Research on immune checkpoints such as programmed death protein-1(PD-1)and cytotoxic T lymphocyte antigen-4(CTLA-4)has provided new directions for tumor treatment.V-domain immunoglobulin suppressor of T-cell activation(VISTA)is an emerging immune checkpoint within the B7 family.Functioning as both a ligand and a receptor,VISTA is an inhibitory immune checkpoint molecule expressed in tumor cells,myeloid cells and T lymphocytes.It plays a crucial role in regulating autoimmunity,inflammatory response and tumor immunity.The non-redundant interactions between VISTA and other immune checkpoints,such as PD-1,may offer new therapeutic strategies and serve as a new target for overcoming immunotherapy resistance.This review summarizes the recent research progress on VISTA in hematological tumors,aiming to provide new insights into its application in the treatment of these malignancies.

OBJECTIVE: This study aimed to evaluate the association between susceptibility genes and non-alcoholic fatty liver disease (NAFLD) in children with obesity. METHODS: We conducted a two-step case-control study. Ninety-three participants were subjected to whole-exome sequencing (exploratory set). Differential genes identified in the small sample were validated in 1,022 participants using multiplex polymerase chain reaction and high-throughput sequencing (validation set). RESULTS: In the exploratory set, 14 genes from the NAFLD-associated pathways were identified. In the validation set, after adjusting for sex, age, and body mass index, ECI2 rs2326408 (dominant model: OR = 1.33, 95% CI: 1.02-1.72; additive model: OR = 1.22, 95% CI: 1.01-1.47), C6orf201 rs659305 (dominant model: OR = 1.30, 95% CI: 1.01-1.69; additive model: OR = 1.21, 95% CI: 1.00-1.45), CALML5 rs10904516 (pre-ad dominant model: OR = 1.36, 95% CI: 1.01-1.83; adjusted dominant model: OR = 1.40, 95% CI: 1.03-1.91; and pre-ad additive model: OR = 1.26, 95% CI: 1.04-1.66) polymorphisms were significantly associated with NAFLD in children with obesity ( P < 0.05). Interaction analysis revealed that the gene-gene interaction model of CALML5 rs10904516, COX11 rs17209882, and SCD5 rs3733228 was optional ( P < 0.05), demonstrating a negative interaction between the three genes. CONCLUSION In the Chinese population, the CALML5 rs10904516, C6orf201 rs659305, and ECI2 rs2326408 variants could be genetic markers for NAFLD susceptibility.
Humans ; Non-alcoholic Fatty Liver Disease/genetics* ; Child ; Male ; Female ; Genetic Predisposition to Disease ; Case-Control Studies ; Exome Sequencing ; Adolescent ; Polymorphism, Single Nucleotide ; Obesity/complications* ; Pediatric Obesity/complications* ; China

At present,the diagnostic criteria for acute severe autoimmune hepatitis(AS-AIH)include acute onset,consistency with the diagnostic criteria for autoimmune hepatitis(AIH),presence of jaundice,and international normalized ratio≥1.5 at the time of diagnosis,without evidence of hepatic encephalopathy or previous liver disease.As a special subtype of AIH,AS-AIH is characterized by acute onset and rapid disease progression,and thus early diagnosis is of vital importance.Glucocorticoid therapy should be given as early as possible after diagnosis to prevent the progression to acute liver failure and reduce the risk of liver transplantation.Management of AS-AIH patients is challenging,since patients often lack typical clinical features and histological manifestations of AIH at the time of diagnosis,and early assessment of glucocorticoid response and a treatment regimen with proper doses are important for improving the prognosis of patients.

Neonatal sepsis is a global health problem that seriously affects the body health and life safety of newborns. It has a higher incidence in preterm infants,especially for early-onset sepsis (EOS) within 72 hours of birth. The diagnosis of neonatal EOS requires a series of examinations,and early and accurate diagnosis can improve clinical outcomes and reduce antibiotic overuse in a timely manner. At present,the commonly used biomarkers and traditional blood culture methods for EOS diagnosis have certain shortcomings,so it is urgent to find new molecular diagnostic methods. This article summarizes and compares the early and novel diagnostic methods of neonatal EOS,in order to provide a reference for clinical practice.

At present,the diagnostic criteria for acute severe autoimmune hepatitis(AS-AIH)include acute onset,consistency with the diagnostic criteria for autoimmune hepatitis(AIH),presence of jaundice,and international normalized ratio≥1.5 at the time of diagnosis,without evidence of hepatic encephalopathy or previous liver disease.As a special subtype of AIH,AS-AIH is characterized by acute onset and rapid disease progression,and thus early diagnosis is of vital importance.Glucocorticoid therapy should be given as early as possible after diagnosis to prevent the progression to acute liver failure and reduce the risk of liver transplantation.Management of AS-AIH patients is challenging,since patients often lack typical clinical features and histological manifestations of AIH at the time of diagnosis,and early assessment of glucocorticoid response and a treatment regimen with proper doses are important for improving the prognosis of patients.

Neonatal sepsis is a global health problem that seriously affects the body health and life safety of newborns. It has a higher incidence in preterm infants,especially for early-onset sepsis (EOS) within 72 hours of birth. The diagnosis of neonatal EOS requires a series of examinations,and early and accurate diagnosis can improve clinical outcomes and reduce antibiotic overuse in a timely manner. At present,the commonly used biomarkers and traditional blood culture methods for EOS diagnosis have certain shortcomings,so it is urgent to find new molecular diagnostic methods. This article summarizes and compares the early and novel diagnostic methods of neonatal EOS,in order to provide a reference for clinical practice.

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1-L3 vertebrae were measured based on QCT.Spongy bones of T5-T10 vertebrae were segmented as RO1,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,MLBagging OP and RadBagging-OP had the best performances for classification of OP.In test set,AUC of MLBagging-OP,RadBagging-op and DLOP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P＞0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of(x)±1.96s),which were highly positively correlated(r=0.910-0.974,all P＜0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.

Objective To propose a measurement method based on improved YOLOv8 for the anterior segment parameters of ultrasonic biological microscopy(UBM)images to solve the problems of the ophthalmic ultrasound images in low quantity,high annotation cost and weak model generalization ability.Methods Firstly,data enhancement using StyleGAN3 was carried out to improve YOLOv8 model in decreased sensitivity to UBM images and increased generalization ability;secondly,the pseudo-labels of virtual UBM images were generated based on the YOLOv8 model with the original UBM images as the dataset and the method of pseudo-label self-training in semi-supervised learning;finally,the YOLOv8 model was trained with the expan-ded dataset and improved with the global context network(GCNet)module,and the prediction results of the YOLOv8 model were sorted using the key-point ranking algorithm,and the measurements of the anterior segment physiological parameters were computed after screening qualified images based on prior knowledge.Results Compared with the hand-labeled results by the ophthalmologists,the localization error of the StyleGAN3 data-enhanced and self-trained YOLOv8 model was(61.94±40.66)μm,and the mean relative errors for the measurements of anterior chamber angle distance,pupil diameter,ciliary sulcus distance,central corneal thickness,anterior chamber depth and lens thickness were 0.62％,1.35％,0.68％,4.87％,0.93％and 0.75％,respectively.Conclusion The method proposed enhances the accuracy of the measurement method for anterior segment parameters of UBM images,and can meet real-time requirements.[Chinese Medical Equipment Journal,2024,45(2):8-16]

Objective:To explore and analyze the clinical features of patients with immunoglobulin (Ig)G4-related hepatobiliary-pancreatic disease and the independent factors affecting the prognosis of IgG4-related sclerosing cholangitis (IgG4-SC).Methods:The clinical data of 179 adult cases diagnosed with IgG4-related hepato-pancreato-biliary disease in the Division of Gastroenterology and Hepatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2011 to December 2022 were retrospectively analyzed. Patients were divided into three groups: isolated IgG4-SC, IgG4-SC/type 1 autoimmune pancreatitis(type 1 AIP), and isolated AIP according to the clinical manifestations. Demographic characteristics, baseline biochemical immunological indexes, and imaging manifestations were analyzed. The treatment response rate and survival rate were compared. The COX proportional hazards model was used to analyze the independent factors related to prognosis.Results:The mean age of diagnosis of patients with IgG4-related hepatobiliary-pancreatic disease was 60.3±12.0 years. Males accounted for 74.9%, and the median follow-up time was 38 months. The 1-year clinical response rate of patients with isolated IgG4-SC was lower than that of IgG4-SC/AIP (67.9% vs. 91.7%, P=0.019), and the primary endpoint-free 5-year survival rate was significantly reduced (64.9% vs. 95.9%, P<0.001). COX regression analysis showed that having cirrhosis before treatment ( HR=6.708, P=0.004) and poor response after half a year of treatment ( HR=11.488, P=0.002) were independent risk factors associated with the occurrence of adverse events in hepatobiliary diseases among patients with IgG4-SC. Conclusions:The clinical response rate and survival rate of patients with isolated IgG4-SC are lower than those of patients with IgG4-SC/AIP. Patients with IgG4-SC who do not respond well at six months of treatment and who have progressed to cirrhosis before treatment are at significantly increased risk of adverse events.