Search Results (5,108)

Background/Objectives: Beyond glycemic control, oral antidiabetic drugs (OADs) may exert class-specific effects on muscle mass and hematologic parameters. However, real-world evidence comparing these effects across OAD classes remains limited. This study aimed to evaluate the differential effects of commonly prescribed OADs on skeletal muscle mass (SMM) and hemoglobin (Hb) levels in adults with type 2 diabetes mellitus (T2DM). Methods: In this prospective observational cohort study, 60 adults with newly initiated OAD therapy were followed for six months at a tertiary care center in Türkiye. Patients were classified according to the OAD class newly added to their regimen (metformin, sulfonylureas, dipeptidyl peptidase-4 inhibitors, pioglitazone, or sodium–glucose cotransporter-2 inhibitors [SGLT2-i]). Multi-frequency bioelectrical impedance analysis was used to evaluate body composition, and hematologic parameters including Hb were obtained at both time points. To account for potential confounders—including age, sex, BMI, baseline Hb, and eGFR—binary logistic regression analyses were performed. Results: Patients initiated on pioglitazone (n = 11) demonstrated a borderline within-group increase in SMM in unadjusted analysis (median delta +0.17 kg, IQR −0.55 to +0.50; p = 0.050); however, this association was attenuated and no longer statistically significant after multivariable adjustment (OR 2.16, 95% CI 0.60–7.83; p = 0.240). In contrast, SGLT2-i users (n = 28) showed a significant increase in Hb (median delta +0.10 g/dL, IQR −0.30 to +0.50; p = 0.022), which remained significant after adjustment (OR 4.22, 95% CI 1.32–13.44; p = 0.015). Other OAD classes were not associated with meaningful changes in SMM or Hb. Conclusions: In this real-world prospective cohort, pioglitazone showed a trend toward increased SMM in unadjusted analysis that did not reach significance after adjustment, suggesting a hypothesis-generating signal warranting further investigation. SGLT2 inhibitors were independently associated with increased Hb levels, though the observed median increment was modest in absolute terms. These findings highlight potentially clinically relevant, non-glycemic effects of OAD classes and may inform individualized treatment selection, particularly in patients at risk of sarcopenia or anemia. Adequately powered, prospective studies are needed to validate and extend these preliminary observations. Full article

Deep learning has revolutionized medical image segmentation; however, the clinical deployment of state-of-the-art models is severely impeded by their quadratic computational complexity and substantial resource demands, particularly in multisensor and multimodal imaging scenarios. In response, the field is undergoing a paradigm shift towards efficiency, characterized by the rise of linear-complexity architectures and the optimization of foundation models. This paper presents a comprehensive survey of efficient medical image segmentation methodologies, systematically reviewing the evolution from heavy, accuracy-driven models to lightweight, deployment-ready paradigms. In particular, we highlight the growing importance of efficient segmentation in multisensor medical imaging, where heterogeneous data sources such as CT, MRI, ultrasound, and infrared imaging introduce additional challenges in scalability and computational cost. We propose a novel taxonomy that categorizes these advancements into four distinct streams: (1) Mamba and State Space Models, which leverage selective scanning mechanisms to achieve global receptive fields with linear complexity; (2) Efficient Adaptation of Foundation Models, focusing on parameter-efficient fine-tuning and knowledge distillation to tailor the Segment Anything Model (SAM) for medical domains; (3) Advanced Lightweight Architectures, covering the resurgence of large-kernel CNNs and the emergence of Kolmogorov–Arnold Networks (KANs); and (4) Data-Efficient Strategies, including semi-supervised and federated learning to address annotation scarcity. Furthermore, we conduct a rigorous comparative analysis of representative algorithms on mainstream benchmarks, providing a granular evaluation of the trade-offs between segmentation accuracy and computational overhead. The survey also discusses key challenges in multisensor and multimodal settings, including modality heterogeneity, data fusion complexity, and resource constraints. Finally, we identify critical challenges and outline future research directions, serving as a roadmap for the development of next-generation efficient and scalable medical image analysis systems. Full article

To solve the problems of poor weld formation, difficult slag removal, and inferior joint microstructure and hardness in conventional narrow-gap submerged arc welding (NG-SAW), a swing arc NG-SAW process assisted by pre-embedding cold wires was proposed. Synergistically optimizing the welding energy parameters and additional cold wires ensured sound weld formation and enhanced slag detachability, while the efficiency of multilayer welding was improved by reducing the number of weld layers by 33.3%. The slag adhesion mechanism is clarified as follows: a high welding heat input facilitates elemental diffusion at the weld–slag interface, leading to the formation of a continuous and thick interlayer composed of (Fe,Mn)O and MgO-Al₂O₃-CaO phases. This interlayer strengthens the chemical bonding between slag and weld, thereby impeding slag removal. Microstructure evolution analysis of the multilayer welded joint revealed that the variable-angle design increases the groove volume and, combined with the heat-absorbing effect of the additional wires, accelerates molten pool cooling, thereby refining grains in both the weld metal zone and reheat-affected zone. Meanwhile, the tempering exerted by the heat-affected zone (HAZ) of the subsequent weld layer on the previous layer is attenuated. This promotes the gradual transformation of hard-brittle lath martensite in the coarse-grained heat-affected zone (CGHAZ) of the bottom layer into tougher tempered martensite/bainite in the CGHAZ of the upper layers. As a result, the hardness uniformity within the HAZ, the critical weak region of the joint, was enhanced by 54%, enabling synchronous improvement in microstructural homogeneity, hardness distribution, and overall welding efficiency. Full article

This study investigates the antioxidant and anticorrosive properties of Mentha pulegium L. essential oil (MP EO) as a sustainable and eco-friendly alternative to synthetic oxidation inhibitors. The antioxidant activity of MP EO was evaluated using the ferric reducing antioxidant power (FRAP) assay, which demonstrated a strong electron-donating capacity and effective reduction of ferric ions, indicating promising antioxidant potential. The anticorrosive performance was assessed on mild steel in 0.5 M H₂SO₄ using potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). The results showed inhibition efficiencies of up to 75.8% at a concentration of 2 g/L. Molecular docking simulations revealed favorable binding interactions between the key oil components (pulegone and menthone) and the ROS-generating enzyme model (PDB ID: 2CDU), providing complementary mechanistic insight into their potential role in oxidative stress modulation. Additionally, quantum chemical calculations highlighted electronic properties favoring adsorption on metallic surfaces. Surface morphology analysis using SEM/EDX confirmed the formation of a protective film on steel in the presence of MP EO. These combined findings position Mentha pulegium essential oil as a potent, biodegradable candidate for both antioxidant applications and corrosion prevention in acidic environments. Full article

Background/Objectives: To evaluate the utility of phase angle (PhA) derived from bioelectrical impedance analysis as a screening indicator for pre-frailty in community-dwelling older adults. Methods: This cross-sectional study included 171 participants (36 men and 135 women) in Japan in 2023. PhA at 50 kHz was measured using bioelectrical impedance analysis and evaluated as a potential screening indicator for pre-frailty. Assessments included body composition, physical function tests (maximum walking speed, Timed Up and Go (TUG), grip strength, knee extension strength, and one-leg stance time with eyes open), cognitive function (MoCA-J), and the Motor Fitness Scale (MFS), a questionnaire assessing physical function, along with the Kihon Checklist (KCL). Frailty status was defined using KCL scores (4–7: pre-frailty; ≥8: frailty), and participants were classified into robust and pre-frail/frail groups. Results: PhA was significantly correlated with physical function measures, including grip strength (r = 0.54, p < 0.01), MFS (r = 0.36, p < 0.01), maximum walking speed (r = 0.20, p < 0.05), knee extension strength (r = 0.16, p < 0.05), and TUG (r = −0.17, p < 0.05). In women, logistic regression analysis showed that PhA was independently associated with pre-frailty (age-adjusted odds ratio: 2.38; 95% CI: 1.08–5.23; p < 0.05). ROC analysis yielded an area under the curve of 0.65 (95% CI: 0.56–0.74), indicating modest discriminative ability. Age-adjusted cutoff values of PhA were 4.19° and 4.74°, corresponding to points prioritizing sensitivity and specificity, respectively. Conclusions: PhA is associated with physical function and may serve as a simple, non-invasive indicator for identifying pre-frailty in community settings. However, given its modest discriminative ability, PhA alone may not be sufficient as a standalone screening tool and should be used in combination with other clinical indicators for clinical application. Full article

Background/Objectives: Cardiovascular diseases are the leading cause of mortality worldwide, with coronary artery disease (CAD) being the most prevalent. An atherogenic diet contributes to oxidative stress by promoting lipid peroxidation in lipoproteins and cellular membranes, thereby compromising membrane integrity, which is reflected in lower phase angle (PhA) values. Dietary antioxidants play a crucial role in cellular health and in reducing atherosclerotic risk; therefore, the Dietary Antioxidant Index (DAI) is an important measure, as dietary antioxidants may counteract oxidative damage. This study aimed to assess the association between anthropometric, PhA, and biochemical variables across groups classified according to DAI. Methods: This was an analytical cross-sectional study. A total of 107 subjects, with and without CAD, were included. Oxidized LDL (oxLDL) and oxidized HDL (oxHDL) were determined using the ELISA technique. PhA was measured by bioelectrical impedance analysis, and DAI was calculated using the formula proposed by Wright et al. Results: DAI was positively associated with HDL concentrations in women with CAD, indicating that HDL levels increased by 5.8 mg/dL for each unit increase in DAI (R² = 0.625, p = 0.001). Furthermore, for each unit increase in DAI, the TC/HDL ratio decreased by 0.3 (R² = 0.625, p = 0.006), and the LDL/HDL ratio decreased by 0.2 (R² = 0.506, p = 0.012). Conclusions: A higher DAI is associated with a more favorable lipid profile in women with CAD, particularly with higher HDL concentrations and lower TC/HDL and LDL/HDL ratios. Full article

Background/Objectives: Measures of excess body fat are often more informative for predicting health risk than body mass index (BMI) alone. With obesity prevalence increasing among young adults, this study evaluated whether adding dominant handgrip strength improves prediction of body fat percentage (BF%) and BF%-defined obesity in a university population. Methods: Cross-sectional data from 895 students (401 women, 494 men; mean age 19.9 years; fall 2015–spring 2016) in Kentucky, USA were analyzed. BMI was calculated from self-reported height and weight. BF% was estimated using bioelectrical impedance analysis (BIA), and dominant handgrip strength was measured with a hydraulic hand grip dynamometer. Sex-specific linear and logistic regression models assessed associations among BMI, grip strength, relative grip strength, and BF%. Results: BMI was a strong predictor of BF% in linear models (R² = 0.74 in women; 0.68 in men). Grip strength alone was not associated with BF% but showed an inverse association when combined with BMI. For BF%-defined obesity, BMI remained the most influential predictor, with grip strength contributing additional predictive value. Among men, age significantly modified these relationships, with marked differences between those aged 18–19 years versus older participants. Conclusions: BMI strongly predicted BF% and BF%-based obesity in this cross-sectional study of a predominantly white young adult population. Incorporating handgrip strength modestly improved classification, particularly among women, suggesting that a functional measure like hand grip strength may enhance obesity screening and health communication in young adults. Full article

Accurate and robust battery health prognostics are critical for reliable battery management in electronic devices and electric vehicles. Previous studies have demonstrated that combining electrochemical impedance spectroscopy (EIS) with machine learning enables accurate health-state forecasting in LiCoO₂ coin cells. However, the applicability of this EIS-AI paradigm across diverse chemistries and industrial-grade battery formats remains unvalidated, limiting its practical deployment in energy storage systems. Here, we develop an EIS–AI battery prognostic framework and validate its performance on LiNi_1/3Mn_1/3Co_1/3O₂ (NMC111) cylindrical cells and LiNi_0.8Mn_0.1Co_0.1O₂ (NMC811) pouch cells. A hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN–BiLSTM) architecture is developed to estimate state of health (SoH) and predict remaining useful life (RUL) from EIS spectra. Trained on an in-house dataset comprising over 13,000 impedance spectra from 22 cells (8 NMC111 and 14 NMC811), the model achieves robust performance, with average coefficients of determination (R²) exceeding 0.92 for SoH estimation and 0.90 for RUL prediction across various batteries and cycling protocols. Salient feature analysis further reveals chemistry- and protocol-dependent frequency regimes associated with degradation. These results demonstrate that impedance spectra constitute physically informative descriptors for data-driven battery prognostics and provide a scalable and interpretable pathway for deploying EIS-AI frameworks in real-world battery management systems (BMSs). Full article

This study systematically reviews the evolution of Qatar’s tourism sector to evaluate the historical barriers impeding its development and the strategic initiatives deployed to enhance destination competitiveness. The research’s primary aim is to provide a theory-driven longitudinal analysis of Qatar’s tourism evolution, identifying systemic barriers and adaptive responses required for long-term sustainability. Grounded in the theoretical synthesis of Butler’s Tourism Area Life Cycle (TALC) and Dynamic Capability Theory (DCT), the research employs a systematic literature review (SLR) guided by the PRISMA framework, screening 4846 records to analyze 24 final studies. The findings reveal five primary structural and perceptual barriers: a price–value mismatch (luxury perception), regional political instability, cultural and regulatory constraints, environmental vulnerabilities, and gaps in tourist infrastructure. Utilizing DCT, the results demonstrate how the destination exhibited adaptive governance by sensing these barriers and seizing strategic opportunities—such as mega-event hosting and visa reforms—to partially transform its tourism system. These insights highlight that while created resources drive initial visibility, sustaining long-term competitiveness and sustainable growth relies on continuous institutional reconfiguration and socio-cultural alignment. Full article

Background/Objectives: Electroanatomic mapping (EAM) provides high-resolution spatial and electrogram information, but the prognostic utility of quantitative EAM features has not been systematically evaluated with contemporary artificial intelligence (AI) methods. We investigated whether an AI analysis of quantitative EAM exports from the CARTO system enhances the prediction of major arrhythmic events (MAEs). Methods: In this retrospective, multicenter cohort study, 248 consecutive patients undergoing left ventricular EAM at four tertiary electrophysiology centers were analyzed. Numerical EAM descriptors (spatial coordinates, unipolar/bipolar voltages, local activation time, impedance) were transformed into derived metrics, including local activation heterogeneity (GR), late-potential extent (LAT), bipolar–unipolar discrepancy (VLT), and low-amplitude scar extent (Scar Areas), and were spatially normalized via spherical projection. Clinical, anamnestic, and imaging variables were integrated. Machine learning and deep learning models were trained with an 80:20 train/test split and evaluated using three-fold cross-validation. Performance metrics included area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision. Results: Models incorporating both clinical and AI-processed EAM features achieved high discriminatory performance (test AUC up to 0.92; accuracy up to 0.896). Specificity was consistently high (≈0.97–0.998), whereas sensitivity remained modest (≈0.39–0.58). Among the EAM-derived features, GR was the most consistently informative predictor across algorithms and analyses; VLT, LAT, and Scar Areas also contributed substantially. Regionally, basal sub-mitral, subaortic, and posterolateral basal-to-mid zones exhibited the strongest associations with MAEs. Conclusions: AI-driven quantitative analysis of left ventricular EAM exports augments risk stratification for MAEs beyond conventional clinical and binary EAM descriptors. Reflecting local conduction heterogeneity, GR emerged as the dominant EAM predictor. Prospective validation in larger, disease-specific cohorts and real-time integration within EAM platforms are warranted. Full article

In vitro cell barrier models have been increasingly integrated into pharmaceutical and academic research pipelines to evaluate drug safety and drug delivery due to a shift towards New Approach Methodologies (NAMs) in research and regulatory safety assessment. Such models require reliable and interpretable functional readouts. Bioimpedance-based monitoring, particularly transepithelial/endothelial electrical resistance (TEER), is a widely adopted readout due to its non-invasive and real-time capabilities. However, substantial variability arises from differences in measurement settings, frequency selection, electrode configuration, impedance measuring techniques, and data analysis strategies. In numerous studies, TEER is approximated from single-frequency impedance magnitude measurements, which do not isolate the resistive component associated with tight junction-mediated paracellular transport but instead reflect the combined response of a coupled electrochemical system. This review clarifies impedance measuring techniques and systematically analyzes impedance-based measurement and analysis strategies for in vitro biological cell barrier integrity. We compare mono-frequency and broadband acquisition approaches, examine the influence of electrode–electrolyte interfaces, electrode geometry, and culture configuration, and evaluate equivalent circuit modeling and phase-resolved electrical impedance spectroscopy (EIS). Based on this comparison, we propose a three-level analytical hierarchy adapted to experimental objectives and instrumentation constraints. We conclude that phase-informed impedance analysis and harmonized reporting are essential to improve measurement reproducibility, inter-platform comparability, and integration of impedance-derived cell barrier assessment within NAMs-oriented research workflows. Full article

China has rich bamboo resources, with Moso bamboo (Phyllostachys edulis) being the most economically important species. Bamboo shoot bud development directly determines the eating quality of the shoots and the properties of bamboo materials; however, the intrinsic biological characteristics of this process have hindered foundational research. Traditional methods using whole shoot buds or mixed tissues obscure cellular and tissue heterogeneity, limiting our mechanistic understanding. This review synthesizes cytological features, molecular networks, and technical limitations pertaining to Moso bamboo shoot bud development, identifying four key bottlenecks: tissue homogenization masking cellular heterogeneity, loss of spatial positional information impeding analysis of position effects, challenges in single-cell technology application due to sample preparation and data interpretation issues, and unresolved coupling between chromatin accessibility and transcriptional regulation. To address these, we propose a core strategy centered on constructing a single-cell resolution, spatially resolved, multi-omics integrated, and functionally validated framework. Key approaches include developing bamboo-specific single-cell sequencing and spatial transcriptomics, integrating positional information with multi-omics data to identify spatially distinct regulatory targets, standardizing technical pipelines and functional validation platforms, and elucidating epigenetic–transcriptional coupling. Overcoming these bottlenecks will reveal the molecular basis of bamboo’s unique developmental patterns and provide key targets for the genetic improvement of the shoot quality and mechanical properties of bamboo. Full article

Background: Hepatitis B virus (HBV) infection continues to be a major public health concern, especially in sub-Saharan Africa, where widespread epidemics and restricted availability of long-term antiviral therapies result in higher mortality and morbidity rates. Drug repurposing represents a strategic approach to accelerate the discovery of effective therapies by leveraging agents with demonstrated antiviral and immunomodulatory activity. Product Nkabinde (PN) is a patented African polyherbal formulation initially developed for the treatment of HIV. Recent experimental studies demonstrate PN’s potent anti-HIV activity and significant immunomodulatory effects in human immune cells, implicating host-directed mechanisms relevant to chronic viral infections. This study combines an integrative application of network pharmacology and molecular docking to evaluate the repurposing potential of PN as a multi-target agent in HBV. Method: Bioactive components of PN were screened, and compound-associated targets were intersected with HBV-associated genes (proteins) to construct a protein–protein interaction (PPI) network. Topological analysis identified 10 hub targets (STAT1, STAT3, SRC, HCK, EGFR, SYK, PIK3CA, PIK3CB, PIK3R1, and PTPN11). Gene Ontology and KEGG pathway enrichment were performed with an FDR cut-off < 0.05. Significantly enriched pathways included JAK–STAT signaling, chemokine signaling, EGFR-TKI resistance, PI3K complex signaling, and viral infection pathways, particularly those related to Kaposi sarcoma virus and HSV-1, indicating immunoregulatory and antiviral roles. Molecular docking was performed using AutoDock Vina 1.1.2 to evaluate binding affinity and interaction mode of key PN phytochemicals against the hub proteins, and results were compared to their respective co-crystallized ligands. Results: Molecular docking indicated that major phytochemicals from PN exhibited significant binding affinities across all 10 hub host targets, typically outperforming or closely matching their respective co-crystallized ligands. The strongest contacts were observed for β-sitosterol–PIK3CB (−14.2 kcal/mol) and oleanolic acid–SYK (−14.0 kcal/mol), which were significantly stronger than the co-crystallized ligands (−7.9 and −8.3 kcal/mol, respectively), indicating robust stabilization within catalytic and regulatory pockets. Procyanidin B2 toward HCK (−10.5 vs. −7.9 kcal/mol) and PIK3CA (−9.5 vs. −7.3 kcal/mol), quercetin toward PIK3R1 (−10.6 vs. −8.2 kcal/mol) and PTPN11 (−9.2 vs. −7.5 kcal/mol), rutin toward SRC (−10.5 vs. 7.8 kcal/mol), and diosgenin toward EGFR (−9.4 vs. 8.4 kcal/mol). Procyanidin B2 maintained robust multi-hydrogen bonding networks, demonstrating significant binding, despite STAT1 and STAT3 docking showing identical affinities to co-crystals. Conserved hydrogen bonds, π–cation interactions, and significant hydrophobic packing at ATP-binding clefts and regulatory domains supported these interaction patterns, indicating competitive suppression of host signaling nodes taken over by HBV. Conclusions: Together, these results demonstrate that the components of PN possess strong multitarget binding capabilities across the PI3K/AKT, JAK–STAT, SRC-family kinase, EGFR, and SYK pathways, supporting their potential repurposing as host-directed HBV therapeutics with the ability to impede immune evasion, viral persistence, and HBV-associated oncogenic progression. Full article

This paper presents a novel voltage differencing transconductance amplifier (VDTA)-based mixed-mode inverse filter capable of operating in voltage mode, transadmittance mode, transimpedance mode, and current mode using a single topology. The proposed configuration employs only three VDTAs with two resistors and three capacitors, offering low component count, high input/output impedance flexibility, and no requirement for component matching. It simultaneously realizes first-order inverse lowpass and highpass, as well as second-order inverse bandpass responses. A comprehensive non-ideal analysis, which includes the effects of VDTA parasitic impedances, determines the practical operating frequency range. The design is validated through PSPICE simulations using 0.18 μm CMOS technology, showing close alignment between theoretical predictions and simulation results, with cutoff frequencies of approximately 1.60 MHz and low power consumption of 0.972 mW. Further analyses confirm orthogonal tuning capability, acceptable temperature stability, and robustness against component tolerances. In a practical application, the proposed inverse filter is employed to implement a mixed-mode PID controller, which significantly improves transient response characteristics by reducing rise time, settling time, and steady-state error. These findings highlight the effectiveness and versatility of the proposed design for analog signal processing and control system applications. Full article

Water-based lubricants (WBLs) are increasingly being considered for electrified drivetrain applications; however, their electrochemical stability toward bearing steels remains insufficiently understood. This study evaluated the corrosion behavior of through-hardened AISI 52100 bearing steel in novel WBLs to elucidate the corrosion kinetics and surface degradation mechanisms. Round steel disks were cleaned and tested in 50 wt% aqueous dilutions of glycerol, ethylene glycol (MEG), polyethylene glycol (PEG), and polyalkylene glycol (PAG). Electrochemical measurements were conducted using a three-electrode cell in accordance with ASTM G3-14, employing open circuit potential (OCP), linear polarization resistance (LPR), electrochemical impedance spectroscopy (EIS), and potentiodynamic polarization curves. Among the uninhibited fluids, DI water exhibited the highest corrosion current density (19.85 µA/cm²), while glycerol- and PEG-based systems showed the lowest values (0.79 and 0.85 µA/cm², respectively), attributed to organic adsorption at the steel/electrolyte interface. EIS analysis revealed a single charge-transfer-controlled process across all fluids, consistent with a weak, non-passive interfacial oxide whose protective character is modulated by organic adsorption. The addition of NaNO₃ produced divergent effects depending on the base fluid chemistry: the corrosion activity was reduced in DI water and glycerol systems through enhanced passivation, while PEG- and PAG-based formulations showed increased corrosion current densities and reduced charge transfer resistance, attributed to competitive disruption of the polymer boundary layer by nitrate ions. Surface characterization by SEM/EDAX and white-light interferometry corroborated the electrochemical findings, revealing fluid-dependent corrosion morphologies ranging from uniform attack in DI water to localized pitting in polymer-based systems, with NaNO₃ shifting the corrosion mode in PEG/PAG systems from localized to combined localized and uniform attack. These findings highlight the critical role of fluid chemistry in controlling corrosion processes in water-based lubricants and provide mechanistic insight for the development of corrosion-stable formulations for high-performance electrified drivetrain applications. Full article