Search Results (25,906)

Background/Objectives: Pelvic organ prolapse (POP) is a common condition that significantly impacts quality of life. Research has focused largely on older women, while experiences of younger women remain relatively underexplored despite challenges unique to this population. Informed by the biopsychosocial model of illness, this study aims to assess the symptom burden, treatment goals, and information needs of younger women complaining of prolapse by analyzing questionnaire responses from an existing electronic Personal Assessment Questionnaire—Pelvic Floor (ePAQ-PF) dataset. Methods: Mixed-methods content analysis was conducted using free-text data from an anonymized multi-site ePAQ-PF dataset of 5717 responses collected across eight UK NHS trusts (2018–2022). A quantitative, deductive approach was first used to identify younger women (≤50 years old) with self-reported prolapse. ePAQ-PF scores for younger women with prolapse were compared with those aged >50 years, using Mann–Whitney tests. Free-text response data were analyzed inductively to qualitatively explore younger women’s symptom burden, treatment goals, and information needs. Results: Of the 1473 women with prolapse identified, 399 were aged ≤50 years. ePAQ-PF scores of the younger cohort demonstrated significantly greater symptom severity and bother than those aged >50, particularly in bowel, prolapse, vaginal, body image, and sexual health domains (p < adjusted threshold). Qualitative analysis undertaken to understand women’s concerns and priorities produced five health-related themes (physical health; functionality; psychosocial and emotional wellbeing; reproductive and sexual health; and healthcare journeys) and a sixth intersecting theme representing information needs. Conclusions: The findings highlight the substantial symptom burden of younger women with prolapse, as well as treatment goals and information needs specific to this population. The development of age-specific resources is identified as a requirement to support this group. Full article

The aim of this study was to determine, through meta-analysis, the effects of malic acid/malate addition on ruminal and blood parameters and diet digestibility in cattle. The literature search was conducted in Web of Science, Science Direct, and Google Scholar using the terms “organic acids”, “malic acid”, “malate”, and “bovine”. The database was composed of papers published between 1980 and 2023. The average effect of malate/malic acid inclusion was calculated using the “DerSimonian and Laird” random effects model. Meta-regression and subgroup analyses were conducted to explore sources of heterogeneity. Overall, malic acid (MAC) addition did not significantly affect rumen pH (ES = 0.310, p = 0.17), but subgroup analysis showed that malate increased pH (ES = 1.420, p < 0.01). MAC increased rumen propionate (ES = 0.560, p < 0.01) and total volatile fatty acids (VFAs; ES = 0.508, p = 0.03), while reducing the acetate-to-propionate ratio (p < 0.01). Starch and NDF intake were significant covariates affecting pH and VFA-related variables. MAC improved total-tract digestibility of dry matter (DM; ES = 0.547, p ≤ 0.05), crude protein (CP; ES = 0.422, p ≤ 0.05), and acid detergent fiber (ADF; ES = 0.635, p ≤ 0.05). It increased glucose levels (Overall ES = 0.170, p = 0.05) and reduced NEFA (Overall ES = −0.404, p = 0.03). In conclusion, the effectiveness of MAC depends on its chemical form. Improvements in rumen pH, fiber degradation, and blood parameters suggest more efficient energy use and potential metabolic benefits. The influence of diet-related covariates suggests that the response to MAC may vary depending on the nutritional composition of the diet. Full article

Autonomous vehicles (AVs) hold the potential to revolutionize transportation by improving safety, operational efficiency, and environmental impact. However, ensuring reliability and safety in real-world conditions remains a major challenge. Based on an in-depth examination of 33 peer-reviewed studies (2015–2025), this systematic review organizes advancements across five key domains: fault detection and diagnosis (FDD), collision avoidance and decision making, system reliability and resilience, validation and verification (V&V), and safety evaluation. It integrates both hardware- and software-level perspectives, with a focus on emerging techniques such as Bayesian behavior prediction, uncertainty-aware control, and set-based fault detection to enhance operational robustness. Despite these advances, this review identifies persistent challenges, including limited cross-layer fault modeling, lack of formal verification for learning-based components, and the scarcity of scenario-driven validation datasets. To address these gaps, this paper proposes future directions such as verifiable machine learning, unified fault propagation models, digital twin-based reliability frameworks, and cyber-physical threat modeling. This review offers a comprehensive reference for developing certifiable, context-aware, and fail-operational autonomous driving systems, contributing to the broader goal of ensuring safe and trustworthy AV deployment. Full article

Background/Objectives: Truncating mutations in PALB2, a critical component of the BRCA1-PALB2-BRCA2 homologous recombination repair complex, are associated with increased risk and aggressiveness of breast cancer. The consequences of PALB2 truncation on the expression, localization, and functional dynamics of the scaffold protein IQGAP1 were investigated in this study based on two cases of truncated PALB2 human breast invasive ductal carcinoma (IDC), specifically, c.1240C>T (p.Arg414*) and c.2257C>T (p.Arg753*). Methods: Using confocal microscopy, we examined co-expression patterns of IQGAP1 with PALB2, PCNA, CK7, and β-tubulin in tumor tissues from both control cancer and PALB2-mutated cases. Results: In PALB2-truncated tumors, IQGAP1 exhibited enhanced peripheral and plasma membrane localization with elevated co-localization levels compared to controls, suggesting altered cytoskeletal organization. PALB2 truncation increased nuclear and cytoplasmic N-terminal PALB2 immunoreactivity, indicating the presence of truncated isoforms disrupting the homologous recombination repair system. Co-expression analyses with PCNA revealed an inverse expression pattern between IQGAP1 and proliferation markers, suggesting S-phase cell cycle-dependent heterogeneity. Furthermore, the loss of IQGAP1 dominance over CK7 and β-tubulin in mutant tumors, along with persistent intercellular spacing, implied a loss of cell–cell cohesion and the acquisition of invasive traits. Conclusions: These data support a model where PALB2 truncation triggers a reorganization of IQGAP1 that disrupts its canonical structural functions and facilitates tumor progression via enhanced motility and impaired cell–cell interaction. IQGAP1 thus serves as both a functional effector and potential biomarker in PALB2-mutated IDC, opening novel paths for diagnosis and targeted therapeutic intervention. Full article

As a result of the catalytic decomposition of H₂O₂, hydroxyl radicals are produced. Hydroxyl radicals are strong oxidants and effectively inactivate bacteria, ensuring water disinfection without toxic chlorinated organic by-products. The kinetics of bacterial inactivation were studied in a laboratory-scale flow catalytic reactor. A granular cobalt ferrite catalyst was thoroughly characterized using XRD and XRF techniques, SEM with EDS, and Raman spectroscopy. At lower H₂O₂ concentrations, H₂O₂ decomposition follows first-order reaction kinetics. At higher H₂O₂ concentrations, the obtained kinetics lines suggest that the reaction order increases. The kinetics of bacterial inactivation in the developed flow reactor depends largely on the initial number of bacteria. The initial bacterial concentrations in laboratory tests were within the range typical of real river water. A regression model was developed that relates the degree of bacterial inactivation to the initial number of bacteria, the initial H₂O₂ concentration, and the contact time of water with the catalyst. Full article

In today’s rapidly evolving organizations, talent management plays a critical role in driving sustainable growth. Talents, particularly those exhibiting leadership potential, are often seen as essential assets for organizational development. However, the presence of high employee’s leadership potential can also generate adverse emotional reactions from leaders, potentially leading to behaviors such as leader jealousy and leader ostracism. This study investigates the dark side of employee’s leadership potential by examining the mechanisms through which employee’s leadership potential influences leader ostracism, with leader jealousy acting as a mediator. Drawing on social comparison theory, we propose a theoretical model that includes organizational competitive climate and leader’s core self-evaluation as moderating factors. Using a three-wave survey of 672 leaders in the Chinese construction industry, hierarchical regression analysis was employed to test the hypotheses. The results show that employee’s leadership potential significantly increases both leader jealousy and leader ostracism, with leader jealousy serving as a mediator. Moreover, a high organizational competitive climate strengthens the relationship between employee’s leadership potential and leader jealousy, thereby enhancing the entire mediated effect. In contrast, high leader core self-evaluation weakens the relationship between employee’s leadership potential and leader jealousy, reducing the likelihood of leader ostracism and attenuating the mediated effect. This study provides both theoretical contributions and practical insights for organizations seeking to manage high-leadership potential employees while minimizing the risk of negative leadership behaviors. Full article

Healthcare supply chain management operates amid fluctuating patient demand, rapidly advancing biotechnologies, and unpredictable supply disruptions pose high risks and create an imperative for sustainable resource optimization. This study investigates the underlying mechanisms through which digital intelligence drives strategic decision optimization in healthcare supply chains. Drawing on the Resource-Based View and Dynamic Capabilities Theory, we develop a chain-mediated model, defined as the multistage indirect path whereby digital intelligence first bolsters innovation capability, which then activates supply chain resilience (absorptive, response, and restorative capability), to improve decision optimization. Data were collected from 360 managerial-level respondents working in healthcare supply chain organizations in China, and the proposed model was tested using structural equation modeling. The results indicate that digital intelligence enhances innovation capability, which in turn activates all three dimensions of resilience, producing a synergistic effect that promotes sustained decision optimization. However, the direct effect of digital intelligence on decision optimization was not statistically significant, suggesting that its impact is primarily mediated through organizational capabilities, particularly supply chain resilience. Practically, the findings suggest that in the process of deploying digital intelligence systems and platforms, healthcare organizations should embed technological advantages into organizational processes, emergency response mechanisms, and collaborative operations, so that digitalization moves beyond the technical system level and is truly internalized as organizational innovation capability and resilience, thereby leading to sustained improvement in decision-making performance. Full article

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

Background: Accuracy of optical impressions—defined by the intraoral scanner (IOS)’s trueness and precision per International Organization for Standardization (ISO) standards—is influenced by both operator- and patient-related factors. Thus, this in vitro study aimed to (1) evaluate how scanning distance affects the accuracy of three different intraoral scanners (IOSs), and (2) identify the optimal scanning distance for each scanner. Methods: A maxillary arch model was obtained using polyvinyl siloxane impression material and poured with Type IV stone (Octa-rock royal^®, Kulzer, Germany). Using three different types of IOSs—the trios 3 shape (TRIOS ^® cart, 3Shape, Copenhagen, Denmark); the Helios 500 (Eighteeth ^®, Changzhou, China); and the Heron (3Disc ^®, Herndon, VA 20170, USA)—ten scans were performed with each of the IOSs with five predetermined distances: 0 mm, 2.5 mm, 5 mm, 7.5 mm, and 10 mm. Spacers of varying heights were designed using Meshmixer version 3.5 (Autodesk, Inc., Mill Valley, CA, USA) and three-dimensional printed with the Form 2 printer (Formlabs, Somerville, MA, USA). The scanned data was processed using Geomagic Control X (Version 16.0.2.16496, 3D Systems, Wilsonville, OR, USA). Statistical analyses were performed using R Statistical Software (version 4.2.2), with significance set at α = 0.05. Results: Scanning distance significantly influenced scan accuracy for all three scanners. The 3Disc scanner (3Disc, Herndon, VA, USA) demonstrated the highest accuracy at a 7.5 mm distance, while both the Helios 500 (Eighteeth, Changzhou, China) and Trios 3 (3Shape, Copenhagen, Denmark) scanners achieved their best accuracy at a 5 mm distance, as indicated by the lowest root mean square (RMS) values (p < 0.05). Conclusions: To conclude, each IOS has an optimal scanning distance for best accuracy. Trios 3 (3Shape, Copenhagen, Denmark) outperformed the others in both trueness and precision. Future studies should examine these effects under full-arch and clinical conditions. Full article

Metformin is one of the most commonly used medications to treat type 2 diabetes. In addition to lowering blood sugar, it can also promote the regeneration of certain organs or tissues. Planarian Dugesia japonica, with its remarkable regenerative capacity, has become an important model organism for studying pharmacology and regenerative medicine. Planarian eyespot regeneration involves precise tissue regeneration via mechanisms like cell proliferation, differentiation, and gene regulation following body damage. Experiments on planarian eyespot regeneration have confirmed that 1 mM metformin significantly promotes regeneration. Through analysis of the regenerating planarian miRNA database and the metformin-treated transcriptome database, combined with target gene prediction by TargetScan, the DjmiR-27b/DjPax6 axis was finally determined as the research focus. qPCR showed that metformin significantly affects the expression levels of DjmiR-27b and DjPax6. DjPax6 was identified as the target gene of DjmiR-27b through dual luciferase reporter gene analysis. Functional experiments revealed that metformin regulates the expression of DjPax6 via DjmiR-27b, thereby influencing the regeneration of planarian eyespots. In situ hybridization showed that both DjmiR-27b and DjPax6 are expressed throughout the entire body. This study reveals the molecular mechanism of metformin regulating planarian regeneration through miRNA, providing further insights into its role in the field of regeneration. Full article

Respiratory viral diseases infecting poultry lead to variable lesions in the respiratory organs, including nasal sinuses, trachea, lungs, and air sacs. Additional involvement of eyelids/conjunctiva was reported. The distribution and the intensity of lesions depend on multiple factors, including virulence, the host’s immunity, and secondary or concurrent infections. It may be challenging to detect remarkable lesions during experimental infections conducted in a controlled environment because some viruses fail to produce the intense lesions seen in field cases. This creates a challenge in developing a reliable model to study pathogenicity or vaccine efficacy experimentally. The development of the proposed histologic respiratory index (HRI) aims to help monitor the least microscopic changes that can be scored, thereby creating an objective and accurate grading of lesions in experimentally infected birds. HRI scores the changes in eyelids/conjunctiva and respiratory mucosa, including hyperplasia, metaplasia, inflammatory cellular infiltration in the submucosa, including lymphocytes and heterophils, and vascular changes (vasculitis) in nasal sinuses, trachea, and lungs. The score was validated in birds infected experimentally with avian metapneumovirus (aMPV) and low pathogenic avian influenza (LPAI-H4N6). The HRI reliably graded higher scores in the respiratory organs of experimentally infected birds compared with non-infected control ones. The HRI is the first of its type with poultry viral respiratory pathogens and it was initially proven to be a reliable in pathogenicity and vaccine trials of certain poultry respiratory viral diseases. Full article

Aerogel sponges of bio-based polymers loaded with metal–organic frameworks (MOFs) are highly promising for environmental applications, but a central challenge is to improve their stability and efficiency for removal processes. Here, the effective incorporation of the MOFs MIL-100(Fe) and ZIF-8 in composite aerogels of chitosan–pectin–lactic acid is reported. The presence of pectin was critical to loading the MOFs efficiently and homogeneously, while the incorporation of lactic acid induced a large increase in the Young’s modulus and provided structural preservation in aqueous solutions. The presence of MOFs enhanced the removal of two dyes, methyl orange (MO) and methylene blue (MB), under batch and flow conditions, with removal efficiencies of methyl orange of about 85% and 90% when loaded with ZIF-8 and MIL-100(Fe), respectively. Bentonite, celite 545, and two ionenes were loaded for comparison. Factors beyond charge-to-charge electrostatic interactions influenced the removal, since no correlations were obtained between the electrical charges of dyes, fillers, and polymers. The kinetic data were analyzed by adapting the Langmuir kinetic model, incorporating absorption and desorption processes, which allowed the recovery of the respective rate constants. Full article

In this study, we systematically investigated the adsorption behavior of a titanium-based metal–organic framework (MOF) sensing layer on five primary alcohol homologs using the quartz crystal microbalance (QCM) technique. Unexpectedly, response signals were significantly enhanced for molecules exceeding the framework’s pore dimensions, contradicting conventional molecular sieving models. Further investigations revealed that the adsorption time constant (${\tau }_a$) is linearly proportional to the molecular diameter ($R^2=0.952$) and the integral response (AUC) increases almost exponentially with the molecular weight ($R^2=0.891$). Although the effective diffusion coefficient ($D_{\mathrm{eff}}$) decreases with increasing molecular size ($D_{\mathrm{eff}}\propto d^{-5.96}$, $R^2=0.981$), the normalized diffusion hindrance ratio ($D_{\mathrm{eff}}/D_{\mathrm{gas}}$) decreases logarithmically with an increasing diameter. Larger responses result from stronger host–guest interactions with the framework despite significant diffusion limitations for larger molecules. These findings demonstrate the synergistic regulation of adsorption and diffusion in MOF-QCM systems. Our investigation experimentally elucidates the ’size-selectivity paradox’ in microporous sensing interfaces and establishes a quantitative framework for optimizing sensor performance through balanced control of diffusion kinetics and interfacial interactions in similar materials. Full article

As industrial companies transition from the Industry 4.0 stage to the more human-centric and resilient Industry 5.0 paradigm, there is a growing need for structured assessment tools to prioritize modern technologies. This paper presents an integrated multi-criteria decision analysis (MCDA) approach to support the strategic assessment of technologies from three complementary perspectives: economic, organizational, and technological. The proposed model encompasses six key transformation areas and 22 technologies representing both the Industry 4.0 and 5.0 paradigms. A hybrid approach combining the DEMATEL (Decision-Making Trial and Evaluation Laboratory) and PROMETHEE II (Preference Ranking Organization Method for Enrichment Evaluation) methods is used to identify cause–effect relationships between the transformation areas and to construct technology rankings in each of the assessed perspectives. The results indicate that technologies such as the Internet of Things (IoT), cybersecurity, and supporting IT systems play a central role in the transition process. Among the Industry 5.0 technologies, hyper-personalized manufacturing, smart grids and new materials stand out. Moreover, the economic perspective emerges as the dominant assessment dimension for most technologies. The proposed analytical framework offers both theoretical input and practical decision-making support for companies planning their transformation towards Industry 5.0, enabling a stronger alignment between implemented technologies and long-term strategic goals. Full article

Objective: To evaluate the prognostic utility of the Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score 3 (SAPS 3) in COVID-19 patients and assess whether incorporating C-reactive protein (CRP), procalcitonin, lactate, and lactate dehydrogenase (LDH) enhances their predictive accuracy. Methods: Single-center, observational, cohort study. We analyzed a database of adult ICU patients with severe or critical COVID-19 treated at a large academic center. We used binary logistic regression for all analyses. We assessed the predictive performance of SAPS 3 and SOFA scores within 24 h of admission, individually and in combination with serum lactate, LDH, CRP, and procalcitonin. We examined the independent association of these biomarkers with hospital mortality. We evaluated discrimination using the C-statistic and determined clinical utility with decision curve analysis. Results: We included 1395 patients, 66% of whom required mechanical ventilation, and 59.7% needed vasopressor support. Patients who died (39.7%) were significantly older (61.1 ± 15.9 years vs. 50.1 ± 14.5 years, p < 0.001) and had more comorbidities than survivors. Among the biomarkers, only procalcitonin was independently associated with higher mortality in the multivariable analysis, in a non-linear pattern. The AUROC for predicting hospital mortality was 0.771 (95% CI: 0.746–0.797) for SAPS 3 and 0.781 (95% CI: 0.756–0.805) for the SOFA score. A model incorporating the SOFA score, age, and procalcitonin demonstrated high AUROC of 0.837 (95% CI: 0.816–0.859). These associations with the SOFA score showed greater clinical utility. Conclusions: The SOFA score may aid clinical decision-making, and incorporating procalcitonin and age could further enhance its prognostic utility. Full article