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/3VYH2fO .

Background Inflammation has long-term health impacts across the life course. Breastfeeding substantially reduces inflammation risk, but key pathways, including the extent that this is due to protection against early life infection, are poorly understood. We aimed to investigate the relationships between breastfeeding, inflammation, and infection burden, and to determine the extent to which metabolomic and lipidomic profiles associated with breastfeeding mediate these health outcomes. Methods We utilised data from the Barwon Infant Study (BIS), a longitudinal birth cohort in Victoria, Australia. Infants (n = 889) with available breastfeeding (categorised as yes/no) clinical, metabolomic, and Lipidomic data at 6 and/or 12 months were included (n = 793 at 6 months, n = 734 at 12 months). Inflammation, measured via glycoprotein acetyls (GlycA), at 6 and 12 months and infection burden, including parent-reported and medically attended infections assessed through standardised 3-monthly questionnaires were used as outcomes. Results Any breastfeeding, regardless of supplementary feeding, was associated with lower inflammation, fewer infections, and significant, potentially beneficial changes in metabolomic and lipidomic markers, particularly plasmalogens. There was evidence of bidirectional mediation: metabolomic biomarkers and lipids mediated breastfeeding’s effects on inflammation, while inflammation partly mediated breastfeeding’s impact on certain metabolites and lipids. Conclusions These findings highlight pathways through which breastfeeding reduces inflammation and infection burden, identifying potential targets for optimising infant feeding.

Background Cardiovascular-kidney-metabolic (CKM) syndrome, characterized by interconnected cardiovascular, renal, and metabolic dysfunctions, poses a growing global health burden. While both light at night (LAN) and air pollutants have independently been linked to adverse health outcomes, their synergistic and joint effects on CKM syndrome risk remain poorly understood. This study aimed to assess the independent, interactive, and joint associations of LAN, air pollutants, and PM2.5 components with CKM syndrome. Methods Data from 4,361 participants aged ≥ 45 years in the China Health and Retirement Longitudinal Study (CHARLS, 2011–2015) were analyzed. Cox proportional hazards regression models were employed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for CKM syndrome risk. Multiplicative and additive interactions between LAN and air pollutants were assessed using likelihood ratio tests and relative excess risk due to interaction (RERI). Joint effects were evaluated by categorizing exposures into tertiles. Results Over a median follow-up of 4.2 years, 792 incident CKM syndrome cases were identified. Adjusted models indicated that higher LAN exposure (highest vs. lowest quartile: HR = 1.46, 95% CI: 1.18–1.80) and increased levels of NO₂ (HR = 1.44, 95% CI: 1.18–1.75), PM2.5 (HR = 1.49, 95% CI: 1.19–1.87), PM10 (HR = 1.75, 95% CI: 1.40–2.18), NO₃⁻ (HR = 1.42, 95% CI: 1.15–1.75), and NH₄⁺ (HR = 1.42, 95% CI: 1.15–1.75) were independently associated with elevated CKM risk. Significant multiplicative interactions were observed between LAN and all pollutants except O₃, NO₃⁻, and NH₄⁺ (P for interaction < 0.05). In the additive interaction analysis, the RERI values ranged from 0.158 to 0.792, indicating a significant synergistic effect between LAN and air pollutants, which increases the risk of CKM syndrome. Joint exposure analysis showed that the combination of high LAN and high PM₁₀ increased CKM risk by 56.3% (HR = 1.563, 95% CI: 1.092–2.238), while moderate co-exposure to LAN and PM2.5 elevated risk by 33.4% (HR = 1.334, 95% CI: 0.872–2.041). Conclusion This study provided evidence that LAN, air pollutants, and PM2.5 components were positively associated with CKM syndrome, and significant synergistic and joint effects existed, increasing the risk of CKM syndrome in older adults. These results highlighted the urgency of comprehensive environmental intervention measures and emphasized the necessity of incorporating multi-factor joint exposure assessment in future CKM syndrome research.

Dietary restriction (DR) refers to a broad set of interventions that limit the intake of specific nutrients or overall food consumption, either in quantity or timing, without causing malnutrition. DR has long been considered the most robust intervention for increasing healthspan and lifespan. This includes, not exhaustively, caloric restriction (CR), protein restriction (PR), amino acid restriction (AAR), intermittent fasting (IF), and time-restricted fasting (TRF), each with overlapping but distinct metabolic and physiological effects. This brief review examines the current scientific understanding of how some of the most commonly employed DR regimens may impact metabolism, lifespan, and healthspan. Particular attention is given to the underlying biological mechanisms and supporting evidence derived from both human clinical studies and fundamental biological research conducted with model organisms ranging from yeast to non-human primates.

Background The diagnostic and therapeutic potential of neutrophil extracellular traps (NETs) in liver fibrosis (LF) has not been fully explored. We aim to screen and verify NETs-related liver fibrosis biomarkers through machine learning. Methods In order to obtain NETs-related differentially expressed genes (NETs-DEGs), differential analysis and WGCNA analysis were performed on the GEO dataset (GSE84044, GSE49541) and the NETs dataset. Enrichment analysis and protein interaction analysis were used to reveal the candidate genes and potential mechanisms of NETs-related liver fibrosis. Biomarkers were screened using SVM-RFE and Boruta machine learning algorithms, followed by immune infiltration analysis. A multi-stage model of fibrosis in mice was constructed, and neutrophil infiltration, NETs accumulation and NETs-related biomarkers were characterized by immunohistochemistry, immunofluorescence, flow cytometry and qPCR. Finally, the molecular regulatory network and potential drugs of biomarkers were predicted. Results A total of 166 NETs-DEGs were identified. Through enrichment analysis, these genes were mainly enriched in chemokine signaling pathway and cytokine-cytokine receptor interaction pathway. Machine learning screened CCL2 as a NETs-related liver fibrosis biomarker, involved in ribosome-related processes, cell cycle regulation and allograft rejection pathways. Immune infiltration analysis showed that there were significant differences in 22 immune cell subtypes between fibrotic samples and healthy samples, including neutrophils mainly related to NETs production. The results of in vivo experiments showed that neutrophil infiltration, NETs accumulation and CCL2 level were up-regulated during fibrosis. A total of 5 miRNAs, 2 lncRNAs, 20 function-related genes and 6 potential drugs were identified based on CCL2. Conclusions This study identified CCL2 as a biomarker for nets-related liver fibrosis, providing a new perspective for understanding the mechanisms of nets-mediated fibrosis and promoting therapeutic discovery.

Background Circular RNAs (circRNAs) are emerging as promising tools in cancer and immunotherapy, with unique characteristics that offer potential therapeutic applications. Main body This review outlines the discovery, biogenesis, and mechanisms of circRNAs, emphasizing their roles in cancer and immune regulation. CircRNAs modulate immune responses by acting as miRNA sponges, binding RNA-binding proteins, or serving as translation templates. These interactions influence T cells, NK cells, macrophages, and immune checkpoints. The review also explores circRNAs’ roles in different cancers, focusing on target identification, immune effects, and mechanisms of action. Additionally, it examines circRNA-based therapies, including vaccines, CAR-T cell therapy, and database applications. Conclusion Despite their potential, technical hurdles must be overcome to advance circRNAs’ clinical use in cancer immunotherapy. Future research should focus on addressing these challenges to fully realize the therapeutic potential of circRNAs.

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

Metal-organic frameworks (MOFs) have emerged as a groundbreaking class of porous crystalline materials, renowned for their remarkable tunability and high ...

Background A plant-focused, healthy dietary pattern, such as the Mediterranean diet enriched with dietary fiber, polyphenols, and polyunsaturated fats, is well known to positively influence the gut microbiota. Conversely, a processed diet high in saturated fats and sugars negatively impacts gut diversity, potentially leading to weight gain, insulin resistance, and chronic, low-grade inflammation. Despite this understanding, the mechanisms by which the Mediterranean diet impacts the gut microbiota and its associated health benefits remain unclear. Methods This retrospective, observational study explored the relationships between Mediterranean dietary components—vegetables, fruits and nuts, legumes, whole grains, fish, meat, dairy, alcohol, saturated and unsaturated fats—and the gut microbiota in middle-aged adults enrolled in Alberta’s Tomorrow Project, Canada. Diet was recorded using the Canadian Dietary History Questionnaire (CDHQ-II) and participants were classified into four quartiles based on a modified Mediterranean Diet Score. Blood and fecal samples were collected for metabolomics and 16S rRNA sequencing, respectively. Results Findings revealed that higher adherence to the Mediterranean diet was associated with increased alpha diversity and a greater abundance of beneficial fiber-degrading bacteria, including Prevotella, Parabacteroides, Clostridium XIVb, Coprobacter, and Turicibacter. Furthermore, participants who consumed more Mediterranean diet components exhibited higher concentrations of serum microbial metabolites including p-hydroxy hippuric acid and indole-acetaldehyde. Conclusions Results demonstrate a pivotal role of the gut microbiota, via its metabolites in harnessing the health benefits of the Mediterranean diet, highlighting its potential to promote metabolic health and prevent chronic disease.

While cotrimoxazole has anti-inflammatory effects among people with Human Immunodeficiency Virus (PWH), its effect on lipid profiles is not well-characterized. We compared the lipid profiles of PWH on cotrimoxazole to those not on it and assessed its association with individual lipid parameters. PWH on antiretroviral therapy (ART) were randomly selected from an urban HIV clinic at Kiruddu National Referral Hospital in Kampala, Uganda. Participants were administered an interviewer-administered study questionnaire, underwent anthropometric measurements, and had blood samples evaluated for total cholesterol, low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides. Non-HDL-c was the difference between total cholesterol and HDL-c and was considered elevated if > 4.0 mmol/l. Dyslipidemia was characterized as elevated total cholesterol (> 5.0 mmol/L), high LDL-c (> 4.14 mmol/L), high triglycerides (≥ 1.7 mmol/L), or low HDL-c (< 1.03 mmol/L for males and < 1.29 mmol/L for females. We used linear, logistic and modified Poisson regression analyses to determine if cotrimoxazole use was independently associated with the individual lipid parameters when controlling for age, smoking, dolutegravir, anthropometrics, alcohol use, HIV clinical stage and glycated hemoglobin. Among 395 PWH enrolled, 100 (25.3%) were on cotrimoxazole prophylaxis for a median (IQR) of 1.0 (0.6–2.5) year, and 364 (92.2%) were on dolutegravir-based ART with a median (IQR) ART duration of 4 (1.8–10.0) years. PWH on cotrimoxazole had significantly lower total cholesterol (4.2 vs. 4.6 mmol/l, p < 0.001), non-HDL-c (3.09 vs. 3.62 mmol/l, p < 0.001), and LDL-c (2.7 vs. 3.0 mmol/l, p = 0.002) compared to those not on the drug. Additionally, a higher proportion of those not on cotrimoxazole had low HDL-c (75.3% vs. 61.6%, p = 0.009) and elevated non-HDL-c (33.3% vs. 11.1%, p < 0.001). Compared to PWH not on cotrimoxazole, a significantly lower proportion of PWH on cotrimoxazole had dyslipidaemia (83.8% (n = 83) vs. 91.1% (n = 265), p = 0.045). After adjusting for confounders, cotrimoxazole use was independently associated with lower total cholesterol levels (adjusted beta coefficient (β) = -0.18, 95% confidence interval (CI) -0.35 to -0.01), p = 0.040), non-HDL-c (β = -0.34, 95% CI -0.58 to -0.11, p = 0.005) and lower odds for elevated non-HDL-c (adjusted prevalence ratio = 0.45, 95% CI 0.26–0.77, p = 0.003). Cotrimoxazole use was independently associated with lower total cholesterol and non-HDL-c levels. These findings suggest a potential lipid-lowering effect of cotrimoxazole, warranting further longitudinal investigation into its potential long-term cardioprotective benefits among PWH.

Accurate identification of protein-protein interaction sites (PPIS) is critical for elucidating biological mechanisms and advancing drug discovery. However, existing methods still face significant challenges in leveraging structural information, including inadequate equivariant modeling, coarse graph representations, and limited multimodal fusion strategies. In this study, we propose a novel multimodal and multiscale deep learning framework, EDG-PPIS, that achieves efficient PPIS prediction by jointly enhancing structural and geometric representations. Specifically, a 3D equivariant graph neural network (LEFTNet) is employed to capture the global spatial geometry of proteins. For structural modeling, a dual-scale graph neural network is constructed to extract protein structural features from both local and remote perspectives. Finally, an attention mechanism is utilized to dynamically fuse structural and geometric features, enabling cross-modal integration. Experimental results demonstrate that EDG-PPIS achieves superior performance across multiple benchmark datasets. EDG-PPIS provides an effective and robust computational tool for target identification and protein function analysis, addressing existing challenges in PPIS prediction and offering a promising approach for advancing the understanding of PPIS.

The incidence of early-onset malignancies in reproductive-aged women is rising, necessitating effective fertility preservation strategies. Ovarian tissue cryopreservation (OTC) remains the sole option for prepubertal girls and patients requiring urgent oncologic treatment. However, post-transplant follicular attrition—driven by ischemia-reperfusion injury, oxidative stress, and aberrant primordial follicle activation—remains a major barrier. This comprehensive review elucidates the multiscale mechanisms of cryopreservation-induced follicular damage and evaluates cutting-edge strategies, including antifreeze protein-engineered cryoprotectants, angiogenesis-modulating scaffolds, and mTOR pathway inhibition. By integrating recent advances in biomaterial science and cryobiology, this study provides actionable insights to enhance OTC clinical efficacy and advance reproductive medicine.

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 Cathepsin K (CatK) contributes to vessel collagene remodelling and high CatK concentrations have been found in atherosclerotic lesions. CatK ablation in a murine model determined an amelioration of diabetes-induced hyperglycemia and cardiovascular structural/functional abnormalities. To date, it is unknown whether glucose tolerance status affects circulating levels of CatK, and if CatK is involved with the cardiovascular complications associated with type 2 diabetes (T2DM). Methods We assayed the levels of serum CatK in a cohort of 544 well-characterized Caucasian adults. assessing subclinical cardiovascular organ damage defined by carotid artery intima-media thickness (c-IMT) and left ventricular mass index (LVMI) in our T2DM cohort. Results CatK levels were significantly higher in individuals with T2DM (2.3 ± 0.8 ng/ml; N = 263) compared to normoglycemia (NGT; 1.2 ± 0.5 ng/ml; N = 146) or predabetes (IFG/IGT; 1.2 ± 0.3 ng/ml; N = 135). Consistent with the literature, CatK levels correlated with age (r = − 0.190, p = 0.001), 2 h-PG (r = − 0.118, p = 0.048) and c-IMT (r = 0.157, p < 0.01) in the subset without T2DM. In the T2DM group, CatK positively correlated with FPI (r = 0.277; p < 0.001), HOMA-IR (r = 0.269; p < 0.001) and c-IMT (r = 0.155; p = 0.013). Multiple logistic regression analysis, adjusted for potential confounders, revealed that a one-quintile increment in CatK levels was associated with a 6.5-fold increased odds of T2DM. Furthermore, multiple linear regression analysis in T2DM patients, including sex, age, BMI, hypotensive therapy, and HOMA-IR (or alternatively HbA1c or FPI) as covariates, identified age and CatK as the strongest determinants of c-IMT. CatK levels did not correlate with LVMI in either the T2DM or non-T2DM cohorts. Conclusions Our data show that the variability of CatK circulating levels is associated with glucose tolerance status, and with early signs of atherosclerosis in a population with T2DM as well as in non-diabetic individuals. These findings, combined with the established role of CatK in vascular remodeling, suggest that CatK may play a role in the early etiopathogenesis of cardiovascular complications in T2DM.

Background Iron deficiency (ID) exhibits strikingly high prevalence in colorectal cancer (CRC), yet its prognostic implications remain insufficiently characterized. This study aimed to evaluate the association between pre-treatment ID status and therapeutic outcomes in patients undergoing standardized treatment protocols for CRC. Methods A retrospective cohort of 1003 CRC patients was analyzed to assess the prevalence of ID and its correlations with clinicopathologic features, postoperative recovery, neoadjuvant therapy response, and iron metabolism and ferroptosis-related gene expression. The association of ID with clinicopathologic data, laboratory parameters, and treatment patient outcome was analyzed using logistic regression. Prussian blue staining was used to assess iron levels in tumor and adjacent noncancerous tissues. Bioinformatics was employed to analyze the expression levels of iron metabolism and ferroptosis-related genes. Results ID was identified in 50.85% (510/1003) of patients. Compared with non-ID patients, those with ID exhibited higher female predominance (56.8% vs. 43.2%), significant increased prevalence of anemia (76.2% vs. 23.8%), and elevated levels of C-reactive protein (CRP), along with decreased albumin (Alb) levels. Clinicopathologic associations with ID included larger tumor diameter, more advanced pathological T/N/M stages, poorer tumor differentiation, and increased lymphovascular and perineural invasion. Among patients received neoadjuvant therapy, ID was associated with higher clinical T/N stages and lower tumor regression grades. Postoperatively, ID patients experienced significantly longer time to first flatus, lower albumin levels, and elevated inflammatory markers. Prussian blue staining revealed reduced iron content in both tumor and adjacent tissues of ID patients. Molecular analyses identified dysregulated iron metabolism genes, with DMRT1, HAMP, FTH1, FTL, TFRC, LCN2, PCBP1 and PCBP2 upregulated and ACO1, IRPEB2, OTUD1, SLC40A1 and NCOA4 downregulated in tumor tissues. Ferroptosis suppressor genes (LCN2, TFRC and SLC40A1) were overexpressed in non-responders to chemoradiotherapy. Conclusion ID is closely associated with aggressive tumor biology, suboptimal response to neoadjuvant therapy, and impaired postoperative recovery. Dysregulation of iron homeostasis and ferroptosis pathways in ID patients may contribute to CRC progression. These findings highlight ID as a potential biomarker for risk stratification and suggest that targeting iron metabolism could improve therapeutic outcomes in CRC management.

Objective To evaluate the predictive value of maternal and umbilical cord blood triglyceride-glucose (TyG) index for adverse neonatal outcomes in pregnancies complicated by preeclampsia. Study design This prospective case-control study included 43 pregnant women diagnosed with preeclampsia and 45 normotensive controls. Maternal and umbilical cord blood samples were collected at the time of delivery to measure glucose and triglyceride levels. TyG index was calculated for both maternal and cord blood. Neonatal outcomes including Apgar scores, NICU admission, and composite neonatal morbidity were recorded. ROC analysis was performed to assess the predictive accuracy of TyG indices. Results Maternal and cord blood TyG indices were significantly higher in the preeclampsia group compared to the control group (p < 0.001). ROC analysis revealed that a cord blood TyG index > 7.59 predicted composite adverse neonatal outcomes with 92% sensitivity and 72% specificity (AUC: 0.853, 95% CI: 0.74–0.96, p < 0.001). NICU admission rates and low Apgar scores were more frequent in the preeclampsia group, indicating a significant association between elevated TyG indices and adverse neonatal outcomes. Conclusion The TyG index, particularly when measured in umbilical cord blood, may serve as a useful predictor of adverse neonatal outcomes in pregnancies affected by preeclampsia. This easily accessible metabolic marker could support perinatal risk stratification and clinical decision-making.

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 Interspecific interactions, including competition and predation, are key drivers of ecological systems. Understanding these interactions remains challenging in the wild as it requires quantifying their effects, particularly the non-consumptive effects (NCEs) driven by predation risk. We conducted a 7-month study in a semi-natural open bat colony, monitoring interactions between Egyptian fruit bats (Rousettus aegyptiacus) and black rats (Rattus rattus) competing for food, where rats also pose a potential predation risk to the bats. Results Video analysis revealed that bat responses to rats were fundamentally different from responses to conspecifics. The primary response was avoidance, with bat landings near food decreasing significantly when rats were present. For the 789 landings that did occur, bats showed increased vigilance and reduced foraging success, demonstrating clear NCEs. Crucially, bat foraging strategies were highly context-dependent, shifting with seasonal resource availability and rat abundance. During winter when rats were uncommon, the bats primarily employed predation risk-averse strategies (avoidance and vigilance). In spring, when rats were frequent, although there was clear temporal partitioning between the bat and the rat populations, some of the bats shifted to heterospecific interference competition, and occasionally attacked the rats to gain access to food—a behavior inconsistent with simple risk-aversion models. Conclusions Our findings demonstrate that the bat-rat interactions are dynamically modulated by resource availability, which alters rat presence and thereby the context-dependent interplay between interference competition and NCEs. This study provides rare quantitative evidence of how behaviorally flexible animals strategically manage interference competition and predation risk based on seasonal ecological conditions.

Background A significant proportion of individuals maintain cognition despite extensive Alzheimer’s disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals could reveal therapeutic targets for AD. Methods This study defines molecular and cellular signatures of cognitive resilience by integrating bulk RNA and single-cell transcriptomic data with genetics across multiple brain regions. We analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk RNA sequencing (n = 631 individuals) and multiregional single-nucleus RNA sequencing (n = 48 individuals). Subjects were categorized into AD, resilient, and control based on β-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole-genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition. Results Transcriptomics and polygenic risk analysis position resilience as an intermediate AD state. Only GFAP and KLF4 expression distinguished resilience from controls at tissue level, whereas differential expression of genes involved in nucleic acid metabolism and signaling differentiated AD and resilient brains. At the cellular level, resilience was characterized by broad downregulation of LINGO1 expression and reorganization of chaperone pathways, specifically downregulation of Hsp90 and upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. MEF2C, ATP8B1, and RELN emerged as key markers of resilient neurons. Excitatory neuronal subtypes in the entorhinal cortex (ATP8B+ and MEF2Chigh) exhibited unique resilience signaling through activation of neurotrophin (BDNF-NTRK2, modulated by LINGO1) and angiopoietin (ANGPT2-TEK) pathways. MEF2C+ inhibitory neurons were over-represented in resilient brains, and the expression of genes associated with rare genetic variants revealed vulnerable somatostatin (SST) cortical interneurons that survive in AD resilience. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. Conclusions We have defined molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preserved neuronal function, balanced network activity, and activation of neurotrophic survival signaling. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable interneurons likely provides compensation against AD-associated hyperexcitability. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

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 Depression is associated with multiple physical health conditions, and inflammation is a mechanism commonly proposed to explain this association. We aimed to investigate the association between depression and the incidence of physical health conditions thought to have an inflammatory etiological component, including coronary heart disease, peripheral arterial disease, type 2 diabetes, inflammatory bowel disease, inflammatory arthritis and Parkinson’s Disease. Methods We conducted a cohort study using UK Biobank (UKB) data linked to primary care, hospital admission and death data. We ascertained depression at baseline using primary care and hospital records, and self-report at the UKB baseline assessment. We identified incident physical health conditions during follow-up using primary care, hospital admission and death data. We used Cox proportional hazards models to determine hazard ratios of each incident inflammation-related condition in those with versus without depression at baseline, serially adjusting for sociodemographic factors, lifestyle factors and baseline count of morbidities. Result We included 172,556 UKB participants who had continuous primary care records. Of these, 30,770 (17.8%) had a history of depression at baseline. After excluding participants with missing data, 168,641 (98%) were included in analysis. Median follow-up was 7.1 years (IQR: 6.3, 8.0). In the model adjusted for age and sex, depression was significantly associated with a higher hazard of all inflammation-related conditions. After additionally accounting for differences in country, ethnicity and deprivation, the association between depression and each condition generally attenuated but remained statistically significant, with effect estimates ranging from a 30% increased hazard of inflammatory bowel disease (HR 1.30, 95% CI 1.06 to 1.58) to a 53% increased hazard of Parkinson's Disease (HR 1.53, 95% CI 1.25 to 1.87). After further adjusting for lifestyle factors and comorbidity count, the association persisted only for Parkinson's Disease (HR 1.45, 95% CI 1.18–1.79). Conclusions Our study found that depression is consistently associated with multiple inflammation-related physical health conditions, although associations did not persist after adjustment for lifestyle factors and baseline physical condition count. Further research is needed to explore underlying mechanisms, including inflammatory biomarkers and modifiable lifestyle factors on the causal pathway.

Background The relationship between the TyG index and MASLD in lean young populations remains unclear. Methods In this retrospective study, we analyzed data from individuals aged 18 to 35 Years old who underwent abdominal ultrasound examinations at a healthcare management center from January 2019 to December 2023. First, we categorized the TyG index into quartiles and used logistic regression models to examine the relationship between MASLD and TyG. Next, we applied restricted cubic splines (RCS) to assess whether the relationship between TyG and MASLD followed a nonlinear pattern. Additionally, we stratified the analysis by sex to explore whether the association between MASLD and TyG differed between males and females. Results A total of 20,242 participants (14763 women [72.9%]; [mean ± SD] age, 29.07 [3.60]) were included in the study. The overall incidence of MASLD was 5.1%. The median (IQR) TyG index was 8.0 (7.6, 8.2). The association between TyG index and the incidence of MASLD followed a reverse L-shaped, with a cut-off value of 8.3. For each 1-unit increase in the TyG index, the association was significant both below 8.3 (HR = 2.1; 95%CI: 1.4-3.4 ) and above this threshold (HR = 12.1; 95%CI: 8.2–17.8). A significant interaction between sex and the TyG index was observed (P < 0.001). Both males and females showing an increase in MASLD risk after the TyG index exceeded 8.3. Conclusion In young populations, higher TyG index is associated with an increased risk of MASLD, with distinct patterns observed between sexes. The risk of MASLD rises sharply once the TyG index exceeds 8.3.

Spinal cord injury (SCI) imposes a significant physical, social, and economic burden on millions of patients and their families worldwide. Although medical and surgical care improvements have decreased mortality rates, sustained recovery remains constrained. Cell-based therapies offer a promising strategy for neuroprotection and neuro-regeneration post-SCI. This article reviews the most promising preclinical approaches, encompassing the transplantation of embryonic stem cells (ESCs), mesenchymal stem cells (MSCs), neural stem cells (NSCs), oligodendrocyte progenitor cells (OPCs), Schwann cells (SCs), and olfactory ensheathing cells (OECs), along with the activation of endogenous pluripotency cell banking strategies. We also outline key ancillary strategies to enhance graft cell viability and differentiation, such as trophic factor assistance, engineered biomaterials for supportive scaffolds, and innovative methods for a synergistic effect in treatment, including promoting neuronal regeneration and reducing glial scars. We highlight the key aspects of SCI pathophysiology, the fundamental biology of cell treatments, and the advantages and limitations of each approach. Graphical abstract There are several approaches to treating spinal cord injuries that show great promise: Cellular therapies, which utilize a range of cells such as embryonic, neural, and mesenchymal stem cells, along with astrocytes, Schwann cells, olfactory ensheathing cells, and reprogrammed cells; The use of innovative biomaterials, including hydrogels, collagen, polycaprolactone fibers, and advanced 3D-printing technologies, provides valuable support for tissue repair.

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/4mX3Ck0 .