Search Results (277)

This research presents a comprehensive multi-domain environmental assessment of Delos Island, a UNESCO World Heritage Site, through integration of long-term atmospheric and satellite remote sensing datasets. A significant methodological contribution of this research is the development of a cross-mission harmonization approach that enables the reconstruction of a continuous, multi-decadal atmospheric record. By implementing a hierarchical calibration pipeline to harmonise Ozone Monitoring Instrument (OMI) and Tropospheric Monitoring Instrument (TROPOMI) observations, the study effectively eliminated a 6.61-fold systematic instrument offset, producing a 21-year time series (2004–2025) of tropospheric NO₂ concentrations. Simultaneously, a 24-year analysis (2000–2024) of coastline dynamics was conducted using the Landsat archive to quantify land area changes across the island and within a 1.03 km² Archaeological Area of Interest (AOI). Results indicate that atmospheric NO₂ concentrations stabilised following a 2015 peak, while coastal erosion represents a measurable risk to structural integrity. Net land loss of 18,400 m² was documented within the AOI, driven by localised geomorphological factors and exposure to Meltemi winds. The results indicate that these environmental processes are physically independent yet collectively require a multilayered conservation strategy to protect vulnerable archaeological heritage from atmospheric pollution and coastal retreat. Furthermore, the research highlights the value of long-term satellite datasets spanning more than two decades for supporting heritage monitoring and management, especially in remote or hard-to-reach locations. Through the analysis of the spatial and temporal characteristics of these sensors, the research enables the identification of hazard proxies that can inform risk-aware decision-making. Full article

Background: Patients with NSTEMI who are found with a totally occluded culprit vessel on coronary angiography are at higher risk of mortality and major adverse cardiac events. Artificial intelligence (AI) models can help identify this subgroup of NSTEMIs. Objectives: The purpose of this study was to examine the performance of an AI model in identifying patients with total thrombotic coronary artery occlusion myocardial infarctions (OMIs) using a single 12-lead ECG as input. Methods: In this retrospective cohort study, 12-lead ECGs corresponding to patients with suspected OMI were analyzed by an AI model. Confirmation of OMI was based on angiographic evidence of acute culprit coronary artery stenosis. Results: Over a one-year period, emergency physicians at our hospital identified 474 patients with suspected OMI, of whom 88 met STEMI criteria. Out of the 142 angiographically confirmed OMIs, the AI model correctly identified 115 (81%) with high confidence, corresponding to an accuracy of 89.4%, sensitivity of 90.0%, specificity of 93.2%, positive predictive value (PPV) of 84.6%, and negative predictive value (NPV) of 91.4%. Out of the 74 angiographically confirmed OMIs that did not meet STEMI criteria, the AI model correctly identified 49 (66%) with high confidence, corresponding to an accuracy of 87.9%, sensitivity of 66.2%, specificity of 93.4%, PPV of 72.1%, and NPV of 91.5%. Out of the 68 angiographically confirmed OMIs that met STEMI criteria, the AI model correctly identified 66 (97%) with high confidence, corresponding to an accuracy of 95.5%, sensitivity of 97.1%, specificity of 90.0%, PPV of 97.1%, and NPV of 90.0%. Conclusions: The AI model examined in this study outperformed the STEMI criteria for the identification of OMI with respect to accuracy, sensitivity, specificity, PPV, and NPV and accurately identified a significant portion of NSTEMIs found to have total thrombotic coronary artery occlusion. Full article

Current research is still striving to maximize the expansion of protein feed sources in order to reduce the production costs of the livestock industry. In this context, the current study aimed to evaluate the impacts of replacing soybean meal protein in diets with mulberry silage (at 50 and 100% substitution levels) on the growth, health status, and carcass characteristics of growing goat kids. Forty-five Xiangdong black goat kids weighing 18.2 ± 1.6 kg (approximately 6 months old) were divided into three experimental groups and fed one of the following diets: a control diet consisting of a 50:50 concentrate-to-roughage ratio on a dry matter basis (control), a diet replacing 50% of soybean meal protein with mulberry silage (MS-50), or a diet replacing 100% of soybean meal protein with mulberry silage (MS-100). The results show that replacing soybean meal protein with mulberry silage significantly increased (p < 0.05) the intakes of dry matter (DMI), crude protein (CPI), neutral detergent fiber (NDFI), and organic matter (OMI). However, no significant (p > 0.05) differences were observed in the digestibility of dry matter (DM), crude protein (CP), ether extract (EE), or neutral detergent fiber (NDF) among the groups, whereas the digestibility of OM and acid detergent fiber (ADF) was significantly reduced (p < 0.05) in the MS-100 group. Additionally, the MS-100 group exhibited significantly higher (p < 0.05) plasma total protein, albumin, and calcium levels. Total antioxidant capacity (TAC) was significantly enhanced in both the MS-50 and MS-100 groups compared to the control, although the MS-100 showed a significant increase (p < 0.05) in malondialdehyde (MDA) levels related to the other groups. In terms of growth performance, the MS-100 group improved (p < 0.05) final body weight, average daily gain, and carcass weights. Meanwhile, the MS-50 group recorded the highest contents (p < 0.05) of the following amino acids: aspartic acid, threonine, serine, glutamic acid, alanine, lysine, and proline. Overall, the results of the present study indicate that replacing soybean meal protein with mulberry silage generally produced comparable impacts, with additional positive effects on growth performance, meat quality, and health status of goats. Full article

To improve diagnostics and prediction of changes caused by increased impact of anthropogenic activity, it is necessary to increase the comparative analysis of measurements and modeling of ozone—one of the climatically important atmospheric gases due to the decisive influence of stratospheric ozone on the radiation balance of the Earth-atmosphere system and the role of tropospheric ozone, the third most significant anthropogenic factor contributing to the greenhouse effect. This task is particularly relevant for Russia, as its geographical location makes it more vulnerable to climate change than other countries, whereas its regional tendencies in ozone variability have not yet been studied in sufficient detail. An analysis of IKFS-2 tropospheric ozone content (TrOC) measurements for 2015–2022 revealed that in Siberian, Far Eastern, North Caucasian, and Southern federal districts of Russia TrOC maximum, caused by photochemical formation of ground-level ozone, is observed in July (up to 30–35 DU for monthly means in surface-400 hPa layer). In Northwestern federal district, TrOC maximum (up to 25–30 DU), determined by meridional transport, is observed in late spring. No statistically significant linear trends in TrOC are detected. The WRF-Chem model qualitatively describes the seasonal variations of TrOC as well as the anomalous increase in TrOC caused by forest fires. The variability of total ozone content (TOC) is analyzed by OMI (2005–2023) and IKFS-2 (2015–2022) measurements as well as by SOCOLv3 simulations. Ozone negative anomalies in spring (up to 15% for monthly means) are generally observed with positive Arctic oscillation index values and a westerly phase of Quasi-biennial oscillations. For the 2008–2022 period, a statistically significant increase in TOC (+1.6–1.7% per year) is obtained for European Russia and Western and Central Siberia in November. Full article

The rapid integration of artificial intelligence (AI) has heightened the need for evidence-based regulatory frameworks to effectively address its legal, ethical, and societal consequences. This research carefully analyzes the prevailing landscape of AI-related legislation in Mexico. The study conducts a comprehensive review of legislative initiatives related to AI regulation submitted to Mexican legislative bodies, encompassing those approved or pending in commissions. This process leads to the identification and categorization of outstanding initiatives across seven policy areas: Congress, Education, Health, Intellectual Property, Justice, AI Promotion, and AI Regulation. As a principal contribution, this work offers the first exhaustive mapping and thematic classification of legislative activity related to AI in Mexico. Furthermore, the analysis identifies systemic regulatory deficiencies, such as the lack of AI-specific legislation, the limited scope of existing data protection laws in relation to AI systems, and an absence of technical provisions concerning ethical design, algorithmic transparency, cybersecurity, and accountability frameworks. By showcasing these deficiencies, the study contributes a diagnostic framework for evaluating AI governance readiness in emerging economies. The findings emphasize the importance of establishing a comprehensive, technically sound, and internationally harmonized regulatory framework to reduce AI-related risks while promoting responsible innovation in Mexico. Full article

Active athletes represent a specific target for learning and development. Their schedules, including training sessions and competitions, leave little time for education. However, athletes still need skills beyond sports to ensure they are prepared for future employment. Our study approaches this issue by identifying appropriate settings for athletes’ learning and development. (1) Based on the background of current athletes’ education, it addresses the gap of not enough attention being paid to transferable practices from corporate attitudes to learning and development. (2) The study’s methodology primarily uses the case study concept because this conveys the video content we created for the athletes’ learning and development. This is combined with the method of content analysis of selected examples from corporate learning and development and the design thinking workshop, with the engagement of important stakeholder groups: athletes (2 participants), lecturers (2 participants), and representatives of sports organizations (1 participant). The other 9 workshop participants were master’s students in a managerial study programme because of their age similarities with the current athletes and the applicability of the courses they were studying to athletes’ education. (3) The designed process was created as a digital twin using haptic artefacts and the S2M technology (version 1.0) within the OMiLAB platform (version 1.6). Our results show that video content tailored to the athletes’ constraints is a viable solution that improves their career prospects. (4) The study’s practical implications are supported by the expert validation of the model provided by the inside of the large sports organizations’ management. Full article

The rapid evolution of SARS-CoV-2, particularly the emergence of Omicron subvariants, has significantly reduced the efficacy of existing vaccines and monoclonal antibodies. This study investigates the phenomenon of immune imprinting by comparing two phage display antibody libraries derived from early 2020 wild-type SARS-CoV-2 convalescents (WT-AbLib) and early 2023 Omicron convalescents (Omi-AbLib). The capacity and diversity of both antibody libraries were systematically evaluated. The libraries were screened using BF.7 and XBB.1.5 antigens. WT-AbLib showed markedly reduced diversity after Omicron antigen selection, with dominant clones shifting from IGHV3-66-class broadly neutralizing antibodies (bnAbs) targeting the receptor-binding motif to IGHV1-46-class broadly non-neutralizing antibodies targeting conserved lateral receptor-binding domain (RBD) sites. Omi-AbLib maintained higher diversity, but dominant antibodies were also non-neutralizing and targeted the same conserved lateral region. These findings suggest that immune imprinting drives the dominance of broadly non-neutralizing antibodies following Omicron breakthrough or reinfection. This phenomenon provides a mechanistic explanation for persistent viral evasion and recurrent infection, and highlights major challenges for the development of next-generation broadly neutralizing therapeutics. Full article

The COVID-19 pandemic led to an unprecedented slowdown in global economic and transportation activities, offering a unique opportunity to assess the relationship between human activity and atmospheric pollution. This study analyzes global variations in major air pollutants and meteorological conditions during the pandemic period using multi-satellite and reanalysis datasets. Nitrogen dioxide (NO₂) data were obtained from the OMI sensor aboard NASA’s Aura satellite, while carbon monoxide (CO) observations were taken from the MOPITT instrument on Terra. Reanalysis products from MERRA-2 were used to assess CO, sulfur dioxide (SO₂), black carbon (BC), organic carbon (OC), and key meteorological variables, including temperature, precipitation, evaporation, wind speed, and direction. Average concentrations of pollutants for April, May, and June 2020, representing the lockdown phase, were compared with the average values of the same months during 2017–2019, representing pre-pandemic conditions. The difference between these multi-year means was used to quantify spatial changes in pollutant levels. Results reveal widespread reductions in NO₂, CO, SO₂, and BC concentrations across major industrial and urban regions worldwide, consistent with decreased anthropogenic activity during lockdowns. Meteorological analysis indicates that the observed reductions were not primarily driven by short-term weather variability, confirming that the declines are largely attributable to reduced emissions. Unlike most previous studies, which examined local or regional air-quality changes, this work provides a consistent global-scale assessment using harmonized multi-sensor datasets and uniform temporal baselines. These findings highlight the strong influence of human activities on atmospheric composition and demonstrate how large-scale behavioral and economic shifts can rapidly alter air quality on a global scale. The results also provide valuable baseline information for understanding emission–climate interactions and for guiding post-pandemic strategies aimed at sustainable air-quality management. Full article

Background: The optimal timing of cytoreductive surgery for advanced high-grade serous carcinoma (HGSC) remains a critical unmet question in the modern era of platinum-based chemotherapy and PARP inhibitor (PARPi) maintenance. To address this gap, we compared outcomes following primary debulking surgery (PDS) versus interval debulking surgery (IDS) in a uniformly treated, contemporary cohort. Methods: Patients with FIGO stage IIIB–IVB HGSC treated between 2019 and 2023 were retrospectively analyzed. Baseline tumor burden was assessed using detailed radiologic and laparoscopic evaluations, including both presurgical and intraoperative assessments. Progression-free survival (PFS) and overall survival (OS) were examined using multivariable Cox proportional hazards models and reported as adjusted hazard ratios (aHRs). Subgroup analyses were rigorously conducted according to residual disease status and BRCA mutation status. Results: Among 221 patients (PDS, n = 60; IDS, n = 151), the median follow-up was 40 months. In the overall cohort, adjusted PFS and OS did not differ significantly between the PDS and IDS groups (PFS: aHR, 1.15; 95%CI, 0.67–1.98; OS: aHR, 1.24; 95%CI, 0.54–2.83). Outcomes were comparable among patients achieving R0 resection. Notably, BRCA-mutated patients demonstrated a substantial survival advantage with PDS (BRCA-mutated PFS: aHR, 3.34; 95%CI, 1.06–16.67; OS: aHR, 6.07; 95%CI, 2.13–∞), whereas BRCA wild-type patients showed no significant difference between surgical strategies. Conclusions: The findings suggest that BRCA-mutated patients may derive a survival benefit from PDS, whereas surgical timing had a limited impact on BRCA wild-type disease. This result underscores the importance of integrating molecular profiling, particularly BRCA mutation status, with surgical assessment to guide optimal and personalized treatment strategies in the PARPi era. Full article

Cardiovascular disease is the leading cause of morbidity and mortality worldwide, with ischemic and structural heart diseases being key contributors. While the 12-lead electrocardiogram (ECG) is a common low-cost diagnostic test, its interpretation is limited by human variability. Through machine learning with large diverse ECG data sets and artificial intelligence (AI) algorithms, ECG analysis can be automated for pattern recognition with higher accuracy. AI-augmented ECG algorithms have been demonstrated to be able to detect myocardial infarction with high accuracy and reduce door-to-balloon coronary intervention times. Similar models can be utilized to detect subtle ECG waveforms suggestive of current or future asymptomatic left ventricular dysfunction, aortic stenosis, and hypertrophic cardiomyopathy. Despite these promising results, there is concern for generalizability and bias or errors in training data. As AI systems evolve to multimodal integration, AI-augmented ECG has the potential to redefine cardiovascular diagnostics and enable earlier detection, risk stratification, and precision-guided interventions. Full article

Porphyromonas gingivalis plays a key role in periodontal disease and has been associated with several serious systemic diseases. Its fimbriae are a major virulence factor. We recently demonstrated the formation of bundles of long FimA fimbriae in strain ATCC 33277. Transmission (TEM) and scanning electron microscopy (SEM) were used to examine a collection of P. gingivalis strains representing all seven known FimA types (I, Ib, IIa, IIb, III–V) and a P. gulae strain (type A). Additionally, two P. gingivalis strains (ATCC 49417 and OMI 1127) were investigated in dual-species approaches together with Fusobacterium nucleatum or Streptococcus oralis as well as in co-culture with human gingival fibroblasts (HGFs). To evaluate the role of fimbriae accessory proteins FimCDE, proteomic analysis of outer membrane vesicles (OMVs) was performed. Bundling was confirmed to occur regardless of FimA type but was impaired by strong capsule formation. Furthermore, tubular and chain-like outer membrane extensions (OMEs) were identified in most strains examined, including P. gulae. For the first time, fimbriae-associated OMVs (FAVs) were observed. REM images suggest that bundled fimbriae, OMEs and FAVs form connections with F. nucleatum and S. oralis. Proteome analysis of OMV content revealed the ratios of FimA to accessory proteins to be approximately 13:1 for FimC and FimD and approximately 7:1 for FimE. The results imply more accessory proteins per fimbriae or shorter FimA fimbriae in OMVs than in cells. Since FimCDE are known to be responsible for the adhesion properties and autoaggregation of FimA fimbriae, we propose that they could also mediate the stability of bundled fimbriae and the binding of OMVs. Full article

Understanding the function of enzymes before their use as additives in ruminant diets is essential for achieving sustainable and efficient agricultural practices. Ruminants such as cattle, sheep, and goats are vital for global food production because of their ability to convert fibrous plant materials into high-quality proteins through enteric fermentation. Various datasets were carefully selected from four scientific databases: Science Direct, Scopus, PubMed, and Google Scholar. The rigorous Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol was employed to ensure the eligibility of the selected articles used in the analysis. A systematic review showed that the administration of various types of enzymes can increase dry (DMD) and organic (OMD) matter, neutral (NDFD), and acid (ADFD) detergent fibre, and crude protein (CPD) digestibility in both in vitro and in vivo tests in individual studies. However, the pooled meta-analysis indicated that their overall effect on CPD was not significant (p > 0.05). The OpenMEE approach was used to calculate the effect size (Hedges’ g) for each experimental unit for various parameters. Across enzyme types and doses in the meta-analysis, the administration of enzymes did not have any significant effect (p > 0.05) on DMI, OMI, and CPD, but it did have a significant effect (p < 0.05) on DMD, OMD, ADFD, NDFD, pH and gas production at 24, 48, and 72 h, as assessed by in vitro experiments. Ruminant in vivo studies indicated that the administration of enzymes has significant impacts (p < 0.05) on digestibility parameters (DMD, OMD, NDFD, ADFD), milk production, milk lactose content, acetate, and propionate, but it had non-significant impacts on milk protein and rumen total volatile fatty acids and acetate: propionate ratio. Full article

Carbapenem-resistant Gram-negative (CR-GN) pathogens pose a critical threat to patient outcomes in high-dependency and intensive care environments. This study aimed to delineate species prevalence, antimicrobial resistance phenotypes, carbapenemase genotypes, and clinical–environmental transmission dynamics across critical-care units. Cross-sectional surveillance was conducted in six ICUs and HDUs of a tertiary-care hospital in Karachi, Pakistan. We identified predominant species, quantified resistance patterns, and detected carbapenemase genes using PCR, exclusively on meropenem-resistant isolates. Network analysis highlighted high-centrality contamination hubs across ICUs and HDUs. Acinetobacter baumannii (36.7%) and Klebsiella pneumoniae (33.9%) were predominant, with 58% originating from environmental reservoirs. Meropenem non-susceptibility was 55% (60/109), and colistin non-susceptibility was 68.6% (35/51), based on standardized CLSI testing. ICU isolates exhibited significantly higher meropenem resistance than HDU isolates. Among carbapenem-resistant isolates, blaOXA-48-like (52.8%) and blaNDM (25%) were most prevalent. Network topology revealed ICU1 and HDU2 as high-centrality transmission nodes. These findings highlight pervasive environmental colonization and heightened antimicrobial pressure in ICUs, necessitating reinforced decontamination protocols, antimicrobial stewardship, and continuous molecular surveillance. This study provides the first integrated clinical–environmental surveillance of MDR Gram-negative bacteria in Pakistan, revealing that over half of isolates originated from surfaces and that network-based mapping can pinpoint contamination hubs driving hospital transmission. Full article

Asphalt binders that perform exceptionally well in resisting both rutting and cracking are highly desirable for withstanding the combined effects of extreme low temperatures and heavy vehicle loads. This work highlights the benefits of softening oils on the cracking performance of styrene–butadiene–styrene-modified asphalt (SBSMA). Additionally, the inherent correlations between cracking-performance parameters of binders and mixtures were thoroughly analyzed. A bio-based oil (bio-oil) and a petroleum-based oil (re-refined engine oil bottom, REOB) were selected as the softening oils. The benefit provided by softening oils was evaluated using various rheological indices, while the adverse effects of oxidative aging on cracking resistance were also considered. The cracking properties at intermediate temperatures were characterized by the modified Glover–Rowe (M G–R) parameter, δ_{8967 kPa}, and fatigue life (N_f). The low-temperature cracking properties of binders were evaluated by stiffness and m-value. The indirect tensile asphalt cracking (IDEAL-CT) test was conducted utilizing the CT-index and post-peak slope to estimate the fracture properties of the mixtures. The oxidative aging of binder and mixture samples was simulated and carried out based on lab aging methods; meanwhile, the carbonyl index obtained from the Fourier transform infrared (FTIR) scanning was used to track and evaluate the aging level of binders. The results show that the cracking performance could be greatly improved by the application of softening oils. Meanwhile, the bio-oils were found to operate with much higher efficiency than REOB, since the oil modification index (OMI) result showed that bio-oils exhibited four to six times the efficiency of REOB, in terms of improving the stress relaxation property. The correlations proved that the cracking-related parameters shared an inherent relationship with R² above 0.85, while these parameters consistently declined as the binder aged. The cracking performance of the mixtures at intermediate temperatures was mainly governed by the fatigue life of the binder, whereas thermal cracking performance was highly associated with the binder’s relaxation property. Full article

Although access to quality public spaces encourages physical activity (PA), their unequal distribution can exacerbate social inequalities. This study examined the relationship between the availability of spaces for PA and social marginalization in urban Basic Geostatistical Areas (Spanish acronym AGEB) in Mexico, using national databases on urban facilities and demographics. AGEB calculated space densities for PA, and the bivariate Moran’s I and LISA methodology were followed to identify global and local patterns. A weak negative spatial correlation was detected (I = −0.006) at the national level, with clusters of AGEBs with low marginalization and low density of spaces for PA. Contrasts were observed among the three most populous metropolitan areas: Mexico City and Guadalajara showed significant positive correlations, while Monterrey exhibited a different pattern. The urban furniture earmarked for PA is insufficient and its distribution reproduces socio-spatial inequalities. The dynamics differ across metropolises, underscoring the need for localized policies that will prioritize the provision of public spaces in marginalized communities. Full article