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Mapping SBiP1 protein-protein interactions in Symbiodinium microadriaticum CassKB8 using the Yeast Two-Hybrid assay and structural prediction
BiP chaperones are central regulators of protein folding, endoplasmic reticulum homeostasis, and stress response across eukaryotes, but their client networks remain largely uncharacterized in Symbiodiniaceae. Here, we performed an initial yeast two-hybrid screening using a spliced-leader-based cDNA library to explore the interactome and regulatory dynamics of the Symbiodiniaceae BiP homolog, SBiP1, from Symbiodinium microadriaticum CassKB8. Using this approach, we identified eight candidate interactors with functions in translation, redox balance, RNA processing, and photosynthesis. AlphaFold2 structural modeling and Foldseek similarity analysis supported the plausibility of these candidates as BiP clients, revealing shared structural features such as globular folds and exposed hydrophobic or basic surfaces. Notably, two of the eight candidates, POX18 and TARBP1 were recovered in multiple independent clones, and even unannotated candidates displayed BiP-compatible surfaces. Gene expression analysis by RT-qPCR revealed dynamic transcriptional regulation of SBiP1 , HSP70 , and POX18 over an 18-day growth time course. All three genes peaked between days 6 and 12, suggesting coordination with intrinsic cellular cycles. SBiP1 expression was not significantly affected by light availability while HSP70 showed a modest but statistically significant increase following cycloheximide treatment, indicating transcript stabilization. In contrast, SBiP1 and POX18 expressions under the latter condition remained stable, suggesting their regulation may occur post-transcriptionally. Together, our findings highlight SBiP1 as a central player in ER proteostasis, bridging multiple cellular pathways essential for stress resilience. This work provides the first structural and functional map of a BiP-centered interaction network in a photosynthetic dinoflagellate, contributing to our molecular understanding of stress adaptation in these microorganisms.
Efficacy of radial and focused shockwave therapy for tendinopathy: a systematic review and meta-analysis
Malaria-diabetes comorbidity is linked to higher parasitaemia and enhanced IgG response to malaria vaccine candidate antigens
Background The coexistence of type 2 diabetes mellitus (T2DM) and malaria presents a significant public health concern, particularly in malaria-endemic regions. T2DM’s immunomodulatory effects may influence immune responses to infectious diseases, but its impact on naturally acquired antibodies against malaria vaccine candidate antigens remains unclear. This study investigated how T2DM-malaria comorbidity affects IgG responses to malaria vaccine candidate antigens (GLURP-R2, GLURP-RO, MSP3, MSP1, AMA-1 and CSP) among individuals in the Central Region of Ghana. Methods This hospital-based case-control study recruited a total of 144 participants 40 with diabetes, 25 with both diabetes and malaria, 41 with malaria only, and 38 controls (hospital staff without malaria or diabetes matched by age and sex). Malaria status and parasitaemia were confirmed using microscopy, blood glucose levels were measured via glucometer, and antibody levels were quantified using indirect ELISA. Data were analyzed using parametric and non-parametric statistical methods. Results Patients with malaria-diabetes comorbidity exhibited significantly higher parasitaemia levels compared to those with malaria alone [1702 (IQR1 = 926.50, IQR3 = 4102) vs. 932 (IQR1 = 722.50, IQR3 = 1321), p = 0.02]. Relative to the negative control group, IgG responses to GLURP-R2 were markedly elevated, showing a 1.60-fold increase in the comorbidity group (β = 0.47 [95% CI: 0.10–0.83], p = 0.01) and a 1.43-fold increase in the malaria-only group (β = 0.36 [95% CI: 0.04–0.69], p = 0.03). Among individuals with comorbidity, IgG levels to GLURP-R0 and MSP1 were also 1.43-fold higher (β = 0.36 [95% CI: 0.03–0.68], p = 0.03) and 1.42-fold (β = 0.35 [95% CI: 0.09–0.61], p < 0.05), respectively. Conversely, antibody responses to MSP3, AMA1, and CSP did not differ significantly between the study groups (p > 0.05). In the multivariate regression model adjusted for age and sex, individuals with comorbidity exhibited significantly elevated IgG responses, showing a 1.38-fold increase to GLURP-R0 (β = 0.32 [95% CI: 0.07–0.59], p = 0.027) and a 1.34-fold higher response to MSP1 (β = 0.29 [95% CI: 0.02–0.47], p = 0.048), relative to the malaria-only group. Conclusion These findings suggest that diabetes may enhance malaria parasite multiplication while also augmenting IgG antibody responses to malaria vaccine candidate antigens in individuals with comorbidity. Further research is required to elucidate the mechanisms by which diabetes influences antibody responses to malaria infection and its potential implications for malaria vaccine development.
Correction: Coupling and coordination between the digital economy and carbon emissions in the Yangtze River Economic Belt
Fast decision mechanism for ternary tree partitioning in VVC intra coding
In Versatile Video Coding (VVC), the partition patterns for coding units (CUs) have significant impact on the encoding efficiency. Determining the optimal CU partition is particularly time-consuming due to the calculation and comparison of rate-distortion costs for all possible partition patterns, especially during the ternary tree (TT) partitioning in intra coding. In this paper, a fast decision mechanism is proposed for TT partitioning based on image feature analysis to skip the complex rate-distortion calculation. Firstly, the correlation between the image structural features and the TT partition patterns is investigated based on experimental analysis and the most relevant features are selected for the subsequent prediction of optimal TT partition patterns. Secondly, we devise an efficient scheme for representing and extracting the selected features, further optimizing the extraction process to minimize computational complexity. Comprehensive datasets for partition pattern prediction are constructed based on these refined features. Finally, these datasets serve as the foundation for training and optimizing a predictive model, which is designed to achieve an optimal trade-off between prediction accuracy and model complexity. The predictive model is seamlessly incorporated into the VVC Test Model (VTM), facilitating efficient feature extraction prior to the Rate-Distortion Optimization (RDO) process for intra prediction and optimal partition pattern selection. By leveraging the prediction results, the model effectively determines whether TT partitioning can be bypassed, thereby streamlining the decision-making process and enhancing overall coding efficiency. Experimental results demonstrate that in comprehensive performance evaluations of time-saving metrics and Bjøntegaard Delta Bit Rate (BDBR), the proposed mechanism significantly outperforms existing lightweight neural network algorithms. Our decision mechanism effectively preserves coding quality while substantially accelerating the video coding process.
Echo-coexisting reference channel processing for target detection in passive bistatic radar
Factors influencing the caregiver burden for family caregivers of people with moderate-to-severe dementia: A structural equation modeling analysis
Background Dementia poses an increasingly serious public health challenge worldwide, particularly in China, where home-based care remains the primary form of management. Family caregivers of older adults with moderate-to-severe dementia often experience a substantial caregiving burden, which can adversely affect both their own well-being and that of the patients. Objective This study aimed to examine the level of caregiver burden among family caregivers of older adults with moderate-to-severe dementia and to explore the relationships between patient activities of daily living (ADL), quality of life (QoL), depression severity, caregiver QoL, depression severity, and caregiver burden. Methods A cross-sectional study in 22 tertiary general hospitals in Shanxi Province, China, involved 529 dyads of older adults with moderate-to-severe dementia and their family caregivers. Caregivers completed the Zarit Burden Interview, the Patient Health Questionnaire-9, and the World Health Organization Quality of Life–Brief Version. Older adults completed the Patient Health Questionnaire-9, the Activity of Daily Living Scale, and the Quality of Life in Alzheimer’s Disease scale. Structural equation modeling evaluated relationships among patient ADL, QoL, depression severity, caregiver QoL, depression severity, and caregiver burden. Results Patient QoL, ADL, and caregiver QoL had direct negative effects on caregiver burden, whereas patient and caregiver depression severity had direct positive effects on caregiver burden. Meanwhile, caregiver QoL partially mediated the relationships between patient QoL, depression severity, ADL, caregiver depression severity, and caregiver burden. Conclusion The results indicate that higher patient QoL, better patient ability in ADL, higher caregiver QoL, and lower levels of depressive severity in both patients and caregivers are associated with reduced caregiver burden. Healthcare professionals should implement family-centered, comprehensive interventions to alleviate caregiver burden.
Quantum secure image encryption using hybrid QTRNG and QPRNG
Multi-omics analysis reveals STING activation mediates NLRP3-related pyroptosis and exacerbates myocardial ischemia-reperfusion injury
Background Myocardial ischemia-reperfusion injury (I/R) significantly exacerbates cardiomyocyte damage post-recanalization therapy in acute myocardial infarction. Pyroptosis and the NLRP3 inflammasome are crucial in I/R, yet the precise mechanism remains unclear. Materials and Methods Transcriptomics, proteomics, and single-cell transcriptomics were employed to examine cellular subtype changes and pyroptosis-associated gene regulation in I/R. Differential pyroptosis-related genes were identified from transcriptomics data and validated with proteomics. Single-cell RNA sequencing assessed pyroptosis levels and intercellular communication. Mouse myocardial I/R and human cardiomyocyte hypoxia/reoxygenation (H/R) models were used to explore STING overexpression/silencing effects on NLRP3 inflammasome activation, oxidative stress, and cellular injury. Results Pyroptosis-related genes were significantly dysregulated, implicating multiple inflammatory pathways. Single-cell analyses revealed increased granulocytes, macrophage infiltration, cardiomyocyte injury, and enhanced pyroptosis scores post-I/R. Cardiomyocytes, endothelial cells, and fibroblasts exhibited increased pyroptosis and inflammatory cell-cell interactions. Animal studies indicated significant declines in cardiac function and increased oxidative stress and inflammation post-I/R. STING activation (SR717) worsened cardiac function, enhanced ROS production, and elevated myocardial injury markers; STING inhibition (H151) markedly mitigated these effects. Correspondingly, the cGAS-STING pathway and NLRP3 inflammasome factors were significantly upregulated post-I/R, exacerbated by STING agonists and alleviated by STING inhibitors. Cellular studies confirmed that STING overexpression intensified oxidative stress and pyroptosis, effects reversed by STING knockdown and blocked by NLRP3 inhibitor MCC950. Conclusion STING activation contributes to oxidative stress and NLRP3 inflammasome–associated pyroptosis during I/R. Targeting the STING-NLRP3 axis may represent a potential strategy to reduce myocardial injury after ischemia-reperfusion.
Novel histological observation method using the scattered light of unstained collagen sections
Data-driven predictive modeling for massive intraoperative blood loss during living donor liver transplantation: Integrating machine learning techniques
Background Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating better predictive models for risk stratification. As traditional models often fail to capture the complex, non-linear patterns underlying bleeding risk, this study aimed to develop data-driven machine learning models for predicting massive IBL during living donor LT (LDLT) using preoperative factors. Methods Two hundred ninety consecutive LDLT cases from a prospective database were analyzed. Logistic regression models were built using 73 preoperative demographic and laboratory variables to predict massive IBL (≥ 80 mL/kg). The dataset was randomly split (70% training, 30% testing). The model was trained and validated through three-fold cross-validation, with backward stepwise feature selection iterated 100 times across unique random splits. The final model, based on a high stability index, was evaluated using the area under the curve (AUC). Results Massive IBL was observed in 141 patients (48.6%). In standard logistic regression, significant differences were found in 42 of 73 factors between groups stratified by massive IBL, however, substantial multicollinearity limited interpretability. In the feature selection across 100 iterations, the data-driven model achieved an average AUC of 0.840 in the validation and 0.738 in the test datasets. The final model, based on 11 selected features with a high stability index, achieved an AUC of 0.844. An easy-to-use online risk calculator for massive IBL was developed and is available at: https://tai1wakiya.shinyapps.io/ldlt_bleeding_ml/ . Conclusions Our findings highlight the potential of machine learning in capturing complex risk factor interactions for predicting massive IBL in LDLT.
Effects of applied magnetic fields on the performance of magnetoplasmadynamic thrusters
Measuring and understanding labor exploitation on a sample of workers in the Costa Rican fishing industry
Due to the challenging nature of surveying exploited workers, scholars are often limited in their ability to standardize data collection efforts. Using two samples of survey data from workers in the Costa Rican fishing industry, we compare latent classes of exploitative labor between a subset of individuals surveyed through a proportional probability sample (PPS) and Vincent-link-tracing sampling (VLTS). Results suggest there are some differences between latent classes across the differently sampled groups, with those in the PPS sample being more defined by severe forms of exploitation. Despite these differences, latent classes largely looked similar, with each group having a more highly exploited class and a more minimally exploited class. This study suggests that sampling techniques may affect the broader understanding of the issue, but most of the variation of exploitative experiences may lie in the characteristics of specific contexts or occupations.
Prevalence of complementary and alternative medicine use among osteoarthritis patients in a developing country and their level of satisfaction
A qualitative exploration of video-based motor action observation perceptions in patients with chronic low back pain and asymptomatic participants: An interpretative phenomenological analysis
Background Video-based action observation (AO) of exercise/motor-action content is increasingly delivered via social media. This expands reach and ecological validity but may shape motor simulation, perceived safety, and engagement. How people with chronic low back pain (CLBP) interpret and intend to use such videos remains underexplored. Methods We conducted an interpretative phenomenological analysis (IPA) of semi-structured interviews with purposively sampled adults (n = 20; 10 CLBP, 10 asymptomatic). Interviews probed perceptions of exercise/motor-action AO videos drawn from common platforms. Analysis followed IPA procedures with iterative coding, constant comparison, and team reflexivity, and is reported according to COREQ. Results Three interrelated themes were identified: (1) Emotional & motivational impact: CLBP participants frequently appraised bending, load and fast tempo as threatening and described protective avoidance rules. Motivation was present in both groups when videos felt safe and adaptable; (2) Self-assessment of physical capacity: Perceived competence increased when videos provided graded options and explicit safety cues. Anticipated task demand decreased with appropriate pacing/tempo, egocentric viewpoint, and credible modeling; (3) Cognitive movement assessment: Viewers attended to posture, tempo, breathing and error-avoidance cues. Action comprehension faltered when instructions were dense/fast or goals were unclear. Judgments about delivery (goal clarity, safety cues, pacing, viewpoint, modeling fidelity) shaped internal rehearsal and willingness to attempt. Conclusions Individuals with and without CLBP perceive social-media–delivered exercise AO as useful when videos are tailored (graded options, clear safety messaging, appropriate pacing/viewpoint) and contextualized to pain-related concerns and digital literacy. These insights inform clinically oriented AO exercise-video libraries and implementation strategies (e.g., curated playlists, level-tagging, therapist-mediated briefing) to enhance acceptability and adherence in CLBP rehabilitation.
A novel photo-induced synthesis of carboxymethyl chitosan-silver nanocomposite: preparation, characterization and antibacterial efficacy of cotton finished fabrics
Systematic review of lung function assessment among youth and young adults e-cigarette users: Current tools and emerging methods
Introduction This review focuses on the need to identify the lung function assessment tools used for young EC users. The objectives are to examine the current and emerging methods used in assessing lung function among young EC users, besides identifying the alterations in lung function following EC exposure measured by those tools. Methodology This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 flow checklist. Six databases (Web of Science, PubMed, Scopus, Taylor & Francis, SAGE, and ScienceDirect) were searched in April 2025 for original articles published between 2016 and 2025. Quality appraisal of the eligible articles was conducted using the Joanna Briggs Institute (JBI) Critical Appraisal Tools. Findings were synthesized using Narrative analysis. Results A total of 7 studies were included. Spirometry was used in all included studies; however, it is unable to detect subclinical lung alterations, as observed through ventilation-perfusion (V/Q) MRI and fractional exhaled nitric oxide (FeNO). Acute exposure to EC results in a decrease of FEV₁, FVC, PEF, and MEF₇₅ spirometric parameters, as well as reducing FeNO levels, while concurrently increasing exhaled breath temperature (EBT). Besides, an increase in V/Q mismatch and heterogeneity in ventilation is observed, with a reduction in perfusion heterogeneity. Chronic EC exposure causes a reduction in FEV 1 , PEF, FEV 1 /FVC, and FEF 25–75% , besides an increment of Carboxyhaemoglobin (HbCO) level. The assessment of the lung function post-EVALI in association with EC cessation revealed lung function improvement and increased diffusing capacity of the lung for carbon monoxide (DLCO). Conclusions Spirometry remains the first-line tool for assessing the lung function of young EC users; however, it often misses early lung dysfunction. Emerging methods (FeNO, DLCO, EBT, MRI, HbCO) increasingly complement this limitation. Tailoring multimodal assessment to exposure context, alongside screening and monitoring programs, may assist in early disease detection and prevent long-term respiratory effects.
“One Health” perspective on the prevalence of Listeria monocytogenes and its antibiotic resistance profiles in South Africa: a comprehensive systematic review and meta-analysis
Simultaneous triclosan degradation and nitrate reduction by a UV/Sulfite/Phenol process based on sulfite radical mechanism: dechlorination, mineralization, and bioassessment
Industrial development has increased the introduction of pollutants such as nitrate (NO₃⁻) and triclosan (TCS) into the environment, both of which pose significant environmental and health risks. The experiments were carried out in a 150 ml glass tube (photoreactor) equipped with a UV lamp (mercury vapor lamp (16 W) with a quartz cover operated at a controlled temperature (21 ± 2 °C), with an ultraviolet (UV) lamp and 2 mg/L dissolved oxygen. In the UV/sulfite process, the weak S-S bonds of sulfite, when exposed to UV radiation, produce SO3 •- radicals. The study assessed the effects of sulfite concentration, reaction time, pH, and pollutant levels on treatment efficiency. At pH 3 and 7 with 50 mg/L concentrations of TCS and NO₃ ⁻ , TCS removal efficiencies were 23% and 100%, while NO₃ ⁻ removal was 18% and 68%, respectively. Increasing sulfite from 50 to 200 mg/L improved results, achieving 85% NO₃⁻ and 100% TCS reduction in 90 minutes. SMP outperformed UV and sulfite-only treatments, achieving 68% and 100% reductions after 180 minutes. The process also led to partial nitrate-to-nitrite conversion, which decreased over time. In the SMP process, the values of Kobs (min-1) were 0.017, 0.031 for NO3- and TCS and EEM (kWh m-3), 0.3 and 0.2, respectively.Chemical oxygen demand (COD) and total organic carbon (TOC) reduced notably, and toxicity levels dropped dramatically. Given its high efficiency, low energy consumption, and minimal environmental impact, the SMP process shows significant potential for practical scale-up in wastewater treatment applications, especially in industries dealing with persistent organic pollutants and high nitrate concentrations.