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 explore the mechanism for the occurrence and phenotypic characteristics of Turner syndrome based on a prenatally diagnosed case of a mosaic karyotype containing double pseudo-isodicentric X chromosome and a review of relevant literature.Methods:A fetus who was diagnosed with increased risk of trisomy 21 at the Provincial Hospital Affiliated to Shandong First Medical University in August 2023 was selected as the study subject. Clinical data of the fetus was collected. Following amniocentesis, chromosomal G-banding karyotype analysis and chromosomal microarray analysis (CMA) were carried out. This study has been approved by the Ethics Committee of the Hospital (Ethics No.: SWYX No. 2022-287).Results:The early-trimester screening suggested a high risk of trisomy 21(1/19), with free β-hCG of 116 ng/mL (MoM value 2.35), PAPP-A of 0.394 ng/mL (MoM value 0.12), and NT value of 1.3 mm, though no abnormality was found in the fetus at 19 weeks gestation. The karyotype of amniocyte was determined as 46, X, psu idic(X)(p11.21)[55]/45, X[27]/47, X, psu idic(X)(p11.21)×2[5]/46, XX[13]. CMA has yielded a result of arr[GRCh37] Xp22.33p11.21(168552_55585678)×1[0.67], Xp11.21q28(55703291_155233098)×3[0.5].Conclusion:Karyotypes of Turner syndrome are complex and diverse, and a rare 46, X, psu idic(X)(p11.21)[55]/45, X[27]/47, X, psu idic(X)(p11.21)×2[5]/46, XX[13] mosaic karyotype with double pseudo-isodicentric X chromosome has been identified. Literature review suggested that this karyotype may lead to phenotypic diversification and a risk of reduced sensitivity to hormone therapy.

The applications of nuclear technology in industries, medicine, and other fields have increased the risk of radiation injury. Although some small-molecule drugs for radiation injury treatment have been applied clinically or are in preclinical research, their therapeutic efficacy is significantly limited by short circulation time and rapid metabolism. Nanomaterials have attracted growing attention with their outstanding bioactivity, chemical stability, tissue compatibility, and targeted delivery capabilities, therefore having the promise of offering the potential solutions to the limitations of current small-molecule drugs. However, their biosafety and clinical efficacy require further investigation. This review summarizes the design strategies and classifications of nanomaterials for radiation injury treatment, analyzes current research progress in their therapeutic applications, and introduces nanomaterial-based approaches for enhancing the elimination of internal radionuclide contamination. Finally, the challenges and future prospects of nanomaterials in radiation injury treatment are discussed. This review aims to provide researchers with a comprehensive understanding of recent advances in nanomaterial-based radiation injury therapeutics, thereby promoting further development in this field.

OBJECTIVE: To explore the mechanism for the occurrence and phenotypic characteristics of Turner syndrome based on a prenatally diagnosed case of a mosaic karyotype containing double pseudo-isodicentric X chromosome and a review of relevant literature. METHODS: A fetus diagnosed with increased risk for trisomy 21 at the Provincial Hospital Affiliated to Shandong First Medical University in August 2023 was selected as the study subject. Clinical data of the fetus was collected. Following amniocentesis, chromosomal G-banding karyotype analysis and chromosomal microarray analysis (CMA) were carried out. This study has been approved by the Ethics Committee of the Hospital (Ethics No.: SWYX No. 2022-287). RESULTS: The early-trimester screening suggested a high risk of trisomy 21 (1/19), with free β-hCG of 116 ng/mL (MoM value 2.35), PAPP-A of 0.394 ng/mL (MoM value 0.12), and NT value of 1.3 mm, though no abnormality was found in the fetus at 19 weeks gestation. The karyotype of amniocyte was determined as 46,X,psu idic(X)(p11.21)[55]/45,X[27]/47,X,psu idic(X)(p11.21)×2[5]/46,XX[13]. CMA has yielded a result of arr[GRCh37] Xp22.33p11.21(168552_55585678)×1[0.67],Xp11.21q28(55703291_155233098)×3[0.5]. CONCLUSION Karyotypes of Turner syndrome are complex and diverse, and a rare 46,X,psu idic(X)(p11.21)[55]/45,X[27]/47,X,psu idic(X)(p11.21)×2[5]/46,XX[13] mosaic karyotype with double pseudo-isodicentric X chromosome has been identified. Literature review suggested that this karyotype may lead to phenotypic diversification and a risk of reduced sensitivity to hormone therapy.
Humans ; Turner Syndrome/diagnosis* ; Female ; Pregnancy ; Chromosomes, Human, X/genetics* ; Mosaicism ; Prenatal Diagnosis ; Karyotyping ; Adult ; Karyotype ; Amniocentesis

ObjectiveTo investigate the value of Fried Frailty Phenotype （FFP）， liver frailty index （LFI）， and Short Physical Performance Battery （SPPB） in predicting 2-year all-cause mortality and decompensation events in patients with liver cirrhosis. MethodsA total of 277 patients with liver cirrhosis who were hospitalized in Beijing Friendship Hospital， Capital Medical University， from December 2020 to December 2021 were enrolled， and FFP， LFI， and SPPB were used to assess the state of frailty. Based on the scores of each tool， these patients were divided into frail and non-frail groups. These three tools were compared in terms of consistency and independent predictive performance. The primary endpoints were 2-year all-cause mortality rate and composite endpoints （death+decompensation events）， and the Cox regression analysis， the receiver operating characteristic （ROC） curve， net reclassification index （NRI）， and integrated discrimination improvement （IDI） index were used to analyze the predictive value of the three tools. Normally distributed continuous data were compared between two groups using the independent samples t-test， while non-normally distributed continuous data were compared using the Mann-Whitney U test. Categorical data were compared between groups using the chi-square test or Fisher’s exact test. The agreement among different frailty tools was evaluated using Cohen’s Kappa statistic. The Kaplan-Meier survival curve was plotted， and a survival analysis was performed using the log-rank test. ResultsThe prevalence rate of frailty assessed by FFP， LFI， and SPPB was 37.2%， 22.4%， and 20.2%， respectively， with a moderate consistency between FFP and LFI/SPPB （κ=0.57， 95% confidence interval ［CI］： 0.47 — 0.67； κ=0.51， 95%CI： 0.41 — 0.62） and a relatively high consistency between LFI and SPPB （κ=0.87， 95%CI： 0.80 — 0.94）. Compared with the non-frailty group， the frailty group had significantly higher all-cause mortality rate and incidence rate of composite endpoints （P0.001）. After multivariate adjustment， FFP， LFI， and SPPB had a hazard ratio of 2.42（95%CI： 1.51 — 5.11）， 2.21（95%CI： 1.11 — 4.42）， and 2.21（95%CI： 1.14 — 4.30）， respectively， in predicting all-cause mortality， as well as a hazard ratio of 2.51（95%CI： 1.61 — 3.91）， 2.40（95%CI： 1.51 — 3.80）， and 2.20（95%CI： 1.39 — 3.47）， respectively， in predicting composite endpoints. Compared with Child-Pugh score， FFP had a significantly greater area under the ROC curve （AUC） in predicting all-cause mortality （0.79 vs 0.69， P=0.032） and composite endpoints （0.75 vs 0.68， P=0.044）. Frailty assessment tools combined with Child-Pugh score significantly improved the performance in predicting all-cause mortality and composite endpoints， with an AUC of 0.81 — 0.82 and 0.77 — 0.78， respectively （P0.05）. NRI and IDI analyses further confirmed the improvement of the combined model in classification （all P0.001）. ConclusionFFP， LFI， and SPPB can independently predict adverse outcomes in patients with liver cirrhosis， among which FFP has the best predictive performance， and the combination of frailty assessment tools with Child-Pugh score can significantly enhance the accuracy of prognostic evaluation.

The applications of nuclear technology in industries, medicine, and other fields have increased the risk of radiation injury. Although some small-molecule drugs for radiation injury treatment have been applied clinically or are in preclinical research, their therapeutic efficacy is significantly limited by short circulation time and rapid metabolism. Nanomaterials have attracted growing attention with their outstanding bioactivity, chemical stability, tissue compatibility, and targeted delivery capabilities, therefore having the promise of offering the potential solutions to the limitations of current small-molecule drugs. However, their biosafety and clinical efficacy require further investigation. This review summarizes the design strategies and classifications of nanomaterials for radiation injury treatment, analyzes current research progress in their therapeutic applications, and introduces nanomaterial-based approaches for enhancing the elimination of internal radionuclide contamination. Finally, the challenges and future prospects of nanomaterials in radiation injury treatment are discussed. This review aims to provide researchers with a comprehensive understanding of recent advances in nanomaterial-based radiation injury therapeutics, thereby promoting further development in this field.

Objective:To explore the mechanism for the occurrence and phenotypic characteristics of Turner syndrome based on a prenatally diagnosed case of a mosaic karyotype containing double pseudo-isodicentric X chromosome and a review of relevant literature.Methods:A fetus who was diagnosed with increased risk of trisomy 21 at the Provincial Hospital Affiliated to Shandong First Medical University in August 2023 was selected as the study subject. Clinical data of the fetus was collected. Following amniocentesis, chromosomal G-banding karyotype analysis and chromosomal microarray analysis (CMA) were carried out. This study has been approved by the Ethics Committee of the Hospital (Ethics No.: SWYX No. 2022-287).Results:The early-trimester screening suggested a high risk of trisomy 21(1/19), with free β-hCG of 116 ng/mL (MoM value 2.35), PAPP-A of 0.394 ng/mL (MoM value 0.12), and NT value of 1.3 mm, though no abnormality was found in the fetus at 19 weeks gestation. The karyotype of amniocyte was determined as 46, X, psu idic(X)(p11.21)[55]/45, X[27]/47, X, psu idic(X)(p11.21)×2[5]/46, XX[13]. CMA has yielded a result of arr[GRCh37] Xp22.33p11.21(168552_55585678)×1[0.67], Xp11.21q28(55703291_155233098)×3[0.5].Conclusion:Karyotypes of Turner syndrome are complex and diverse, and a rare 46, X, psu idic(X)(p11.21)[55]/45, X[27]/47, X, psu idic(X)(p11.21)×2[5]/46, XX[13] mosaic karyotype with double pseudo-isodicentric X chromosome has been identified. Literature review suggested that this karyotype may lead to phenotypic diversification and a risk of reduced sensitivity to hormone therapy.

Objective:To explore the effect of NOD-like receptor thermal protein 3 ( NLRP3) knockout in γ-aminobutyric acid (GABA)-ergic neurons in the hippocampal CA1 area on improving cognitive dysfunction in mice after traumatic brain injury (TBI). Methods:Forty-eight healthy male NLRP3 flox/flox mice weighing 25-28 g were randomly divided into 4 groups ( n=12): sham-operated+control virus group (SV group), sham-operated+ NLRP3 specific knockout group (SG group), TBI+control virus group (TV group), TBI+ NLRP3 specific knockout group (TG group). TBI in the TV and TG groups was established by free-fall method, while surgical procedures such as scalp incision and cranial window opening without impact were given to the SV and SG groups. Adenovirus was injected into the hippocampal CA1 area of SG and TG groups 21 d before TBI to induce NLRP3 specific knockout in GABA-ergic neurons in the hippocampal CA1 area; empty virus was injected into the CA1 area of SV and TV groups. Cognitive function was evaluated using novel object recognition test 30 and 31 d after TBI, and learning and memory functions were assessed using Morris water maze test 32-36 d after TBI. Field potentials in the hippocampal CA1 area were recorded during novel object recognition 31 d after TBI. After behavioral tests, these mice were sacrificed. Immunofluorescent staining was used to detect the fluorescent intensity of microtubule-associated protein2 (MAP2), glutamic acid decarboxylase 67 (GAD67), and postsynaptic density protein 95 (PSD95) in the hippocampal CA1 area, as well as percentage of pyroptosis-associated inflammatory factor interleukin-18 (IL-18)/GAD67 double-positive neurons in total GAD67 positive neurons. Results:Compared with the SV and SG groups, the TV and TG groups had decreased novel object recognition index, decreased number of platform crossings during the experimental period, increased escape latency on day 3 and day 4 of the training period in Morris water maze test, decreased θ and γ oscillation power in the hippocampal CA1 area during novel object recognition, decreased fluorescent intensity of MAP2, GAD67, and PSD95 in the hippocampal CA1 area, increased percentage of IL-18/GAD67 double-positive neurons, with significant differences ( P<0.05). Compared with the TV group, the TG group had increased novel object recognition index, increased number of platform crossings in Morris water maze test, decreased escape latency during the training period, increased θ and γ oscillation power in the hippocampal CA1 area during novel object recognition, increased fluorescence intensity of MAP2, GAD67, and PSD95 in the hippocampal CA1 area, decreased percentage of IL-18/GAD67 double-positive neurons, with significant differences ( P<0.05). Conclusion:Specific inhibition of NLRP3 expression in GABA-ergic neurons in the hippocampal CA1 area can improve cognitive dysfunction in mice after TBI, whose mechanism may be related to inhibited GABA-ergic neuronal pyroptosis in the hippocampal CA1 area.