Background: Inflammation and immune dysregulation following ST-elevation myocardial infarction (STEMI) contribute to adverse remodelling and major adverse cardiac events (MACE). This study aimed to identify serum cytokine networks that predict 12-month MACE in STEMI patients, with a focus on IL-17A, VCAM-1, sIL-2R, IL-8, GATA1, IL-3, IL-5, and GM-CSF. Methods: A prospective cohort of 320 STEMI patients undergoing primary percutaneous coronary intervention (pPCI) was enrolled. Serum levels of 18 cytokines, including the eight prespecified markers, were measured at admission, 24 hours, and 72 hours post-pPCI. The primary endpoint was MACE (cardiac death, recurrent MI, heart failure hospitalisation, or target vessel revascularisation) at 12 months. Cytokine networks were analysed using partial correlation matrices and machine learning (LASSO regression). Results: MACE occurred in 71 patients (22.2%). A five-cytokine network comprising IL-17A, VCAM-1, sIL-2R, IL-8, and GATA1 at 24 hours post-pPCI most strongly predicted MACE (AUC 0.86, 95% CI 0.81-0.91). Elevated IL-17A (HR 2.45, p<0.001), VCAM-1 (HR 1.98, p=0.003), and sIL-2R (HR 2.12, p=0.001) were independent predictors. GATA1 was detectable in 62% of patients at 24 hours and correlated with infarct size (r=0.54, p<0.001). IL-3, IL-5, and GM-CSF showed significant univariable associations with MACE, but these associations did not remain independent after multivariable adjustment. Conclusion: A serum cytokine network comprising IL17A, VCAM-1, sIL-2R, IL-8, and GATA1 at 24 hours postpPCI robustly predicts MACE in STEMI. These findings support early immune profiling for risk stratification.

OBJECTIVES:Acute myeloid leukemia (AML), a heterogeneous hematopoietic malignancy, continues to present significant challenges in clinical management due to its unfavorable prognosis despite advances in therapy. The identification of novel molecular markers remains essential for improving prognostic stratification and guiding therapeutic decision-making. METHODS:ATXN1 expression, its prognostic significance, and associated immune infiltration patterns in AML were systematically evaluated using bioinformatic analyses of The Cancer Genome Atlas (TCGA) and independent validation cohorts. A prognostic nomogram incorporating ATXN1 expression was developed to estimate survival outcomes. The functional role of ATXN1 was further examined in vitro using proliferation and colony formation assays. RESULTS:ATXN1 expression was significantly downregulated in AML relative to normal hematopoietic cells (p < 0.001). Decreased ATXN1 expression was associated with inferior overall survival across multiple datasets (TCGA, p = 0.023) and was associated with prognosis in multivariate analysis adjusted for age and sex (p = 0.03). Gene set enrichment analysis identified pathways related to cysteine metabolism and immune regulation associated with ATXN1 expression. Immune profiling demonstrated a positive correlation between higher ATXN1 expression and monocyte infiltration (R = 0.42, p < 0.001), along with enhanced activity of immune cell populations, including macrophages, neutrophils, and dendritic cells. Functional assays demonstrated that ATXN1 overexpression suppressed proliferation and colony formation in AML cell lines. CONCLUSION:ATXN1 represents a potential prognostic marker in AML, with reduced expression associated with adverse clinical outcomes and transcriptomic features suggestive of immune-related alterations. Further investigation is needed to determine whether ATXN1-associated pathways represent viable therapeutic targets.

Objective:To study the genetic characteristics and clinical manifestations of a family with hereditary hemochromatosis(HH)type 4 caused by SLC40A1 c.G205A mutation.Methods:Clinical investigation and genetic testing were carried out on one hemochromatosis patient and her family members(7 individuals in total)at the PLA General Hospital.Sanger sequencing was used to validate the mutation site and a pedigree chart was drawn.For the patients,tests were performed to measure ferritin levels,liver function,glucose tolerance,pituitary function and thyroid function;additionally,liver MRI was performed to assess iron overload.Results:Genetic sequencing revealed that among the 7 family members,2 cases carried SLC40A1 c.G205A heterozygous mutation,both of which exhibited elevated ferritin and liver enzyme levels,and were diagnosed as HH type 4.The inheritance pattern of hemochromatosis caused by the heterozygous mutation of SLC40A1 c.G205A is autosomal dominant inheritance.Conclusion:SLC40A1 c.G205A heterozygous mutation can cause type 4 hemochromatosis,which is closely related to serum ferritin elevation.Abnormal liver function is often an early clinical manifestation of this disease.

Post-traumatic stress disorder (PTSD) is a psychological condition with a high incidence rate and widespread influence, but its pathophysiological mechanism is unknown, and existing treatment options have limited efficacy. Exploration of potential biomarkers and therapeutic targets for PTSD aids in the understanding of its pathogenesis and therapeutic strategies. Human PTSD sample data were retrieved from public databases, merged, and corrected to eliminate bias. The differentially expressed genes (DEGs) were then evaluated using bioinformatics tools, and the pathological mechanism was investigated using GO, KEGG, DO, and GSEA enrichment analyses. Furthermore, key genes were identified using machine learning methods, and gene interaction was investigated by establishing a protein-protein interaction (PPI) network and screening for hub genes. A total of 524 DEGs were identified, 236 were upregulated and 288 were downregulated. Enrichment analysis revealed an association of PTSD with inflammation and immune responses. The identification of 50 key genes and 9 hub genes (e.g., CEBPA, MMP13) adds to our understanding of the occurrence and development mechanisms of PTSD. Additionally, immune infiltration studies of PTSD patients revealed differences in distinct immune cells. This study investigates the occurrence and development pathways of PTSD by combining machine learning and bioinformatics methods. Potential biomarkers of PTSD have been identified. The findings provide theoretical references for the development of potential therapeutic strategies and an understanding of the immune regulatory mechanisms of PTSD.

BACKGROUND:Sepsis is a dysregulated host response to infections, leading to organ dysfunction and posing a critical threat to human health. Despite tremendous progress in understanding the pathophysiology of sepsis, early diagnosis and clinical treatment efficacy remain unsatisfactory. This study aimed to identify transcriptomic alterations in peripheral blood mononuclear cells as potential biomarkers of sepsis. METHODS:Bulk RNA-seq was performed on peripheral blood mononuclear cells obtained from 20 patients with sepsis and 12 healthy individuals. Multiple bioinformatics tools were used to identify key genes and signaling pathways associated with sepsis progression. The hub genes were further externally validated by publicly available blood transcriptomic data and experimentally verified by immunocytofluorescence assay. RESULTS:Differential expression analysis revealed 4,522 differentially expressed genes in patients with sepsis (n = 20) compared with healthy individuals (n = 12). Weighted gene coexpression network analysis identified multiple gene modules closely related to sepsis, with the royal blue module exhibiting the most positive correlation with sepsis. Intersection analysis yielded 176 common genes between the royal blue module genes and differentially expressed genes. Protein-protein interaction analysis revealed five hub genes ( CTSB , CTSD , ATP6V0D1 , UBE2D1 , and ATP6V0C ) associated with sepsis. Immune infiltration was dissected by single-sample gene set enrichment analysis, revealing associations between hub genes and monocytes. Single-cell RNA sequencing data analysis and immunocytofluorescence assay confirmed the upregulation of CTSB and ATP6V0D1 in circulating monocytes. Notably, CTSB and ATP6V0D1 were significantly associated with 28-day mortality of sepsis patients in the external validation cohort (n = 479). CONCLUSION:This study identifies CTSB and ATP6V0D1 expression in circulating monocytes as potential biomarkers and promising therapeutic targets for sepsis.

Background: Suboptimal cure rates with frontline therapy and limited treatment tolerance in elderly and frail patients were two major challenges in diffuse large B-cell lymphoma (DLBCL). We evaluated a novel chemotherapy-free regimen including polatuzumab vedotin, zanubrutinib, rituximab, lenalidomide and prednisone (Pola-ZR2P) as induction therapy for previously untreated patients with DLBCL to investigate its efficacy and safety. Methods: Newly diagnosed patients with DLBCL were enrolled and received Pola-ZR2P regimen every 21 days for 6 cycles. Polatuzumab vedotin was given at a dosage of 1.8 mg/kg intravenously on day 1, zanubrutinib was given 160 mg orally twice a day, from day 1 to day 21, lenalidomide was given 25 mg orally once a day, from day 1 to day 14, rituximab was administered at a dosage of 375 mg/m2 intravenously on day 1 and prednisone was given 60 mg/m2 orally once a day, from day 1 to day 5. Positron emission tomography/computed tomography (PET/CT) scan was used to evaluate interim therapeutic effects. If patients received complete response (CR) or partial response (PR) after 2-4 cycles, remaining cycles will be finished. Overall response rate (ORR) and adverse events were evaluated.(NCT06664411) Results: Between October 2024 and July 2025, 4 newly diagnosed DLBCL patients were enrolled. Patient 1 was a 72-year-old female patient diagnosed with de novo DLBCL NOS, stage IVB, high-risk (IPI score 5), GCB subtype, genetically classified as BN2. The patient was complicated with hereditary hemorrhagic telangiectasia and pulmonary hypertensionPET-CT evaluation after 3 cycles of Pola-ZR2P showed complete response (CR). Treatment was interrupted after cycle 1 due to gastrointestinal bleeding and intestinal infection (Candida albicans), and after cycle 2 due to grade 4 myelosuppression, but resumed in the subsequent cycle successfully. Patient 2was a 38-year-old female patient diagnosed with de novo DLBCL NOS, stage IA, low-risk (IPI score 0), GCB subtype, with no definitive genetic mutations identified. PET-CT evaluation after 4 cycles of Pola-ZR2P showed CR. During cycle 1, the patient developed septic shock and recovered following anti-infective therapy. Patient 3 was a 63-year-old female patient diagnosed with de novo DLBCL NOS, stage IVA, high-risk (IPI score 5), GCB subtype, genetically classified as EZB. She had a history of arrhythmia managed with intermittent propafenone. PET-CT evaluations after both cycle 3 and cycle 6 confirmed CR. During cycle 1, she developed rash and pruritusand resolved by anti-allergy treatment, and During cycle 3, she developed COVID-19 and recovered following antiviral therapy. Patient 4 was a 68-year-old male patient diagnosed with DLBCL NOS transformed from follicular lymphoma, stage IIIB, high-risk (IPI score 5), non-GCB subtype, genetically classified as ST2 and TP53. The patient was complicated with coronary artery disease and hypertension. The patient has completed 6 cycles to date. PET-CT evaluation after 3 cycles of Pola-ZR2P showed CR, and assessment after cycle 6 is pending. Treatment was interruptedduring cycle 1 due to severe pulmonary infection (Citrobacter braakii, HHV-6B, Mycoplasma), and resumed treatment at cycle 2 following anti-infective therapy. In conclusion, all 4 patients achieved complete response (CR) (3 at interim assessment, 1 at EOT assessment). The most common grade ≥3 adverse events (AEs) were infection, neutropenia and gastrointestinal bleeding, and most occurred after the first cycle. Grade 1 skin hyperpigmentation, potentially treatment-related, was observed in all patients. Treatment was interrupted due to AEs in two patients but was successfully resumed in the subsequent cycle. No fatal AEs were observed. Conclusion: Pola-ZR2P regimen demonstrated promising efficacy and a manageable safety profile in this cohort of previously untreated DLBCL patients. This report provides clinical evidence on the efficacy and safety of Pola-ZR2P regimen as the frontline immunochemotherapy in previously untreated DLBCL patients. Further enrollment of more patients is necessary to better clarify the effectiveness and safety of Pola-ZR2P regimen as the frontline chemotherapy in DLBCL patients.

Background: The survival rate of patients diagnosed with acute myeloid leukemia (AML) has shown improvement in recent decades. However, the induction chemotherapy regimen for AML still relies on the standard 7+3 regimen. Standard 7+3 regimen can achieve a complete response (CR) rate of 70%-80% in AML patients up to 60 years of age and 50% in older patients. After years of development, the CR rate has shown improvement in both young and elderly AML patients. However, more than 20%-30% of patients still fail to achieve a response after induction chemotherapy, particularly among elderly patients who are deemed unfit. Based on this premise, we endeavored to develop a low-dose, long-course CHG regimen (cytarabine, homoharringtonine, and granulocyte stimulating factor) in combination with the demethylating agent azacytidine and the Bcl-2 inhibitor venetoclax as an induction regimen(NCT06470841). Our aim is to investigate a more efficient and safer induction chemotherapy regimen. Methods: Adult patients with AML were enrolled to receive VACHG induction chemotherapy treatment (venetoclax 100mg po qd d1, 200mg po qd d2, 400mg po qd d3-14; azacytidine 75 mg/m2 subcutaneous injection qd d1-7; homoharringtonine 1mg/m2 iv qd d1-14; cytarabine 10mg/m2 subcutaneous injection q12h d1-14; granulocyte stimulating factor 250ug/m2 subcutaneous injection qd d0-14). After induction therapy, patients will be given standardized treatment according to risk stratification according to NCCN guidelines (NCT06470841). Results: We have currently enrolled a total of 5 patients with acute myeloid leukemia. Among them, 3 patients were over 65 years of age with newly diagnosed acute myeloid leukemia, while the remaining 2 patients were under 60 years of age with refractory/refractory acute myeloid leukemia. One patient achieved CRi after receiving daunorubicin plus cytarabine (DA) induction chemotherapy. However, the patient relapsed after completing 2 courses of consolidation chemotherapy (1 course of DA and 1 course of venetoclax + azacytidine + sorafenib). The patient then obtained CR after completing 1 course of VACHG reinduction chemotherapy. In another patient, non-response (NR) was observed after 1 course of idarubicin plus cytarabine. After the second course of venetoclax + azacytidine(VA) induction chemotherapy, the patient still achieved NR. Then, the patient underwent treatment with the VACHG regimen and achieved CR after a single course of induction chemotherapy using the VACHG regimen. Three additional elderly patients, who were newly diagnosed with AML, achieved a complete response after receiving a single course of VACHG chemotherapy. All the 2 refractory/relapsed AML patients and 3 newly diagnosed elderly AML patients achieved complete remission by a single course of VACHG induction chemotherapy. Grade Ⅳ myelosuppression and infection were observed in all five patients. Two patients experienced gastrointestinal hemorrhage, while one patient suffered from acute kidney injury. Side effects were effectively managed. Following the achievement of complete response, the two refractory/relapsed patients underwent allogeneic hematopoietic stem cell transplantation. The three elderly patients received consolidation and maintenance therapy after achieving complete response. Conclusion: In this trial, we utilized a low-dose, long-course regimen of CHG in combination with the demethylating drug azacytidine and the Bcl-2 inhibitor venetoclax as an induction regimen. Notably, all 5 patients achieved complete remission by a single course of VACHG induction chemotherapy, and the combined chemotherapy regimen demonstrated excellent tolerance in both young and elderly patients. This combined chemotherapy regimen demonstrated remarkable efficacy and merits further implementation. Further enrollment of more patients is necessary to better clarify the effectiveness and safety of VACHG regimen as induction chemotherapy in AML patients.

Background: The prevalence of depression in COVID-19 patients is notably high, disrupting daily life routines and compounding the burden of other chronic health conditions. In addition, to elucidate the connection between COVID-19 and depression, we conducted an analysis of commonly differentially expressed genes [co-DEGs], uncovering potential biomarkers and therapeutic avenues specific to COVID-19-related depression. Methods: We obtained gene expression profiles from the Gene Expression Omnibus [GEO] database with strategic keyword searches ["COVID-19", "depression," and "SARS"]. We used functional enrichment analysis of the co-DEGs to decipher their likely biological roles. Then, we utilized protein-protein interaction [PPI] network analysis to identify hub genes among the co- DEGs. These findings were validated via an independent third-party dataset. Results: Our analysis of blood samples from COVID-19 patients revealed 10,716 upregulated genes and 10,319 downregulated genes. In addition, by applying the same approach to depression samples, we identified 571 upregulated and 847 downregulated genes. Furthermore, by intersecting these datasets, we extracted 121 upregulated and 175 downregulated co-DEGs. Through PPI network construction and hub gene selection, we identified MPO, ARG1, CD163, FCGR1A, ELANE, LCN2, and CR1 as co-upregulated hub genes and MRPL13, RPS23, and MRPL1 as co-downregulated hub genes. The incorporation of third-party datasets revealed that these hub genes are specific targets of SARS-CoV-2, not generic viral response mechanisms. Conclusion: The identification of potential biomarkers represents a groundbreaking strategy for assessing and treating depression in the context of COVID-19, with the potential to reduce its prevalence among these patients. However, to fully harness this potential, additional clinical research is paramount.

Cancer is a major social, public health, and economic issue. The Systemic Immune-Inflammation Index (SII) has been linked to the prognosis of various cancer types. This study aims to explore the potential relationship between SII and cancer. This study utilized National Health and Nutrition Examination Survey (NHANES) data from 2013 to 2020, encompassing a total of 16,897 participants. We employed multivariate logistic regression models, subgroup analyses, smooth curve fitting, and threshold effect analyses to examine the relationship between SII and cancer. The analysis of the multivariate logistic regression models revealed a significant positive correlation between SII and cancer, consistent across most subgroups. Additionally, an "N"-shaped pattern was observed between SII and cancer, with significant inflection points at 1169 and 1950. Notably, when SII was below 1169, the positive correlation between SII and cancer remained statistically significant. Our findings indicate an "N"-shaped relationship between SII and cancer, suggesting a potentially high cost-effectiveness ratio in cancer screening that could enhance early cancer detection. However, this discovery necessitates further validation through additional research.

BACKGROUND:Cupriavidus gilardii is a species of the genus Cupriavidus. Knowledge about the pathogenic characteristics of Cupriavidus gilardii is limited, especially cardiac infection with this bacterium has not been reported. CASE PRESENTATION:We encountered a case of pulmonary infection after myocardial infarction and heart failure. The initial empirical treatment with meropenem was ineffective. After cultured Cupriavidus gilardii, cefoperazone sulbactam and minocycline were used, and the infection and heart failure was improved for few days. Unfortunately, the patient eventually died of heart failure exacerbated by infection with Staphylococcus Epidermidis. CONCLUSION:Meropenem has a limited therapeutic effect on this bacterium. Monitoring heart function and selecting effective antibiotics are crucial for improving the prognosis of patients suffered from heart disease and Cupriavidus gilardii infection.

Background Post-traumatic stress disorder (PTSD), a disease state that has an unclear pathogenesis, imposes a substantial burden on individuals and society. Traumatic brain injury (TBI) is one of the most significant triggers of PTSD. Identifying biomarkers associated with TBI-related PTSD will help researchers to uncover the underlying mechanism that drives disease development. Furthermore, it remains to be confirmed whether different types of traumas share a common mechanism of action. Methods For this study, we screened the eligible data sets from the Gene Expression Omnibus (GEO) database, obtained differentially expressed genes (DEGs) through analysis, conducted functional enrichment analysis on the DEGs in order to understand their molecular mechanisms, constructed a PPI network, used various algorithms to obtain hub genes, and finally evaluated, validated, and analyzed the diagnostic performance of the hub genes. Results A total of 430 upregulated and 992 down-regulated differentially expressed genes were extracted from the TBI data set. A total of 1919 upregulated and 851 down-regulated differentially expressed genes were extracted from the PTSD data set. Functional enrichment analysis revealed that the differentially expressed genes had biological functions linked to molecular regulation, cell signaling transduction, cell metabolic regulation, and immune response. After constructing a PPI network and introducing algorithm analysis, the upregulated hub genes were identified as VNN1, SERPINB2, and ETFDH, and the down-regulated hub genes were identified as FLT3LG, DYRK1A, DCN, and FKBP8. In addition, by comparing the data with patients with other types of trauma, it was revealed that PTSD showed different molecular processes that are under the influence of different trauma characteristics and responses. Conclusions By exploring the role of different types of traumas during the pathogenesis of PTSD, its possible molecular mechanisms have been revealed, providing vital information for understanding the complex pathways associated with TBI-related PTSD. The data in this study has important implications for the design and development of new diagnostic and therapeutic methods needed to treat and manage PTSD.

BackgroundInhibition of indolamine-2,3-dioxygenase 1 (IDO1) has been proposed as a promising strategy for cancer immunotherapy; however, it has failed in clinical trials. Macrophages in the tumor microenvironment (TME) contribute to immune escape and serve as potential therapeutic targets. This study investigated the expression pattern of IDO1 in TME and its impact on prognosis and therapeutic response of patients with esophageal squamous cell carcinoma (ESCC).MethodsRNA sequencing data from 95 patients with ESCC from The Cancer Genome Atlas (TCGA) database were used to explore the prognostic value of IDO1. Bioinformatics tools were used to estimate scores for stromal and immune cells in tumour tissues, abundance of eight immune cell types in TME, and sensitivity of chemotherapeutic drugs and immune checkpoint (IC) blockage. The results were validated using digitalized immunohistochemistry and multiplexed immunofluorescence in ESCC tissue samples obtained from our clinical center.ResultsTCGA and validation data suggested that high expression of IDO1 was associated with poor patient survival, and IDO1 was an independent prognostic factor. IDO1 expression positively correlated with macrophages in TME and PDCD1 within diverse IC genes. Single-cell RNA sequencing data analysis and multiplexed immunofluorescence verified the coexpression of IDO1 and PD-1 in tumor-associated macrophages (TAMs). Patients with high IDO1 expression showed increased sensitivity to various chemotherapeutic drugs, while were more likely to resist IC blockage.ConclusionThis study identifies IDO1 as an independent prognostic indicator of OS in patients with ESCC, reveals a compelling connection of IDO1, PD-1, and TAMs, and explores the sensitivity of patients with high IDO1 expression to chemotherapeutic drugs and their resistance to IC blockade. These findings open new avenues for potential targets in ESCC immunotherapy.

Macrophage polarization is a critical determinant of disease progression and regression. Studies on macrophage plasticity and polarization can provide a theoretical basis for the tactics of diagnosis and treatment for macrophage-related diseases. These include inflammation-related diseases, such as sepsis, tumors, and metabolic disorders. Growth differentiation factor-15 (GDF-15) or macrophage inhibitory cytokine-1, a 25 kDa secreted homodimeric protein, is a member of the transforming growth factor-β (TGF-β) superfamily that is released in response to external stressors. GDF-15 regulates biological effects such as tumor occurrence, inflammatory response, tissue damage, angiogenesis, and bone metabolism. It has been shown to exert anti-inflammatory and pro-inflammatory effects in inflammation-related diseases. Moreover, inflammatory stimuli can induce GDF-15 expression in immune and parenchymal cells. GDF-15 exhibits a feedback inhibitory effect by inhibiting tumor necrosis factor-α secretion during the macrophage activation anaphase, suggesting that there may be a close association between the two. GDF-15 directly induces CD14+ monocytes to produce the M2-like macrophage phenotype, inhibits monocyte-derived macrophage for M1-like polarization, and induces monocyte-derived Mφ for M2-like polarization. This review summarizes the macrophage polarization mechanism of GDF-15 under the conditions of sepsis, colon cancer, atherosclerosis, and obesity. An improved understanding of the role and molecular mechanisms of action of GDF-15 could greatly elucidate the mechanism of disease occurrence and development and provide new ideas for targeted disease prevention and treatment. An advanced understanding of the function and molecular mechanisms of action of GDF-15 may be helpful in the assessment of its potential value as a therapeutic and diagnostic target.

Purpose: Acute kidney injury (AKI) is one of the most common functional injuries observed in trauma patients. However, certain trauma medications may exacerbate renal injury. Therefore, the early detection of trauma-related AKI holds paramount importance in improving trauma prognosis. Methods: Qualified datasets were selected from public databases, and common differentially expressed genes related to trauma-induced AKI and hub genes were identified through enrichment analysis and the establishment of protein-protein interaction (PPI) networks. Additionally, the specificity of these hub genes was investigated using the sepsis dataset and conducted a comprehensive literature review to assess their plausibility. The raw data from both datasets were downloaded using R software (version 4.2.1) and processed with the ''affy'' package19 for correction and normalization. Results: Our analysis revealed 585 upregulated and 629 downregulated differentially expressed genes in the AKI dataset, along with 586 upregulated and 948 downregulated differentially expressed genes in the trauma dataset. Concurrently, the establishment of the PPI network and subsequent topological analysis highlighted key hub genes, including CD44, CD163, TIMP metallopeptidase inhibitor 1, cytochrome b-245 beta chain, versican, membrane spanning 4-domains A4A, mitogen-activated protein kinase 14, and early growth response 1. Notably, their receiver operating characteristic curves displayed areas exceeding 75%, indicating good diagnostic performance. Moreover, our findings postulated a unique molecular mechanism underlying trauma-related AKI. Conclusion: This study presents an alternative strategy for the early diagnosis and treatment of trauma-related AKI, based on the identification of potential biomarkers and therapeutic targets. Additionally, this study provides theoretical references for elucidating the mechanisms of trauma-related AKI.

目的 制定新型冠状病毒奥密克戎(Omicron)变异株感染的急诊和发热门诊诊治方案.方法 总结解放军总医院第一医学中心急诊科和发热门诊救治新型冠状病毒 Omicron变异株感染患者经验,参考国内外相关指南和诊疗建议,结合文献报道撰写本文.结果 新型冠状病毒 Omicron变异株感染患者临床表现具有"双峰五层"显著特点,提出了不同病程阶段和层级患者的糖皮质激素和抗菌药物使用方案,并就治疗过程中需要关注的抗凝、血糖升高和医务人员自身防护等特殊问题提出建议.结论 新型冠状病毒 Omicron变异株感染,是综合性医院急诊科和发热门诊面临的新的临床挑战,"双峰五层"的急诊和发热门诊诊治方案,可以对提高救治水平、降低病死率有所帮助.

BACKGROUND:Glioma is the most common malignant primary brain tumor and is characterized by a poor prognosis and limited therapeutic options. ISG20 expression is induced by interferons or double-stranded RNA and is associated with poor prognosis in several malignant tumors. Nevertheless, the expression of ISG20 in gliomas, its impact on patient prognosis, and its role in the tumor immune microenvironment have not been fully elucidated.METHODS:Using bioinformatics, we comprehensively illustrated the potential function of ISG20, its predictive value in stratifying clinical prognosis, and its association with immunological characteristics in gliomas. We also confirmed the expression pattern of ISG20 in glioma patient samples by immunohistochemistry and immunofluorescence staining.RESULTS:ISG20 mRNA expression was higher in glioma tissues than in normal tissues. Data-driven results showed that a high level of ISG20 expression predicted an unfavorable clinical outcome in glioma patients, and revealed that ISG20 was possibly expressed on tumor-associated macrophages and was significantly associated with immune regulatory processes, as evidenced by its positive correlation with the infiltration of regulatory immune cells (e.g., M2 macrophages and regulatory T cells), expression of immune checkpoint molecules, and effectiveness of immune checkpoint blockade therapy. Furthermore, immunohistochemistry staining confirmed the enhanced expression of ISG20 in glioma tissues with a higher WHO grade, and immunofluorescence assay verified its cellular localization on M2 macrophages.CONCLUSIONS:ISG20 is expressed on M2 macrophages, and can serve as a novel indicator for predicting the malignant phenotype and clinical prognosis in glioma patients.

IntroductionSepsis is the leading cause of death in intensive care units and is characterized by multiple organ failure, including dysfunction of the immune system. In the present study, we performed an integrative analysis on publicly available datasets to identify immune-related genes (IRGs) that may play vital role in the pathological process of sepsis, based on which a prognostic IRG signature for 28-day mortality prediction in patients with sepsis was developed and validated.MethodsWeighted gene co-expression network analysis (WGCNA), Cox regression analysis and least absolute shrinkage and selection operator (LASSO) estimation were used to identify functional IRGs and construct a model for predicting the 28-day mortality. The prognostic value of the model was validated in internal and external sepsis datasets. The correlations of the IRG signature with immunological characteristics, including immune cell infiltration and cytokine expression, were explored. We finally validated the expression of the three IRG signature genes in blood samples from 12 sepsis patients and 12 healthy controls using qPCR.ResultsWe established a prognostic IRG signature comprising three gene members (LTB4R, HLA-DMB and IL4R). The IRG signature demonstrated good predictive performance for 28-day mortality on the internal and external validation datasets. The immune infiltration and cytokine analyses revealed that the IRG signature was significantly associated with multiple immune cells and cytokines. The molecular pathway analysis uncovered ontology enrichment in myeloid cell differentiation and iron ion homeostasis, providing clues regarding the underlying biological mechanisms of the IRG signature. Finally, qPCR detection verified the differential expression of the three IRG signature genes in blood samples from 12 sepsis patients and 12 healthy controls.DiscussionThis study presents an innovative IRG signature for 28-day mortality prediction in sepsis patients, which may be used to facilitate stratification of risky sepsis patients and evaluate patients’ immune state.

BackgroundThe negative impact of long COVID on social life and human health is increasingly prominent, and the elevated risk of cardiovascular disease in patients recovering from COVID-19 has also been fully confirmed. However, the pathogenesis of long COVID-related inflammatory cardiomyopathy is still unclear. Here, we explore potential biomarkers and therapeutic targets of long COVID-associated inflammatory cardiomyopathy.MethodsDatasets that met the study requirements were identified in Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) were obtained by the algorithm. Then, functional enrichment analysis was performed to explore the basic molecular mechanisms and biological processes associated with DEGs. A protein–protein interaction (PPI) network was constructed and analyzed to identify hub genes among the common DEGs. Finally, a third dataset was introduced for validation.ResultsUltimately, 3,098 upregulated DEGs and 1965 downregulated DEGs were extracted from the inflammatory cardiomyopathy dataset. A total of 89 upregulated DEGs and 217 downregulated DEGs were extracted from the dataset of convalescent COVID patients. Enrichment analysis and construction of the PPI network confirmed VEGFA, FOXO1, CXCR4, and SMAD4 as upregulated hub genes and KRAS and TXN as downregulated hub genes. The separate dataset of patients with COVID-19 infection used for verification led to speculation that long COVID-associated inflammatory cardiomyopathy is mainly attributable to the immune-mediated response and inflammation rather than to direct infection of cells by the virus.ConclusionScreening of potential biomarkers and therapeutic targets sheds new light on the pathogenesis of long COVID-associated inflammatory cardiomyopathy as well as potential therapeutic approaches. Further clinical studies are needed to explore these possibilities in light of the increasingly severe negative impacts of long COVID.

BACKGROUND:In-hospital cardiac arrest (IHCA) is an acute disease with a high fatality rate that burdens individuals, society, and the economy. This study aimed to develop a machine learning (ML) model using routine laboratory parameters to predict the risk of IHCA in rescue-treated patients.METHODS:This retrospective cohort study examined all rescue-treated patients hospitalized at the First Medical Center of the PLA General Hospital in Beijing, China, from January 2016 to December 2020. Five machine learning algorithms, including support vector machine, random forest, extra trees classifier (ETC), decision tree, and logistic regression algorithms, were trained to develop models for predicting IHCA. We included blood counts, biochemical markers, and coagulation markers in the model development. We validated model performance using fivefold cross-validation and used the SHapley Additive exPlanation (SHAP) for model interpretation.RESULTS:A total of 11,308 participants were included in the study, of which 7779 patients remained. Among these patients, 1796 (23.09%) cases of IHCA occurred. Among five machine learning models for predicting IHCA, the ETC algorithm exhibited better performance, with an AUC of 0.920, compared with the other four machine learning models in the fivefold cross-validation. The SHAP showed that the top ten factors accounting for cardiac arrest in rescue-treated patients are prothrombin activity, platelets, hemoglobin, N-terminal pro-brain natriuretic peptide, neutrophils, prothrombin time, serum albumin, sodium, activated partial thromboplastin time, and potassium.CONCLUSIONS:We developed a reliable machine learning-derived model that integrates readily available laboratory parameters to predict IHCA in patients treated with rescue therapy.

Internet of Things (IoT) technology plays an important role in smart healthcare. This paper discusses IoT solution for emergency medical devices in hospitals. Based on the cloud-edge-device architecture, different medical devices were connected; Streaming data were parsed, distributed, and computed at the edge nodes; Data were stored, analyzed and visualized in the cloud nodes. The IoT system has been working steadily for nearly 20 months since it run in the emergency department in January 2021. Through preliminary analysis with collected data, IoT performance testing and development of early warning model, the feasibility and reliability of the in-hospital emergency medical devices IoT was verified, which can collect data for a long time on a large scale and support the development and deployment of machine learning models. The paper ends with an outlook on medical device data exchange and wireless transmission in the IoT of emergency medical devices, the connection of emergency equipment inside and outside the hospital, and the next step of analyzing IoT data to develop emergency intelligent IoT applications.