EBioMedicine最新文献

Background: Tocilizumab, an interleukin-6 receptor inhibitor, is a promising cytoprotective agent selected by the Stroke Preclinical Assessment Network. It showed a protective effect on infarct volume and functional outcomes in animal stroke models.

Methods: In this investigator-initiated, multicentre, randomised, double-blind, placebo-controlled trial, patients with acute ischaemic stroke undergoing EVT were recruited. Eligible patients were randomly assigned (1:1) to receive tocilizumab or placebo treatment. Both patients and investigators were blinded to the treatment assignments. A single dose of tocilizumab (240 mg) or placebo was administered intravenously as soon as possible within 24 h after stroke onset and within 1 h after randomisation. The primary efficacy outcome was the change in infarct volume from baseline (before EVT and start of study drug) to 72 h. Primary and safety analyses were done in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT06238024.

Findings: A total of 108 patients were enrolled (n placebo = 57; n tocilizumab = 51). The median change in infarct core volume between baseline and 72 h was 27.0 mL (7.6-62.4) in the placebo group and 8.8 mL (IQR 3.4-20.6) in the tocilizumab group (adjusted mean difference in cubic root volume [ml^1/3] -0.41, 95% CI -0.79 to -0.03, P = 0.04, wald-type test). Symptomatic intracranial haemorrhage occurred in 7 (12%) patients in the placebo group and 3 (6%) patients in the tocilizumab group. The incidence of all-cause death and serious adverse events were similar between the two groups.

Interpretation: Among patients with acute ischaemic stroke undergoing endovascular treatment, tocilizumab tended to reduce infarct volume growth at 72 h post-treatment and is well tolerated. Future trials are necessary to confirm the beneficial effect of tocilizumab on long-term functional outcome following stroke.

Funding: Noncommunicable Chronic Diseases-National Science and Technology Major Project, Beijing Nova Program, National Natural Science Foundation of China, Beijing Natural Science Foundation.

Sleep problems commonly coexist with chronic pain conditions, with growing evidence that they may precede and contribute to pain persistence. Meanwhile, pain itself can disturb sleep, creating a bidirectional relationship. In this narrative review we explore how the sleep-pain relationship changes across the lifespan. In childhood and adolescence, poor sleep may predict the emergence of pain, possibly through neurodevelopmental impacts on pain modulation and affective regulation. In adulthood, sleep interacts with lifestyle, psychological state and occupational stressors to shape pain risk. In older adults, chronic pain and comorbidities such as sleep apnoea and depression may further impair sleep quality, reinforcing a vicious cycle. Across all stages, shared mechanisms, such as hypothalamic-pituitary-adrenal axis dysregulation, neuroinflammation, and impaired glymphatic clearance may contribute to this interplay. Recognising early sleep disturbance as a modifiable risk factor for later pain offers opportunities for prevention, while improving sleep may reduce the impact of established chronic pain.

Background: Community health workers (CHWs) play a vital role in identifying patients within the community. To enhance their decision-making and reduce unnecessary referrals, Rwanda introduced a digital integrated disease screening tool (d-IDS), embedded within the national community Electronic Medical Records (cEMR) system. This study aimed to design, integrate, and evaluate the d-IDS to support its broader national scale-up.

Methods: This study employed a pre-post effectiveness-implementation hybrid design to implement the d-IDS and evaluate its effectiveness in improving patient management at the community level in five districts during April-July 2024. The d-IDS was designed into a single decision-support workflow embedded within the cEMR platform, and deployed on CHWs' smartphones. The workflow automatically guides CHWs through case registration, symptom assessment, diagnostic testing, and treatment or referral decisions. The d-IDS tool consolidated the screening processes for tuberculosis, malaria, pneumonia, and diarrhoeal diseases. Referral data extracted from the cEMR following d-IDS implementation and retrospective data from similar period (April-July 2023) collected under the paper-based approach; Standard of Care (SOC), were analysed using Chi-square tests. Qualitative feedback from CHWs were gathered through structured interviews to assess acceptability and feasibility.

Findings: The implementation of d-IDS led to a statistically significant 24.2% reduction in overall referrals to health facilities (p < 0.0001) when compared to the SOC period. Of the 3060 individuals screened using the d-IDS, 45.6% triggered further assessment, and 1687 (55.1%) were successfully managed by CHWs at the community level. Notably, in Rwamagana district, referral rates dropped from 79.8% to 32.5%, a 59.2% reduction (p < 0.0001). CHWs reported that d-IDS improved workflow efficiency, data accuracy, and decision-making compared to the paper-based approach, especially with features like offline functionality and symptom-guided screening protocols.

Interpretation: The findings confirm that d-IDS is both feasible and acceptable for CHW use in community settings. It improves community-based patient management and reduces the burden on health facilities. However, close follow-up mechanisms are necessary to ensure early detection of any worsening conditions. These promising results support the future national rollout of d-IDS as a scalable solution to strengthen primary healthcare and CHW-led service delivery.

Funding: The study received financial support from the United Kingdom (FCDO 40105983), Canada (DFATD 7429348) and Germany (BMZ ACT Accelerator support 25.04.2022).

Background: The association and mechanisms between biotin and dementia remain unclear.

Methods: We investigated the association through a population and animal study. UK Biobank data were used to evaluate the association of biotin with incident dementia and brain structural alteration. To validate our findings, we established a biotin-deficient mouse model, and performed behavioural tests, immunofluorescence, RT-qPCR, Western blotting, and molecular docking.

Findings: In humans, higher biotin intake was significantly associated with reduced risks of all-cause dementia (moderate: 0.83 [0.74-0.94]; high: 0.78 [0.68-0.89]), Alzheimer's disease (AD, moderate: 0.74 [0.61-0.89]; high: 0.79 [0.64-0.98]), and delayed-onset dementia (DOD, moderate: 0.810 [0.715-0.918]; high: 0.776 [0.672-0.896]), but not vascular dementia (VD) and early-onset dementia (EOD). Neuroimaging results revealed a "pseudo-atrophy" pattern-reduced cortical volume with increased tissue intensity-resembling structural remodelling rather than neurodegeneration. In mice, biotin deficiency triggered region-specific alteration of APP, PSEN1, and APOE in the hippocampus and prefrontal cortex. It was accompanied by elevated Aβ42 levels and an increased Aβ42/40 ratio. Molecular docking suggested that biotin physically interacts with the catalytic pocket of PSEN1 and the receptor-binding domain of APOE.

Interpretation: Dietary biotin is associated with a lower risk of dementia, especially AD, potentially by inhibiting amyloidogenic processing and modulating APOE-mediated clearance. The observed neuroimaging and molecular patterns suggest that maintaining adequate biotin intake is a viable strategy for dementia prevention.

Funding: This work was supported by the National Natural Science Foundation of China (No. 82273619).

Background: Exploitation of the sodium iodide symporter (NIS) has potentially broad clinical application across different tumour ablative settings but often fails in aggressive cancer due to diminished transport activity. We aimed to discover whether enhancing NIS function by modulating proteostasis was targetable in vivo, as well as the clinical relevance to radioiodide (RAI) treatment of patients with cancer.

Methods: We used 3D modelling, iterative design, reformulation, RAI uptake, RNA-Seq, cell surface biotinylation assays and NanoBRET in transformed cell lines and primary thyroid cells from patients to identify new drugs targeted at enhancing NIS function and to uncover their respective mechanisms. Systemic drug responses were monitored via ^99mTc pertechnetate gamma counting and SPECT/CT imaging in wild-type BALB/c and Tg-rtTA/tetO-BRAF^V600E mice, as well as orthotopic NOD.Cg-Prkdc^scid Il2rg^tm1Wjl/SzJ (NSG) breast cancer.

Findings: Copper diethyldithiocarbamate (Cu(DDC)₂), a metabolite of the FDA-approved drug disulfiram, modulated NIS function in thyroid and breast cancer cells (P < 0.05). Mechanistically, Cu(DDC)₂ elicited a dual effect on NIS function, targeting valosin containing protein (VCP)-a key regulator of proteostasis-as well as inducing potent transcriptional responses (P < 0.05). In mice, the copper-bound metabolite stimulated NIS activity in normal thyroid tissue, thyroid tumours and in breast orthotopic tumours (P < 0.05), the latter augmented by the histone deacetylase inhibitor vorinostat (SAHA). Notably, there was clinical association of drug-perturbed genes in RAI-treated thyroid cancer, enabling construction of a robust dual risk score classifier for predicting recurrence (AUC >0.95; P < 0.001).

Interpretation: Our findings reveal a mechanistic pathway towards enhancing radionuclide uptake in vivo, with clinical relevance for RAI therapy and identifying survival indicators of recurrent disease.

Funding: This work was funded by the U.S. Department of Defense (BC201532P1), Medical Research Council (CiC/1001505 and MR/Z504828/1), British Thyroid Foundation (1002175). We further acknowledge support from the Wellcome Trust and EPSRC funded Centre for Medical Engineering at King's College London (203148/Z/16/Z), the Wellcome Multiuser Equipment Radioanalytical Facility (212885/Z/18/Z), and the EPSRC programme for Next Generation Molecular Imaging and Therapy with Radionuclides (EP/S019901/1).

Background: Lung cancer is mainly diagnosed in elderly adults, yet the incidence of early-onset disease in people aged ≤45 years is increasing. Current screening strategies largely target elder populations, leaving younger individuals at risk of delayed diagnosis and adverse outcomes. Phenotypic Age Acceleration (PhenoAgeAccel), which indicates the difference between biological age and chronological age, has been associated with cancer susceptibility, but its role in early-onset lung cancer is unclear.

Methods: We performed a case-control and prognostic cohort study in China, including 222 early-onset lung cancer patients and 222 age- and sex-matched healthy volunteers, and externally validated findings in the UK Biobank. PhenoAgeAccel was calculated from routinely available haematological and biochemical markers. Logistic regression models estimated associations between PhenoAgeAccel and lung cancer risk. Survival analyses assessed the relationship between PhenoAgeAccel and overall survival among early-onset patients.

Findings: Early-onset lung cancer patients had substantially higher PhenoAgeAccel than matched controls (P < 0.001). PhenoAgeAccel was associated with a dose-dependent increase in early-onset lung cancer risk (odds ratio [OR] = 1.18; 95% CI: 1.14-1.23). Subgroup analyses by chronological age demonstrated a stronger association in earlier adulthood, whereas associations among elder adults (≥65 years) were not significant. In early-onset patients, higher PhenoAgeAccel predicted worse overall survival (hazard ratio [HR] = 2.17; 95% CI: 1.20-3.93). Results were corroborated in the UK Biobank cohort.

Interpretation: PhenoAgeAccel is positively associated with both a greater risk of early-onset lung cancer and poorer prognosis, supporting its potential utility for early detection and risk stratification in younger populations.

Funding: National Natural Science Foundation of China (no. 82303969); Beijing Xisike Clinical Oncology Research Foundation (no. Y-2024AZ [EGFR]MS-0079); Beijing Natural Science Foundation (no. 7222144).

Background: Most gastric cancer (GC) patients receive uniform treatment due to the lack of predictive biomarkers for chemotherapy or radiotherapy. We previously identified epithelial-mesenchymal transition (EMT) and metabolism subgroups in GC cell lines based on kinomic profiles, but their clinical relevance was unknown.

Methods: We developed an ensemble model using 37 kinases that differed between cell line subgroups to classify stage II-IV GC into EMT and metabolism subgroups. Survival differences between those who received chemotherapy or radiotherapy and those who did not were compared within each subgroup to validate the model effectiveness in predicting therapeutic response. An iteration approach was further applied to optimise and validate the feature set via multiple publicly-available datasets.

Findings: An 11-kinase signature stratified 893 patients into two subgroups. The metabolism subgroup showed significantly better survival with chemotherapy (HR_{multivariable} = 0.56) and radiotherapy (HR_{multivariable} = 0.55), whereas no such improvement was observed in the EMT subgroup. Significant interaction between kinomic subgroups and treatments were noted. The chemotherapy benefits between subgroups were greater with 5-fluorouracil-based regimens than cisplatin-based ones. This kinomic taxonomy was distinct from Lauren classification and previous transcriptomic subtypes and also suggested differential therapeutic vulnerabilities between subgroups.

Interpretation: This model holds promise for optimising chemotherapy and radiotherapy decisions for GC.

Funding: Biomedicine Discovery Scholarship and Graduate Research Completion Award, Monash University; National Natural Science Foundation of China (81602165) (C.H.). Australian Research Council Centre of Excellence for the Mathematical Analysis of Cellular Systems (CE230100001) (L.K.N.).

Background: Early-life exposure to exogenous chemicals can disrupt neurodevelopment. Perfluorohexanesulfonic acid (PFHxS), a legacy PFAS widely used and detected globally, remains poorly studied for its neurotoxicity.

Methods: CD-1 mice (n = 90 dams) were exposed to human-relevant dose of PFHxS from gestational day (GD) 0-17. PFHxS levels were measured in maternal plasma and foetal/offspring medial prefrontal cortex (mPFC) (GD 18, postnatal weeks [PNW] 4 and 10) using liquid chromatography tandem mass-spectrometry (LC-MS/MS). Offspring social behaviour was assessed with the Three-Chamber social test. Neurotransmitters in mPFC of PNW 10 offspring were profiled by LC-MS/MS, transcriptomics was performed on GD 18 and PNW 4 mPFC, GABAergic neurons were quantified by immunofluorescence, and glutamate decarboxylase (GAD) expression by western blotting. PFHxS-GAD interactions were examined via molecular docking and microscale thermophoresis (MST).

Findings: Maternal plasma reached 5.1 ± 0.1 ng/mL, equivalent to human biomonitoring data, and PFHxS accumulated in foetal mPFC (68.1 ± 4.1 pg/g). PFHxS exposure induced social deficits at PNW 4 and 10, which were more pronounced in males. The mPFC of PFHxS exposed offspring exhibited an excitatory-tilted neurotransmitter profile, feature with reduced γ-aminobutyric acid (GABA, 90.6 ± 12.2 vs. 70.2 ± 4.3 μg/g, p = 0.008). The differentially expressed genes were enriched in GABAergic and synaptic signalling pathways. Despite unchanged percentage of GABAergic neuron and GAD expression, metabolite GABA/glutamate ratio was attenuated, suggesting impaired GAD function. Both molecular docking and MST suggested moderate-to-strong binding affinity between PFHxS and GAD, affecting GABA synthesis.

Interpretation: Gestational PFHxS exposure at human-relevant levels impairs offspring social behaviour, likely via disruption of GAD-mediated imbalance in excitation/inhibition.

Funding: This work was provided by grants from the National Natural Science Foundation of China (82404221 and 82373586), Anhui Provincial Natural Science Foundation (2308085Y50 and 2408085QH275), Education Department of Anhui Province for Excellent Young Scientist (2022AH030076), and funding from Center for Big Data and Population Health of IHM (JKS2022020).