Search Results (28,086)

Background/Objectives: The emergence of methicillin-resistant Staphylococcus aureus (MRSA) highlights the need for new antibacterial agents. Here, we report the identification and evaluation of a novel Gram-positive selective antibacterial: NDM-552. Methods: Antibacterial activity was determined by broth microdilution against a panel of Gram-positive and Gram-negative pathogens. Mechanistic studies included BOCILLIN-FL competition assays, microscale thermophoresis (MST), and antibiotic interaction with oxacillin and moenomycin. Additionally, time–kill analyses, frequency-of-resistance measurements, cytotoxicity assays, plasma stability studies, and a murine wound infection model were performed to characterize NDM-552. Results: NDM-552 exhibits activity against Gram-positive pathogens including S. aureus, Enterococcus faecium, and Staphylococcus epidermidis, with minimum inhibitory concentrations (MICs) of 1–2 µg/mL. NDM-552 displays no activity against Gram-negative bacteria. NDM-552 displays bacteriostatic activity against MRSA and additive interactions with oxacillin and moenomycin. The frequency of resistance in MRSA is low (2.39 × 10⁻⁹). BOCILLIN-FL competition assays and MST binding analysis identify the essential penicillin-binding protein 2 (PBP2) as the potential target of NDM-552. NDM-552 demonstrates acceptable cytotoxicity, favorable plasma stability, and reduces bacterial burden in a murine wound infection model. Conclusions: NDM-552 is a potent Gram-positive selective antibacterial agent that potentially targets PBP2-associated cell wall biosynthesis and exhibits in vivo efficacy against MRSA. Findings establish NDM-552 as a promising scaffold for the development of new antibacterial agents. Full article

Background and Objectives: COVID-19 restrictions altered population mobility and healthcare use. Most reports describe changes in facial-trauma counts; fewer characterise how injury composition changed or separate policy-associated changes from the secular trend. We examined the volume and structure of maxillofacial trauma around the March 2020 restrictions and the January 2022 easing of restrictions. Materials and Methods: A retrospective study of 3954 patients treated for confirmed facial fractures between 2018 and 2023 at three Slovak tertiary centres. The primary outcome was the monthly count of treated cases (case volume, not incidence, as no catchment denominator was available), modelled by segmented negative binomial regression with level and slope terms at two a priori interruptions and harmonic seasonality. Centre–month panel, centre-specific, and leave-one-centre-out models addressed between-centre heterogeneity. Structural outcomes were modelled by segmented binomial regression at the patient level, adjusting for centre, mechanism, sex, and age. Results: The restrictions were followed by a non-significant reduction in monthly case volume (count ratio 0.84, 95% confidence interval CI 0.67–1.04), and the easing was followed by an increase in the pooled series (1.50, 95% CI 1.22–1.86). This increase was strongly heterogeneous between centres (p < 0.001), was confined to one centre (1.86, 95% CI 1.42–2.43), and was compatible with no change once that centre was excluded (1.15, 95% CI 0.88–1.50). The non-mandibular fracture share fell at the onset of restrictions (odds ratio 0.54, 95% CI 0.38–0.77) and returned thereafter; the post-easing estimate was inconclusive. Electric-scooter injuries rose on a secular trend, with no level shift at either interruption. Conservative management increased at the easing and persisted after adjustment for case mix and centre (aOR 1.44, 95% CI 1.22–1.70). Conclusions: These periods were associated with changes in maxillofacial trauma composition, most consistently a shift toward conservative management. The post-easing volume rise was centre-specific, not a national rebound. Full article

Background: Antimicrobial resistance complicates the selection of appropriate regimens for urinary tract infections (UTIs), even when susceptibility data are available, particularly where infectious disease (ID) expertise is scarce. Machine learning clinical decision support systems (CDSS) may support prescribing, but evidence from Latin America is limited. The goal of this study was to evaluate the concordance between antimicrobial regimens selected by physicians and those recommended by a machine-learning-with-human-in-the-loop (ML-HITL) CDSS (OneChoice^®), and to assess CDSS appropriateness against an independent, blinded expert reference standard. Methods: In this cross-sectional, survey-based concordance study conducted in Lima, Peru, 194 verified physicians contributed 224 eligible evaluations across 42 real UTI case codes with complete culture and antimicrobial susceptibility data. Of the 224 evaluations, 70 were contributed by infectious disease specialists and 154 by non-ID physicians. Participants selected OneChoice^® and alternative antimicrobial regimens. Responses were compared with CDSS recommendations under three concordance definitions. Discordances were adjudicated by an external panel blinded to the source of the recommendation. Non-independence was addressed using cluster-robust methods. Results: First-choice, alternative, and general concordance were 50.9%, 40.6%, and 62.5%, respectively. ID specialists showed higher concordance than non-ID physicians (65.7% vs. 44.2%; 51.4% vs. 35.7%; 72.9% vs. 57.8%; all p ≤ 0.034). ID specialty was independently associated with concordance (adjusted OR 2.19–2.68; p ≤ 0.016). Among discordant evaluations, the external panel judged the CDSS recommendation to be preferable in 90.5–93.2% of cases. Physician–CDSS concordance was moderate and higher among ID specialists. The external adjudication findings indicate that the CDSS recommendations were frequently aligned with expert assessment when physician and CDSS recommendations differed; however, the study did not evaluate comparative clinical effectiveness or patient outcomes. Conclusions: Physician–CDSS concordance was moderate and higher among ID specialists, yet discordances overwhelmingly favored the CDSS on independent adjudication. These findings suggest the CDSS aligns with expert reasoning and may support antimicrobial selection in high-resistance settings. Full article

Background: Candidozyma auris (C. auris) is an emerging multidrug-resistant yeast associated with healthcare-related transmission, difficult laboratory identification, antifungal resistance, and high mortality in critically ill patients. This study aimed to describe the clinical and microbiological characteristics of early institutional C. auris cases detected in a tertiary hospital in Istanbul, Türkiye. Methods: Adult patients hospitalized between January 2021 and December 2022 with C. auris isolation were retrospectively reviewed. Demographic data, underlying conditions, intensive care unit (ICU) exposure, invasive procedures, antimicrobial and antifungal use, culture sources, antifungal susceptibility testing (AFST) results, and clinical outcomes were evaluated. C. auris isolates were identified using VITEK MS v.3.2, and AFST was performed using C. auris isolates were identified using VITEK MS v.3.2, and AFST was performed using Sensititre YeastOne YO10 (Thermo Fisher Scientific, Waltham, MA, USA) panels. Results were interpreted according to CDC interim breakpoints. Multiple isolates from an individual patient were retained when they represented different specimen types or sampling events. Results: Thirty-three adult patients and 62 clinical isolates were included. The mean age was 67.8 years, and 20 patients (60.6%) were aged 65 years or older. Most patients had prior ICU admission (93.9%), urinary catheterization (97.0%), central venous catheterization (90.9%), mechanical ventilation (81.8%), and broad-spectrum antimicrobial exposure. Blood cultures represented the most frequent source of isolation (56.5%), followed by urine cultures (27.4%). Resistance rates were 98.4% for amphotericin B, 88.7% for fluconazole, 6.6% for micafungin, and 6.5% for caspofungin. Overall mortality was 72.7%. While mortality was numerically higher among patients aged 65 years or older and those requiring inotropic support, only the need for mechanical ventilation was statistically significantly associated with mortality. The cohort-level APACHE II-based expected mortality was 48.0%, whereas observed mortality was 72.7%; this comparison was descriptive and no formal calibration analysis was performed. Conclusions: Early institutional C. auris cases in this tertiary hospital occurred predominantly among elderly, critically ill patients with prolonged healthcare exposure, invasive devices, and extensive antimicrobial use. The findings support the need for early laboratory recognition, cautious interpretation of commercial AFST results, particularly given the propensity of Sensititre YeastOne to overestimate amphotericin B resistance, strengthened infection control practices, and multicenter studies incorporating molecular typing to clarify transmission dynamics and antifungal resistance patterns. Full article

This study proposes the Expanding-Window Tensor TOPSIS method, a novel dynamic multi-criteria decision analysis framework that integrates temporal feature extraction with an expanding-window estimation scheme. The method structures panel data as a third-order tensor and extracts three time-series features—linear trend, mean, and standard deviation—from rolling windows for each alternative-criterion pair. These features are retained as distinct dimensions of the decision matrix. At each target year, normalization bounds, entropy weights, and ideal solutions are calculated based on the information accumulated up to that year, thereby avoiding look-ahead bias. A burn-in threshold prevents unreliable early estimates, while complementary diagnostics assess the convergence of weights and sensitivity to the window width. The method yields a dynamic score matrix representing the evolution of the relative position of each alternative over time. The proposed framework is applied to the ND-GAIN Country Index, which includes data for 152 countries from 2000 to 2024. The dynamic rankings have high face validity, almost perfect robustness to the choice of window width and burn-in threshold, fast convergence of the entropy weights, and robustness to changes in the alternative set. Extensive robustness checks—including Monte Carlo weight-uncertainty analysis, comparisons with alternative weighting (CRITIC, standard-deviation-based, equal weighting) and aggregation (VIKOR) methods, and benchmarks against Dynamic TOPSIS-Entropy and a rolling-window variant—confirm the insensitivity of the findings to the choice of weighting and aggregation strategy. The methodology is not domain-specific and offers a transparent and diagnostically rich tool for dynamic performance evaluation. Full article

This study examines the impact of energy security risk on the economic growth rate of the world’s 74 largest energy-consuming countries. The Energy Security Risk Index is employed to assess national vulnerability to fluctuations in energy security risk over a specified period. To investigate the empirical relationship between energy security risk and economic growth, the analysis utilizes a balanced panel dataset spanning from 1980 to 2025 and applies a series of econometric techniques, including cross-section dependence tests, unit root tests, Pedroni’s residual cointegration test, pooled mean group estimation, and a heterogeneous panel causality test. The empirical findings confirm the presence of a statistically significant causal relationship running from energy security risk to economic growth (LESR → GDPG) at the aggregate panel level. In advanced economies, energy security risk is found to constrain economic growth. Conversely, in developed economies, the results indicate that energy security risk exerts a positive and statistically significant effect on economic growth, which may be attributable to energy-related investments that drive structural transformation. These findings carry important implications for the global community, given that energy continues to serve as the lifeblood of modern production systems. Full article

Aptamer-based multiplexed proteomic platforms, especially the SOMAmer-based SomaScan assay, are widely used for large-scale discovery of circulating biomarkers relevant to human aging. This review summarizes 42 original research articles published from 2020 through 2026 in which aptamers or aptamer-derived biosensors were used to characterize aging-related biomarkers in human samples or clinically relevant human-disease contexts. The eligible literature falls into several thematic areas: whole-plasma and organ-specific proteomic aging clocks; inflammaging and senescence-associated secretory phenotype (SASP) markers; cardiovascular, metabolic, renal, hepatic, musculoskeletal and neurodegenerative biomarker panels; and aptasensor platforms for detection of individual analytes. Only a small number of studies have compared aptamer- and antibody-based platforms in the same specimens; we tabulate these and show that median between-platform agreement is low to moderate, which constrains the pooling of findings across technologies. We also make explicit an interpretive point that is usually left implicit: because proteomic clocks are trained against chronological age, their correlation with chronological age measures fit to the training target rather than biological validity, and the informative quantity is the residual age gap. In the reviewed literature, SomaScan-based studies are concentrated in cardiovascular, neurodegenerative, frailty, and proteomic aging-clock research, whereas de novo SELEX campaigns targeting aging-specific epitopes and longitudinal human validation of wearable aptasensors were not identified. The main barriers to translation are cross-platform discordance, limited replication across ancestries, under-reported pre-analytical variability, cost, and the research-use-only status of most assays. Full article

Evidence linking annual wildfire burden to administrative wildlife monitoring counts remains limited, particularly in fire-prone Mediterranean settings. This study examined whether wildfire activity was associated with province-level administrative target-species monitoring counts in Türkiye, focusing on delayed rather than contemporaneous relationships. A retrospective ecological panel design (2005–2024) harmonized official wildfire and wildlife inventory data across 22 Turkish provinces (440 observations). Two-way fixed effects panel models estimated same-year, lagged, and supplementary robustness associations between wildfire exposure (fire count, burned area, and damage per fire) and administrative target-species counts. Same-year models showed no clear associations. Burned area showed its clearest negative association at a two-year lag, while paired models indicated negative one- and two-year associations for burned area and damage per fire. Province-specific trend models preserved the main negative directions, and false-discovery-rate adjustment retained the lag-1 burned-area and damage-per-fire terms in the paired model families. The lag-2 burned-area association remained visible after excluding 2021 and after winsorizing extreme burned-area values. Restricted target-frame sensitivity analyses supported a narrower interpretation of the administrative outcome; deer/roe-deer frames showed negative cumulative burned-area associations, whereas wild-goat frames yielded less precise estimates. Burned area and damage per fire were interpreted as spatial fire-footprint indicators rather than direct burn-severity measures. The highest composite risk scores were observed in Antalya, Muğla, and İzmir. Distinguishing wildfire frequency from areal fire burden remains central for interpreting delayed administrative monitoring patterns. Full article

This research assesses the practical synthesis of Building Information Modeling (BIM), Autodesk Forma and Dalux to support LEED-oriented sustainable design for a higher education building. Autodesk Revit 2025 functioned as the central BIM platform, while Autodesk Forma enabled early-stage simulations of solar exposure, daylight potential, wind conditions, microclimate, noise and solar-energy potential. Dalux supported model coordination and information management in accordance with ISO 19650 principles. The workflow links simulation outputs to BIM elements through project-defined parameters, allowing performance evidence to inform design refinement. Quantitative indicators were consolidated for daylight exposure, wind comfort, outdoor thermal stress, acoustic exposure and photovoltaic potential. The solar-energy analysis considered an area of approximately 970 m², an annual potential of 1030 kWh/m² and a theoretical yield of approximately 999,100 kWh/year. Assuming 70% roof coverage and 18% panel efficiency, the estimated photovoltaic the expected output is approximately 125,113 kWh/year. These findings demonstrate the value of combining BIM, cloud-based analysis and CDE-based coordination for early-stage sustainable design, while LEED certification, operational energy modelling and lifecycle assessment require additional specialist validation. The proposed workflow provides a consistent approach for aligning design development with sustainability objectives and can be applied to similar building types. Full article

Economic growth and the effectiveness of official development assistance (ODA) have long been a topic of debate, with the current concern being that there are high levels of aid dependency in Sub-Saharan Africa, despite low levels of structural transformation. The study analyses the growth impacts of multidimensional ODA dependency, the moderating effect of institutional quality and the possible thresholds of aid dependency in an unbalanced panel of 48 Sub-Saharan African countries over the period 2000–2025. Two-way fixed effects, System Generalized Method of Moments, Difference Generalized Method of Moments, and Common Correlated Effects Pooled are used to analyze a principal component-based ODA Dependency Index, and least-squares threshold regression is used to investigate multiple thresholds. These results show that there is a strong negative correlation between aid dependency and economic growth, while institutional quality is consistently positive to growth, but does not significantly moderate the aid–growth relationship. There are no stable thresholds for aid dependency as a function of the specification of the index. The findings highlight the need to improve domestic resource mobilization, productive investment and institutional capacity to decrease reliance on structural aid and ensure sustainable economic growth in the long term. Full article

This study examines whether and when environmental, social, and governance (ESG) performance alleviates financial constraints, focusing on firm life cycle heterogeneity. Using a panel of Korean listed firms from 2011 to 2021, we employ industry-and-year fixed-effects regression to identify the empirical relationship of ESG on financial constraints proxied by the KZ index or Z-score. We classify firm life cycle stages using both retained-earnings- and cash-flow-based measures to capture distinct dimensions of firm development. We document that ESG performance significantly relaxes financial constraints, with governance being the most influential sub-dimension in our sample. Importantly, this effect is highly state-dependent: ESG is largely ineffective in the introduction stage but becomes economically and statistically significant from the growth stage onward, with the strongest impact observed in early-growth and declining firms. Our findings challenge the notion of uniformly priced ESG benefits and demonstrate that ESG operates as a contingent financial mechanism whose effectiveness critically depends on firm life cycle stages. Full article

Clinical practice guidelines require expert synthesis that large language models (LLMs) might partly automate, yet their ability to reproduce clinically actionable recommendations is poorly quantified. We evaluate an LLM (Claude Sonnet 4.6) against the 103 recommendations of the Spanish enhanced-recovery guideline Vía RICA 2026, grouped in 17 bundles. The model used the panel’s own closed corpus (617 documents) in a multilingual retrievalaugmented generation pipeline. Concordance was assessed twice: by optimal 1:1 bipartite matching (Hungarian) on cosine similarity, and by an LLM-as-a-judge clinical adjudicator (Claude Haiku 4.5) validated against a three-clinician panel (Fleiss’ κ = 0.538). The two schemes bracket a micro F₁ of 0.61–0.69 and reveal four findings: (i) a systematic granularity bias, producing 1–8 recommendations per bundle regardless of ground-truth size; (ii) failure of cosine similarity to discriminate within narrow clinical domains; (iii) high reference-concordance precision (0.70–0.81) despite low exhaustiveness; and (iv) no transfer of the GRADE fields, evidence level agreeing no better than chance and strength systematically downgraded. An eight-fold larger retrieval budget left it intact. A corpus audit found 25 documents that formulate recommendations; excluding them lowers judged micro F₁ to 0.602. The results delimit the current utility of generative AI for guideline development. Full article

Emotional eating (EE) is associated with poor dietary quality and weight gain among university students. Therefore, exploring innovative, non-invasive interventions to support healthier food-related responses is essential. While multisensory environments show promise in influencing food-related responses, their effectiveness in managing stress-induced EE remains understudied. Grounded in the Environment–Organism–Health (EOH) model, this study used an immersive virtual reality (VR) platform and recruited 49 Chinese university students. After emotional induction tasks, participants were randomly assigned to VR campus environments with varying wall colors and environmental sounds. The study combined physiological indicators and subjective questionnaires to evaluate the effects of color–sound combinations on emotional responses, physiological recovery, food preferences, and food cravings. Food preference was assessed via an image-selection task, and food healthiness was rated by an expert panel (n = 7). A mixed-design analysis of variance (ANOVA) revealed a significant interaction between wall color and sound. Natural sounds were associated with reduced negative emotions and higher healthy food preference scores under several color conditions, while both color and sound influenced food craving. Independent t-tests revealed significant differences according to gender and emotional eating tendency on multiple outcomes. This study suggests that multisensory environments may offer a novel approach to influencing stress-related emotional responses, food preferences, and food cravings. Full article

This research presents a straightforward and detailed method for calculating the cost of recycling solar panels and the associated economic benefits. The contribution of this research is to estimate the impact of the recycling process on the cost of energy and the payback period. The Full Recovery End-of-Life Photovoltaic (FRELP) method was utilized to assess the PV recycling process. Calculations were made for every 1000 kg of solar panels and converted to calculate the cost and revenue per square meter of panels. Calculations showed that the cost of recycling in Saudi Arabia reached 9.46 $/m² based on the geographical environment, fuel prices, and the various materials used in recycling processes, while the revenue was approximately 24.6 $/m² according to the current prices of materials resulting from the recycling process, especially the price of silver. The study results were applied to a 400 MW solar power plant to determine the feasibility of recycling the energy price and the payback period. The solar power plant was designed using variable-sized solar panels with capacities of 255, 330, and 580 watts. The recycling revenue for the plant with the smaller panels was the highest, being $2.6 M as an annual rate. Full article

Inter-provincial administrative boundary areas are particularly vulnerable to ineffective regional pollution governance because they are simultaneously affected by transboundary pollution diffusion and administrative fragmentation. Existing governance practices, however, continue to rely heavily on territorially based regulation and administrative coordination, while the potential of cross-regional green-technology collaboration to address boundary pollution has received insufficient attention. Using panel data for Chinese prefecture-level cities from 2011 to 2023, this study systematically examines the impact of green innovation collaboration (GIC) on pollution control in areas along interprovincial administrative boundaries through two-way fixed-effects, instrumental-variable, Heckman two-step, and spatial Durbin models. The results show that, first, GIC significantly reduces pollution in these areas, and this finding remains robust across a range of robustness checks. GIC also generates significant spatial spillovers: while reducing local boundary pollution, it improves air quality in neighboring cities. Second, the heterogeneity analysis indicates that this effect is more pronounced in cities facing greater pollution-control pressure, lower fiscal pressure, and higher levels of openness. The regional results also reveal certain differences. Third, the mechanism analysis shows that cross-regional collaborative governance and industrial upgrading constitute two relatively independent parallel transmission pathways rather than a sequential chain, and their relative contributions vary with city conditions. These findings provide empirical evidence for improving interprovincial collaborative governance, facilitating the cross-regional diffusion of green technologies, and implementing differentiated environmental policies. Full article