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The impact of internet use on the subjective well-being of older adults: The mediating role of mental health

Background As internet use rises among older adults, the internet has become a vital tool for maintaining social ties and enhancing life satisfaction. Prior research suggests that online engagement may be linked to subjective well-being (SWB) by offering emotional support and opportunities for participation. However, the psychological pathways underlying this association—such as psychological anxiety, social loneliness, and goal deficiency (reduced sense of purpose)—remain underexplored. To address this gap, this study examines how these psychological factors are associated with internet use and older adults’ SWB in a cross-sectional context. Methods Drawing on cross-sectional data from the 2021 Chinese General Social Survey (CGSS), this study analyzed a sample of 825 Chinese adults aged 60 years and above. A structural equation modeling (SEM) approach was used to examine the associations among internet use, three psychological variables (psychological anxiety, social loneliness, and goal deficiency), and SWB. Control variables included age, gender, education level, and place of residence. Results The direct association between internet use and SWB was non-significant. However, internet use was associated with lower psychological anxiety, lower social loneliness, and lower goal deficiency, and the overall indirect association with SWB was positive. Among the mediators, psychological anxiety accounted for the largest share of the indirect association, goal deficiency contributed modestly, and the loneliness pathway was not statistically significant. The total association between internet use and SWB remained positive when indirect paths were considered. Conclusion The evidence indicates that, among older adults, digital engagement is associated with SWB chiefly via mental-health pathways—particularly through its associations with lower anxiety and reduced goal deficiency—rather than through a direct association. These findings suggest that policy and practice may complement access and digital-literacy initiatives with supports that reduce anxiety and strengthen purpose and competence (e.g., step-by-step onboarding, simplified interfaces, peer mentoring) as well as goal-oriented uses such as health self-management and community participation. Since the loneliness-mediated route was not supported, programs should emphasize emotionally meaningful online connections and relationship quality rather than merely increasing contact volume.

Too much social media gives AI chatbots ‘brain rot’

Signal inference in financial stock return correlations through phase-ordering kinetics in the quenched regime

Financial stock return correlations have been analyzed through the lens of random matrix theory to differentiate the underlying signal from spurious correlations. The continuous spectrum of the eigenvalue distribution derived from the stock return correlation matrix typically aligns with a rescaled Marchenko-Pastur distribution, indicating no detectable signal. In this study, we introduce a stochastic field theory model to establish a detection threshold for signals present in the limit where the eigenvalues are within the continuous spectrum, which itself closely resembles that of a random matrix where standard methods such as principal component analysis fail to infer a signal. We then apply our method to Standard & Poor’s 500 financial stocks’ return correlations, detecting the presence of a signal in the largest eigenvalues within the continuous spectrum.

Changing the narrative: A qualitative study on the impact of media portrayals on people with schizophrenia

The stigma surrounding schizophrenia, heavily shaped by media portrayals, significantly affects individuals’ lives, often delaying help-seeking and treatment. These negative representations can lead to social rejection, isolation, and worsened mental health outcomes. This qualitative study delves into the lived experiences of individuals diagnosed with schizophrenia, exploring how public perceptions of mental disorders, particularly schizophrenia, influence their health journeys and daily lives. Rooted in Gadamer’s hermeneutic phenomenology, the study involved in-depth interviews with 10 participants diagnosed with schizophrenia. Data were analyzed using ATLAS.ti software to uncover key themes in their experiences. Four themes emerged. Media Portrayal highlighted how negative depictions of schizophrenia, such as violence, reinforce societal stigma. This leads to Self-Stigma, where people diagnosed with schizophrenia internalize these views, hindering help-seeking. Social Support emphasized the importance of family and friends, although stigma sometimes complicates these relationships. Healthcare Provider Relationships pointed to frustration with frequent staff changes, undermining trust in care. Participants suggested Professional Training in empathy and a Shift in Media Representation to improve perceptions of schizophrenia and Mental Health Literacy. Media representations and societal stigma significantly impact the health-illness process for individuals with schizophrenia. More accurate portrayals in the media, combined with greater awareness and empathy from healthcare providers, could reduce stigma and improve treatment engagement and trust.

Powerful new antibiotic that can kill superbugs discovered in soil bacteria

Compensatory mechanisms to maintain glenohumeral joint stability in rotator cuff tears of differing severity during activities of daily living: A musculoskeletal model simulation study

Rotator cuff tears decrease glenohumeral joint stability; however, surrounding uninjured muscles could compensate for the reduced function of injured muscles to maintain joint stability. This study set out to analyze compensatory mechanisms that could maintain glenohumeral joint stability following rotator cuff tears of varying severity during normal daily life, using a musculoskeletal model simulation of rotator cuff tears. Fifteen healthy males performed 6 activities including shoulder flexion and abduction, contralateral shoulder reaching, head reaching, and lifting a 1 kg object placed on low and high shelves. Glenohumeral joint stability and scapulohumeral muscle forces were estimated using an intact model and 7 models with complex injuries to the supraspinatus, infraspinatus, and subscapularis muscles. Joint stability was quantified using the positional relationship between joint reaction force and the glenoid. Relationships between changes in glenohumeral joint stability and scapulohumeral muscle forces, in the different models, were analyzed. Glenohumeral joint stability decreased in all activities according to rotator cuff tear severity. Decreased glenohumeral joint stability was more pronounced with lower arm elevation angles and greater severity of rotator cuff tear. At this moment, increase in teres minor and long head of the biceps were observed in the rotator cuff tear models compared with the Intact model. Teres minor force increased in the isolated supraspinatus model during all activities, and long head of biceps forces increased in Flexion, Abduction, and Head reaching activities. These increases in muscle forces were significantly correlated with joint instability, indicating their contribution to stabilization of the glenohumeral joint. In conclusion, in rotator cuff tear models of differing severity, increased uninjured muscle forces compensated for decreased glenohumeral joint movement. Compensatory mechanisms differed according to the pattern and severity of rotator cuff tears, as well as activity type.

Pan-immune inflammation value: A novel biomarker for cataract

Background Inflammation significantly contributes to cataract formation; Pan-immune inflammation value (PIV) is an emerging marker that may reflect systemic inflammation. This study aimed to explore the connection between PIV and cataract formation. Methods We analyzed 8,235 participants from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2008. PIV was log-transformed, and weighted logistic regression, restricted cubic splines (RCS), subgroup, and sensitivity analyses were performed to evaluate associations. The receiver operating characteristic (ROC) curves were used to assess predictive performance. Results Cataract prevalence was 6.6%. Higher ln-PIV was positively associated with cataract prevalence [OR=1.35, 95%CI: 1.08–1.69, P = 0.015]. The association was linear, consistent across subgroups, and robust in sensitivity analyses. The ROC analysis indicated that PIV had better predictive ability for cataract than other inflammatory indices. Conclusion We found that higher PIV levels were positively associated with cataract prevalence, which highlights the value of inflammatory markers in assessing cataract development and provides new ideas for the clinical detection of cataracts.

Electro-induced C-H/S-H cross-coupling for the functionalization/macrocyclization of cysteine-containing peptides

An integrated approach for rare disease detection and classification in Spanish pediatric medical reports

Abstract Rare disease detection and classification is one of the most significant challenges in the application of Natural Language Processing techniques to the analysis and extraction of information from biomedical texts. In this paper, we present a novel research focused on the detection and classification of rare diseases in clinical notes extracted from a cohort of pediatric patients from the Community of Madrid in Spain. From a set of collected and anonymized medical records, we propose a semi-supervised, keyphrase-based system to perform an initial detection of mentions of rare diseases, which is then validated and refined by experts to build a consolidated dataset concerning a subset of different rare diseases. Based on this dataset, we carry out a series of experiments for rare disease classification using both a semi-supervised technique and state-of-the-art supervised systems based on both discriminative and generative models. A detailed case analysis provides insights on which systems excel in specific scenarios and why. The validated dataset contains a total of 1900 annotated texts containing mentions to rare diseases. Experiments on this dataset show that the best supervised models improve the performance of the semi-supervised system by more than 10% (78.74% vs 67.37% micro-average F-Measure), individually enhancing the classification of a significant number of diseases in the dataset. State-of-the-art supervised systems are able to offer promising results on the detection and classification of rare diseases in clinical texts, even in cases for which the amount of annotated information is low. On the other hand, semi-supervised models present interesting capabilities for dealing with limited information and data in the field.

Decoding the redox behaviour of copper in Ullmann-type coupling reactions

Publisher Correction: The bandgap-detuned excitation regime in photonic-crystal resonators

Soil quality dynamics in natural pine forests lands integrating fuzzy-AHP and prediction based on random forest algorithms

Publisher Correction: Wearable device-based health equivalence of different physical activity intensities against mortality, cardiometabolic disease, and cancer

Development and validation of a type 2 diabetes mellitus prediction tool using a large Japanese regional insurance claims database

Hotly debated dinosaur is not a tiny T. rex after all

Condensation-dependent interactome of a chromatin remodeler underlies tumor suppressor activities

Abstract Chromatin remodelers are vital for cellular functions like transcription by modulating nucleosome accessibility. Although biological condensates regulate these processes, the contribution of chromatin remodelers to condensation mechanisms remains poorly understood. Here, we examine the role of the E1321 frameshift mutation in CHD1 , a chromatin remodeler, which is often targeted in cancers. This mutation truncates CHD1’s C-terminus, leading to an oncogenic transcriptome and promoting tumorigenesis. This is due to the loss of an intrinsically disordered region (IDR) crucial for forming CHD1 condensates. These condensates are facilitated by the presence of H3K4me3-modified nucleosomes and RNA, guided to active promoters to regulate gene expression. Furthermore, CHD1 condensates contain long noncoding RNA and histone-modifying proteins, revealing an integral role for CHD1 condensates in epigenetic regulation. Among these components, MLL mutations frequently co-occur with CHD1 mutations in various cancers, suggesting a shared pathway in cancer development. These findings underscore the importance of chromatin remodeler condensation as a regulatory hub in various cellular processes and tumor suppression.

Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran

‘Teenage T. rex’ fossil is actually a different species

Discovery of obesity genes through cross-ancestry analysis

Effects on nonverbal numerical acuity performance after a single-session transient random noise stimulation over the intraparietal sulcus or dorsolateral prefrontal cortex

Abstract We investigated the effects of cognitive training with transcranial random noise stimulation (tRNS) applied to the intraparietal sulcus (IPS) or dorsolateral prefrontal cortex (DLPFC) on improving a multidirectional number line estimation task. We predicted that a single session of tRNS targeting IPS would enhance accuracy without affecting response speed, while a single session of tRNS targeting the DLPFC would improve response speed without influencing accuracy. Through a repeated measure within-between-subject design, 39 healthy participants (M = 21.39, SD = 2.64) were divided into either an IPS (n = 20) or DLPFC (n = 19) bilateral stimulation group, whereby in a counterbalanced order, the participants received a sham session and a session of tRNS separated by 1 week. Stimulation was paired with training tasks focused on the approximate number system. Participants were measured by their speed and accuracy on a multidirectional number line estimation task. Findings partially support predictions, tRNS to the IPS improved accuracy but not speed on the number line estimation task after a single session. Contrary to expectations on tRNS to the DLPFC, no effects were observed. Findings contribute to our understanding of using a single session tRNS as a tool in interventions aimed at maths low achievers.