Climate change is an intensifying force reshaping the global sporting landscape. From elite international competitions to community-level recreation, rising temperatures, extreme weather events and shifting environmental conditions are profoundly affecting how sport is played, organised and sustained. Thus, this paper is an attempt to explore the multidimensional implications of climate change for athletes, competition frameworks and sports infrastructure, highlighting the urgent need for proactive adaptation and mitigation strategies within the sports sector. For athletes, the most direct consequences stem from increased heat exposure and deteriorating air quality. Prolonged training and competition in high temperatures elevate risks of heatstroke, dehydration and cardiovascular strain, while poor air quality impairs respiratory function and recovery. Outdoor sports such as athletics, football, tennis and cycling face heightened physiological demands, altering performance outcomes and increasing health-related withdrawals. Moreover, psychological stressors, including uncertainty about event cancellations and concerns over long-term health, add another layer of burden. Winter sports are particularly vulnerable, with declining snow cover and glacier retreat threatening venues for skiing, snowboarding and bobsleigh. Major events such as the Winter Olympics have already faced logistical challenges to secure adequate snow, prompting a rethinking of host selection and timing. Simultaneously, the carbon footprint of sports infrastructure, particularly energy-intensive arenas and sprawling event campuses, contributes to the very problem it must adapt to. As climate impacts intensify, the world of sport stands at a crossroads: continue business-as-usual while facing escalating disruptions or embrace its role as a catalyst for resilience and sustainability. In short, the choices made today will determine whether sport remains a viable, equitable and inspiring pursuit for future generations.

Temporomandibular Disorders (TMDs) are a group of conditions affecting the temporomandibular joint and related structures, frequently encountered in dental and medical practice. With the increasing use of large language models (LLMs) for health-related queries, this study aimed to evaluate the quality of responses provided by four leading AI platforms Google Gemini, Microsoft Copilot, ChatGPT, and Meta AI to the most commonly asked questions about TMDs. A set of 45 standardized questions covering definitions, symptoms, causes, diagnosis, and management of TMDs was used. Responses from each platform were assessed on a Likert scale (1–20) across four key domains: Understandability, Readability, Credibility, and Contextual Relevance. While all four AI models demonstrated potential as educational tools for patients seeking information about TMDs, their quality and consistency varied. Based on this Likert-scale assessment, the overall ranking was: Google Gemini (1st) > Microsoft Copilot (2nd) > ChatGPT (3rd) > Meta AI (4th).

Ho Chi Minh’s thought on people’s security represents a profound synthesis of Marxist–Leninist theory and Vietnamese revolutionary practice. From a philosophical and political–military perspective, it reflects a dialectical understanding of the relationship between the people, the state, and national defense. Ho Chi Minh emphasized that genuine security originates from the people, is maintained by the people, and serves the people. This concept transcends the traditional notion of state security by integrating moral, political, and social dimensions into a unified system of people-based defense. The study clarifies the ideological foundations of Ho Chi Minh’s thought, including its roots in dialectical materialism, collective strength, and the unity of security and development. In contemporary times, his vision offers enduring relevance for safeguarding national independence, strengthening political stability, and addressing non-traditional security challenges. The paper concludes that Ho Chi Minh’s philosophy of people’s security continues to serve as a theoretical and practical framework for Vietnam’s comprehensive approach to defense and social order.

Background and Objective: The environment serves as a gateway to many disease conditions, especially when compromised or altered. Bayelsa State is known for its fragile environment, occasioned by crude oil contamination, reckless gas flaring, illegal artisanal oil refining, flooding, and gross lack of water, sanitation, and hygiene (WASH) systems. These factors have direct correlations with Communicable diseases (CDs) and non-communicable diseases (NCDs). This study is therefore designed to establish a verifiable basis for the impact of environmental degradation and contamination on the health conditions of residents in Bayelsa State. Materials and Methods: This descriptive study reviewed this thematic discourse using secondary data and literature sources from search engines and internationally revered publication platforms such as Elsevier, Scopus, ResearchGate, Google Scholar, Francis and Tylor, Springer, and a handful of others. Results: The findings have clearly shown that environmental degradation and contamination have obvious effects on the health conditions of the residents of Bayelsa State. Public health conditions such as infectious diseases, non-communicable diseases, malaria, cancer, pulmonary diseases, cardiac diseases, renal failure, infertility, congenital disorders, diabetes, and hypertension topped the list of associated diseases. Conclusion: There is a two-prong approach to resolving the disease proliferations associated with environmental degradation in Bayelsa State. Firstly, there is a need for effective policy directions by the federal and state governments in addressing the issue of environmental degradation using internationally accepted standards sourced locally. Secondly, it is on the side of the citizens to be responsive in ensuring an assurance of an environmentally friendly ecosystem in Bayelsa State.

Background: Stroke-like migraine attacks after radiation therapy (SMART) syndrome is a rare, delayed complication of cranial irradiation characterized by subacute, potentially reversible neurological deficits and distinctive imaging features. Its diagnosis is particularly challenging in patients with metastatic brain disease, where clinical and radiological findings overlap with tumor progression, radiation necrosis, and seizure-related phenomena. Case Presentation: We report the case of a 43-year-old male with stage IV ALK-positive non-small-cell lung adenocarcinoma with extensive brain metastases who developed acute global aphasia and altered mental status following multiple courses of cranial irradiation, including stereotactic radiosurgery, and whole-brain radiation therapy in addition to subtotal resection of a frontal brain lesion. The patient had prolonged systemic disease control with sequential ALK inhibitors but experienced repeated intracranial progression requiring multimodal local therapies. During an acute neurological deterioration in November 2025, neuroimaging demonstrated extensive post-radiation and metastatic changes, and the differential diagnosis included tumor progression, radiation necrosis, and focal status epilepticus. Given the clinical context and imaging limitations, SMART syndrome was suspected. High-dose intravenous corticosteroids led to partial neurological improvement, supporting the diagnosis of radiation-induced cortical dysfunction. Conclusion: This case highlights the diagnostic complexity of SMART syndrome in patients with advanced metastatic brain disease and cumulative radiation exposure.

This work presents an unsteady analysis of the hydromagnetic flow of an exothermic fluid with thermal characteristics through a microchannel. Following the discretization of the partial differential equations, the modelled time-dependent governing equations are solved using the implicit finite-difference technique (IFDM). Graphs depicting the influence of key parameters are created, and the findings are thoroughly described. As the temperature rises due to the exothermic process, the buoyant force frequently overcomes the Darcy resistance. This creates a rise in fluid velocity, especially if the medium is highly permeable. The interconnecting ligaments (pores) significantly improve the fluid-solid contact area over a simple microchannel. Furthermore, it is discovered that varying thermal conductivity has a substantial impact on temperature and hydromagnetic fluid in the microchannel. This study's findings will benefit applications in biomedical and chemical engineering, including catalytic packed-bed reactors, bioreactors, and waste treatment. In these systems, the porous structure functions as both a flow regulator and a thermal stabilizer. Bio-microfluidic systems and heat management in microelectronics, where properties vary fast with temperature, can all benefit from the findings of this study.

Despite the growing recognition of the transformative benefits of electronic procurement (e-procurement) systems, their adoption and effective implementation in developing countries, particularly Nigeria, has been considerably slow and uneven. Hence, the effectiveness of E-Procurement systems in enhancing supply chain efficiency in Kogi State, Nigeria, was investigated in this study. The study participant were workers in Kogi State ministries, departments, and agencies (MDAs) and questionnaires through electronic platforms/online survey platforms was used to gather data from the respondents, after which the data were analysed using Statistical Package for Social Sciences (SPSS) software v23. Results from the findings showed that majority of the respondents are procurement officers (81.8%), with 4-6 years working experience (63.6%). Also, 54.5% majority of the respondents stated that the e-procurement system has reduced procurement led time to a moderate extent, whereas more than half of the respondents (54.5%) stated that the e-procurement system has reduced procurement costs to a moderate extent. More also, 63.6 % majority of the respondents stated that e-procurement system significantly enhanced transparency and accountability in their organizations to a large extent. The major challenges usually encountered when implementing e-procurement systems in Kogi State MDAs were found to be lack of proper infrastructure (26.1%) and poor staff training and support (26.1%). Hence, it was recommended that there should be proper strengthening of digital infrastructure, adequate capacity building and training, change in management strategies, and stakeholders’ engagement among Kogi state MDAs, which will improve E-Procurement systems and supply chain efficiency.

Background: Orthodontic auxiliaries are frequently reused and may act as potential sources of cross-infection if not adequately sterilized. Limited comparative data exist regarding the effectiveness of commonly used sterilization methods for orthodontic materials. Aim: To evaluate and compare the effectiveness of different sterilization and disinfection methods in eliminating microbial contamination from selected orthodontic materials. Materials and Methods: This in-vitro microbiological study evaluated 48 orthodontic samples including NiTi closed coil springs, pre-formed molar bands with buccal tubes, and Class II elastics. Samples were divided into five groups: control, 70% ethanol, 2% glutaraldehyde, ultraviolet (UV) irradiation, and autoclaving. Following sterilization, all specimens were cultured on tryptic soy agar and incubated at 37°C for 72 hours. Microbial growth was assessed visually. Statistical analysis was performed using chi-square test. Results: All unsterilized samples demonstrated microbial growth. No microbial growth was observed in any samples treated with 70% ethanol, 2% glutaraldehyde, UV irradiation, or autoclaving. Statistically significant differences were observed between control and treated groups (Chi-square = 8.778, p = 0.003). Conclusion: All evaluated sterilization methods were effective in eliminating microbial contamination from orthodontic materials. Autoclaving and glutaraldehyde immersion are recommended as primary methods, while UV irradiation and ethanol can serve as adjunctive alternatives.

The study seeks to explore the olden days and contemporary tricks deployed by fraudlers in rubbing off their victims of their valuable possessions, money, food items etc. The study used both primary and secondary means in collecting its data and descriptive survey data analysis was used in order to analyses the study’s data. The study revealed among other things that the fraudulent activities via tricking has negative effects on both the victims as well as their communities. The study also recommends that fraudlers be exposed among the communities and people should morally upright as there is no short-cut to richness.

The purpose of this study is to explore the intricate relationships between Value-Based Care (VBC) and various organizational and leadership factors within healthcare settings. The research question concerns what is the impact of those factors on the implementation of VBC. The research adopts an explanatory approach and utilizes a quantitative method by employing a questionnaire to reach a sample of 376 respondents. The research was exclusively carried out in the eastern health cluster hospitals of the kingdom of Saudi Arabia. The findings revealed that effective nursing leadership, employee engagement, change management skills, and organizational culture significantly contribute to the successful implementation of VBC. The findings underscore the critical role of nursing leadership in driving improvements in patient care quality and operational efficiency. This research also highlights the importance of fostering a positive organizational culture and robust change management capabilities to enhance VBC practices. By identifying these key factors, the study provides actionable insights for healthcare administrators and policymakers aimed at improving patient outcomes and achieving cost-efficiency through the adoption of VBC models. Despite its contributions, the study acknowledges certain limitations and suggests avenues for future research to further validate and expand upon these findings.

Background: Healthcare workers in resource-constrained settings experience significant occupational stressors that may influence coping behaviours and psychological wellbeing. Objective: To examine the relationship between frustration, sociodemographic characteristics, and coping styles among healthcare workers in a tertiary hospital in North-Central Nigeria. Methods: A cross-sectional analytical study was conducted among 385 healthcare workers using stratified sampling. Data were collected using a structured questionnaire, the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS), and the Brief COPE inventory. Descriptive statistics summarized participant characteristics and workplace stressors. Pearson and partial correlation analyses assessed relationships between frustration and coping styles. Multiple linear regression identified independent predictors of maladaptive coping. Statistical significance was set at p < 0.05. Results: Workplace frustration was highly prevalent, driven by workload, inadequate equipment, and poor remuneration. Adaptive coping strategies predominated, particularly active coping, planning, and religious coping. Frustration was not associated with adaptive coping (r = –0.017, p = 0.737) but was significantly associated with maladaptive coping (r = 0.266, p < 0.001). This relationship remained significant after adjusting for sociodemographic variables (r = 0.241, p < 0.01). Regression analysis showed that frustration independently predicted maladaptive coping (β = 0.266, p < 0.001), while longer professional experience was protective. Conclusion: Healthcare workers demonstrated resilience through adaptive coping strategies; however, increased frustration is associated with greater reliance on maladaptive coping. Addressing structural stressors is essential to improve coping and wellbeing.

Determining the fetal weight accurately is essential for prenatal treatment and decision-making. The purpose of this study was to estimate the weight of the fetus in Ojo, Lagos State, Nigeria between 20 and 40 weeks of gestation by developing a fetal anthropometric model using ultrasound measures. A longitudinal study of 300 pregnant women was conducted, with obstetric ultrasound scans images. Fetal biometric parameters (abdominal circumference and femur length) were measured and correlated to estimate fetal weight using Hadlock’s formula. A predictive model for fetal weight estimation was created using regression analysis. From the results, fetal biometric measurements are connected. When one goes up, the other goes down. This means that there is a relationship between fetal biometric measurements and estimated fetal weight (EFW). Hence, the size of a fetus can help us estimate how much it weighs. This shows that fetal measurements are helpful in predicting fetal weight.

Artificial intelligence (AI), coupled with machine learning (ML) has been rapidly incorporated into pharmaceutical discovery and development. We reviewed 53 publications from 2018-2026 to summarize current applications of AI/ML in drug discovery. AI and ML have potential to impact every step of the drug development pipeline and have already shown to drastically reduce time frames for developing therapeutics. Specific deep learning models such as graph neural networks and transformers have shown promise in de novo molecular generation, molecular property prediction, and target recognition. Accurate protein structure prediction using AlphaFold allows for exploration of drug-target binding. De novo drug design with reinforcement learning allows for targeted design of molecules with desired properties. Machine learning models for QSAR provide more accurate toxicity predictions and ADMET profiling to avoid potential failures during drug development. However, current limitations include lack of interpretability, data limitations, and lack of regulatory approval. According to a review of recent literature, AI has the potential to decrease the time required for drug discovery from years to months and lower the cost of drug development. This review discusses recent advances, successful clinical examples, and opportunities for artificial intelligence/machine learning in drug discovery.

Much recent studies in trying to discover a more accurate and reliable method in age estimation have been ongoing. The study aimed at estimating age using the metrical parameters of the tibia bone. Long bones adjudged to be reliable also offer researchers an easy-to-use approach for its robustness and uniqueness. The cadaveric samples included bones of the right tibia of 78 males (53 profiled and 25 non-profiled for age) who are within the age range of 21 and 60 years. A convenience sampling technique was utilized for the bone collection. Two to three bone sections were collected from the mid-shaft of the right tibia using a hacksaw. The data was analyzed with SPSS 25. The findings showed that the mean of the marrow cavity diameter (MCD), marrow area (MA), radius, and area of cortex were 2.15 ± 0.07, 4.10 ± 0.27, 0.36 ± 0.01, and 0.45 ± 0.04, respectively. ANOVA test for variation shows a statistically significant (P=0) variation in the MCD and MA between the different age groups studied. The variation in the area of cortex was not statistically significant (P>0.05). The MCD, MA, and the radius of the cortex show weak correlation with age (r= 0.264, 0.363, and 0.031), and are hence poor assessors of age in males using the tibia.

Cancer continues to be a leading cause of death globally, with almost 10 million people dying from the disease annually, presenting a significant global health challenge. While traditional therapies - surgery, radiotherapy, chemotherapy, targeted therapy and immunotherapy - have extended survival rates, they are often compromised due to systemic toxicity, inadequate pharmacokinetics, lack of selectivity, and drug resistance. Innovative drug delivery systems (DDS), especially nanotechnology-based DDS, have recently gained attention as potential methods to improve therapeutic outcomes and outcomes. This review critically examines the advances in drug delivery for cancer treatment, with particular emphasis on nanotechnology-based systems such as liposomes, polymeric nanoparticles, dendrimers, inorganic nanoparticles, exosomes, and antibody–drug conjugates. Various features such as passive and active targeting strategies, drug release in response to stimuli, internalization and intracellular trafficking, administration routes, and in vivo considerations are thoroughly reviewed. Further, the review outlines the current clinical translation, regulatory advances, and key challenges, such as biological barriers, protein corona, scalability and tumor heterogeneity. The review also outlines future perspectives - such as artificial intelligence-driven formulation development, multi-omics integration, organoid-based systems for drug validation and precision nanomedicine - are also discussed as key factors for next-generation cancer treatment. In general, advanced DDS are helping to transform non-specific, conventional chemotherapy into targeted, efficient and individualized cancer therapies.