Objectives To evaluate the most up-to-date burden of traumatic brain injury (TBI) and spinal cord injury (SCI) and analyse their leading causes in different countries/territories. Design An analysis of Global Burden of Disease (GBD) data. Setting The epidemiological data were gathered from GBD Results Tool (1 January, 1990─31 December 2019) covering 21 GBD regions and 204 countries/ territories. Participants Patients with TBI/SCI. Main outcomes and measures Absolute numbers and age-standardised rates/estimates of incidence, prevalence and years lived with disability (YLDs) of TBI/SCI by location in 2019, with their percentage changes from 1990 to 2019. The leading causes (eg, falls) of TBI/SCI in 204 countries/territories. Results Globally, in 2019, TBI had 27.16 million new cases, 48.99 million prevalent cases and 7.08 million YLDs. SCI had 0.91 million new cases, 20.64 million prevalent cases and 6.20 million YLDs. Global age-standardised incidence rates of TBI decreased significantly by −5.5% (95% uncertainty interval −8.9% to −3.0%) from 1990 to 2019, whereas SCI had no significant change (−6.1% (−17.3% to 1.5%)). Regionally, in 2019, Eastern Europe and High-income North America had the highest burden of TBI and SCI, respectively. Nationally, in 2019, Slovenia and Afghanistan had the highest age-standardised incidence rates of TBI and SCI, respectively. For TBI, falls were the leading cause in 74% (150/204) of countries/territories, followed by pedestrian road injuries (14%, 29/204), motor vehicle road injuries (5%, 11/204), and conflict and terrorism (2%, 4/204). For SCI, falls were the leading cause in 97% (198/204) of countries/territories, followed by conflict and terrorism (3%, 6/204). Conclusions Global age-standardised incidence rates of TBI have decreased significantly since 1990, whereas SCI had no significant change. The leading causes of TBI/SCI globally were falls, but variations did exist between countries/territories. Policy-makers should continue to prioritise interventions to reduce falls, but priorities may vary between countries/territories.

Background: Aging is an influential risk factor for progression of both degenerative and oncological diseases of the bone. Osteosarcoma, considered the most common primary mesenchymal tumor of the bone, is a worldwide disease with poor 5-year survival. This study investigated the role of aging-/senescence-induced genes (ASIGs) in contributing to osteosarcoma diagnosis, prognosis, and therapeutic agent prediction.Methods: Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) were used to collect relevant gene expression and clinical data of osteosarcoma and paracancerous tissues. Patients were clustered by consensus using prognosis-related ASIGs. ssGSEA, ESTIMATE, and TIMER were used to determine the tumor immune microenvironment (TIME) of subgroups. Functional analysis of differentially expressed genes between subgroups, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVAs), was performed to clarify functional status. Prognostic risk models were constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. SCISSOR was used to identify relevant cells in osteosarcoma single-cell data for different risk groups. The effect of immunotherapy was predicted based on TIDE scores and chemotherapy drug sensitivity using CTRP and PRISM.Results: Three molecular subgroups were identified based on prognostic differentially expressed ASIGs. Immunological infiltration levels of the three groups differed significantly. Based on GO and KEGG analyses, differentially expressed genes between the three subgroups mainly relate to immune and aging regulation pathways; GSVA showed substantial variations in multiple Hallmark pathways among the subgroups. The ASIG risk score built based on differentially expressed genes can predict patient survival and immune status. We also developed a nomogram graph to accurately predict prognosis in combination with clinical characteristics. The correlation between the immune activation profile of patients and the risk score is discussed. Through single-cell analysis of the tumor microenvironment, we identified distinct risk-group-associated cells with significant differences in immune signaling pathways. Immunotherapeutic efficacy and chemotherapeutic agent screening were evaluated based on risk score.Conclusion: Aging-related prognostic genes can distinguish osteosarcoma molecular subgroups. Our novel aging-associated gene signature risk score can be used to predict the osteosarcoma immune landscape and prognosis. Moreover, the risk score correlates with the TIME and provides a reference for immunotherapy and chemotherapy in terms of osteosarcoma.

N¹-Methyladenosine (m1A) is an abundant modification of transcripts, plays important roles in regulating mRNA structure and translation efficiency, and is dynamically regulated under stress. However, the characteristics and functions of mRNA m1A modification in primary neurons and oxygen glucose deprivation/reoxygenation (OGD/R) induced remain unclear. We first constructed a mouse cortical neuron OGD/R model and then used methylated RNA immunoprecipitation (MeRIP) and sequencing technology to demonstrate that m1A modification is abundant in neuron mRNAs and dynamically regulated during OGD/R induction. Our study suggests that Trmt10c, Alkbh3, and Ythdf3 may be m1A-regulating enzymes in neurons during OGD/R induction. The level and pattern of m1A modification change significantly during OGD/R induction, and differential methylation is closely associated with the nervous system. Our findings show that m1A peaks in cortical neurons aggregate at both the 5’ and 3’ untranslated regions. m1A modification can regulate gene expression, and peaks in different regions have different effects on gene expression. By analysing m1A-seq and RNA-seq data, we show a positive correlation between differentially methylated m1A peaks and gene expression. The correlation was verified by using qRT-PCR and MeRIP-RT-PCR. Moreover, we selected human tissue samples from Parkinson’s disease (PD) and Alzheimer’s disease (AD) patients from the Gene Expression Comprehensive (GEO) database to analyse the selected differentially expressed genes (DEGs) and differential methylation modification regulatory enzymes, respectively, and found similar differential expression results. We highlight the potential relationship between m1A modification and neuronal apoptosis following OGD/R induction. Furthermore, by mapping mouse cortical neurons and OGD/R-induced modification characteristics, we reveal the important role of m1A modification in OGD/R and gene expression regulation, providing new ideas for research on neurological damage.

Spinal cord injury (SCI) has no effective treatment modalities. It faces a significant global therapeutical challenge, given its features of poor axon regeneration, progressive local inflammation, and inefficient systemic drug delivery due to the blood–spinal cord barrier (BSCB). To address these challenges, a new nano complex that achieves targeted drug delivery to the damaged spinal cord is proposed, which contains a mesoporous silica nanoparticle core loaded with microRNA and a cloaking layer of human umbilical cord mesenchymal stem cell membrane modified with rabies virus glycoprotein (RVG). The nano complex more readily crosses the damaged BSCB with its exosome‐resembling properties, including appropriate size and a low‐immunogenic cell membrane disguise and accumulates in the injury center because of RVG, where it releases abundant microRNAs to elicit axon sprouting and rehabilitate the inflammatory microenvironment. Culturing with nano complexes promotes axonal growth in neurons and M2 polarization in microglia. Furthermore, it showed that SCI mice treated with this nano complex by tail vein injection display significant improvement in axon regrowth, microenvironment regulation, and functional restoration. The efficacy and biocompatibility of the targeted delivery of microRNA by nano complexes demonstrate their immense potential as a noninvasive treatment for SCI.

The G protein–coupled bile acid receptor (GPBAR) is the membrane receptor for bile acids and a driving force of the liver–bile acid–microbiota–organ axis to regulate metabolism and other pathophysiological processes. Although GPBAR is an important therapeutic target for a spectrum of metabolic and neurodegenerative diseases, its activation has also been found to be linked to carcinogenesis, leading to potential side effects. Here, via functional screening, we found that two specific GPBAR agonists, R399 and INT-777, demonstrated strikingly different regulatory effects on the growth and apoptosis of non–small cell lung cancer (NSCLC) cells both in vitro and in vivo. Further mechanistic investigation showed that R399-induced GPBAR activation displayed an obvious bias for β-arrestin 1 signaling, thus promoting YAP signaling activation to stimulate cell proliferation. Conversely, INT-777 preferentially activated GPBAR-Gs signaling, thus inactivating YAP to inhibit cell proliferation and induce apoptosis. Phosphorylation of GPBAR by GRK2 at S310/S321/S323/S324 sites contributed to R399-induced GPBAR–β-arrestin 1 association. The cryoelectron microscopy (cryo-EM) structure of the R399-bound GPBAR-Gs complex enabled us to identify key interaction residues and pivotal conformational changes in GPBAR responsible for the arrestin signaling bias and cancer cell proliferation. In summary, we demonstrate that different agonists can regulate distinct functions of cell growth and apoptosis through biased GPBAR signaling and control of YAP activity in a NSCLC cell model. The delineated mechanism and structural basis may facilitate the rational design of GPBAR-targeting drugs with both metabolic and anticancer benefits.