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Abstract Background Nurses’ secondary traumatic stress, compassion satisfaction and posttraumatic growth are closely related, but for newly graduated nurses, there are few reports to evaluate the specific path between these three. The aim of this study was to investigate examine the mediating role of compassion satisfaction in secondary traumatic stress and posttraumatic growth among newly graduated nurses. Methods From March 2021 to May 2021, a total of 330 newly graduated nurses from five tertiary hospitals in China were enrolled, and asked to complete questionnaires regarding secondary traumatic stress, compassion satisfaction and posttraumatic growth. Descriptive statistics, independent-samples T-test, one-way analysis of variance (ANOVA), Pearson correlation analysis and structural equation model were used in this study. A STROBE checklist was used to report findings. Results The scores of secondary traumatic stress, compassion satisfaction and posttraumatic growth of newly graduated nurses were 27.11 ± 4.94 (score range: 10–50), 31.89 ± 6.22 (score range: 10–50) and 56.47 ± 20.41 (score range: 0-100), respectively. Additionally, structural equation modeling showed that compassion satisfaction mediated the relationship between secondary traumatic stress and posttraumatic growth with the partial mediating effect of 0.089. Conclusions Newly graduated nurses may experience moderate secondary traumatic stress, but their posttraumatic growth is at a low level, and compassion satisfaction significantly affects the relationship between the two. Nursing managers should strengthen psychological evaluation, and promote their posttraumatic growth by improving their level of compassion satisfaction.

Abstract Background Islet transplantation is used therapeutically in a minority of patients with type 1 diabetes (T1D). However, successful outcomes are hampered by early islet β-cell loss caused by immune rejection and autoimmunity. Recent studies have demonstrated that mesenchymal stromal cells can enhance islet function both in vitro and in vivo by secreting ligands that activate islet G-protein coupled receptors (GPCRs). Stromal cell-derived factor 1 (SDF-1) is an MSC-secreted GPCR ligand, whereas the suppressor of cytokine signaling 3 (SOCS3) is a negative regulator of STAT3-activating cytokines. Here, we determined whether improvement in islet function mediated by exogenous SDF-1 is impaired by SOCS3 in experimental models of T1D. Methods Isolated islets were cultured for 48 h with SDF-1. Cytokine-induced apoptosis was measured immediately. Islets from Socs3 −/− mice were pre-cultured with exogenous SDF-1 and transplanted underneath the kidney capsule of C57BL/6 mice with streptozotocin-induced diabetes. Blood glucose levels were monitored for 28 days. AMD3100, an antagonist of the SDF-1 ligand CXCR4, was administered subcutaneously to islet transplanted mice to inhibit CXCR4 before and after transplantation. Results SDF-1 protected islet cells from cytokine-induced apoptosis in vitro. SOCS3-knockout (KO) islets pretreated with SDF-1 were effective in reducing blood glucose in non-obese diabetic mice in vivo. We found that SDF-1 elicits localized immunosuppression in transplanted SOCS3-KO islets. Immunomodulation was observed when SOCS-KO islets were preconditioned with SDF-1. Gene expression and flow cytometric analyses revealed significantly decreased immune cell infiltration, inflammatory cytokines, and concomitant increases in FOXP3+ regulatory T cells, alternatively activated M2 macrophages, and dendritic cell phenotypes. Administration of AMD3100 impaired the SDF-1-mediated improvement in SOCS3-KO islet function and local immune suppression. Conclusion SDF-1 improves the function of islet grafts in autoimmune diabetes through regulation by CXCR4; however, the presence of SOCS3 reverses the protective effect of SDF-1 on islet grafts. These data reveal a molecular pathway that can elicit localized immunosuppression and delay graft destruction in transplanted islets.

To evaluate the efficacy of static and dynamic visual perception training combined with rigid gas permeable contact lens （RGPCL） in the treatment of one case of nystagmus complicated with ametropia，aiming to provide guidance for clinical treatment. Clinical data of one case of nystagmus complicated with ametropia treated with visual perception training combined with RGPCL were retrospectively analyzed. After 1-year treatment，bilateral best-corrected visual acuity was improved to 1.0，nystagmus and ametropia were effectively controlled，and fine stereopsis was obtained. Static and dynamic visual perception training combined with RGPCL has potential therapeutic value for nystagmus complicated with ametropia.

The vigorous development of two-dimensional (2D) materials brings about numerous opportunities for lithium-ion batteries (LIBs) due to their unique 2D layered structure, large specific surface area, outstanding mechanical and flexibility properties, etc. Modern technologies for production of 2D materials include but are not limited to mechanochemical (solid-state/liquid-phase) exfoliation, the solvothermal method and chemical vapor deposition. In this review, strategies leading to the production of 2D materials via solid-state mechanochemistry featuring traditional high energy ball-milling and Sichuan University patented pan-milling are highlighted. The mechanism involving exfoliation, edge selective carbon radical generation of the 2D materials is delineated and this is followed by detailed discussion on representative mechanochemical techniques for tailored and improved lithium-ion storage performance. In the light of the advantages of the solid-state mechanochemical method, there is great promise for the commercialization of 2D materials for the next-generation high performance LIBs.

Network dismantling is one of the most challenging problems in complex systems. This problem encompasses a broad array of practical applications. Previous works mainly focus on the metrics such as the number of nodes in the Giant Connected Component (GCC), average pairwise connectivity, etc. This paper introduces a novel metric, the accumulated 2-core size, for assessing network dismantling. Due to the NP-hard computational complexity of this problem, we propose SmartCore, an end-to-end model for minimizing the accumulated 2-core size by leveraging reinforcement learning and graph neural networks. Extensive experiments across synthetic and real-world datasets demonstrate SmartCore’s superiority over existing methods in terms of both accuracy and speed, suggesting that SmartCore should be a better choice for the network dismantling problem in practice.

Crop residue decomposition is an important part of the carbon cycle in agricultural ecosystems, and microorganisms are widely recognized as key drivers during this process. However, we still know little about how nitrogen (N) input and rhizosphere effects from the next planting season impact key straw-decomposing microbial communities. Here, we combined amplicon sequencing and DNA-Stable Isotope Probing (DNA-SIP) to explore these effects through a time-series wheat pot experiment with four treatments: 13C-labeled maize straw addition with or without N application (S1N1 and S1N0), and no straw addition with or without N application (S0N1 and S0N0). The results showed that straw addition significantly reduced soil microbial alpha diversity in the early stages. Straw addition changed microbial beta diversity and increased absolute abundance in all stages. Growing plants in straw-amended soil further reduced bacterial alpha diversity, weakened straw-induced changes in beta diversity, and reduced bacterial and fungal absolute abundance in later stages. In contrast, N application could only increase the absolute abundance of soil bacteria and fungi while having little effect on alpha and beta diversity. The SIP-based taxonomic analysis of key straw-decomposing bacteria further indicated that the dominant phyla were Actinobacteria and Proteobacteria, with overrepresented genera belonging to Vicinamibacteraceae and Streptomyces. Key straw-decomposing fungi were dominated by Ascomycota, with overrepresented genera belonging to Penicillium and Aspergillus. N application significantly increased the absolute abundance of key straw-decomposing microorganisms; however, this increase was reduced by the rhizosphere effect. Overall, our study identified key straw-decomposing microorganisms in straw-amended soil and demonstrated that they exhibited opposite responses to N application and the rhizosphere effect.

The unique topic of allocating and scheduling tasks on a single machine in a multitasking environment is the main emphasis of this research, which also takes into account the effects of worsening maintenance and job-dependent aging effects. In this scenario, the performance and efficiency of the machine in handling different tasks should be symmetric, without significant bias due to the nature or size of the tasks. In a multitasking environment, waiting for jobs can disrupt the processing of the primary job being currently handled. As a result, the actual time required to complete a task becomes erratic and contingent upon the duration of the disruption. In addition to figuring out the best time for maintenance, where to put the due-window, and how big it should be in a multitasking environment, the primary objective is to minimize the costs associated with meeting due-window regulations. To tackle this problem, we propose two optimal algorithms. Additionally, we conduct numerical experiments to compare our approach with the classic due date assignment problem. Interestingly, we observe that in most cases, the average and minimum percentage costs tend to increase as the quantity of jobs increases. However, it is noteworthy that, when the number of jobs is relatively small, specifically when it does not exceed 20, there are instances where these costs decrease with an increase in the number of jobs.

Abstract Background Nurses’ organizational citizenship behavior, a spontaneous “altruistic work behavior”, may be affected by psychological capital and organizational commitment, but its mechanism is not clear. The aim of this study was to investigate the characteristics and distribution of psychological capital, organizational commitment and organizational citizenship behavior among nurses during the COVID-19 epidemic, and explore the mediating role of organizational commitment in psychological capital and organizational citizenship behavior. Methods A cross-sectional survey was conducted among 746 nurses from 6 designated hospitals for COVID-19 treatment in China. Descriptive statistics, Pearson correlation analysis, and structural equation model were used in this study. Results Nurses’ psychological capital, organizational commitment and organizational citizenship behavior scores were 103.12 ± 15.57, 46.53 ± 7.14 and 101.47 ± 12.14, respectively. Additionally, organizational commitment partially mediates between psychological capital and organizational citizenship behavior. Conclusions During the COVID-19 pandemic, nurses’ psychological capital, organizational commitment, and organizational citizenship behavior were found to be at an upper-middle level, influenced by various social-demographic factors. Furthermore, the results illustrated that psychological capital can affect organizational citizenship behavior through the mediating role of organizational commitment. Therefore, the findings emphasize the importance of nursing administration to monitor and prioritize the mental health and organizational behavior of nurses during the ongoing COVID-19 crisis. It is crucial to focus on developing and nurturing nurses’ psychological capital, strengthening their organizational commitment, and ultimately promoting their organizational citizenship behavior.

Abstract Aim Nurses play roles in hospitals, families, society and other aspects and often face stress sources, such as heavy workload, doctor–patient conflict and medical accidents. Resilience can help the nurses to avoid or reduce various adverse consequences caused by stress sources; however, this phenomenon remains ill‐defined and under‐researched. The aim of this review was to summarize the experiences of development of nurses' resilience and explore the reasons for the formation of resilience by examining the findings of the existing qualitative studies. Design The review is a systematic review and meta‐synthesis of qualitative studies. Data Sources PubMed, Cochrane Library, CINAHL, Web of Science, Embase, and Ovid and Chinese databases include the following: Chinese National Knowledge Infrastructure (CNKI), Wanfang Database (CECDB), VIP Database and China Biomedical Database (CBM). Review Methods Relevant publications were identified by systematic searches across 11 databases in June 2021. All qualitative and mixed‐method studies in English and Chinese that explored the experiences of development of nurses' resilience were included. The qualitative meta‐synthesis followed the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) recommendations. Two independent reviewers selected the studies and assessed the quality of each study. Meta‐synthesis was performed to integrate the results. Results A total of nine studies revealed 10 sub‐themes and three descriptive themes: being psychologically strong, physical positive coping and adoption of external support. Conclusion Several factors contributed to the development of nurses' resilience, and various supporting strategies in the nursing management and education are helpful to their adaption ability. However, it is necessary to focus on the cultivation of nurses' resilience to improve the quality of clinical nursing. Leaders or organizations are required to establish and sustain multifaceted strategies to improve nurse’ resilience through scientific resilience training programmes and improved organizational support.

Abstract Osteoarthritis (OA) is characterized by the progressive deterioration of articular cartilage, involving complicated cell-matrix interactions. Systematic investigations of dynamic cellular and matrix changes during OA progression are lacking. In this study, we use label-free two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging to assess cellular and extracellular matrix features of murine articular cartilage during several time points at early stages of OA development following destabilization of medial meniscus surgery. We detect significant changes in the organization of collagen fibers and crosslink-associated fluorescence of the superficial zone as early as one week following surgery. Such changes become significant within the deeper transitional and radial zones at later time-points, highlighting the importance of high spatial resolution. Cellular metabolic changes exhibit a highly dynamic behavior, and indicate metabolic reprogramming from enhanced oxidative phosphorylation to enhanced glycolysis or fatty acid oxidation over the ten-week observation period. The optical metabolic and matrix changes detected within this mouse model are consistent with differences identified in excised human cartilage specimens from OA and healthy cartilage specimens. Thus, our studies reveal important cell-matrix interactions at the onset of OA that may enable improved understanding of OA development and identification of new potential treatment targets.

The fungal pathogen Setosphaeria turcica causes northern corn leaf blight (NCLB), which leads to considerable crop losses. Setosphaeria turcica elaborates a specialized infection structures called appressorium for maize infection. Previously, we demonstrated that the S. turcica triggers an S-phase checkpoint and ATR (Ataxia Telangiectasia and Rad3 related)-dependent self-protective response to DNA genotoxic insults during maize infection. However, how the regulatory mechanism works was still largely unknown. Here, we report a genome wide transcriptional profile analysis during appressorium formation in the present of DNA replication stress. We performed RNA-Seq analysis to identify S. tuicica genes responsive to DNA replication stress. In the current work, we found that appressorium-mediated maize infection by S. turcica is significantly blocked by S-phase checkpoint. A large serial of secondary metabolite and melanin biosynthesis genes were blocked in appressorium formation of S. turcica during the replication stress. The secondary metabolite biosynthesis genes including alcohol dehydrogenase GroES-like domain, multicopper oxidase, ABC-transporter families, cytochrome P450 and FAD-containing monooxygenase were related to plant pathogen infection. In addition, we demonstrated that autophagy in S. turcica is up-regulated by ATR as a defense response to stress. We identified StATG3, StATG4, StATG5, StATG7 and StATG16 genes for autophagy were induced by ATR-mediated S-phase checkpoint. We therefore propose that in response to genotoxic stress, S. turcica utilizes ATR-dependent pathway to turn off transcription of genes governing appressorium-mediated infection, and meanwhile inducing transcription of autophagy genes likely as a mechanism of self-protection, aside from the more conservative responses in eukaryotes.

Photosynthesis occurs mainly in chloroplasts, whose development is regulated by proteins encoded by nuclear genes. Among them, pentapeptide repeat (PPR) proteins participate in organelle RNA editing. Although there are more than 450 members of the PPR protein family in rice, only a few affect RNA editing in rice chloroplasts. Gene editing technology has created new rice germplasm and mutants, which could be used for rice breeding and gene function study. This study evaluated the functions of OsPPR9 in chloroplast RNA editing in rice. The osppr9 mutants were obtained by CRISPR/Cas9, which showed yellowing leaves and a lethal phenotype, with suppressed expression of genes associated with chloroplast development and accumulation of photosynthetic-related proteins. In addition, loss of OsPPR9 protein function reduces the editing efficiency of rps8-C182, rpoC2-C4106, rps14-C80, and ndhB-C611 RNA editing sites, which affects chloroplast growth and development in rice. Our data showed that OsPPR9 is highly expressed in rice leaves and encodes a DYW-PPR protein localized in chloroplasts. Besides, the OsPPR9 protein was shown to interact with OsMORF2 and OsMORF9. Together, our findings provide insights into the role of the PPR protein in regulating chloroplast development in rice.

Advances in spatial transcriptomics technologies have enabled the gene expression profiling of tissues while retaining spatial context. Here the authors present GraphST, a graph self-supervised contrastive learning method that learns informative and discriminative spot representations from spatial transcriptomics data.

The powerful combination of large-scale drug-related interaction networks and deep learning provides new opportunities for accelerating the process of drug discovery. However, chemical structures that play an important role in drug properties and high-order relations that involve a greater number of nodes are not tackled in current biomedical networks. In this study, we present a general hypergraph learning framework, which introduces Drug-Substructures relationship into Molecular interaction Networks to construct the micro-to-macro drug centric heterogeneous network (DSMN), and develop a multi-branches HyperGraph learning model, called HGDrug, for Drug multi-task predictions. HGDrug achieves highly accurate and robust predictions on 4 benchmark tasks (drug-drug, drug-target, drug-disease, and drug-side-effect interactions), outperforming 8 state-of-the-art task specific models and 6 general-purpose conventional models. Experiments analysis verifies the effectiveness and rationality of the HGDrug model architecture as well as the multi-branches setup, and demonstrates that HGDrug is able to capture the relations between drugs associated with the same functional groups. In addition, our proposed drug-substructure interaction networks can help improve the performance of existing network models for drug-related prediction tasks.

Heavy metal contamination from coal mining calls for advanced bioremediation, i.e., using sulfate-reducing bacteria (SRB) technology. Yet, the interaction of SRB with native soil microbiota during metal sequestration, especially in the presence of plants, remains ambiguous. In this study, we assessed the metal sequestration capabilities, ecological network interactions, and enzymatic functions in soils treated with a predominant SRB consortium, mainly Desulfovibrio (14 OTUs, 42.15%) and Desulfobulbus (7 OTUs, 42.27%), alongside Acacia dealbata (AD) and Pisum sativum (PS) plants. The SRB consortium notably enhanced the immobilization of metals such as Zn, Cu, As, and Pb in soil, with the conversion of metals to residual forms rising from 23.47 to 75.98%. Plant inclusion introduced variability, potentially due to changes in root exudates under metal stress. While AD flourished, PS demonstrated significant enhancement in conjunction with SRB, despite initial challenges. Comprehensive microbial analyses revealed the pivotal role of SRB in influencing microbial networking, underpinning critical ecological links. This interplay between plants and SRB not only enhanced microbial diversity but also enriched soil nutrients. Further, enzymatic assessments, highlighting enzymes like NADH:ubiquinone reductase and non-specific serine/threonine protein kinase, reinforced contribution of SRB to energy metabolism and environmental resilience of the entire soil microbial community. Overall, this research underscores the potential of SRB-driven bioremediation in revitalizing soils affected by coal mining.

Abstract Despite tremendous efforts that have been dedicated to high‐performance electrochemical energy storage devices (EESDs), traditional electrode fabrication processes still face the daunting challenge of limited energy/power density or compromised mechanical compliance. 3D thick electrodes can maximize the utilization of z‐axis space to enhance the energy density of EESDs but still suffer from limitations in terms of poor mechanical stability and sluggish electron/ion transport. Direct ink writing (DIW), an eminent branch of 3D printing technology, has gained popularity in the manufacture of 3D electrodes with intricately designed architectures and rationally regulated porosity, promoting a triple boost in areal mass loading, ion diffusion kinetics, and mechanical flexibility. This focus review highlights the fundamentals of printable inks and typical configurations of 3D‐printed devices. In particular, preparation strategies for high‐performance and multifunctional 3D‐printed EESDs are systemically discussed and classified according to performance evaluation metrics such as high areal energy density, high power density, high volumetric energy density, and mechanical flexibility. Challenges and prospects for the fabrication of high‐performance 3D‐printed EESDs are outlined, aiming to provide valuable insights into this thriving field.

BackgroundDermatomyositis (DM) is an autoimmune and inflammatory disease that can affect the lungs, causing interstitial lung diseases (ILD). However, the exact pathophysiological mechanisms underlying DM-ILD are unknown. Idiopathic pulmonary fibrosis (IPF) belongs to the broader spectrum of ILD and evidence shows that common pathologic pathways might lie between IPF and DM-ILD.MethodsWe retrieved gene expression profiles of DM and IPF from the Gene Expression Omnibus (GEO) and utilized weighted gene co-expression network analysis (WGCNA) to reveal their co-expression modules. We then performed a differentially expressed gene (DEG) analysis to identify common DEGs. Enrichment analyses were employed to uncover the hidden biological pathways. Additionally, we conducted protein-protein interaction (PPI) networks analysis, cluster analysis, and successfully found the hub genes, whose levels were further validated in DM-ILD patients. We also examined the relationship between hub genes and immune cell abundance in DM and IPF. Finally, we conducted a common transcription factors (TFs)-genes network by NetworkAnalyst.ResultsWGCNA revealed 258 intersecting genes, while DEG analysis identified 66 shared genes in DM and IPF. All of these genes were closely related to extracellular matrix and structure, cell-substrate adhesion, and collagen metabolism. Four hub genes (POSTN, THBS2, COL6A1, and LOXL1) were derived through intersecting the top 30 genes of the WGCNA and DEG sets. They were validated as active transcripts and showed diagnostic values for DM and IPF. However, ssGSEA revealed distinct infiltration patterns in DM and IPF. These four genes all showed a positive correlation with immune cells abundance in DM, but not in IPF. Finally, we identified one possible key transcription factor, MYC, that interact with all four hub genes.ConclusionThrough bioinformatics analysis, we identified common hub genes and shared molecular pathways underlying DM and IPF, which provides valuable insights into the intricate mechanisms of these diseases and offers potential targets for diagnostic and therapeutic interventions.

BackgroundImmune checkpoint inhibitors (ICIs) has emerged as a popular cancer treatment approach. However, non-specific activation of T cells by ICIs can lead to immune-related adverse events (irAEs), including specific rheumatic manifestations. The study aimed to explore the current trend of ICIs associated rheumatic irAEs and summarize the knowledge structure through bibliometric methods.MethodsThe Web of Science Core Collection database (WoSCC) was selected for retrieving literature on ICIs associated rheumatic irAEs. To evaluate contributions from different countries/regions, institutions, journals, and authors, bibliometric analysis software, including VOSviewer and CiteSpace, as well as bibliometric online platforms, were utilized to construct and visualize bibliometric networks. Through the systematic review of this knowledge domain, future research directions were determined.ResultsIn This study, a total of 803 publications on ICIs-associated rheumatic irAEs were included for analysis. The distribution of these publications revealed two distinct growth phases: a stable phase between 2007 to 2015 followed by rapid growth from 2016 to 2020. The United States emerged as the top contributor in terms of publications, citations, and h-index, with the majority of leading institutions and funding agencies located there. Apart from government funding, pharmaceutical companies such as Bristol Myers Squibb and Merck Company also play a significant role in drug development and research. Analysis of keywords and citation bursts indicated that the initial burst was related to “monoclonal antibody,” “anti-CLTA4 antibody,” and “melanoma”. This was followed by a rise in interest related to “sarcoidosis,” “safety,” “inflammatory arthritis,” and “preexisting autoimmune.”ConclusionThis study summarized the global research trends concerning ICIs associated rheumatic irAEs. The findings can provide valuable insights into the current understanding of rheumatic irAEs, highlight the research trend and developments in the field. Future efforts should focus on developing classification criteria and guidelines, conducting prospective studies, investigating the mechanisms involved, and identifying biomarkers for prediction and monitoring of these events.

BackgroundObservational studies have suggested that COVID-19 increases the prevalence of psychiatric disorders, but the results of such studies are inconsistent. This study aims to investigate the association between COVID-19 and the risk of psychiatric disorders using Mendelian randomization (MR) analysis.MethodsWe used summary statistics from COVID-19 Host Genetics Initiative genome-wide association study (GWAS) of COVID-19 involving 2,586,691 participants from European ancestry. Genetic variations of five psychiatric disorders including autism spectrum disorder (ASD) (N = 46,351), bipolar disorder (BID) (N = 51,710), major depressive disorder (MDD) (N = 480,359), anxiety disorder (N = 83,566), and schizophrenia (SCZ) (N = 77,096) were extracted from several GWAS of European ancestry. The inverse-variance weighted (IVW) method as the main MR analysis conducted. We further performed sensitivity analyzes and heterogeneity analyzes as validation of primary MR results.ResultsThe IVW analysis found that COVID-19 hospitalization phenotype was the risk factor for BID (OR = 1.320, 95% CI = 1.106–1.576, p = 0.002) and SCZ (OR = 1.096, 95% CI = 1.031–1.164, p = 0.002). Moreover, we detected a significant positive genetic correlation between COVID-19 severity and two psychiatric traits, BID (OR = 1.139, 95% CI = 1.033–1.256, p = 0.008) and SCZ (OR = 1.043, 95% CI = 1.005–1.082, p = 0.024). There was no evidence supporting the causal relationship between COVID-19 susceptibility and psychiatric disorders.ConclusionOur results found that the COVID-19 hospitalization phenotype and COVID-19 severity phenotype might be the potential risks of BID and SCZ in European populations. Therefore, patients infected with SARS-CoV-2 should have enhanced monitoring of their mental status.

We report the case of a 31-year-old Chinese woman with a chief complaint of weakness in the lower limbs, which was diagnosed as limb-girdle muscular dystrophy 2B (LGMD2B) with compound heterozygous mutations of the DYSF gene. Meanwhile, this woman is an asymptomatic carrier with the mutation of the X-linked DMD gene. The electromyography, muscle MRI, and muscle biopsy indicated a chronic myogenic injury with dysferlin deletion. As a result of genetic testing, compound heterozygous G-to-T base substitution at position 5,497 in exon 49 of the DYSF gene, leading to a codon change from glutamic acid to termination codon at position 1,833, and a heterozygous C-to-G base change at position 4,638 + 8 in intron 42 of the DYSF gene with a consequence of splice, which has never been reported, were identified as candidate causative mutations. Unfortunately, DMD gene mutation c.3921+12A>G of the DMD gene on the X chromosome was also found in this patient. Finally, the patient was diagnosed as LGMD2B clinically and genetically. In the previous 2 years, the patient's lower limb weakness became slightly worse, resulting in even the total distance walked than before. Fortunately, during the follow-up, her son had not shown slowness or limitation of movement. Genetic testing by next-generation sequencing confirmed the final diagnosis of LGMD2B, and we identified the novel compound heterozygous variants in the DYSF gene, which is of great significance to the accurate diagnosis of genetically coded diseases. Much attention needs to be paid in clinics toward hereditary neuromuscular diseases with multiple pathogenic gene mutations. Genetic counseling and clinical follow-up should be the priorities in future, and promising treatments are also worth exploring.

BackgroundThere is mounting evidence suggesting that autoimmune encephalitis (AE) can be observed as a neurological complication in patients with COVID-19. This review aimed to summarize the clinical manifestations, types, and outcomes of COVID-19-associated AE.MethodsA systematic search was conducted in the PubMed, Embase, and Web of Science databases to identify case reports and case series related to COVID-19-associated AE from 1 January 2020 to 31 March 2023. After a thorough screening and evaluation, irrelevant articles were excluded. Relevant information concerning types, clinical manifestations, and outcomes was extracted and synthesized.ResultsA total of 37 studies, comprising 34 case reports and 3 case series, were included in this review. Among the 42 COVID-19-associated AE patients, 21 (50%) cases were classified as an unknown antibodies (Ab) type of COVID-19-associated AE, 10 (23.80%) cases as anti-N-methyl-D-aspartate (NMDA) encephalitis, 4 (9.5%) cases as limbic encephalitis, and 3 (7.1%) cases as anti-myelin-oligodendrocyte-glycoprotein encephalitis, along with other rare types of AE. Disturbance of consciousness, seizures, and psychiatric symptoms were identified as the main clinical manifestations of COVID-19-associated AE. While the symptoms of AE displayed variation, most patients achieved full recovery although a few experienced residual symptoms of neurological damage.ConclusionThis systematic review comprehensively describes the characteristics of COVID-19-associated AE. The main type of COVID-19-associated AE identified in this study is an unknown Ab type of COVID-19-associated AE. Despite the potentially life-threatening risks of COVID-19-associated AE, the majority of patients survived, with some patients reporting residual neurological symptoms.