Spinal cord injury results in severe sensory and motor deficits, with a dramatic impact on lifespan and healthspan, due to the limited regenerative capacity of the central nervous system. Following the initial injury, glial scarring and extracellular matrix barriers prevent axonal regeneration, while secondary damage exacerbates inflammation and tissue loss. The gold standard treatment in the last decades is acute surgery and systemic drug administration. New technologies have been developed, such as stem cell therapies, or the combinatory use of biomaterials, nonetheless still offering limited recovery. Successful therapies must act directly on neurons, activating regenerative pathways, while simultaneously promoting a pro-regenerative environment. However, polymeric materials have, in recent years, shown a regenerative potential through a series of different processes, from promoting neural regeneration by supporting tissue repair and reducing inflammation, to local drug delivery mechanisms. In this work, we systematize the state-of-the-art, exploring recent advancements in polymer-based therapies for spinal cord injury, discussing their characteristics, limitations, and promising future applications.

Although endogenous neural stem cells represent a promising target for noninvasive spinal cord injury repair, inflammatory lesion environments frequently trigger their death. Our prior work identified necroptosis as a key death pathway for endogenous neural stem cells migrating to spinal cord injury lesions. Rapamycin-insensitive companion of mTOR (Rictor; a core component of the mechanistic target of rapamycin complex 2 [mTORC2] complex) regulates neural stem cell self-renewal and differentiation, and our preliminary data implicate it in spinal cord injury repair; however, its role in promoting endogenous neural stem cell survival post-spinal cord injury remains unclear. Here, we generated conditional endogenous neural stem cell-specific Rictor knockout mice using the Cre-loxP system. Although the endogenous neural stem cell-specific Rictor knockout mice displayed normal baseline spinal cord morphology and function, they exhibited impaired functional recovery after spinal cord injury compared with wild-type controls. This deficit correlated with elevated inflammatory responses and the increased susceptibility of endogenous neural stem cells to necroptosis. Mechanistically, lentiviral-mediated Rictor knockdown in neural stem cells in vitro impaired lysosomal function, leading to heightened sensitivity to tumor necrosis factor-alpha- and lipopolysaccharide-induced necroptosis. Collectively, these findings indicate that Rictor/mTORC2 signaling protects endogenous neural stem cells against receptor-interacting protein kinase 1-mediated necroptosis following spinal cord injury. Consequently, the modulation of intrinsic Rictor activity represents a potential therapeutic strategy to enhance endogenous neural stem cell survival and functional recovery post-spinal cord injury.

Although many previous studies have highlighted the advances in prediction models, instruments for pathological and histological diagnosis and treatment, as well as individualized treatment modalities in mental disorders, these previous syntheses usually study the research outcomes separately and ignore the holistic integration of research regarding artificial intelligence technological approaches, data sets used and applications in mental health research. We used the BioBERT pretrained language model to systematically extract relevant information and develop an extensive knowledge graph that includes 3158 entities connected with 3248 different relationships. Our knowledge graph delineates essential artificial intelligence technological frameworks and explicitly maps out the relationships linking artificial intelligence methods, mental disorders, and diverse data modalities. The synthesis, centered on the analytical axis of "method-disease-data," highlights key research areas where artificial intelligence and neuropsychiatry meet. Specifically, it focuses on key applications in early detection, improved accuracy of diagnosis, and individualized therapeutic interventions. In addition, we summarized the applications derived from basic research findings that extend to ongoing clinical trials, revealing the path toward future clinical application in psychiatric work. Importantly, the research paid special attention to the application of artificial intelligence in identifying key brain regions and neural circuits, providing important clues for elucidating the neural mechanisms of mental disorders and developing targeted interventions. Although artificial intelligence presents great opportunities, there are also significant challenges, including imbalanced data sets, ethical issues, and clinical concerns about trustworthiness and transparency. Strategies to address these challenges are proposed, and a perspective on emerging methods enabled by artificial intelligence is provided, which are expected to greatly change the management and treatment of the future.

Ferroptosis constitutes a pivotal pathological event following spinal cord injury and presents substantial challenges to the restoration of neurological function. Cystine-glutamate transporter SLC7A11 is essential for maintaining cellular redox homeostasis and resisting ferroptosis. However, the mechanisms underlying neuronal ferroptosis caused by SLC7A11 downregulation following spinal cord injury remain unclear. Herein, we provide evidence that tumor protein 53, a negative regulator of SLC7A11, was significantly upregulated post-spinal cord injury. Transcriptomic analysis indicated that tumor protein 53 was associated with injury severity. We subsequently confirmed that tumor protein 53 inhibition restored the expressions of SLC7A11 and glutathione peroxidase 4, alleviated neuronal ferroptosis, and improved neurological function in a contusion spinal cord injury rat model. The regulatory effects of tumor protein 53 on the transcription and ubiquitination of SLC7A11 were further elucidated using chromatin immunoprecipitation polymerase chain reaction and cleavage under targets and tagmentation techniques. Additionally, Kelch-like protein 4, an E3 ubiquitin ligase adaptor, was demonstrated to play an important role in the tumor protein 53-mediated ubiquitination of SLC7A11. In summary, the present study elucidated the possible mechanisms of tumor protein 53-mediated neuronal ferroptosis in spinal cord injury, thereby providing potential targets and insights for clinical translation.

Growing evidence suggests that abnormal lipid metabolism occurs in amyotrophic lateral sclerosis, even in the presymptomatic stage, implying an etiologic link. However, the genetic mechanism underlying altered lipid levels in amyotrophic lateral sclerosis remains elusive. Therefore, in this study, we performed genetic correlation analysis, a cross-trait meta-analysis, tissue-specific enrichment analysis, and bidirectional two-sample Mendelian randomization analysis of European population to explore whether there is a genetic and causal relationship between lipids and amyotrophic lateral sclerosis. The effect of lipid-lowering drugs on amyotrophic lateral sclerosis was also evaluated using a drug target Mendelian randomization approach. The results showed a positive genetic correlation between amyotrophic lateral sclerosis and both high-density lipoprotein cholesterol and apolipoprotein A1 and identified 71 independent shared loci between amyotrophic lateral sclerosis and high-density lipoprotein cholesterol, as well as 55 independent shared loci between amyotrophic lateral sclerosis and apolipoprotein A1. These shared loci were enriched in the lipid metabolic pathway and the alcohol metabolic pathway. Further Mendelian randomization analysis targeting lipid-lowering drugs showed that single nucleotide polymorphisms within the ACLY and PCSK9 genes had a protective effect against amyotrophic lateral sclerosis risk by decreasing low-density lipoprotein cholesterol. The combination of ACLY and PCSK9 inhibitors has a greater protective effect on amyotrophic lateral sclerosis risk than that of PCSK9 inhibitors alone. In summary, there is a common genetic structure between lipids and amyotrophic lateral sclerosis. Mendelian randomization analysis supports an association between elevated blood lipids and the risk of developing amyotrophic lateral sclerosis, and the use of ACLY or PCSK9 inhibitors may improve disease prognosis.