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PubMed2026

Assessment of temporomandibular joint space changes after orthognathic surgery in skeletal malocclusion patients: a systematic review.

PURPOSE: To interpret postoperative changes in temporomandibular joint (TMJ) joint space dimensions and condylar position following orthognathic surgery in patients with skeletal malocclusions, and to determine whether reported alterations represent clinically meaningful displacement or physiological adaptive remodeling. MATERIALS AND METHODS: A comprehensive search of PubMed, SCOPUS, Web of Science, EBSCOhost, and Cochrane Library was performed to assess pre- and postoperative TMJ changes using three-dimensional imaging. Joint spaces including anterior (AJS), superior (SJS), and posterior (PJS) and condylar morphology were evaluated. Methodological quality was appraised using the Joanna Briggs Institute (JBI) checklist. Due to methodological and clinical heterogeneity, findings were synthesized narratively with attention to malocclusion type and surgical movement. RESULTS: A total of 16 studies consisting 628 patients undergoing BSSO, Le Fort I osteotomy, vertical ramus osteotomy, or bimaxillary surgery were included. Most studies reported minor, adaptive postoperative changes in AJS, SJS, and PJS. Class II patients showed more consistent increases in AJS/SJS, whereas Class III patients demonstrated variable posterior or anterior remodelling depending on surgical movement. Volumetric analyses revealed region-specific adaptations without significant condylar displacement. Postoperative temporomandibular disorder symptoms were infrequent, and no consistent evidence supported detrimental TMJ effects attributable to surgery. CONCLUSION: Postoperative TMJ joint space changes after orthognathic surgery primarily represent physiological adaptive remodeling rather than pathological condylar displacement, with reported variability driven by malocclusion type, surgical movement, fixation method, and imaging protocol. Recognizing these predictable patterns is essential to prevent overinterpretation of postoperative imaging and to improve clinical assessment through standardized three-dimensional and long-term evaluation strategies.

Humans↗
PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗
PubMed2026

Early infantile developmental and epileptic encephalopathy: clinical spectrum, diagnosis, outcomes, and evolving treatment strategies.

Early infantile developmental and epileptic encephalopathy (EIDEE) is among the most severe epilepsy syndromes, with onset before three months of age and an estimated incidence of approximately 10 per 100,000 live births. The 2022 International League Against Epilepsy classification unified the historically distinct Ohtahara syndrome and early myoclonic encephalopathy under a single diagnostic framework defined by frequent drug-resistant tonic and/or myoclonic seizures, an abnormal neurological examination, and an abnormal interictal electroencephalogram-most characteristically a burst-suppression pattern. This narrative review synthesizes the clinical, electrophysiological, neuroimaging, genetic, and therapeutic literature within the EIDEE framework. The clinical phenotype is characterized by central hypotonia, postnatal microcephaly, cortical visual impairment, and age-dependent syndromic evolution toward infantile epileptic spasms syndrome or Lennox-Gastaut syndrome in the majority of patients. Electroencephalography remains essential for syndromic classification, while systematic metabolic screening and early trio whole-exome or whole-genome sequencing are central to the etiologic workup, achieving diagnostic yields of 60-65%. The most commonly identified genetic causes include STXBP1, KCNQ2, and SCN2A variants. Outcomes are poor overall and strongly etiology-dependent: vitamin-responsive disorders carry a substantially more favorable prognosis, whereas mortality reaches 25% in genetic cohorts. Genotype-guided pharmacotherapy is now applicable to a clinically meaningful subset of patients, with sodium channel blockers, potassium channel openers, and emerging antisense oligonucleotide therapies representing important therapeutic advances. Gene therapy trials are underway but have encountered early safety signals, underscoring the vulnerability of this population. Critical unmet needs include earlier molecular diagnosis, precision therapies targeting developmental outcomes beyond seizure control, and prospective international registries to characterize the long-term natural history of EIDEE.

Humans↗
PubMed2026

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals↗
PubMed2026

Understanding psychosocial adjustment in military-to-civilian transition: A latent profile analysis of ex-serving Australian Defence Force members.

Military-to-civilian transition is a critical life stage that can expose veterans to elevated risks of psychological distress, social difficulties, and reduced wellbeing. Although psychosocial factors are central to successful reintegration, little is known about distinct patterns of needs among ex-serving Australian Defence Force (ADF) members. This study used latent profile analysis (LPA) to identify psychosocial needs profiles across five domains of the Military-Civilian Adjustment and Reintegration Measure (M-CARM) in a sample of 725 ex-serving ADF members. The optimal three-class solution identified: a Low Adjustment Need (LAN) group (20.7%) reporting minimal reintegration challenges; a Cultural Adjustment Need (CAN) group (42.9%) characterized by cultural adaptation difficulties, particularly beliefs about civilians and regimentation; and a Cultural and Psychological Need (CPN) group (36.4%) showing broader challenges across beliefs about civilians, purpose and connection, regimentation, and resentment and regret. The CAN group was more likely to be male, have lower educational attainment, and have no combat deployment history. The CPN group was similarly male dominated with lower education, and was additionally characterized by Navy service, unemployment or not being in the labor force, and medical discharge. Compared with the LAN group, both CAN and CPN groups reported higher levels of depression, anxiety, posttraumatic stress, and nightmare distress, as well as poorer quality of life and greater functional impairment. These findings highlight persistent reintegration challenges among veterans and support the need for stratified support models, ranging from psychoeducation to intensive multidisciplinary care, to better address diverse psychosocial needs of ex-serving ADF members.

Australian defense force↗
PubMed2026

Cloning of two Hsp70 genes and association analysis between SNP haplotypes and high temperature tolerance trait in red swamp crayfish (Procambarus clarkii).

Aquaculture is suffering the challenge from high temperature climate. Two Hsp70 genes, PcHsp70-1 and PcHsp70-2, as key genes involved in the high temperature tolerance of red swamp crayfish (Procambarus clarkii) were identified and cloned in this study. Their molecular features and expression patterns were characterized, revealing the distinct tissue-specific upregulation expression under high temperature stress (33 °C). Two SNPs, PcHsp70-1 (SNP258) and PcHsp70-2 (SNP555) were examined to associate with high temperature tolerance in three populations (n = 675). The genotypes of PcHsp70-1-SNP258 (GA) and PcHsp70-2-SNP555 (TT) were significantly associated with stronger high temperature tolerance. Notably, individuals carrying the haplotype of Hap I (GG + TT) showed a survival rate exceeding 70% under high temperature stress, whereas, the Hap VIII (AA + CT) showed it at 5.2%. RNA interference of PcHsp70-1 resulted in a significant decrease expression of the gene GSH-Px and its encoding protein (glutathione peroxidase) activity, and damage in intestinal tissue under high temperature stress. The transcriptome result revealed that PcHsp70-1 participates in regulation of the pathways related to cytoskeletal construction, immune response, apoptosis, and antioxidant defense. These findings indicate that PcHsp70 genes are crucial for the cellular stress response under high temperature stress. The developed Kompetitive Allele Specific PCR (KASP) markers provide valuable tools for the marker-assisted selection of high temperature tolerant crayfish varieties, supporting the sustainable development of aquaculture under the challenge of global warming.

Animals↗
PubMed2026

EZH1/2 inhibition selectively targets SMARCA4/2 co-deficient lung cancer cells by suppressing stemness and proliferation.

SMARCA4-deficient thoracic malignancies comprise biologically heterogeneous tumors, ranging from conventional non-small cell lung cancer with SMARCA4 alterations to thoracic SMARCA4-deficient undifferentiated tumor (SMARCA4-UT), an aggressive entity frequently associated with concomitant SMARCA2 loss. However, the extent to which SMARCA4-deficient lung cancer cell lines recapitulate SMARCA4-UT-like biology remains incompletely defined. Here, we characterized lung cancer cell lines across distinct SMARCA4 and SMARCA2 states and identified a subgroup with SMARCA4/2 co-deficiency that exhibited reduced expression of epithelial lineage markers and transcriptional similarity to SMARCA4-UT and other SWI/SNF-deficient malignancies. The EZH1/2 inhibitor HM97662 selectively suppressed growth in SMARCA4/2-deficient cells, with limited effects in SMARCA2-proficient cells. EZH1/2 inhibition broadly reduced H3K27me3 and induced derepression of PRC2 targets regardless of drug sensitivity. However, its biological effects were most pronounced in SMARCA4/2-deficient cells, where it promoted apoptosis, reduced stemness marker expression, attenuated the SMARCA4-UT-associated transcriptional signature, and suppressed proliferative and mTORC1-related programs. Chromatin accessibility analysis further revealed cell-line-specific patterns of accessibility loss, with reduced accessibility at stemness-associated transcription factor motif-enriched regions coupled with transcriptional repression of nearby genes in SMARCA4/2-deficient cells. These findings support dual EZH1/2 inhibition as a potential therapeutic vulnerability in SMARCA4/2-deficient, SMARCA4-UT-like lung cancer cells.

Humans↗
PubMed2026

Integrative modeling of the genome structure and dynamics in fission yeast.

Genome organization in the nucleus is highly structured and dynamic. Recent advances in genomic technology have enabled the measurement of genome-wide architecture and locus-specific motion, yielding contact maps and live-cell trajectories. However, these outcomes are derived from different modalities and are not directly comparable, with their quantitative integration being a key challenge. Here we establish a genome-wide live-cell imaging platform in fission yeast Schizosaccharomyces pombe, tracking 131 chromosomal loci, along with the spindle pole body (SPB) and nucleolus, to construct a quantitative map of locus dynamics. By integrating these dynamics with contact data through polymer modeling of Hi-C data, we build a physics-based "digital twin" of the S. pombe genome consistent with the spatiotemporal dynamics of interphase chromatin. We validate it against genome-wide mobility patterns and known architectural features, including centromere and telomere clustering. The model also identifies distinct dynamical regimes: centromere- and telomere-proximal loci relax within [Formula: see text]150 s, whereas the remaining loci relax within [Formula: see text]70 s. We measure semiperiodic dynamics of SPB motion, including a characteristic peak near 225 s and [Formula: see text] fluctuations. We use the model with SPB-directed forcing to show how these low-frequency components propagate through the genome to drive genome-wide chromatin displacements. Together, this predictive physics-based modeling framework integrates genome structure and dynamics to reveal how nuclear mechanical driving forces shape chromosome motion, linking mechanically driven chromatin responses to genome maintenance and regulation.

Schizosaccharomyces↗
PubMed2026

Lactylation-related immune-metabolic dysregulation defines prognostic and therapeutic stratification in lung adenocarcinoma.

BACKGROUND: Lactylation links lactate metabolism with inflammatory signaling and immune regulation in tumors. However, its cellular distribution and translational value in lung adenocarcinoma (LUAD) remain unclear. METHODS: Single-cell RNA-sequencing datasets GSE189357 and GSE171145 were integrated to characterize lactylation-related activity, intercellular communication, and malignant epithelial cell states in LUAD. Single-cell-derived lactylation-related differentially expressed genes were mapped to TCGA-LUAD and multiple GEO cohorts. Univariate Cox regression and machine learning algorithms were used to construct a lactylation-related prognostic signature (LRPS). The associations of LRPS with prognosis, immunotherapy response, drug sensitivity, genomic alterations, immune infiltration, and inflammation- and metabolism-related pathways were evaluated. KRT7 was further validated using virtual knockout analysis, spatial transcriptomics, and in vitro and in vivo experiments. RESULTS: lactylation-related transcriptional activity showed heterogeneous distribution across LUAD cell populations and was associated with altered cell-cell communication. In malignant epithelial cells, LRTS-high and LRTS-low states exhibited distinct metabolic, inflammatory, and tumor-related pathway activities. LRPS showed stable prognostic performance in TCGA-LUAD and multiple GEO cohorts and remained an independent prognostic factor. Low LRPS was associated with greater potential benefit from immunotherapy, whereas different LRPS groups displayed distinct drug sensitivity, genomic alteration, and immune microenvironment patterns. KRT7 was highly expressed in LUAD and associated with poor prognosis. KRT7 knockdown suppressed LUAD cell proliferation, migration, invasion, colony formation, and tumor growth in vivo. CONCLUSIONS: This study identifies lactylation-related immune-metabolic dysregulation as a clinically relevant feature of LUAD and develops a single-cell-guided LRPS for prognosis and therapeutic stratification. KRT7 emerged as an LRPS-related functional candidate with experimentally supported roles in malignant LUAD phenotypes.

Immunotherapy↗
PubMed2026

Characteristics and functions of a cell adhesion molecule PvCadN in Penaeus vannamei during WSSV infection.

Cell adhesion not only maintains the integrity of the organism, but also plays an important role in the immune system, which is involved in modulation in the interaction between host and virus. In this study, a novel cell adhesion molecule from Penaeus vannamei, designated as PvCadN, was investigated. It had the typical molecular characteristics of cadherin family, with multiple extracellular cadherin repeat domains, a transmembrane region, and a conserved β-catenin-binding motif. Pvcadn is expressed ubiquitously across all detected tissues, with the highest transcriptional level in gills. RNA interference-mediated silencing of pvcadn significantly impaired the adhesion ability of shrimp hemocytes. Upon WSSV infection, pvcadn showed a tissue-specific expression pattern, with upregulation in gills and downregulation in hemocytes. Knockdown of pvcadn markedly suppressed the transcription of WSSV immediate-early gene ie1 and replication of the viral genome in vivo, suggesting that PvCadN acted as a potential virus-associated molecule. Furthermore, it was found that PvCadN was regulated by Lvβ-catenin, a core molecule in the Wnt signaling pathway that functions in innate immunity, at the transcriptional and protein levels. Silencing of lvβ-catenin significantly downregulated pvcadn transcription, and Lvβ-catenin bound directly to the Cadherin C domain of PvCadN. In summary, the study revealed that PvCadN was a key cell adhesion molecule involved in WSSV infection, which was regulated by Lvβ-catenin. Our findings will provide fundamental data for further investigation into cadherin-mediated immune regulation in shrimp, and offer new insights for the prevention and control of WSSV.

Animals↗
PubMed2025

Barriers and Facilitators of Help-Seeking for LGBTQ+ Survivors of Sexual Violence: A Systematic Review.

People who identify as LGBTQ+ (Lesbian, Gay, Bisexual, Transgender, Queer, plus) are known to experience similar or higher levels of sexual violence compared to their heterosexual cisgender counterparts. However, sexual violence research has largely focused on heterosexual female survivors of male perpetrated crime. Thus, the unique support needs and help-seeking patterns of LGBTQ+ survivors are poorly understood. This review addresses this gap by systematically exploring literature on barriers and facilitators to help-seeking for LGBTQ+ survivors of sexual violence. Four databases (PsycINFO, CINAHL, MEDLINE, and Web of Science) were searched to identify relevant material, with 35 articles (30 qualitative, 1 quantitative, and 4 mixed-methods) meeting the inclusion criteria. Data were extracted and analyzed using a narrative synthesis. The topic was investigated almost exclusively cross-sectionally. Barriers included discrimination experiences, myths and stereotypes, feelings of shame and self-blame, and rejection of victim status. Additional barriers were reported by survivors who hold multiple minority identities, in particular LGBTQ+ people of color and sex workers. Facilitators to help-seeking included the intrinsic need to connect with others, social encouragement and empowerment, and positive disclosure experiences. The Power Threat Meaning framework provides insight into these findings by presenting help-seeking behaviors as adaptive responses to increase a sense of safety following a traumatic experience. The analyzed data indicate several implications for the development and improvement services to support LGBTQ+ survivors. They further serve to highlight the need for additional robust research, conducted with an intersectional lens, to explore the needs of sexual and gender minority survivors of sexual violence.

Humans↗
PubMed2026

From premature adrenarche to adult metabolic risk and hyperandrogenism: a systematic review and meta-analysis.

CONTEXT: Idiopathic premature adrenarche (IPA) has been associated with a higher risk of metabolic and reproductive dysfunction, but long-term/adult outcomes remain incompletely known. OBJECTIVE: To assess the relationship between IPA and metabolic syndrome, as well as polycystic ovarian syndrome, in premenarcheal adolescent and adult women. METHODS: We conducted a systematic review and meta-analysis of observational studies reporting outcomes in females with IPA after menarche. Databases were searched through February 2025. Primary outcomes included body mass index (BMI), insulin resistance markers, and clinical and biochemical markers of hyperandrogenism. Data were pooled using random-effects models. The GRADE approach was applied to assess the certainty of evidence. RESULTS: A total of 21 studies comprising 635 females with IPA and 307 age-matched controls were included. Compared to controls, IPA individuals showed significantly higher BMI (mean difference: 1.4; CI: 1.0-1.9), fasting insulin, and homeostasis model assessment of insulin resistance, indicating persistent insulin resistance. Markers of hyperandrogenism, including Ferriman-Gallwey score, dehydroepiandrosterone sulfate, and Free androgenic index, were also elevated. Secondary analyses revealed higher triglycerides, lower high-density lipoprotein, increased leptin, and greater carotid intima-media thickness, supporting an early pattern of cardiometabolic risk. GRADE assessment rated most outcomes as low certainty. CONCLUSION: Women with a history of IPA are at increased risk of long-term insulin resistance and hyperandrogenism, with early signs of adverse cardiometabolic profiles. These findings support the need for long-term monitoring in this population.

Humans↗
PubMed2026

The composition of the periostracum in the razor clam Sinonovacula constricta and the mantle's response to sulfide.

The razor clam Sinonovacula constricta inhabits sulfide-rich intertidal sediments and exhibits remarkable tolerance to this toxicant, yet the role of its periostracum in sulfide adaptation remains poorly understood. In this study, we investigated the composition and structure of the periostracum proteins, and the response of the mantle to sulfide stress. Scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed that the periostracum is approximately 10 μm thick and contains 1.43 wt% sulfur, and proteomic analysis further confirmed the presence of organic sulfur (Cys/Met-rich proteins), suggesting its involvement in sulfur deposition. Using LC-MS/MS, we identified 77 high-confidence proteins from the periostracum, which were classified into six functional categories: enzymes, framework proteins, immune-related proteins, calcium ion-related proteins, other proteins, and proteins with unknown functions. Phylogenetic analyses of representative proteins revealed bivalve-specific evolutionary patterns, with several proteins exclusively present in Bivalvia, such as Unknown protein 2 and 7, which possess signal peptides and low-complexity domains. For the sulfide exposure experiment, razor clams were subjected to three Na2S concentrations (0, 10, and 100 μM). qPCR analysis showed that, compared with the control group, Chitin-binding protein 3 and Tyrosinase were significantly upregulated in the mantle, peaking in the 100 μM group at 48 h (5677.84-fold and 157.20-fold, respectively), whereas Collagen and Cadherin 3 were generally suppressed. This study represents one of the most comprehensive proteomic profiles of the razor clam periostracum and highlights the mantle's potential role in sulfide tolerance, offering insights for sulfur-tolerant aquaculture breeding and bioremediation applications.

Animals↗
PubMed2026

Post-Breakup Instagram Surveillance: Attachment Style, Personality Traits, and Breakup Distress as Predictors.

The end of a romantic relationship is one of the most emotionally challenging life events. Social media platforms such as Instagram enable users to monitor an ex-partner, a behavior known as Interpersonal Electronic Surveillance (IES), which may complicate coping. This study examined associations with retrospectively reported IES on Instagram during the first 3 weeks post-breakup, focusing on attachment, personality, and breakup-related emotional distress. Previous studies suggest that higher anxious attachment and emotional distress are related to increased monitoring behaviors on Facebook. The present research extends this approach to Instagram, a popular platform among Generation Z, and additionally examines personality factors. Data from N = 232 participants (aged 18-27 years; 84 percent women), who had experienced a breakup within the past year and followed their ex-partner on Instagram, were collected using a cross-sectional online questionnaire. The survey included standardized measures and self-constructed items. Hierarchical regression analyses including breakup-related variables, mediation analyses, and independent-samples t-tests were conducted. Due to extremely low internal consistency, Agreeableness was excluded from inferential analyses. The analyses indicated that Extraversion was the only personality trait directly associated with increased IES. Attachment styles showed no direct associations after emotional distress was included in the model. Emotional distress emerged as the most consistent factor associated with IES, showing patterns consistent with indirect associations involving Neuroticism and anxious attachment, suggesting a central role of emotional distress in post-breakup surveillance behavior. These findings highlight digital monitoring as a potentially maladaptive coping strategy and underscore the importance of addressing social media use in post-breakup adjustment.

Humans↗
PubMed2026

Joint association of sedentary behaviour and physical activity with cardiovascular disease: a systematic review and meta-analysis.

This systematic review and meta-analysis of cohort studies aimed to synthesize existing evidence on the joint association of physical activity (PA) and sedentary behaviour (SB) with cardiovascular disease (CVD) risk among adults. We searched PubMed, EMBASE, and Cochrane for English studies published between January 2010 and February 2025 that examined the joint association of PA and SB (fatal and non-fatal) CVD among adults and pooled their results through meta-analyses using study-level data. Using findings from 17 studies, the pooled effect size for the lowest PA + highest SB group was 1.78 (95% CI: 1.59-2.00), suggesting increased risk for CVD compared with the reference group (i.e. highest PA + lowest SB). Compared with the same reference group, we found an increased risk for CVD in the lowest PA + lowest SB (HR = 1.25, 95% CI: 1.12-1.40) and the highest PA + highest SB (HR = 1.16, 95% CI: 1.06-1.27) groups. Subgroup analyses according to domains or types of PA and SB exposure, outcome measures, and exposure measurement method revealed a similar pattern. In conclusion, individuals with the lowest PA combined with the highest SB may experience an increased risk for CVD events compared with those with the highest PA and lowest SB. There was also an increased risk for individuals with a combination of either low PA + low SB and high PA + high SB, albeit to a lesser extent. Although substantial study-level heterogeneity exists, the results highlight the potential value of considering both behaviours jointly in relation to CVD risk.

Humans↗
PubMed2026

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans↗
PubMed2026

Symptom Networks and Core Symptoms in Patients with Solid Tumors Undergoing Chemotherapy: A Systematic Review.

OBJECTIVES: To summarize symptom network characteristics in patients with solid tumors undergoing chemotherapy and synthesize evidence on core symptoms, bridge symptoms, and temporal associations. METHODS: We systematically searched eight databases through October 2025 to identify studies that applied symptom network analysis to adults with solid tumors receiving chemotherapy. Eligible studies assessed symptoms using cross-sectional, longitudinal, or interventional designs. Two reviewers independently screened articles and extracted data on study characteristics, symptom assessment, and network outcomes. Methodological quality was assessed using the National Institutes of Health Study Quality Assessment Tool. RESULTS: Twenty-seven studies involving 13,452 participants were included, yielding 79 symptom networks. Fatigue was the most frequently identified core symptom (10/20, 50%), whereas sadness, lack of appetite, and nausea each occurred in 10% of studies, with variation across cancer types, treatment phases, and latent classes. Bridge symptoms included disturbed sleep, lack of appetite, and dry mouth (2/7, 28.6%). Studies evaluating temporal associations found that symptoms such as sadness, dyspnea, somnolence, and dry mouth predicted subsequent changes in appetite, distress, nausea, and other outcomes. Strength metrics showed acceptable stability (correlation stability coefficients: 0.28-0.83). CONCLUSIONS: Fatigue was frequently identified as a central symptom across studies, largely reflecting evidence from breast cancer studies. Core symptoms varied across cancer types, treatment phases, and latent classes, suggesting heterogeneity. IMPLICATIONS FOR NURSING PRACTICE: These findings highlight the importance of considering relationships among symptoms in clinical care. Focusing on key symptoms such as fatigue, while tailoring management strategies to cancer-specific symptom patterns, may support more effective symptom management.

Humans↗
PubMed2026

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma↗