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.

Objective:To investigate the association of urinary cadmium levels with peripheral leukocyte classification counts among middle-aged and older adults aged 40 to 89 years in selected areas of China.Methods:The research was based on the survey of the impact of soil quality of agricultural land on human health in typical areas conducted in 2019-2020. A total of 5 600 middle-aged and older adults aged 40 to 89 years were included by using a multi-stage stratified random sampling method. Baseline characteristics of the subjects were collected and physical examinations were performed. Random midstream urine was collected to measure urinary cadmium and urinary creatinine and fasting venous blood was collected to measure the leukocyte count, neutrophil count, lymphocyte count, monocyte count and eosinophil count. The linear mixed effect model was used to analyse the association of urinary cadmium levels with leukocyte classification counts, and the dose-response relationship between them was analyzed by using the restricted cubic spline (RCS) function.Results:The age of the subjects was (63.17±12.02) years; 2 851 (50.91%) were males; and the M ( Q 1, Q 3) of urinary creatinine-corrected urinary cadmium levels was 2.69 (1.52, 4.69) μg/g·creatinine. After adjusting for confounding factors, the results of linear mixed effects model analysis showed that for each 1-unit increase in urinary creatinine-corrected urinary cadmium level, the percentage change [% (95% CI)] of leukocyte count and lymphocyte count was -1.70% (-2.61%, -0.79%) and -1.57% (-2.86%, -0.26%), respectively. RCS function showed a negative linear relationship between urinary creatinine-corrected urinary cadmium levels and leukocyte counts and lymphocyte counts, respectively (all Pnon-linear>0.05). Conclusion:Urinary cadmium levels are negatively associated with leukocyte count and lymphocyte count among middle-aged and older adults aged 40 to 89 years in selected areas of China.

Objective:To investigate the association of urinary cadmium levels with peripheral leukocyte classification counts among middle-aged and older adults aged 40 to 89 years in selected areas of China.Methods:The research was based on the survey of the impact of soil quality of agricultural land on human health in typical areas conducted in 2019-2020. A total of 5 600 middle-aged and older adults aged 40 to 89 years were included by using a multi-stage stratified random sampling method. Baseline characteristics of the subjects were collected and physical examinations were performed. Random midstream urine was collected to measure urinary cadmium and urinary creatinine and fasting venous blood was collected to measure the leukocyte count, neutrophil count, lymphocyte count, monocyte count and eosinophil count. The linear mixed effect model was used to analyse the association of urinary cadmium levels with leukocyte classification counts, and the dose-response relationship between them was analyzed by using the restricted cubic spline (RCS) function.Results:The age of the subjects was (63.17±12.02) years; 2 851 (50.91%) were males; and the M ( Q 1, Q 3) of urinary creatinine-corrected urinary cadmium levels was 2.69 (1.52, 4.69) μg/g·creatinine. After adjusting for confounding factors, the results of linear mixed effects model analysis showed that for each 1-unit increase in urinary creatinine-corrected urinary cadmium level, the percentage change [% (95% CI)] of leukocyte count and lymphocyte count was -1.70% (-2.61%, -0.79%) and -1.57% (-2.86%, -0.26%), respectively. RCS function showed a negative linear relationship between urinary creatinine-corrected urinary cadmium levels and leukocyte counts and lymphocyte counts, respectively (all Pnon-linear>0.05). Conclusion:Urinary cadmium levels are negatively associated with leukocyte count and lymphocyte count among middle-aged and older adults aged 40 to 89 years in selected areas of China.

Objective To quantitatively study the correlation between T1ρ and T2 values of glenohumeral articular cartilage and the degree of rotator cuff injury.Methods A total of 149 patients with rotator cuff injury and healthy volunteers were prospectively selected.All of them underwent MRI routine scanning and T1 ρ and T2 mapping sequences.The degree of rotator cuff injury was graded,and the T1ρ and T2 values of glenohumeral articular cartilage were measured to analyze their relationship.Results With the development of rotator cuff injury grading,the T1 ρ and T2 values of glenohumeral articular cartilage increased.There were statistically significant differences in T1ρ and T2 values of articular cartilage between the different grades of rotator cuff injury(P＜0.001).Conclusion The injury of glenohumeral articular cartilage is aggravated with the severity of rotator cuff injury.The severity of rotator cuff injury can be evaluated by analyzing the T1 ρ and T2 values of glenohumeral articular cartilage.

Objective To explore the value of measuring infrapatellar fat pad(IPFP)and muscle fat fraction(FF)around the knee joint based on iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification(IDEAL-IQ)quantitative technology in patients with knee osteoarthritis(KOA)for the degree of KOA.Methods A total of 106 participants were included in this study.Participants were grouped based on Kellgren-Lawrence grading(KLG),divided into no KOA group,mild KOA group and severe KOA group.The IDEAL-IQ technology was used to measure FF values of IPFP and muscles around the knee joint,the correlation between FF values and KOA was analyzed,and its value in diagnosing KOA was evaluated.Results In severe KOA group and mild KOA group can be observed in the way of lower IPFP FF values and higher FF values muscles around the knee joint.The FF values of IPFP and part of the muscles around the knee joint[vastus medialis muscle(VM),vastus lateralis muscle(VL),semimembranosus(SE),sartorius(SA),medial head of gastrocnemius muscle(Gas(media)),lateral head of gastrocnemius muscle(Gas(lateral))]were correlated with the degree of KOA(r/rs=-0.708,0.737,0.567,0.468,0.280,0.491,0.378),the area under the curve(AUC)for diagnosing KOA were 0.850,0.950,0.842,0.759,0.692,0.763,and 0.725,respectively.Conclusion IDEAL-IQ sequence can quantitatively assess fat infiltration of IPFP and muscles around the knee joint in patients with KOA,and has certain potential to predict the development and severity of KOA.

Bowel sounds can reflect the movement and health status of the gastrointestinal tract.However,the traditional manual auscultation method has subjective deviation and is time-consuming and labor-intensive.In order to better assist doctors in diagnosing bowel sounds and improve the reliability and efficiency of bowel sound detection,this study proposed a deep neural network model that combines a residual neural network(ResNet),a bidirectional long short-term memory network(BiLSTM),and an attention mechanism.Firstly,a large number of labeled clinical data was collected using the self-developed multi-channel bowel sound acquisition system,and the multi-scale wavelet decomposition and reconstruction method was used to preprocess the bowel sounds.Then,log Mel spectrogram features were extracted and sent to the network for training.Finally,the performance and effectiveness of the model were evaluated and verified by 10-fold cross-validation and an ablation experiment.The experimental results showed that the precision,recall,and F1 score of the model reached 83%,76%,and 79%,respectively,and it could effectively detect bowel sound segments and locate their start and end times,performing better than previous algorithms.This algorithm can not only provide auxiliary information for doctors in clinical practice but also offer technical support for further analysis and research of bowel sounds.

Migraine is one of the most prevalent and disabling neurological disease, but the current pharmacotherapies show limited efficacy and often accompanied by adverse effects. Acupuncture is a promising complementary therapy, but further clinical evidence is needed. The influence of acupuncture on migraine is not an immediate effect, and its mechanism remains unclear. This study aims to provide further clinical evidence for the anti-migraine effects of acupuncture and explore the mechanism involved. A randomized controlled trial was performed among 10 normal controls and 38 migraineurs. The migraineurs were divided into blank control, sham acupuncture, and acupuncture groups. Patients were subjected to two courses of treatment, and each treatment lasted for 5 days, with an interval of 1 day between the two courses. The effectiveness of treatment was evaluated using pain questionnaire. The functional magnetic resonance imaging (fMRI) data were analyzed for investigating brain changes induced by treatments. Blood plasma was collected for metabolomics and proteomics studies. Correlation and mediation analyses were performed to investigate the interaction between clinical, fMRI and omics changes. Results showed that acupuncture effectively relieved migraine symptoms in a way different from sham acupuncture in terms of curative effect, affected brain regions, and signaling pathways. The anti-migraine mechanism involves a complex network related to the regulation of the response to hypoxic stress, reversal of brain energy imbalance, and regulation of inflammation. The brain regions of migraineurs affected by acupuncture include the lingual gyrus, default mode network, and cerebellum. The effect of acupuncture on patients' metabolites/proteins may precede that of the brain.
Humans ; Migraine Disorders/etiology* ; Brain/diagnostic imaging* ; Acupuncture Therapy/methods* ; Magnetic Resonance Imaging

Objective:To investigate the application value of domestic robotic surgical system in radical resection of hilar cholangiocarcinoma (hCCA).Methods:The retrospective and descriptive study was constructed. The clinicopathological data of a 66-year-old male patient with hCCA who was admitted to the Second Hospital of Shandong University in November 2022 were collected. Radical resection of hCCA was performed using the Toumai? laparoscopic surgical robot system. Observation indicators: (1) intraoperative conditions; (2) postoperative conditions; (3) follow-up. Count data were represented as absolute numbers and (or) percentages.Results:(1) Intraoperative conditions. The patient underwent radical resection of hCCA successfully using robotic surgical system, including tumor resection, lymph node dissection, and gastrointestinal reconstruc-tion. The operation time and volume of intraoperative blood loss were 400 minutes and 100 mL, respectively, and no intraoperative blood transfusion was required. (2) Postoperative conditions. The patient began ambulation on postoperative day 1 and began taking liquid food on postoperative day 4. Liver function examination and abdominal computed tomograph (CT) on postoperative day 5 showed a decrease in serum bilirubin, no biliary or intestinal leakage, and no edema or necrosis at the anastomotic site. The abdominal pre-anastomotic and post-anastomotic drainage tubes were removed on the 7th and 9th day after the surgery respectively, and the patient was discharged on the 10th day after surgery. Results of postoperative pathological examination showed moderately to poorly differentiated adenocarcinoma of the bile duct. Immunostaining was positive for CK7 and CK19. The Ki-67 proliferation index was 35%. The proximal and distal resection margin of bile duct were negative. The tumor diameter was 30 mm. Perineural invasion was positive. The surgical specimen margin was negative. Two lymph nodes were identified containing tumor cells positive for malignancy. No tumor cell metastasis was detected in the No.8, No.12 or gastric lesser curvature lymph nodes submitted for pathological examination. (3) Follow-up. The patient was followed up at postoperative 1-, 3-, 5-month after discharge. During follow-up period, results of liver function examination and abdominal CT showed liver function restore to normal levels, no complication such as biliary fistula, intestinal fistula, gastroparesis or tumor metastasis.Conclusion:The Domestic Toumai ? laparoscopic surgical robot system can be applied to radical resection of hCCA.