Browse Articles

Evaluating triple inactivated vaccine-induced immunity from a large-scale study in feline population

Association between changes in self-esteem and smartphone dependency among Korean adolescents

Increasing smartphone ownership across all age groups has raised concerns about the rising risk of smartphone addiction, particularly during adolescence when self-esteem development is critical. This study aimed to investigate the association between changes in self-esteem and smartphone dependency over a five-year period using data from the Korean Children and Youth Panel Survey (2018–2022). A total of 1,971 participants from the middle school 1st grade cohort were analyzed. Self-esteem was measured annually using the Rosenberg Self-Esteem Scale, with a cutoff of 25 points classifying individuals into high and low self-esteem groups. Self-esteem was measured annually, and year-to-year change variables were created by comparing each participant’s score to that of the previous year. These lagged changes were used to assess their association with smartphone dependency measured at the same time point: (1) good → good, (2) good → poor, (3) poor → good, and (4) poor → poor. Smartphone dependency was assessed using the Smartphone Addiction Proneness Scale, with measurements taken at each annual survey point. The Generalized Estimating Equations model was used to analyze the association between self-esteem changes and smartphone dependency. The results indicated that both males and females with consistently low self-esteem or those whose self-esteem declined were more likely to exhibit smartphone dependency compared to those with consistently high self-esteem (females: good → poor: adjusted odds ratio (OR) 2.19, 95% confidence interval (CI) 1.78–2.71; poor → poor: adjusted OR 2.21, 95% CI 1.81–2.70; males: good → poor: adjusted OR 2.09, 95% CI 1.76–2.50; poor → poor: adjusted OR 2.04, 95% CI 1.70–2.48). These findings emphasize that stable self-esteem during adolescence may reduce the risk of smartphone dependency and related health issues.

Chimeras co-targeting antigens and FcγRIIb trigger degradation of extracellular soluble proteins and pathological aggregates

Effect of carbohydrate substrates on growth and enterotoxin gene expression in Bacillus cereus (pacificus)

Abstract Bacillus cereus sensu lato is a common contaminant of improperly stored food and human milk, capable of causing severe emetic and diarrheal diseases, particularly in infants and immunocompromised individuals. In this in vitro study, the effects of various temperatures and carbohydrate substrates on the growth of B. cereus ( pacificus ) strain ATCC 10987 and its expression of enterotoxin genes were explored. Bacterial growth at several temperatures and with six different carbohydrate substrates was evaluated. In cultures grown with various substrates at 37 °C, selected metabolites were analyzed using capillary electrophoresis and RNA-seq transcriptomic profiling was performed. At the same temperature, glucose, fructose, sucrose, and xylitol-enriched environments were preferable for the bacterial growth to lactose and galactose-enriched media. Lactate production markedly increased in bacterial cultures grown with glucose, fructose, or sucrose, accompanied by a drop in pH and increased substrate consumption. The lowest expression of non-hemolytic enterotoxin genes ( nhe ) was observed in glucose and lactose-enriched media, while downregulation of enterotoxin FM gene ( entFM ) expression was found in bacteria cultured with lactose. Other known enterotoxin genes, such as hemolysin BL ( hbl ) and cytotoxin K ( cytK ), were not expressed by this bacterial strain under any of the tested conditions. In conclusion, a lactose-rich environment slowed the growth of B. cereus ( pacificus ) ATCC 10987 and was associated with a downward trend in the expression of the enterotoxin genes nhe and entFM . These findings indicate that the presence of lactose, a dominant carbohydrate of human milk, may influence the pathogenic potential of B. cereus s. l.

Under renovation: Large-scale societal events induce shifts between moral ideologies

Existing research has revealed various cross-sectional inter-personal/group (e.g., regional) differences in moral traits; it has, however, paid less attention to cross-temporal intra-personal/group moral differences – simply, changes over time. Addressing the intellectual gap, the present research proposes that morality is redefined – renovated – in times when a society undergoes widespread social upheavals, in a manner that the incoming new ideology would better serve the society. Using longitudinal social media (Reddit) text data (N = 459,077,063) from Reddit over the 63 months since the last global great recession starting in late 2007, we report a partial, economy-focused demonstration of the hypothesis, wherein people associated their overall conception of morality more with support for authority and hierarchy and less with fairness and equality when the economic stress was increasing. In comparison, the public reversed the association to lean back on fairness and away from authority when the market was on the rise. Together, the findings offer insights into the communal nature of morality and call for caution that personal moral disposition may be malleable and fluctuating with the collective surroundings, thus cannot be adequately measured without first considering what the disposition means for the cultural-social unity at the moment.

MAASTY: a (dis)ordered copolymer for structural determination of human membrane proteins in native nanodiscs

Valproic acid boosts hair follicle stem cell resilience to oxygen-glucose deprivation through autophagy induction and AKT/mTOR suppression

Experiences of psychological mistreatment in older adults and promising practices: A scoping review protocol

Objective This project aims to gain a thoroughly understanding of the characteristics and experiences of psychological mistreatment among older adults, acknowledging the diversity within this population. It also seeks to identify clinical tools and practices for its detection and intervention. While there is extensive literature on mistreatment of older adults, specific studies focusing on psychological aspects and intersecting social and identity dimensions are scarce. The findings will provide valuable insights for policymakers and healthcare professionals, helping to shape interventions and policies aimed at countering mistreatment in the ageing population. Introduction Psychological mistreatment involves a range of behaviors, expressions, and gestures—or the lack of appropriate actions—that negatively impact an individual's health and dignity. Often subtle and difficult to detect, this type of mistreatment is prevalent and can coexist with other types of abuse. Examination of psychological mistreatment, shaped by various social and identity dimensions, is lacking in current research, particularly regarding how it is experienced by older adults. This scoping review seeks to map the current knowledge on psychological mistreatment of older adults, while highlighting gaps and future directions for research. Inclusion criteria This scoping review will encompass studies that explore the characteristics and experiences of psychological mistreatment among older adults, including their experiences and those of perpetrators and witnesses. It will also identify clinical tools and practices for the detection and intervention of psychological mistreatment in this population. Method A scoping review will be undertaken by a multidisciplinary team, examining studies from post-2010, sourced from both bibliographic databases and grey literature, available in English or French. Employing an intersectional framework, the review will use Gender-Based Analysis Plus (GBA+) to examine how different forms of discrimination intersect and shape experiences of mistreatment. That is, this approach will help explore how social and identity dimensions—including gender, age, sexual orientation, ethnicity, socioeconomic status, and health conditions—shape the experiences and manifestations of psychological mistreatment.

Differential gut transmission of IncP plasmid clades involving hypervirulent Klebsiella pneumoniae reveals plasmid-specific ecological adaptation

Advanced XRD peak broadening analysis of gallium-doped ZnO nanoparticles for crystallite size evaluation

Abstract This study investigates the most reliable approach for determining the crystallite size of nanoparticles through advanced X-ray diffraction (XRD) analysis. Gallium-doped zinc oxide nanoparticles (ZnO-NPs) were synthesized via a gelatin-assisted sol–gel method with Ga concentrations of 0%, 3%, 9%, and 15%. Structural characterization was performed using XRD, and crystallite size and lattice strain were evaluated through multiple analytical methods, including Scherrer’s equation, the Williamson–Hall (W–H) method, and both simple and modified Size–Strain Plot (SSP and MSSP) techniques. These complementary approaches enabled clear separation of size and strain effects, offering deeper insight into the microstructural evolution with increasing Ga content. The results revealed that higher Ga doping led to smaller crystallite sizes and increased lattice strain. Overall, the findings demonstrate that the MSSP method provides superior accuracy for nanoscale material characterization and highlight the significant influence of Ga incorporation on the structural properties of ZnO nanoparticles.

Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services

Objectives We developed an efficient Research-Ready Data Asset (RRDA) for the Welsh Longitudinal General Practice (WLGP) data within the Secure Anonymised Information Linkage Databank to standardise curation, enhance reproducibility, and facilitate research on primary care trends. Using this, we investigated primary care activity trends during and after the COVID-19 pandemic. Methods The RRDA involves cleaning, curation using GP-registration history, and transforming data into a structured, normalised format to support efficient large-scale queries. A comprehensive clinical code look-up was developed, incorporating official, local, and supplementary categories to enhance event classification. To enable patient-practice interaction analysis, a four-layer approach was developed to capture healthcare providers, access mode, interaction type, and event details. We assessed RRDA coverage, defined as the proportion of residents with shared primary care records, stratified by demographic and geographic factors, using longitudinal binomial Generalised Additive Mixed Models (GAMMs). We categorised GP events into key activity types and summarised averaged daily rates per month per 100,000 people (2000–2024), with trends analysed using negative binomial GAMMs. Results Curating 4.6 billion records for 5.1 million people (1990–2024) revealed significant improvements in data quality and completeness over time, with data retention increased from 40% to 94%, and patient inclusion from 43% to 98%. Use of SNOMED-CT and local codes increased after Read-V2 discontinuation in 2018, while invalid codes declined—reflecting evolving coding practices and improved data quality. WLGP RRDA coverage rose from 35% in 1990 to 86% in 2024, with regional variation but modest demographic differences. From 2000 to 2024, consultation rates rose by 1.9 times, with post-COVID-19 pandemic levels 8% above 2019. Prescription-only activity doubled with little variation associated with the pandemic. Vaccination rates spiked during the pandemic, and remain 1.8 times above pre-pandemic levels. Other less frequent activities were significantly disrupted during the COVID-19 pandemic but recovered to 2019 levels. Conclusions The WLGP RRDA improves the usability of primary care data, supporting timely, scalable analysis of healthcare delivery and system-level trends.

Observation of perfect absorption in hyperfine levels of molecular spins with hermitian subspaces

Abstract We investigate Perfect Absorption (PA) of radiation, in which incoming energy is entirely dissipated, in a system consisting of molecular spin centers coherently coupled to a planar microwave resonator operated at milliKelvin temperature and in the single photon regime. This platform allows us to fine tune the spin-photon coupling and to control the effective dissipation of the two subsystems towards the environment, thus giving us the opportunity to span over a wide space of parameters. Our system can be effectively described by a non-Hermitian Hamiltonian exhibiting distinct Hermitian subspaces. We experimentally show that these subspaces, linked to the presence of PA, can be engineered through the resonator-spin detuning, which controls the composition of the polaritons in terms of photon and spin content. In such a way, the required balance between the feeding and the loss rates is effectively recovered even in the absence of PT-symmetry. We show that Hermitian subspaces influence the overall aspect of coherent spectra of cavity QED systems and enlarge the possibility to explore non-Hermitian effects in open quantum systems. We finally discuss how our results can be potentially exploited for applications, in particular as single-photon switches and modulators.

A fractional model based on caputo derivative for tuberculosis transmission using real data from Kenya

FFO-based controller for 3-phase inverter to reduce power quality problems in PV-integrated microgrid system

Renewable Energy Sources (RESs) are extensively utilized in the energy sector to meet the present energy demand. As a result of the excessive use of allotted resources, converters must be used numerous times to synchronize the power grid, resulting in low-quality power. The uncertainties resulting from the integration of multiple energy sources were reflected by the distribution system. As microgrids (MGs) transition, the main Power Quality (PQ) issues like voltage unbalancing, voltage swell/sag, poor power factor, power transients appear and Total Harmonic Distortion (THD). Numerous researches studies were going on for reducing PQ issues as well as improving the system reliability under all circumstances, but those models have some impact for attaining a good power flow at the end users. In this study, a microgrid including PVs, wind turbines, and batteries was constructed as a Distributed Energy Resource (DER). To address the aforementioned PQ difficulties, a unique regulating system has been proposed to manage the power flows. The input of the proposed optimal controller was considered as dc voltage, coupling voltage and load current, based on these values, the controller generated a pulse signal of a three-phase inverter to decrease the power supply from PV and wind to maintain a constant frequency and power factor. The optimal problem of the proposed controller was solved through the use of Fennec Fox Optimization (FFO). The performance of the FFO-based controller was analyzed under various PQ issue conditions. The suggested controller’s functionality was verified by expanding the microgrid to create a large, three-phase structure. The realistic microgrid’s feasibility is verified by the inclusion of demand response, line impedance, and off-nominal scenarios. The proposed model offers 2.2% THD, 50 Hz, 0.8 power factor at a simple microgrid. The proposed model provides well-mitigated performance in any circumstance with a constant frequency and power factor.

Learning from imagined experiences via an endogenous prediction error

Abstract Experiences shape preferences. This is particularly the case when they deviate from our expectations and thus elicit prediction errors. Here we show that prediction errors do not only occur in response to actual events – they also arise endogenously in response to merely imagined events. Specifically, people repeatedly chose between different acquaintances and then imagined interacting with them. Our results show that they acquired a preference for acquaintances with whom they had pictured unexpectedly pleasant events. This learning can best be accounted for by a computational model that calculates prediction errors based on these rewarding experiences. Using functional MRI, we show that the prediction error is mediated via striatal activity. This activity, in turn, seems to update preferences about the individuals by updating their cortical representations. Our findings demonstrate that imaginings can violate our own expectations and thus drive endogenous learning by coopting a neural system that implements reinforcement learning.

Critical role of EEG signals in assessment of sex-specific insights in neurological diagnostics via machine learning approach

Emergency department visits for ambulatory care sensitive conditions by persons with Rheumatoid Arthritis: A population-based study

Purpose We estimated emergency department (ED) visit rates for Canadian-indicator Ambulatory Care Sensitive Conditions (ACSCs) by persons with rheumatoid arthritis (RA) relative to age- and sex-matched general population controls. Methods Cases were identified using a validated definition based on International Classification of Diseases codes (years 2002–2023). We identified visits in the National Ambulatory Care Reporting System (NACRS) where the most responsible diagnosis was for any ACSC (grand mal seizures, chronic lower respiratory diseases, asthma, diabetes, heart failure and pulmonary edema, hypertension, angina) and extracted visit acuity. Annual incidence rates were calculated within five years from the index date. The incidence rate ratio between RA and non-RA was estimated using a multivariable regression model, adjusting for age, sex, location of residence, and socioeconomic status. Results RA (n = 35,770 individuals) had higher ED visit rates for all ACSCs combined compared to Non-RA (n = 94,094 individuals) (crude IRR 1.26, 95% CI 1.22, 1.31), persisting after adjusting for confounders (adjusted IRR 1.30, 95% CI 1.25, 1.34). More than two-thirds of ED visits for ACSCs were triaged as “urgent” or higher severity. Over the study period, there was a 34% increase in the proportion of ED visits for an ACSC condition among those with RA. Conclusion RA cases had a 30% higher rate of avoidable ED visits in the first 5 years following diagnosis compared to non-RA. Improved ambulatory care access and care quality, inclusive of primary care and subspecialty care, is proposed to reduce the burden on the acute care system.

The promise of organ rejuvenation to overcome the shortage in organ transplantation

Abstract Organ shortage remains a major barrier in treating end-stage organ failure, with many patients dying while waiting or becoming medically unfit by the time an organ is offered. A substantial number of organs, particularly from older donors, remain unused due to concerns over age-related decline in quality. This review highlights emerging strategies to rejuvenate and optimize such organs by mitigating ischemia-reperfusion injury and reducing age-related immunogenicity. Advances in organ preservation, perfusion technologies, and novel therapies – including senotherapeutics, anti-inflammatory agents, and stem cell treatments – show promise in improving graft viability and bridging the gap between organ supply and demand.

Uterotropic response to the antidepressant fluoxetine (Prozac) is dependent on a functional serotonin transporter and circulating serotonin

Abstract Selective serotonin reuptake inhibitors (SSRI) are the most used antidepressants. However, they appear to pose a role as endocrine disrupting agents, particularly related to estrogen signaling. We sought to investigate the in vivo effects of fluoxetine, the most well-known SSRI, on uterine dynamic using uterotropic bioassays. In prepubertal mice, lack of increase in uterine weight in a three-day uterotrophic assay indicated fluoxetine does not directly bind estrogen receptor to elicit estrogenic effects. Conversely, in virgin, sexually mature mice and pseudopregnant mice, fluoxetine (2 mg/kg/d) elicited uterotropic response with increased uterine weight. Further, we observed increased uterine thickness, increased epithelial height, increased endometrial grands, and altered uterine gene expression (upregulated Alkp and downregulated Igfbp3) consistent with the uterotropic response and suggestive with modulation of estrogen signaling. In mice with genetic ablation of the serotonin transporter (Slc6a4 −/− , target site for SSRI) and depleted peripheral (nonneuronal) synthesis of serotonin (Tph1 −/− ), fluoxetine did not elicited uterotropic response. Therefore, the uterotropic response to fluoxetine is dependent on inhibition of serotonin transporter function and mediated by circulating serotonin.

Temporal social network modeling of mobile connectivity data with graph neural networks

Graph neural networks (GNNs) have emerged as a state-of-the-art data-driven tool for modeling connectivity data of graph-structured complex networks and integrating information of their nodes and edges in space and time. However, as of yet, the analysis of social networks using the time series of people’s mobile connectivity data has not been extensively investigated. In the present study, we investigate four recently proposed snapshot - based temporal GNNs in predicting the phone call and SMS activity between users of a mobile communication network. In addition, we develop a simple non - GNN baseline model using recently proposed EdgeBank method. Our analysis shows that the ROLAND temporal GNN outperforms the baseline model in most cases, whereas the other three GNNs perform on average worse than the baseline. The results show that GNN based approaches hold promise in the analysis of temporal social networks through mobile connectivity data. However, due to the relatively small performance margin between ROLAND and the baseline model, further research is required on specialized GNN architectures for temporal social network analysis.