Search Results (78,598)

Research into auxetic foams—materials with a negative Poisson’s ratio— is expanding, yet their integration into orthotics for diverse neuropathic conditions remains largely unexplored. This pilot study evaluates the feasibility of fabricating custom auxetic foam insoles and characterizing vertical ground reaction force (vGRF) trends across a heterogeneous cohort. In collaboration with the NASA/Marshall Space Flight Center, six participants, including five representing varied neuropathic etiologies and one healthy control, performed randomized walking trials under three conditions: barefoot, over-the-counter (OTC) insoles, and custom auxetic prototypes. The healthy control was retained in the cohort-level analysis to preserve methodological symmetry across experimental conditions. To maintain physical rigor, vGRF data were mass-normalized (N/kg). A Friedman test (n = 6) evaluated global differences, supplemented by a dual-bootstrap analysis (1000 resamples) to quantify effect magnitudes (r) and numerical uncertainty. Although the Friedman test revealed no statistically significant global differences (Q = 0.333, df = 2, p = 0.846), a descriptively large effect size (r = 0.58) was observed for the auxetic material versus barefoot walking. However, wide 95% bootstrap confidence intervals prevent population-level inference, reinforcing the exploratory nature of these findings. Subject-specific observations showed descriptive differences in vGRF in three participants (0.17 to 1.18 N/kg), while increases in others occurred alongside confounding factors such as self-selected walking velocity. This work demonstrates the mechanical application of auxetic insole prototypes, providing a foundational rationale for future trials utilizing standardized walking velocity to isolate material performance. Full article

Objectives: Seawater-immersed burn wounds are highly susceptible to contamination, persistent inflammation, oxidative stress, and delayed healing, while current irrigation solutions remain suboptimal for such acute injuries. This study aimed to evaluate the therapeutic efficacy and underlying mechanisms of plasma-activated water (PAW) as a novel irrigation strategy for these complex wounds. Methods: The antibacterial efficacy of PAW against marine pathogens was first evaluated in vitro. Subsequently, a rat model of seawater-immersed burn injury was established in male Sprague-Dawley (SD) rats to assess the therapeutic effects of PAW irrigation on wound healing, infection control, and underlying biological mechanisms. Results: In vitro, PAW significantly eradicated two major marine pathogens, Vibrio vulnificus and Vibrio parahaemolyticus (p < 0.001). In vivo, PAW markedly accelerated wound closure, achieving complete healing in 23.60 ± 6.50 days vs. 38.67 ± 2.08 days (Normal saline group) and 58.33 ± 10.97 days (Model group) (p < 0.05). PAW significantly reduced bacterial burden, modulated inflammation by decreasing interleukin-6 and increasing interleukin-10, and alleviated oxidative stress, as evidenced by reduced malondialdehyde levels and enhanced superoxide dismutase activity. Histological evaluation demonstrated enhanced re-epithelialization, collagen deposition, and increased expression of vascular endothelial growth factor and platelet endothelial cell adhesion molecule-1. No adverse effects on serum biochemistry or major organ histopathology were observed. Conclusions: PAW may be a safe, promising, and multifunctional irrigation strategy that promotes seawater-immersed burn healing through coordinated antibacterial, anti-inflammatory, antioxidant, and pro-angiogenic effects, highlighting its strong potential for clinical translation. Full article

Quantifying vegetation dynamics has become a critical scientific imperative in the context of global ecosystem restoration initiatives targeting degraded forests. Previous studies have explored vegetation-cover change trends at different spatial scales worldwide using the Theil–Sen (TS) estimator and Mann–Kendall (MK) test, yet few have accounted for the uncertainty in resulting trends across time-series datasets of varying lengths. Taking the coastal zone of Fujian Province in Southeast China as a case study, we investigated the uncertainty of vegetation-cover change trends using normalized difference vegetation index (NDVI) datasets of different lengths (e.g., 20-year, 15-year, and 10-year) via the TS estimator and MK test. Additionally, piece-wise regression was employed to detect turning points and shifts in vegetation trends between 2001 and 2020. The results indicate significant discrepancies in trend estimation across datasets of different lengths, with consistency ratios ranging from 46.1% to 64.7% among the 20-year, 15-year, and 10-year series. The MK test is more sensitive to time-series length than the TS estimator, with areas of significant change decreasing by over 50% when transitioning from a 20-year to a 10-year dataset. The spatial distribution of trend shifts exhibits a distinct “coastal–inland” polarization pattern, with 2010 as the turning point. Eight modes of vegetation trend shifts were identified based on pre- and post-turning point dynamics. Furthermore, piece-wise regression improved trend accuracy by approximately 15%. This research advances the mechanistic understanding of spatiotemporal vegetation dynamics and supports adaptive ecosystem management strategies. Full article

Background: Postmenopausal osteoporosis is a common metabolic bone disorder characterized by decreased bone mass and microstructural deterioration, often accompanied by increased bone marrow adiposity and systemic fat accumulation. Kun-Ling Wan Formula (KLW) is a compound Chinese medicine clinically used for gynecological disorders, though its effects on postmenopausal osteoporosis and associated fat accumulation remain unclear. Distinct from previous herbal formulation studies that primarily focused on bone outcomes, our study uniquely integrates bone protection, marrow adiposity reduction, systemic metabolic improvement, and multi-omics mechanistic dissection in a high-fat diet-fed ovariectomized mouse model. Methods: KLW chemical composition was analyzed by UPLC-Q-TOF/MS. Ovariectomized (OVX) C57BL/6J mice fed high-fat or normal diet were treated with KLW at clinically equivalent or double doses, with estrogen and active compounds as controls. Bone microstructure was assessed by micro-CT, bone marrow fat by MRI-PDFF, and metabolism by OGTT, ITT, and metabolic cages. Network pharmacology, proteomics, molecular docking, and dynamics simulations identified core targets. C3H10T1/2 cells were used to assess osteogenic/adipogenic differentiation and mTOR pathway activation. Results: Twelve compounds were identified in KLW. In OVX mice, KLW significantly improved bone mineral density and trabecular microstructure, reduced adiposity and bone marrow fat, and enhanced glucose tolerance and insulin sensitivity. In vitro, KLW promoted osteogenesis and suppressed adipogenesis in C3H10T1/2 cells. Integrative analyses identified mTOR as a central target, with chrysophanol, pyrogallol, and apigenin showing high-affinity binding. KLW inhibited mTOR/S6K phosphorylation during differentiation, an effect reversible by leucine. Conclusions: KLW ameliorates osteoporosis and reduces fat accumulation in OVX mice by shifting mesenchymal stem cell differentiation toward osteogenesis via mTOR pathway modulation. Full article

Background: Wugeng San (WGS) is a traditional Tibetan medicinal preparation that has long been used to treat inflammatory and arthritic conditions. However, its contemporary pharmacological validation and the mechanisms underlying its action in rheumatoid arthritis (RA) have not been fully investigated. Objective: For the first time, this study aimed to systematically investigate the therapeutic effects of WGS on RA, identify its potential targets, and elucidate its action mechanisms. Methods: This study, as the first comprehensive investigation of WGS in RA, employed integrated multiple approaches including chemical component identification via UPLC-Q-TOF/MS, network pharmacology, bioinformatics, machine learning, and in vivo efficacy assessment and mechanism verification in a collagen-induced arthritis (CIA) rat model, a widely accepted experimental model that mimics the key pathological features of RA. Results: The results demonstrated that WGS reduced the severity of arthritis in a dose-dependent manner, as evidenced by decreased paw swelling, normalized body weight, and restored levels of pro- and anti-inflammatory cytokines. The high dose of WGS (252 mg/kg) showed an effect comparable to that of methotrexate (0.2 mg/kg). Histological analysis revealed that WGS reduced synovial hyperplasia, cartilage erosion and bone destruction, decreased osteoclast numbers, and promoted osteoblast activity. Eighty-four compounds were identified using UPLC-Q-TOF/MS. Network pharmacology and machine learning analyses indicated SYK as a key target enriched in the NF-κB signaling and osteoclast differentiation pathways. Experimental validation confirmed that WGS suppressed the phosphorylation of SYK and NF-κB pathway components (p65, IκBα, and IKKα/β), decreased MMP1/MMP3 levels, and modulated the Bax/Bcl-2 ratio to promote apoptosis. Conclusions: In conclusion, WGS exhibits strong anti-arthritic effects through “multi-component, multi-target, and multi-pathway” mechanisms, likely attributable to the inhibition of the SYK/NF-κB signaling axis, suppression of matrix degradation, and regulation of cellular apoptosis. This research offers a pharmacological basis for repurposing WGS as a promising natural candidate for RA therapy. Full article

Abiotic stress factors, including drought and salinity, severely limit crop productivity worldwide. Furthermore, the extensive use of herbicides, such as glyphosate, disrupts beneficial soil microbiota, further impairing crop growth. Plant growth-promoting bacteria (PGPB) represent a sustainable and efficient strategy to enhance crop yields, particularly under unfavorable environmental and soil conditions. In this study, we characterized Paenibacillus sp. JSM-10, newly isolated from glyphosate-exposed agricultural soil, for its stress tolerance and plant growth-promoting potential, including its morphology examined using complementary microscopy techniques. The strain tolerated up to 0.5 g/L glyphosate, 15 g/L NaCl, and 100 g/L polyethylene glycol (PEG-6000) without significant growth inhibition (p > 0.05), demonstrating robust resilience to such multiple abiotic stresses. Beyond its tolerance, the strain exhibited several beneficial characteristics, including indole-3-acetic acid (IAA) synthesis, siderophore production, and inorganic phosphate solubilization. Furthermore, both living cells and culture filtrates of JSM-10 exhibited a positive trend toward enhancing buckwheat growth under normal and saline conditions, with effect sizes ranging from Hedges’ g = 0.56−0.92. In addition, JSM-10 exhibited antagonistic activity against a range of pathogenic microorganisms, including Nigrospora oryzae, Bipolaris sorokiniana, Alternaria spp., and Escherichia coli. Altogether, these characteristics highlight the Paenibacillus sp. JSM-10 strain and its culture filtrates as promising candidates for application in organic farming aimed at promoting plant growth and improving stress tolerance via plant–microbe interactions. Full article

Nuclear factor kappa B (NF-κB) signaling plays a central role in inflammation, immunity, cell survival, and cancer progression. Its constitutive activation is frequently observed in breast cancer, contributing to tumor growth, treatment resistance, and metastasis. MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and may modulate NF-κB signaling in a subtype-specific or -independent manner. The aim of the study was to identify miRNAs that may potentially regulate the activity of genes associated with NF-κB signaling across five molecular subtypes of breast cancer in Polish women. Tumor and matched normal tissue samples were collected from 405 patients with five breast cancer subtypes: luminal A (n = 130), HER2-negative luminal B (n = 100), HER2-positive luminal B (n = 96), non-luminal HER2-positive (n = 36), and triple-negative breast cancer (TNBC, n = 43). Expression profile of selected NF-κB-related genes were evaluated using mRNA microarrays and RT-qPCR. Protein levels were assessed by ELISA. Candidate regulatory miRNAs were identified via miRNA microarrays and validated using the miRDB database. A consistent upregulation of MAP3K7, TAB2, TNFAIP3, CSNK2A1, BCL2L1, XIAP, CXCL2, and PLAU was observed across all subtypes, suggesting activation of canonical NF-κB signaling. Downregulation of specific miRNAs, miR-1297 and miR-30a (targeting MAP3K7), miR-134 (TAB2), miR-125b (TNFAIP3), and miR-4329 (XIAP), may contribute to this deregulation. For CSNK2A1, BCL2L1, CXCL2, and PLAU, no regulatory miRNAs meeting our criteria were identified. Our study reveals a subtype-independent activation of the canonical NF-κB signaling pathway in breast cancer, underpinned by consistent upregulation of key components (at both the transcript and protein levels. Dysregulation of specific miRNAs likely contributes to this altered gene expression. These findings suggest the presence of a common NF-κB-driven oncogenic program across molecular subtypes, with potential implications for developing miRNA-based therapeutic strategies targeting inflammation, survival signaling, and treatment resistance in breast cancer. Full article

Urban heat islands present a significant obstacle to climate adaptation strategies, yet the interplay between surface and atmospheric thermal elements is not fully understood. This research investigates the spatial relationship between land surface temperature (LST) and near-surface air temperature (TAIR) across Zagreb’s 218 local councils during the summer of 2024, assessing the premise that these constitute separate thermal dimensions with varying land cover correlations. Landsat 8/9-derived LST and CERRA-derived TAIR, temporally aligned to the Landsat overpass slot (09:00 UTC), were examined through spatial autocorrelation (Moran’s I, Getis–Ord Gi*), correlation analysis, and Fisher’s z-tests to compare the effects of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The findings indicated partial coupling (r = 0.537, R² = 0.288), with 71.2% of the variance remaining unexplained, suggesting considerable surface-atmospheric decoupling. Furthermore, hot spot overlap analysis revealed limited convergence (11.9% of neighborhoods), while 44.5% displayed divergent thermal extremes. Land cover showed much stronger connections with LST (NDVI: r = −0.970, R² = 0.941; NDBI: r = +0.973, R² = 0.947) than with TAIR (NDVI: r = −0.478; NDBI: r = +0.496), representing reductions in explained variance of 63–64% (p < 0.001). These findings suggest that surface and atmospheric urban heat are related but distinct thermal aspects. Full article

Background/Objectives: Osteonecrosis of the femoral head (ONFH) is difficult to diagnose, particularly in the early stages, because radiological findings may be subtle. Delayed or inaccurate staging may increase the risk of femoral head collapse and functional loss. Although magnetic resonance imaging is highly sensitive for early-stage lesion detection, interpretation may vary depending on observer experience. Therefore, reliable and explainable automated decision support approaches are needed. Methods: In this study, a deep learning-based approach was proposed to classify ONFH into early and late stages according to the Ficat–Arlet staging system. Stage I–II cases were defined as early-stage, whereas Stage III–IV cases were defined as late-stage. Axial and coronal MR images were evaluated separately to investigate plane-dependent classification performance. The images were converted into a three-channel format, resized to a common spatial resolution, normalized, and augmented during training. Feature extraction was performed using transfer learning with modern convolutional neural network architectures. ConvNeXt Tiny was used as the main classification backbone. Weighted loss was applied to reduce the effect of class imbalance, and the decision threshold was optimized on validation data to reduce missed clinically critical late-stage cases. Results: A dataset collected from the Orthopedics and Traumatology Department of Firat University Hospital was used in the experimental evaluation. The dataset was divided into training and test sets using an 80:20 split, and 10-fold cross-validation was additionally performed to assess model stability. In the hold-out test, the axial plane model achieved 94.51% accuracy, 96.80% sensitivity, 93.49% specificity, 0.9162 F1-score, and 0.981 AUC. In the coronal plane model, 92.84% accuracy, 96.13% sensitivity, 90.96% specificity, 0.9072 F1-score, and 0.988 AUC were obtained. The 10-fold cross-validation results provided a more conservative estimate of generalization performance. Conclusions: The findings indicate that deep learning-based plane-wise analysis of MR images can distinguish early- and late-stage ONFH with high performance. Grad-CAM-based visual explanations showed that the model focused mainly on clinically relevant subchondral and weight-bearing regions of the femoral head. The proposed approach may serve as an explainable decision support tool for reducing observer-dependent variability in clinical staging. Future studies should validate the method using external, multicenter datasets and paired patient-level axial–coronal images. Full article

Background: Carbonic Anhydrases (CAs) represent regulators of cell adaptation to hypoxia, pH regulation, and metabolic fitness. Among cancers, multiple myeloma (MM) is a plasma cell malignancy sustained by hypoxia-driven metabolic adaptation, extracellular acidification, and redox imbalance. Tight regulation of tumor extracellular pH, mediated by Carbonic Anhydrases IX and XII, is crucial for myeloma survival, progression, and stemness, making these isoforms attractive therapeutic targets. Methods: We designed and synthesized a library of terpenoid-based hybrids by derivatizing chlorothymol and 4-isopropyl-3-methylphenol with either the natural coumarin umbelliferon or the 2,2′-dipicolylamine (DPA) scaffold. This chemical strategy aimed to selectively inhibit tumor-associated CAs IX/XII through coumarin- or DPA-mediated recognition, while terpenoid fragments were introduced to enhance lipophilicity, membrane permeability, and potential redox-modulating properties. The compounds were tested by a Stopped-Flow assay for CA inhibition, in cell-based assays for antiproliferative properties and by means of several antioxidant assays. Results: The most active compounds, connecting the coumarin core to a terpenoid tail, inhibited the targeted CAs in the nanomolar range, showing up higher selectivity over off-target isoforms (I and II). In studies performed on MM cell lines, selected derivatives reduced viability (IC₅₀ = 15.8–85.4 µM) and displayed favorable selectivity over normal cells. In silico investigations suggested that the compounds were able to interact selectively with the target enzymes. Conclusions: Collectively, these results support a dual-targeting strategy in which selective inhibition of tumor-associated CAs, combined with redox modulation, interferes with adaptive mechanisms of MM cells, providing a rational framework for the development of multifunctional agents against metabolically resilient hematological malignancies. Full article

Background/Objectives: Camellia bee pollen refers to pollen pellets collected by bees from plant stamens and mixed with salivary secretions. Alcoholic fatty liver disease (AFLD), as the initial phase within the spectrum of alcohol-induced liver diseases, has resulted in a rising global incidence rate and treatment burden of such liver ailments. Methods: This study employs acute zebrafish juvenile and adult zebrafish chronic alcoholic liver models to explore the protective effects of camellia bee pollen as well as its ethanol and water extracts on zebrafish alcoholic fatty liver. Results: The research findings indicate that the intervention group treated with camellia bee pollen significantly mitigated the accumulation of lipid droplets in zebrafish larvae and notably improved the liver lobule structure of adult zebrafish, bringing it close to normal conditions. The camellia pollen intervention group could significantly decrease the levels of triglyceride (TG), total cholesterol (T-CHO), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and malondialdehyde (MDA), while increasing the levels of glutathione (GSH) and total superoxide dismutase (T-SOD). Conclusions: This experiment indicates that the pollen of tea flowers has a significant protective effect against alcoholic liver damage. Full article

Background/Objectives: Portal vein thrombosis (PVT) is a clinically significant condition in which early risk stratification remains challenging, particularly in emergency settings where rapid decision-making is required. This study aimed to evaluate the prognostic value of the Systemic Immune-Inflammation Index (SII), Systemic Inflammation Response Index (SIRI), and the Model for End-Stage Liver Disease (MELD) score in predicting the need for intensive care in patients with PVT. Methods: A retrospective analysis was conducted on adult patients (>18 years) diagnosed with PVT in the emergency department between January 2018 and December 2024. A total of 29 patients meeting the inclusion and exclusion criteria were included. Demographic characteristics, laboratory parameters, Intensive Care Unit (ICU) admission status, and 90-day mortality were analyzed. The sensitivity and specificity of MELD, SII, and SIRI for predicting ICU admission were calculated. Non-normally distributed variables were expressed as median (interquartile range, IQR) and compared using the Mann–Whitney U test. Results: The mean age of patients was 60.5 ± 16.2 years, and 18/29 (62.1%) were male. ICU admission was required in 9/29 (31.0%) of cases. MELD score (median 18.7 [11.0–21.9] vs. 7.9 [6.7–13.5], p = 0.003), bilirubin (median 2.4 [1.0–4.2] vs. 0.7 [0.4–1.1], p = 0.016), and SIRI (median 6.4 [2.3–21.3] vs. 1.4 [0.6–9.3], p = 0.038) were significantly higher in ICU-admitted patients. MELD score showed 66.7% sensitivity and 95% specificity, while SIRI had 88.9% sensitivity and 55% specificity for ICU prediction. Conclusions: MELD score, bilirubin, and SIRI are significantly associated with ICU admission in PVT patients. Their integration into emergency department protocols may assist in early risk stratification and resource allocation. Full article

Individuals with diabetes mellitus (DM) experience impaired wound healing, where the healing process is often compromised by a complex, hostile microenvironment characterized by persistent inflammation, high oxidative stress, and dysfunctional angiogenesis. The hyperglycemic environment damages the blood vessels and disturbs the normal hypoxia-induced upregulation of vascular endothelial growth factors, causes poor vascularization and insufficient production of new blood vessels, and leads to impaired perfusion and thickened and dysfunctional capillary basement membranes, which reduce blood flow to the wound, leading to delayed wound healing. Mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs) are the main effectors of intercellular communication and have emerged as a potent cell-free strategy for the acceleration of tissue repair. MSC-EVs can be isolated from various adult tissues, but increasing evidence suggests that pla Full article

A male castrated Shih Tzu was evaluated for recurrent nocturnal episodes of acute respiratory distress accompanied by hemoptysis and transient erythrocytosis. The dog was clinically normal between episodes, but each nighttime event was severe and prompted repeated emergency visits. During each emergency presentation, thoracic radiographs revealed severe diffuse interstitial-to-alveolar pulmonary infiltrates, and packed cell volume showed marked but reversible increases. A stepwise diagnostic evaluation, including serial indirect blood pressure measurement, coagulation assessment, echocardiography, and bronchoscopy with bronchoalveolar lavage, progressively excluded typical infectious, cardiac, structural, and coagulopathic causes of hemoptysis and acute respiratory distress. Given the stereotyped pattern of near-acute crises with diffuse pulmonary infiltrates and hemoptysis, mechanisms analogous to noncardiogenic pulmonary edema or exercise-induced pulmonary hemorrhage were considered. Therapeutic trials with sildenafil and furosemide failed to prevent further nocturnal recurrences. Considering concurrent transient PCV surges and the proposed role of catecholamine-driven splenic contraction as a rapidly mobilizable erythrocyte reservoir, a sympathetically mediated process was suspected, and α₁-adrenergic blockade with prazosin was initiated. Following prazosin therapy, sustained clinical remission was achieved, with no further emergency episodes over a 15-month follow-up period. The response may have reflected multiple pharmacological effects of prazosin, including attenuation of sympathetically mediated splenic α₁-adrenergic activity, systemic vasodilation, and reduction in venous return. This unique case suggests that dysregulation of the sympathetic nervous system may have contributed to the recurrent hemoptysis and acute respiratory distress and highlights adrenergic modulation as a potential therapeutic consideration in similar cases. Full article

Reliable anomaly early warning for hydropower station sump wells remains challenging due to the strong nonlinearity of water level dynamics and the limited adaptability of conventional fixed-threshold alarms. Here, we present a hybrid deep learning framework—termed CNN–Attention–LSTM–BO—that fuses multi-scale local feature extraction, adaptive temporal weighting, and sequential dependency modeling within a unified architecture, with all critical hyperparameters tuned via Bayesian optimization. A four-dimensional input representation is first constructed from the raw water level signal and its first- and second-order differences together with the drainage pump operating state, capturing both trend and transient information. One-dimensional convolutions at multiple kernel scales encode short-range fluctuation patterns, a Bahdanau-style temporal attention layer selectively amplifies informative time steps, and a stacked LSTM propagates long-horizon risk dependencies. At the decision stage, a dual dynamic thresholding scheme couples an improved $3\sigma$ criterion with kernel density estimation (KDE) to partition the smoothed risk score into three graded alert levels (normal/warning/critical), replacing the binary alarm paradigm. Experiments on the SWaT benchmark yield an average area under the ROC curve (AUC) of 0.9246, an average Accuracy of 0.8812, and a best single-well false alarm rate (FAR) of 3.21% (Well-4), with an average FAR of 8.97% across three wells, outperforming both traditional limit-value alarms and ablated variants lacking CNN or attention modules. Full article