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 analyze the nonlinear relationship between hypothermic machine perfusion (HMP) parameters and delayed graft function (DGF) and optimize the construction of a predictive model for DGF. Methods The data of 923 recipients who underwent kidney transplantation from deceased donors were retrospectively analyzed. According to the occurrence of DGF, the recipients were divided into DGF group (n=823) and non-DGF group (n=100). Donor data, HMP parameters and recipient data were analyzed for both groups. The nonlinear relationship between HMP parameters and the occurrence of DGF was explored based on restricted cubic splines (RCS). Over-sampling, under-sampling and balanced sampling were used to address the imbalance in the proportion of DGF to construct logistic regression predictive models. The area under the curve (AUC) of each model was compared in the validation set, and a nomogram model was constructed. Results Donor BMI, cold ischemia time of the donor kidney, and HMP parameters (initial and final pressures, resistance, and perfusion time) were significantly different between the DGF and non-DGF groups (all P<0.05). The RCS analysis revealed a threshold-like nonlinear relationship between HMP parameters and the risk of DGF. Among the models constructed using different sampling methods, the balanced sampling model had the highest AUC. Using this model, a nomogram was constructed to stratify recipients based on risk scores. Recipients in the high-risk group had higher serum creatinine levels at 1, 6, and 12 months after kidney transplantation compared to those in the low-risk group (all P<0.05). Conclusions There is a nonlinear relationship between HMP parameters and the risk of DGF, and the threshold is helpful for organ quality assessment and monitoring of graft function after transplantation. The predictive model for DGF constructed on the base of balanced sampling algorithms helps perioperative decision-making and postoperative graft function monitoring of kidney transplantation.

OBJECTIVE: To summarize the latest research progress of graphene and its derivatives (GDs) in bone repair. METHODS: The relevant research literature at home and abroad in recent years was extensively accessed. The properties of GDs in bone repair materials, including mechanical properties, electrical conductivity, and antibacterial properties, were systematically summarized, and the unique advantages of GDs in material preparation, functionalization, and application, as well as the contributions and challenges to bone tissue engineering, were discussed. RESULTS: The application of GDs in bone repair materials has broad prospects, and the functionalization and modification technology effectively improve the osteogenic activity and material properties of GDs. GDs can induce osteogenic differentiation of stem cells through specific signaling pathways and promote osteogenic activity through immunomodulatory mechanisms. In addition, the parameters of GDs have significant effects on the cytotoxicity and degradation behavior. CONCLUSION GDs has great potential in the field of bone repair because of its excellent physical and chemical properties and biological properties. However, the cytotoxicity, biodegradability, and functionalization strategies of GDs still need to be further studied in order to achieve a wider application in the field of bone tissue engineering.
Graphite/pharmacology* ; Tissue Engineering/methods* ; Humans ; Osteogenesis/drug effects* ; Biocompatible Materials/pharmacology* ; Bone Regeneration ; Tissue Scaffolds/chemistry* ; Cell Differentiation ; Bone and Bones ; Bone Substitutes/chemistry* ; Animals

OBJECTIVES: To investigate the prognostic significance of PDZ-binding kinase (PBK) in pan-cancer and its potential as a therapeutic target for pancreatic cancer. METHODS: PBK expression levels were investigated in 33 cancer types based on data from TCGA, GEO and CPTAC databases. RT-PCR and Western blotting were employed to examine PBK expression in clinical pancreatic cancer specimens and cell lines. The diagnostic and prognostic value of PBK in pancreatic cancer was evaluated using survival analysis, Cox regression analysis, ROC curve analysis, and clinical correlation studies. Gene enrichment and immune correlation analyses were conducted to explore the potential role of PBK in tumor microenvironment, and its correlation with drug sensitivity was investigated using GDSC and CTRP datasets. In pancreatic cancer BXPC-3 cells, the effects of lentivirus-mediated PBK knockdown on cell proliferation, migration, and invasion were examined using CCK-8, colony formation, and Transwell assays. The interaction between PBK and non-SMC condensin II complex subunit G2 (NCAPG2) was analyzed using co-immunoprecipitation and Western blotting. RESULTS: PBK was overexpressed in multiple cancer types, including pancreatic cancer. A high PBK expression was associated with a poor prognosis of the patients and correlated with immune infiltration and alterations in the tumor microenvironment. Elevated PBK expression was positively correlated with the sensitivity to MEK inhibitors (Trametinib) and EGFR inhibitors (Afatinib) but negatively with the sensitivity to Bcl-2 inhibitors (TW37) and niclosamide. In BXPC-3 cells, PBK knockdown significantly suppressed NCAPG2 expression and inhibited cell proliferation, migration, and invasion. Co-immunoprecipitation confirmed a direct binding between PBK and NCAPG2. CONCLUSIONS PBK is a key regulator of pancreatic cancer and interacts with NCAPG2 to promote tumor progression, suggesting its value as a potential biomarker and therapeutic target for pancreatic cancer.
Humans ; Pancreatic Neoplasms/genetics* ; Prognosis ; Biomarkers, Tumor/genetics* ; Cell Line, Tumor ; Cell Proliferation ; Adenocarcinoma/metabolism* ; Tumor Microenvironment ; Cell Movement ; Mitogen-Activated Protein Kinase Kinases

Objective To explore the molecular mechanisms and cell-cell interactions in the injury process of pancreatic islet transplantation.Methods Single-cell transcriptome data from mouse islets treated with inflammatory factors were used,and data processing was performed using the Seurat package,with integrated data to remove batch effects.Cell subpopulations were annotated based on known markers.Cell-cell interactions in the inflammatory factor-treated group were analyzed using the CellChat package,and inferred based on the expression of cell surface receptors and ligands.Gene set enrichment analysis was used to clarify the biological processes enriched in β-cells after treatment with inflammatory factors.Finally,differentially expressed transcription factors were identified and verified using microarray datasets of donor islet ischemic injury and Western blotting.Results A total of 7 different cell subpopulations were found in mouse islets,with β-cells being the most abundant.Cell-cell interaction network analysis showed that the number and strength of interactions between ductal cells and other cells were the highest.Gene set enrichment analysis showed that after treatment with inflammatory factors,the immune response was positively enriched in β-cells,while peptide hormone metabolism,bile acid metabolism,and ion homeostasis were downregulated.The common differential transcription factors identified in the mouse single-cell transcriptome and the microarray dataset of donor islet ischemic injury were early growth response 1(EGR1),nuclear factor-κB inhibitor α(NFKBIA),and activating transcription factor 3(ATF3).Among them,NFKBIA and ATF3 were upregulated,while EGR1 was downregulated.The expression of EGR1 protein was downregulated after 24 h,48 h,and 72 h of cold ischemia.Conclusions EGR1 is a transcription factor closely related to islet cold ischemia,and future research should focus on the specific mechanisms of EGR1 and its downstream target genes,in order to provide more effective strategies for clinical treatment of islet transplantation.

Objective To investigate the efficacy of red and blue lights combined with Yufa Shengfa solution and 5% minoxidil solution in treating Ludwig type Ⅰ female androgenetic alopecia. Methods A total of 160 patients with Ludwig type Ⅰ female androgenetic alopecia were randomly divided into group A (Yufa Shengfa solution combined with 5% minoxidil solution), group B (red and blue lights therapy combined with Yufa Shengfa solution), group C (red and blue lights therapy combined with 5% minoxidil solution) and group D (red and blue lights therapy combined with Yufa Shengfa solution and 5% minoxidil solution), with 40 cases in each group. All the patients orally took compound glycyrrhizin tablets and Centrum multivitamins, and the therapeutic period was 3 months. Differences in hair diameter, hair density, and the number of hair follicles with multiple hairs were compared before and after treatment. Results The hair density, hair diameter, and the number of hair follicles with multiple hairs improved significantly in 4 groups compared with those before treatment, and group D showed the best improvement in these parameters, with significant between-group differences (P < 0.001). There were no serious adverse events or side effects during treatment in all the patients. Conclusion Red and blue lights therapy combined with Yufa Shengfa solution and 5% minoxidil solution is an effective non-surgical treatment for Ludwig type Ⅰ female androgenetic alopecia.

OBJECTIVE To test and compare the median effective dose(ED50) of ciprofol for gastroscope in patients of different genders and ages. METHODS Patients who planed to undergo gastroscope examination and treatment from March 2023 to April 2023 were selected, and divided into four groups according to stratified random method: N1 group(non-elderly male patients), N2 group(non-elderly female patients), N3 group(elderly male patients), and N4 group(elderly female patients). All patients received intravenous injection of 0.1 μg·kg−1 sufentanil followed by injection of the test dose of ciprofol according to Dixon’s modified sequential method. Gastroscope was performed after the disappearance of the eyelash reflex. The initial dose of ciprofol in all four groups was 0.4 mg·kg−1, and the ratio of adjacent doses was 1∶1.1. The next patient would receive a 10% increase in the dose of ciprofol if the patient experienced positive reactions such as coughing, frowning, and body movements during the endoscopy process. Otherwise, it would be judged as a negative reaction, and the next patient would receive a 10% decrease in the dose of ciprofol. The transition from a positive reaction to a negative reaction was defined as a turning point, and the study was terminated when seven turning points occurred. Hemodynamic parameters, oxygen saturation and adverse reactions were recorded at different time points. The Probit regression analysis method was used to calculate the ED50 of ciprofol for four groups. RESULTS The ED50 of ciprofol combined with 0.1 μg·kg−1 sufentanil for gastroscope in the non-elderly men, non-elderly women, elderly men, and elderly women were 0.409, 0.373, 0.356, 0.327 mg·kg−1, respectively. The ED50 of ciprofol in the N1 group was significantly higher compared with the N2 group and N3 group(P<0.05). The ED50 of ciprofol in the N4 group was significantly lower compared with the N2 group and N3 group(P<0.05). CONCLUSION The ED50 of ciprofol is significantly different among gastroscope patients of different genders and ages, which is lower in female patients than in male patients, and is lower in older patients than in non-elderly patients.

Objective:To explore the effect of family empowerment model on the improvement of swallowing care ability and care preparedness of primary caregivers of first-episode stroke dysphagia patients, further to explore its impact on patients′s wallowing function and life quality.Methods:This study was a randomized controlled study. From January 2021 to December 2022, 80 main caregivers of patients with dysphagia caused by manual stroke admitted to the Department of Acupuncture and Moxibustion, Shenzhen Hospital of Traditional Chinese Medicine were selected as the research objects, and 40 cases in the control group and 40 cases in the observation group were selected by random number table method. The control group were treated with conventional nursing care of first-episode stroke dysphagia patients in the acupuncture and moxibustion Department. On the basis of the conventional care in the control group, the observation group were treated with family empowerment model intervention for 14 days and was followed up for 28 days. Primary caregivers′ swallowing care ability, Caregiver Preparedness Scale (CPS), patients′ swallowing function rate, Swallowing Related Quality of Life (SWALQOL) were used to evaluate the effects before intervention and at the end of intervention.Results:There were 18 males and 19 females primary caregivers in the control group, aged (55.61 ± 7.43) years old. There were 18 males and 21 females primary caregivers in the observation group, aged (58.23 ± 8.22) years old. The swallowing care ability score showed a statistically significant difference between the observation group (143.47 ± 3.96) and the control group (107.74 ± 1.43) ( t=-26.76, P<0.05). After intervention, the caregiver preparedness scale was (26.11 ± 3.81) in the observation group, and (18.35 ± 4.54) in the control group, and the difference was statistically significant ( t=-4.11, P<0.05).The patients′ swallowing function rate and SWALQOL score were respectively 97.44% (38/39) and (91.41 ± 8.08) points in the observation group, and 72.97% (27/37) and (80.33 ± 4.21) points in the control group, and the difference was both statistically significant ( χ2=10.76, t=-2.54, both P<0.05). Conclusions:The implementation of family empowerment model could enhance the swallowing care ability and care preparedness of primary caregivers of the first-episode stroke dysphagia patients, which could further improve patients′ swallowing function and life quality.