Search Results (698)

Oct4 is well established as a core regulator of pluripotency, yet emerging evidence points to an additional role in lineage specification during the exit from the pluripotent state. Although Oct4 expression has been observed in early mesodermal progenitors, its precise function in this developmental context remains unclear. To investigate this, we employed embryoid bodies (EBs) as a model of spontaneous differentiation that recapitulates key aspects of early embryonic development in vitro. In accordance with previous studies, reporter assay revealed a distinct temporal pattern characterized by the strong, transient co-expression of Oct4 and the early mesoderm-specifying marker gene Brachyury within a narrow developmental window, consistent with the Oct4 role in early mesodermal progenitors. We further examined the consequences of the Oct4 loss at early stages of this differentiation. Conditional knockout of the Oct4 gene resulted in a significant reduction in EB size and accumulation of cells in the G0/G1 phase, indicating a critical requirement for Oct4 in maintaining cell proliferation. Despite this defect, cells retained the ability to initiate multilineage differentiation, albeit with reduced expression of Brachyury and elevated expression of endodermal markers FoxA2 and Sox17. Interestingly, the formation of beating cardiomyocyte-like structures was also diminished following Oct4 loss and could not be rescued by simply increasing cell numbers. Taken together, these findings highlight an important Oct4 function in mesodermal differentiation, mediated through the maintenance of proliferative capacity of early mesodermal progenitors. Full article

Objective: Intraoperative hypothermia is a common perioperative complication. This large-scale, multicenter, prospective clinical study aimed to delineate the occurrence patterns of intraoperative hypothermia in adults and to identify its major independent risk factors, thereby providing evidence-based support for early clinical risk assessment and intervention. Methods: This study adopted a multicenter, prospective, observational design. Eligible participants were screened based on predefined inclusion and exclusion criteria, and a total of 4516 surgical patients (≥18 years) from 12 tertiary general hospitals across China were ultimately enrolled. Core body temperature was continuously monitored intraoperatively using standardized methods. Data on demographic characteristics, surgical and anesthesia-related parameters, and perioperative temperature management interventions were collected. Patients were stratified into groups according to the presence or absence of hypothermia (core temperature <36.0 °C). Univariate analyses were first conducted to identify associated factors, followed by multivariable logistic regression to determine factors independently associated with intraoperative hypothermia. Results: The overall incidence of intraoperative hypothermia among surgical patients was 23.82%. Hypothermia occurred most frequently in patients with a preoperative baseline core temperature ≤ 35.9 °C (85.93%). Among surgical specialties, hand surgery had the highest incidence of hypothermia (51.35%), and among surgical sites, procedures involving the upper extremities showed the highest rate (35.00%). Multivariable logistic regression analysis identified the following as independent risk factors for intraoperative hypothermia: Type of anesthesia (OR = 1.743, 95% CI: 0.834–3.644), ASA classification (OR = 1.408, 95% CI: 1.197–1.657), Surgical approach (OR = 0.735, 95% CI: 0.577–0.936), Skin disinfection site (OR = 2.024, 95% CI: 1.534–2.670), Volume of cold intravenous fluids infused (mL) (OR = 1.365, 95% CI: 1.140–1.633), Volume of transfused blood (U) (OR = 1.116, 95% CI: 0.807–1.542), Intraoperative blood loss (mL) (OR = 1.252, 95% CI: 0.892–1.756), and Duration of surgery (hours) (OR = 2.014, 95% CI: 1.683–2.411). Conclusions: The incidence of intraoperative hypothermia in adults was relatively high at 23.82% and was observed to be associated with multiple modifiable perioperative factors. These findings support the need to strengthen risk assessment and implement individualized temperature management strategies in clinical practice, with the goal of reducing the risk of intraoperative hypothermia and improving perioperative safety and outcomes. Full article

The Space–Air–Ground Integrated Network (SAGIN), a core architecture for 6G, faces formidable routing challenges stemming from its high-dynamic topological evolution and strong heterogeneous resource characteristics. Traditional protocols like OSPF suffer from excessive convergence latency due to frequent topology updates, while existing intelligent methods such as DQN remain confined to a passive reactive decision-making paradigm, failing to leverage spatiotemporal predictability of network dynamics. To address these gaps, this study proposes an adaptive routing algorithm (GCN-T-PPO) integrating a GCN-Transformer hybrid encoder, Particle Swarm Optimization (PSO), and Proximal Policy Optimization (PPO) with spatiotemporal attention. Specifically, the GCN-Transformer encoder captures spatial topological dependencies and long-term temporal traffic evolution, with PSO optimizing hyperparameters to enhance prediction accuracy. The PPO agent makes proactive routing decisions based on predicted network states (next K time steps) to adapt to both topological and traffic dynamics. Extensive simulations on real dataset-parameterized environments (CelesTrak TLE data, CAIDA 100G traffic statistics, CRAWDAD UAV mobility models) demonstrate that under 80% high load and bursty Pareto traffic, GCN-T-PPO reduces end-to-end latency by 42.4% and packet loss rate by 75.6%, while improving QoS satisfaction rate by 36.9% compared to DQN. It also outperforms SOTA baselines including OSPF, DDPG, D2-RMRL, and Graph-Mamba. Ablation studies validate the statistical significance (p < 0.05) of key components, confirming the synergistic gains from spatiotemporal joint modeling and proactive decision-making. This work advances SAGIN routing from passive response to active prediction, significantly enhancing network stability, resource utilization efficiency, and QoS guarantees, providing an innovative solution for 6G global seamless coverage and intelligent connectivity. Full article

Background and Objectives: Sjögren’s syndrome (SS) causes destructive salivary gland dysfunction with substantial oral morbidity. To synthesize practical, evidence-based approaches for early recognition, initial oral management, and timely referral to dental care. Materials and Methods: Narrative review of English-language literature from the Web of Science Core Collection and PubMed, prioritizing systematic reviews, randomized trials, and consensus guidelines. Results: Early oral signs include rapid multifocal root and cervical caries, burning sensations, and rising dental treatment needs. Unstimulated whole saliva ≤ 0.1 mL/min supports significant hypofunction and complements the 2016 ACR/EULAR criteria. Preventive care should combine dietary counseling, salivary stimulation, and topical remineralization. Adjuncts include high-fluoride toothpaste, biomimetic hydroxyapatite dentifrices, and casein phosphopeptide–amorphous calcium phosphate (CPP-ACP). However, evidence for fluoride varnish in SS remains mixed. Pharmacologic sialogogues require screening for contraindications. Conclusions: Embedding oral screening, simple salivary metrics, and a structured referral pathway into rheumatology visits can reduce preventable tooth loss and improve comfort, function, and treatment adherence. Full article

Steep olive orchards in northwest Syria are experiencing severe land degradation as a result of unsustainable uphill–downhill tillage, which accelerates erosion and reduces productivity. To address this problem, three tillage systems, no-till natural vegetation strips (NVSs), contour tillage, and uphill–downhill tillage, were evaluated at two research sites, Yakhour and Tel-Hadya, NW Syria. The adoption of no-till NVSs significantly increased soil organic matter (SOM) at both sites, outperforming uphill–downhill tillage. While contour tillage resulted in lower SOM levels than NVSs, it still performed better than the conventional uphill–downhill practice. Contour soil flux (CSF) was lower in Yakhour, where mule-drawn tillage on steep slopes (31–35%) was practiced, compared to higher CSF values in Tel-Hadya, where tractor tillage was applied on gentler slopes (11–13%), which highlights the influence of slope steepness on soil fluxes. Over four years, net soil flux (NSF) indicated greater soil loss under tractor tillage, confirming that mule-drawn tillage is less disruptive. Olive trees with no-till NVSs benefited from protected root systems, improved soil structure through SOM accumulation, reduced erosion risk, and improved surface runoff buffering, which resulted in increased water infiltration and soil water retention. This study was carried out using a participatory technology development (PTD) framework, which guided the entire research process, from diagnosing problems to co-designing, field testing, and refining soil conservation practices. In Yakhour, farmers actively identified the challenges of degradation. They collaboratively chose no-till natural vegetation strips (NVSs) and contour tillage as key interventions, valuing NVSs for their ability to conserve moisture, suppress weeds and pests, and increase olive productivity. The farmer–scientist co-learning network positioned PTD not only as an outreach tool but also as a core research method, enabling locally relevant and scalable strategies to restore soil functions and combat land degradation in northwest Syria’s hilly olive orchards. Full article

Inter-basin water transfer projects are core infrastructure for achieving sustainable water resource allocation and addressing regional water scarcity, and pumping station units, as their critical energy-consuming and operation-controlling components, are vital to the projects’ sustainable performance. With the growing complexity and scale of these projects, pumping station units have become more intricate, leading to a gradual rise in failure rates. However, existing fault diagnosis methods are relatively backward, failing to promptly detect potential faults—this not only threatens operational safety but also undermines sustainable development goals: equipment failures cause excessive energy consumption (violating energy efficiency requirements for sustainability), unplanned downtime disrupts stable water supply (impairing reliable water resource access), and even leads to water waste or environmental risks. To address this sustainability-oriented challenge, this paper focuses on the fault characteristics of pumping station units and proposes a comprehensive and accurate fault diagnosis model, aiming to enhance the sustainability of water transfer projects through technical optimization. The model utilizes advanced algorithms and data processing technologies to accurately identify fault types, thereby laying a technical foundation for the low-energy, reliable, and sustainable operation of pumping stations. Firstly, continuous wavelet transform (CWT) converts one-dimensional time-domain signals into two-dimensional time-frequency graphs, visually displaying dynamic signal characteristics to capture early fault features that may cause energy waste. Next, the multi-head attention mechanism (MHA) segments the time-frequency graphs and correlates feature-location information via independent self-attention layers, accurately capturing the temporal correlation of fault evolution—this enables early fault warning to avoid prolonged inefficient operation and energy loss. Finally, the improved convolutional neural network (CNN) layer integrates feature information and temporal correlation, outputting predefined fault probabilities for accurate fault determination. Experimental results show the model effectively solves the difficulty of feature extraction in pumping station fault diagnosis, considers fault evolution timeliness, and significantly improves prediction accuracy and anti-noise performance. Comparative experiments with three existing methods verify its superiority. Critically, this model strengthens sustainability in three key ways: (1) early fault detection reduces unplanned downtime, ensuring stable water supply (a core sustainable water resource goal); (2) accurate fault localization cuts unnecessary maintenance energy consumption, aligning with energy-saving requirements; (3) reduced equipment failure risks minimize water waste and environmental impacts. Thus, it not only provides a new method for pumping station fault diagnosis but also offers technical support for the sustainable operation of water conservancy infrastructure, contributing to global sustainable development goals (SDGs) related to water and energy. Full article

Background/Objectives: Skin cancer is one of the most common diseases in the world, whose early and accurate detection can have a survival rate more than 90% while the chance of mortality is almost 80% in case of late diagnostics. Methods: A modified EfficientNet-B0 is developed based on mobile inverted bottleneck convolution with squeeze and excitation approach. The 3 × 3 convolutional layer is used to capture low-level visual features while the core features are extracted using a sequence of Mobile Inverted Bottleneck Convolution blocks having both 3 × 3 and 5 × 5 kernels. They not only balance fine-grained extraction with broader contextual representation but also increase the network’s learning capacity while maintaining computational cost. The proposed architecture hyperparameters and extracted feature vectors of standard benchmark datasets (HAM10000, ISIC 2019 and MSLD v2.0) of dermoscopic images are optimized with the quantum-behaved particle swarm optimization algorithm (QBPSO). The merit function is formulated by the training loss given in the form of standard classification cross-entropy with label smoothing, mean fitness value (mf^val), average accuracy (mAcc), mean computational time (mCT) and other standard performance indicators. Results: Comprehensive scenario-based simulations were performed using the proposed framework on a publicly available dataset and found an mAcc of 99.62% and 92.5%, mfval of 2.912 × 10⁻¹⁰ and 1.7921 × 10⁻⁸, mCT of 501.431 s and 752.421 s for HAM10000 and ISIC2019 datasets, respectively. The results are compared with state of the art, pre-trained existing models like EfficentNet-B4, RegNetY-320, ResNetXt-101, EfficentNetV2-M, VGG-16, Deep Lab V3 as well as reported techniques based on Mask RCCN, Deep Belief Net, Ensemble CNN, SCDNet and FixMatch-LS techniques having varying accuracies from 85% to 94.8%. The reliability of the proposed architecture and stability of QBPSO is examined through Monte Carlo simulation of 100 independent runs and their statistical soundings. Conclusions: The proposed framework reduces diagnostic errors and assists dermatologists in clinical decisions for an improved patient outcomes despite the challenges like data imbalance and interpretability. Full article

This study focused on the preparation of microcapsules that simulate adipose tissue cells via complex coacervation, followed by the formation of block-like fat analogue products through gelation. The results indicated that microcapsules obtained by encapsulating coconut oil with soy protein isolate (SPI) and sodium alginate (SA) through a complex coacervation process could serve as effective fat substitutes in meat products. When the mass ratio of SPI to SA was 3:1, the core-to-wall mass ratio was 1:1, and the total wall material concentration was 3% (w/v), the oil loading rate of the microcapsules reached 39.17%. The particle size of the oil-loaded microcapsules was mainly distributed between 40–180 μm, which was comparable to the size of fat cells in animal adipose tissue. Microcapsules (50%, w/w) were mixed with a 5% (w/v) curdlan dispersion and heated at 95 °C for 60 min to form fat analogues. The fat analogues demonstrated significantly reduced cooking loss, enhanced textural rigidity, and superior chew resistance, achieving performance metrics comparable to those of natural adipose tissue. This dual-phase strategy—combining interfacial engineering of lipid microcapsules with polysaccharide-mediated gelation—provides a promising approach for developing sustainable, plant-based fat alternatives in meat product reformulation. The methodology not only addresses texture and flavour challenges in fat replacement but also enables precise control over lipid content, supporting applications in healthier food systems. Full article

Soil microbial carbon use efficiency (CUE) is the core of the soil carbon (C) cycle that captures a dual microbial control point between soil organic C (SOC) accumulation and loss. The interpretation of these patterns and drivers of microbial CUE after long-term afforestation remains, however, a major scientific challenge. In particular, there are major uncertainties about the role of microbial traits in driving CUE. Here, we compared sites along a 45-year afforestation chronosequence and combined the novel ¹⁸O-H₂O tracer method with metagenomic analysis to quantify CUE and explore the mechanisms underlying microbe-mediated C dynamics. The results showed that soil microbial CUE significantly increased following afforestation and showed a positive relationship with SOC, which suggested that microbial CUE could promote C accumulation in afforested ecosystems. We further found the critical role of microbial traits in the regulation of CUE through altering microbial life history strategies: microbial CUE was positively and significantly correlated with resource acquisition (A) genes, but showed a negative and significant correlation with stress tolerance (S) strategy genes. These results suggested that soil microbes reduce investment in S strategies and shift to A and high yield (Y) strategies, thereby increasing CUE. This knowledge is important because it advances our understanding of the microbial physiological and evolutionary tradeoffs mediating soil C cycling in the context of human-induced land use change. Full article

This study investigates underwater acoustic propagation patterns under mesoscale eddy conditions through numerical modeling and parametric analysis. A mathematical model of mesoscale eddies was developed, and acoustic transmission loss was computed using the BELLHOP ray-tracing model. Systematic simulations were conducted to examine the effects of source depth, eddy polarity (cold/warm), eddy intensity, and seabed topography. The results reveal distinct acoustic behaviors: cold-core eddies shift convergence zones forward, reduce their width, elevate their depth, and enhance convergence gain within certain ranges. In contrast, warm-core eddies displace convergence zones backward, broaden their width, and can induce surface duct formation. Furthermore, seabed topography exerts minimal influence on acoustic propagation under cold-core eddies but significantly modulates propagation under warm-core eddies, with different topographies producing markedly distinct effects. These findings provide valuable insights for marine scientific research and engineering applications leveraging mesoscale eddy phenomena. Full article

This study presents an optimization-driven design of a wireless communications network to continuously transmit environmental variables—temperature, humidity, weight, and water usage—in poultry farms. The reference site is a four-shed facility in Quito, Ecuador (each shed $120\mathrm{m}\times 12\mathrm{m}$) with a data center located $200\mathrm{m}$ from the sheds. Starting from a calibrated log-distance path-loss model, coverage is declared when the received power exceeds the receiver sensitivity of the selected technology. Gateway placement is cast as a mixed-integer optimization that minimizes deployment cost while meeting target coverage and per-gateway capacity; a capacity-aware greedy heuristic provides a robust fallback when exact solvers stall or instances become too large for interactive use. Sensing instruments are Tekon devices using the Tinymesh protocol (IEEE 802.15.4g), selected for low-power operation and suitability for elongated farm layouts. Model parameters and technology presets inform a pre-optimization sizing step—based on range and coverage probability—that seeds candidate gateway locations. The pipeline integrates MATLAB R2024b and LpSolve 5.5.2.0 for the optimization core, Radio Mobile for network-coverage simulations, and Wireshark for on-air packet analysis and verification. On the four-shed case, the algorithm identifies the number and positions of gateways that maximize coverage probability within capacity limits, reducing infrastructure while enabling continuous monitoring. The final layout derived from simulation was implemented onsite, and end-to-end tests confirmed correct operation and data delivery to the farm’s data center. By combining technology-aware modeling, optimization, and field validation, the work provides a practical blueprint to right-size wireless infrastructure for agricultural monitoring. Quantitatively, the optimization couples coverage with capacity and scales with the number of endpoints M and candidate sites N (binaries $M+N+MN$). On the four-shed case, the planner serves 72 environmental endpoints and 41 physical-variable endpoints while keeping the gateway count fixed and reducing the required link ports from 16 to 4 and from 16 to 6, respectively, corresponding to optimization gains of up to 82% and 70% versus dense baseline plans. Definitions and a measurement plan for packet delivery ratio (PDR), one-way latency, throughput, and energy per delivered sample are included; detailed long-term numerical results for these metrics are left for future work, since the present implementation was validated through short-term acceptance tests. Full article

Power converters are essential for solar energy systems but achieving over 96% efficiency at 1 kW and 300 kHz with compact magnetic and EMC compliance remains challenging for high-power-density PV applications. This study presents the design, modeling, and experimental validation of a 1 kW two-phase interleaved boost converter operating from 12 V input to 48 V/20 A output, featuring a single EE32 Litz-wound coupled-core inductor with coupling coefficient k = −0.475 that reduces per-phase current ripple to just 120 mA (0.6% relative) at full load, a load-selective active zero-current switching (ZCS) circuit activated above 5 A threshold via DCR sensing to minimize switching losses without light-load penalties, and digital peak-current control with 2P2Z compensator implemented on an XMC4200 microcontroller, ensuring robust stability. Experimental results demonstrate peak efficiency of 98.6% at approximately 190 W load, full-load efficiency of approximately 96% with total losses limited to 40 W dominated by conduction rather than switching, thermal rise below 80 °C on key components, voltage regulation with less than 1% deviation down to 2 A minimum load, and full compliance with electromagnetic compatibility standards, including EN 55014-1/2 and EN 61000-4-2 ESD testing. The novel integration of selective ZCS, single-core magnetic, and high-frequency operation outperforms prior interleaved boost converters, which typically achieve 94–97% peak efficiency at lower switching frequencies of 20–100 kHz using multiple inductors or complex always-active resonant networks, making this solution particularly suitable for compact photovoltaic micro-converters, electric vehicles, and industrial power supplies requiring high efficiency, reliability, and regulatory compliance. Full article

Background: Transition from paediatric to adult care in congenital heart disease (CHD) represents a pivotal and vulnerable phase that critically influences long-term survival, morbidity, and quality of life. Advances in paediatric cardiology and surgery have generated a rapidly growing population of adults with congenital heart disease who exhibit complex, lifelong, and multidisciplinary needs. However, survival does not equate to cure, and discontinuity of care during adolescence remains a major predictor of adverse outcomes. Despite widespread recognition of their importance, transition programmes are heterogeneous worldwide, and standardised, evidence-based protocols are missing. Objective: This review calls for action acknowledging the urgent need for structured and standardised transition programmes in CHD care, integrating the key elements that should be addressed in any programme to optimise outcomes. Content: Transition should be understood as a multidisciplinary, longitudinal process integrating medical management, patient and family education, psychological preparation, and societal inclusion. Core domains include tailored physical activity, nutritional counselling, cardiovascular risk factor management, infective endocarditis prevention, reproductive health, psychosocial support, and engagement of primary care providers, educators, and employers. Evidence demonstrates that structured transition programmes enhance health literacy, adherence, and self-management, while reducing loss to follow-up. The active involvement of primary care providers, psychologists, educators, and employers is essential to sustain holistic and equitable care. Conclusions: Transition should be reframed as an essential, lifelong component of CHD care. The development and implementation of standardised, multidisciplinary, evidence-based transition protocols are urgently required to ensure continuity, empower patients, and optimise long-term clinical and psychosocial outcomes for adults with CHD. Full article

Background/Objectives: Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB) are neurodegenerative disorders characterized by the accumulation of misfolded alpha-synuclein protein in the brain. Mutations in the glucocerebrosidase 1 (GBA1) gene have been identified as a significant genetic risk factor for both PD and DLB. GBA1 encodes for the lysosomal enzyme glucocerebrosidase, which is responsible for the breakdown of glucosylceramide (GC). Deficiencies in glucocerebrosidase activity lead to the accumulation of glucosylceramide within lysosomes, contributing to lysosomal dysfunction and impaired protein degradation. The aim of this narrative review is to update the underlying mechanisms by which GBA1 mutations contribute to the pathogenesis of PD and DLB. Methods: A comprehensive literature search was conducted across four major electronic databases (PubMed, Web of Science (Core Collection), Scopus, and Embase) from inception to 8 November 2025. The initial search identified approximately 1650 articles in total, with the number of hits from each database being as follows: PubMed (~450), Web of Science (~380), Scopus (~520), and Embase (~300). Results: The mechanism by which mutations in the GBA1 gene contribute to PD involves both loss-of- function and gain-of-function pathways, which are not mutually exclusive. Typically, GBA1 mutations lead to a loss of function by reducing the activity of the GCase enzyme, impairing the autophagy- lysosomal pathway and leading to α-synuclein accumulation. However, some mutant forms (GBA1L444P) of the GCase enzyme can also acquire a toxic gain of function, contributing to α-synuclein aggregation through mechanisms like endoplasmic reticulum stress and misfolding. While Venglustat effectively reduced GC levels, a key marker associated with GBA1-PD, the lack of clinical improvement led to the discontinuation of its development for this indication. Conclusions: GBA1-mediated lysosomal and lipid dysregulation represents a key pathogenic axis in PD and DLB. Understanding these mechanisms provides crucial insight into disease progression and highlights emerging therapeutic strategies—such as pharmacological chaperones, substrate reduction therapies, and gene-targeted approaches—aimed at restoring GCase function and lysosomal homeostasis to slow or prevent neurodegeneration. Full article

To address the limitation of the IEC 60287 standard in accurately representing the electrothermal characteristics of cables under different grounding conditions, this study proposes a modified equivalent thermal resistance method, using a YJLW03-Z 64/110 1 × 1200 mm² high-voltage single-core cable as a case study to analyze three typical grounding modes, namely two-end solid bonding, segmented solid bonding, and semiconductive outer sheath. Equivalent circuit models are established to calculate the induced current, voltage, and losses of the metallic sheath and armor. Based on these results, the equivalent thermal resistance model is modified, and correction formulas for cable ampacity considering grounding effects are derived. The proposed model is validated through numerical simulations under typical laying conditions and field tests conducted in Zhoushan, Zhejiang Province. Results show that grounding modes significantly influence the electromagnetic losses and temperature distribution of cables. Segmented solid bonding effectively reduces sheath losses and increases ampacity, while its enhancement tends to stabilize beyond two bonding sections. The semiconductive outer sheath improves electric field distribution and thermal stability with limited ampacity gain. This study provides theoretical guidance and engineering reference for optimizing grounding designs, ampacity evaluation, and digital operation of high-voltage cable systems. Full article