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.

Background::Carotid intima-media thickness (IMT) and diameter, stiffness, and wave reflections, are independent and important clinical biomarkers and risk predictors for cardiovascular diseases. The purpose of the present study was to establish nationwide reference values of carotid properties for healthy Chinese adults and to explore potential clinical determinants.Methods::A total of 3053 healthy Han Chinese adults (1922 women) aged 18-79 years were enrolled at 28 collaborating tertiary centers throughout China between April 2021 and July 2022. The real-time tracking of common carotid artery walls was achieved by the radio frequency (RF) ultrasound system. The IMT, diameter, compliance coefficient, β stiffness, local pulse wave velocity (PWV), local systolic blood pressure, augmented pressure (AP), and augmentation index (AIx) were then automatically measured and reported. Data were stratified by age groups and sex. The relationships between age and carotid property parameters were analyzed by Jonckheere-Terpstra test and simple linear regressions. The major clinical determinants of carotid properties were identified by Pearson’s correlation, multiple linear regression, and analyses of covariance.Results::All the parameters of carotid properties demonstrated significantly age-related trajectories. Women showed thinner IMT, smaller carotid diameter, larger AP, and AIx than men. The β stiffness and PWV were significantly higher in men than women before forties, but the differences reversed after that. The increase rate of carotid IMT (5.5 μm/year in women and 5.8 μm/year in men) and diameter (0.03 mm/year in both men and women) were similar between men and women. For the stiffness and wave reflections, women showed significantly larger age-related variations than men as demonstrated by steeper regression slopes (all P for age by sex interaction <0.05). The blood pressures, body mass index (BMI), and triglyceride levels were identified as major clinical determinants of carotid properties with adjustment of age and sex. Conclusions::The age- and sex-specific reference values of carotid properties measured by RF ultrasound for healthy Chinese adults were established. The blood pressures, BMI, and triglyceride levels should be considered for clinical application of corresponding reference values.

Objective:To explore the effect of pentraxin 3 (PTX3) on memory improvement and Aβ expression in Alzheimer's disease (AD) model mice.Methods:(1) Ten 5-month-old 5×FAD mice were randomly divided into PTX3 group and model group ( n=5); 5 C57BL/6 wild-type mice at the same age were selected as control group; mice in the PTX3 group and control group were stereotactically injected 4 μL 0.5 g/L PTX3 or same dose of phosphate buffered saline (PBS); Morris water maze test was used to detect the learning and memory abilities, Y maze test was used to detect the short-term memory, and ELISA was used to obsevre the contents of Aβ 40 and Aβ 42 in the brain hemisphere. (2) Twenty-five 3-month-old 5×FAD mice were randomly divided into model group, 2 μg/kg PTX3 group, 4 μg/kg PTX3 group, 8 μg/kg PTX3 group, and 16 μg/kg PTX3 group ( n=5); 5 C57BL/6 wild-type mice at the same age were selected as control group; mice in the PTX3 groups were intranasally injected 2, 4, 8, and 16 μg/kg PTX3, respectively; those in the model group and control group were intranasally injected same dose of PBS; injection was given once every 96 h for a total of 7 times. Morris water maze test was used to detect the learning and memory abilities, Y maze test was used to detect the short-term memory, and ELISA was used to obsevre the contents of Aβ 40 and Aβ 42 in the hippocampus. Results:(1) Compared with the model group, the PTX3 group had significantly shorter platform latency, higher percentage of exploration time and higher percentage of spontaneous alternations ( P<0.05). Compared with those in model group ([63.38±21.42] pg/mL, [29.77±6.11] pg/mL), the concentrations of Aβ 40 and Aβ 42 in the brain tissues of PTX3 group ([15.87±2.11] pg/mL, [16.55±1.95] pg/mL) were statistically lower ( P<0.05). (2) Compared with the model group, the 16 μg/kg PTX3 group had significantly shorter escape latency and higher percentage of exploration time ( P<0.05); compared with the model group, the 2 μg/kg PTX3 group and 16 μg/kg PTX3 group had significantly higher percentage of spontaneous alternations ( P<0.05). The contents of Aβ 40 and Aβ 42 in the hippocampus of 8 μg/kg PTX3 group and 16 μg/kg PTX3 group were statistically lower compared with those in the model group ( P<0.05). Conclusion:PTX3 may attenuate cognitive deficits and decrease Aβ expression in the brain or hippocampus tissues of 5×FAD mice with AD.

Objective:To explore the efficacy and safety of domestic bortezomib in combination with lenalidomide and dexamethasone in the treatment of newly diagnosed multiple myeloma (NDMM) .Methods:This multicenter, prospective, single-arm clinical study included 126 patients with NDMM admitted to seven hospitals between December 2019 and January 2022. All patients received domestic bortezomib in combination with lenalidomide and dexamethasone (BLD regimen), and the efficacy, prognostic factors, and safety were analyzed.Results:Among the 126 patients with NDMM, 118 completed four cycles of treatment, with an overall response rate (ORR) of 93.22% (110/118) and a ≥very good partial response (VGPR) rate of 68.64% (81/118). Ultimately, 114 patients completed at least eight cycles of treatment, with an ORR of 92.98% (106/114) and a ≥VGPR rate of 77.19% (88/114). Eighteen patients underwent autologous hematopoietic stem cell transplantation after completing 6-8 cycles of the BLD regimen, with an ORR of 100% (18/18) and a ≥VGPR rate of 88.9% (16/18). The proportion of patients achieving ≥VGPR increased with the treatment duration, and factors such as staging and age did not significantly affect efficacy. Single-factor analysis showed that R2-ISS stage Ⅲ/Ⅳ, blood calcium >2.27 mmol/L, and failure to achieve VGPR after six cycles were adverse prognostic factors for progression-free survival (PFS) ( P<0.05), whereas failure to achieve VGPR after six cycles was an adverse prognostic factor for overall survival (OS) ( P<0.001). Multifactor analysis demonstrated that failure to achieve VGPR after six cycles is an independent adverse prognostic factor for PFS ( P=0.002). The incidence of hematologic adverse reactions was 16.7% (19/114), and nonhematologic adverse reactions were mainly mild to moderate, with no significant cardiac or renal adverse reactions observed. Conclusion:The BLD regimen is effective in treating NDMM, in which patients with high-risk genetic features are still achieving a high ≥VGPR rate, and the overall safety is good.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

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 investigate the risk factors for re-fracture after percutaneous kyphoplasty (PKP) in elderly patients with osteoporotic thoracolumbar compression fractures and to construct a line graph prediction model. Methods One hundred and eighty-two elderly patients with osteoporotic thoracolumbar compression fractures treated with PKP from January 2016 to November 2019 were selected for the study‚ and the patients were continuously followed up for 3 years after surgery. Clinical data were collected from both groups; Receiver operating characteristic (ROC) curve analysis was performed on the measures; Logistic regression analysis was performed to determine the independent risk factors affecting postoperative re-fracture in PKP; the R language software 4. 0 “rms” package was used to construct a predictive model for the line graph‚ and the calibration and decision curves were used to internally validate the predictive model for the line graph and for clinical evaluation of predictive performance. Results The differences between the two groups were statistically significant (P<0. 05) in terms of bone mineral density (BMD)‚ number of injured vertebrae‚ single-segment cement injection‚ type of cement distribution‚ cement leakage‚ difference in vertebral body height before and after PKP‚ and change in posterior convexity angle. The area under the curve (AUC) for BMD‚ number of injured vertebrae‚ single-segment cement injection volume‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity change were 0. 772‚ 0. 732‚ 0. 722‚ 0. 801‚ and 0. 813‚ respectively‚ and the best cutoff values were -3. 1‚ 2‚ 3. 9 ml‚ 0. 4 mm‚ and 8. 7°‚ respectively. BMD‚ number of injured vertebrae‚ single-segment cement injection volume‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity change were independent risk factors for re-fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fractures. The calibration curve of the column line graph prediction model was close to the original curve and the ideal curve with a C-index of 0. 818 (95% CI: 0. 762-0. 883)‚ and the model fit was good; the threshold value of the column line graph prediction model was >0. 22‚ which could provide a net clinical benefit‚ and the net clinical benefit was higher than the independent predictors. Conclusion BMD‚ number of injured vertebrae‚ single-segment cement injection‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity angle change are independent risk factors affecting the recurrent fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fracture‚ and this study constructs a column line graph model to predict the recurrent fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fracture as a predictor for clinical. This study provides an important reference for clinical prevention and treatment‚ and has clinical application value.

ObjectiveTo explore the molecular mechanism of Sanhuang Xiexintang （SHXXT） in protecting stress gastric ulcer （SGU） in rats through network pharmacology， molecular docking， and animal experiments. MethodThe active ingredients and corresponding targets in SHXXT were collected and screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Traditional Chinese Medicine Information Database （TCMID）， Bioinformation Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine （BATMAN-TCM）， and Swiss Target Prediction database. SGU-related targets were screened from the Online Mendelian Inheritance in Man （OMIM）， Therapeutic Target Database （TTD）， GeneCards database， and PharmGKB database. Herbal-ingredient-target （H-C-T） network was constructed by using Cytoscape 3.9.1 software. Protein-protein interaction （PPI） of drug and disease intersection targets was analyzed by using the Protein Interaction Platform （STRING） database. Gene ontology （GO） enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis were conducted through the Database for Annotation Visualization and Integrated Discovery （DAVID）. The active ingredients and key targets were validated using AutodockVina 1.2.2 molecular docking software， and the experimental results were further validated through animal experiments. ResultThe 55 active ingredients were screened， and 255 potential target genes for SHXXT treatment of SGU were predicted. The PPI analysis showed that protein kinase B （Akt）， phosphatase and tensin homolog deleted on chromosome ten （PTEN）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and cyclooxygenase-2 （COX-2） are the core targets of SHXXT for protecting SGU. GO and KEGG analyses showed that SHXXT may affect the development of SGU by regulating various biological processes such as the phosphoinositide 3-kinase （PI3K）/Akt signaling pathway and inflammatory processes. The molecular docking results showed that both the active ingredients and key targets had good binding ability. Animal experiments showed that compared with the blank group， the ulcer index （UI） of the model group was significantly increased （P<0.01）， and the serum levels of TNF-α and IL-1β significantly increased （P<0.01）. The phosphorylation level of PTEN in gastric mucosal tissue was significantly down-regulated （P<0.05）. The phosphorylation levels of PI3K， Akt， and nuclear factor kappa-B （NF-κB） were significantly up-regulated （P<0.05）. Compared with the model group， the UI of the treatment group was significantly reduced （P<0.01）， and the serum levels of TNF-α and IL-1β were significantly reduced （P<0.01）. The phosphorylation level of PTEN in gastric mucosal tissue was significantly up-regulated （P<0.01）， and the phosphorylation levels of PI3K， Akt， and NF-κB were significantly downregulated （P<0.01）. ConclusionThe application of network pharmacology prediction， molecular docking simulation， and animal experimental validation confirms that SHXXT regulates the PI3K/Akt/NF-κB signaling pathway to regulate the inflammatory response of rats and thus protects the gastric mucosa of SGU rats.