Objective To evaluate the correlation between alterations in DNase1 and DNase1L3 enzyme activities and impairment of NET degradation in patients with sporadic SLE, and to investigate the underlying mechanism. Methods 46 sporadic SLE patients and 30 age- and sex-matched healthy individuals were recruited. Serum levels of DNase1, DNase1L3 and corresponding autoantibodies were detected by ELISA. DNase1 and DNase1L3 were isolated by immunoprecipitation; NETs and enzyme degradation activities were detected using a modified immunofluorescence. DNase1L3 secretion by PBMCs was analyzed by ELISPOT, Western blotting and reverse transcription PCR. Results Levels of H3-dsDNA and Ela-dsDNA complexes were significantly elevated in SLE patients. LDGs in SLE population was significantly higher than in the control group, and LDGs was positively correlated with H3-dsDNA and Ela-dsDNA NETs complexes. The ability of SLE patients to degrade NET in vitro was significantly lower than that of the control group. Degradation experiments of DNase1 and DNase1L3 in different proportions showed that the decrease in DNase1L3 activity was the primary contributor to the elevated NET residue level. The concentration of DNase1L3 autoantibodies in SLE patients was significantly elevated compared to the control group. In addition, the capacity of PBMCs to secrete DNase1L3 was significantly lower in the SLE patients compared to the control group. Conclusion Decreased secretion of DNase1L3 and the presence of relevant autoantibodies notably impede NET degradation in patients with SLE, offering new directions for the monitoring and treatment of SLE patients.
Humans ; Autoantibodies ; Blotting, Western ; Enzyme-Linked Immunosorbent Assay ; Extracellular Traps ; Lupus Erythematosus, Systemic

BACKGROUND:Establishing a nomogram prediction model for postoperative pulmonary infection in hip fractures and taking early intervention measures is crucial for improving patients'quality of life and reducing medical costs. OBJECTIVE:To construct a nomogram risk prediction model of postoperative pulmonary infection in elderly patients with hip fracture,and provide theoretical basis for feasible prevention and early intervention. METHODS:Case data of 305 elderly patients with hip fractures who underwent surgical treatment at Wuxi Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine between January and October 2020(training set)were retrospectively analyzed.Using univariate and multivariate logistic regression analysis and Hosmer-Lemeshow goodness of fit test,receiver operating characteristic curve was utilized to analyze the diagnostic predictive efficacy of independent risk factors and joint models for postoperative pulmonary infections.Tools glmnet,pROC,and rms in R Studio software were applied to construct a nomogram model for predicting the risk of postoperative pulmonary infection in elderly patients with hip fractures,and calibration curves were further drawn to verify the predictive ability of the nomogram model.Receiver operating characteristic curves,calibration curves,and decision curves were analyzed for 133 elderly patients with hip fractures(validation set)receiving surgery at the same hospital from November 2022 to March 2023 to further predict the predictive ability of the nomogram model. RESULTS AND CONCLUSION:(1)The postoperative pulmonary infection rate in elderly patients with hip fractures in this group was 9.18%(28/305).(2)Single factor and multivariate analysis,as well as forest plots,showed that preoperative hospitalization days,leukocyte count,hypersensitive C-reactive protein,and serum sodium levels were independent risk factors(P<0.05).The Hosmer-Lemeshow goodness of fit test showed good fit(χ2=4.57,P=0.803).Receiver operating characteristic curve analysis was conducted on the independent risk factors and their joint models mentioned above,and the differentiation of each independent risk factor and joint model was good,with statistical significance(P<0.05).(3)The graphical calibration method,C-index,and decision curve were used to validate the nomogram prediction model.The predicted calibration curve was located between the standard curve and the acceptable line,and the predicted risk of the nomogram model was consistent with the actual risk.(4)The validation set used receiver operating characteristic curve,graphic calibration method,and decision curve to validate the prediction model.The results showed good consistency with clinical practice,indicating that the model had a good fit.The nomogram risk prediction model constructed for postoperative pulmonary infection in elderly patients with hip fractures has good predictive performance.The use of the nomogram risk prediction model can screen high-risk populations and provide a theoretical basis for early intervention.

Objective To explore the value of droplet digital polymerase chain reaction(ddPCR)in the etiological diagnosis of severe acute pancreatitis(SAP)patients with suspected bloodstream infection(BSI).Methods SAP patients admitted to the department of critical care medicine in a hospital July to September 2022 were enrolled.When BSI was suspected,venous blood was collected for both ddPCR detection and blood culture(BC)with antimi-crobial susceptibility testing(AST)simultaneously.The time required for two detection methods was recorded,and the detection results of ddPCR and BC were compared.The etiological diagnostic efficacy of ddPCR was calculated,and the correlation between the value of pathogen load detected by ddPCR and the level of infection parameters was explored.Results A total of 22 patients were included in the analysis,and 52 venous blood specimens were collec-ted for detection.BC revealed 17 positive specimens(32.7％)and 29 pathogenic strains,while ddPCR showed 41 positive specimens(78.8％)and 73 pathogenic strains.Detection time required for ddPCR was significantly lower than that of BC([0.16±0.03]days vs[5.92±1.20]days,P＜0.001).Within the detection range of ddPCR and taking BC results as the gold standard,the sensitivity and specificity of ddPCR were 80.0％and 28.6％,respective-ly.With the combined assessment of BSI based on non-blood specimen microbial evidence within a week,the sensi-tivity and specificity of ddPCR detection increased to 91.9％and 76.9％,respectively.ddPCR detected resistance genes of blaKPC,blaNDM/IMP,VanA/VanM,and mecA from 19,9,6,and 5 specimens,respectively.Correlation analysis showed a positive correlation between pathogen load and levels of C-reactive protein as well as procalcitonin(r=0.347,0.414,P＜0.05).Conclusion As a supplementary detection method for BC in BSI diagnosis,ddPCR has the advantages of higher sensitivity and shorter detection time,and is worthy of further exploration in clinical application.

BACKGROUND:The alteration of miR-146a-3p level is a common event in the pathogenesis of most neurological diseases,and the specific mechanism of miR-146a-3p regulation of astrocytes has not been studied. OBJECTIVE:To verify that miR-146a-3p regulates astrocyte proliferation,migration and apoptosis through insulin-like growth factor 1. METHODS:12 SD rats were divided into a sham operation group and a spinal cord injury group,with six rats in each group.RNA sequencing analysis was performed on the spinal cord tissues of all groups 2 weeks after surgery to screen out the differential genes(log2FC>2),and to select spinal cord injury-related genes(Score>20)in the Genecards database,and then to predict the target genes of miR-146a-3p by Targetscan.The intersection of three gene sets was obtained to screen out insulin-like growth factor 1 as one of the important target genes.qPCR,western blot assay and immunohistochemistry were performed to analyze the expression level of insulin-like growth factor 1 in spinal cord tissues.The primary astrocytes were divided into NC group,NC-mimics group and miR-146a-3p mimics group.Annexin-V/PI staining was used to detect cell apoptosis.CCK-8 assay was used to detect cell proliferation.Transwell assay was used to detect cell migration ability. RESULTS AND CONCLUSION:The expression of miR-146a-3p in the spinal cord tissue of the spinal cord injury group was lower than that of the sham operation group(P<0.05).The expression of insulin-like growth factor 1 in the spinal cord tissue of the spinal cord injury group was higher than that of the sham operation group(P<0.05).Compared with the NC group and NC-mimics group,the apoptotic rate of astrocytes was increased(P<0.01);the proliferation of astrocytes was decreased(P<0.01)and the number of migration was decreased(P<0.01)in the miR-146a-3p mimics group.To conclude,the expression of miR-146a-3p decreased and the expression of insulin-like growth factor 1 increased in spinal cord tissue after spinal cord injury.miR-146a-3p targeted regulation of insulin-like growth factor 1 in astrocytes,inhibited the proliferation and migration of astrocytes and promoted their apoptosis.

Fluorescence anisotropy(FA)analysis has many advantages such as no requirement of separation,high throughput and real-time detection,and thus has been widely used in many fields,including biochemical analysis,food safety detection,environmental monitoring,etc.However,due to the small volume or mass of the target,its combination with the fluorescence probe cannot produce significant signal change.To solve this issue,researchers often use nanomaterials to enhance the mass or volume of fluorophore to improve the sensitivity.Nevertheless,this FA amplification strategy also has some disadvantages.Firstly,nanomaterials are easy to quench fluorescence.As a result,the FA value is easily influenced by light scattering,which reduces the detection accuracy.Secondly,fluorescent probes in most methods require complex modification steps.Therefore,it is necessary to develop new FA probes that do not require the amplification of volume and mass or modification.As a new kind of nanomaterials,luminescent metal-organic framework(MOF)has a large volume(or mass)and strong fluorescence emission.It does not require additional signal amplification materials.As a consequence,it can be used as a potential FA probe.This study successfully synthesized a lanthanide metal organic framework(Ce-TCPP MOF)using cerium ion(Ce3+)as the central ion and 5,10,15,20-tetra(4-carboxylphenyl)porphyrin(H2TCPP)as the ligand through microwave assisted method,and used it as a novel unmodified FA probe to detect phosphate ions(Pi).In the absence of Pi,Ce-TCPP MOF had a significant FA value(r).After addition of Pi,Pi reacted with Ce3+in MOF and destroyed the structure of MOF into the small pieces,resulting in a decrease in r.The experimental results indicated that with the increase of Pi concentration,the change of the r of Ce-TCPP MOF(Δr)gradually increased.The Δr and Pi concentration showed a good linear relationship within the range of 0.5-3.5 μmol/L(0.016-0.108 mg/L).The limit of detection(LOD,3σ/k)was 0.41 μmol/L.The concentration of Pi in the Jialing River water detected by this method was about 0.078 mg/L,and the Pi value detected by ammonium molybdate spectrophotometry was about 0.080 mg/L.The two detection results were consistent with each other,and the detection results also meet the ClassⅡwater quality standard,proving that this method could be used for the detection of Pi in complex water bodies.

Adaptive immunity is a critical component of the human immune system, playing an essential role in identifying antigens and orchestrating a tailored immune response. This review delves into the significant strides made in the development of epitope prediction tools, their integration into vaccine design, and their pivotal role in enhancing immunotherapy strategies. The review emphasizes the transformative potential of these tools in refining our understanding and application of immune responses. Adaptive immunity distinguishes itself from innate immunity by its ability to recognize specific antigens and remember past infections, leading to quicker and more effective responses upon subsequent exposures. This facet of immunity involves complex interactions between various cell types, primarily B cells and T cells, which recognize distinct epitopes presented by antigens. Epitopes are small sequences or configurations on antigens that are recognized by the immune receptors on B cells and T cells, acting as the focal points of immune recognition and response. Epitopes can be broadly classified into two types: linear (or sequential) epitopes and conformational (or discontinuous) epitopes. Linear epitopes consist of a sequence of amino acids in a protein that are recognized by B cells and T cells in their primary structure form. Conformational epitopes, on the other hand, are formed by spatially distinct amino acids that come together in the tertiary structure of the protein, often recognized by the immune system only when the protein folds into its native conformation. The role of epitopes in the immune response is critical as they are the primary triggers for the activation of B cells and T cells. When an epitope is recognized, it can stimulate B cells to produce antibodies, mobilize helper T cells to secrete cytokines, or prompt cytotoxic T cells to kill infected cells. These actions form the basis of the adaptive immune response, tailored to eliminate specific pathogens or infected cells effectively. The prediction of B cell and T cell epitopes has evolved with advances in computational biology, leading to the development of several sophisticated tools that utilize a variety of algorithms to predict the likelihood of epitope regions on antigens. Tools employing machine learning methods, such as support vector machines (SVMs), XGBoost, random forest, analyze large datasets of known epitopes to classify new sequences as potential epitopes based on their similarity to known data. Moreover, deep learning has emerged as a powerful method in epitope prediction, leveraging neural networks capable of learning high-dimensional data from vast amounts of immunological inputs to identify patterns that may not be evident to other predictive models. Deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and ESM protein language model have demonstrated superior accuracy in mapping the nonlinear relationships inherent in protein structures and epitope interactions. The application of epitope prediction tools in vaccine design is transformative, enabling the development of epitope-based vaccines that can elicit targeted immune responses against specific parts of the pathogen. These vaccines, by focusing the immune response on highly specific regions of the pathogen, can offer high efficacy and reduced side effects. Similarly, in cancer immunotherapy, epitope prediction tools help identify tumor-specific antigens that can be targeted to develop personalized immunotherapeutic strategies, thereby enhancing the precision of cancer treatments. The future of epitope prediction technology appears promising, with ongoing advancements anticipated to enhance the precision and efficiency of these tools further. The integration of broader immunological data, such as patient-specific immune profiles and pathogen variability, along with advances in AI and machine learning, will likely drive the development of more adaptive, robust, and clinically relevant prediction models. This will not only improve the effectiveness of vaccines and immunotherapies but also contribute to our broader understanding of immune mechanisms, potentially leading to breakthroughs in the treatment and prevention of multiple diseases. In conclusion, the development and refinement of epitope prediction tools stand as a cornerstone in the advancement of immunological research and therapeutic design, highlighting a path toward more precise and personalized medicine. The ongoing integration of computational models with experimental immunology holds the promise of revolutionizing our approach to combating infectious diseases and cancer.

Systemic rheumatic disease is a kind of autoimmune disease which is caused by the dys-function of autoimmune cells and the damage of multiple systems and organs.Traditional immuno-suppressants play an important role in the treat-ment of systemic rheumatic diseases,but there are still a considerable number of refractory systemic rheumatic diseases that do not respond well to tra-ditional immunosuppressant therapy,and new ther-apeutic methods need to be explored.Chimeric an-tigen receptor T cell therapy(CAR-T)immunothera-py was initially used for the treatment of malig-nant hematological diseases and has shown good efficacy.Recently,CAR-T immunotherapy has also achieved remarkable efficacy in refractory systemic lupus erythematosus.It brings new hope for the treatment of systemic rheumatic diseases.This arti-cle summarizes the progress of clinical application of CAR-T immunotherapy in systemic rheumatic dis-eases in recent years,aiming to enhance clinicians'cognition of CAR-T immunotherapy and promote the further development of CAR-T immunotherapy in systemic rheumatic diseases.

This is the first reported case of a female with monkeypox infection in Kunming City,Yunnan Province.An epi-demiological investigation was conducted to provide a scientific basis for the prevention and control of monkeypox epidemics in China,especially for early detection in females in accordance with the"Monkeypox prevention and control program(2023 ver-sion)".Diagnosis was performed as described in the"Monkeypox Diagnosis and Treatment Guidelines(2022 version)".Speci-mens were collected for laboratory testing.The epidemiological investigation determined that the female patient had sexual in-tercourse with her newly married husband once before disease onset and the husband hid his history of male homosexual sex.The laboratory test results of the woman and her husband were positive for the nucleic acid of the monkeypox virus.Both had typical clinical symptoms,including rash.The epidemiological investigation,clinical symptoms,laboratory test results,and previous epidemic data of monkeypox in Yunnan province confirmed the woman as the first female infected with monkeypox in Yunnan Province and her husband was the presumed source of infection.

Vascular cognitive impairment(VCI)includes a range of illnesses from mild cognitive impairment to dementia,attributable to cerebrovascular factors.Although appropriate animal models are needed to allow clinicopathological research and drug development,there are currently no animal models that can perfectly simulate the pathogenesis of VCI.At present,carotid artery and vertebral artery stenosis or occlusion are the main method for VCI modeling;however,increasing numbers of non-surgical method have recently emerged,providing new ideas and prospects for the study of this disease.In this paper,we consider the construction method,model mechanisms,and model characteristics of non-surgical animal models of VCI,to provide a reference to help researchers choose the most suitable animal model.

Objective:To analyze the efficacy and safety of flumatinib,a second-generation tyrosine kinase inhibitor(TKI)independently developed in China,in patients with chronic myelogenous leukemia in chronic phase(CML-CP)who falied first-line and second-line treatment.Methods:The clinical data of 30 CML-CP patients treated with flumatinib in Lianyungang First People's Hospital from January 2020 to September 2022 were collected retrospectively.Among them,15 patients who received imatinib first-line treatment but failed treatment were included in the second-line group,and the other 15 patients who failed second-line treatment with nilotinib or dasatinib were included in the third-line group.The hematological and molecular responses of the patients in the two groups at 3,6 and 12 months of treatment,and the event-free survival(EFS)and adverse reactions of patients at the end of follow-up were statistical analyzed.Results:At 3,6,and 12 months of treatment,10,11,and 12 patients in the second line group achieved major molecular response(MMR),which was higher than that of 3,4,and 5 patients in the third line group(P=0.010,P=0.011,P=0.010).At 3 months of treatment,12 and 13 patients achieved complete hematological response(CHR)and early molecular response(EMR)in the second-line group,which was higher than that of 9 and 13 patients in the third-line group,but the difference between the two groups was not statistically significant(P=0.232,P=1.000);At 6 and 12 months of treatment,6 and 7 patients in the second-line group achieved MR4.5,which were higher than of 3 and 2 cases in the third-line group,but the difference was not statistically significant(P=0.427,P=0.713).The hematological adverse reactions of patients in the second-line group during treatment the period were mainly grade 1-2 thrombocytopenia and anemia,and no grade 3-4 of adverse reactions occurred.In the third-line group,there were 2 cases of grade 1-2 thrombocytopenia,grade 1-2 anemia and white blood cell 3 cases were reduced each,1 case of grade 3-4 anemia,2 cases of grade 3-4 neutropenia.The non-hematological adverse reactions in the second-line group were rash(2 cases),headache(1 case),diarrhea(1 case),fatigue(1 case),limb pain(1 case).There were 1 cases of diarrhea,1 cases of nausea,and 1 cases of edema in the third-line group.There was no statistical significance in hematological and non-hematological adverse reactions between the two groups of patients(P＞0.05).At the end of follow-up,the EFS rate of patients in the second-line group was higher than that in the third-line group(100％vs 93.3％),but the difference was not statistically significant(P=0.317).Conclusion:The second-generation TKI flumatinib independently developed in China,has good curative effect and safety for CML-CP patients who failed first-line and second-line treatment.