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

Introduction The incidence of type 2 diabetes (T2D) in youth is increasing and in-utero exposure to maternal diabetes is a known risk factor, with higher risk associated with pregestational T2D exposure compared to gestational diabetes mellitus (GDM) exposure. We hypothesize this differential risk is reflected in DNA methylation (DNAm) changes induced by differential timing of in-utero exposure to maternal diabetes, and that exposure to diabetes throughout pregnancy (T2D) compared to exposure later in development (GDM), induces different DNAm signatures and different T2D risk to offspring. This study presents an epigenome-wide investigation of DNAm alterations associated with in-utero exposure to either maternal pregestational T2D or GDM, to determine if the timing of prenatal diabetes exposure differentially alters DNAm. Methods We performed an epigenome-wide analysis on cord blood from 99 newborns exposed to pregestational T2D, 70 newborns exposed to GDM, and 41 unexposed to diabetes in-utero from the Next Generation birth cohort. Associations were tested using multiple linear regression models while adjusting for sex, maternal age, BMI, smoking status, gestational age, cord blood cell type proportions and batch effects. Results We identified 27 differentially methylated sites associated with exposure to GDM, 27 sites associated with exposure to T2D, and 9 common sites associated with exposure to either GDM or T2D (adjusted p value < 0.05 and effect size estimate > 0.01). One site at CLDN15 and two unannotated sites were previously reported as associated with obesity. We also identified 87 differentially methylated regions (DMRs) associated with in-utero exposure to GDM and 69 DMRs associated with in-utero exposure to T2D. We identified 23 DMR sites that were previously associated with obesity, three with T2D and five with in-utero exposure to GDM. Furthermore, we identified six CpG sites in the PTPRN2 gene, a gene previously associated with DNAm differences in blood of youth with T2D from the same population. Conclusion Our findings support that in-utero exposure to maternal diabetes is associated with DNAm alterations in offspring. Moreover, the timing of maternal diabetes in-utero exposure (GDM or T2D) produces overlapping but distinct DNAm patterns, suggesting that the window of exposure to maternal diabetes produces different molecular modifications and may reflect, at least in part, the difference in risk for youth-onset T2D in offspring. We also identified sites in this study that have been previously associated with T2D or obesity, which may serve as potential early-life biomarkers of exposure and/or risk, warranting further investigation in longitudinal studies.

Background Procrastination, defined as the voluntary delay of intended actions, affects personal and academic tasks and is linked to decreased quality of life and well-being. This study evaluates the prevalence, causes, and effects of chronic procrastination among adults in Saudi Arabia, with a focus on demographic associations, psychological impacts, and coping strategies. Objective To determine the prevalence of chronic procrastination among adults in Saudi Arabia, identify its demographic and psychological predictors, and evaluate its effects on personal well-being, academic performance, and daily functioning. Methods A cross-sectional study was conducted among 1,093 participants, aged 18–55 years, residing in Saudi Arabia. Data were collected through a self-administered online survey covering demographics, procrastination behaviors, and coping strategies. Statistical analysis, including chi-square and exact probability tests, identified associations between procrastination frequency and demographic factors. Results Of the participants, approximately 70% reported frequent procrastination, with academic tasks (56.6%) and household chores (13.9%) being the most delayed activities. Common reasons for procrastination included poor time management (76.2%), boredom (59.7%), and lack of motivation (57.3%). Over 65% experienced health impacts, such as sleep problems and stress. Procrastination significantly affected both personal life (55.1%) and work/studies (70%). Time management, task division, and deadline-setting were the most utilized strategies, though effectiveness varied. Conclusion The study indicates a high prevalence of procrastination among young adults, particularly students, with detrimental impacts on personal and academic functioning. Training programs focused on time management and prioritization could help reduce procrastination. Categories Psychology, Behavioral science, Time management, Well-being.

Background Gratitude interventions have shown various psychological benefits, including enhanced motivation in academic settings. However, their impact on work engagement - a key factor in employee well-being and organizational performance - remains underexplored. This study examined whether a 12-day online gratitude journaling intervention enhances work engagement and increases awareness of job resources, based on the Job Demands-Resources (JD-R) Model. Methods A total of 100 Japanese employees (mean age = 41.0 ± 5.2 years, evenly split by gender) were randomly assigned to a gratitude journal group or a daily life journal group (control). Participants in the gratitude journal group recorded things they felt grateful for, while the control group documented daily occurrences. Work engagement was assessed using the Utrecht Work Engagement Scale (UWES), alongside measures of work motivation, gratitude disposition, perspective-taking, life satisfaction, and psychological well-being. Journal entries were analyzed using word frequency analysis and correspondence analysis to examine whether gratitude journaling enhanced awareness of job resources. Results Participants in the gratitude journal group exhibited a significant increase in work engagement (total score and absorption dimension) post-intervention, supporting the idea that gratitude journaling enhances engagement. Journal content analysis revealed that gratitude journaling was associated with greater recognition of job resources, such as social support, suggesting a mechanism through which gratitude influences work engagement. Both groups showed increases in gratitude disposition, life satisfaction, and competitive-oriented work motivation, suggesting possible broader journaling benefits. In contrast, the daily life journal group experienced temporary declines in purpose in life and autonomy. Conclusions This study provides experimental evidence that gratitude journaling enhances work engagement by increasing awareness of job resources, integrating gratitude into the JD-R Model. The findings suggest that gratitude must be actively cultivated rather than assumed to arise naturally. Given its accessibility and low cost, gratitude journaling offers a promising tool for organizations to foster employee engagement. Future research should examine its long-term effects and evaluate its applicability across diverse cultural contexts.

Background Circulating tumour DNA (ctDNA) in liquid biopsies has emerged as a powerful biomarker in cancer patients. Its relative abundance in cell-free DNA serves as a proxy for the overall tumour burden. Here we present GeneBits, a method for cancer therapy monitoring and relapse detection. GeneBits employs tumour-informed enrichment panels targeting 20–100 somatic single-nucleotide variants (SNVs) in plasma-derived DNA, combined with ultra-deep sequencing and unique molecular barcoding. In conjunction with the newly developed computational method umiVar, GeneBits enables accurate detection of molecular residual disease and early relapse identification. Results To assess the performance of GeneBits and umiVar, we conducted benchmarking experiments using three different commercial cell-free DNA reference standards. These standards were tested with targeted next-generation sequencing (NGS) workflows from both IDT and Twist, allowing us to evaluate the consistency and accuracy of our approach across different oligo-enrichment strategies. GeneBits achieved comparable depth of coverage across all target sites, demonstrating robust performance independent of the enrichment kit used. For duplex reads with ≥ 4x UMI-family size, umiVar achieved exceptionally low error rates, ranging from 7.4×10-7 to 7.5×10-5. Even when including mixed consensus reads (duplex & simplex), error rates remained low, between 6.1×10-6 and 9×10-5. Furthermore, umiVar enabled variant detection at a limit of detection as low as 0.0017%, with no false positive calls in mutation-free reference samples. In a reanalysed melanoma cohort, variant allele frequency kinetics closely mirrored imaging results, confirming the clinical relevance of our method. Conclusion GeneBits and umiVar enable highly accurate therapy and relapse monitoring in plasma as well as identification of molecular residual disease within four weeks of tumour surgery or biopsy. By leveraging small, tumour-informed sequencing panels, GeneBits provides a targeted, cost-effective, and scalable approach for ctDNA-based cancer monitoring. The benchmarking experiments using multiple commercial cell-free DNA reference standards confirmed the high sensitivity and specificity of GeneBits and umiVar, making them valuable tools for precision oncology. UmiVar is available at https://bit.ly/4p116dS .

The dairy industry is a cornerstone of global food security and nutrition, yet it faces significant challenges due to the rising incidence of antibiotic ...

Background Glycated albumin (GA) is a useful marker for short-term glycemic control, but its levels may be influenced by body composition. Therefore, we aimed to investigate the impact of increasing body mass index (BMI) on GA levels in healthy individuals. Methods This cross-sectional study included healthy individuals with normal and elevated BMI. Individuals with diabetes mellitus, pregnancy, acute infection, a history of cardiovascular events, malignancy, chronic liver disease, nephrotic syndrome, thyroid dysfunction, anemia, morbid obesity (BMI ≥ 40 kg/m²), or any other condition known to affect GA levels were excluded. Anthropometric and biochemical measurements were obtained and compared between normal and elevated BMI groups. Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) version 22.0. Results A total of 52 individuals with elevated BMI and 49 with normal BMI were included in the analysis. Individuals with elevated BMI had significantly lower levels of GA (42.8 ± 7.2 vs. 51.3 ± 6.0, p < 0.001), while levels of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were markedly higher (0.6 ± 0.4 vs. 0.4 ± 0.2, p < 0.001 and 13.5 ± 12.3 vs. 8.3 ± 7.5, p = 0.002; respectively). BMI showed a moderate inverse association with GA (r=-0.583, p < 0.001). Moreover, BMI was positively associated with CRP (r = 0.366, p < 0.001) and ESR (r = 0.299, p = 0.002). In addition, GA levels exhibited negative correlations with CRP (r=-0.401, p < 0.001) and ESR (r=-0.384, p < 0.001). Multivariate regression analysis confirmed that BMI was independently associated with GA levels (B=-2.727, 95% CI:-5.077 to -0.377, p = 0.024). Conclusion Our results suggest a potential inverse association between BMI and GA levels. Clinical trial number Not applicable.

Background Recent studies have shown that the maternal gut microbiota can regulate placental growth, particularly the transport region, in association with fetal growth. However, the specific role of certain microorganisms in modulating the hormonal production of the placenta, which is critical for supporting fetal development and maintaining a healthy pregnancy, remains largely unexplored. In this context, the objective of this study is to determine whether the maternal colonisation with the early life gut bacterium Bifidobacterium breve UCC2003 regulates placental endocrine function. Methods Pregnant germ-free mice were colonized with or without Bifidobacterium breve UCC2003 (BIF) during pregnancy. The endocrine region of the placenta (junctional zone, Jz) was collected to assess its metabolic profile using metabolomics, the expression of key nutrient uptake genes, hormones and synthetic genes by qPCR, and proteome using LC-MS/MS. Results BIF colonised dams had increased lactate and taurine concentrations in the placental Jz. BIF presence was also associated with upregulated expression of nutrient carriers, particularly those involved in large neutral amino acid and monocarboxylate uptake (e.g., Slc7a8 and Slc16a4). Additionally, key hormones, such as prolactins and pregnancy-specific glycoproteins, were upregulated. The Jz proteome was changed in BIF colonised dams, with over 400 proteins dysregulated. Pathway analysis revealed more than 150 biological processes were altered, including transcriptional activity, protein synthesis, cell cycle progression, and metabolic regulation. Proteins regulated by BIF in the placental Jz were correlated with fetal growth and nutrient levels (namely glucose). Notably, maternal-associated BIF reduced the number of fetal resorptions (early fetal loss). Conclusions In germ-free mice, maternal-associated gut Bifidobacterium breve UCC2003 regulates placental endocrine capacity, by altering its metabolic profile and ability to produce endocrine factors. This study provides the first clear evidence that the maternal gut microbiota not only influences placental transport function, but also regulates its endocrine outputs. Graphical Abstract

Aneurysmal subarachnoid hemorrhage is a critical condition with high case-fatality and lasting impacts on survivors. Acute events that are the direct result of aneurysm rupture, such as acute ischemia, elevated intracranial pressure, cerebral edema, seizures, and hydrocephalus, lead to early brain injury. A delayed cascade of processes, including a prominent systemic inflammatory response, may lead to secondary brain injury and delayed cerebral ischemia, which often further impairs recovery. Systemic complications, including cardiac and pulmonary dysfunction, fever, and electrolyte imbalances, arise in the interplay between early and secondary brain injury and challenge the clinical course. Early management focuses on the prevention of rebleeding mainly through aneurysm securement, amelioration of early brain injury through cerebrospinal fluid drainage, control of intracranial pressure, and organ support to avoid or attenuate secondary brain injury. Nimodipine remains the only pharmacological agent shown to reduce delayed cerebral ischemia, and lumbar drainage of cerebrospinal fluid to reduce subarachnoid blood may improve outcome. Management strategies for hemodynamic interventions, seizures, intracranial pressure control, large artery vasospasm, and electrolytes remain consensus-based and with large variation in practice. Several advances in understanding inflammation and delayed cerebral ischemia, as well as in monitoring and interventions hold promise, but robust trials are needed to refine protocols and improve patient recovery. Understanding and mitigating the cascade of damage from rupture to recovery is essential to reduce the burden of this devastating condition. In this review, we appraise the current understanding of the pathophysiology of post-rupture complications as well as scientific and management data, with a focus on recent advances.

Background Liquid biopsy assays using cerebrospinal fluid (CSF) can revolutionize care for children with central nervous system (CNS) tumors by enabling precise monitoring of therapeutic responses and detecting recurrence or measurable residual disease (MRD). These assays can detect cell-free, circulating tumor DNA (ctDNA) via somatic alterations, though accurately measuring low-abundance ctDNA in CSF is challenging. Methods Our research focused on the optimization of next-generation sequencing library preparation from cell-free DNA (cfDNA), evaluating four commercial kits to address the low nucleic acid yield in CSF-derived cfDNA. The selected kit minimized false positives and detected somatic variants at 5% variant allele frequency using 0.1 ng input of synthetic cfDNA, suitable for low-volume CSF samples. Results We then applied our optimized workflow to six children with CNS tumors using a personalized hybrid-capture sequencing strategy (“MRD4U”), in which individualized panels were designed based on each patient’s tumor sequencing. Using MRD4U, we identified ctDNA in two samples, even though neither patient had radiographic or clinical evidence of disease at the time of liquid biopsy. Notably, one ctDNA-positive patient developed radiographic recurrence four months later, demonstrating the assay’s potential to detect molecular relapse ahead of conventional clinical measures. Conclusions These findings demonstrate applicability of our personalized MRD4U assay in early detection of disease recurrence. Unlike non-targeted or tumor-agnostic CSF liquid biopsy approaches, MRD4U leverages patient-specific genomic information to enable sensitive, tumor-informed monitoring that can be deployed across a wide range of pediatric CNS tumors. Our approach is broadly applicable to any tumor type with existing genomic data, enabling ctDNA detection across diverse diagnoses. Ultimately, this strategy may inform clinical decision-making and enable earlier therapeutic intervention.

Background Chemotherapy remains the cornerstone of cancer treatment despite its well-documented challenges, including toxic side effects and drug resistance. Here, we demonstrate that a novel, highly toxic, daunosamine-modified derivative of daunorubicin (2-pyrrolino-daunorubicin, PyDau) can be safely administered to mice when encapsulated in liposome. Methods PyDau was synthesized from daunorubicin in a one-step reaction. Its increased in vitro cytotoxicity was confirmed across 42 human cell lines representing 12 cancer types, including multidrug resistant cells. The activity profile of this new derivative was analyzed in the context of 13 commonly used cancer drugs across a panel of lymphoblast cell lines missing individual components of DNA-repair enzymes. To enable in vivo application, PyDau was encapsulated in pegylated liposome, resulting in liposomal PyDau (LiPyDau). In vivo efficacy of LiPyDau was evaluated in three allograft models (melanoma, breast, lung), a xenograft model (uterine sarcoma), a patient-derived xenograft model (lung), and a genetically engineered mouse model of mammary cancer, including two models of drug resistance. Results While PyDau exhibited up to 1000-fold greater cytotoxicity than daunomycin and doxorubicin against cancer cell lines, its in vivo application was hindered by an extremely narrow therapeutic window. Liposomal nanoformulation mitigated the limiting toxicity, allowing LiPyDau to be tested in preclinical allograft and xenograft mouse models. LiPyDau demonstrated robust efficacy across all models including multidrug-resistant cancer, completely eradicating tumors in a genetically engineered mouse model of triple-negative breast cancer. LiPyDau exerts its anticancer effect through a unique mechanism involving the crosslinking of complementary DNA strands, resulting in irreversible DNA damage. Conclusion Liposomal formulations of extremely cytotoxic anthracycline analogs, such as LiPyDau, represent a promising and highly effective therapeutic approach for combating drug resistant cancer.

SARS-CoV-2 infection is associated with long-lasting neuropsychiatric and cognitive symptoms, collectively referred to as neuro-PASC. Emerging studies indicates that accelerate brain aging and cellular senescence in COVID brain could lead to altered neuroimmune responses and neurodegenerative outcomes. However, little is known about how cellular senescence is development in neuro-PASC. Here, we examined the role of spike protein subunit S1, a persistent viral antigen, in driving the development of cellular senescence in primary human astrocytes. We have demonstrated that S1 enters endolysosomes and induces endolysosome dysfunction and cellular senescence. Moreover, the multibasic motif is critical for such S1-induced damaging effects. Importantly, we identified Toll-like receptor 7 (TLR7), an endolysosome-resident pattern recognition receptor, as a critical mediator of S1-induced damaging effects. Mechanistically, S1 interacts with TLR7 at the site of the endolysosome lumen and activates p38 MAPK signaling of downstream of TLR7, which drive the development of cellular senescence. Together, these findings suggest that TLR7 mediates S1-induced endolysosome dysfunction and cellular senescence, and that TLR7 represents a therapeutic target for mitigating neuro-PASC.