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Bipolar complex fuzzy set (BCFS) theory is a newly developed framework for addressing real-world decision-making (DM) problems that involve ambiguous, uncertain, and dual-valued information. The theory is based on bipolar fuzzy set (BFS) and complex fuzzy set (CFS), which enable the association of both positive membership degree (PMD) and negative membership degrees (Ne-MD) within the unit square of the complex plane. This paper considers the use of Aczel-Alsina (AA) operational laws in the BCFS setting to introduce two new aggregation operators (AOs): bipolar complex fuzzy Choquet integral Aczel-Alsina averaging (BCFCIAAA) and order averaging (BCFCIAAOA). These operators are studied analytically in terms of essential properties, such as idempotency, monotonicity, and boundedness. To demonstrate the superiority of the proposed approach, we develop a hybrid DM model that combines the decision-making trial and evaluation laboratory (DEMATEL) method with the Choquet integral (CI) within the BCFS framework. This model is applied to a real-world case study focused on prioritizing critical factors influencing the integration of image processing and big data analytics (IP-BDA) into software development. The causal effects indicate that feature extraction, automation and efficiency, as well as object detection, are critical causal factors, whereas image enhancement, security, and segmentation are dependent effects. These findings offer actionable insights for decision-makers (DMKs), emphasizing the importance of intelligent feature handling and scalable analytics workflows in designing adaptive and high-performance software systems.

Background The adverse effects of loneliness and of poor perceived social support on physical health and mortality are established, but no systematic synthesis is available of their relationship with the outcomes of mental health problems over time. In this systematic review, we aim to examine the evidence on whether loneliness and closely related concepts predict poor outcomes among adults with mental health problems. Methods We searched six databases and reference lists for longitudinal quantitative studies that examined the relationship between baseline measures of loneliness and poor perceived social support and outcomes at follow up. Thirty-four eligible papers were retrieved. Due to heterogeneity among included studies in clinical populations, predictor measures and outcomes, a narrative synthesis was conducted. Results We found substantial evidence from prospective studies that people with depression who perceive their social support as poorer have worse outcomes in terms of symptoms, recovery and social functioning. Loneliness has been investigated much less than perceived social support, but there is some evidence that greater loneliness predicts poorer depression outcome. There is also some preliminary evidence of associations between perceived social support and outcomes in schizophrenia, bipolar disorder and anxiety disorders. Conclusions Loneliness and quality of social support in depression are potential targets for development and testing of interventions, while for other conditions further evidence is needed regarding relationships with outcomes.

PurposeSubjective and objective social isolation are important factors contributing to both physical and mental health problems, including premature mortality and depression. This systematic review evaluated the current evidence for the effectiveness of interventions to improve subjective and/or objective social isolation for people with mental health problems. Primary outcomes of interest included loneliness, perceived social support, and objective social isolation.MethodsThree databases were searched for relevant randomised controlled trials (RCTs). Studies were included if they evaluated interventions for people with mental health problems and had objective and/or subjective social isolation (including loneliness) as their primary outcome, or as one of a number of outcomes with none identified as primary.ResultsIn total, 30 RCTs met the review’s inclusion criteria: 15 included subjective social isolation as an outcome and 11 included objective social isolation. The remaining four evaluated both outcomes. There was considerable variability between trials in types of intervention and participants’ characteristics. Significant results were reported in a minority of trials, but methodological limitations, such as small sample size, restricted conclusions from many studies.ConclusionThe evidence is not yet strong enough to make specific recommendations for practice. Preliminary evidence suggests that promising interventions may include cognitive modification for subjective social isolation, and interventions with mixed strategies and supported socialisation for objective social isolation. We highlight the need for more thorough, theory-driven intervention development and for well-designed and adequately powered RCTs.

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression at the posttranscriptional level. The dysregulation of miRNAs has been linked to a series of diseases, including various types of cancer. Since their discovery in the circulation of cancer patients, there has been a steady increase in the study of circulating miRNAs as stable, non-invasive biomarkers. However, the origin and function of circulating miRNAs has not been systematically elucidated. In this review, we summarize the discovery of circulating miRNAs and their potential as biomarkers. We further emphasize their possible origin and function. Finally, we discuss the application and existing questions surrounding circulating miRNAs in cancer diagnostics. Although several challenges remain to be concerned, circulating miRNAs could be useful, non-invasive biomarkers for cancer diagnosis.

In this study, the effects of surface roughness and pore characteristics on fatigue lives of laser powder bed fusion (LPBF) Ti–6Al–4V parts were investigated. The 197 fatigue bars were printed using the same laser power but with varied scanning speeds. These actions led to variations in the geometries of microscale pores, and such variations were characterized using micro-computed tomography. To generate differences in surface roughness in fatigue bars, half of the samples were grit-blasted and the other half were machined. Fatigue behaviors were analyzed with respect to surface roughness and statistics of the pores. For the grit-blasted samples, the contour laser scan in the LPBF strategy led to a pore-depletion zone isolating surface and internal pores with different features. For the machined samples, where surface pores resemble internal pores, the fatigue life was highly correlated with the average pore size and projected pore area in the plane perpendicular to the stress direction. Finally, a machine learning model using a drop-out neural network (DONN) was employed to establish a link between surface and pore features to the fatigue data ( logN ), and good prediction accuracy was demonstrated. Besides predicting fatigue lives, the DONN can also estimate the prediction uncertainty.

PurposeLoneliness is an important issue for mental health service users. However, it has not been a particularly prominent focus of recent mental health research. This paper aimed to explore the severity of loneliness among people leaving mental health community crisis services, and to identify factors associated with loneliness.MethodsA total of 399 participants experiencing mental health crises recruited for a research trial from community crisis services were included in this cross-sectional study. They completed the eight-item measure of the University of California at Los Angeles Loneliness Scale and a set of instruments assessing socio-demographic, psychosocial, and psychiatric variables.ResultsSeverity of loneliness was high among people leaving community crisis services. Longer years since first contact with mental health services (2–10 years, coefficient = 1.83, 95% CI 0.49–3.16; more than 10 years, coefficient = 1.91, 95% CI 0.46–3.36) and more severe affective symptoms (coefficient = 0.32, 95% CI 0.23–0.40) were associated with greater loneliness, whereas bigger social network size (coefficient = − 0.56, 95% CI − 0.76 to − 0.36) and greater social capital (coefficient = − 0.16, 95% CI − 0.31 to − 0.003) were associated with less severe loneliness.ConclusionsThis paper supports a view that people experiencing mental health crises often report relatively severe loneliness, and that loneliness tends to become more severe during the course of illness. A greater awareness of loneliness among mental health professionals may be beneficial. Loneliness is a potential focus of the development of interventions to improve the lives and outcomes of people with significant mental health problems.

Sarcoidosis has been considered to be associated with many autoimmune diseases (ADs), but the cause-and-effect relationship between these two diseases has not been fully explored. Therefore, the objective of this study is to explore the possible genetic association between sarcoidosis and ADs. We conducted a bidirectional Mendelian randomization (MR) study using genetic variants associated with ADs and sarcoidosis (4,041 cases and 371,255 controls) from the FinnGen study. The ADs dataset comprised 96,150 cases and 281,127 controls, encompassing 44 distinct types of autoimmune-related diseases. Subsequently, we identified seven diseases within the ADs dataset with a case size exceeding 3,500 and performed subgroup analyses on these specific diseases. The MR evidence supported the causal association of genetic predictors of ADs with an increased risk of sarcoidosis (OR = 1.79, 95% CI = 1.59 to 2.02,   = 1.01 × 10 ), and no reverse causation (OR = 1.05, 95% CI 0.99 to 1.12, = 9.88 × 10 ). Furthermore, subgroup analyses indicated that genetic predictors of type 1 diabetes mellitus (T1DM), celiac disease, and inflammatory bowel disease (IBD) were causally linked to an elevated risk of sarcoidosis (All < 6.25 × 10 ). Conversely, genetic predictors of sarcoidosis showed causal associations with a higher risk of type 1 diabetes mellitus ( < 6.25 × 10 ). The present study established a positive causal relationship between genetic predictors of ADs (e.g. T1DM, celiac disease, and IBD) and the risk of sarcoidosis, with no evidence of reverse causation.

PurposeIt is well known that loneliness can worsen physical and mental health outcomes, but there is a dearth of research on the impact of loneliness in populations receiving mental healthcare. This study aimed to investigate cross-sectional correlates of loneliness among such patients and longitudinal risk for acute general hospitalisations.MethodA retrospective observational study was conducted on the data from patients aged 18 + receiving assessment/care at a large mental healthcare provider in South London. Recorded loneliness status was ascertained among active patients on the index date, 30th Jun 2012. Acute general hospitalisation (emergency/elective) outcomes were obtained until 31st Mar 2018. Length of stay was modelled using Poisson regression models and time-to hospitalisation and time-to mortality were modelled using Cox proportional hazards regression models.ResultsThe data from 26,745 patients were analysed. The prevalence of patients with recorded loneliness was 16.4% at the index date. In the fully adjusted model, patients with recorded loneliness had higher hazards of emergency (HR 1.15, 95% CI 1.09–1.22) and elective (1.05, 1.01–1.12) hospitalisation than patients who were not recorded as lonely, and a longer duration of both emergency (IRR 1.06, 95% CI 1.05–1.07) and elective (1.02, 1.01–1.03) general hospitalisations. There was no association between loneliness and mortality. Correlates of loneliness included having an eating disorder (OR 1.67, 95% CI 1.29–2.25) and serious mental illnesses (OR 1.44, 1.29–1.62).ConclusionLoneliness in patients receiving mental healthcare is associated with higher use of general hospital services. Increased attention to the physical healthcare of this patient group is therefore warranted.

Macrophages are increasingly recognized as crucial therapeutic targets in the treatment of diverse pathological conditions. While considerable research has focused on macrophage-related mechanisms within Traditional Chinese Medicine (TCM), there remains a notable absence of comprehensive quantitative analyses in this field. This study aims to examine the evolutionary trajectory of macrophage-related research in TCM from 2003 to 2023, providing insights to guide future investigative directions. We searched for articles published between 2003 and 2023 from the Web of Science Core Collection (WoSCC) database and analyzed them using R software, VOSviewer and CiteSpace. A total of 1,823 documents were obtained through the search. The results indicated that the number of publications between 2003 and 2023 exhibited an upward trend, with the majority of these documents originating from Chinese academic institutions and authored by Chinese scholars. This observation suggests a potential correlation with the growing prominence of Chinese medicine within China. Macrophage polarizations, a prominent focus in the study of macrophages, has also assumed an increasingly significant role in the domain of macrophages in TCM-related disciplines. The publication of these results also suggests that targeting macrophages in TCM for the treatment of some diseases is very promising, especially in ulcerative colitis, tumor-related diseases, and some liver diseases. This study provides a more comprehensive analysis of the current status and significant areas of research in the field of macrophage research in TCM, offering valuable insights for prospective research endeavors. Macrophage-related studies in TCM have garnered increasing attention from global scholars from researchers worldwide, and are expected to become a hotspot for targeting macrophages to develop new drugs to treat diseases in the future. This study comprehensively analyzes the current status and hotspots of macrophages in Chinese medicine, which can provide valuable references for future research.

Background Most of theevidence has focused on examining the influence of moderate-to-vigorous intensity physical activity on mental health, but he role of light intensity physical activity (LIPA) is less understood. The purpose of this systematic review was to assess the relationship between time spent in LIPA and mental ill health across the lifespan. Methods Data were obtained from online databases (Medline, Embase, Scopus, PsychInfo and CINAHL). The search and collection of eligible studies was conducted up to May 28, 2020. Observational studies conducted in the general population and reporting on the association between LIPA (1.6–2.9 metabolic equivalents; either self-reported or device-based measured) and mental ill health were included. Results Twenty-two studies were included in the review (16 cross-sectional and 6 longitudinal). In older adults (≥ 65 years) and adults (18–64 years), the evidence examining the relationship between LIPA and depressive symptoms is mixed. Data on anxiety, psychological distress and overall mental health are scarce, and results are inconclusive. There is no evidence suggesting favorable associations between LIPA and anxiety in college students. Finally, very limited data was found in adolescents (11–17 years) ( n  = 2 studies) and children (6–10 years) ( n  = 2 studies), but the evidence suggests that LIPA does not influence mental health outcomes in these age groups. Conclusions This review provided mostly cross-sectional evidence indicating that LIPA may not be associated with mental health outcomes across age groups. Future research efforts employing prospective research designs are warranted to better understand the role of LIPA on mental ill health across age groups.