OBJECTIVE: To investigate the predictive value of endothelial activation and stress index (EASIX) for the prognosis of patients with mantle cell lymphoma (MCL). METHODS: A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023, had therapeutic indications and received standard treatment. RESULTS: A total of 66 patients were included and divided into high EASIX group and low EASIX group, according to a cutoff value of 0.97 determined by the receiver operating characteristic (ROC) curve. Multivariate Cox regression analysis showed that prealbumin <0.2 g/L, high EASIX, and ECOG PS score ≥2 were independent risk factors influencing overall survival (OS) in MCL patients. The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months, and the median progression-free survival was 8.8 and 26.0 months, respectively. The proportions of patients with ECOG PS score ≥2 and prealbumin <0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group. CONCLUSION At the time of initial diagnosis, EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL. Furthermore, patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.
Humans ; Lymphoma, Mantle-Cell/pathology* ; Prognosis ; Retrospective Studies ; Male ; Female ; Middle Aged ; Aged ; ROC Curve

Objective: To screen and identify the key active molecules, signaling pathways, and therapeutic targets of Shuxuening (SXN) injection for treating liver cirrhosis (LC) and to evaluate its therapeutic potential using a mouse model. Methods: Target genes of SXN and LC were retrieved from public databases, and enrichment analysis was performed. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and hub genes were identified using Molecular Complex Detection (MCODE). LC was induced in rats and mice via intraperitoneal injections of diethylnitrosamine and carbon tetrachloride (CCl4) for 12 weeks. Starting at week 7, SXN was administered intraperitoneally to the mice in the treatment group. Serum and liver tissues of the mice were collected for the detection of indicators, pathological staining, and expression analysis of hub targets using quantitative real-time polymerase chain reaction (qRT-PCR). Results: We identified 368 overlapping genes (OLGs) between SXN and LC targets. These OLGs were subsequently used to build a PPI network and to screen for hub genes. Enrichment analysis showed that these genes were associated with cancer-related pathways, including phosphoinositide-3-kinase/Akt and mitogen-activated protein kinase signaling and various cellular processes, such as responses to chemicals and metabolic regulation. In vivo experiments demonstrated that SXN treatment significantly improved liver function and pathology in CCl4-induced LC mice by reducing inflammation and collagen deposition. Furthermore, qRT-PCR demonstrated that SXN regulated the expression of MAPK8, AR and CASP3 in the livers of LC mice. Conclusion This study highlighted the therapeutic effects of SXN in alleviating LC using both bioinformatics and experimental methods. The observed effect was associated with modulation of hub gene expression, particularly MAPK8, and CASP3.

One patient was admitted to a hospital due to"sepsis,chronic kidney disease,type 2 diabetes,shock,and cerebral infarction".Patient's blood specimen was taken for clinical examination.Aerobic and anaerobic culture results of catheter blood and venous blood were both positive.The pathogen was identified as Staphylococcus pas-teuri by VITEK MS,and the patient was diagnosed as catheter-related bloodstream infection caused by Staphylo-coccus pasteuri.Clinical empirical use of piperacillin for anti-infection treatment was ineffective,and vancomycin was eventually used for treatment based on in vitro antimicrobial susceptibility testing.Patient's condition improved after removing the venous catheter.There are currently no reported cases of Staphylococcus pasteuri in China.Ear-ly identification of pathogen and adjustment of treatment plans based on antimicrobial susceptibility testing results are crucial for effective treatment of this case.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Objectives: To investigate the role of donor change in the second hematopoietic stem cell transplantation (HSCT2) for hematological relapse of malignant hematology after the first transplantation (HSCT1) . Methods: We retrospectively analyzed patients with relapsed hematological malignancies who received HSCT2 at our single center between Mar 1998 and Dec 2020. A total of 70 patients were enrolled[49 males and 21 females; median age, 31.5 (3-61) yr]. Results: Forty-nine male and 21 female patients were enrolled in the trial. At the time of HSCT2, the median age was 31.5 (3-61) years old. Thirty-one patients were diagnosed with acute myeloid leukemia, 23 patients with ALL, and 16 patients with MDS or other malignant hematology disease. Thirty patients had HSCT2 with donor change, and 40 patients underwent HSCT2 without donor change. The median relapse time after HSCT1 was 245.5 (26-2 905) days. After HSCT2, 70 patients had neutrophil engraftment, and 62 (88.6%) had platelet engraftment. The cumulative incidence of platelet engraftment was (93.1±4.7) % in patients with donor change and (86.0±5.7) % in patients without donor change (P=0.636). The cumulative incidence of CMV infection in patients with and without donor change was (64.0±10.3) % and (37.0±7.8) % (P=0.053), respectively. The cumulative incidence of grade Ⅱ-Ⅳ acute graft versus host disease was (19.4±7.9) % vs (31.3±7.5) %, respectively (P=0.227). The cumulative incidence of TRM 100-day post HSCT2 was (9.2±5.1) % vs (6.7±4.6) % (P=0.648), and the cumulative incidence of chronic graft versus host disease at 1-yr post-HSCT2 was (36.7±11.4) % versus (65.6±9.1) % (P=0.031). With a median follow-up of 767 (271-4 936) days, 38 patients had complete remission (CR), and three patients had persistent disease. The CR rate was 92.7%. The cumulative incidences of overall survival (OS) and disease-free survival (DFS) 2 yr after HSCT2 were 25.8% and 23.7%, respectively. The cumulative incidence of relapse, OS, and DFS was (52.6±11.6) % vs (62.4±11.3) % (P=0.423), (28.3±8.6) % vs (23.8±7.5) % (P=0.643), and (28.3±8.6) % vs (22.3±7.7) % (P=0.787), respectively, in patients with changed donor compared with patients with the original donor. Relapses within 6 months post-HSCT1 and with persistent disease before HSCT2 were risk factors for OS, DFS, and CIR. Disease status before HSCT2 and early relapse (within 6 months post-HSCT1) was an independent risk factor for OS, DFS, and CIR post-HSCT2. Conclusion: Our findings indicate that changing donors did not affect the clinical outcome of HSCT2.
Humans ; Male ; Female ; Adult ; Child, Preschool ; Child ; Adolescent ; Young Adult ; Middle Aged ; Retrospective Studies ; Hematologic Neoplasms/therapy* ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Leukemia, Myeloid, Acute/therapy* ; Recurrence ; Graft vs Host Disease/etiology* ; Chronic Disease

Delayed wound healing in diabetes is a global challenge, and the development of related drugs is a clinical problem to be solved. In this study, purpurolide C (PC), a small-molecule secondary metabolite of the endophytic fungus Penicillium purpurogenum, was found to promote diabetic wound healing. To investigate the key regulation targets of PC, in vitro RNA-seq, molecular docking calculations, TLR4-MD2 dimerization SDS-PAGE detection, and surface plasmon resonance (SPR) were performed, indicating that PC inhibited inflammatory macrophage activation by inhibiting both TLR4-MD2 dimerization and MYD88 phosphorylation. Tlr4 knockout in vivo attenuated the promotion effect of PC on wound healing. Furthermore, a delivery system consisting of macrophage liposome and GelMA-based microneedle patches combined with PC (PC@MLIP MN) was developed, which overcame the poor water solubility and weak skin permeability of PC, so that successfully punctured the skin and delivered PC to local tissues, and accurately regulated macrophage polarization in diabetic wound management. Overall, PC is an anti-inflammatory small molecule compound with a well-defined structure and dual-target regulation, and the PC@MLIP MN is a promising novel biomaterial for the management of diabetic wound.

Objective:To predict and analyze the number of acute pancreatitis (AP) inpatients based on time series model, and to explore the predictive efficiency of the model.Methods:Clinical data of AP inpatients in the Affiliated Hospital of Southwest Medical University from January 2014 to December 2019 were collected. R software was used to collect the time series of AP inpatients, and the trend and seasonal characteristics of AP inpatients from 2014 to 2018 were analyzed. Furthermore, the autoregressive moving average (ARIMA) model was established through stationarity test, model ordering and model testing steps, and the best selected model was used to predict the monthly number of inpatients in 2019 to verify its prediction efficiency.Results:A total of 3 939 AP patients were included in the study. The most common etiology for AP was cholestrogenic (48.2%), followed by hyperacylglyceremia (36.3%). The peak age of hospitalization was from 40 to 60 years old. Time series analysis showed that the number of AP inpatients increased year by year. The highest peak of the disease was from February to March, followed by September to November; and there was seasonal variation and the incidence was relatively small in summer. The established original training set sequence did not pass the stationarity test ( P=0.061), so the ARIMA model was established after it was transformed into a stationarity sequence by first-order difference. According to the criterion of minimum AIC value, ARIMA(2, 1, 1)(1, 1, 1) 12 was selected as the best model. The model was used to predict the number of AP inpatients in 2019, showing that it could better fit the trend of onset time and had good short-term prediction effect. The mean root error and absolute error were 6.8790 and 4.7783, respectively. Conclusions:The number of AP inpatients increases year by year with seasonal changes. ARIMA model is effective in predicting the number of AP inpatients and can be used for short-term prediction.

Objective To investigate the fluorescence resonance energy transfer (FRET) effect between dylight (DL) and AuNP (AuNP), and to construct a new fluorescence immunoassay for insulin in combination with the immunocompetition method. Methods Insulin antigen (Ag) and insulin antibody (Ab) were conjugated with DL and AuNP respectively to form DL-Ag conjugate and AUNp-AB conjugate. A novel fluorescence immunoassay for insulin was developed on the basis of FRET effect and the immune competition response between them. Then the performance of the method was evaluated and its application in actual samples was explored. Results The fluorescence immunoassay showed high sensitivity (0.015 ng/mL), short measurement time (4 min) and good specificity. It was successfully used in the measurement of serum insulin, and the recovery was between 96.9% and 121.1%. Conclusion FRET effect between AuNP and DL can be applied to develop a fluorescence immunoassay for the measurement of serum insulin.
Fluorescence Resonance Energy Transfer ; Insulin ; Immunoassay

OBJECTIVE: To explore the relationship between drug treatment and outcomes in patients with late-onset severe pneumonia (LOSP) after allogeneic stem cell transplantation (allo-SCT). METHODS: We retrospectively analyzed the effects of the initiation time of treatment drugs, especially antiviral drugs and glucocorticoids on the clinical outcomes in 82 patients between January 2016 and August 2021 who developed LOSP after allo-SCT in Peking University People's Hospital. Univariate analysis was performed by Mann-Whitney U test and χ² test, and multivariate analysis was performed by Logistic regression. When multiple groups (n>2) were involved in the χ² test, Bonferroni correction was used for the level of significance test. RESULTS: Of all 82 patients in this study, the median onset time of LOSP was 220 d (93-813 d) after transplantation, and the 60-day survival rate was 58.5% (48/82). The median improvement time of the survival patients was 18 d (7-44 d), while the median death time of the died patients was 22 d (2-53 d). Multivariate analysis showed that the initiation time of antiviral drugs from the onset of LOSP (< 10 d vs. ≥10 d, P=0.012), and the initiation time of glucocorticoids from antiviral drugs (< 10 d vs. ≥10 d, P=0.027) were the factors affecting the final outcome of the patients with LOSP at the end of 60 d. According to the above results, LOSP patients were divided into four subgroups: group A (antiviral drugs < 10 d, glucocorticoids ≥10 d), group B (antiviral drugs < 10 d, glucocorticoids < 10 d), group C (antiviral drugs ≥10 d, glucocorticoids ≥10 d) and group D (antiviral drugs ≥10 d, glucocorticoids < 10 d), the 60-day survival rates were 91.7%, 56.8%, 50.0% and 21.4%, respectively. CONCLUSION Our study demonstrated that in patients who developed LOSP after allo-SCT, the initiation time of antiviral drugs and glucocorticoids were associated with the prognosis of LOSP, and the survival rate was highest in patients who received antiviral drugs early and glucocorticoids later. It suggested that for patients with LOSP of unknown etiology should be highly suspicious of the possibility of a secondary hyperimmune response to viral infection.
Antiviral Agents/therapeutic use* ; Glucocorticoids/therapeutic use* ; Hematopoietic Stem Cell Transplantation/methods* ; Humans ; Pneumonia/etiology* ; Prognosis ; Retrospective Studies ; Transplantation, Homologous/adverse effects*

The composition of serum is extremely complex,which complicates the discovery of new pharmaco-dynamic biomarkers via serum proteome for disease prediction and diagnosis.Recently,nanoparticles have been reported to efficiently reduce the proportion of high-abundance proteins and enrich low-abundance proteins in serum.Here,we synthesized a silica-coated iron oxide nanoparticle and devel-oped a highly efficient and reproducible protein corona(PC)-based proteomic analysis strategy to improve the range of serum proteomic analysis.We identified 1,070 proteins with a median coefficient of variation of 12.56％using PC-based proteomic analysis,which was twice the number of proteins iden-tified by direct digestion.There were also more biological processes enriched with these proteins.We applied this strategy to identify more pharmacodynamic biomarkers on collagen-induced arthritis(CIA)rat model treated with methotrexate(MTX).The bioinformatic results indicated that 485 differentially expressed proteins(DEPs)were found in CIA rats,of which 323 DEPs recovered to near normal levels after treatment with MTX.This strategy can not only help enhance our understanding of the mechanisms of disease and drug action through serum proteomics studies,but also provide more pharmacodynamic biomarkers for disease prediction,diagnosis,and treatment.