Browse Articles

Nitric Oxide Inhibition of Glycyl Radical Enzymes and Their Activases

Global burden and future trends of head and neck cancer: a deep learning-based analysis (1980–2030)

Background: Head and neck cancer (HNC) becomes a vital global health burden. Accurate assessment of the disease burden plays an essential role in setting health priorities and guiding decision-making. Methods: This study explores data from the Global Burden of Disease (GBD) 2021 study, involving totally 204 countries during the period from 1980 to 2021. The analysis focuses on age-standardized incidence, mortality, and disability-adjusted life years (DALYs) for HNC. A Transformer-based model, HNCP-T, is used for the prediction of future trends from 2022 to 2030, quantified based on the estimated annual percentage change (EAPC). Results: The global age-standardized incidence rate (ASIR) for HNC has escalated between 1980 and 2021, with men bearing a higher burden than women. In addition, the burden rises with age and exhibits regional disparities, with the greatest impact on low-to-middle sociodemographic index (SDI) regions. Additionally, the model predicts a continued rise in ASIR (EAPC = 0.22), while the age-standardized death rate (ASDR) is shown to decrease more sharply for women (EAPC = -0.92) than men (EAPC = –0.54). The most rapid increase in ASIR is projected for low-to-middle SDI countries, while ASDR and DALY rates are found to decrease in different degrees across regions. Conclusions: The current work offers a detailed analysis of the global burden of HNC based on the GBD 2021 dataset and demonstrates the accuracy of the HNCP-T model in predicting future trends. Significant regional and gender-based differences are found, with incidence rates rising, especially among women and in low-middle SDI regions. Furthermore, the results underscore the value of deep learning models in disease burden prediction, which can outperform traditional methods.

Insomnia and risk of all-cause dementia: A systematic review and meta-analysis

Background The evidence on the relationship between insomnia and risk of dementia, Alzheimer’s disease (AD), and Vascular dementia (VD) is not consistent. We conducted this meta-analysis to examine the evidence for the risk of developing dementia, AD, or VD in patients with all subtypes of insomnia. Methods A comprehensive search of PubMed, Embase, and the Cochrane Library was conducted using the following search strings: ‘Insomnia OR Sleep initiation and Maintenance disorders OR Early morning awakening’ AND ‘Dementia OR Alzheimer’s Disease OR Vascular Dementia’ AND ‘Risk’. Data extraction was done independently by two researchers. Pooled odds ratio (OR) accompanied by 95% confidence interval (CI) were calculated using either a random-effects model or a fixed-effects model. Sensitivity analyses were performed to assess the robustness of the findings. The potential for publication bias was evaluated through Egger’s test and Begg’s test. Results This meta-analysis included 16 studies with a combined sample size of over 9 million individuals. Pooled analyses revealed a significant association between insomnia and dementia risk (OR = 1.36; 95% CI: 1.01-1.84), with increased risks for AD (OR = 1.52; 95% CI: 1.19-1.93) and VD (OR = 2.10; 95% CI = 2.06-2.14). Subgroup analyses showed no evidence of associations between initial insomnia (OR = 1.01; 95% CI = 0.71-1.31), sleep-maintenance insomnia (OR = 0.88; 95% CI = 0.66-1.17), and early morning awakening (OR = 0.94; 95% CI = 0.83-1.07) with dementia risk. Insomnia patients from Europe (OR = 1.24; 95% CI = 1.14-1.35), Asia (OR = 2.19; 95% CI = 2.06-2.32), and the Americas (OR = 1.05; 95% CI =  1.04-1.07) had varying risks of dementia. Subgroups with less than five years of follow-up (OR = 2.16; 95% CI = 1.81-2.60) exhibited higher dementia risks in insomnia patients, while those with more than five years of follow-up (OR = 1.17; 95% CI = 1.03-1.33) showed a lower risk. Conclusion Our meta-analysis reveals that insomnia is linked to the risk of dementia, AD, and VD. These findings suggest that insomnia may significantly contribute to the risk of all-cause dementia, highlighting the importance of early intervention and management of insomnia. Despite our efforts to minimize and explore the sources of heterogeneity, it still remained, and therefore our results should be interpreted with caution.

Configuration Retention in <i>P</i>-Trifluoromethyl Phosphine Enabled Rh(I)-Catalyzed Decarbonylative Coupling of Carboxylates and Boroxines

Dicyphus cerastii: First data on development, survival, and reproduction

Dicyphus cerastii Wagner (Hemiptera: Miridae) is an important predator in horticultural crops. This study provides the first data on biological traits like development, survival, and reproduction for this species. We investigated how host (tomato, tobacco, and Cape gooseberry) and temperature (15.0, 20.0, 25.0 ±  1 °C) influenced nymphal development, survival, and adult longevity. In the absence of prey, nymphs failed to complete development on any host. When prey was available, nymphal development, survival and longevity declined as temperature increased across all hosts. Development and longevity of D. cerastii were further examined on tomato, at seven temperatures (15.0, 20.0, 25.0, 27.5, 30.0, 32.5, 35.0 ±  1°C). Reproductive capacity was measured at 20.0, 25.0, 30.0 ±  1°C, on tomato. Egg development ranged from 30.6 days (15.0 °C) to 9.7 days (32.5 °C). Nymph development decreased from 40.0 days (15.0 °C) to 16.4 days (30.0 °C), and no nymphs completed development above 30.0 °C. The optimal temperature for development from egg to adult was estimated at 29.2 °C., while the minimum threshold for immature development was approximately 7.0 °C. The thermal constant for development was 230.4 degree-days for eggs, and 394.0 degree-days for nymphs. Adult longevity ranged from 158.6 days (15.0 °C) to 13.8 days (30.0 °C). The net reproductive rate (R0) and generation time (T) were highest at 20.0 °C, while the intrinsic rate of increase (rm) was highest at 25.0 °C.

Single-Crystal X-ray Structures of Homochiral Brønsted Acidic Covalent Organic Frameworks

Retraction: TrustBlock: An adaptive trust evaluation of SDN network nodes based on double-layer blockchain

Prevalence and factors associated with road traffic crashes among truck drivers in Southeast Iran

Road traffic injuries are the second leading cause of death in Iran. The study investigated the prevalence and the influencing factors of Road traffic crashes (RTCs) among truck drivers in southeast Iran. In this cross-sectional study, 592 truck drivers were recruited using a multi-stage sampling method from November 2022 to February 2023. Data was collected through a researcher-administered questionnaire that included the crashes, individual characteristics, driving characteristics, work patterns, sleep and fatigue-related factors, workload, driving styles, and personality traits. Simple and multiple logistic regressions were used to assess the association between risk factors and crash involvement in the 3 last years. The surveyed drivers had a mean age of 37.4 ± 8.9 years, with an average driving history of 13.7 ±  7.6 years. Among the respondents, 28.4% reported involvement in crashes over the last 3 years, with 12.1% reporting one, 10% reporting two, and 6.3% experiencing three or more crashes. A significant portion of the crashes (42.5%) occurred between midnight and 6:00 a.m. In their lifetime, 24.2% of participants reported at least one sleep-related crash, 40.5% reported at least one fatigue-related crash, and 6.9% reported at least one crash resulting in a fatality. The odds of RTCs were higher among truck drivers who used drugs (OR = 2.03, 95% CI, 1.36-3.04), used mobile devices for texting (OR = 2.88, 95% CI, 1.56-5.30), neglected seat belt usage (OR = 1.81, 95% CI, 1.10-2.99), had accumulated traffic fines in the last year (OR =  8.18, 95% CI, 3.82–17.52, OR =  11.39, 95% CI, 5.42–23.92, OR =  17.78, 95% CI, 7.50–42.17, for 1-2, 3-6, and &gt; 6 traffic fines, respectively), consumed sleeping pills (OR = 2.52, 95% CI, 1.19-5.35), engaged sleep driving (OR = 11.30, 95% CI, 7.18-17.80), extended their driving hours without a break (OR =  3.02, 95% CI, 1.55–5.87, for consecutive driving hours before taking a break ≥ 8), experienced fatigue while driving (OR =  1.98, 95% CI, 1.24–3.17, for sometimes experienced fatigue while driving), faced high visual demands (OR = 1.23, 95% CI, 1.02-1.50), exhibited a careless driving style (OR = 0.95, 95% CI, 0.91- 0.99), and had higher levels of neuroticism (OR = 1.05, 95% CI, 1.01-1.10). The study sheds light on the significant prevalence of road traffic crashes among truck drivers. The findings underscore a constellation of factors amplifying crash risks within this occupational group. These outcomes emphasize the multifaceted nature of road safety issues within the trucking industry, indicating the need for targeted interventions and preventive measures to enhance driver safety and reduce the incidence of road traffic crashes among truck drivers.

Dissolved Oxygen Redox as the Source of Hydrogen Peroxide and Hydroxyl Radical in Sonicated Emulsive Water Microdroplets

Preparation of Fecal Microbiota Transplantation Products for Companion Animals

Fecal microbiota transplantation (FMT) is increasingly utilized in small animal medicine for the treatment of a variety of gastrointestinal and non-gastrointestinal disorders. Despite proven clinical efficacy, there is no detailed protocol available for the preparation and storage of FMT products for veterinarians in a variety of clinical settings. Herein, the effect of processing technique on the microbial community structure was assessed with amplicon sequence analysis. Microbial viability was assessed with standard culture techniques using selective media. Given the fastidious nature of many intestinal microbes, colony forming units are considered surrogate viable microbes, representing a portion of potentially viable microbes. FMT products from four screened canine fecal donors and six screened feline fecal donors were processed aerobically according to a double centrifugation protocol adapted from the human medical literature. Fresh feces from an additional three screened canine fecal donors were used to evaluate the effect of cryopreservative, centrifugation, and short-term storage on microbial community structure and in vitro surrogate bacterial viability. Finally, fresh feces from a third group of three screened canine and three screened feline fecal donors were used to evaluate the long-term in vitro surrogate bacterial viability of three frozen and lyophilized FMT products. Microbiota analysis revealed that each canine fecal donor has a unique microbial profile. Processing of canine and feline feces for FMT does not significantly alter the overall microbial community structure. The addition of cryopreservatives and lyopreservatives significantly improved long-term viability, up to 6 months, for frozen and lyophilized FMT products compared to unprocessed raw feces with no cryopreservative. These results prove the practicality of this approach for FMT preparation in veterinary medicine and provide a detailed protocol for researchers and companion animal practitioners. Future in vivo research is needed to evaluate how the preparation and microbial viability of FMT impacts the recipient’s microbial community and clinical outcomes across multiple disease phenotypes.

Protocol for the development of a core outcome set for respectful maternal and newborn care in a low-middle income setting

Introduction Disrespect and abuse have been seen as a real hindrance to achieving universal coverage for skilled delivery. Improving respectful maternal and newborn care and quality of care around the time of birth has been identified as a key strategy in low- and middle-income countries for reducing the rates of stillbirths and maternal and newborn mortality and morbidity rates. Currently, there is no core outcome set on respectful maternal and newborn care, resulting in reporting of various study outcomes from different studies which hinders the improvement of maternal and neonatal health. Objective To develop a core outcome set for respectful maternal and newborn care that can be used in research studies and clinical practice in low-middle income countries. Methods/design An exploratory sequential mixed methods evidence synthesis design will be adopted for the study. This design will enable the utilisation of the core outcome set development methodology in three stages. First, a systematic review and secondary analysis of qualitative interviews of women who utilise maternal care services will be undertaken in order to generate a list of outcomes. This will be followed by a two-round online Delphi study with multiple stakeholder groups which include women and their partners, women representative groups, parents, health workers and researchers. Each person will score the outcomes in terms of the defined criteria. Lastly, the results of the Delphi will be summarised and discussed at a virtual consensus meeting with representation from all stakeholder groups where the final core outcome set will be decided. Discussion The core outcome set will predominantly be developed for use in a low-middle income country setting to measure and improve the quality of respectful maternal and newborn services.

Polymorphic ROYalty: The 14th ROY Polymorph Discovered via High-Throughput Crystallization

Modeling the impacts of natural and human factors on the hatching success of the loggerhead sea turtle Caretta caretta along the coasts of Italy

Coastal biodiversity is globally threatened by climate change and human pressures, including habitat destruction, overfishing, eutrophication, and pollution, which alter natural coastal ecosystem processes. Caretta caretta, hereafter referred to as loggerhead sea turtle, is listed as “Vulnerable” at global level and “Least Concern” in the Mediterranean Sea by the International Union for Conservation of Nature (IUCN). This species is the only sea turtle nesting along Italian coasts, making it crucial to understand the factors affecting its reproductive success for effective conservation strategies. However, key aspects of the ecology and life cycle in Italian waters, such as spatial distribution, reproductive site selection, and factors influencing reproductive outcomes and migratory movements, remain unknown. This study aimed to identify factors influencing the reproductive success of the loggerhead sea turtle. Data from 237 nests between 2019 and 2023 across 14 Italian regions were recovered, quality-checked, and analyzed. A statistical model predicting reproductive success, represented by hatching success, was developed, incorporating various environmental variables from marine and terrestrial spheres, along with local pressures from urbanization and anthropization. These predictors were related to hatching success using a generalized linear model (GLM) accounting for zero-inflated data. The best models identified both environmental variables, such as temperature and extreme wave events, and human-controlled factors, including the presence of dunes and coastal urbanization, as key predictors of hatching success. Coastal anthropization and beachfront disturbances were particularly important. While human activities can pose notable challenges to the loggerhead sea turtle, their identification also offers opportunities for enhancing its reproductive success through targeted management actions focused on mitigating pressures. Our findings highlight the urgent need for targeted conservation efforts to address both local and global challenges to protect and enhance the reproductive success of the loggerhead sea turtle and possibly other coastal species. Effective management can and should focus on mitigating human-induced pressures. Policymakers and conservationists need to work together to implement strategies that consider both the immediate human impacts and the long-term effects of climate change, ensuring the sustainable management of coastal ecosystems and the protection of endangered species like the loggerhead sea turtle.

Identifying core leadership competencies to success non-communicable disease control and prevention programs: A mixed-methods study

Introduction Strengthening strong leadership skills is essential for program managers to successfully implement programs for the prevention and control of noncommunicable diseases (NCDs). This study identified leadership competencies for managers of individuals with noncommunicable diseases in Iran. Methods The study had three steps: a literature review, an expert panel, and a Delphi technique survey. First, the literature was reviewed to compile a list of leadership competencies in the field of primary health care (public health, NCDs). To refine and adapt the original list of leadership competencies, it was provided to the expert panel in two stages. The list of leadership competencies was sent via email to 30 experts over the course of two Delphi rounds. Descriptive statistics were used to analyze the outcomes. Results Fifteen leadership competencies, comprising multisectoral collaboration, political awareness, evidence-informed decision making, risk and disaster management, planning, innovation, leading and managing change, team building, communication, quality improvement, systematic thinking, management, ethics and professionalism, motivation and inspiration and personality, were identified. Conclusion The leadership competencies identified in this study can be a helpful tool in evaluating and identifying skills, knowledge, and attitudes with program managers for the prevention and control of NCDs and in designing training programs to strengthen leadership skills.

Effects of nitrate supplements on cardiopulmonary fitness at high altitude: A meta-analysis of nine randomized controlled trials

Background Nitrate is a dietary intervention commonly used to enhance exercise capacity, including cardiopulmonary fitness, yet its effectiveness has been recently questioned at high altitudes. This meta-analysis systematically evaluates the effects of dietary nitrate supplements on cardiopulmonary fitness at high altitude, as reflected in the biomarker of cardiopulmonary fitness, paving the way for informed dietary strategies. Methods We conducted a systematic assessment and meta-analysis of randomized controlled trials to examine the effects of dietary nitrate supplementation on biomarkers of cardiorespiratory health at high altitude. Studies were included if they involved healthy individuals (≥16 years of age) engaging in endurance activities such as hiking, long-distance running, mountain climbing, or bicycling at high altitude. Outcomes of interest included nitrite levels (NO2-), maximal oxygen uptake (VO2max), heart rate (HR), perceived exertion (RPE), and pulse oxygen saturation (SpO2). Exclusion criteria included duplicate publications, non-human studies, studies with missing data that could not be retrieved, non-randomized clinical trials, and non-original research articles such as conference papers, expert consensus, or reviews. Our search for articles was conducted across PubMed, Scopus, Web of Science, and Embase, without any language restrictions. A random effects model was employed for quantitative data analysis, utilizing Standardized Mean Difference (SMD) and 95% confidence intervals as summary statistics. The methods and results were reported according to the PRISMA2020 statement. Results A total of 9 studies with a sample size of 161 cases were included in the analysis. The meta-analysis indicated that dietary nitrate supplement significantly elevated NO2- concentration (95% CI: 1.38 to 3.12; SMD = 2.25, P &lt; 0.00001; I2 = 70%). However, there was no significant effect observed on VO2max (95% CI: -0.58 to 0.23; SMD = -0.17, P = 0.76; I2 = 0%), HR (95% CI: -0.31 to 0.23; SMD = -0.04, P = 0.77; I2 = 0%), RPE scores (95% CI: -0.49 to 0.18; SMD = -0.16, P = 0.36; I2 = 0%), and SpO2 percentage (95% CI: -0.36 to 0.20; SMD = -0.08, P = 0.58; I2 = 0%). Conclusions The current meta-analysis indicates that dietary nitrate intake is less correlated with cardiopulmonary fitness at high altitudes, and further research is required to clarify its impact on exercise capacity.

How does digital inclusive finance enhance rural economic resilience? — A study based on provincial panel data in China

This paper explores the role of digital inclusive finance in enhancing rural economic resilience, using panel data from 30 Chinese provinces, municipalities, and autonomous regions from 2013 to 2023. The results show that digital inclusive finance significantly improves rural economic adaptability and transformation capabilities, though its impact on risk resistance is minimal. It strengthens rural economic resilience through two main channels: improving transportation infrastructure and promoting rural technological innovation. This effect is particularly strong in areas with advanced rural digital infrastructure. Heterogeneity analysis reveals that digital inclusive finance positively impacts rural economic resilience in both eastern and western regions, but has no significant effect in central regions. Furthermore, its impact is more pronounced in non-agricultural provinces compared to agricultural ones. The study suggests that the government should continue expanding digital inclusive finance, while tailoring policies to local conditions, to support the sustainable development of the rural economy.

Ligand-Controlled Enantioselective Copper-Catalyzed Hydroboration and Ring-Opening Dihydroboration of Arylidenecyclobutanes

MAF-Net: A multimodal data fusion approach for human action recognition

3D skeleton-based human activity recognition has gained significant attention due to its robustness against variations in background, lighting, and viewpoints. However, challenges remain in effectively capturing spatiotemporal dynamics and integrating complementary information from multiple data modalities, such as RGB video and skeletal data. To address these challenges, we propose a multimodal fusion framework that leverages optical flow-based key frame extraction, data augmentation techniques, and an innovative fusion of skeletal and RGB streams using self-attention and skeletal attention modules. The model employs a late fusion strategy to combine skeletal and RGB features, allowing for more effective capture of spatial and temporal dependencies. Extensive experiments on benchmark datasets, including NTU RGB+D, SYSU, and UTD-MHAD, demonstrate that our method outperforms existing models. This work not only enhances action recognition accuracy but also provides a robust foundation for future multimodal integration and real-time applications in diverse fields such as surveillance and healthcare.

An Atomically Dispersed Mn Photocatalyst for Vicinal Dichlorination of Nonactivated Alkenes

Integrating DRN-RF with computer vision for detection of control room operator’s mental fatigue

Control room operators encounter a substantial risk of mental fatigue, which can reduce their human reliability by diminishing concentration and responsiveness, leading to unsafe operations. There is value in detection of individuals’ mental fatigue status in the workplace. This study introduces a new method for mental fatigue detection (MFD) that combines computer vision and machine learning. Traditional methods for MFD typically rely on multi-dimensional data for fatigue analysis and detection, which can be challenging to apply in a real situation. The traditional methods such as the use of biological data, e.g., electrocardiograms, require operators to be in constant contact with sensors, while this study utilizes computer vision to collect facial data, and a machine learning model to assess fatigue states. The developed machine learning method consists both Deep Residual Network and Random Forest (DRN-RF). A comparison with existing MFD methods, including K Nearest Neighbors and Gradient Boosting Machine, has been carried out. The results show that the accuracy of the DRN-RF model reaches 94.2% and the deviation is 0.004. Evidently, the DRN-RF model demonstrates high accuracy and stability. Overall, the proposed method has the potential to contribute to improving the safety of process system operations, particularly in the aspect of human factor management.