Objectives: Hypoparathyroidism (HP) is a rare endocrine disorder caused by parathyroid hormone (PTH) defi ciency. The PTH is a candidate gene for familial isolated hypoparathyroidism (FIH). This study aimed to investigate the pathogenicity of two novel rare variants (RVs) ofPTH through in vitro functional study. Methods: Targeted next-generation sequencing was used to identify candidate gene mutations. Clinical data were retrospectively collected. Wild-type (WT) PTH was used as a template for site-directed mutagenesis to create mutant eukaryotic expression plasmids, which were transfected into cells. Treated with or without 4-phenylbu tyric acid (4-PBA), the levels of intact PTH (iPTH) and PTH (1-84) were measured by chemiluminescence, and protein expression was assessed using Western blotting. Results: Two patients carrying PTH mutations (c.154G > A: p.Val52Ile, c.270G > T: p.Leu90Phe) were identified.Patient 1, a 45-year-old male, presented with carpal and pedal numbness, muscle cramps, and low serum calcium (1.29 mmol/L). Patient 2, a 12-year-old female, had muscle twitches, convulsions, low calcium (1.50 mmol/L), and iPTH of 4 pg/mL. The iPTH or PTH (1-84) levels in the medium transfected with mutant Val52Ile and Leu90Phe PTH decreased by 31%–38%, and 51%–96% compared to WT (allP < 0.05), which were not rescued by 4-PBA. No significant changes in intracellular PTH expression were observed. Conclusions In this study, two novel RVs of PTH(Val52Ile and Leu90Phe) were identified that may impair hormone synthesis and secretion. Our study has broadened the mutation spectrum of the PTH and shed light on potential mechanisms underlying FIH.

Objectives: Hypoparathyroidism (HP) is a rare endocrine disorder caused by parathyroid hormone (PTH) defi ciency. The PTH is a candidate gene for familial isolated hypoparathyroidism (FIH). This study aimed to investigate the pathogenicity of two novel rare variants (RVs) ofPTH through in vitro functional study. Methods: Targeted next-generation sequencing was used to identify candidate gene mutations. Clinical data were retrospectively collected. Wild-type (WT) PTH was used as a template for site-directed mutagenesis to create mutant eukaryotic expression plasmids, which were transfected into cells. Treated with or without 4-phenylbu tyric acid (4-PBA), the levels of intact PTH (iPTH) and PTH (1-84) were measured by chemiluminescence, and protein expression was assessed using Western blotting. Results: Two patients carrying PTH mutations (c.154G > A: p.Val52Ile, c.270G > T: p.Leu90Phe) were identified.Patient 1, a 45-year-old male, presented with carpal and pedal numbness, muscle cramps, and low serum calcium (1.29 mmol/L). Patient 2, a 12-year-old female, had muscle twitches, convulsions, low calcium (1.50 mmol/L), and iPTH of 4 pg/mL. The iPTH or PTH (1-84) levels in the medium transfected with mutant Val52Ile and Leu90Phe PTH decreased by 31%–38%, and 51%–96% compared to WT (allP < 0.05), which were not rescued by 4-PBA. No significant changes in intracellular PTH expression were observed. Conclusions In this study, two novel RVs of PTH(Val52Ile and Leu90Phe) were identified that may impair hormone synthesis and secretion. Our study has broadened the mutation spectrum of the PTH and shed light on potential mechanisms underlying FIH.

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/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Objectives: Hypoparathyroidism (HP) is a rare endocrine disorder caused by parathyroid hormone (PTH) defi ciency. The PTH is a candidate gene for familial isolated hypoparathyroidism (FIH). This study aimed to investigate the pathogenicity of two novel rare variants (RVs) ofPTH through in vitro functional study. Methods: Targeted next-generation sequencing was used to identify candidate gene mutations. Clinical data were retrospectively collected. Wild-type (WT) PTH was used as a template for site-directed mutagenesis to create mutant eukaryotic expression plasmids, which were transfected into cells. Treated with or without 4-phenylbu tyric acid (4-PBA), the levels of intact PTH (iPTH) and PTH (1-84) were measured by chemiluminescence, and protein expression was assessed using Western blotting. Results: Two patients carrying PTH mutations (c.154G > A: p.Val52Ile, c.270G > T: p.Leu90Phe) were identified.Patient 1, a 45-year-old male, presented with carpal and pedal numbness, muscle cramps, and low serum calcium (1.29 mmol/L). Patient 2, a 12-year-old female, had muscle twitches, convulsions, low calcium (1.50 mmol/L), and iPTH of 4 pg/mL. The iPTH or PTH (1-84) levels in the medium transfected with mutant Val52Ile and Leu90Phe PTH decreased by 31%–38%, and 51%–96% compared to WT (allP < 0.05), which were not rescued by 4-PBA. No significant changes in intracellular PTH expression were observed. Conclusions In this study, two novel RVs of PTH(Val52Ile and Leu90Phe) were identified that may impair hormone synthesis and secretion. Our study has broadened the mutation spectrum of the PTH and shed light on potential mechanisms underlying FIH.

ObjectiveTo investigate the contamination status, transmission risk and drug resistance of Klebsiella pneumoniae (KP) on the object surfaces in the surrounding environment of hospitalized patients infected with carbapenem-resistant Klebsiella pneumoniae (CRKP) , so as to provide a scientific guidance for the prevention and control of healthcare-associated infection. MethodsSamples from the surfaces of objects in the surrounding environment of CRKP infected patients living in the intensive care unit (ICU) and hand specimens from healthcare workers were collected for KP isolation and identification, as well as drug susceptible test in a medical institution located in Minhang District, Shanghai from 2021 to 2023. Additionally, both univariate and multivariate logistic regression analyses were used to identify the influencing factors associated with KP contamination in the hospital environment. ResultsA total of 546 surface samples were collected from the surrounding environment objects of 15 patients infected with CRKP, with a KP detection rate of 6.59% (36/546).The KP detection rate in the ICU of general ward (10.22%) was higher than that in the ICU of emergency department (2.94%) (χ²=12.142, P<0.001). Moreover, the KP detection rate on the surfaces of patient-contacted items (15.66%) was higher than that on shared-use items (6.25%), cleaning items (10.00%), and medical supplies (3.30%) (χ²=17.943, P<0.001). Besides, the detection rate of KP in items sent out of hospital for disinfection (15.38%) was higher than that in those self-disinfected (4.20%) (χ²=19.996, P<0.001).The highest detection rate of KP was observed in high-temperature washing (15.13%, 18/119) (χ²=21.219, P<0.001), while the lowest detection rate was observed in antibacterial hand sanitizer with trichlorohydroxydiphenyl ether sanitizing factor (0, 0/60) ( χ²=21.219, P<0.001).The detection rate of KP in samples taken more than 24 hours after the last disinfection (23.08%) was higher than that in those taken at 4 to24 hours (12.90%) and less than 4 hours (4.22%) (χ²=23.398,P<0.001).ICU of general ward (OR=4.045, 95%CI: 2.206‒7.416), patient-contacted items (OR=3.113, 95%CI: 1.191‒8.141), and self-disinfection ( OR=0.241, 95%CI:0.144‒0.402) were influencing factors for KP contamination in environmental surface. From 2021 to 2023, the drug resistance rates of hospital environmental KP isolates showed an upward trend (P<0.001) to antibiotics such as ceftazidime and gentamicin. Furthermore, high drug resistance rates of KP (>90%) were observed to ciprofloxacin, levofloxacin, cefotaxime, ceftriaxone, and cefepime. ConclusionCRKP can be transmitted outward through the surfaces of objects in the patients’ surroundings, and the drug resistance situation is severe. In clinical settings, it is necessary to implement isolation measures for CRKP infection patients, to increase the frequency of disinfection for objects in their surroundings, to strengthen hand hygiene practices, and to use antibiotics appropriately.

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/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.