Search Results (2,720)

Background: Severe asthma exacerbations (SAEs) significantly contribute to asthma-related morbidity, mortality, and healthcare burden. Despite therapeutic advances, a subset of patients remains exacerbation-prone. This review aims to summarize current evidence on risk factors, phenotypes, and biomarkers associated with SAEs, and explore personalized strategies for their acute management. Methods: We conducted a comprehensive literature review focusing on clinical, inflammatory, and environmental drivers of SAE. Special attention was given to Type 2 (T2) biomarkers—blood eosinophil count (BEC) and fractional exhaled nitric oxide (FeNO)—as tools for phenotyping and treatment guidance. Emerging evidence on the use of biologics during exacerbations was also analyzed. Results: SAEs are heterogeneous in etiology and inflammatory profile. Respiratory infections, allergen exposure, obesity, and comorbidities increase exacerbation risk. T2-high SAEs respond well to corticosteroids and biologics, whereas T2-low SAEs show limited treatment benefit. BEC and FeNO reliably predict exacerbation risk and corticosteroid responsiveness. Recent case reports suggest potential roles for anti-IL-5 and anti-thymic stromal lymphopoietin (TSLP) biologics in acute care. Conclusions: Biomarker-guided management of SAEs may enhance therapeutic precision and avoid overtreatment. Integrating phenotypic (observable characteristics) and endotypic (biological markers) assessment into acute care could improve patient outcomes and optimize resource use. Prospective trials are needed to confirm these approaches. Full article

Melanoma is the deadliest form of skin cancer, characterized by high metastatic potential and intrinsic heterogeneity. In addition to genetic mutations such as BRAF^V600E^ and NRAS, lipid metabolic reprogramming has emerged as a critical factor in tumor progression and therapy resistance. Lipid metabolism supports melanoma cell survival, phenotypic switching, immune evasion, and resistance to targeted therapies and immunotherapy, while also modulating susceptibility to ferroptosis. This review summarizes current knowledge on lipid dysregulation in melanoma, highlighting alterations in fatty acid synthesis, desaturation, uptake, storage, and oxidation, as well as changes in phospholipids, sphingolipids, cholesterol, and bioactive lipid mediators. These lipid pathways are tightly regulated by oncogenic signaling networks, including MAPK and PI3K–AKT–mTOR pathways, and are influenced by tumor microenvironmental stressors such as hypoxia and nutrient limitation. Advances in lipidomics technologies, particularly mass spectrometry-based approaches, have enabled comprehensive profiling of lipid alterations at bulk, spatial, and single-cell levels, offering new opportunities for biomarker discovery and therapeutic stratification. Targeting lipid metabolic vulnerabilities represents a promising strategy to improve melanoma diagnosis, prognosis, and treatment efficacy. Full article

Candidozyma auris (formerly Candida auris) is an emerging multidrug-resistant fungal pathogen with confirmed cases in over 30 countries. Although whole-genome sequencing (WGS) analysis defined distinct clades during characterization of underlying genetic mechanism behind multidrug resistance, Clade II remains under-evaluated. In this study, a three-level comparative genomic strategy (Global, Clade, Phenotype) was employed by integration of unbiased genome-wide comparative SNP screening (GATK v4.1.9.0), targeted BLAST profiling (BLAST+ v2.17.0), and in silico protein analysis (ColabFold v1.5.5; DynaMut2 v2.0) for systematic evaluation of mechanisms of antifungal resistance in thirty-nine Clade II C. auris clinical isolates and fourteen reference strains. Global and clade-level analyses confirmed that all the clinical isolates belong to Clade II, according to phylogenetic clustering and mating type locus (MTL) conservation. At the phenotype level, a distinct subclade of fluconazole-resistant mutants was identified to have a heterogenous network of mutations in seven key enzymes associated with cell membrane dynamics and the metabolic stress response. Among these, four core mutations (TAC1B, CAN2, NIC96, PMA1) were confirmed as functional drivers based on strict criteria during multitier in silico protein analysis: cross-species conservation, surface exposure, active site proximity, thermodynamic stability, and protein interface interaction. On the other hand, three high-level fluconazole-resistant clinical isolates (≥128 μg/mL) that lacked these functional drivers were subjected to comprehensive subtractive genomic profiling analysis. The absence of coding mutations in validated resistance drivers, yeast orthologs, and convergent variants suggests that there is an alternative novel non-coding or regulatory mechanism behind fluconazole resistance. These findings highlight Clade II’s evolutionary divergence into two distinct trajectories towards the development of a high level of fluconazole resistance: canonical protein alteration versus regulatory modulation. Full article

Non-communicable diseases (NCDs) impose an overwhelming burden on global health systems. Prevailing healthcare for NCDs remains largely hospital-centered, episodic, and reactive, rendering them poorly suited to address the long-term, heterogeneous, and multifactorial nature of NCDs. Rapid advances in digital technologies, artificial intelligence (AI), and precision medicine have catalyzed the development of an integrative framework for digital-intelligent precision health management, characterized by the functional integration of data, models, and decision support. It is best understood as an integrated health management framework operating across three interdependent dimensions. First, it is grounded in multidimensional health-related phenotyping, enabled by continuous digital sensing, wearable and ambient devices, and multi-omics profiling, which together allow for comprehensive, longitudinal characterization of individual health states in real-world settings. Second, it leverages intelligent risk warning and early diagnosis, whereby multimodal data are fused using advanced machine learning algorithms to generate dynamic risk prediction, detect early pathological deviations, and refine disease stratification beyond conventional static models. Third, it culminates in health management under intelligent decision-making, integrating digital twins and AI health agents to support personalized intervention planning, virtual simulation, adaptive optimization, and closed-loop management across the disease continuum. Framed in this way, digital-intelligent precision health management enables a fundamental shift from passive care towards proactive, anticipatory, and individual-centered health management. This Perspectives article synthesizes recent literature from the past three years, critically examines translational and ethical challenges, and outlines future directions for embedding this framework within population health and healthcare systems. Full article

Artificial intelligence (AI) has rapidly evolved from an experimental tool in spine research to a multi-domain framework that has significantly influenced imaging analysis, surgical decision-making, and individualized outcome prediction. Recent advances have expanded beyond isolated applications, enabling automated image interpretation, patient-specific risk stratification, discovery of qualitative phenotypes, and integration of heterogeneous clinical and biomechanical data. These developments signal a shift toward more comprehensive, context-aware analytic systems capable of supporting complex clinical workflows in spine care. Despite these gains, widespread clinical adoption remains limited. High internal performance metrics do not consistently translate into reliable generalizability, interpretability, or real-world clinical readiness. Persistent challenges, which include dataset heterogeneity, transportability across institutions, alignment with clinical decision-making processes, and appropriate validation strategies, continue to constrain widespread implementation. In this perspective, we synthesize post-2019 advances in spine AI across key application domains: imaging analysis, predictive modeling and decision support, qualitative phenotyping, and emerging hybrid and language-based frameworks through a unified clinical-readiness lens. By examining how methodological progress aligns with clinical context, validation rigor, and interpretability, we highlight both the transformative potential of AI in spine research and the critical steps required for responsible, effective integration into routine clinical practice. Full article

Neonatal Diabetes Mellitus (NDM) is a rare, heterogeneous monogenic disorder typically presenting within the first six months of life. Unlike type 1 or type 2 diabetes, NDM is caused by single-gene mutations that disrupt pancreatic β-cell function or development. With the advent of next-generation sequencing, the genetic spectrum of NDM has expanded significantly, necessitating a shift from symptomatic management to precision medicine. This narrative review summarizes the genetic basis and pathogenic mechanisms of NDM, categorizing them into three major pathways: (1) ATP-sensitive potassium (K_ATP) channelopathies (e.g., ABCC8, KCNJ11), where gain-of-function mutations inhibit insulin secretion; (2) Transcription factor defects (e.g., GLIS3, PAX6, GATA6), which impair pancreatic development and often present with syndromic features; and (3) Endoplasmic reticulum (ER) stress-mediated β-cell apoptosis, exemplified by WFS1 mutations. Furthermore, we highlight the clinical complexity of these mutations, including the “biphasic phenotype” observed in ABCC8 and HNF1A variants. Understanding these molecular mechanisms is critical for clinical decision-making. We discuss the transformative impact of genetic diagnosis in treatment, particularly the successful transition from insulin to oral sulfonylureas in patients with K_ATP channel mutations, and emphasize the importance of early genetic testing to optimize glycemic control and prevent complications. Full article

Background: Postpartum haemorrhage (PPH) remains the leading cause of maternal mortality globally. Women with inherited or unexplained bleeding disorders such as von Willebrand disease (VWD), factor XI deficiency (FXI), platelet function disorders, or bleeding disorder of unknown cause (BDUC) face a higher risk. While tranexamic acid (TXA) is routinely used in obstetric care, its specific efficacy and safety in these populations remain unclear. Methods: A systematic review and meta-analysis followed PRISMA 2020 guidelines (PROSPERO: CRD420251082349). Databases searched included PubMed, Scopus, Web of Science, and Dimensions. Studies evaluating TXA for PPH prevention or treatment in women with bleeding disorders were included. Six cohort studies (2016–2024) involving 213 deliveries met the criteria. Three contributed to a meta-analysis on primary PPH; the other three were synthesised narratively. Results: TXA use was associated with a 56% reduction in primary PPH risk (risk ratio 0.44; 95% CI: 0.27–0.70; p = 0.0007), with no observed heterogeneity (I² = 0%). Because contributing cohorts were phenotypically heterogeneous (BDUC, FXI, mixed), the pooled effect reflects an average across disorders rather than disorder-specific efficacy. TXA also appeared to reduce secondary and severe PPH in some cohorts. However, bleeding occurred in 26–36% of high-risk deliveries despite prophylaxis. No maternal deaths or thromboembolic events were reported in 136 TXA-exposed cases. Attribution was complicated by concurrent use of desmopressin and platelet transfusions. Most studies had moderate to severe bias. Conclusions: TXA significantly lowers the risk of primary PPH in women with bleeding disorders and appears safe. Despite this, residual bleeding underscores the need for trials to optimise TXA use alongside disease-specific strategies. However, this conclusion is derived from only six observational studies with heterogeneous patient populations and co-interventions. The evidence remains preliminary and should be interpreted cautiously. TXA should be considered as part of a multimodal postpartum haemorrhage management algorithm rather than a stand-alone therapy. Full article

Background/Objectives: Diagnosing ASD becomes more difficult with age, especially in girls. This study explores developmental factors and diagnostic tools that affect ASD diagnoses after age six. The study also integrates the neurodiversity paradigm to evaluate how diagnostic tools like the ADOS-2 and Social Attribution Test (SAT) capture the heterogeneous presentation of ASD across genders. Methods: This retrospective study analyzed data from 91 children (73 boys, 18 girls) assessed for ASD between ages 6–18. Multivariate Generalized Linear Models (GLMs) were employed to identify independent predictors of diagnosis, controlling for age, gender, and language difficulties. Results: Notable gender differences emerged: boys showed more atypical development and restricted interests, while girls showed higher sensory sensitivity. Multivariate analysis confirmed that Social Affect (SA), age of initial concern, and the absence of structural language difficulties significantly impacted diagnosis likelihood. Conclusions: This study emphasizes the need for gender-sensitive criteria and implicit measures like the SAT to identify “masking” phenotypes. It emphasizes current tool limitations, the risk of diagnostic overshadowing, and the importance of longitudinal studies with comprehensive assessments to better capture ASD diversity, especially in social and language skills. Full article

Aim: To report on the clinical and genetic spectrum of retinopathy associated with CDHR1 variants in a Hungarian cohort. Methods: A retrospective cohort study was conducted at a single tertiary care referral center. The study enrolled nine patients harboring biallelic variants in the CDHR1 gene. Detailed clinical history, multimodal imaging, electroretinography, and molecular genetics are presented. Results: We identified four CDHR1 variants predicted to cause loss-of-function and five phenotypes (cone dystrophy, central areolar choroidal dystrophy, cone-rod dystrophy, rod-cone dystrophy, and late-onset macular dystrophy). The most frequent variant was the synonymous CDHR1 c.783G>A (p.Pro261=) variant (10/18 alleles, 55.6%). A novel splice acceptor site variant, CDHR1 c.349-1G>A, and a novel intronic variant, CDHR1 c.1168-10A>G, were also detected. Fundus examination revealed macular atrophy with or without peripheral retinal changes. Full-field electroretinography, available in seven patients, demonstrated decreased light-adapted and extinguished dark-adapted responses in both the rod-cone dystrophy group and patients with macular involvement. OCT imaging indicated ellipsoid zone disruption with foveal sparing in two out of nine patients and severe retinal damage in rod-cone dystrophy cases. Conclusions: The predominant clinical manifestations of cone dystrophy, cone-rod dystrophy, and macular dystrophy in the Hungarian patient cohort showed heterogeneity, with a rod-cone dystrophy phenotype observed in five of nine cases (55.6%). The natural history of CDHR1-associated retinopathy typically follows a slow progression, providing a therapeutic window, which makes the disease a candidate for gene therapy. Full article

Background/Objectives: Anti-mGluR1 encephalitis is a rare form of autoimmune encephalitis predominantly manifesting as acute/subacute cerebellar ataxia. We describe a newly diagnosed case series from our center and conduct a comprehensive review of reported cases worldwide to compare clinical manifestations, treatment options, and outcomes. Methods: We consecutively identified 11 patients at Peking Union Medical College Hospital, and additionally extracted clinical data from 42 previously published cases identified via PubMed and Google Scholar (search updated to 1 August 2025). Demographics, phenotypes, laboratory findings, imaging, treatment, and outcomes were systematically summarized. This pooled review was not prospectively registered, and extracted data from 21 published articles were analyzed alongside our 11 newly diagnosed cases. Results: The integrated cohort comprised 53 patients with anti-mGluR1 encephalitis, including 29 males and 24 females, with patients reported from Asia (n = 18), North America (n = 11), and Europe (n = 24). The median age at onset was 50 years (IQR 29.5–58.5; range 3–81), with North American patients presenting later than their Asian and European counterparts (median 60 vs. 48 and 45 years, respectively; all p < 0.05). Disease onset was subacute in most cases (58.7%). Comorbid tumors were present in nine patients, most commonly lymphomas. Clinical phenotypes were classified as pure cerebellar syndrome (n = 31), cerebellar ataxia with encephalitic features (n = 20), and non-cerebellar presentations (n = 2). Baseline severity differed across phenotypes (χ² = 35.7, p < 0.001). Regional variability in severity was observed but did not reach significance. CSF analyses revealed pleocytosis in 59% (23/39), elevated protein in 31.3% (5/16), and oligoclonal bands in 52.2% (12/23). MRI abnormalities were detected in 34.7% (17/49) of patients, with 21.9% (7/32) developing cerebellar atrophy on follow-up. Therapeutic strategies varied significantly across regions (p = 0.041), with Asian cohorts more frequently receiving long-term immunosuppression, European cohorts favoring combined regimens, and North American cases relying predominantly on first-line therapies. Overall, 65.9% (29/44) of patients clinically improved, 13.6% (6/44) relapsed and 20.5% (9/44) remained unaffected. Conclusions: Anti-mGluR1 encephalitis presents with significant clinical heterogeneity, ranging from cerebellar-dominant ataxia to neuropsychiatric or non-cerebellar phenotypes, and demonstrates differences in reported age of onset, disease severity, and therapeutic approaches across publication regions. Our findings underscore the importance of early recognition, sustained immunotherapy, and international collaboration to establish standardized, evidence-based management for this rare but disabling disorder. Full article

Pediatric obesity is an increasingly prevalent, chronic, and multifactorial disease. Achieving successful and sustained weight reduction with current interventions remains challenging due to significant heterogeneity in treatment response. This review summarizes current evidence describing variability in outcomes across lifestyle, pharmacologic, and metabolic/bariatric surgery interventions in children and adolescents, and examines key biological, metabolic, behavioral, environmental, and psychosocial factors that influence response. In adults, recent findings on energy balance obesity phenotypes (characterized by abnormal satiation, abnormal postprandial satiety, abnormal hedonic eating, and reduced energy expenditure) have demonstrated promise in predicting weight loss outcomes and guiding tailored interventions. However, data on obesity phenotyping within children and adolescents remain limited. Addressing this gap is essential for advancing precision medicine approaches in pediatric obesity, with the potential to improve treatment selection, enhance effectiveness, and optimize long-term clinical outcomes. Full article

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple and heterogeneous clinical manifestations (e.g., skin lesions, kidney damage, neuropsychiatric dysfunction), that primarily affects women and whose etiology remains unclear. Various therapies that regulate and reduce the immune system activity are in use or are being developed; however, many of them have serious side effects. Therefore, new approaches are needed to maximize remission periods and reduce associated side effects. In this review, we summarize the currently recommended therapeutic strategies. Furthermore, we hypothesize that the combined use of drugs targeting various dysregulated cellular processes in SLE (i.e., cytokine production, neutrophil extracellular traps (NETs), phagocytosis) might have therapeutic potential, at least in some disease phenotypes. Preliminary data show that Toll-like receptors 7/8 (TLR 7/8) inhibition (e.g., Enpatoran) may reduce interferon-α (IFN-α) production by monocytes and NET formation by neutrophils. Our hypothesis is that future therapies combining compounds that modulate the three cellular processes might result in a better disease management as current therapies. Full article

Colorectal cancer (CRC) develops through evolutionary processes involving genomic alterations, epigenetic regulation, and microenvironmental interactions. While traditionally explained by the stepwise accumulation of driver mutations, contemporary evidence supports a ‘Big Bang’ model in which many early-arising clones expand simultaneously to establish extensive heterogeneity. We reviewed recent studies employing spatially resolved multi-omic sequencing of tumour glands combined with computational modelling. These approaches enable high-resolution reconstruction of clonal architecture, transcriptional states, and chromatin accessibility. Findings show that although early clonal mutations shape tumour expansion, gene expression variability can be independent of genetic ancestry and instead reflects phenotypic plasticity driven by microenvironmental cues. Epigenomic analyses identified recurrent somatic chromatin accessibility alterations in promotors and enhancers of oncogenic pathways, frequently in the absence of DNA mutations, suggesting alternative mechanisms of gene regulation. Immune-focused studies demonstrated that early silencing of antigen-presenting genes and loss of neoantigens facilitate immune escape despite active surveillance. CRC is shaped by an interplay of genome, epigenome, and immune evolution, with non-genetic mechanisms and tumour plasticity emerging as important drivers of progression and therapeutic resistance. Full article

Studying intraspecific differentiation in closely related species is essential to clarify the phylogenetic relationships and mechanisms of early stage speciation, particularly in evolutionarily young lineages affected by human-driven population declines. The endangered saker falcon (Falco cherrug), with its ambiguous phylogenetic links to the gyrfalcon (F. rusticolus), exemplifies this scenario. This study presents a comprehensive genetic analysis of F. cherrug and F. rusticolus using mtDNA markers and microsatellite loci, focusing on the diversity of southern Siberian saker falcon populations. The genotyping results for these populations were correlated with phenotypic data obtained from long-term monitoring (1999–2021). Our findings provide novel insights into the current subspecific differentiation and the remnants of a nascent subspecies structure that existed before the recent demographic collapse. Furthermore, our results support the hypothesis of the gyrfalcon’s origin as a descendant species of the Asian saker falcon, i.e., an evolutionarily young lineage undergoing divergence. Our data contribute to the understanding of the Hierofalco evolutionary history, particularly through the analysis of heterogeneous mutation rates among mitochondrial haplogroups. This study underscores the critical importance of conservation efforts for wild endangered populations through long-term monitoring integrated with combined genetic approaches. Full article

Objectives: Polycystic ovary syndrome (PCOS) is a heterogeneous disorder with diverse pathogenetic mechanisms and clinical manifestations. Phenotype D PCOS is characterized by oligomenorrhoea and polycystic ovaries without hyperandrogenism. Altered adipokine profiles may contribute to reproductive and metabolic disturbances. Chemerin is an adipokine involved in inflammatory and metabolic processes. It remains unclear whether altered chemerin levels in PCOS reflect metabolic dysfunction alone or are directly associated with hyperandrogenism. The aim of this study was to compare serum chemerin levels in women with normoandrogenic PCOS and a control group. Methods: This cross-sectional preliminary study included 49 women with phenotype D PCOS and 40 healthy, age- and body mass index (BMI)-matched controls. Anthropometric, biochemical, hormonal parameters, and serum chemerin concentrations were assessed. Results: Serum chemerin concentrations did not differ significantly between the groups. In the PCOS group, the 95% confidence interval ranged from 198.61 to 234.37, while in the controls, it ranged from 187.13 to 216.21. In women with PCOS, chemerin showed significant positive correlations with weight, BMI, waist and hip circumference, total adipose tissue, and both gynoid and android fat content. Positive correlations were also observed with highly sensitive C-reactive protein (hs-CRP), insulin, glucose, triglycerides, and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), and a negative correlation was found with high-density lipoprotein (HDL) cholesterol. Chemerin was weakly negatively correlated with sex hormone binding globulin (SHBG) and positively correlated with the free androgen index (FAI). In the control group, chemerin correlated positively with CRP, insulin, triglycerides, total and gynoid adipose tissue, and negatively correlated with HDL cholesterol and SHBG. Conclusions Although chemerin levels did not differ from controls, chemerin was associated with metabolic and inflammatory markers in both groups. These findings should be considered preliminary due to the limited sample size. Chemerin may reflect metabolic and inflammatory status rather than hyperandrogenism in normoandrogenic PCOS. Full article