Background Transcranial magnetic stimulation (TMS) is an established treatment for major depressive disorder (MDD), yet response rates remain suboptimal and biomarkers predictive of treatment outcomes are currently lacking. Recently, DNA methylation (DNAm) has shown promise as an epigenetic predictor of antidepressant and electroconvulsive therapy treatment outcomes but no study to our knowledge has characterized DNAm profiles of treatment outcomes in the context of TMS. Here, we present the first genome-scale DNAm analysis of TMS outcomes in patients with treatment-resistant depression (TRD). Methods Peripheral blood samples from 60 TRD patients were collected prior to a standard 36-session TMS course. DNAm was profiled using the Illumina EPIC array and filtered to retain only the top 5% most variable probes for subsequent analysis in relation to three treatment outcomes in an analytic sample of 46 patients: treatment response (> 50% PHQ-9 reduction), symptom trajectory (ΔPHQ-9), and remission (PHQ-9 < 5). Results Methylated CpG Set Enrichment Analysis (mCSEA) identified 67, 23, and 163 differentially methylated regions (DMRs) associated with treatment response, symptom trajectory, and remission, respectively (FDR < 0.05). Sixteen DMRs were common across all outcomes, implicating genes involved in neurodevelopment (HOXA4, HOXA5), immune signaling (RUNX1, OTUD5), and synaptic function (EFNB1, RAP2C). Targeted analysis of 84 CpGs in the BDNF promoter revealed 10 nominally significant CpGs that differentiated responders from non-responders. Several DMRs showed strong blood–brain methylation concordance (r > 0.5), supporting their potential relevance to central nervous system mechanisms. Conclusions Despite the limited sample size, these findings suggest distinct epigenetic signatures prior to treatment that are associated with TMS outcomes, supporting the potential utility of DNAm as a biomarker for response stratification in TRD.

Editorial Open access Published: BioData Mining 18, Article number: 78 (2025) Cite this article 415 Accesses 14 Altmetric Metrics The rise of large language models (LLMs) has revolutionized biomedical data science, transforming the way we access, synthesize, and reason over data and information.

Abstract Cell death is a fundamental process essential to all living organisms, with apoptosis serving as one of the most crucial pathways across various stages of life. Dysregulation of apoptosis is closely associated with numerous diseases, particularly cancer. PUMA (p53 upregulated modulator of apoptosis) is a key mediator of apoptotic cell death. It is activated in response to a wide range of internal and external signals. Beyond its established role in apoptosis, PUMA also regulates other forms of cell death, including necroptosis, autophagy, and ferroptosis, underscoring its critical role in cancer cell death, especially during chemotherapy. However, PUMA activation is frequently impaired in many cancers, leading to resistance to cell death and treatment failure. This review highlights recent advancements in understanding the regulation of PUMA expression at multiple levels, including epigenetic, transcriptional, post-transcriptional, and post-translational mechanisms. It also examines the influence of diverse cellular regulators, such as epigenetic modifiers, transcription factors, non-coding RNAs, kinases, and ubiquitin ligases in modulating PUMA activity. Additionally, we discuss PUMA’s role in cancer progression, its impact on the effectiveness of anti-cancer therapies, and its potential as a prognostic biomarker for therapeutic resistance. Finally, we propose critical questions to inspire future research, aiming to deepen the understanding of PUMA regulation and its significance in cancer therapy. Graphical abstract The diagram highlights the regulatory network of p53 under stress conditions such as DNA damage, hypoxia, or oncogenic stress. In normal conditions, MDM2 binds to and sequesters p53, leading to its proteasomal degradation. Stress signals activate p53, inducing the pro-apoptotic protein PUMA, which inhibits anti-apoptotic proteins (BCL-2, BCL-XL, and BCL-W), thereby activating the effector proteins BAX and BAK. This activation results in mitochondrial outer membrane permeabilization (MOMP) and cytochrome c (Cyt c) release, triggering caspase activation and apoptosis. Proper apoptosis maintains tissue homeostasis, whereas alterations in this pathway can lead to uncontrolled cell proliferation and cancer.

On the occasion of World Diabetes Day, celebrated each year on November 14th to honor the birthday of Frederick Banting, who co-discovered insulin, Cardiovascular Diabetology is delighted to announce the Associate Editors of the Year 2025: Prof. Dídac Mauricio and Prof. Francesco Paneni!

Background Sleep duration has a well-established effect on mental health and well-being, with durations of 7 to 9 hours being the general recommendation. Here, we analyze the significance of sleep patterns and find that a consistent routine reduces the risk of developing mental disorders far more than simply ensuring a certain average sleep duration. Methods We analyzed the sleep behavior of 100,000 adults for one week using motion data from wrist-worn devices. We modeled sleep behavior using multivariate generalized additive Cox proportional hazard models, incorporating a smooth 2D interaction effect of sleep duration and routine sleep hours. We calculated C-statistics and E-values to evaluate model performance and assess the robustness against hidden confounders. We also stratified analyses by age and gender. Results Most participants slept for 7 to 9 hours as recommended, yet they consistently only slept during the same 4.8 hours each night. We found that an average sleep duration around 8 hours minimizes the risk of future mental disorders—but only if integrated into a rigorous sleep routine spanning at least the same 7 hours each night. Our study provides evidence that adopting such sleep behavior could reduce the population incidence rate of mental disorders by 23% (HR: 0.79, $$p<0.0001$$ , for the average participant). The models showed a strong fit (C-statistics: 0.63), robustness to hidden confounders (E-value: 1.8), and stability under age- and gender-based stratification. We identified weekend behavior as a frequent reason for low sleep routines, with over 25% of the population disrupting their weekly sleep routine during weekend nights—raising the risk of future mental disorders by 10%. Conclusions Our results suggest that maintaining a consistent sleep routine is more important for mental health than sleep duration alone. Socially disadvantaged groups, including low-income households and ethnic minorities, exhibited poorer sleep routines and thus higher mental disorder risks, underscoring existing social inequalities. Promoting regular sleep behavior may therefore have significant public health benefits.

Background Diet and genetic risk are established risk factors for kidney cancer, but their interaction remains unclear. This study aims to systematically investigate the associations between various dietary patterns and kidney cancer risk, as well as to evaluate the combined effects of diet and genetic risk on kidney cancer risk. Methods We conducted a prospective cohort study involving 113,594 participants from the UK Biobank who completed at least two 24-hour dietary recalls, and adherence to four dietary patterns (Alternate Mediterranean Index (aMED), Alternative Healthy Eating Index 2010 (AHEI), dietary approaches to stop hypertension (DASH), and dietary inflammatory index (DII)) was assessed. Incident kidney cancer cases were ascertained via records. Genetic risk was quantified using polygenic risk score (PRS). Associations were evaluated using Cox proportional hazards models, adjusting for confounders. Furthermore, mediation analyses were conducted to identify potential mediators. Results During a median follow-up of 11.44 years, 425 participants developed kidney cancer. Higher aMED (HR = 0.71, 95% CI: 0.54–0.94) and DASH (HR = 0.67, 95% CI: 0.49–0.90) were associated with reduced risk of kidney cancer, while higher DII was associated with increased risk (HR = 1.36, 95% CI: 1.02–1.79). Moreover, participants with high genetic risk combined with low aMED, AHEI and DASH scores or high DII score presented the highest kidney cancer risk. Additive interaction was observed between genetic risk and AHEI as well as DII. Moreover, a series of biochemical indicators were identified as potential mediators, with the mediation proportions ranging from 0.76% to 8.40%. Conclusion Adherence to healthy dietary patterns, such as aMED, AHEI, and DASH is associated with a reduced risk of kidney cancer, whereas a pro-inflammatory diet confers a greater risk, particularly in high-genetic-risk populations. These findings provide strong evidence that promoting these healthy dietary patterns represents a promising public health strategy for the primary prevention of kidney cancer.

Breast cancer, the most common cancer among women worldwide, continues to pose significant public health challenges. Among the subtypes of breast cancer, triple-negative breast cancer (TNBC) is particularly aggressive and difficult to treat due to the absence of receptors for estrogen, progesterone, or human epidermal growth factor receptor 2, rendering TNBC refractory to conventional targeted therapies. Emerging research underscores the exacerbating role of metabolic disorders, such as type 2 diabetes and obesity, on TNBC aggressiveness. Here, we investigate the critical cellular and molecular factors underlying this link. We explore the pivotal role of circulating plasma exosomes in modulating the tumor microenvironment and enhancing TNBC aggressiveness. We find that plasma exosomes from diet-induced obesity mice induce epithelial-mesenchymal transition features in TNBC cells, leading to increased migration in vitro and enhanced metastasis in vivo. We build on our previous reports demonstrating that plasma exosomes from obese, diabetic patients, and exosomes from insulin-resistant 3T3-L1 adipocytes, upregulate key transcriptional signatures of epithelial-mesenchymal transition in breast cancer. Bioinformatic analysis reveals that TNBC cells exhibit higher expression and activation of proteins related to the Rho-GTPase cascade, particularly the small Ras-related protein Rac1. Our approach suggests novel therapeutic targets and exosomal biomarkers, ultimately to improve prognosis for TNBC patients with co-morbid metabolic disorders.

Background It has been shown that neopterin levels in various body fluids can help predict the diagnosis of different malignancies. Although many studies have investigated the roles of serum neopterin concentrations, tryptophan metabolism, and the dietary inflammation index (DII) in various cancers, the connection between these factors and prostate cancer (PC) remains uncertain. The aim of this study was to investigate the predictive and prognostic roles of serum neopterin, and kynurenine levels, along with the kynurenine-to-tryptophan ratio (KTR) and DII in prostate cancer. Methods This study was conducted with 57 newly diagnosed prostate cancer patients, 55 benign prostate hyperplasia patients, and 56 healthy male individuals in the control group, all aged 40 years and older. Participants had specific anthropometric measurements taken, and three-day food records were kept. DII was calculated based on data for thirty-four available nutrients by using food records. Serum levels of neopterin, kynurenine, tryptophan, tumor necrosis factor alpha (TNF-α), and interferon-gamma (IFN-γ) were measured using an enzyme-linked immunosorbent assay (ELISA) method. Results Serum neopterin (11.79 ± 6.09), kynurenine (1655.48 ± 1122.04), TNF-α (221.59 ± 232.06) and IFN-γ (137.68 ± 107.11) levels were higher in the malignant group than in both the control (2.72 ± 0.76, 352.40 ± 69.33, 223.94 ± 226.67, and 23.03 ± 7.28, respectively) and benign groups (3.17 ± 0.74, 377.94 ± 109.05, 179.61 ± 224.36, and 25.63 ± 7.50, respectively) (p < 0.05). Another result of our study is that in the malignant group, serum neopterin levels exhibited significant positive correlations with serum kynurenine (r = 0.80, p < 0.0001), IFN-γ (r = 0.86, p < 0.0001) and TNF-α levels (r = -0.27, p = 0.0453) and DII (r = 0.30, p = 0.0229), while they exhibited weak correlations with serum PSA, and other diet parameters. Additionally, kynurenine was the only parameter showing significant differences in mean values concerning surgical margins (p < 0.05). Conclusions The findings of this study support the hypothesis that serum neopterin and specific tryptophan catabolites (e.g., kynurenine), could serve as predictive and prognostic biomarkers for prostate cancer diagnosis. However, our results do not support the hypothesis that DII and certain dietary factors play a direct role in the development or diagnosis of prostate cancer.

Exosomes, containing molecular constituents of their cell of origin, including proteins and nucleic acids, were first discovered in immature red blood cells in 1983. Excellent intercell communication can be achieved by shuttling these various molecules between cells. Stem cell-derived exosomes (SC-Exos) contain paracrine-soluble factors that play important roles in tissue development, homeostasis, and regeneration. This paracrine activity of SC-Exos has been found to be a predominant mechanism by which stem cell-based therapies mediate their effects on degenerative, autoimmune and/or inflammatory diseases. Compared to other types of stem cells, human embryonic stem cells (hESCs), human induced pluripotent stem cells (hiPSCs), human mesenchymal stem cells (hMSCs) are the most popular because of their efficient immunomodulatory effects. The advantages and disadvantages of using exosomes isolated from the stem cell trio for therapeutic applications are further discussed in this review.

World Antimicrobial Resistance Awareness week is celebrated every year from the 18th to the 24th of November. The campaign is one of the World Health Organisations official campaigns and aims to raise awareness of AMR and promote global action to tackle the spread of drug resistant diseases.

Prematurity, defined as birth before 37 weeks of gestation, remains a significant global health concern due to its strong association with increased infant morbidity and mortality. Despite significant advances in antenatal care and neonatal intensive care, preterm infants remain highly susceptible to complications including bronchopulmonary dysplasia, intraventricular hemorrhage, and necrotizing enterocolitis. These conditions not only affect immediate survival but also contribute to long-term neurodevelopmental and neuropsychiatric challenges that may persist throughout the life span. Survivors of preterm born infants continue to face higher risks of cognitive, motor, and behavioural impairments, as well as psychiatric disorders such as attention-deficit/hyperactivity disorder, anxiety, and depression. This narrative review synthesises the recent findings regarding long-term impacts of prematurity on neurodevelopmental and neuropsychiatric outcomes. It highlights their incidence, risk factors, and the screening and assessment tools currently used in clinical and research settings. By synthesising current knowledge, the review aims to guide clinical care, support early identification of at-risk infants, and inform future research priorities.

Background Alice in Wonderland syndrome (AIWS) is a neuropsychiatric disorder characterized by sensory perception distortions, including altered body image perception and distortions of shape, size, motion, color, and speed. Migraine and infectious diseases are among the most common etiologies of AIWS. However, it has not been studied in individuals with persistent headache after COVID-19. Methods This cross-sectional study included a subset of individuals with AIWS symptoms derived from a survey conducted in Latin America to identify adults with persistent headache after COVID-19. For data analysis, AIWS individuals were characterized by sex and analyzed using univariable tests. Subsequently, the entire study cohort was stratified into two groups: the AIWS group and the non-AIWS group. Binomial logistic regression using the backward stepwise selection method was performed to identify the factors associated with AIWS after COVID-19. Results Out of 421 participants with persistent headache after COVID-19, 106 (25.2%) reported at least one AIWS symptom. The AIWS group was significantly younger (median age 36 vs. 39 years, p = 0.011) and had a higher proportion of pre-existing migraine (40.6% vs. 29.5%, p = 0.035) compared to the non-AIWS group. The most common post-COVID-19 AIWS symptoms were time distortion (32.1%), derealization/depersonalization (24.5%), and hyperchromatopsia (20.8%). Logistic regression analysis revealed that experiencing any AIWS symptom during acute COVID-19 was the strongest predictor for post-acute AIWS (OR = 9.937, 95% CI = 5.603–17.62, p <0.001). Other significant predictors included phonophobia (OR = 2.322, 95% CI = 1.288–4.185, p = 0.005) and depressive symptoms (OR = 1.937, 95% CI = 1.099–3.413, p = 0.022) during acute COVID-19. Conclusion In this cohort, AIWS was a notable feature in adults with persistent headache after COVID-19, particularly in younger individuals with a history of migraine. Experiencing AIWS symptoms during acute infection increased the odds of post-acute AIWS symptoms nearly tenfold, suggesting SARS-CoV-2 may be a potent trigger. Clinicians should be aware of this association and screen for perceptual disturbances in patients with post-COVID-19 neurological sequelae.

Background Ultra-processed foods (UPFs), often high in sodium, sugar, and unhealthy fats, compose more than half of total dietary energy consumption in the United States. A diet composed of a high amount of UPFs can contribute to glucose dysregulation and insulin resistance, which may lead to prediabetes and type 2 diabetes (T2D). However, few studies have assessed the associations between UPFs and T2D or obesity in young people. The goal of this study is to examine associations between UPF consumption and prediabetes and related biomarkers in youth. Methods Young adults (age 17–22, n = 85) with a history of overweight or obesity from the Metabolic and Asthma Incidence Research (Meta-AIR) study, a subset of the Children’s Health Study, were enrolled between 2014 and 2018 and returned for a second visit between 2020 and 2022. Participants completed two 24-hour dietary recalls and an oral glucose tolerance test at each visit. Food items were categorized as either an UPF or non-UPF according to NOVA classification guidelines. The proportion of the diet composed of UPFs was calculated for each participant. Regression models were used to assess relationships of UPF consumption at baseline and change between visits with markers of glucose homeostasis at follow-up, adjusting for demographics, physical activity, and total energy intake. Results A 10%-point increase in UPF consumption between visits was associated with a 51% (OR: 1.51, 95% Cl: 1.04, 2.31) higher odds of having prediabetes and 158% (OR: 2.58, 95% CI: 1.43, 5.85) higher odds of impaired glucose tolerance at follow-up. Higher baseline UPF consumption was significantly positively associated with 2-hour insulin ( $$\:\beta\:$$ = 45.11, 95% CI: 22.42, 67.80) and insulin area under the curve ( $$\:\beta\:$$ = 63.56, 95% CI: 34.95, 92.17) at follow-up. Conclusion UPF consumption may increase the risk for T2D among young adults. Our findings suggest that limiting UPF consumption could be an important strategy for T2D prevention in this population.

Background Growing evidence implicates gut microbiota (GM) dysbiosis in Alzheimer’s disease (AD) pathogenesis via the gut-brain axis. Dysbiosis contributes to neuroinflammation, amyloid-β deposition, tau hyperphosphorylation, blood-brain barrier disruption, and cognitive decline. Synbiotics (combinations of probiotics and prebiotics) offer a promising strategy to modulate GM, potentially ameliorating these AD hallmarks through multiple mechanisms including enhanced production of neuroprotective short-chain fatty acids (SCFAs), reduced inflammation, improved gut barrier integrity, and immunomodulation. Objective This review critically evaluates the current evidence on the therapeutic potential of synbiotics for AD. It aims to synthesize findings from preclinical and clinical studies regarding the efficacy of synbiotics in improving cognitive function and AD pathology, elucidate the underlying biological mechanisms including GM modulation, SCFA production, immune regulation, and gut-brain signaling, and identify key challenges and future research directions for translating GM-targeted interventions into effective AD therapies. Conclusion Synbiotics demonstrate significant potential, particularly in early AD, by improving cognitive domains, reducing neuroinflammation and AD biomarkers, and modulating beneficial microbial metabolites. However, challenges include confounding factors, unresolved questions about causality, inconsistent results in advanced disease, and insufficient large-scale human trials. Future success hinges on rigorous longitudinal randomized controlled trials integrating multi-omics approaches, advanced in vitro models, and personalized strategies considering baseline microbiota and host genetics. While not a standalone cure, synbiotics represent a valuable component within multi-target therapeutic approaches aimed at modulating the gut-brain axis to slow AD progression.

Intrinsically disordered proteins and regions (IDRs) lack stable 3D structures, posing challenges for interaction prediction. We present SpatPPI, a geometric deep learning model tailored for IDPPI prediction. SpatPPI leverages structural cues from folded domains to guide the dynamic adjustment of IDRs via geometric modeling, adaptive conformation refinement, and a two-stage decoding mechanism. It captures spatial variability without requiring supervised input and achieves state-of-the-art performance on benchmark datasets. Molecular dynamics simulations further validate its high adaptability to conformational changes in IDRs and strong capacity to generate distinct and structure-aware embeddings. A freely accessible server is available at https://bit.ly/4p9Znmj .

Background Small extracellular vesicles (sEVs) or exosomes are small-sized (30–150 nm), nanoparticles that are released from nearly all cells under normal and pathophysiological conditions. The sEVs have a vital role in biological systems as they communicate and transfer their contents, such as proteins, lipids, and nucleic acids, from the cells of origin to nearby or distant cells. There is a growing interest in sEVs due to their potential applications in understanding disease mechanisms, identifying biomarkers, making clinical diagnoses, and developing therapeutics. Human biofluids such as blood, saliva, and urine are routinely collected in clinical settings and hold significant potential for isolating sEVs for accurate and early clinical biomarker identification. Currently, there is no established method for isolating sEVs in a single method utilizing different human biofluids. Here, we present a protocol for isolating sEVs from small volumes of plasma, saliva, and urine, that are clinically relevant for identifying biomarkers and for subsequent downstream applications. Methods Our method is specifically designed to efficiently isolate sEVs from 1 mL of blood, 2 mL of saliva, and 10 mL of urine samples using a widely available ultracentrifugation instrument. We examined the morphology of sEVs using Transmission Electron Microscopy and Scanning Electron Microscopy. The size distribution and concentration were determined using Nanoparticle Tracking Analysis. Additionally, we assessed exosome-specific markers such as CD-9, CD-63, Flotillin 1, and TSG 101 using western blotting. Our method has undergone successful testing for high-throughput applications with small sample volumes, demonstrating its clinical utility. Results We compared and discussed the results obtained from our tested method for isolating sEVs from three different sample sources. We used sequential centrifugation combined with filtration and sucrose gradient ultracentrifugation. We compared the yields of sEVs from these samples and found that this method resulted in high purity and yield of EVs. Further, we have identified the isolated proteins using mass spectrometry. Discussion The ease of obtaining patient samples from biofluids such as plasma, saliva, and urine makes them valuable for diagnostic purposes. The isolation of sEVs allows for the early diagnosis and prediction of diseases. Our method is simple to use, cost-effective, and reproducible. It has been tested with small sample volumes using proteomics and RNA analysis. When applied to human biofluids, this method can identify clinical research biomarkers, understand disease mechanisms, and monitor disease progression, among other related applications.

For World Diabetes Day 2025, Springer Nature highlights contributions from our publishers and community that supports this year’s theme on “Diabetes and well-being