Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

OBJECTIVES: To investigate the protective mechanism of quercetin, the core component of Zuo Gui Wan, against Alzheimer's disease through the PI3K/AKT signaling pathway, based on network pharmacology, molecular docking, and cell experi-ments. METHODS: The active components of Zuo Gui Wan were identified by searching TCMSP, PubChem, Swiss Target Prediction, and BATMAN-TCM databases, and their potential targets were predicted. The target information was standardized using Uniprot, and Alzheimer's disease-related target genes were obtained from Drugbank, GeneCards, and OMIM. The intersection of these datasets was used to identify the potential targets of Zuo Gui Wan for treating Alzheimer's disease. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The protein-protein interaction (PPI) network of potential targets was visualized using Cytoscape 3.10.1 software and the STRING database. The key active compounds and core potential targets for treating Alzheimer's disease with Zuo Gui Wan were identified through calculation. Based on the enrichment analysis results and literature, quercetin and the PI3K/AKT pathway were selected for verification. Molecular docking and binding ability prediction between quercetin and the core target AKT were performed using CB-Dock2, and visualization was conducted with AutoDock and PyMOL software. Finally, Aβ_1-42-induced HT-22 mouse hippocampal neuronal cells were used to construct an Alzheimer's disease cell model. Quercetin, the PI3K inhibitor LY294002, and the activator EGF were used as interventions. The groups were divided as follows: Control, Aβ_1-42, Aβ_1-42+Quercetin 2.5 μM, Aβ_1-42+Quercetin 5 μM, Aβ_1-42+Quercetin 10 μM, Aβ_1-42+EGF, and the PI3K/AKT modulation group: Control, LY294002, LY294002+Quercetin 10 μM, LY294002+EGF. CCK-8 assays were performed to detect cell viability, while JC-1, Calcein AM-PI, and Hoechst staining were used to assess cell apoptosis. Western blotting was employed to detect the expression of relevant target proteins. RESULTS: Network pharmacology and cell experiments collectively demonstrate that the key active ingredient of Zuo Gui Wan, quercetin, targets core proteins such as AKT1 and GSK3β through a network-based approach, significantly enriching the PI3K/AKT pathway. Molecular docking results indicate that quercetin has a strong binding affinity with AKT. Experimental validation in the Aβ_1-42 oligomer-induced HT-22 model reveals that quercetin significantly activates the PI3K/AKT signaling pathway, which is inhibited by Aβ_1-42 oligomers, as well as Bcl-2 protein expression. It also suppresses the expression of Cleaved Caspase 3/Caspase 3, BAX, and Cytochrome C proteins. JC-1, Hoechst 33342, and Calcein AM-PI staining results further show that quercetin can significantly alleviate apoptosis induced by Aβ_1-42 oligomers in HT-22 cells. Treatment with the PI3K inhibitor LY294002 in HT-22 cells leads to reduced cell viability and decreased expression of p-AKT/AKT and Bcl-2 proteins, while increasing the expression of Cleaved Caspase 3/Caspase 3, BAX, and Cytochrome C proteins. Additionally, apoptosis levels increase as observed in JC-1, Hoechst 33342, and Calcein AM-PI staining, all of which can be reversed by quercetin and the PI3K agonist EGF. CONCLUSIONS Quercetin, the key active ingredient of Zuo Gui Wan, exerts its protective effects against Alzheimer's disease by regulating the PI3K/AKT signaling pathway, inhibiting neuronal cell damage and apoptosis.

Colorectal cancer (CRC) poses a severe global health challenge with high incidence and mortality rates. USP37 has been identified as the bona fide deubiquitinase of SND1, playing a critical role in stabilizing SND1, thereby augmenting its oncogenic potential. The interaction between USP37 and SND1 was confirmed through extensive proteomics, ubiquitinomics, and interactomics, underscoring their synergistic effects on CRC proliferation and metastasis. Additionally, CDK1 has emerged as a pivotal regulator of USP37, phosphorylating it at threonine 631 rather than serine 628, enhancing its deubiquitinase activity, and consequently stabilizing SND1 to drive CRC malignancy further. Histological analyses of human CRC samples linked the upregulation of CDK1 and USP37 with increased SND1 levels and poor patient prognosis. High-throughput virtual screening and subsequent experimental validation identified Dacarbazine as a pharmacological inhibitor of USP37, and its inhibition disrupted SND1 stability, hindering CRC cell proliferation and metastasis. This study reveals a novel and promising molecular mechanism driving CRC progression through the CDK1-USP37-SND1 axis, highlighting the clinical importance of targeting this pathway to improve patient outcomes.

Objective To investigate the expression of microRNA(miR)-143-3p and signal transduction and transcriptional activator protein(STAT)3 in serum of patients with hepatocellular carcinoma(HCC)and its clinical significance.Methods A total of 110 HCC patients admitted to Rugao People's Hospital from Jan-uary 2022 to February 2023 were selected as HCC group,and 40 healthy people who underwent physical ex-amination during the same period were selected as healthy control group.The expression of miR-143-3p and STAT3 mRNA was compared in the serum of two groups.In addition,they were divided into good prognosis group(n=82)and poor prognosis group(n=28),according to the prognosis of HCC patients followed up for 1 year.Multivariate Logistic regression analysis was used to analyze the the influencing factors of poor prog-nosis in HCC patients.The predictive efficacy of serum miR-143-3p and STAT3 mRNA expression on poor prognosis of HCC patients was analyzed by receiver operating characteristic(ROC)curve.Results Compared with healthy control group,the expression level of miR-143-3p in serum of HCC group was lower(P＜0.05),while the expression level of STAT3 mRNA was higher(P＜0.05).Multivariate Logistic regression analysis showed that microvascular invasion,maximum diameter of tumor＞5 cm,down-regulated serum miR-143-3p expression and up-regulated STAT3 mRNA expression were independent risk factors for poor prognosis of HCC patients(P＜0.05).ROC curve showed that the area under the curve of serum miR-143-3p,STAT3 mR-NA and their combined detection for predicting the poor prognosis of HCC patients were 0.888,0.810 and 0.922,respectively,and the combined detection had the best predictive value(P＜0.05).Conclusion The ex-pression of miR-143-3p is abnormally down-regulated in the serum of HCC patients,while the mRNA of STAT3 is abnormally up-regulated.The combined detection of miR-143-3p and STAT3 has good predictive value for the poor prognosis of HCC patients.

Objective To construct mouse BaF3-FIP1L1-PDGFRA(F/P),BaF3-F/P-T674I and BAF3-F/P-D842V pre-B cell strains which stably express F/P fusion protein and its T674I and D842V mutants in order to e-valuate their activity by checking their responses to tyrosine kinase inhibitors(TKIs).Methods Lentivirus infected technique was used to transfect the target gene into BaF3 cells.RT-qPCR was used to detect mRNA expression,and CCK-8 method was used to detect the inhibitory effect of TKIs on the proliferation of stable cell strains.Results The constructed BaF3-F/P,BaF3-F/P-T674I and BAF3-F/P-D842V cell strains all transcripted FIP1L1 and PDGFRA mRNA.They exhibited malignant phenotypic characteristics of proliferation independent of IL-3 and sen-sitivity to corresponding TKIs.Conclusions The pre-B-cell strains stably expressing F/P and its T674I and D842V mutants are successfully constructed,which provide a good cell model for the development of compounds targeting at those molecules.

Objective To construct and validate a clinical prediction model for delayed extubation undergoing non-emergency major surgery based on the random forest algorithm.Methods Clinical data of 7 528 patients undergoing non-emergency major surgery under general anesthesia from January 2018 to De-cember 2022 were retrospectively collected.The patients were divided into two groups according to whether extubation was performed within 2 hours after surgery:non-delayed extubation group(≤2 hours)and de-layed extubation group(＞2 hours).All the patients were randomly divided into a training set and a valida-tion set in a ratio of 7 ∶ 3.The predictive factors for delayed extubation after surgery were screened through LASSO regression and Logistic regression.The random forest model was established and verified by random forest algorithm.Results There were 123 patients(1.6%)experienced delayed extubation after surgery.ASA physical status,department,intraoperative use of flurbiprofen ester,dexmedetomidine,glucocorticoid,hypocalcemia,severe anemia,intraoperative blood transfusion,and airway spasm were identified as inde-pendent predictive factors for delayed extubation.The area under curve(AUC)value of the random forest prediction model in the validation set was0.751(95%CI0.742-0.778),and the sensitivity was98.1%,and the specificity was 41.9%.Conclusion The predictive model of delayed extubation undergoing non-e-mergency major surgery based on random forest algorithm has a good predictive value,which may be helpful to prevent delayed extubation undergoing non-emergency major surgery.

Objective:To explore the prevalence, clinical features, genetic characteristics and prognosis of Citrin deficiency in Henan province of China.Methods:A total of 986 565 neonates screened by tandem mass spectrometry at the Third Affiliated Hospital of Zhengzhou University from January 2013 to December 2021 were retrospectively analyzed. Analysis of SLC25A13 gene variants and parental verification were carried out for neonates suspected for Citrin deficiency by next-generation sequencing. The clinical, biochemical and genetic characteristics of Citrin deficiency patients were integrated to guide the diet treatment and follow up the growth and development. Paired- t test was used to compare the amino acid levels in the peripheral blood samples before and after the treatment. Results:Nine cases of Citrin deficiency were diagnosed among the 986 565 neonates. Specific elevation of citrulline was observed in all of the 9 cases. Six variants were detected by genetic sequencing, among which c. 852_855delTATG, c. 615+ 5G>A, c. 550C>T and IVS16ins3kb were known pathogenic variants, whilst c. 1111_1112delAT and c. 837T>A were unreported previously. The detection rate for c. 852_855delTATG was the highest (61.6%, 11/18), followed by IVS16ins3kb (16.7%, 3/18). The clinical symptoms of all patients were relieved after the treatment, and the blood amino acid profile and biochemical parameters were significantly improved by gradually falling within the normal range. By June 2022, all patients had shown a good prognosis.Conclusion:The prevalence of Citrin deficiency among neonates from Henan Province by tandem mass spectrometry is 1/109 618, and the carrier rate for the pathogenic variants of the SLC25A13 gene was 1/166. The c. 852_855delTATG may be a hot spot variant among the patients. Discovery of the novel variants has enriched the mutational spectrum of the SLC25A13 gene. Above results have provided a basis for the early diagnosis, treatment, prognosis and genetic counseling for the affected families.

Objective:To establish contact dermatitis pruritus model and detect itch,anxiety and depression-like behaviors.To observe the activation of the medial prefrontal cortex(mPFC)neurons and provide morphological evi-dence for its involvement in the regulation of itch perception information.Methods:A model of contact dermatitis pruri-tus was constructed with diphenylcyclopyrenone(DCP)applied on the neck and back of the mouse,and the itch per-ception video tracking system was used to detect the scratching behavior.Open field and suspended tail behavioral ex-periments were conducted to explore the anxiety and depression-like behaviors of mice under contact dermatitis.The dis-tribution of c-Fos and p-ERK1/2 positive cells in the mPFC of contact dermatitis model mice was investigated by immu-nofluorescence staining.Results:The contact dermatitis pruritus model was successfully established,and the bouts of scratching in the contact dermatitis model group was significantly higher than that in the control group(P＜0.05).The results of open field test showed that the time and distances were significantly reduced in the central area of the contact dermatitis model group.The results of the tail suspension experiment suggested that the time of immobility increased sig-nificantly in the contact dermatitis model group(P＜0.05).There were more c-Fos positive and p-ERK1/2 positive cells in the mPFC compared with the control group(P＜0.05).Conclusion:Bouts of scratching were increased in the contact dermatitis group and the mice had anxiety and depression-like behaviors.In the contact dermatitis state,mPFC neurons were activated,providing morphological evidence for the involvement of mPFC neurons in contact dermatitis pruritus and accompanying affective disorders such as anxiety and depression.

The microbiome plays a role in the development of lower urinary tract diseases, but the impact of viruses on these conditions remains unclear. In recent years, research has emerged demonstrating a potential link between viruses and lower urinary tract diseases, including bladder cancer, prostate cancer, and overactive bladder. In this paper, the research of the correlation between viruses and lower urinary tract diseases and the related mechanisms were reviewed.