Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

China is a country with a high incidence of esophageal cancer.The pathological type is mainly squamous cell carcinoma.Squamous intraepithelial neoplasia is the most recognized precancerous lesion of esopha-geal squamous cell carcinoma,and its monitoring and intervention is an effective method to reduce the incidence of esophageal squamous cell carcinoma and improve the quality of life of patients.Understanding the etiology,clinical features,diagnosis and treatment of esophageal squamous cell carcinoma plays a crucial role in the prevention and early diagnosis and treatment of esophageal squamous cell carcinoma.At present,the clinical research related to esophageal squamous intraepithelial neoplasia is still insufficient,and there are some differences in clinical treat-ment.This review summarizes the risk factors,clinical features,diagnosis,prognosis and treatment of esophageal squamous intraepithelial neoplasia,hoping to provide ideas for the clinical management of esophageal squamous intraepithelial neoplasia.

Objective The leptin receptor,encoded by the LEPR gene,is involved in tumorigenesis.A potential functional variant of LEPR,rs1137101(Gln223Arg),has been extensively investigated for its contribution to the risk of digestive system(DS)cancers,but results remain conflicting rather than conclusive.Here,we performed a case-control study and subsequent meta-analysis to examine the association between rs1137101 and DS cancer risk. Methods A total of 1,727 patients with cancer(gastric/liver/colorectal:460/480/787)and 800 healthy controls were recruited.Genotyping of rs1137101 was conducted using a polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP)assay and confirmed using Sanger sequencing.Twenty-four eligible studies were included in the meta-analysis. Results After Bonferroni correction,the case-control study revealed that rs1137101 was significantly associated with the risk of liver cancer in the Hubei Chinese population.The meta-analysis suggested that rs1137101 is significantly associated with the risk of overall DS,gastric,and liver cancer in the Chinese population. Conclusion The LEPR rs1137101 variant may be a genetic biomarker for susceptibility to DS cancers(especially liver and gastric cancer)in the Chinese population.

Objective To explore the clinical characteristics of pediatric patients with cerebral palsy(CP)who also have comorbid epilepsy.Methods A retrospective analysis was conducted on the clinical data of 155 pediatric patients with CP and comorbid epilepsy admitted to the Third Affiliated Hospital of Zhengzhou University from January 2019 to December 2022.Patients were divided into 4 groups based on CP subtype:spastic diplegia group(n=29),spastic hemiplegia group(n=33),spastic quadriplegia group(n=73),and non-spastic group(n=20).Differences in sex,season of birth,birth weight,gestational age,and the relationship between gestational age and weight were compared among the groups.Additionally,the relationships between perinatal risk factors,MRI classification system(MRICS),gross motor function classification system(GMFCS),and the age of the first onset of epilepsy with respect to CP subtype were analyzed.Results Among the 155 patients,101 were male and 54 were female.A lower proportion of patients with spastic hemiplegia was observed with a gestational age of 28-31+6 weeks compared with those with spastic diplegia and spastic quadriplegia(P=0.009).The proportion of patients with a history of asphyxia in spastic hemiplegia group was significantly lower than that in the other 3 groups,and the proportion of patients with hypoxic-ischemic encephalopathy(HIE)in spastic hemiplegia group was significantly lower than in that both spastic quadriplegia group and non-spastic group(P<0.05).The proportion of patients in spastic quadriplegia group who had their first seizure at an age of<1 year was significantly higher than that in spastic diplegic group(P=0.041).The spastic diplegia group exhibited a higher percentage of white matter damage compared with the other 3 groups,and had a lower percentage of gray matter damage compared with both spastic hemiplegic group and non-spastic group(P=0.001).The proportion of patients with GMFCS levels Ⅳ-Ⅴ in spastic quadriplegia group was higher than those in the other 3 groups(P<0.001),and the proportion of patients with levels Ⅰ-Ⅲ in spastic hemiplegia group was significantly higher than those in spastic quadriplegia group and non-spastic group(P<0.001).Conclusion Significant differences were observed among pediatric patients with different subtypes of CP and comorbid epilepsy in factors such as gestational age,history of asphyxia,HIE history,age of first seizure,MRICS classification and GMFCS levels.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To compare the anesthetic potency of dexmedetomidine combined with remifentanil for colonoscopy in the patients with different body mass indexes (BMIs) to assess the clinical significance of the influence of weight on the level of pain during the procedure.Methods:American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ patients, aged 18-64 yr, undergoing elective colonoscopy, were divided into 3 groups based on the BMI: group Ⅰ (underweight group, BMI<18.5 kg/m 2), group Ⅱ (normal weight group, BMI 18.5-24.0 kg/m 2), and group III (overweight group, 24.0 kg/m 2 < BMI <30.0 kg/m 2). The prescribed dose of dexmedetomidine was infused within 2 min, then remifentanil was infused as a bolus of 1 μg/kg within 2 min followed by an infusion of 0.1 μg · kg -1 · min -1 throughout the surgery, and then colonoscopy was performed in patients of each group. The up-and-down sequential allocation was used to determine the dose of dexmedetomidine, the initial dose of dexmedetomidine in each group was 0.3 μg/kg, and the ratio between the two successive doses was 1.2. The positive response was defined as the Modified Observer′s Assessment of Alertness/Sedation Scale score > 1 and occurrence of body movement during the operation. Each time the dose of dexmedetomidine increased/decreased in the next patient depending on whether or not the response was positive. The median effective dose (ED 50) and 95% confidence interval ( CI) of dexmedetomidine were calculated using the Dixon-Massey formula. Results:Compared with group Ⅰ (0.42 [95% CI 0.38-0.47] μg/kg), the ED 50 of dexmedetomidine was significantly decreased in group II (0.23 [95% CI 0.19-0.32] μg/kg) and in group III (0.18 [95% CI 0.13-0.22] μg/kg) ( P<0.05). The ED 50 of dexmedetomidine was significantly decreased in group Ⅲ when compared with group Ⅱ ( P<0.05). Conclusions:With the increase of patients′ BMIs, the anesthetic potency of dexmedetomidine for colonoscopy is significantly enhanced when combined with remifentanil, indicating that clinicians should pay attention to the influence of weight on the level of pain during procedures.

The number of investigator initiated research (IIR) is increasing. But the recognition and management of IIR in China is still in its infancy, and there is a lack of specific and operable guidance for the implementation process. Based on our practical experiences, previous literature reports, and current policy regulations, the authors took prospective IIR as an example to summarize the implementation process of IIR into 14 steps, which are as the following: study initiation, ethical review, study registration, study filing, case report form design, database establishment, standard operating procedure making, investigator training, informed consent, data collection, data entry, data verification, data locking and data archiving.

Platelets are reprogrammed by cancer via a process called education, which favors cancer development. The transcriptional profile of tumor-educated platelets (TEPs) is skewed and therefore practicable for cancer detection. This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n = 3; Netherlands, n = 5; Poland, n = 1) between September 2016 and May 2019. The main outcomes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889-0.948), 0.923 (0.855-0.990), 0.918 (0.872-0.963), and 0.887 (0.813-0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889-0.955) in the combined validation cohort; 0.955 (0.912-0.997) in VC1; 0.939 (0.901-0.977) in VC2; 0.917 (0.824-1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, and early-stage ovarian cancer. However, these observations warrant prospective validations in a larger population before clinical utilities.
Humans ; Female ; Blood Platelets/pathology* ; Biomarkers, Tumor/genetics* ; Ovarian Neoplasms/pathology* ; China