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PubMed2026

Tissue origins of the plasma proteomic response to glucose ingestion in humans.

AIMS/HYPOTHESIS: Circulating proteins act as important hormonal signals of nutrient intake. We aimed to systematically characterise the time-resolved proteomic response to glucose ingestion in humans, and to assess its robustness following prolonged complete caloric restriction. METHODS: We conducted oral glucose tolerance tests (OGTTs) in 11 healthy volunteers before and after 7 days of complete caloric restriction and measured the response of >2900 targets through high-resolution plasma protein profiling. RESULTS: We identified a signature of 44 proteins that changed significantly following glucose ingestion, which was reproducible after 7 days without food, and was strongly (20-fold) enriched for 'stomach-specific' proteins. We report that annexin A10 (ANXA10) shows the most significant post-glucose change observed, similar to the trajectories of secreted hormones. We present observational human evidence from multiple sources suggesting that ANXA10 is secreted upon sensing an increase in gastric pH, with the stomach as the major contributing tissue. Despite a profound metabolic shift after 7 days of complete caloric restriction, characterised by delayed insulin secretion and postprandial hyperglycaemia, only four proteins showed robust evidence for a differential trajectory during both OGTTs. This included plasma levels of tryptophanyl-tRNA synthetase 1 (WARS), for which we found a genetic association with glucose homeostasis and coronary artery disease. CONCLUSIONS/INTERPRETATION: Our exploratory study identifies the proteomic response to glucose ingestion and demonstrates its reproducibility despite major shifts in glucose homeostasis. We characterise the gastrointestinal origin of these changes, and hypothesise a hitherto under-recognised role for sensing of changes in gastric pH on the plasma proteome.

Humans↗

PubMed2026

Clinical Performance in Critical Care Simulation under Sleep Deprivation: Effects of Power Napping in the Recovery Napping Protocol for Anesthesiologist Performance (R-NAP) Randomized Controlled Trial.

BACKGROUND: Sleep deprivation is common among anesthesia residents and impairs both technical and nontechnical skills such as leadership. Napping is recommended in fatigue management across healthcare and other safety-sensitive sectors, yet its effectiveness for healthcare providers remains underexplored. This study evaluated whether a 30-min nap opportunity improved simulated crisis performance after a 24-h shift. METHODS: Residents were tested twice: once rested and once using a 24-h shift to induce partial sleep deprivation. Between sessions, they were trained in fatigue management. In the sleep-deprived condition, they were randomized to a nap opportunity or a control condition. Actigraphy objectively assessed sleep and nap duration. The primary endpoint was overall simulated clinical performance (0 to 200; combined technical and nontechnical scores). Secondary endpoints were technical and nontechnical subscales. Group effects were primarily tested using intention-to-treat regression models adjusted for rested performance, previous sleep, and critical care experience. RESULTS: Thirty-five residents were enrolled (nap opportunity, n = 19; control, n = 16). In the primary analysis sample (n = 27), clinical performance was 14.8 points higher after the nap opportunity compared with controls (95% CI, 2.8 to 26.9; P = 0.018), corresponding to a 7.4% improvement. Technical skills did not differ significantly between groups, although more sleep was associated with better technical performance. Nontechnical skills were higher in the nap opportunity condition (+11.0 points; 95% CI, 2.2 to 19.8; P = 0.016), including significant effects of leadership and resource utilization. Exploratory analyses suggested associations between longer nap duration and multiple performance domains, strongest for technical skills ( P = 0.010). CONCLUSIONS: Napping appears to enhance clinical performance, while the nap opportunity, nap duration, and previous sleep deprivation each influenced technical and nontechnical performance in distinct ways. These findings support integrating napping and recovery into medical education and scheduling.

Adult↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Origins and timing of somatic variants in the brain.

Somatic variants accumulate in human brain cells throughout the lifespan. Variant allele fraction has traditionally been used as a proxy for both the developmental timing of somatic variants and their functional effect, based on the assumption that earlier mutations are shared by larger cell populations and therefore have greater potential for severe phenotypes. However, recent discoveries challenge this simplified model. Variables such as developmental bottlenecks, lineage restriction, and cellular and molecular context play critical roles in shaping the distribution and functional impact of somatic variants in the brain. These insights support a shift toward a context-dependent framework for interpreting somatic mosaicism.

Humans↗

PubMed2026

Spore-forming Clostridia as overlooked determinants of microbial risk in wastewater reuse systems.

Using treated municipal wastewater for crop irrigation is a key strategy to combat drought-induced water scarcity. However, current wastewater reclamation standards systematically underestimate risks from spore-forming pathogens. As highlighted in a recent minireview by A. Mrozinski, C. Le Maréchal, and E. Topp in Applied and Environmental Microbiology (92:e00173-26, 2026, https://doi.org/10.1128/aem.00173-26), Clostridioides difficile and Clostridium perfringens survive conventional disinfection, persist indefinitely in agricultural soils, and harbor critical antibiotic resistance genes. To safeguard the food supply and protect public health, regulatory frameworks must shift from relying solely on standard vegetative bacterial indicators and include monitoring resilient, spore-forming pathogens.

Clostridium↗

PubMed2026

Somatic mutations: recent advances in brain aging and neurodegeneration.

Somatic mutations are genetic variants that occur after the single-cell phase of development and have been implicated in disease pathogenesis. While most DNA lesions are detected and repaired, examination of healthy tissue has revealed that some lesions escape repair, leading to somatic mutations that accumulate at a consistent rate, including in human brain tissue and postmitotic neurons. Emerging methodological and analytical advances have revealed the presence of persistent mutagenic mechanisms during healthy brain aging as well as mutational pattern shifts in the context of neurodegenerative diseases. Here, we highlight recent methodological advances, summarize our current understanding of somatic mutagenesis in neurotypical brain aging, and examine the role of somatic mutations in neurodegenerative diseases.

Humans↗

PubMed2026

Risk Factors and Predictive Model for Postoperative High Myopia in Children Undergoing Congenital Cataract Surgery With Intraocular Lens Implantation.

PURPOSE: To identify risk factors associated with the development of high myopia following congenital cataract surgery and to establish a robust predictive model. DESIGN: Retrospective clinical cohort study. SUBJECTS: This retrospective study included 106 pediatric patients who underwent congenital cataract surgery with primary IOL implantation (mean follow-up 8.19 years). The model was externally validated in an independent cohort of 72 patients with a mean follow-up of 7.83 years. METHODS: Preoperative and postoperative ocular biometric parameters were collected. Risk factors for postoperative high myopia were analyzed using Cox proportional hazards regression, which served as the basis for model construction. The predictive performance of the model was rigorously evaluated for discrimination and calibration. Discriminative ability was quantified using Harrell's C-index and the area under the receiver operating characteristic curve (AUC). Model calibration was assessed via calibration plots by comparing predicted probabilities with actual observed outcomes. Internal validation was performed using a bootstrapping method (500 iterations) to ensure model stability and adjust for potential overfitting. RESULTS: An initial postoperative refraction of <+0.75D, and a higher IOL Power to Axial length Ratio (IOL/AL ratio) were identified as significant risk factors for the development of postoperative high myopia. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. The predictive model demonstrated robust performance, achieving a C-index of 0.711 (internal validation C-index: 0.713). The area under the receiver operating characteristic curve (AUC) values for predicting high myopia at 5 and 10 years were 0.858 and 0.745, respectively. Furthermore, calibration curves demonstrated excellent agreement between the predicted and observed outcomes throughout the follow-up period. In external validation, the model achieved a C-index of 0.825, 5-year AUC of 0.833, and 10-year AUC of 0.713. CONCLUSIONS: Our analysis established that initial postoperative refraction <+0.75D, and an elevated IOL/AL ratio are key determinants of high myopia risk following surgery. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. This predictive framework provides clinicians with a practical tool to optimize preoperative IOL selection and identify high-risk infants who require vigilant myopia prevention and balanced amblyopia management.

Humans↗

PubMed2026

Primary ACL Repair and Reconstruction in Isolated ACL Ruptures: Forgotten Joint Scores and the Association Between Residual Laxity and Joint Awareness.

BACKGROUND: Primary anterior cruciate ligament (ACL) repair has recently reemerged as a treatment option for carefully selected proximal ACL tears. However, evidence regarding patient-reported joint awareness and the relationship between postoperative laxity and joint awareness remains limited. PURPOSE: To compare joint awareness, clinical outcomes, and postoperative laxity between primary ACL repair and hamstring tendon autograft reconstruction in carefully selected patients with isolated ACL rupture, and to explore the association between residual laxity and postoperative joint awareness. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: This retrospective cohort study included 85 patients with isolated ACL rupture treated with either primary ACL repair (n = 26) or hamstring autograft reconstruction (n = 59), with a minimum follow-up of 24 months. Clinical outcomes, including visual analog scale score, Lysholm score, International Knee Documentation Committee (IKDC) score, Tegner activity scale score, postoperative knee laxity, return to sport, and rerupture rates, were evaluated. The authors also used the Forgotten Joint Score-12 (FJS-12), a measure of joint awareness, to evaluate patients. A higher score reflects lower joint awareness, suggesting function more similar to a native knee. Multivariable regression analyses were performed to evaluate variables associated with postoperative FJS-12 values. RESULTS: No differences were observed between groups in postoperative Lysholm, IKDC, and Tegner activity scale scores; Lachman- and pivot-shift-assessed postoperative laxity; and return-to-sport rates. However, postoperative FJS-12 values were significantly higher in the repair group compared with the reconstruction group (87.0 ± 15.0 vs 77.5 ± 14.2; mean difference, 9.5 points [95% CI, 2.8-16.3]; P = .006), corresponding to a moderate effect size (Cohen d = 0.66). Secondary exploratory regression analyses demonstrated that residual postoperative laxity was associated with lower postoperative FJS-12 values in both Lachman- and pivot-shift-based models (R2 = 0.649 and 0.680, respectively; P < .001 for both). CONCLUSION: In carefully selected patients with proximal ACL tears and adequate tissue quality, no significant between-group differences were detected in conventional clinical outcomes, postoperative laxity, return-to-sport rates, or rerupture rates between primary ACL repair and reconstruction. Primary ACL repair was associated with higher postoperative FJS-12 values at short- to midterm follow-up, suggesting function more similar to that of a native knee. Residual postoperative laxity was associated with lower FJS-12 values in secondary exploratory analyses.

Humans↗

PubMed2026

Delayed maturation of the milk microbiome in women with type 1 diabetes.

AIMS/HYPOTHESIS: The breastmilk microbiome plays a crucial role in gut microbial colonisation and immune development, but little is known about how it is influenced by type 1 diabetes. METHODS: We conducted a longitudinal 16S rRNA gene sequencing study of milk from women with type 1 diabetes (n=69 pregnancies; 174 samples) and women who did not have type 1 diabetes (n=49 pregnancies; 123 samples), collected at seven timepoints from birth to 15 months postpartum. Alpha diversity (richness, inverse Simpson evenness) was analysed by generalised linear mixed models, beta diversity was analysed by Bray-Curtis dissimilarities and PERMANOVA, and differential abundance was analysed by limma. Additionally, we examined associations with maternal genetic risk score (GRS), maternal HLA type, glycaemic management (HbA1c) and breastmilk secretory IgA (sIgA), and performed a parallel analysis for the infant stool microbiome. RESULTS: A significant interaction between type 1 diabetes status and timepoint was observed for alpha diversity, both richness (p=0.01) and inverse Simpson diversity (p=0.003), indicating distinct temporal trajectories between women with and without type 1 diabetes. In those without type 1 diabetes, richness increased significantly between birth and 1 week postpartum, but this early increase was delayed in women with type 1 diabetes to between 1 week and 3 months postpartum (p=0.002). Beta diversity analysis revealed earlier and more extensive compositional shifts in women without type 1 diabetes compared to those with type 1 diabetes. These differences persisted after adjusting for Caesarean delivery, BMI, parity and infant sex, and were not attributable to a delay in initiating breastfeeding. Taxa with delayed enrichment in women with type 1 diabetes included Streptococcus spp. and Rothia mucilaginosa, which metabolise human milk oligosaccharides to short-chain fatty acids to promote development of the infant's gut barrier and immune system. Maternal GRS, HLA, HbA1c or sIgA were not associated with milk microbiota diversity trajectories. In infant stool samples, alpha diversity did not differ between exposure groups, and showed no evidence of delayed maturation. Beta diversity revealed an early compositional shift between birth and 1 week postpartum only in infants born to women without type 1 diabetes. Similarly, significant taxonomic changes between birth and 1 week postpartum were detected only in infants born to women without type 1 diabetes, but with some taxa differing between exposure groups at 1 week. CONCLUSIONS/INTERPRETATION: Maternal type 1 diabetes is associated with delayed early maturation of the breastmilk microbiome. Early compositional differences in microbiota restructuring were also observed in the infant gut, partially mirroring the pattern in the milk microbiome; however, sustained differences in infant gut microbiota diversity were not detected. Further investigation could determine whether these changes affect development of the infant's gut and immune system.

Humans↗

PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗

PubMed2026

Algae-to-host horizontal gene transfer in Paramecium bursaria is associated with host adaptation during endosymbiosis.

Paramecium bursaria maintains a stable endosymbiosis with green algae, yet the evolutionary consequences of this association remain unclear. Here, we screened the host genome for algal-derived horizontally transferred genes (HTGs) using a lineage-aware workflow designed to detect horizontal gene transfer (HGT) between two defined lineages. We identified 16 candidate HTGs, including four putative newly transferred genes and 12 homologous transferred genes, most of which were functionally associated with redox homeostasis and metabolism. Five HTGs showed symbiosis-dependent expression. RNAi knockdown of GH32s and SATs reduced host proliferation, total cell area, and motility, while GH32s knockdown also reduced endosymbiont load. Duplication patterns suggest that most transfers may have occurred after the P. bursaria lineage diverged from the sampled Paramecium species but before its lineage-specific whole-genome duplication (WGD). The HTGs also showed host-associated shifts in GC content and gene length, while representative HTGs retained conserved domains and functional motifs. Together, our results support algae-to-host HGT in P. bursaria and suggest that some transferred genes may contribute to metabolic integration during endosymbiosis.

Gene Transfer, Horizontal↗

PubMed2026

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis↗

PubMed2026

Integrated widely targeted metabolomics and GC-IMS reveal dynamic flavor, nutritional, functional, and metabolic profiles in macadamia kernels during processing.

Different processing stages influence the color, flavor, and antioxidant activities of macadamia kernels. However, the biochemical mechanisms that occur during processing are not well known. This study integrated widely targeted metabolomics (UPLC-MS/MS) with GC-IMS to systematically characterize non-volatile and volatile compounds in macadamia kernels across key three sample groups: fresh kernels (FMN), low-temperature-dried kernels (DMN), and roasted kernels (BMN). A total of 622 non-volatile metabolites and 52 volatile compounds were identified. Low-temperature drying promoted the accumulation of phenolic acids and flavonoids, enhancing antioxidant capacity. Roasting degraded heat-sensitive nutrients but generated flavor compounds via Maillard reaction and lipid oxidation, shifting aroma from green to nutty notes. Nutritional assessment confirmed that roasting significantly reduced antioxidant activities and bile acid binding capacity. Pearson correlation analysis verified the key metabolite-antioxidant relationships. These findings provide critical insights into metabolic dynamics during nut processing and establish a scientific basis for optimizing thermal processing strategies.

Metabolomics↗

PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗

PubMed2026

To longevity and beyond: A systems view of aging and stress resilience.

Aging is a dynamic and time-dependent process characterized by progressive functional decline across biological systems. Key hallmarks, including genomic instability, telomere attrition, loss of proteostasis, mitochondrial dysfunction, and immunosenescence, have been widely described, each reflecting distinct yet interconnected mechanistic frameworks. Rather than acting in isolation, these processes arise from complex interactions among cellular stressors, impaired repair mechanisms, and the cumulative burden of maladaptive responses. This system-level perspective explains the inter-individual variability in aging trajectories. Centenarians represent an extreme and informative model of successful aging, in which the balance between damage accumulation and repair is shifted toward the maintenance of physiological function. Their exceptional longevity is supported by coordinated genetic, epigenetic, metabolic, and immunological adaptations that enhance resilience to age-related stressors. Here, we summarize the biological drivers and theoretical frameworks of aging within an integrative context, focusing on mechanisms associated with extended healthspan in centenarians. We also examine the contribution of major animal models, highlighting their complementary roles in elucidating conserved and species-specific aging pathways. Overall, aging outcomes reflect a dynamic equilibrium between damage and repair processes. Understanding how this balance is modulated in long-lived individuals may inform strategies to promote healthy aging and delay the onset of age-related diseases.

Humans↗

PubMed2026

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans↗

PubMed2026

Perioperative care for patients with opioid exposure and opioid use disorder: screening and treatment strategies.

PURPOSE OF REVIEW: The prevalence of opioid tolerance, dependence, and use disorder is increasing among patients presenting for surgical care, yet perioperative management strategies for these patients remain inconsistent. This review examines the impact of preoperative opioid exposure on surgical outcomes, the scope of untreated opioid use disorder (OUD) among surgical patients, and advances in clinical and systems-level approaches to perioperative care. RECENT FINDINGS: Preoperative opioid exposure independently predicts worse surgical outcomes, including higher opioid consumption, readmissions, complications, and mortality, in a dose-dependent manner. Perioperative opioid exposure predicts persistent opioid use after surgery, with the duration of exposure a stronger predictor of subsequent OUD than daily dose. Data-driven prescribing guidelines and structured opioid tapering reduce overprescribing without compromising pain control. Among surgical patients with diagnosed OUD, approximately two-thirds do not receive medications for opioid use disorder (MOUD), though treatment engagement and maintenance substantially improve outcomes. Evidence now clearly supports perioperative buprenorphine continuation over interruption. SUMMARY: Effective perioperative management of opioid-complex surgical patients requires systematic screening, evidence-based prescribing, MOUD continuation, and institutional infrastructure. The primary barrier is shifting from evidence generation to implementation.

Humans↗

PubMed2026

"Out of sync and overlooked" - Relationship between social jetlag and anxiety in adolescents: Systematic review and meta-analysis.

Anxiety is the most prevalent mental health difficulty in adolescence, a period characterised by a shift towards an eveningness chronotype that is not aligned with societal demands (i.e., school start times). Experiencing "social jetlag" (SJL), a discrepancy in weekday-weekend sleep timing, is proposed to be associated with increased anxiety. A PRISMA-compliant systematic review and meta-analysis was conducted to investigate the relationship between SJL and anxiety in adolescents (age range: 12-18 years). Systematic searches were conducted in PsycINFO, Web of Science, Embase, PubMed, MEDLINE, and ProQuest Dissertations & Theses Global on 14th November 2024 to retrieve empirical studies analysing the relationship between SJL and anxiety in 12-18-year-olds. A multi-level random-effect meta-analysis was conducted in R to estimate the magnitude of the association between SJL and anxiety. After screening 2,138 records, 18 studies were included in the systematic review, with 12 included in the meta-analysis (235,526 participants in total) and six in a narrative review. A small association was found between increased SJL and more severe anxiety (Fisher's z = 0.0614, 95% CI [0.0268, 0.0961], p = 0.0011). These findings highlight the importance of addressing behavioural strategies targeting healthy regular sleep as a tool to improve mental health in adolescence.

Adolescent↗