Programmed cell death is known to play a crucial role in host defense,with various cell death pathways having u-nique regulatory mechanisms.In recent years,further research into cell death pathways has revealed crosstalk and coordination among them,leading to the proposition of a new cell death path-way:PANoptosis.PANoptosis is believed to be an inflammatory form of programmed cell death regulated by the PANoptosome complex,possessing key features of pyroptosis,apoptosis,and ne-croptosis,and it cannot be solely characterized by any single mode of cell death.PANoptosis is involved in various diseases,such as infectious diseases and tumor-related conditions,where specific triggers can induce host cell death via the PANoptosis pathway.In-depth investigation of PANoptosis promises a better understanding of the complex regulatory network of cell death and may offer new therapeutic targets for diseases.This review provides an overview of the specific mechanisms underlying PANoptosis and its potential roles in various diseases such as cancer,infectious diseases,and cardiovascular disorders.

Objective:To investigate the clinical manifestations, long-term survival, and prognosis of childhood T-cell acute lymphoblastic leukemia (T-ALL).Methods:Case summary.The clinical data of 43 T-ALL children who were diagnosed and treated in Children′s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2010 to December 2021 were retrospectively analyzed.They were stratified for treatment according to the CCCG-ALL regimen, and the correlation of prognosis with the condition at initial diagnosis, early treatment response, and induced remission was analyzed.The Kaplan-Meier survival curve was used to analyze the survival rate, and the survival rates were compared between groups by the Log-rank test.The multivariate Cox regression model was used to analyze the impact of multiple factors on the long-term survival of children.Results:T-ALL patients accounted for 9.5% (43/451) of the total number of acute lymphoblastic leukemia patients admitted to the hospital at the same period.The median onset age of the 43 T-ALL patients was 7 years (1-13 years).Of the 43 patients included, 14 patients (32.6%) had concomitant mediastinal widening, 8 patients (18.6%) had concomitant giant mediastinal masses, and 4 patients (9.3%) had early precursor T-cell acute lymphoblastic leukemia (ETP-ALL) at initial diagnosis.These 43 children were treated according to the CCCG-ALL intermediate- and high-risk group regimen.Among them, 33 children (76.7%) achieved sustained remission, 5 children died, and 5 children had a relapse.As of September 30, 2024, the median follow-up time was 62 months (1-170 months), the 10-year event-free survival rate was (80.2±6.4)%, and the 10-year overall survival rate was (86.6±5.8)%.The median relapse time and 10-year cumulative relapse rate of the 5 relapsed children were 28 months (7-58 months) and (13.7±5.8)%, respectively.The relationship of prognosis with clinical characteristics at initial diagnosis and induced remission in 43 T-ALL children was analyzed.The results showed that patients aged ≥10 years, with a grade-1 non-central nervous system at initial diagnosis, ETP-ALL, abnormal chromosome number and structure, non-M1 status of bone marrow and minimal residual disease (MRD)≥ 1% on day 19 of induction treatment, and MRD ≥ 0.01% on day 46 to 55 of induction treatment had poorer long-term survival(all P<0.05).The multivariate analysis showed that age ≥10 years, ETP-ALL, and abnormal chromosome number and structure were risk factors of poor prognosis ( P=0.045, 0.030, 0.021). Conclusions:The CCCG-ALL regimen has a good overall therapeutic effect in children with T-ALL.Age ≥10 years, abnormal chromosome number and structure, ETP-ALL, grade-1 non-central nervous system at initial diagnosis, and early remission are risk factors of poor prognosis.Treatment after relapse in children with T-ALL is difficult.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective:To construct evaluation index system of core competence of dental nurses applying digital technology, and to provide reference for training, assessment and digital technology application capabilities evaluation of dental nurses.Methods:From May to August 2024, literature review, semi-structured interview, Delphi expert letter consultation and analytic hierarchy process were used to build anevaluation index system of core competence of dental nurses applying digital technology and determine the weights of each index.Results:The effective response rate of the two rounds of expert inquiry questionnaires was 100%(26 / 26), the expert authority coefficient of the two rounds of expert correspondence was 0.943, and the Kendall harmony coefficient of the first, second and third indexes in the second round of inquiry were 0.221, 0.261 and 0.200 (all P<0.05), respectively. Finally, the evaluation index system of digital technology application core competence of dental nurses included 7 first-level indicators, 15 second-level indicators and 61 third-level indicators. Conclusions:The evaluation index system of digital technology application core competence of dental nurses established in this study has a high degree of expert authority, concentrated opinions, and scientific and reliable research results. It can provide reference for nursing managers to train, assess and hire dental nurses.

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma（TFE3-rRCC）.Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma（RCC）patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023，including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC（comprising clear cell RCC，papillary RCC，and chromophobe RCC）. Among them，627 were male and 238 were female，with a mean age of（54.1 ± 12.7）years（range：14?82 years）. The median maximum tumor diameter was 4.0（2.6，6.0）cm. Based on the chronological order of CT examinations，the patients were divided into training（ n=478），validation（ n=206），and test（ n=181）sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images，we extracted peritumoral imaging features，habitat features，3D radiomic features，and 2.5D deep learning radiomic features. A deep learning radiomics score（DLR-SCORE）prediction model was constructed using least absolute shrinkage and selection operator（LASSO）regression. The diagnostic performance of the model was evaluated by receiver operating characteristic（ROC）curve analysis，with the area under the curve（AUC）as the primary metric. Additionally，sensitivity，specificity，and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images，from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%（471/478）in the training set，81.6%（168/206）in the validation set，and 86.2%（156/181）in the test set. The AUC of ROC curve was 0.98（95% CI 0.96?1.00）in the training set，0.83（95% CI 0.71?0.94）in the validation set，and 0.88（95% CI 0.76?1.00）in the test set. In the test set，the DLR-SCORE model achieved a sensitivity of 88.9%（16/18）and a specificity of 85.9%（140/163）for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC，offering a promising noninvasive tool to assist preoperative diagnosis.

A method for simultaneous determination of 21 kinds of Aconitum alkaloids(ATS)in biological specimens and infused liquor using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)was developed.The biological samples were pretreated with methanol-acetonitrile(1∶2,V/V)for protein precipitation,while infused liquors were diluted 100-fold with acetonitrile,followed by centrifugation,and filtration by a 0.22-μm membrane.Chromatographic separation was carried out on an EC-C18 column using gradient elution with the mixture of 10 mmol/L ammonium acetate and 0.2%formic acid as mobile phase A and acetonitrile as mobile phase B.With this method,all the analytes were separated within 9.5 min.The samples were detected in positive ESI mode with dynamic multiple reaction monitoring(MRM)and quantified via external standard calibration.The results showed that the concentrations of the analytes in the range of 2-1000 ng/mL had excellent linearity(R2>0.9992)with the peak area.The developed method was successfully used for detection of 21 kinds of aconitum alkaloids,with limits of detection of 0.5-2 ng/mL,quantification limits of 2-6 ng/mL,intra/inter-day precision≤6.0%,spiked recoveries of 89.4%-100.9%,extraction recoveries of 74.2%-104.4%,and matrix effects ranging from-11.1%to 9.2%in blood/urine.The method was applied to detection of 12 samples from 4 fatal aconite poisoning cases,and all 21 kinds of ATS with total alkaloid concentrations of 0.04-4.18 μg/mL in blood and 154.96-422.83 μg/mL in medicinal liquors were detected.Tissue distribution revealed that the order of concentrations from highest to lowest is as follows:urine(157.22 μg/mL)>gastric contents(51.37 μg/mL)>kidney(21.6 μg/g)>whole blood(4.18 μg/mL)>liver(0.03 μg/g).This method showed many advantages such as simple pretreatment,low detection limits,accurate quantification,broad analyte coverage,and superior anti-interference capability in complex matrices,proving ideal for forensic and toxicological analysis of aconitum alkaloids.

Objective To explore the influencing factors of different types of small intestinal bacterial overgrowth(SIBO).Methods A total of 539 patients who were hospitalized in the Department of Gastroenterology,the Sixth Medical Center of PLA General Hospital from June 2021 to December 2021 and who underwent methane-hydrogen breath test were retrospectively selected.Based on breath test results,patients were divided into SIBO-negative group(n=300)and SIBO-positive group(n=239).The clinical data were compared between two groups.According to the specific values of breath test results,SIBO-positive patients were further divided into hydrogen-producing bacterial overgrowth(hydrogen-positive,n=103),intestinal methanogen overgrowth(methanogen-positive,n=80),and simultaneous methanogen and hydrogen-producing bacterial overgrowth(double positive,n=56)groups.Multivariate logistic regression analysis was employed to identify influencing factors of different SIBO types.Additionally,SIBO-positive patients were categorized by age into<45 years(n=23),45-60 years(n=82),60-75 years(n=124),and≥75 years(n=10)to compare SIBO positivity rates across age groups.Results The patients in SIBO-positive and double positive groups were older and had a lower body mass index(BMI)than those in SIBO-negative group,with statistically significant differences(P<0.05).Compared with the patients in SIBO-negative group,those in hydrogen-positive group showed a higher proportion of history of coronary heart disease,those in methanogen-positive group were older,and higher proportion of statin use,with statistically significant differences(P<0.05).Multivariate logistic regression analysis revealed that,among different SIBO types,a history of coronary heart disease served as an independent risk factor for hydrogen-producing bacterial overgrowth(OR=2.728,95%CI 1.271-5.857,P=0.010).For methanogen overgrowth,increasing age was identified as an independent risk factor(OR=1.040,95%CI 1.009-1.063,P=0.010),while the application of statin played the role of an independent protective factor(OR=0.420,95%CI 0.236-0.754,P=0.003).As for the simultaneous overgrowth of methane-producing and hydrogen-producing bacteria,increased BMI was found to be an independent protective factor(OR=0.870,95%CI 0.786-0.964,P=0.008).In SIBO-positive group,it was found that for patients aged<45 years,both the methane-positive rate and the double-positive rate were significantly lower than the hydrogen positivity rate(P<0.05).Moreover,among patients aged 45-60 years,the double-positive rate was significantly lower than the hydrogen positivity rate(P<0.01).When it comes to the hydrogen-positive rate,it was significantly lower for patients aged 45-60 and 60-75 years compared with that of patients aged<45 years(P<0.05).In contrast,the methane-positive rate and the double-positive rate were significantly higher for patients aged 45-60 and 60-75 years than those of patients aged<45 years(P<0.01).Conclusion A history of coronary heart disease and increasing age are independent risk factors for intestinal hydrogen-producing bacterial overgrowth and methanogen overgrowth,respectively.The application of statins and increased BMI are independent protective factors for intestinal methanogen simultaneous overgrowth of methanogen and hydrogen-producing bacteria,respectively.

Based on the interleukin-17(IL-17) signaling pathway, this study explores the effect and mechanism of Bufei Decoction on Klebsiella pneumoniae pneumonia in rats. SD rats were randomly divided into the control group, model group, Bufei Decoction low-dose group(6.68 g·kg~(-1)·d~(-1)), Bufei Decoction high-dose group(13.36 g·kg~(-1)·d~(-1)), and dexamethasone group(1.04 mg·kg~(-1)·d~(-1)), with 10 rats in each group. A pneumonia model was established by tracheal drip injection of K. pneumoniae. After successful model establishment, the improvement in lung tissue damage was observed following drug administration. Core targets and signaling pathways were screened using transcriptomics techniques. Real-time fluorescence quantitative polymerase chain reaction was used to detect the mRNA expression of core targets interleukin-6(IL-6), interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and chemokine CXC ligand 6(CXCL6). Western blot was used to assess key proteins in the IL-17 signaling pathway, including interleukin-17A(IL-17A), nuclear transcription factor-κB activator 1(Act1), tumor necrosis factor receptor-associated factor 6(TRAF6), and downstream phosphorylated p38 mitogen-activated protein kinase(p-p38 MAPK), and phosphorylated nuclear factor-κB p65(p-NF-κB p65). Apoptosis of lung tissue cells was detected by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling(TUNEL). The results showed that, compared with the control group, the model group exhibited significant pathological damage in lung tissue. The mRNA expression of IL-6, IL-1β, TNF-α, and CXCL6, as well as the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly increased, and the number of apoptotic cells was notably higher, indicating successful model establishment. Compared with the model group, both low-and high-dose groups of Bufei Decoction showed reduced pathological damage in lung tissue. The mRNA expression levels of IL-6, IL-1β, TNF-α, and CXCL6, and the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly decreased, with a significant reduction in apoptotic cells in the high-dose group. In conclusion, Bufei Decoction can effectively improve lung tissue damage and reduce inflammation in rats with K. pneumoniae. The mechanism may involve the regulation of the IL-17 signaling pathway and the reduction of apoptosis.
Animals ; Interleukin-17/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Rats ; Male ; Klebsiella pneumoniae/physiology* ; Klebsiella Infections/immunology* ; Humans ; Lung/drug effects*