Objective:Glioblastoma(GBM)and brain metastases(BMs)are the two most common malignant brain tumors in adults.Magnetic resonance imaging(MRI)is a commonly used method for screening and evaluating the prognosis of brain tumors,but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited.In recent years,deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system.This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases(SBMs),and to further explore the impact of multimodality data fusion on classification tasks. Methods:Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed.First,structural T1-weight,T1C-weight,and T2-weight were selected as 3 inputs to the entire model,regions of interest(ROIs)were manually delineated on the registered three modal MR images,and multimodality radiomics features were obtained,dimensions were reduced using a random forest(RF)-based feature selection method,and the importance of each feature was further analyzed.Secondly,we used the method of contrast disentangled to find the shared features and complementary features between different modal features.Finally,the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. Results:The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs.Furthermore,compared with single-modal data,the multimodal fusion models using machine learning algorithms such as support vector machine(SVM),Logistic regression,RF,adaptive boosting(AdaBoost),and gradient boosting decision tree(GBDT)achieved significant improvements,with area under the curve(AUC)values of 0.974,0.978,0.943,0.938,and 0.947,respectively;our comparative disentangled multi-modal MR fusion method performs well,and the results of AUC,accuracy(ACC),sensitivity(SEN)and specificity(SPE)in the test set were 0.985,0.984,0.900,and 0.990,respectively.Compared with other multi-modal fusion methods,AUC,ACC,and SEN in this study all achieved the best performance.In the ablation experiment to verify the effects of each module component in this study,AUC,ACC,and SEN increased by 1.6%,10.9%and 15.0%,respectively after 3 loss functions were used simultaneously. Conclusion:A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

Background and objective Pembrolizumab(PEM)has been shown to be effective in clinical trials for the treatment of advanced non-small cell lung cancer(NSCLC),but clinical trials were based on cohorts of patients selected on specific criteria,and whether the findings are consistent with real-world patients is debatable.The aim of this study is to evaluate the efficacy and safety of PEM in the treatment of advanced NSCLC based on real-world data.Methods A retro-spective collection of real-world data from patients with advanced NSCLC receiving PEM was conducted.Propensity score matching was used to eliminate inter-group differences and assess the efficacy and safety of PEM compared to chemotherapy.Results Among 450 matched patients,the incidence rates of any-grade adverse events were 79.87％in the PEM group and86.71％inthe chemotherapy group,while the incidence rates of grade＞3 adverse events were 4.03％and 7.31％,respectively.The objective response rates were 48.63％for PEM and 36.00％for chemotherapy(P=0.011).The median progression-free survival was 15.5 months for PEM and 8.8 months for chemotherapy(P＜0.001),and the median overall survival was not reached for PEM and 26.2 months for chemotherapy(P＜0.001).Conclusion PEM treatment for advanced NSCLC demonstrates favorable survival outcomes and acceptable safety in real-world clinical practice.

Objective:To evaluate direct and indirect costs for schizophrenia,major depressive disorder(MDD)and bipolar disorder,and to compare their differences of cost composition,and to explore the drivers of the total costs.Methods:A total of 3 175 inpatients with schizophrenia,MDD,and bipolar disorder were recruited.In-patient's self-report total direct of medical costs outpatient and inpatient,out-of-pocket costs,and direct non-medical costs were regarded as direct costs.Productivity loss and other loss caused by damaging properties were defined as indirect costs.The perspectives of this study included individual and societal levels.Multivariate regression analysis was applied for detecting the factors influencing disease costs.Results:The total cost of schizophrenia was higher than those of MDD and bipolar disorder at individual and societal levels.The indirect costs of three mental disorders were higher than the direct costs,and the indirect cost ratio of bipolar disorder was higher than those of schizophre-nia and MDD.Age,gender,working condition and marital status(P＜0.05)were the important drivers of total costs.Conclusion:The economic burden of the three mental disorders is relatively heavy.Schizophrenia has heaviest disease burden,and the productivity loss due to mental disorders is the driving force of the soaring disease cost

Oral squamous cell carcinoma (OSCC) is a prevalent malignant tumor affecting the head and neck region (Leemans et al., 2018). It is often diagnosed at a later stage, leading to a poor prognosis (Muzaffar et al., 2021; Li et al., 2023). Despite advances in OSCC treatment, the overall 5-year survival rate of OSCC patients remains alarmingly low, falling below 50% (Jehn et al., 2019; Johnson et al., 2020). According to statistics, only 50% of patients with oral cancer can be treated with surgery. Once discovered, it is more frequently at an advanced stage. In addition, owing to the aggressively invasive and metastatic characteristics of OSCC, most patients die within one year of diagnosis. Hence, the pursuit of novel therapeutic drugs and treatments to improve the response of oral cancer to medication, along with a deeper understanding of their effects, remains crucial objectives in oral cancer research (Johnson et al., 2020; Bhat et al., 2021; Chen et al., 2023; Ruffin et al., 2023).
Humans ; Mouth Neoplasms/pathology* ; Carcinoma, Squamous Cell/metabolism* ; Luteolin/therapeutic use* ; Squamous Cell Carcinoma of Head and Neck/drug therapy* ; Head and Neck Neoplasms/drug therapy* ; Cell Line, Tumor

Objective:To investigate the effect of LRRK2G2019S mutation on activation of microglia after iron deprivation and its mechanism.Methods:(1) Microglia were differentiated from human induced pluripotent stem cells (IPSC) with the help of hematopoietic progenitor cells (HPC) and identified by immunofluorescent staining, and α-synuclein (α-syn) A53T mutant protein was obtained by protein purification technology. (2) Microglia were divided into control group, α-syn group, α-syn+ deferoxamine (DFO) group; phosphate buffer solution (PBS), 1 μmol/L purified α-syn A53T mutant protein, 1 μmol/L purified α-syn A53T mutant protein+30 mmol/L DFO were given respectively for 24 h. Fe 2+ concentration was detected by colorimetry, Rab35 protein expression was detected by Western blotting, intracellular reactive oxygen species (ROS) level was detected by flow cytometry, and interleukin-6 ( IL-6), tumor necrosis factor-α ( TNF-α) and transforming growth factor-β ( TGF-β) mRNA expressions were detected by real time-PCR (RT-PCR); microglia culture supernatant (MCS) in the 3 groups were transfered to SH-SY5Y cells, and SH-SY5Y cell apoptosis was detected by flow cytometry. (3) Bidirectional DNA sequencing was used to detect leucine rich repeat kinase 2 ( LRRK2) gene mutations in microglia treated with 1 μmol/L purified α-syn A53T mutant protein. Microglia were divided into control group, α-syn group and α-syn+GSK3357679A group, and treated with corresponding drugs for 24 h, respectively (LRRK2 inhibitor GSK3357679A concentration: 10 nmol/L), and LRRK2 protein expression was detected by Western blotting; microglia were divided into control group, α-syn group, α-syn+GSK3357679A, and α-syn+GSK3357679A+DFO group, and treated with corresponding drugs for 24 h, Rab35 protein expression was detected by Western blotting, intracellular ROS level was detected by flow cytometry, and IL-6, TNF-α and TGF-β mRNA expressions were detected by RT-PCR. (4) Microglia were divided into control group, α-syn group, α-syn+rapamycin (RAPA) group, and treated with corresponding drugs for 24 h (concentration of autophagy inducer RAPA: 50 nmol/L); protein expressions of Rab35, P62 and microtubule-associated protein light chain 3 II (LC3II) were detected by Western blotting; intracellular ROS level was detected by flow cytometry, and IL-6, TNF-α and TGF-β mRNA expressions were detected by RT-PCR. (5) Microglia were divided into control group, α-syn group, and α-syn+Rab35 group, and treated with corresponding drugs for 24 h (concentration of Rab35 overexpressed plasmids: 1 μg/mL); Rab35, P62, and LC3II protein expressions were detected by Western blotting; ROS level was detected by flow cytometry, and IL-6, TNF-α and TGF-β mRNA expressions were detected by RT-PCR. Results:(1) Immunofluorescent staining showed negative neuronal nuclei (NeuN) expression and positive ionized calcium-binding adapter molecule 1 (Iba1) expression in microglia, and high LRRK2 expression; PcDNA3.1-SNCA-A53T expression plasmid was constructed and α-syn A53T mutant protein was purified. (2) The Fe 2+ concentration in α-syn group was significantly higher than that in control group, and the Fe 2+ concentration in α-syn+DFO group was significantly lower than that in α-syn group ( P<0.05); the Rab35 protein and TGF-β mRNA expressions in control group, α-syn group and α-syn+DFO group were decreased successively, while the IL-6 and TNF-α mRNA expressions were increased successively, with significant differences ( P<0.05); ROS level and SH-SY5Y cell apoptosis rate in control group, α-syn group, α-syn+DFO group were increased successively. (3) Bidirectional DNA sequencing showed that the LRRK2G2019S mutation in microglia was the most obvious after α-syn A53T mutant protein stimulation; compared with the control group, the α-syn group had significantly increased LRRK2 protein expression, while the α-syn+GSK3357679A group had significantly decreased LRRK2 protein expression compared with α-syn group ( P<0.05); compared with the control group, the α-syn group had significantly decreased Rab35 protein and TGF-β mRNA expressions, and statistically increased IL-6 and TNF-α mRNA expressions ( P<0.05); compared with α-syn group, the α-syn+GSK3357679A group had significantly increased Rab35 protein and TGF-β mRNA expressions, and statistically decreased IL-6 and TNF-α mRNA expressions ( P<0.05); compared with α-syn+GSK3357679A group, α-syn+GSK3357679A+DFO group had significantly increased IL-6 and TNF-α mRNA expressions, and significantly decreased Rab35 protein and TGF-β mRNA expressions ( P<0.05). The α-syn group had higher ROS level than the control group, the α-syn+GSK3357679A group had lower ROS level than the α-syn group, and the α-syn+GSK3357679A+DFO group had higher ROS level than the α-syn+GSK3357679A group. (4) Compared with the control group, the α-syn group had significantly decreased Rab35 and LC3II protein, and TGF-β mRNA expressions, and significantly increased P62 protein, IL-6 and TNF-α mRNA expressions ( P<0.05); compared with α-syn group, the α-syn+RAPA group had significantly increased Rab35 and LC3II protein, and TGF-β mRNA expressions, and significantly decreased P62 protein, and IL-6 and TNF-α mRNA expressions ( P<0.05); the α-syn group had higher ROS level than the control group and α-syn+RAPA group. (5) Compared with the control group, the α-syn group had significantly decreased Rab35 and LC3II protein, and TGF-β mRNA expressions, and statistically increased P62 protein, and IL-6 and TNF-α mRNA expressions ( P<0.05); compared with the α-syn group, the α-syn+Rab35 group had significantly increased Rab35 and LC3II protein, and TGF-β mRNA expressions, and significantly decreased P62 protein, and IL-6 and TNF-α mRNA expressions ( P<0.05). The α-syn group had higher ROS level than the control group and α-syn+Rab35 group. Conclusion:LRRK2G2019S can induce neuroinflammation by inhibiting Rab35-related autophagy under iron deprivation, and Rab35 is expected to be a key factor in intervening neuroinflammation.

Objective:To investigate the clinical and pathological features of congenital hepatic fibrosis (CHF).Methods:The clinical and pathological findings of 20 patients diagnosed with CHF from 2017 to 2023 were retrospectively analyzed.Results:Among the 20 patients, 8 were males and 12 were females with a median age of 21.5 years. Mostly patients were admitted to the hospital with cirrhosis, portal hypertension and upper gastrointestinal bleeding. Pathological features were diffuse fibrosis in the portal area, formation of fibrous septa of varying width, segmentation of the liver parenchyma, with hyperplasia of small bile ducts. Among them, 1 case (5%) was complicated with Caroli's disease, and 1 case (5%) was HNF1α hepatocellular adenoma. IHC GS showed that was positively expressed in acinar region 3 in 75% cases.Conclusion:CHF is mainly manifested by portal hypertension and its complications. Histopathology is the gold standard for diagnosis. The possibility of CHF should be considered first in children and adolescents with portal hypertension but no history of hepatitis, and complicated kidney disease. The positive pattern of acinus-3 region of GS in IHC is helpful for the diagnosis of CHF.

Influenza is an infectious respiratory disease caused by the influenza viruses. Older people, infants and people with underlying medical conditions could have a higher risk of severe influenza symptoms and complications. The co-infection of Coronavirus Diseases 2019 (COVID-19) with influenza viruses could lead to the complication of prevention, diagnosis, control, treatment, and recovery of COVID-19. Influenza vaccine and COVID-19 vaccine overlapped in target populations, vaccination time, and inoculation units. Although there was insufficient evidence on the immunogenicity and safety of co-administration of influenza vaccine and COVID-19 vaccine, World Health Organization and some countries recommended co-administration of inactivated influenza vaccine and COVID-19 vaccine. This review summarized domestic and international vaccination policies and research progress, and put forward corresponding suggestions in order to provide scientific support for the formulation of vaccination strategy on seasonal influenza vaccine and COVID-19 vaccine.
Aged ; COVID-19 ; COVID-19 Vaccines ; China ; Humans ; Infant ; Influenza Vaccines ; Influenza, Human/prevention & control* ; Pandemics/prevention & control* ; SARS-CoV-2 ; Seasons ; Vaccination

OBJECTIVES: The automatic delineation of organs at risk (OARs) can help doctors make radiotherapy plans efficiently and accurately, and effectively improve the accuracy of radiotherapy and the therapeutic effect. Therefore, this study aims to propose an automatic delineation method for OARs in cervical cancer scenarios of both after-loading and external irradiation. At the same time, the similarity of OARs structure between different scenes is used to improve the segmentation accuracy of OARs in difficult segmentations. METHODS: Our ensemble model adopted the strategy of ensemble learning. The model obtained from the pre-training based on the after-loading and external irradiation was introduced into the integrated model as a feature extraction module. The data in different scenes were trained alternately, and the personalized features of the OARs within the model and the common features of the OARs between scenes were introduced. Computer tomography (CT) images for 84 cases of after-loading and 46 cases of external irradiation were collected as the train data set. Five-fold cross-validation was adopted to split training sets and test sets. The five-fold average dice similarity coefficient (DSC) served as the figure-of-merit in evaluating the segmentation model. RESULTS: The DSCs of the OARs (the rectum and bladder in the after-loading images and the bladder in the external irradiation images) were higher than 0.7. Compared with using an independent residual U-net (convolutional networks for biomedical image segmentation) model [residual U-net (Res-Unet)] delineate OARs, the proposed model can effectively improve the segmentation performance of difficult OARs (the sigmoid in the after-loading CT images and the rectum in the external irradiation images), and the DSCs were increased by more than 3%. CONCLUSIONS Comparing to the dedicated models, our ensemble model achieves the comparable result in segmentation of OARs for different treatment options in cervical cancer radiotherapy, which may be shorten time for doctors to sketch OARs and improve doctor's work efficiency.
Female ; Humans ; Image Processing, Computer-Assisted/methods* ; Machine Learning ; Organs at Risk/radiation effects* ; Radiotherapy Planning, Computer-Assisted/methods* ; Uterine Cervical Neoplasms/radiotherapy*

Objective:To construct a simple, precise and personalized comprehensive nomogram for prediction the risk of multidrug-resistant tuberculosis (MDR-TB) and to evaluate its prediction value among individuals with previous tuberculosis history (PTBH).Methods:A matched case-control study (1∶2 ratios) was performed in 1 881 patients with PTBH treated in 12 designated tuberculosis hospitals in Hangzhou City between January 1, 2005 and December 31, 2019, and there were 1 719 patients in training set, and 162 in validation set. A multivariable Cox regression analysis was used to evaluate independent predictors for the incident of MDR-TB in individuals with PTBH. A comprehensive nomogram was developed based on the multivariable Cox model. The accuracy of the prediction was assessed using concordance index (C-index), calibration curve and area under the receiver operator characteristic (ROC) curve.Results:The nomogram constructed based on the multivariable Cox regression model incorporated 10 independent predictors of the risk of MDR-TB. A history of direct contact (grade 1, 0-100.0 points) ranked on the top of all risk factors, followed by duration of positive sputum culture (grade 2, 0-84.5 points), unfavorable treatment outcome (grade 3, 0-52.0 points), human immunodeficiency virus infection (grade 4, 0-48.5 points), retreated tuberculosis history (grade 5, 0-40.0 points), non-standardized treatment regimens of retreated tuberculosis (grade 6, 0-32.5 points), duration of pulmonary cavities (grade 7, 0-31.0 points), passive mode of tuberculosis case finding (grade 8, 0-25.0 points), age<60 years (grade 9, 0-17.5 points), and standard frequencies of chest X-ray examination (grade 10, 0-14.0 points). The C-indexes of this nomogram for the training and validation sets were 0.833 (95% confidence interval ( CI) 0.807-0.859) and 0.871 (95% CI 0.773-0.969), respectively, indicating that the nomogram had good fitting effect. The calibration curves for the risk of incident MDR-TB showed an optimal agreement between nomogram prediction and actual observation in the training and validation sets, respectively.The areas under ROC curve of the 1-year, 5-year, and 10-year MDR-TB risk probability of the training set were 0.904, 0.921, and 0.908, respectively, and those of the validation set were 0.954, 0.970, and 0.919, respectively. Conclusion:Through this nomogram model, clinicians could precisely predict the risk of incident MDR-TB among individuals with PTBH in the clinical practice.

COVID-19 is caused by the 2019 novel coronavirus (2019-nCoV). COVID-19 clinical cases are considered as the principal source of infection, however, asymptomatic cases may also play a role in the transmission. Significant gap exists in terms of the proportion or prevalence and transmissibility of asymptomatic cases. This study design plans to use data from areas with different epidemiological profiles to investigate the COVID-19 epidemic in China. In each selected region, both general community residents and key populations at high risk of COVID-19 infection, including recovered COVID-19 cases, close contacts of confirmed COVID-19 cases, medical professionals, investigators at CDCs, and visitors to fever clinics, will be recruited and examined for viral RNA of 2019-nCoV and serum antibodies. Prevalence and characterization of asymptomatic cases will be determined, stratified by varied demographics and exposure risk. During the follow-up, the change in the serum antibodies will be studied prospectively in the symptomatic and asymptomatic cases to address the scientific and public health concerns of infectivity and transmissibility of 2019-nCoV.