Background: At present, the most commonly used diagnostic method of carpal tunnel syndrome (CTS) is based on clinical manifestations and electrophysiology, but the electrophysiology is not cheap, invasive, and lacks the presentation of peripheral nerve conditions, which is exactly the advantage of ultrasound (US).The purpose of this study was to evaluate the accuracy and effectiveness of US in the diagnosis of CTS by calculating the cross-sectional area (CSA) at the carpal tunnel and proximally at the level of the pronator quadratus muscle., and to find an appropriate index that can be used to achieve the diagnosis in a more costeffective manner.Methods: Forty-three wrists from 35 symptomatic CTS patients and 23 wrists from 18 asymptomatic volunteers were evaluated. Diagnosis in the CTS group was based on the American Academy of Neurology clinical diagnostic criteria. The ultrasonic probe was placed at the carpal tunnel and the distal 1/3 of the pronator muscle respectively, and the carpal tunnel cross-sectional area (CSAC) and the proximal crosssectional area (CSAP) was calculated, with a further calculation of their difference (ΔCSA) and ratio (R-CSA).Results: There was a significant difference between the 2 groups regarding mean ± standard deviation (SD) of CSAC, CSAP, ΔCSA, and R-CSA (P<0.01). The cutoff value of 12.14 mm 2 for CSAC had a sensitivity and specificity of 90.7% and 100%, respectively; the cutoff value of 1.235 mm 2 for R-CSA had a sensitivity and specificity of 97.67% and 95.65%, respectively; and the cutoff value of 2.035 mm 2 for ΔCSA had a sensitivity and specificity of 100% and 100%, respectively. Therefore, US was found to be an effective method for the diagnosis of CTS. Receiver operating characteristic curve (ROC) analysis of all patients showed area under the curve (AUC) was 0.9778 for CSAC, 0.9949 for R-CSA and 1.000 for ΔCSA.Conclusions: US can provide reference values for the diagnosis of CTS. CSAC, ΔCSA, and R-CSA can be used for CTS diagnosis and evaluation. The ROC curve analysis showed that among the 3 values, ΔCSA was the most useful in the diagnosis of patients with CTS. ΔCSA is considered a valid diagnostic value for CTS, as its threshold of 2.04 mm 2 showed the highest sensitivity and specificity.

Ovarian serous cystadenocarcinoma (OV) is a fatal gynecologic cancer with a five-year survival rate of only 46%. Resistance to platinum-based chemotherapy is a prevalent factor in OV patients, leading to increased mortality. The platinum resistance in OV is driven by transcriptome heterogeneity and tumor heterogeneity. Studies have indicated that ovarian cancer stem cells (OCSCs), which are chemoresistant and help in disease recurrence, are enriched by platinum-based chemotherapy. Stem cells have a significant influence on the OV progression and prognosis of OV patients and are key pathology mediators of OV. However, the molecular mechanisms and targets of OV have not yet been fully understood. In this study, systematic research based on the TCGA-OV dataset was conducted for the identification and construction of key stem cell-related diagnostic and prognostic models for the development of multigene markers of OV. A six-gene diagnostic and prognostic model (C19orf33, CBX2, CSMD1, INSRR, PRLR, and SLC38A4) was developed based on the differentially expressed stem cell-related gene model, which can act as a potent diagnostic biomarker and can characterize the clinicopathological properties of OV. The key genes related to stem cells were identified by screening the genes differentially expressed in OV and control samples. The mRNA-miRNA-TF molecular network for the six-gene model was constructed, and the potential biological significance of this molecular model and its impact on the infiltration of immune cells in the OV tumor microenvironment were elucidated. The differences in immune infiltration and stem cell-related biological processes were determined using gene set variation analysis (GSVA) and single-sample gene set enrichment analysis (ssGSEA) for the selection of molecular treatment options and providing a reference for elucidating the posttranscriptional regulatory mechanisms in OV.