Optical and thermal excitation are known to enhance OFF-state leakage and modify the electrostatics of AlGaN/GaN high-electron-mobility transistors (HEMTs), yet the underlying transport pathway remains insufficiently understood. In this work, a geometry-defined ring-break architecture is introduced to directly probe lateral surface conduction and its role in barrier modulation. Simultaneous measurements of gate leakage current I G and channel potential Va reveal a gate-bias-dependent regime transition characterized by a correlated collapse of surface current and electrostatic modulation beyond a critical electric field. The identical transition behavior observed in both transport and electrostatic responses establishes that this transition is governed by a field-defined stability condition of the lateral surface conduction pathway. Measurements on conventional device geometries exhibit the same transition behavior under optical and thermal conditions, confirming the generality of the mechanism. While the magnitude of Va modulation differs significantly between the two geometries, this variation is attributed to differences in the spatial extent of surface charge redistribution and electrostatic boundary conditions rather than changes in the underlying transport process. These results demonstrate that optically and thermally induced barrier modulation in AlGaN/GaN HEMTs is governed by field-sustained lateral surface conduction mediated by surface trap dynamics.

Deep learning has revolutionized computer vision, yet its application to specialized computational imaging—such as depth estimation and geometric surface analysis—remains constrained by the scarcity of high-quality, annotated real-world data. This paper presents SynDepth-Net, a novel neural architecture designed to extract high-fidelity geometric features from limited consumer-grade imaging data. By leveraging a photorealistic synthetic dataset and a task-driven domain adaptation module, our method improves depth precision and feature detection in diverse lighting conditions. We demonstrate superior performance in recovering intrinsic surface details, bridging the gap between synthetic training environments and real-world deployment. Our framework integrates a multi-scale attention mechanism and an adaptive gain control module, enabling robust feature extraction under significant domain shift. Extensive mathematical formulation and experimental validation on both synthetic benchmarks and real-world captures confirm the efficacy of our approach, achieving state-of-the-art results in depth accuracy and feature localization.

INTRODUCTIONThe treatment of equine patients with angular limb and/or rotational deformities combined with closed physes presents a clinical challenge to equine practitioners. The report by Gaida et al in this issue outlines the management of one such case by utilizing a radial osteotomy for a deformity of the distal metacarpus. Although the authors had some challenges with the post-operative management, they did have an acceptable outcome with this technique.Osteotomies and ostectomies are uncommon surgical procedures used to treat angular and rotational limb deformities in patients beyond the time frame of growth retardation or in older patients that have acquired an angular limb deformity secondary to another pathology (healed fracture, osteoarthritis, or previous infection). The procedure involves transecting and possibly removing a portion of bone and stabilizing the resulting construct with implants to achieve a more anatomically appropriate limb. The most common anatomical location treated is the metacarpophalangeal/metatarsophalangeal joint or the diaphysis of MC3/MT3, followed by deformities of the carpal region, with the traumatic deformation of the carpal bones or the distal radius being the focus. Reports also exist of surgical correction of deformities involving the radial diaphysis (Auer, 2019).A thorough examination of the limb in question is necessary for surgical planning, including static and dynamic examination of the patient. Angular limb deformities can be complex with deformities in more than one plane and so a detailed understanding of the abnormality is fundamental for surgical success. Radiographs and computed tomographic examination of the affected area should be performed on all candidates. Three-dimensional printing combined with planning software can be valuable in assessing complicated deformities (Auer 2019, Auer 2022). When the abnormality involves only a simple deviation, the pivot point should be established based on pre-operative imaging, which is accomplished by drawing lines perpendicular to the joint surfaces proximal and distal to the deformity of the involved long bones and identifying the bisection point. The degree of deviation can then be calculated based on this point. In more complex cases, multiple pivot points may exist in different planes. These bisecting pivot points are used to determine the correction angle to be utilized intra-operatively. Identifying the complexity of the deformity as well as the planes involved will influence the surgical technique to be utilized. (Auer, 2019)

This special feature explored the evolving relationship between humans and brown bears in Hokkaido, Japan, considering shifting wildlife management policies and global biodiversity conservation efforts. Drawing on discussions from symposia held in 2023 and 2025, the collection of articles traced the historical phases of the human-bear relationship—from reverence and utilization (HBR ver.0), to extermination (HBR ver.1), protection and population recovery (HBR ver.2), and the current call for coexistence through mutual vigilance between humans and bears (HBR ver.3). As bears reduce their fear of humans, conflicts such as agricultural damage and human injuries have increased, highlighting the need for new management strategies. A distinctive aspect of Hokkaido’s strategy is categorizing bears as either nuisance or non-nuisance, based on traditional Ainu knowledge. This categorization is made possible through the long-term monitoring of the number of nuisance bears. This approach represents a form of active adaptive management that is rarely seen in large mammal conservation. The case of Hokkaido’s brown bears illustrates a broader global challenge—how a society facing population decline and wildlife recovery can sustainably coexist with large wildlife. This requires not only ethical reflection but also practical, science-based solutions.

Interactions between species structure ecological communities and regulate the flow of energy and information across ecosystems. In marine environments, fishes engage in a wide variety of behavioral associations ranging from mutualistic symbioses to opportunistic foraging interactions. However, these interactions are typically studied independently, limiting our understanding of how multiple interaction types jointly shape community structure in local and regional scales. Here we compile four decades of observations of interspecific associations between marine fishes in the Southwestern Atlantic Ocean and analyze them using an ecological network framework. Our dataset includes 234 species from 14 taxa participating in twelve types of behavioral interactions, including cleaning symbiosis, nuclear–follower assemblages, mimicry, hitchhiking, ecosystem engineering, and waste feeding. Temporal patterns reveal increasing research activity since the late 1990s, with a strong dominance of cleaning and nuclear–follower interactions. However, after 2012 the number of studies has decreased across time. Our network analyses show that individual interaction layers (i.e., type of interactions) tend to display nested organization, whereas the combined multilayer network exhibits modular structure. These results indicate that marine fishes participate opportunistically across multiple interaction layers while also forming specialized modules associated with ecological roles. Our findings demonstrate that integrating multiple interaction types provides new insights into the organization and functioning of marine communities.

Changes in nitrogen (N) deposition and precipitation regime are widely recognized as key drivers of the structure and functioning of terrestrial ecosystems. Precipitation in semi-arid regions show a trend toward increasing precipitation intensity, however, how ecosystem stability responds to the combined changes in precipitation (specifically its intensity and frequency) and N addition, as well as the underlying mechanisms, remains poorly understood. This study focused on a temperate grassland in Inner Mongolia, using 8-year data from a field experiment to investigate the effects of N addition (0, 10, and 40 g N m⁻² yr⁻¹) and changes in precipitation regime (addition of 80 mm with two different intensity: 10 mm × 8 events and 20 mm × 4 events) on ecosystem stability. The results showed that N addition reduced ecosystem stability by decreasing forb abundance and species asynchrony, mediated by soil pH, highlighting the critical role of forbs in maintaining ecosystem stability. Addition of precipitation alleviated the negative impact of N addition on ecosystem stability. The mitigating effect of precipitation on N-induced instability becomes more pronounced under higher precipitation intensity (lower frequency), mainly through its stimulation of soil moisture and soil pH, which in turn enhance ecosystem stability by promoting species richness and forb abundance. Our findings emphasize the importance of considering changes in precipitation regime when predicting the effects of N deposition on grassland ecosystem stability.

The invasive hemlock woolly adelgid (HWA) was recently detected in Ontario and threatens the province’s eastern hemlock forests. A novel risk matrix was created from species distribution model-based predictions of climatic suitability and host abundance data to predict future HWA establishment and impact in Ontario. We found that HWA can infest townships across southwestern Ontario, but the low proportion of eastern hemlock will limit its impact. Under a low emissions climate change scenario, most eastern hemlock in the province will be threatened by mid-century. The combination of host abundance and climatic suitability values from species distribution models was an effective method to model cumulative risk posed by invasive species using readily available datasets. The preparation of such models allowed the presentation of data in a manner interpretable and applicable to forest managers and invasive pest management practitioners.

Phenotypic variation in migration is widespread, yet the extent to which it reflects underlying genetic differentiation versus environmental modulation remains unresolved in partially migratory species. Using a replicated year‑long mesocosm experiment, we quantified migration reaction norms in brown trout from migratory, resident, and cross‑bred strains tracked with PIT telemetry under high‑ and low‑density conditions. Low density enhanced growth, condition, and migratory propensity, but density did not interact with genetic background. Instead, strains exhibited distinct reaction norms, demonstrating clear genetic divergence and supporting an environmental threshold model in which genetically determined thresholds shape sensitivity to environmental cues. Our results reveal how genetic background constrains plasticity in migration strategies and highlight the importance of conserving genetic diversity to maintain adaptive potential under environmental change.

This paper presents a unified variational framework for high-fidelity dense depth reconstruction from passive imaging systems. We formulate depth estimation as a global energy minimization problem, integrating data fidelity terms derived from stereo correspondence and focus measures with a Total Variation (TV) regularizer. The proposed Alternating Direction Method of Multipliers (ADMM) solver efficiently handles the non-smooth convex optimization, while a Random Walk with Restart refinement post-processes confidence. Extensive experiments on high-precision synthetic facial datasets and real-world automotive street scenes validate the method's robustness across modalities. Quantitative results demonstrate superior convergence and lower RMSE compared to traditional gradient-based methods, effectively mitigating noise while preserving critical depth discontinuities. The framework establishes a mathematical foundation for modality-agnostic depth estimation.

The correct and resilient operation of distributed systems-spanning global financial ledgers, decentralized autonomous organizations, and peer-to-peer energy microgrids-depends fundamentally on the correctness of their underlying consensus mechanisms. These protocols must guarantee agreement on shared state among a collection of potentially faulty or adversarial nodes, upholding the dual properties of safety and liveness even under hostile conditions. Despite the growing diversity of consensus algorithms, from classical crash-fault tolerant approaches such as Paxos and Raft to modern Byzantine fault-tolerant (BFT) variants and Directed Acyclic Graph (DAG)-based structures, the research community lacks a unified architecture for their systematic, cross-platform evaluation. This paper proposes a modular, extensible framework called the Consensus Evaluation and Resilience Framework (CERF) to fill this gap. CERF integrates five core components: a high-fidelity network emulation layer, a pluggable system-under-test (SUT) adapter, a fault injection engine (FIE) capable of simulating both benign and Byzantine failure modes, a multi-dimensional performance monitoring unit (PMU), and a formal consistency checker. By decoupling the testing infrastructure from protocol implementation, CERF enables fair comparisons of throughput, latency, energy efficiency, and scalability. The proposed architecture draws on insights from seminal benchmarking works including BlockBench, Jepsen, and ByzzBench, and extends evaluation criteria to address modern challenges in IoT environments, post-quantum security, and DAG-based ledgers. Graph-theoretical principles are incorporated at the topology design stage to model network vulnerabilities and guide adversarial scenario construction.

This paper presents a comprehensive hybrid architecture for mobile health (mHealth) applications designed to overcome three fundamental limitations in current telemedicine systems: severe data scarcity in medical imaging domains, computational constraints inherent to handheld consumer devices, and the critical need for reliable, safety-guaranteed automated patient guidance. We introduce and experimentally validate a novel, integrated pipeline that strategically combines advanced synthetic data generation using Generative Adversarial Networks (GANs) to create expansive, privacy-preserving dermatological datasets, which in turn train robust diagnostic convolutional neural networks (CNNs). Subsequently, we develop and benchmark an ultra-lightweight, quantization-aware skin segmentation model optimized for real-time inference on standard smartphone hardware, serving as a crucial pre-processing step for reliable analysis. Finally, we integrate a deterministic, rule-based Expert System that processes multimodal patient data-including diagnostic outputs from the visual AI and user-reported metrics-to generate personalized, logically-verifiable management recommendations for chronic conditions, with diabetes mellitus serving as our primary case study. Extensive mathematical formalization, architectural details, and experimental results across synthetic data fidelity (Frechet Inception Distance scores below 15.2), segmentation accuracy (Dice coefficients exceeding 0.95 on mobile CPUs), and decision logic validation are provided. The proposed framework demonstrates that the synergistic integration of probabilistic deep learning and deterministic symbolic reasoning can create a scalable, privacy-conscious, and clinically actionable closed-loop system for remote patient care.

Understanding how genetic drift and inbreeding can shape phenotypic traits and the expression of rare genetic variants can be important for conservation management in small and isolated populations. Following the recolonization of the grey wolf (Canis lupus) on the Scandinavian peninsula, the population has remained small and semi-isolated. The population traces back to seven founders, only and is highly inbred. Inbreeding depression has been demonstrated including effects on reproductive output and several congenital deformities. Some wolves also show anomalous coat color, characterized by hypopigmentation displayed as white tail tips, or even larger areas of white fur. In this study, we utilized four decades of monitoring data, dating back to the recolonization of the Scandinavian peninsula in 1983, to examine the occurrence of expressed anomalous coat color investigating its origin and inheritance, genetic architecture, and the effect of inbreeding. SNP genotyping revealed a distinct haplotype linked to the Melanocyte-inducing transcription factor (MITF) gene that co-segregated with anomalous coat color, suggesting a direct causal effect of this variant. The MITF gene regulates mammal melanocyte development, which in turn affects pigmentation. Our findings demonstrate that the identified gene variant is recessive, which in the homozygous state likely causes the disruption of normal melanocyte development, leading to unpigmented or hypopigmented areas. The origin of this haplotype was traced back to a third founder, reproducing for the first time in 1991. Indeed, the genetic constraints and subsequent inbreeding shaped by few founders, small population size, and semi-isolation over several decades point towards the importance of genetic diversity and facilitated gene flow between populations, but also how such vital immigration can bring about unforeseen side effects if inbreeding continues within the immigrant lineages.

This paper introduces LuminaDepth, a unified deep learning framework for the joint recovery of dense three-dimensional geometry and intrinsic material properties from sparse, heterogeneous, and lowresolution sensor data. Conventional computer vision pipelines, heavily reliant on high-quality RGB or specialized depth sensors (e.g., Li-DAR), fail in adverse conditions typical of low-power consumer devices, thermal imagers, or medical sensors. LuminaDepth addresses this by formulating a coupled problem of signal enhancement and geometry estimation as an intrinsic decomposition task within a neural field representation. The core innovation is an attention-guided mechanism that modulates multi-scale features to preserve high-frequency details critical for depth disambiguation, alongside a novel neural gain control layer for sensor-agnostic input normalization. We pre-train the model on a large-scale synthetic dataset to learn robust priors for shape and reflectance, enabling effective transfer to real-world sparse data without requiring ground-truth 3D scans. Extensive mathematical formulation and experimental validation across two distinct domains-medical surface topology reconstruction from clinical photos and object detection enhancement in autonomous thermal imaging-demonstrate state-ofthe-art performance. LuminaDepth significantly outperforms monocular depth estimators and traditional image enhancement operators, offering a versatile solution for resource-constrained and non-standard imaging applications.

Objective: To analyse the evolution of cesarean section rates over three separate years, decades apart at Dubai Hospital using the Robson classification. Design: Retrospective observational study Setting: Tertiary care hospital in Dubai Population: 9,998 women who delivered at a during three distinct periods: 2002, 2012, and 2022 Method: Deliveries were categorized into ten mutually exclusive Robson groups based on six obstetric parameters- number of fetus, parity, gestational age, previous cesarean, fetal lie and onset of labour. We evaluated group size, group-specific cesarean section rates, absolute and relative contributions to the overall cesarean rate, alongside shifts in maternal demographics and instrumental delivery trends. Results: The overall cesarean section rate was 24.65% in 2002, 27.77% in 2012 and 40.17% in 2022. Notably, cesarean section rates in unscarred multipara (Group 3) were found to be considerably low, at 5.97% in 2002, 4.00% in 2012 and 5.36% in 2022. Group 5b (women with more than one prior cesarean section) demonstrated a progressive increase in size, from 3.15% in 2002 to 6.77% in 2012 and 7.32% in 2022. Group 10 (preterm, cephalic presentation) similarly expanded in proportion, rising from 6.18% in 2002 to 7.53% in 2012 to 12.41% in 2022, with a corresponding escalation in cesarean section rate from 32.5% in 2002 to 44.76% in 2012 to 61.05% in 2022. The cesarean section rate among nulliparous women in spontaneous labor (Group 1) increased from 20.5% in 2002 to 26.6% in 2022. Conclusions: This retrospective analysis demonstrates the disproportionate contribution of Group 5b and Group 10 to the rising cesarean section rates observed over the study period. The progressive accumulation of women with multiple prior cesarean sections reflects the compounding obstetric consequences of primary cesarean delivery, emphasizing the critical importance of judicious decision-making at the time of first cesarean. The concurrent expansion of Group 10 in both proportional size and cesarean section rate signals an increasing preterm birth burden.

Pterocarpus marsupium Roxb., locally known as Bijaysal, is a high-value tropical deciduous tree with a restricted and fragmented distribution in Nepal. We integrated 129 spatially occurring records with climatic, anthropogenic, edaphic, and topographic variables in an ensemble species distribution modelling framework (biomod2) to project current and future (2050s and 2090s) habitat suitability under four shared socioeconomic pathways (SSP) scenarios. Minimum temperature of the coldest month and precipitation seasonality were the dominant climatic drivers, followed by soil organic carbon, bulk density, and human footprint. The current suitable habitat is limited (11,154 km²; 7.6 % of Nepal) and confined to the western and central lowlands. Future projections indicate habitat expansion ranging from 40 % (SSP1-2.6 2090s) to 313 % (SSP2-4.5 2050s) with consistent southeastward centroid shifts (46–127 km), reflecting both northward expansion into the mid‑hills and eastward reorganization within the lowlands. However, these projections should be interpreted with caution, as actual migration may be limited by seed dispersal mechanisms and soil suitability in high-elevation zones. The unimodal response to human footprint challenges the conventional protected-area paradigm and indicates that well-managed community forests can serve as critical climate refugia. These findings suggest that well‑managed community forests can complement protected areas by maintaining intermediate disturbance and provide a spatially explicit roadmap for assisted colonization into the mid‑elevation zones.

• As climate change accelerates, increasing ocean temperatures and altered herbivory pressure are reshaping temperate marine ecosystems dominated by macrophyte foundation species. Despite the importance of these processes, it remains unclear how reduced above-ground biomass, due to anticipated in-creased herbivory, will affect the thermal performance of macrophytes. • We simulated herbivory by clipping the leaf length of two temperate seagrass species, Posidonia australis and Heterozostera tasmanica, and grew them at temperatures spanning their thermal range (6-32 °C). We assessed the effects of leaf size on thermal performance by quantifying growth, photosynthetic rates, leaf nutrient content and pigment concentrations. • Responses to clipping treatment and growing temperature were species-specific. Highly clipped P. australis showed higher photosynthetic rates and nutrient concentrations at 32 °C, relative to low-clipped and control plants, while growth did not differ between clipping treatments and survival was high across treatments. In H. tasmanica, clipping lowered optimal growth temperatures, and survival declined sharply at 32 °C across treatments. • Our results suggest that smaller leaf size can increase thermal resilience in P. australis, whereas high herbivory of H. tasmanica is likely to increase its sensitivity to thermal stress. Increased herbivory pressure under climate change may therefore have positive implications for some seagrasses, highlighting the importance of considering species-specific responses when predicting the future resilience of seagrass ecosystems.

Cuticular hydrocarbons (CHCs) are central to insect waterproofing and chemical communication, yet their broad evolutionary pattern in termites has not been synthesized comprehensively. Here, we present a systematic review of termite CHCs with emphasis on worker profiles, caste-level comparisons, and ecological interpretation in a phylogenetic context. The qualitative synthesis included 28 studies, whereas the filtered statistical dataset comprised 37 worker profiles representing 37 species. Across the reviewed literature, termite cuticles contained a recurrent but variable combination of n-alkanes, n-alkenes, alkadienes, alkatrienes, mono-, di-, and trimethylalkanes. Species-level mapping showed that saturated and methyl-branched hydrocarbons are broadly distributed across the termite tree, whereas unsaturated compounds are more unevenly represented and recur in multiple lineages. Genus-level synthesis further showed that dominant worker chemistry is not tightly constrained by phylogeny: methyl-alkane-dominated, olefin-dominated, and mixed profiles all occur across distantly related taxa. Quantitative comparison of selected worker profiles highlighted broad chemistry in Mastotermes darwiniensis, strong methyl-branched dominance in Coptotermes formosanus, dimethyl-rich profiles in Nasutitermes corniger and N. ephratae, and marked alkatriene dominance in Parvitermes wolcotti. Caste-resolved studies showed that workers, soldiers, nymphs, and reproductives usually share the same broad CHC classes, with caste differentiation arising mainly through quantitative shifts, although reproductives in some taxa also express caste-associated compounds. Exploratory ecological analyses indicated that nesting life type explained part of the worker CHC variation: drywood/enclosed wood nesters showed fewer dimethylalkanes and more frequent alkatrienes than other life types. Overall, termite CHC evolution is best interpreted as repeated lineage-specific reweighting of a shared chemical toolkit shaped by both ecology and phylogeny.

A compact, broadband, two-way Wilkinson power divider/combiner is presented, created in 0.18-𝜇m CMOS for use between 60 and 90 GHz. The suggested design uses stacked M5–M6 slow-wave trans- mission lines to shorten the physical quarter-wave length without need- ing extra matching capacitors, which allows for a condensed, meander- ing arrangement. Because of the strong broadside coupling between the stacked conductors, the suggested line has a phase constant about 43% greater than the standard structure at 75 GHz. This lets the necessary 90◦ electrical length be achieved with a considerably shorter physical line. Rather than using M1 as a direct shielding ground, a recurring M1 structure is put under the signal lines as an electromagnetic field-control layer, while the actual RF ground reference is made by the conductive ground under the substrate. Furthermore, an RC isolation network offers frequency-shaped odd-mode damping for wideband isolation. A back- to-back setup is used for precise on-wafer characterization. The mea- surements show an extra insertion loss of 0.5 dB at 75 GHz, a return loss exceeding 20 dB at all ports, and an isolation greater than 34 dB from 60 to 90 GHz within a small 0.086 mm2 core area. The suggested structure works well for small mmWave CMOS front-end uses.

The flexible direct current traction power supply system (DC-TPSS) is a nonlinear system involving kinematics and electrics. Automatic train supervision (ATS) systems are prone to positioning errors and integrate supervision and control systems (ISCS) tend to have missing electrical data of train, making it challenging to accurately obtain the system state in real time. To address these issues, this paper presents a train positioning method that combines the electrical with kinematic measurements for an accurate estimation using a Kalman filter. By solving the real-time power equations for each interval, this method generates pseudo-measured values for the train, addressing the lack of train information in ISCS. Subsequently, a measurement matrix and equations are dynamically generated from the real-time state of the network topology. The weighted least squares (WLS) method is used to filter out bad data for accurate estimates. a flexible DC-TPSS model is finally constructed to verify the accuracy of the algorithm, with the algorithm embedded in the ISCS for in-loop data validation. The results show that the proposed method achieves high-accuracy estimations of the train electrical quantities and position, with significantly reducing variance in the voltage estimation results.

Title: Mathematical Abstract: Informational Multi-connectivity of the AbsolutePrincipal Investigator: Konstantin V. UtolinFormalization Lead: AI Assistant GeminiDate: April 20261. Topological ModelSpace-time is modeled as a stationary n-dimensional (where n can be infinite) manifold with a fixed global parameter of absolute time. The global topology is a limiting case of dense packing of local open subsets. The arrangement and boundaries of these "bubbles" ("rooms") are such that each individual "bubble" (each "room" in the "apartment building") has either an infinite or finite (this remains to be determined mathematically, and then experimentally) number of "doors" (points, and perhaps even areas of contact) with an infinite (or finite?) number of other "bubbles." Boundaries with similar properties can theoretically be described, for example, via fractal structures of the "Lakes of Wada" type. And, accordingly, through these "doors," transitions are possible from one "bubble" to any other with which it shares a "door." And in ordinary local space, the distances between these "bubbles" can be measured in many light years. And even if the number of "doors" in each individual "bubble" is finite, it is possible to construct a chain of "doors" that can lead from each "bubble" to any other.2. Metric Non-localityA distinction is made between the local metric and the topological distance in the connectivity graph of the Absolute. Transitions are automorphisms preserving the global time functional.3. "Resonance" ActivationMovement between subsets is an informational phase transition. The condition is a topological isomorphism between the observer's operator algebra and the structural invariant (homology class) of the "door," described via the resonance of eigenvalues of operators in space (may be Topological, or Fock).4. Cosmological InterpretationObserved expansion is the evolution of local connectivity while the total volume of remains invariant. Dark energy is the metric pressure of informational flux from non-locally coupled nodes.© 2026 Konstantin V. Utolin. License: Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0)Acknowledgment: This work is a product of human-AI (Gemini) collaborative conceptual research.

Objective: To evaluate the relationship between specific pelvic floor–related fears and mode of delivery preference in primigravid women, and to determine the independent effect of these fears on cesarean preference. Design, Setting, Population: Cross-sectional group-comparative study conducted at a tertiary obstetrics center including 510 primigravid women at 32–35 weeks of gestation. Participants were classified into three groups based on delivery preference: vaginal, cesarean, and undecided Methods: Pelvic floor–related fears were assessed using a structured scale with four subscales. A total concern score (0–40) was calculated. Associations between delivery preference and fear scores were analyzed using appropriate statistical methods. Main Outcome Measures: Primary outcome was preference for cesarean delivery. The main exposure variable was the total concern score; subscale scores were evaluated secondarily. Results: The total concern score differed significantly across delivery preference groups (p=0.002) and was higher among women preferring cesarean delivery. Significant differences were observed for fears of urinary incontinence (p=0.001) and perineal deformity (p=0.015), while other subscales were not significant. ROC analysis showed limited discriminatory performance (AUC=0.586; p=0.003). In multivariate analysis, a total concern score ≥25.5 independently increased the likelihood of cesarean preference (OR=1.41; 95% CI: 1.01–2.08; p=0.048). Conclusions: Pelvic floor–related fears significantly influence delivery preferences in primigravid women, with the total concern score emerging as an independent predictor of cesarean preference. Addressing these fears during antenatal care may help reduce non-medically indicated cesarean rates. Funding: No funding was received for this study.

Background: Genitourinary syndrome of menopause (GSM) is a chronic, progressive consequence of hypoestrogenism that affects vaginal, sexual and lower urinary tract health. Treatments include local vaginal estrogen, intravaginal prasterone, oral ospemifene, hyaluronic acid preparations, moisturizers and lubricants and energy-based interventions, but direct head-to-head randomized evidence is limited. Objective: To compare the relative efficacy and safety of contemporary GSM therapies using a systematic review and class-level network meta-analysis of randomized controlled trials. Methodology: MEDLINE/PubMed, Scopus, Cochrane CENTRAL, Web of Science, Google Scholar, ClinicalTrials.gov and WHO ICTRP were searched from inception to 1 March 2026, with backward and forward citation searching. Randomized controlled trials enrolling postmenopausal women with GSM, vulvovaginal atrophy or atrophic vaginitis were eligible. Interventions included local vaginal estrogen, prasterone, ospemifene, hyaluronic acid, moisturizers/lubricants, carbon dioxide laser and radiofrequency. Two reviewers independently screened records and extracted data. The primary efficacy outcome was change in the most bothersome symptom or, when unavailable, dyspareunia or vaginal dryness measured closest to 12 weeks. Risk of bias was assessed with RoB 2. Direct and indirect evidence were synthesized using a random-effects class-level network approach. Results: Twenty-six randomized trials were included. The evidence network was anchored primarily by placebo/sham and local estrogen. In the harmonized continuous symptom network, local estrogen (standardized mean difference [SMD] 0.89, 95% confidence interval [CI] 0.29 to 1.48) and hyaluronic acid (SMD 0.84, 95% CI 0.01 to 1.68) were superior to placebo/sham, while radiofrequency showed a large but sparse estimate (SMD 1.29, 95% CI 0.21 to 2.38). Confidence intervals crossed the null for carbon dioxide laser, moisturizer, ospemifene and prasterone. In the smaller binary responder network, both local estrogen (risk ratio [RR] 2.39, 95% CI 1.69 to 3.38) and hyaluronic acid (RR 2.32, 95% CI 1.64 to 3.29) improved response rates versus placebo/sham. Across the broader evidence base, local estrogen showed the most consistent improvement in vaginal pH and epithelial maturation; prasterone and ospemifene remained effective alternatives in dedicated placebo-controlled programs. Safety events were generally mild and infrequent, but device estimates were less stable and sparse device-related loops showed local inconsistency. Conclusions: Local vaginal estrogen remains the benchmark therapy for GSM. Prasterone and ospemifene are evidence-based alternatives, hyaluronic acid is the strongest active non-hormonal option and moisturizers/lubricants remain appropriate for symptom-focused first-line care. Carbon dioxide laser and radiofrequency should be interpreted cautiously until stronger sham-controlled and long-term data are available.

Authors:Sathesh BaskaranDr. G. Saravanakumar M.S., D.A., F.P.SAffiliation:  Madurai foot care Centre, Madurai, Tamil Nadu, IndiaCorresponding Author:Sathesh BaskaranEmail: sbaskaran@newvision.gePhone: +918754673570

This study investigates intracellular (IC) exposure to tenofovir alafenamide (TAF) and its clinical determinants in experienced people living with HIV. We conducted a monocentric retrospective analysis of 86 adults treated with either Bictegravir (BIC) or dolutegravir (DTG) triple regimen. Plasma and IC trough concentrations (C trough) of tenofovir diphosphate (TFV-DP) were examined in relation to demographic and renal parameters. A significant correlation emerged between plasma and IC TFV-DP C trough. Higher plasma TFV-DP levels were associated with older age and reduced estimated glomerular filtration rate. Adherence calculated as proportion pf days covered (PDC) did not differ between regimens. These findings provide novel real‑world insights into IC TFV pharmacokinetics and suggest that BIC‑containing regimens may enhance IC drug accumulation and virological outcomes. Prospective studies are needed to clarify the clinical implications of intracellular antiretroviral concentrations.