We present X-shooter spectroscopic and photometric observations of a sample of 21 hydrogen-poor superluminous supernovae (SLSNe-I), spanning a redshift range of z = 0.13-0.95, aimed at searching for shells of circumstellar material (CSM). Specifically, we focused on identifying broad absorption features that are blueshifted by several thousand kilometers per second relative to the narrow absorption lines associated with the host galaxy. These broad features have previously been interpreted to arise from resonance line scattering of the SLSN continuum by rapidly expanding CSM ejected shortly before explosion. Utilizing high-quality near-ultraviolet spectra, we modeled the region around 2800 Å to characterize the Mg II Mg II line profiles, enabling us to either confirm their presence or place constraints on undetected CSM shells. We identified five objects in our sample that show broad absorption features consistent with the presence of CSM. While SN,2018ibb, SN,2020xga, and SN,2022xgc have been previously reported, we identified previously undiscovered CSM shells in DES15S2nr and DES16C3ggu. In the case of DES15S2nr, the CSM shell is located at ∼ 3.4 Mg II 10^ 15 ̊m cm and is moving with a maximum velocity of ∼ 4800̊m km s^ -1 . For DES16C3ggu, the shell lies at ∼ 4.8 ̊m cm and reaches up to ∼ 4700 ̊m km s^ 10^ 15 -1 . These shells were likely expelled approximately two and three months before the explosion of their respective associated SNe on timescales consistent with late-stage eruptive mass-loss episodes. We further found evidence that the velocities of the CSM shells in all objects lie within 3000-5000 ̊m km s^ -1 , which may reflect an intrinsic property and could hint at a similar mass-ejection mechanism. We did not find any correlations between the shell properties and the SN properties, except for a marginal correlation between the light curve decline timescale and the shell velocities. This correlation needs further work; however, if it applies, it is a powerful link between the late-time mass ejection and eventual explosion. We further demonstrate that CSM configurations similar to the majority of the detected shells would have been observable in spectra with a signal-to-noise $>5$ per resolution element, and that the lines from a shell are, in general, detectable except in cases where the shell is either very geometrically and/or optically thin. Therefore, we conclude that the non-detections are unlikely to arise from selection effects but they may instead point to the existence of a subclass of SLSN-I progenitors undergoing late-stage shell ejections shortly before explosion.

To systematically summarize and evaluate the current evidence regarding sex-based differences in healthcare utilization (HCRU), direct costs, and indirect socioeconomic burden in patients with pituitary adenomas. A systematic literature search of PubMed, EMBASE, and Web of Science identified studies reporting HCRU and/or cost data with sex-stratified analyses. Studies focusing on drug-specific cost-effectiveness, case reports, and scenario-based models were excluded. Eight studies met the inclusion criteria, including non-functioning pituitary adenoma, prolactinoma, acromegaly, Cushing's disease (CD), and perioperative pituitary tumor cohorts from Europe and the United States. Findings were synthesized narratively due to methodological heterogeneity and the scarcity of sex-specific cost estimates. Total and surgical costs did not differ between men and women across most settings in Europe. Only one U.S. acromegaly cohort showed lower adjusted annual costs in women, and one Chinese perioperative patient cohort reported lower inpatient charges among women. In contrast, sex-based differences in HCRU were consistent and clinically relevant: women with acromegaly demonstrated longer diagnostic delays, more pre-diagnostic visits, higher specialist engagement, and more treatment modifications. Perioperatively, sex was not a predictor of length of stay or cost, but several cohorts reported higher rates of cerebrospinal fluid leak, arginine-vasopressin deficiency, and late hyponatremia in women. The most pronounced disparity was observed in indirect socioeconomic burden, with women more frequently experiencing reduced work capacity, early retirement, psychosocial distress, and poorer quality-of-life in acromegaly and CD. Although sex-based differences in overall healthcare costs are limited, women face a disproportionately complex and burdensome care trajectory. Standardized, value-based care pathways may help mitigate these disparities, underscoring the need for prospective, sex-stratified studies.

Low back pain (LBP) is a global health problem that contributes to disability, psychological distress, and reduced quality of life in older adults. Current treatment guidelines for LBP support the use of conservative therapies such as physical therapy alongside medication management. However, interventional pain management strategies for LBP such as lumbar epidural steroid injection (LESI) are rarely mentioned. We conducted this systematic review to characterize and evaluate the use and effectiveness of LESI amongst older adults with LBP. We conducted a systematic English-language literature search of Ovid MEDLINE, Ovid EMBASE, and Cochrane Library. We used an iterative approach to identify both keywords and controlled vocabulary related to treatment outcomes of epidural interventions for LBP among older adults. The results were reviewed by three members of the team. Our search of 3 databases produced a total of 2657 studies and 12 met final inclusion criteria. In all studies, the use of LESI was associated with improvement in pain and/or quality of life. As compared to medication management, LESI was associated with statistically significant improvements in pain and functional status. The addition of physical therapy was not superior to LESI alone. This systematic review is the first that focuses on the effectiveness of LESI in managing LBP in older adults. This review suggests that LESI may reduce pain and improve functional status in older adults, particularly as compared to medication management. The study was prospectively registered on Prospero (ID # 422087). Not Applicable.

Machine learning (ML) applied to diffusion tensor imaging (DTI) has emerged as a promising tool for detecting microstructural brain alterations in movement disorders. However, existing studies vary widely in design, sample size, imaging pipelines, and analytic rigor, resulting in high methodological heterogeneity that limits quantitative comparability. This exploratory meta-analysis and narrative synthesis aimed to characterize performance trends, methodological diversity, and sources of variability among ML models trained on DTI data for classifying movement disorders, rather than to infer a single pooled diagnostic effect. This was designated exploratory because extreme heterogeneity prevented confirmatory pooled effect inference, so the analysis focused on describing performance distributions and methodological patterns rather than estimating a unified diagnostic effect. A systematic search of PubMed, Web of Science, and Scopus identified human studies applying ML algorithms to DTI for diagnostic or classification purposes. Accuracy, sensitivity, specificity, and the area under the curve (AUC) were extracted, with multiple imputation used for incomplete metrics with missingness rates below 40%. Random-effects modeling was employed to provide descriptive summaries, and subgroup analyses were conducted to explore trends across disorders, model architectures, and imaging modalities. Study qualities were assessed with JBI tools. Forty-six studies (2016-2024) were included, spanning Parkinson's disease, Tourette syndrome, and essential tremor. Reported performance was generally high (median AUC ≈ 0.91), but between-study heterogeneity was extreme (I2 = 94.7%), indicating that studies were estimating distinct effects. Disorder-specific subgroup AUCs varied markedly: Essential Tremor (0.95), Parkinson's (0.90), Tourette's (0.88), and Other (0.79). Deep learning and radiomics-based models have reported higher accuracies, but they were often trained on small, single-center cohorts (37-139 participants), which limits their external validity. Pooled statistics were presented descriptively to illustrate performance ranges despite high heterogeneity, and were not interpreted as confirmatory effect sizes. ML models using DTI demonstrate high internal performance across studies, although generalizability remains limited across multiple movement disorders; however, current evidence remains exploratory due to small sample sizes, methodological fragmentation, and a lack of standardized imaging pipelines. Rather than confirmatory inference, these findings provide a descriptive map of emerging trends in ML-DTI diagnostics. Future progress will depend on data harmonization initiatives, multicenter collaborations, and federated learning frameworks that can support reproducible, generalizable, and clinically interpretable models.

Combining interventional therapy with immune checkpoint inhibitors (ICIs) has shown potential benefits in hepatocellular carcinoma (HCC). However, comprehensive evidence on its efficacy and safety remains limited. A systematic search of PubMed, Embase, Cochrane Library, and Web of Science was conducted to identify eligible studies for single-arm and Bayesian network meta-analyses (NMA). Progression-free survival (PFS) was the primary endpoint, while overall survival (OS), objective response rate (ORR), and grade ≥ 3 adverse events (AEs) were secondary outcomes (PROSPERO: CRD42024619661). This study included 45 studies (n = 4,738), evaluating 14 distinct regimens. In single-arm analysis, transcatheter arterial chemoembolization (TACE) plus tyrosine-kinase inhibitor (TKI) plus tislelizumab [TACE-TKI-Tisle] yielded a pooled median PFS of 11.7months (95% confidence interval [CI] 8.02-15.37), an ORR of 72% (95% CI 63-80%), and a grade ≥ 3 AE rate of 24% (95% CI 15-34%). NMA showed that TACE-TKI-Tisle and TACE-TKI-Camrelizumab (Camre) achieved significantly longer PFS than TACE-TKI or TACE alone. TACE-TKI-Toripalimab (Tori) showed OS benefits over TACE-TKI-Camre (HR = 0.43; 95% CI 0.20-0.95) and TACE-TKI-Pembrolizumab (Pembro) (HR = 0.32; 95% CI 0.13-0.81). Cumulative ranking via surface under the cumulative ranking curve (SUCRA) indicated that TACE-TKI-ICI achieved the highest efficacy ranking. TACE-TKI-Tisle and TACE-TKI-Tori ranked highest for PFS/ORR, with TACE-TKI-Tori ranking first for OS (SUCRA = 0.981). While TACE-TKI-ICI combinations were generally associated with more grade ≥ 3 AEs, TACE-TKI-Tisle ranked intermediately for safety (SUCRA = 0.426). TACE-TKI-ICI combinations show promising efficacy in HCC. TACE-TKI-Tisle offers balanced efficacy and safety, while TACE-TKI-Tori provides notable OS benefits, warranting further validation in prospective studies.

Artificial intelligence (AI) is profoundly transforming the healthcare landscape, presenting unprecedented opportunities to enhance patient care and clinical outcomes. However, the rapid integration of AI technologies has raised significant ethical concerns, requiring rigorous scrutiny to ensure their responsible and equitable use. This study aimed to explore the ethical considerations and strategies related to the implementation of AI in healthcare through a systematic review. A systematic search identified 243 publications published between 2019 and 2025 that were initially identified. After applying inclusion and exclusion criteria, 22 papers were selected for final synthesis to assess ethical concerns and strategies related to AI in healthcare. The analysis identified key ethical concerns, categorizing them into six distinct groups: (1) Transparency and Trust, (2) Bias and Fairness, (3) Privacy and Data Security, (4) Accountability and Responsibility, (5) Ethical and Moral, (6) Regulatory and Legal. Additionally, several ethical strategies were identified in the implementation of AI systems, including adherence to ethical principles, standards, and frameworks; transparency and bias mitigation; monitoring and auditing of AI systems; and stakeholder involvement and governance in decision-making processes. This review emphasizes the importance of addressing these ethical concerns to ensure the successful implementation of AI technologies in healthcare. The findings provide valuable insights and recommendations for stakeholders, including developers, healthcare professionals, and policymakers, to guide the ethical deployment of AI decision support systems in healthcare.

Cannabis sativa L. is an annual herbaceous plant with a long history of multipurpose use, including food, textile, and medicinal applications. The progressive legalization in several countries has significantly increased its large-scale cultivation, consequently generating a substantial amount of biomass waste. This scenario calls for innovative and sustainable strategies to valorize Cannabis residues, aiming at promoting the circular economy and technological innovation. An integrative review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Systematic searches were performed in SCOPUS, PubMed, and SciELO, complemented by specialized platforms such as CANNUSE and CONSENSUS. Peer-reviewed empirical studies were included if they addressed the utilization, reutilization, or recycling of C. sativa by-products or residues for the development of industrial products, processes, or inputs. The analysis considered thematic and commercial domains, geographic origin, and biomass type. A total of 262 studies were included, with 144 retrieved from indexed databases and 118 from alternative methods. The most commonly explored residues were stems (48.2%), seeds (21.0%), and postextraction residuum (9.7%). The majority of applications were related to technology and innovation (37.5%) and industrial sectors (36.9%). A total of 328 technologies were identified, highlighting applications such as textile fibers, bioplastics, biofuels, functional foods, adsorbents, and natural cosmetics. Italy, China, and the United States led in scientific production. Leaves (7.0%) and roots (0.9%) were significantly underexplored despite their bioactive potential. The findings demonstrate a growing global interest in the valorization of C. sativa residues, with promising applications in bioeconomy, regenerative agriculture, phytoremediation, and energy transition. The integration of traditional knowledge and green technologies is a key strategy to enhance sustainability and socioterritorial inclusion. Nonetheless, regulatory gaps and a lack of robust clinical and toxicological studies limit the use of by-products in food and feed chains. The residual biomass of C. sativa holds high technological, environmental, and economic value. Strategic valorization demands regulatory advancement, the development of green technologies, and the strengthening of multidisciplinary research. Industrial Cannabis emerges as a driver of ecological, social, and economic transformation toward sustainable circular production systems.

Lablab ( Lablab purpureus ) is a resilient, multipurpose legume with potential to improve food and feed security, enhance soil fertility, and support climate-resilient agriculture in Tanzania’s dryland regions; however, comprehensive syntheses of its agronomic, socioeconomic, and ecological roles remain limited. To address this, a scoping review was conducted of studies published between January 2000 and June 2025 in Tanzania and comparable dryland agroecological zones in Sub-Saharan Africa. Systematic searches in Scopus and Google Scholar used structured Boolean strings including keywords related to lablab, dryland farming, forage, fodder, intercropping, nitrogen fixation, soil fertility, pests, diseases, market access, and adoption potential, and reference lists of included studies were screened manually. Of 120 full-text articles assessed, 85 met inclusion criteria and were analyzed thematically. Results show that lablab is well-adapted to semi-arid and dryland zones, contributes to soil health, supports livestock feed and human nutrition, and enhances climate-resilient farming systems, while adoption is constrained by limited farmer awareness, inadequate agronomic knowledge, scarcity of improved seeds, weak market linkages, and climate variability. These findings provide a structured evidence map of lablab’s roles, challenges, and potential, highlighting opportunities for coordinated interventions targeting seed systems, value chains, and extension services to facilitate mainstreaming, promote resilient low-input agricultural systems, and support sustainable livelihoods.

Background: Spinal tumors are neoplasms occurring in or around the spinal cord and can be classified based on tissue type and location within the spine. These lesions can lead to spinal cord compression and neurologic deficit. Low- and middle-income countries (LMICs) often face a significant burden of disease due to limited access to healthcare and advanced treatments. We investigate surgical and adjunctive therapies for spinal column tumors in LMICs. Methods: A systematic search was completed to identify articles related to spinal tumors in LMICs. Data were extracted for study parameters and patient outcomes. Country-specific variables were collected for each country. A pooled meta-analysis was completed with this data. Results: Of 99 included articles, 67 provided data on gross total resection (GTR), while 39 articles reported use of adjunctive therapies. Since 1990, there has been an increase in the use of both treatments in LMICs; however, there were significant correlations between the use of adjunctive therapy, life expectancy, and access to healthcare. Conclusion: While treatment and outcomes of spinal column tumors vary within the United States based on socioeconomic factors, including income and gender, this has not been studied on a global scale and in relation to accessibility of specific treatments in LMICs. In this study, we found that specific diagnoses and country income levels were significant drivers of GTR or adjunctive therapy rates. The poor accessibility of these treatments may be overcome with targeted investment, and this should be explored in future research.

Homeopathy is used by some veterinary practitioners as a complementary approach for treatment and prophylaxis in a range of animal species. The clinical evidence base is contested and heterogeneous. This systematic review synthesizes randomized and non-randomized clinical trials, systematic reviews and key policy statements assessing the clinical use, efficacy, safety, welfare implications, and regulatory context of veterinary homeopathy. Methods: A systematic search and synthesis were performed across published systematic reviews, randomized controlled trials (RCTs), controlled clinical trials (CCTs), and institutional position statements concerning homeopathy in animals. Data were extracted on species, indication, study design, risk of bias, outcomes, and main conclusions. Evidence quality and clinical implications were evaluated. High-quality systematic reviews found a limited number of RCTs with heterogeneous quality and endpoints; meta-analysis suggests only very limited evidence of effects beyond placebo in animals, with small, low-quality trials responsible for most positive findings. A small number of trials reported outcomes favoring homeopathy for specific indications like prophylaxis of post-weaning diarrhea in pigs and some mastitis studies, but methodological limitations and risk of bias substantially limit confidence. Broad reviews of complementary and alternative veterinary medicine and evidence syntheses similarly conclude that clear, reproducible evidence for routine clinical effectiveness is lacking. Institutional position statements (RCVS, BVA, AVMA) emphasize evidence-based use and caution where animal welfare could be compromised. Current clinical evidence does not provide robust support for routine substitution of conventional proven therapies with homeopathy in veterinary medicine. Homeopathy may be considered as a complementary option where used alongside conventional treatment, provided informed consent, rigorous monitoring, and safeguards for animal welfare. High-quality, adequately powered randomized trials with transparent reporting are needed for firmer conclusions.

In the 21st century, achieving proficiency in both scientific and digital literacies is crucial for effective societal participation and addressing complex global challenges. However, a significant cultural disconnect often persists in formal science education, marginalizing students' indigenous knowledge. This systematic literature review aims to investigate the efficacy of ethnoscience-based instruction in bridging this gap and enhancing students’ scientific and digital literacies within the Indonesian educational context. Following PRISMA guidelines, a systematic search was conducted in Google Scholar, Scopus, Dimensions, and ERIC. This process identified 28 eligible studies published between 2016 and 2025. Data were analyzed and compared using reported gain scores to evaluate the impact of various instructional interventions. The findings reveal that research in this field is predominantly characterized by Research and Development (R&D) designs (60%), with a primary focus on the secondary school level. The analysis demonstrates that ethnoscience serves as a powerful pedagogical bridge, linking students' local cultural backgrounds to modern scientific concepts. While publications are increasing, a significant disparity exists between the widespread focus on scientific literacy and the emerging, yet underdeveloped, area of digital literacy. Interventions that integrate ethnoscience with digital modalities are effective for general knowledge acquisition but are limited in fostering higher-level scientific attitudes and inquiry when used without a robust pedagogical framework. The results indicate that integrating ethnoscience into established learning models, particularly Project-Based Learning (PjBL) and Problem-Based Learning (PBL), yields significantly more holistic outcomes compared to media-only interventions. These models are uniquely effective in promoting complex competencies, including scientific inquiry, citizenship literacy, and cultural awareness. This study concludes that future pedagogical practices should prioritize structured, model-based integration to fully harness the potential of ethnoscience for comprehensive 21st-century skill development. Keywords: ethnoscience, scientific literacy, digital literacy, systematic review.

Abstract In worldwide, climate change poses an increasingly serious threat to horticultural production and postharvest management, with rising temperatures, shifting rainfall patterns, and more frequent droughts and floods increasingly affecting crop performance and quality. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search was conducted using Web of Science, Scopus, and other major databases. After screening, duplicate removal, and eligibility assessment, 140 studies were synthesized in this review. Horticultural crops particularly fruits, vegetables, and ornamentals are highly sensitive to these changes due to their perishability and narrow climatic tolerances. Induced abiotic stresses disrupt key physiological processes, fruit development, reduce yield, and increase the vulnerability to pests and diseases, while also compromise the nutritional value and market quality of produce. In addition to production-level impacts, climate change accelerates postharvest deterioration, shortens shelf life, and increases losses during storage, transport, and marketing. Beyond production losses, climate variability accelerates postharvest deterioration, shortens shelf life by increasing respiration, water loss, and microbial spoilage, leading to higher losses during storage, transport, and marketing. These impacts are especially severe in developing countries, where limited cold chain capacity and weak adaptive systems constrain resilience. These impacts pose serious threats to food security, livelihoods, and the global competitiveness of horticultural markets, particularly in developing nations where limited cold chain capacity and adaptive systems constrain resilience. This review synthesizes current evidence on the biophysical and socio-economic effects of climate change on horticultural systems, emphasizing its implications for food security, livelihoods, and market stability. It also highlights practical mitigation and adaptation strategies, including climate resilient varieties, improved agronomic and water management practices, efficient and energy smart postharvest technologies, and supportive policy measures. The review underscores the need for integrated, climate-smart approaches that strengthen institutional capacity, promote innovation, and enhance farmer awareness to sustain horticultural productivity and reduce postharvest losses under a changing climate.

This systematic review and meta-analysis aimed to investigate the acute effects of flywheel resistance training (FRT) on jump and sprint performance, and to examine the moderating roles of rest intervals and inertial loads. A systematic search was conducted across seven electronic databases (Web of Science, PubMed, SPORTDiscus, Scopus, CINAHL, Embase, Cochrane) from inception to February 22, 2025. The quality of included randomized controlled trials (including crossover designs) was assessed using the Cochrane RoB 2 tool. The certainty of evidence was evaluated using the GRADE approach. Data were synthesized using random-effects meta-analysis in Review Manager 5.4.1, with subgroup analyses performed for rest intervals and inertial loads. The study protocol was registered in PROSPERO (CRD420251029079). Nine crossover trials were included. Overall, FRT had a small, significant positive effect on CMJ performance [SMD = 0.32, 95% CI: (0.03, 0.60)], but no significant effect on overall sprint performance [SMD = -0.03, 95% CI: (-0.29, 0.22)]. Subgroup analysis revealed enhancement effect on CMJ at rest intervals of 8-12min [SMD = 0.55, 95% CI: (0.17, 0.93)] and when using inertial loads > 0.05kg·m² [SMD = 0.48, 95% CI: (0.09, 0.88)]. No significant subgroup effects were found for sprint performance. Flywheel resistance training induces a small, acute enhancement in jump performance, primarily through a post-activation performance enhancement (PAPE) mechanism, with significant effects observed at 8-12min post-exercise. Greater benefits for jumping occurred with inertial loads > 0.05kg·m², but no significant acute effect was observed for sprint performance. These findings are limited by low evidence certainty and restricted generalizability, necessitating further research with larger, diverse samples and standardized protocols.

Which factors correlate with muscle strength capacity in people with patellofemoral pain? A systematic review with meta-analysis.

Prostate cancer (PC) is the second most common cancer in men. Although many studies have assessed its economic burden, no recent reviews have focused on studies conducted under current clinical guidelines. This study systematically reviews recent cost-of-illness studies evaluating direct and indirect costs associated with PC. A systematic search was conducted using the PICOS framework and a combination of free-text and MeSH terms in PubMed and the Cochrane Library, and only free-text terms in EconLit. The search included articles published between January 2015 and October 2025. Data on total, direct, and indirect costs were extracted and synthesized. All costs were converted to 2025 USD, and quality of studies was assessed with a simplified version of the CHEERS checklist. Ninety-five studies met the inclusion criteria. Direct medical costs for non-metastatic prostate cancer (nmPC) varied widely by disease stage, treatment, and country, ranging from approximately US$1200 to US$280,000 per patient-year, with higher costs observed in advanced stages and in patients experiencing treatment-related adverse events (AEs). Progression to metastatic disease was associated with a marked cost escalation, with annual costs largely driven by systemic therapies and skeletal-related events. Indirect costs ranged from US$666 to US$12,900 per patient-year and accounted for up to 30% of total PC-related costs, primarily due to productivity losses from premature mortality. PC imposes a substantial economic burden on healthcare systems and society, particularly in advanced stages. Policy promoting early detection, risk-adapted treatment, and equitable therapy access may help contain costs. Further research should address the economic impact of emerging diagnostics and minimally invasive interventions.

Background: Most ICU patients are in the terminal phase and require complex palliative care support and End-of-Life Care (EoLC). Nurses play a central role in symptom management, emotional support, and shared decision-making. However, evidence on nurses’ experiences in providing EoLC remains fragmented and lacks a comprehensive synthesis. Objective: This review aimed to identify, map, and synthesize global evidence on ICU nurses’ experiences in delivering EoLC, including challenges, coping strategies, and implications for critical care nursing practice. Methods: A scoping review was conducted following Arksey and O’Malley’s framework and PRISMA-ScR guidelines. Systematic searches were performed in the PubMed, Scopus, and EBSCOhost databases for studies published between 2015 and 2025. Thematic analysis was applied to the qualitative studies to identify patterns and key issues. Results: Twelve qualitative studies conducted in diverse countries met the inclusion criteria. Five major themes emerged: (1) emotional and moral challenges; (2) cultural and spiritual influences; (3) communication and interprofessional collaboration; (4) professional development and organizational support; and (5) resource constraints. These findings indicate that ICU nurses’ experiences with EoLC are multidimensional and shaped by the cultural context and institutional policies. Conclusions: ICU nurses’ experiences with EoLC reflect complex ethical, emotional, and organizational dimensions. Improving care quality requires structured training, organizational support, and culturally sensitive policies to strengthen critical care nursing practice.

Objectives This study aimed to identify multilocus sequence type (MLST), serotype, average nucleotide identity (ANI), antimicrobial resistance genes (ARGs), virulence genes (VGs), and mobile genetic elements (MGEs) from whole-genome sequences of 10 Escherichia coli isolated from seafood in Bangladesh and compared them with the global datasets of beta-lactamase-producing E. coli . Methods Ten E. coli isolates (crab = 3, shrimp = 1, tuna = 6) were subjected to whole-genome sequencing using Oxford Nanopore Technologies (Oxford, UK). In-silico bioinformatics analyses were performed using online tools and Linux-based commands. A systematic advanced search in PubMed identified 722 global genomes of beta-lactamase-producing E. coli for comparative analysis. A population structure and global phylogeny were constructed to illustrate the current status of beta-lactamase-producing E. coli from diverse sources (seafood, human, aquatic, wastewater, and environmental) across countries, based on their STs, ARGs, VGs, MGEs, and serotypes. Results Bioinformatics analysis revealed that most isolates displayed unique sequence types (STs) and core genome sequence types (cgSTs), while three isolates shared both ST1431 and cgST104784, indicating close genetic relatedness supported by ANI analysis. In shrimp and tuna isolates, both O and H antigens were detected, whereas crab isolates carried either O or H antigens. Pangenome analysis identified 56.4% strain-specific genes, 34.2% dispensable genes, and 9.4% core genes, with functions categorized into clusters of orthologous groups (COGs). Several ARGs, including beta-lactamase genes ( CTX-M-15, AmpC, bla DHA-1 ), were detected across isolates, with crabs harboring the highest number. The VGs were more common in tuna isolates. Plasmids were only detected in crabs (Col440I, IncFIA, IncFIB(pHCM2), and ColRNAI) carrying qnrB4 , dfrA17 , qacE , mph(A) , sul1 , bla DHA-1 ARGs, but were absent in shrimp and tuna. Population structure analysis showed that ST345 in Bangladesh closely matched wastewater (Czech Republic) and human (USA) isolates. Some STs overlapped with international records, while others appeared novel, suggesting limited global distribution. Globally, wastewater and human isolates from the Czech Republic showed the greatest similarity to our strains. Conclusion These findings underscore the potential role of seafood in disseminating beta-lactamase-producing E. coli , highlighting the urgent need for integrated surveillance to mitigate antimicrobial resistance risks in humans, animals, and the food chain.

Cardiorespiratory fitness (CRF) is a central determinant of health, performance, and resilience across the lifespan. Its development during childhood and adolescence reflects a complex interplay between growth, biological maturation, habitual activity and training. Understanding how CRF evolves and how it can be enhanced through training is fundamental for optimising youth development, promoting long-term health. Longitudinal research indicates that CRF increases steadily from early childhood to mid-adolescence (Ingvarsdottir et al., 2024). These developmental patterns are strongly sex- and maturation-dependent: boys typically show a steeper rise and higher peak in maximal oxygen uptake (VO₂max) and endurance performance, mainly due to pubertal increases in muscle mass, cardiac output, and haemoglobin concentration, whereas girls experience relatively attenuated improvements due to greater fat mass accretion (Ingvarsdottir et al., 2024). Nevertheless, interindividual variability is substantial. Distinct developmental trajectories emerge depending on early-life activity levels, adiposity, and intrinsic aerobic capacity (de Fátima Guimarães et al., 2023), highlighting that maturation provides only the physiological framework for improvement, whereas behavioural engagement determines the realised potential. The trainability of CRF during growth is well documented but highly dependent on maturational status. Aerobic and high-intensity training interventions in children and adolescents consistently yield meaningful improvements in endurance performance. However, recent large-scale meta-analytic evidence quantifies a distinct trainability gap between children and adults. Across more than 650 studies, children’s mean VO₂max training response amounted to ~58 % of the adult adaptation (Dotan, 2025), although high intensities were more effective. According to Dotan (2025), this attenuated responsiveness likely reflects neuromuscular rather than cardiovascular limitations – specifically, a reduced capacity to recruit high-threshold motor units. With advancing maturation, endocrine changes and neuromuscular efficiency might enhance these mechanisms, closing the trainability gap. While this synthesis of studies is an important foundation, it lacks a systematic literature search and does not account for moderating factors such as training load or the allometric scaling of VO₂max adaptations (Dotan, 2025). This is why we are currently addressing these issues in a systematic review with meta-analysis, where preliminary findings will be presented in the symposium. By integrating developmental, physiological, and methodological perspectives, this work aims to clarify whether the apparent child–adult differences in VO₂max trainability reflect true biological constraints or analytical artefacts. Understanding these mechanisms will contribute to a more accurate framework of aerobic adaptation across growth and maturation, guiding age-appropriate training strategies and informing evidence-based approaches to promote lifelong fitness and health.

Hemodiafiltration (HDF) is increasingly used because of its enhanced theoretical clearance of diverse uremic toxins, particularly middle molecules and inflammatory cytokines, relative to conventional hemodialysis (HD), yet evidence on its biochemical benefits remains conflicting. Therefore, this meta-analysis was performed to evaluate the effects of HDF versus HD on uremic toxins, inflammation, anemia, and nutritional parameters. A systematic literature search was conducted using PubMed, Scopus, and the Cochrane Central Register of Controlled Trials to identify relevant studies. Only randomized controlled trials (RCTs) were included. Random-effects meta-analyses were performed to evaluate changes in the prespecified outcomes. Twenty-four RCTs involving 6072 dialysis patients were included. Compared with conventional HD, HDF was associated with significant reductions in serum phosphorus (weighted mean difference [WMD] −0.28 mg/dL; 95% CI −0.44 to −0.12) and β2-microglobulin (WMD −4.84 mg/dL; 95% CI −6.13 to −3.54). HDF also significantly reduced serum urea and C-reactive protein (CRP) levels, along with weekly erythropoietin requirements. Serum albumin levels were slightly but significantly lower in the HDF group than in the conventional HD group (WMD –0.06 g/dL; 95% CI −0.10 to −0.01); however, the clinical significance of such a difference remains uncertain. Higher convective volumes were identified as a key determinant of greater reductions in β2-microglobulin and CRP. Compared with conventional HD, HDF demonstrated superior reductions in several surrogate endpoints, including serum phosphorus, urea, β2-microglobulin, CRP, and weekly erythropoietin requirements. Reduced need for phosphate binders and anemia management may lower treatment-related costs.

Wearable electroencephalography (EEG) devices are miniaturized, portable, and wireless systems for long-term brain monitoring, demonstrating significant potential as accessible mild cognitive impairment (MCI) screening tools based on objective neurophysiological biomarkers. However, their performance in MCI detection remains unclear, and their translation to real-world applications faces several challenges. This study aimed to comprehensively evaluate wearable EEG for MCI detection, identify key characteristics that optimize classification performance and usability, and address gaps in effective design implementation. We conducted a systematic search across seven databases, screening 1562 records and analyzing 21 studies that examined 16 distinct wearable EEG devices for MCI detection. The results revealed considerable variation in classification accuracy (range: 46-95%). A system-level analysis of the entire wearable EEG system and data flow identified seven critical factors that optimize the trade-off between diagnostic performance, portability, and affordability: (1) moderate channel density; (2) frontal and parietal electrode placement; (3) elderly-friendly multi-domain cognitive tasks; (4) adaptive signal preprocessing; (5) multi-domain feature extraction; (6) ensemble classifiers; and (7) multimodal integration. Additionally, methodological considerations for future wearable EEG-based MCI detection research include: (1) standardize MCI diagnostic frameworks; (2) increase sample diversity; (3) optimizing device usability and technical specifications; (4) standardize recording protocols; (5) harmonizing data processing pipelines; (6) validate in real-world settings; (7) assess cost-effectiveness; and (8) implement comprehensive reporting guidelines. These insights enable further translational applications of wearable EEG-based MCI detection and provide a foundation for developing user-friendly systems that could transform early cognitive impairment screening in community and primary care settings.