Search Results (43,610)

The aim of this study was to determine the effects of supplementing quail diets with 0.5% thyme, sage, mint, and oregano powder on nutritional performance. A total of 400 one-day-old quail chicks, standardized for live weight, were randomly assigned to five treatment groups with four replicates per group (20 chicks per replicate). The groups were allocated to treatments as C—control, T—thyme, S—sage, M—mint, and O—oregano. The experiment lasted for 35 days. Chicks were reared in cages sized 70 × 90 × 60 cm, with a 10 cm layer of wood shavings on the ground. Feed and water were provided ad libitum. At the end of the experiment, live weight gain and lactic acid bacteria (LAB) colonization in ceca were significantly higher in the T (thyme) and O (oregano) groups compared to the C, S and M groups (p < 0.05). Malondialdehyde (MDA) levels in the breast meat were lower in the S, M and O groups compared to the C group. Jejunal villi length was significantly greater in the S and O groups compared to the others (p < 0.05). In the ileum, villi height was higher in the T group than in the other groups (p < 0.05). The villi height/crypt depth ratio in the jejunum was significantly higher in the T and O groups compared to the C group (p < 0.05), whereas in the ileum, this ratio was lower in the S group than in the other groups. Mucin-2 level in the ileum was significantly reduced in the S, M and O groups compared to the C group (p < 0.05) and was similar between T and C. In conclusion, dietary supplementation with vegetative powder of thyme and oregano can be used to improve growth, intestinal villi morphology and LAB colonization in quails. Also, low-dose herbal powder supplementation can be used to suppress MDA formation in the breast meat stored at 4 °C for 3 days. Full article

Background: Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease and end-stage renal disease worldwide. Despite robust evidence-based guidelines, real-world adherence to recommended preventive care remains inadequate. Most prior evaluations have focused on individual care components rather than comprehensive composite care delivery. Methods: A retrospective cross-sectional study of 1010 adult patients with diabetes attending outpatient clinics at King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Jeddah, Saudi Arabia. Full guideline-concordant care (GCC) was defined as composite completion of HbA1c monitoring, albuminuria screening using the urine albumin-to-creatinine ratio (ACR), and renin–angiotensin–aldosterone system inhibitor (RAASi) use among patients with detected albuminuria. Multivariable logistic regression (n = 1007) identified independent predictors of full GCC. Results: Only 22.7% (95% CI: 20.1–25.3%) of patients achieved full GCC. Partial care was the most common pattern (46.2%), followed by no care (20.7%) and near-complete care (10.4%). HbA1c testing was performed in 55.0% and albuminuria screening in 49.3% of patients. Among those with detected albuminuria, RAASi therapy was prescribed in 78.9%. Primary care management (OR 4.79, 95% CI 3.45–6.66; p < 0.001) and hypertension (OR 2.00, 95% CI 1.33–3.00; p = 0.001) were independently associated with full GCC. Age, gender, kidney function, and cardiac disease were not significant predictors. Conclusions: Substantial gaps exist in guideline-recommended DKD care, driven primarily by screening deficiencies rather than treatment failures. Care delivery is influenced more by healthcare setting than by patient characteristics, highlighting the need for system-level interventions targeting detection infrastructure across all care settings. Full article

Background and Objectives: Hyperphosphatemia is a key component of chronic kidney disease-mineral and bone disorder and is associated with higher rates of cardiovascular events and mortality in patients undergoing dialysis. Phosphate binders are essential for phosphorus reduction, and their evaluation relies on several factors, such as chemical composition, binding capacity, and safety profile. Unfortunately, long-term management is hindered by high pill burden and poor adherence. Magnesium phosphate binders have proven effectiveness in reducing phosphate levels. Nevertheless, despite their efficacy, they are not widely used in clinical settings because of concerns related to their use. This study assessed the efficacy of low-dose magnesium carbonate as a phosphate binder in patients undergoing chronic dialysis, focusing on its biochemical control, tolerability, and cost-effectiveness. Materials and Methods: A prospective observational study was conducted on 54 hemodialysis patients with end-stage renal disease at a single dialysis center. Patients were taking either 250 mg magnesium carbonate or 2400 mg sevelamer carbonate for 3 months. Results: Both groups showed decreased phosphorus levels, with a 14.2% significant reduction in the magnesium carbonate group (p < 0.001) and a 5.1% reduction in the sevelamer carbonate group. At the end of the study, no significant differences were observed between the groups (p = 0.682). In the magnesium carbonate group at month 3, compared to baseline, no significant differences were detected in other laboratory parameters reflecting calcium–phosphorus metabolism (Ca—p = 0.681, PTH—p = 0.126). Simultaneously, good compliance without clinically relevant gastrointestinal side effects was observed, including the absence of clinically significant hypermagnesemia. Conclusions: The phosphorus-lowering potential of low-dose magnesium carbonate is non-inferior to that of low-dose sevelamer carbonate. However, its favorable safety profile, low incidence of adverse effects, and cost-effectiveness make it a promising option in clinical practice, further highlighting the need for better recognition by physicians. Full article

Scientific production is expanding so quickly that research teams are struggling to track advances beyond their immediate specialization, especially in interdisciplinary areas where relevant work is scattered across venues and vocabularies. To reduce this overload at the group level, we propose an end-to-end pipeline that transforms structured bibliographic metadata into actionable topic recommendations for research teams. Starting from Scopus records, the method normalizes scholarly text, builds semantic author profiles using Sentence–BERT representations coupled with interpretable keyword descriptors, and forms candidate groups from co-authorship signals and profile similarity. For each group, the approach applies embedding-based topic modeling to generate candidate themes and ranks them using a relevance–novelty trade-off, enabling teams to surface directions that remain aligned with their collective agenda while still encouraging exploration beyond dominant or highly popular topics. Empirical evidence on a Scopus-derived corpus shows that embedding-aware descriptors support cleaner, semantically faithful representations than frequency-based baselines, strengthening downstream topic discovery and producing compact topic lists that are easier for teams to inspect, discuss, and adopt in collaborative planning. Full article

Phosphorus recovery from wastewater and waste streams has become increasingly critical for addressing phosphate-rock supply insecurity and eutrophication control. Building on previous reviews of phosphorus recovery technologies and product applications, this review presents a product-oriented perspective for evaluating phosphorus recovery, explicitly integrating phosphorus sources, process design, product quality, application requirements, regulatory considerations, and life-cycle assessment (LCA) or techno-economic assessment (TEA). Collectively, the available evidence indicates that phosphorus sources differ substantially in phosphorus concentration, speciation, and impurity profiles, underscoring the importance of source–product matching for effective phosphorus recovery. Different phosphorus sources, therefore, require tailored recovery pathways to produce products that satisfy specific quality and application requirements. Product quality is governed primarily by process design rather than by the recovered mineral itself, with purity, contaminant control, regulatory compliance, and end-use suitability ultimately determining the environmental and economic value of recovered phosphorus. A meaningful comparison of recovery pathways further requires harmonized LCA/TEA, as environmental and economic outcomes are highly sensitive to system boundaries, functional units, and allocation assumptions. In addition, regulatory requirements are emerging as a key determinant of product commercialization and should therefore be incorporated throughout process design and technology development. Overall, this review highlights a shift from removal-oriented phosphorus recovery to product-oriented phosphorus recovery, emphasizing the production of high-quality, application-specific phosphorus products as the foundation for technology selection, product innovation, and the transition toward a circular phosphorus economy. Full article

To accurately predict temperature rise due to the concrete hydration heat released from the #0 segment of a continuous concrete girder bridge at an early construction stage for structural design purposes, researchers proposed an approach incorporating empirical predictive formulae with a preliminary numerical analysis. However, due to the uniqueness of the structural geometry and material in each engineering case and the limited data shared by the whole engineering community, no universal predictive empirical model for temperature rise due to hydration heat has yet been identified for practical use that can be applied to a variety of different projects. Moreover, the preliminary numerical analyses are usually based on questionable assumptions and simplifications of the physical truth, the accuracy of which also requires further validation. To this end, the present research measured the time-varying temperature samples of early age massive concrete in the #0 segment of Huangsha Harbor Bridge (a twin-deck three-span continuous concrete box girder bridge located in Jiangsu Province, China) and examined the accuracy of the predictive empirical models formulated by other researchers and the usability of a numerical modal established on a commercial finite element (FE) platform by comparing the corresponding results with the data from the present field measurements. The results suggest that the empirical formulae proposed can generally effectively describe the actual temperature distribution patterns related to the thermal issue, but they are characterized by inferior usability in some cases. In addition, the present comparison also indicates that the actual maximum temperature rise can be correctly predicted by the preliminary FE analysis in most cases. Full article

Terminal glial cells (TGCs) of cutaneous end-organ complexes have traditionally been regarded as structural and trophic elements, although they may also participate in mechanosensory processing. We performed an exploratory immunohistochemical and immunofluorescence study of mechanosensitivity-associated ion channel proteins in human Meissner and Pacinian corpuscles using archival formalin-fixed, paraffin-embedded glabrous skin from 64 donors and several anatomical sites. Immunoreactivity was assessed separately in mechanoreceptor axons and TGCs. In Meissner corpuscles, TGC-associated immunoreactivity for ASIC2 and TRPV4 was observed in subsets of evaluable corpuscles, whereas TRPA1 immunoreactivity was observed in selected specimens. PIEZO1- and PIEZO2-associated immunoreactivity was observed in subsets of corpuscles from the single available labia minora specimen. Among evaluable Pacinian corpuscles, inner-core TGC-associated immunoreactivity was observed for ASIC2, PIEZO2, TRPA1, and TRPV4. Because Pacinian corpuscles were unevenly distributed and scarce outside hand and foot skin, these findings were interpreted exclusively descriptively. To our knowledge, TRPA1 immunoreactivity has not previously been described in TGCs of human sensory corpuscles. These findings are hypothesis-generating and do not demonstrate protein function or mechanotransduction. Because this study used archival tissue and independent target validation was not performed, the results require confirmation using orthogonal antibody- or transcript-based approaches. Full article

Formal undergraduate research training programs are typically two years in length to support student development over time. However, some evidence suggests that many benefits of research participation can be achieved in a shorter duration, raising the question of whether shorter models can be as effective. This prospective study compared outcomes for two concurrent cohort-based research training models: a two-year Scholars Program and an accelerated one-year Fellows Program. The Fellows Program was designed for advanced students who joined the training program later than their peers for a variety of reasons. Both programs provided students with financial support, faculty-mentored research, a Learning Community, and other resources for professional development. The longer duration allowed Scholars to report significantly higher levels of research skills and produce more publications and professional presentations than Fellows by the end of their respective training programs. In contrast, the programs did not differ on graduation GPA, number of awards, or graduate school enrollment. Fellows also did not significantly differ from Scholars on psychosocial measures, including science/researcher identity, belongingness, cultural compatibility, family support, or time management. Findings suggest that a high-intensity, one-year model can deliver many broad academic and social benefits associated with the two-year model, while a longer two-year model provides students with more time and additional research opportunities to be more productive. We conclude that both types of programs should be available to best meet students’ needs and to make the most effective use of program resources. Full article

While drone delivery has gained significant scholarly and industrial interest, rural residents’ acceptance of these systems remains underexplored, despite the region’s acute logistics challenges and service inequities. Using survey data from rural U.S. residents, this study first estimates an ordered logistic regression (OLR) model to identify factors associated with five-level drone delivery acceptance. The study then compares OLR, multinomial logistic regression (MNL), Random Forest (RF), XGBoost, and LightGBM under matched feature sets to evaluate whether nonlinear machine-learning models improve prediction beyond the interpretable statistical baseline. Open-ended responses are coded into LLM-derived sentiment labels and added as supplementary predictors to test whether unstructured feedback improves acceptance prediction. Results show that willingness to pay is the strongest predictor of acceptance, while equitable same-day delivery demand and post-pandemic attitude adjustment are also positively associated with higher acceptance. Household disability status and urban accessibility are not significant after adjustment. In the five-level analysis, OLR provides a strong ordinal baseline, while XGBoost and other tree-based models improve selected class-level prediction metrics. In the binary high-acceptance analysis, machine-learning models show stronger predictive performance, especially when structured predictors are combined with sentiment features. This study contributes to rural drone-delivery literature by linking service equity, perceived value, and LLM-derived sentiment within a comparable statistical and machine-learning framework for rural service design. Full article

SystemVerilog preprocessing determines the effective source code consumed by subsequent front-end compilation stages, yet in many toolchains it is implemented as an internal component tightly coupled with lexical, syntactic, or downstream analysis. Such integration is effective for end-to-end compilation flows, but it can obscure preprocessing behavior and make independent validation difficult, especially for macro expansion, conditional compilation, file inclusion, and source-location tracking. This paper presents Stagira svpp, a standalone SystemVerilog preprocessor implemented in OCaml and designed to follow the preprocessing semantics of IEEE Std 1800–2023. Preprocessing is modeled as an independent, directive-driven frontend stage, in which macro definitions, conditional-compilation contexts, file-inclusion hierarchies, source-location mappings, diagnostics, and auxiliary directive states are maintained through explicit state updates. The implementation supports object-like and function-like macros, token-level macro operators, nested conditional compilation, macro-driven file inclusion with cycle detection, predefined macros, source-location remapping, command-line macro/include configuration, and selected stateful directives. The evaluation uses a focused semantic test suite to exercise implemented preprocessing mechanisms and representative boundary cases. Within the evaluated scope, Stagira svpp passes all 48 test cases and exhibits consistent behavior for tested scenarios including nested conditionals, token-level macro operations, macro-expanded include arguments, cyclic inclusion detection, and source location-related diagnostics. A representative comparison with Icarus Verilog and Quartus II further illustrates observable behavioral differences in selected include-related scenarios. The current evaluation focuses on semantic correctness and boundary behavior rather than large-scale performance benchmarking, which has been identified as a direction for future work. By decoupling preprocessing from later frontend phases and making preprocessing state explicit, Stagira svpp provides a reusable reference implementation for studying and validating SystemVerilog preprocessing behavior. Full article

Increasingly stringent regulations regarding climate policy and the sustainable development paradigm determine the transformation of contemporary multi-family housing typology, manifested by a growing share of single-aspect micro-apartments (units with exterior exposure on only one facade). This article identifies the phenomenon of the energy-efficiency paradox, wherein highly insulated buildings successfully trap winter heat but inadvertently escalate summer cooling demands. Consequently, the primary operational challenge becomes limiting excessive solar heat gains in summer, which directly translates into high cooling energy demand, rather than solely mitigating heat losses in winter. Sustainable construction requires moving beyond the narrowly defined reduction of envelope thermal transmittance towards holistic adaptation to climate change and ensuring adequate indoor environmental quality. The methodology is based on a coupled energy-economic analysis, evaluating thermal balances and their direct financial implications for end-users. The variant analysis of solar heat gains conducted for a reference 30 m² dwelling in Warsaw proves that architectural optimization should not be determined solely by short-term investment profit maximization. Effective engineering optimization in construction requires the implementation of a full building life cycle perspective. Unfavorable glazing orientation and the lack of cross-ventilation necessitate the use of energy-intensive air-conditioning systems, which directly increases the building’s carbon footprint and generates hidden operating costs (differences reaching over 145 PLN annually for heating and approximately 70 PLN for cooling). The findings highlight the necessity for a critical reevaluation of design priorities for compact apartments, integrating social justice (by reducing information asymmetry in the real estate market, where buyers are often unaware of these future cooling burdens) with long-term economic rationality and the resilience of the built environment to extreme weather events. Full article

Gait symmetry analysis has emerged as an important tool in rehabilitation engineering and neurological disorder assessment, as it provides clinically relevant indicators of mobility impairment and gait abnormalities. The proposed framework integrates gait symmetry variability, statistical gait features and Dynamic Time Warping (DTW)-based temporal alignment to enhance robustness against gait variations and irregular walking patterns. A hybrid feature vector comprising DTW similarity scores, the hybrid gait symmetry index (GSI), and statistical gait descriptors was employed to classify gait patterns into five categories: normal, slow, medium, fast, and abnormal. The system was implemented as a wearable edge-computing platform using an NI myRIO device equipped with a tri-axial Inertial Measurement Unit (IMU) mounted on the subject’s body. The onboard FPGA performs real-time signal preprocessing, GSI computation, feature extraction, constrained DTW matching, and gait classification using fixed-point streaming architectures and BRAM-based buffering. Meanwhile, the embedded ARM processor manages TCP/IP communication and transmits real-time gait information to a remote monitoring workstation via a WiFi interface for visualization and analysis. Operating at a clock frequency of 100 MHz, the complete architecture achieves an end-to-end processing latency of approximately 4 ms. The proposed FPGA-based implementation provides low-latency, energy-efficient, and real-time gait analysis, making it well suited for wearable rehabilitation systems, assistive healthcare devices, and continuous mobility monitoring applications. Full article

Hyaluronic acid (HA) is a glycosaminoglycan that is found within the body and has both structural and signaling functions in the extracellular matrix. HA is biocompatible and biodegradable; it has a high water content and binds directly to certain cell-surface proteins. Due to these characteristics, it is considered a promising component for the design of biomaterials for regenerative wound healing. This review covers the most recent findings on the use of HA-based biomaterials in soft tissue repair, while also incorporating earlier, foundational studies relevant to the field, focusing on HA’s characteristics, cellular interactions, design, and preclinical and clinical results. The physicochemical characteristics of HA and their influence on cellular responses and tissue regeneration are discussed to show how material properties can be adjusted for specific therapeutic purposes. There have been great advances in chemically modified composite scaffolds and HA matrices, which offer better mechanical stability and controlled degradation. At the same time, new delivery systems have been built using HA, from nanoparticles to gene delivery platforms and growth factors, and these have given the material an active role as a therapeutic agent rather than just a passive one. This narrative review covers the clinical evidence for the effectiveness of commercial products for acute and diabetic wounds, as well as burns and chronic wounds, and discusses where their use is indicated. In the end, the current limitations of the research and future applications and directions are discussed. Full article

Background: Korean-language medical question-answering datasets are increasingly used for large language model (LLM) development, but structural completeness alone does not establish model performance or clinical validity. We examined two national Korean medical knowledge datasets by combining a public labeling-file audit with a secondary evaluation of item-level outputs distributed with the corresponding official LLM packages. Methods: We reviewed the official documentation and complete public download inventories, parsed 34 training/validation labeling archives containing 31,036 records, and audited required fields, duplication, text length, question type, and specialty distribution. We also audited the official Qwen2.5-14B LoRA model packages and independently recalculated performance from their distributed item-level KorMedMCQA output files (2494 identical items per model). Accuracy was reported with Wilson 95% confidence intervals; model outputs were compared using an exact McNemar test and a paired bootstrap confidence interval. Because no compatible local GPU was available, model inference was not independently rerun. Results: The documentation described 34,487 labeled QA pairs, of which 31,036 (90.0%) were present in the publicly accessible training/validation labeling files; no public test-labeling archive was listed. Required fields were complete, no duplicated qa_id values were found, and one duplicated question-answer pair occurred in the Essential dataset. Multiple-choice items comprised 78.7% of all documented QA pairs, and the top three domains comprised 56.8%. In the distributed KorMedMCQA outputs, the Essential-care model answered 1603/2494 items correctly (64.27%; Wilson 95% CI 62.37–66.13%), while the Specialized-medicine model answered 1596/2494 correctly (63.99%; 95% CI 62.09–65.85%). The paired difference was 0.28 percentage points (bootstrap 95% CI −0.44 to 1.00), with no significant difference by exact McNemar test (46 vs. 39 discordant correct items; p = 0.515). Conclusions: The public training/validation labeling files showed favorable basic structural completeness, but the unavailable test labels, multiple-choice predominance, domain imbalance, limited record-level provenance, and incomplete model-package traceability constrain claims of clinical readiness. The distributed model outputs demonstrated moderate examination-style benchmark performance without a significant difference between the two models. These findings support use as research infrastructure, not evidence of clinical validity, and indicate the need for independent inference reproduction, clinician-led open-ended and safety evaluation, temporal updating, specialty-stratified reporting, and human oversight before clinical use. Full article

Diabetic nephropathy (DN) is a major microvascular complication of diabetes mellitus, and a leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD) worldwide. It is characterized by proteinuria, mesangial expansion, glomerulosclerosis and progressive loss of renal function. Current therapeutic strategies of DN, including renin–angiotensin–aldosterone system (RAAS) blockade, glucagon-like peptide-1 receptor agonists, non-steroidal mineralocorticoid receptor, and sodium-glucose cotransporter-2 (SGLT2) inhibitors, only slow the progression of the disease rather than reversing the pathology. Therefore, there is a growing interest in identifying alternative or complementary therapeutic agents, particularly those derived from natural products with multi-targeted activities. Psoralea corylifolia Linn (PCL) is a medicinal herb commonly used in traditional Asian medicine. It has known pharmacological properties on oxidative stress, inflammation, fibrosis and metabolic disorders. Accumulating recent studies indicated that PCL and its bioactive compounds, such as psoralen, bakuchiol, and corylin, mitigate pathological conditions in various diseases. Here, the current review will provide our current knowledge of major identified and characterized PCL focusing on their biological activity and function, particularly in DN. Full article