narrative synthesis approach was adopted owing to the heterogeneity of study designs and outcome measures across included studies, which precluded meta-analysis. This review was not prospectively registered. A complete list of all 78 included studies, including those not individually discussed in the results and discussion. Results: The available clinical studies report promising findings for orthotics and smart orthotics in pain reduction, ulcer prevention, and potential reduction in economic burden, though conclusions are limited by small sample sizes, heterogeneity, and predominantly open-label designs. Recent research found that orthotics can be used to alter the gait pattern that influences knee OA by reducing excessive force on the affected joint. A randomised controlled trial demonstrated an 80% relative risk reduction in DFU recurrence (RR = 0.20; 95% CI: 0.06–0.79; p = 0.022), with absolute event rates of 6.3% in the intervention group versus 30.8% in controls (ARR = 24.5%); a second trial reported a 71% reduction in ulcer incidence over 18 months; and a third randomised controlled trial demonstrated statistically significant plantar pressure reduction (p < 0.01) in patients with diabetic neuropathy. Conclusions: The available evidence suggests that orthotics may be associated with improved pressure redistribution, reduced ulcer incidence, and benefit in the management of knee OA. Although the number of studies directly comparing smart orthotics with standard orthotics remains limited, the limited comparative studies suggested that smart orthotics showed promising results in reducing ulcer incidence, providing the patient with real-time feedback to offload via their electronic devices. These findings, while preliminary, highlight the potential of smart orthotic technology as an adjunct to standard orthotic care in reducing the overall burden of diabetic foot disease and knee osteoarthritis. Limitations: The primary methodological limitation of this review is the open-label design of all included smart orthotic trials, which precludes participant blinding and introduces performance bias. However, this limitation is structural and inherent to the wearable technology field—analogous to surgical trials—and is substantially mitigated by the use of objective primary outcome measures (plantar pressure and ulcer recurrence) across the three included RCTs, the consistency of effect direction across independent RCTs conducted in different countries, and a narrative sensitivity analysis confirming robustness of findings (Risk of Bias Across Studies Section). Formal per-outcome GRADE evidence profiles were not produced; overall certainty of evidence was assessed narratively with reference to GRADE domains and is judged to be low to moderate for smart orthotics in DFU prevention and low for knee OA management, consistent with the Level 2–3 evidence base and open-label study designs. Future adequately powered, multi-site RCTs with standardised outcome reporting, minimum 24-month follow-up, and integrated health economic modelling are the highest priority to extend these preliminary findings. Registration: This review was not prospectively registered. Full article

Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor remains the cornerstone of antithrombotic management after myocardial revascularization. However, the traditional “one-size-fits-all” approach to DAPT duration and intensity fails to account for marked interindividual variability in drug response—driven by genetic polymorphisms, notably CYP2C19 variants like CYP2C19*2, which reach a frequency of up to 75% in specific groups like the Melanesian population—comorbidities such as diabetes and chronic kidney disease, and dynamic clinical factors including age and concomitant medications. We examine the current landscape of precision medicine tools for individualizing DAPT, including platelet function testing, point-of-care genotyping, validated clinical risk scores, and emerging artificial intelligence (AI)–based predictive models. Evidence from landmark trials is synthesized to evaluate escalation, de-escalation, and duration-tailoring strategies within the ischemic–bleeding trade-off framework. Special populations requiring individualized approaches are reviewed, including patients with atrial fibrillation, the elderly, and those requiring urgent noncardiac surgery with perioperative bridging. Future directions, including multi-omics integration, novel antiplatelet agents, and AI-driven clinical decision support systems, are also explored. As a narrative review, conclusions should be interpreted as reflective of current evidence synthesis rather than systematic-review-grade evidence, given the absence of formal risk-of-bias scoring or meta-analytic pooling. Personalized DAPT guided by complementary genetic and phenotypic testing, integrated with dynamic risk stratification, offers a paradigm shift from empiric therapy toward precision-guided antithrombotic management with the potential to simultaneously reduce ischemic and bleeding complications. Full article

Burn wound healing is a complex and dynamic process involving coordinated regulation of inflammation, oxidative stress, angiogenesis, and tissue remodeling. Polygonum cuspidatum, a traditional Chinese medicinal herb widely used for trauma- and inflammation-related disorders, represents an important source of bioactive compounds for tissue repair. Piceatannol (PIC), a naturally occurring stilbene constituent of P. cuspidatum, possesses potent anti-inflammatory and antioxidant activities; however, its therapeutic potential in burn wound healing remains insufficiently understood. In the present study, the therapeutic effects and underlying mechanisms of topical PIC were investigated using a murine deep second-degree burn model combined with multiple skin-related cellular models, including keratinocytes, fibroblasts, endothelial cells, and macrophages. PIC markedly accelerated wound closure and improved histological architecture, as evidenced by reduced inflammatory infiltration, enhanced collagen organization, and increased neovascularization. Mechanistically, PIC suppressed NF-κB activation and modulated KEAP1/NRF2-associated redox signaling, thereby alleviating inflammation–oxidative stress crosstalk during wound healing. In keratinocyte–fibroblast co-culture systems, PIC inhibited fibroblast-to-myofibroblast transition, reduced α-smooth muscle actin (α-SMA) expression, and attenuated excessive collagen deposition, suggesting anti-fibrotic activity. In addition, PIC promoted endothelial tube formation through activation of the STAT3–VEGF signaling axis. Collectively, these findings demonstrate that PIC facilitates burn wound repair through coordinated anti-inflammatory, antioxidative, pro-angiogenic, and anti-fibrotic effects. This study provides pharmacological support for the therapeutic potential of P. cuspidatum-derived compounds in burn management and highlights PIC as a promising candidate for topical treatment of burn injuries. Full article

Background/Objectives: The “small-n-large-p” dilemma in mammography artificial intelligence (AI)—where the number of candidate imaging features far exceeds the number of labeled cases—commonly results in model overfitting, unstable feature selection, and poor generalization across clinical settings. This study aims to reassess the internal performance of the HiTopology-GOA-CSA (Grasshopper Optimization Algorithm–Crow Search Algorithm) feature-selection framework for mammography using a larger real Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) cohort and a stricter leakage-aware evaluation strategy. Methods: In this retrospective computational study using public anonymized datasets, an expanded internal cohort of 98 CBIS-DDSM mass cases (49 benign, 49 malignant) was assembled from digital imaging and communications in medicine (DICOM) region of interest (ROI) series. A total of 1074 features were extracted per case, including 88 handcrafted radiomic descriptors and 986 EfficientNet-B5 deep features. HiTopology-GOA-CSA selected 102 features, corresponding to 91% feature reduction. Two internal evaluation modes were compared: Mode A, which matched the original pilot methodology by performing feature selection once on the full cohort before cross-validation, and Mode B, which used strict nested feature selection within training folds. Performance was assessed with 5-fold stratified cross-validation using a multilayer perceptron (MLP) classifier. Results: On the expanded cohort, Mode A achieved an area under the receiver operating characteristic curve (AUC) of 0.726 (95% CI: 0.594–0.858), sensitivity of 0.658, specificity of 0.651, and F1-score of 0.644. Under the stricter nested evaluation, Mode B achieved AUC of 0.683 (95% CI: 0.549–0.817), sensitivity of 0.598, specificity of 0.631, and F1-score of 0.595. Mean pairwise Jaccard similarity across nested folds was 0.604, indicating moderate feature stability. Benchmark comparisons showed that the proposed method was competitive but did not outperform standard baselines; LASSO logistic regression achieved the highest AUC of 0.739, while the proposed HiTopology-GOA-CSA + MLP achieved an AUC of 0.683. Real external validation on the locked VinDr-Mammo subset (n = 25) remained near-random (AUC of 0.500 [95% CI: 0.304–0.696]), with complete prediction collapse (sensitivity of 1.000, specificity of 0.000). Conclusions: The framework demonstrated feasibility for structured feature selection and stress testing in a small-cohort mammography AI setting; however, external validation revealed near-random discrimination and prediction collapse, indicating limited generalizability. These findings emphasize the need for benchmark comparisons, transparent uncertainty reporting, patient-level validation, and larger multicenter datasets before clinical translation. Full article

Background/Objectives: Fraxetin (7,8-dihydroxy-6-methoxycoumarin), a coumarin constituent of Cortex Fraxini (Qinpi) used in traditional Chinese medicine, is metabolised mainly by UGT1A9, but its potential to inhibit UGT enzymes and cause herb–drug interactions (HDIs) is largely unstudied. Methods: Fraxetin and four related coumarins were screened against 11 recombinant human UGTs; isoforms inhibited ≥80% underwent full kinetic analysis with 4-methylumbelliferone as probe. Binding was examined by molecular docking on AlphaFold structures with PLIP, triplicate 100 ns molecular dynamics, and MM/GBSA and MM/PBSA free-energy calculations, and interaction risk by FDA 2020 in vitro–in vivo extrapolation (IVIVE). Results: Fraxetin alone inhibited both UGT1A1 and UGT1A9 by >80% and was characterised in detail, acting as a mainly competitive mixed-type inhibitor (UGT1A1 IC₅₀ 15.99 μM, K_i 8.32 μM; UGT1A9 IC₅₀ 8.44 μM, K_i 5.90 μM). A structure–activity comparison identified a dual-element pharmacophore comprising the C-6 methoxy group and the 7,8-dihydroxycoumarin aglycone. MM/GBSA favoured UGT1A9 over UGT1A1 (ΔΔG = −4.06 kcal/mol, p = 0.005), concordant with the kinetic ranking. IVIVE predicted a borderline systemic signal (R₁ > 1.02) but an intestinal R_1,gut approximately five- to seven-fold above the high-risk threshold of 11 after capping the luminal concentration at fraxetin aqueous solubility. Conclusions: This is the first characterisation of fraxetin as a moderate-potency inhibitor of UGT1A1 and UGT1A9 and points to a previously under-recognised herb–drug interaction risk concentrated in the intestinal lumen rather than systemically; the finding constitutes an interaction signal requiring clinical confirmation rather than an established risk. Full article

Background: The aim of the study was to investigate whether red blood cell antigens (A, B, D, C^w, C, c, E, e, K, k, Jk^a, Jk^b, Fy^a, Fy^b, Le^a, Le^b, M, N, S, s, and P1) from clinically relevant blood group systems were associated with susceptibility to COVID-19. Methods: This exploratory case-control study was carried out on a group of 263 donors from the Regional Center for Transfusion Medicine, Bialystok, Poland (including 121 convalescents and 142 healthy subjects). The microplate method was applied to examine the expression of 21 antigens from eight clinically relevant systems in the donors’ red blood cells. Results: No significant correlation was found between any single blood group and susceptibility to COVID-19. For a more detailed analysis, we adopted an approach involving 3-, 4- and 5-element mutual combinations of antigens. In this exploratory analysis of multi-antigen combinations, nominal statistical significance was found for a number of associations, but none remained statistically significant after adjustment for multiple testing. In the case of three-antigen associations, the strongest association was observed for cc combined with Ee and kk, with the effect size showing approximately 4× higher odds of COVID-19 (OR = 4.49, p = 0.020); in the case of four-antigen combinations, the strongest association was found for RhD(+) combined with kk, Fy^b and P1(−), as well as RhD(+) combined with cc, Ee and kk, also indicating 4× higher odds of COVID-19 (OR = 4.49 p = 0.016). For five-antigen combinations, the strongest association was observed for blood type O combined with kk, Le^b, P1(+) and MM, with the association strength reaching an OR = 4.44, p = 0.025. Conclusions: The findings suggest that analyses based solely on single blood group antigens may have limited value for assessing the susceptibility to COVID-19. In contrast, combinations of red blood cell antigens may provide more reliable correlations with the susceptibility to COVID-19. However, these findings should be interpreted with caution and require confirmation on larger and more representative populations. Full article

Sea buckthorn is a valuable medicinal and edible plant, but the sour and astringent taste of its fruit limits the development of the related processing industry. This study focused on establishing the optimal composite enzymatic hydrolysis strategy to reduce acerbity during processing of sea buckthorn berries, while preserving the antioxidant activity. The results indicated that the most effective conditions for deacidification and deastringency were achieved with a pectinase-to-tannase mass ratio of 1:1, an enzyme dosage of 0.20%, at a pH of 4.50, a temperature of 50 °C, and a duration of 4 h. Under this treatment, the sea buckthorn could retain its potent antioxidant activity. Furthermore, a significant alteration was observed in the levels of 36 metabolites, which were correlated with the sensory attributes of the sea buckthorn. The findings of this study provided a theoretical basis for the enhanced utilization of sea buckthorn in processing and for a deeper understanding of its bioactive properties. Full article

During pregnancy, hormonal, metabolic, and immunological changes influence the composition and function of maternal microbial communities. Increasing evidence suggests that the maternal microbiota—particularly in the vaginal, gut, and oral environments—plays a significant role in maintaining pregnancy homeostasis and supporting fetal development. In healthy pregnancies, the vaginal microbiota is typically dominated by Lactobacillus species, which help maintain a low vaginal pH and protect against ascending infections. However, disruption of this balance (vaginal dysbiosis) has been associated with obstetrical complications such as intrauterine infection and preterm birth. Similarly, the maternal gut microbiota undergoes trimester-specific changes that contribute to metabolic adaptations required for fetal growth, while alterations in microbial composition have been linked to metabolic disorders including gestational diabetes mellitus and preeclampsia. Changes in oral microbiota and periodontal disease have also been associated with adverse pregnancy outcomes through systemic inflammatory pathways and potential microbial translocation to the placenta. Recent advances in sequencing technologies have improved the understanding of host–microbiome interactions in pregnancy, although the existence of a placental microbiome remains controversial. Overall, maternal microbiota plays an important role in pregnancy physiology, and its dysregulation may contribute to obstetrical complications. Understanding these mechanisms may facilitate the development of microbiome-based diagnostic and therapeutic strategies in maternal–fetal medicine. Full article

The demand for sustainable, high-performance biomaterials has driven intense research towards natural polysaccharide hydrogels. Accordingly, this study aimed to synthesize novel starch-based hydrogel materials, considering their inherent hydrogel-forming capabilities together with diverse potential applications (e.g., pharmaceuticals, medicine, and the cleaning application for the artifacts). To obtain hydrogels with enhanced mechanical and physico-chemical properties, starch was combined with other polymeric species (i.e., alginate, polyvinyl alcohol, and polyvinylpyrrolidone), and a gelling process was induced by using calcium cations or borate anions. Two distinct hydrogels (named S-Ca and S-SB, respectively) were prepared and characterized by a range of instrumental and experimental techniques. The assessed properties included water and solvent resistance, equilibrium water content, water-releasing capacity, morphology and microstructural features with their composition by SEM-EDS analysis, and mechanical properties (tensile strength, elasticity, Young’s modulus, and hardness). The results indicated that the investigated hydrogels exhibited suitable properties for a variety of applications, including surface cleaning processes in the field of cultural heritage conservation. For instance, they showed equilibrium water content (between 80 and 90%) comparable with other hydrogels commonly used as cleaning tools (e.g., agar and p(HEMA)/PVP) and quite low water-releasing capacity (between 10 and 17 mgcm⁻²). Moreover, the S-SB hydrogel displayed distinctly better tensile strength and elongation at break than hydrogel prepared in the presence of Ca²⁺ (S-Ca). Notably, S-SB experienced considerable elasticity improvement after freezing–thawing cycles, as indicated by a decrease in tensile strength (from 275 to 102 kPa) and an increase in elongation at break (from 121 to 275%). However, it should be noted that the hydrogel selection depends on the requirements of the target application, as different processes demand materials with distinct characteristics. Hence, both S-Ca and S-SB hydrogels were tested as cleaning tools for the removal of artificially aged acrylic coating (i.e., Paraloid B-72) from the surface of marble and wood specimens, respectively. The tests provided positive results, as aged coating was satisfactorily removed by applying the hydrogels loaded with a nanostructured emulsion (NSE). These novel starch-based hydrogels demonstrate significant potential as high-performance alternatives to conventional hydrogel systems currently used in conservation science as well as in other industrial applications. Full article