Search Results (17)

Background/Objectives: Hypertension represents a leading contributor to cardiovascular disorders and premature mortality. Given the pervasive nature of adverse effects associated with current angiotensin-converting enzyme inhibitors (ACEIs), there is a significant interest in identifying novel bioactive lead compounds from natural sources. This study identifies, for the first time, three novel angiotensin-converting enzyme (ACE) inhibitory peptides released from Bungarus multicinctus (BM) via simulated gastrointestinal digestion (SGD). Methods: Active fractions were enriched by ultrafiltration and subjected to stability assessment. The peptide sequences were then determined using Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and bioinformatics tools, followed by chemical synthesis. Finally, the inhibitory mechanism was investigated using kinetic analysis and molecular docking. Results: The intestinal digest exhibited potent ACE inhibition, with the <5 kDa fraction achieving 79% inhibition at 1 mg/mL and demonstrating favorable stability under varying temperatures, pH, and ionic strengths. Molecular docking revealed strong binding (affinity < −9.9 kcal/mol) of the peptides PPSPPRW, WGFTKF, and PSLFPPRL to key ACE residues—Tyr523, His513, and Arg522—via hydrogen and hydrophobic interactions. Enzyme kinetics characterized PPSPPRW and WGFTKF as competitive inhibitors, and PSLFPPRL as mixed type. The peptides demonstrated acceptable cell viability at lower concentrations, establishing a preliminary safety window for therapeutic application. Conclusions: These findings establish BM as a valuable source of stable, bioactive ACE-inhibitory peptides (ACEIPs) acting as promising lead compounds for antihypertensive therapies. Full article

The recolonization of the wolf (Canis lupus italicus) in Italy represents conservation success, but it has led to increased conflicts with livestock farming. These conflicts may undermine traditional pastoral practices, which are important for maintaining rural landscapes and associated biodiversity. In 2023, the European wolf population exceeded 20,300 individuals, with an estimated 65,000 livestock losses reported annually across the EU. This study assesses the effectiveness of an acoustic anti-wolf collar to complement existing protective measures, including fencing, human surveillance, and guarding dogs. A field trial was conducted from June to August 2024 in the municipality of Bova Marina in the metropolitan city of Reggio Calabria, Italy, using three groups of 50 Aspromonte goats. The groups were managed by: (1) a shepherd only (SO), (2) a shepherd with guarding dogs (SGD), and (3) a shepherd with guarding dogs and the anti-wolf collar (SGDC). The collar emitting modulated frequency intervals based on natural harmonic sounds, intended to deter wolves, was mounted on goats. Monitoring, by camera traps, enabled a comparative analysis of predation events. Camera data indicated persistent wolf activity at the site (54 images at CT1, 42 at CT2), but outcomes diverged by treatment. Two camera traps positioned at corridor bottlenecks identified from terrain morphology confirmed wolf presence and provided continuous coverage of the three groups on the single property. SO had 72 attacks and 5 kills; SGD had 26.39% fewer attacks and 1 kill; SGDC had no predation events despite confirmed presence. The preliminary findings suggest that the use of the anti-wolf collar may contribute to a reduction in predation and be a useful addition to strategies aimed at promoting coexistence between wolves and pastoral activities. Full article

With global climate change, urbanization, and agricultural resource limitations, precision agriculture and crop monitoring are crucial worldwide. Integrating multi-source remote sensing data with deep learning enables accurate crop mapping, but selecting optimal network architectures remains challenging. To improve remote sensing-based fruit planting classification and support orchard management and rural revitalization, this study explored feature selection and network optimization. We proposed an improved CF-EfficientNet model (incorporating FGMF and CGAR modules) for fruit planting classification. Multi-source remote sensing data (Sentinel-1, Sentinel-2, and SRTM) were used to extract spectral, vegetation, polarization, terrain, and texture features, thereby constructing a high-dimensional feature space. Feature selection identified 13 highly discriminative bands, forming an optimal dataset, namely the preferred bands (PBs). At the same time, two classification datasets—multi-spectral bands (MS) and preferred bands (PBs)—were constructed, and five typical deep learning models were introduced to compare performance: (1) EfficientNetB0, (2) AlexNet, (3) VGG16, (4) ResNet18, (5) RepVGG. The experimental results showed that the EfficientNetB0 model based on the preferred band performed best in terms of overall accuracy (87.1%) and Kappa coefficient (0.677). Furthermore, a Fine-Grained Multi-scale Fusion (FGMF) and a Condition-Guided Attention Refinement (CGAR) were incorporated into EfficientNetB0, and the traditional SGD optimizer was replaced with Adam to construct the CF-EfficientNet architecture. The results indicated that the improved CF-EfficientNet model achieved high performance in crop classification, with an overall accuracy of 92.6% and a Kappa coefficient of 0.830. These represent improvements of 5.5 percentage points and 0.153, compared with the baseline model, demonstrating superiority in both classification accuracy and stability. Full article

Rare-earth magnesium alloys exhibit higher comprehensive mechanical properties compared to other series of magnesium alloys, effectively expanding their applications in aerospace, weapons, and other fields. In this work, the tensile strength, yield strength, and elongation of a Mg-Gd-Y-Zn-Zr rare-earth magnesium alloy under different process conditions were determined, and a large number of microstructure observations and analyses were carried out for the tensile specimens; a prediction model of the corresponding mechanical properties was established by using a convolutional neural network (CNN), in which the metallographic diagram of the rare-earth magnesium alloy was taken as the input, and the corresponding tensile strength, yield strength, elongation, and three mechanical properties were taken as the output. The stochastic gradient descent (SGD) algorithm was used for parameter optimization and experimental validation, and the results showed that the average relative errors of the tensile strength and yield strength prediction results were 1.90% and 3.14%, respectively, which were smaller than the expected error of 5%. Full article

Oligometastatic patients at [¹⁸F]F-Fluorocholine (¹⁸F-choline) PET/CT may be treated with metastasis-directed therapy (MDT). The aim of this study was to combine radiomic parameters extracted from ¹⁸F-choline PET/CT and clinical data to build machine learning (ML) models able to predict MDT efficacy. Methods: Oligorecurrent patients (≤5 lesions) at ¹⁸F-choline PET/CT and treated with MDT were collected. A per-patient and per-lesion analysis was performed, using 2-year biochemical recurrence (BCR) after MDT as the standard of reference. Clinical parameters and radiomic features (RFts) extracted from ¹⁸F-choline PET/CT were used for training five ML Models for both CT and PET images. The performance metrics were calculated (i.e., Area Under the Curve—AUC; Classification Accuracy—CA). Results: A total of 46 metastases were selected and segmented in 29 patients. BCR after MDT occurred in 20 (69%) patients after 2 years of follow-up. In total, 73 and 33 robust RFTs were selected from CT and PET datasets, respectively. PET ML Models showed better performances than CT Models for discriminating BCR after MDT, with Stochastic Gradient Descent (SGD) being the best model (AUC = 0.95; CA = 0.90). Conclusion: ML Models built using clinical parameters and CT and PET RFts extracted via ¹⁸F-choline PET/CT can accurately predict BCR after MDT in oligorecurrent PCa patients. If validated externally, ML Models could improve the selection of oligorecurrent PCa patients for treatment with MDT. Full article

This study introduces an innovative strategy to mitigate global carbon emissions by integrating carbon dioxide (CO₂) absorption and sequestration through the carbonation of recycled concrete aggregate (RCA). This approach not only promotes the recycling of concrete waste but also alleviates the demand for new natural resources, addressing both environmental impact and geographical challenges associated with mining. The integrated process utilizes ammonia to capture flue gas emissions from natural gas combined cycle (NGCC) power plants, employing the captured solution to carbonate RCA for effective CO₂ sequestration and to enhance the quality of RCA. The study comprehensively assesses the process’s viability, considering capture performance, energy penalty, compliance with ammonia emissions standards, and capital costs. A techno-economic analysis (TEA) highlights the potential and economic feasibility of the proposed approach. Bench-scale experiments, conducted at low CO₂ concentrations (3~5%), focused on optimizing the carbonation process. The concentration of carbonated ammonia solution and its ratio to RCA were investigated to enhance the yield of carbonated RCA, resulting in an approximate 10% CO₂ capacity when using a 5% carbonated ammonia solution with a 0.25 ratio. The design of a large-scale plant, with an annual carbonated RCA production capacity of around 150 ktonnes, was formulated, and TEA calculations using Aspen Plus® V14 indicated a cost of approximately SGD 13 per tonne of carbonated product. These findings underscore the promising potential of the proposed process in efficiently reducing carbon emissions while providing economic viability at a larger scale. Full article

The programme aimed to improve selected cardiometabolic risk (CMR) variables using a nutritional intervention among farmers who reported hypertensive disorders as hindrances during agricultural activities. The intervention had two case controls (n = 103) [experimental group-EG (n = 53) and control group-CG (n = 50)] which were tracked and whose blood pressure measurements, dietary intake, blood indices for cholesterol concentration and glucose levels from pre- and post-intervention surveys after the baseline survey (n = 112) were analysed. The interval for data collection was 12 weeks (±120 days) after five legume varieties were consumed between 3 and 5 times a day, and servings were not <125 g per at least three times per week. Sixty-five per cent of farmers were above 60 years old, with mean age ranges of 63.3 (SD ± 6.3) years for women and 67.2 (SD ± 6.7) for men. The post-intervention survey revealed that EG blood results indicated nutrient improvement with p <= 0.05 for blood glucose (p = 0.003) and cholesterol (p = 0.001) as opposed to the CG. A trend analysis revealed that cholesterol (p = 0.033) and systolic blood pressure (SBP); (p = 0.013) were statistically significant when comparing genders for all study phases. Interventions focusing on legumes can improve hypertension and cardiovascular disease and fast-track the achievement of SGDs 3 and 12 through community-based programmes. Full article

Evolution of magnetic resonance imaging (MRI) findings in horses with sagittal groove disease (SGD) of the proximal phalanx is relatively sparsely described. This retrospective, descriptive, longitudinal study describes the findings of sequential low-field MRI fetlock examinations in horses with SGD of the proximal phalanx using a classification system. Twenty-nine horses were included, predominantly warmbloods used for show jumping (79%). For 29 limbs re-examined during the initial rehabilitation period, classification remained constant (n = 18), increased (n = 2), decreased (n = 7), and fluctuated (n = 2). Notably, two limbs with initial classification 4b (bone oedema-like signal with subchondral microfissure) and one with 4c (bone oedema-like signal with subchondral demineralisation) progressed to classification 5 (incomplete macrofissure/fracture), highlighting their potential as prodromal or imminent fissure pathology. Following conservative (n = 28) and surgical (n = 1) treatment, 86% of the horses re-entered full training and competition with a mean ± sd recovery time of 9.4 ± 4.4 months. In total, 20% of horses in the study subsequently presented for repeat MRI due to recurrent lameness after resuming full work, with classification that was the same (n = 2), increased (n = 2), or decreased (n = 2) compared with the last scan. This study underscores the variability in progression of SGD MRI findings, emphasising the need for further larger-scale research into patterns of progression. Full article

Based on the Quick Access Recorder (QAR) data covering over 9000 routes in China, the monthly and intra-day distribution characteristics of aircraft bumpiness at different levels were analyzed, and the relationships between the eddy dissipation rate (EDR) and other aircraft flight status elements during bumpiness occurrence were also analyzed. Afterward, aircraft bumpiness routes were constructed using 19 machine learning models. The analyses show that (1) aircraft bumpiness was mainly concentrated between 0:00 a.m. and 17:00 p.m. Severe aircraft bumpiness occurred more frequently in the early morning in January, especially between 5:00 a.m. and 6:00 a.m., and moderate bumpiness always occurred from 3:00 a.m. to 11:00 a.m. (2) The relationship between the left and right attack angles and aircraft bumpiness on the routes was more symmetrical, with a center at 0 degrees, unlike in the approach area where the hotspots were mainly concentrated in the range of −5 to 0 degrees. In the approach area, the larger the Mach number, the more severe the bumpiness. (3) The performances of the Automatic Relevance Determination Regression (ARD), Partial Least Squares Regression (PLS), Elastic-Net Regression (ENR), Classification and Regression Tree (CART), Passive Aggressive Regression (PAR), Random Forest (RF), Stochastic Gradient Descent Regression (SGD), and Tweedie Regression (TWD) based models were relatively good, while the performances of the Huber Regression (HUB), Least Angle Regression (LAR), Polynomial Regression (PLN), and Ridge Regressor (RR) based models were very poor. The aircraft bumpiness prediction models performed best over the approach area of ZBDT (airport in Datong), ZULS (airport in Lhasa), ZPPP (airport in Kunming), and ZLQY (airport in Qingyang). The model performed best in predicting the ZLLL-ZBDT air route (flight routes for Lanzhou to Datong) with different prediction times. Full article

In this study, we investigated HLA class I and class II allele and haplotype frequencies in Emiratis and compared them to those of Asian, Mediterranean, and Sub-Saharan African populations. Methods: Two-hundred unrelated Emirati parents of patients selected for bone marrow transplantation were genotyped for HLA class I (A, B, C) and class II (DRB1, DQB1) genes using reverse sequence specific oligonucleotide bead-based multiplexing. HLA haplotypes were assigned with certainty by segregation (pedigree) analysis, and haplotype frequencies were obtained by direct counting. HLA class I and class II frequencies in Emiratis were compared to data from other populations using standard genetic distances (SGD), Neighbor-Joining (NJ) phylogenetic dendrograms, and correspondence analysis. Results: The studied HLA loci were in Hardy–Weinberg Equilibrium. We identified 17 HLA-A, 28 HLA-B, 14 HLA-C, 13 HLA-DRB1, and 5 HLA-DQB1 alleles, of which HLA-A*02 (22.2%), -B*51 (19.5%), -C*07 (20.0%), -DRB1*03 (22.2%), and -DQB1*02 (32.8%) were the most frequent allele lineages. DRB1*03~DQB1*02 (21.2%), DRB1*16~DQB1*05 (17.3%), B*35~C*04 (11.7%), B*08~DRB1*03 (9.7%), A*02~B*51 (7.5%), and A*26~C*07~B*08~DRB1*03~DQB1*02 (4.2%) were the most frequent two- and five-locus HLA haplotypes. Correspondence analysis and dendrograms showed that Emiratis were clustered with the Arabian Peninsula populations (Saudis, Omanis and Kuwaitis), West Mediterranean populations (North Africans, Iberians) and Pakistanis, but were distant from East Mediterranean (Turks, Albanians, Greek), Levantine (Syrians, Palestinians, Lebanese), Iranian, Iraqi Kurdish, and Sub-Saharan populations. Conclusions: Emiratis were closely related to Arabian Peninsula populations, West Mediterranean populations and Pakistanis. However, the contribution of East Mediterranean, Levantine Arab, Iranian, and Sub-Saharan populations to the Emiratis’ gene pool appears to be minor. Full article

Introduction: The Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) criteria for alcohol use disorders (AUD) was a significant shift from the historical DSM-IV Text Revised version. Following this shift in diagnostic criteria, a difference in the prevalence of AUD was expected. The current study aimed to evaluate the consequences of the modification of the diagnostic criteria from DSM-IV to DSM-5 AUD using lifetime diagnosis in Singapore’s multi-ethnic population using data from a nationwide epidemiological study. Methods: Respondents were assessed for lifetime mental disorders using the Composite International Diagnostic Interview (CIDI) administered through face-to-face interviews. Lifetime DSM-IV AUD diagnoses were compared with DSM-5 AUD diagnoses generated by modifying the criteria and the addition of the craving criterion. Sociodemographic correlates of lifetime DSM-IV/DSM-5 AUD were examined using multiple logistic regression analysis. Associations between DSM-IV/DSM-5 AUD, chronic conditions, and the HRQOL summary scores were examined using logistic and linear regression after controlling for significant sociodemographic factors. Results: The lifetime prevalence of DSM-IV AUD was 4.6% (0.5% for dependence and 4.1% for abuse) in the adult population, while the lifetime prevalence of DSM-5 AUD was 2.2%. Younger age, male gender, and lower education were associated with higher odds of both DSM-IV and DSM-5 AUD. However, those who were economically inactive (versus employed) (AOR, 0.4; 95% CI 0.2–0.9) and had a higher monthly household income (SGD 4000–5999 versus below SGD 2000) had lower odds of DSM-IV AUD (AOR, 0.4; 95% CI 0.2–0.7), but this was not observed among those with DSM-5 AUD. Both DSM-IV and DSM-5 AUD were associated with significant comorbidities in terms of other mental disorders; however, those diagnosed with lifetime GAD had significantly higher odds of having DSM-5 AUD (AOR, 5; 95% CI 1.9–13.2) but not DSM-IV AUD. Conclusions: While using the DSM-5 criteria would result in a lower prevalence of AUD in Singapore, it remains a highly comorbid condition associated with a poor health-related quality of life that is largely untreated, which makes it a significant public health concern. Full article

Research has demonstrated that older adults with multiple chronic diseases (CD) are particularly vulnerable to depression. Meeting current recommendations for physical activity (PA) may help ameliorate the impact of depression on this population. Nonetheless, the impact of frequency versus duration of PA on depression in older adults remains to be explored. Therefore, the purpose of the present study was to determine the combined effect of PA and multiple CD on depression and the combined effect of the frequency, duration, and multiple CD on depression in older adults. Methods: The present study utilized data from the 2017 and 2020 Living Profiles of Older People Surveys. Data from a total of 19,907 older adults (10,042 older adults from 2017 and 9865 older adults from 2020) were included in the present study. Depression was assessed using the Korean version of the Short Form of Geriatric Depression Scale (K-SGDS) and CD included cardiovascular disease, respiratory diseases, thyroid syndromes, orthopedic complications, and diabetes. Participants who participated in PA ≥ 150 min/week were categorized as the high PA group, and those who participated in PA < 150 min/week were categorized as the low PA group. Furthermore, the frequency of PA (FRE) was divided into high FRE (≥5 times/week) and low FRE (<5 times/week), and duration (DUR) was divided into DUR30 (≥30 min/bout) and DUR0 (<30 min/bout). Results: The high PA group exhibited a lower risk of depression relative to the low PA group (p < 0.001). Furthermore, the risk of depression was consistently lower at DUR30 than DUR0 regardless of FRE in all CD categories and this result was maintained after adjusting for age, gender, BMI, height, weight, income, education levels, smoking status, and cognitive function. Conclusion: These results interestingly demonstrated that it is important for older adults to participate in a longer duration of PA to impact and prevent depression symptoms regardless of FRE. Full article

The United Nations Children’s Fund (UNICEF) and World Health Organisation (WHO) Joint Monitoring Programme (JMP) reports that only three African countries are on track to achieve universal access to at least basic water services by 2030 and only one country, Botswana, within the East and Southern Africa region (ESAR). Monitoring is crucial to advancing progress on SGD 6 in the region through providing reliable data to decision makers for policy, planning and much needed investment in the sector. This paper presents findings of the rapid assessment termed SDG 6 + 5 which relates to monitoring systems for Water Supply, Sanitation and Hygiene (WASH) in 21 countries of ESAR, five years into the SDGs. The paper presents the results of a fuzzy logic analysis applied to aspects and findings from the rapid assessment. Fuzzy logic benefits the study by managing unconscious bias from qualitative assessment and evaluating the strengths of countries’ WASH monitoring systems. The paper demonstrates similarities and variations between results from the rapid assessment and fuzzy analysis including Angola and Botswana scoring more favourably in enabling environments for monitoring from the analysis. The paper provides methods of rapid assessment of key aspects that impact on effective WASH monitoring and recommends the use of fuzzy logic to reduce data bias from qualitative methods. The methodology presented in the paper can be adapted and applied to other regions of the world and settings to enhance evaluations on the strength of systems within other sectors. Full article

In Sport for Development (SFD), sport is used as a cost-effective tool to facilitate the objectives of various organizations, not limited to increasing access to education, youth development, social cohesion, and gender equality. This review aims to systematically analyze SFD programs that contribute to gender equality and women empowerment under Sustainable Development Goal 5 (SDG 5). The PRISMA methodology was used to guide the screening and selection process. Fifteen studies were identified from the Web of Science, Scopus, and SPORTDiscus databases, the Journal of Sport for Development, forward–backward reference searches, and manual searches on four prominent sport, gender, and development researchers. The findings indicated that there was evidence of micro-level outcomes in every study and three achieved meso-level impact; however, none of these studies’ suggested changes have reached the macro-level of impact when the outcomes were reported in these articles. There was a lack of intervention studies that investigated the mechanisms and reported outcomes through a validated monitoring and evaluation process. This review provides significant insights into: (a) identifying future SFD research areas, (b) refining SFD program evaluations, (c) developing indicators of outcomes for sport programs contributing to SDG 5, and (d) reproducing sustainable development outcomes under SDG 5. Full article

The United Nations plans have marked global sustainable development for more than two decades. Most of the developed and developing countries have adopted these plans to achieve the Agenda 2030, currently formed by the 17 Sustainable Development Goals (SDGs). The analysis of the interactions between the SDGs is a growing area in research and of interest for governments. However, studies on how positive correlations can improve deteriorated goals are scarce for countries to date. This study aims at filling this gap by finding and quantifying the synergies and trade-offs among the SDGs of Spain. During the years 2000–2019, almost 80% of the SDG targets had significant interactions, either positive (synergy) or negative (trade-off). SDG 4 (quality education), SDG 5 (gender Equality) and SDG 7 (affordable and clean energy) contained the largest number of positive interactions, more than 60% in all of them. SDG 3 (good health and wellbeing) was strongly linked with indicators from SDG 4 (quality education) and also SDG 6 (clean water and sanitation). Furthermore, indicators from SDG 7 (affordable and clean energy) shared a high correlation with the ones from SGD 12 (responsible consumption and production) and SDG 15 (life on land). SDG 1 (no poverty), 2 (zero hunger), 6 (clean water and sanitation), 8 (decent work and economic growth) and 11 (sustainable cities and communities) had the slowest evolution during the years 2000–2019, showing contractions in some instances. We developed a regression model to assess the influence that selected targets have had on a less evolved target (target 8.6—proportion of youth not in education, employment or training). We managed to clarify high influence from target 1.3 (unemployment compensations), target 8.4 (domestic material consumption) and target 10.5 (non-performing loans) on the dependent variable. Identifying numerical dependencies between the SDGs may help nations to develop a roadmap where targets work as cogwheel towards achieving the Agenda 2030. Full article