Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion.

Brain-computer interface (BCI) for motor imagery is an advanced technology used in the field of medical rehabilitation. However, due to the poor accuracy of electroencephalogram feature classification, BCI systems often misrecognize user commands. Although many state-of-the-art feature selection methods aim to enhance classification accuracy, they usually overlook the interrelationships between individual features, indirectly impacting the accuracy of feature classification. To overcome this issue, we propose an adaptive feature learning model that employs a Riemannian geometric approach to generate a feature matrix from electroencephalogram signals, serving as the model's input. By integrating the enhanced adaptive L1 penalty and weighted fusion penalty into the sparse learning model, we select the most informative features from the matrix. Specifically, we measure the importance of features using mutual information and introduce an adaptive weight construction strategy to penalize regression coefficients corresponding to each variable adaptively. Moreover, the weighted fusion penalty balances weight differences among correlated variables, reducing the model's overreliance on specific variables and enhancing accuracy. The performance of the proposed method was validated on BCI Competition IV datasets IIa and IIb using the support vector machine. Experimental results demonstrate the effectiveness and superiority of the proposed model compared to the existing models.

Erratum: CircRNA_100395 inhibits cell proliferation and metastasis in ovarian cancer via regulating miR-1228/p53/epithelial-mesenchymal transition (EMT) axis: Erratum.

[This corrects the article DOI: 10.7150/jca.35041.].

Screening and validation of potential markers associated with uterine corpus endometrial carcinoma and polycystic ovary syndrome based on bioinformatics methods.

Background: Endometrial cancer (UCEC) is a commonly occurring tumor in females, and polycystic ovary syndrome (PCOS) is closely related to UCEC, but the molecular mechanisms remain unclear. This article aims to explore potential molecular mechanisms in UCEC and PCOS, as well as identify prognostic genes for UCEC. Methods: Bioinformatics methods were employed to screen for DEGs in UCEC and PCOS. The shared DEGs were analyzed by constructing a protein-protein interaction (PPI) network using the String database and Cytoscape software. The enrichment analysis was performed using Metascape. The shared DEGs associated with the prognosis of UCEC were identified through univariate and lasso Cox regression methods. A multivariate Cox regression model was constructed and internally validated. The expression and test efficiency of the key prognostic genes were verified using external datasets for UCEC and PCOS. Furthermore, the Gepia database was utilized to analyze the expression of key prognostic genes and their correlation with the disease-free survival (RFS) of UCEC. Tumor mutation burden (TMB), immune infiltration, and the correlation of immune cells were assessed for the prognostic genes of UCEC. Results: There were 151 shared DEGs identified between UCEC and PCOS through bioinformatics screening. These shared DEGs were primarily enriched in leukocyte activation. Following model construction and verification, nine genes were determined to be prognostic for UCEC from the shared DEGs. Among them, TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 were confirmed as prognostic genes in UCEC through external validation. Additionally, RTN1 was identified as a key gene in both UCEC and PCOS. Gepia analysis revealed that higher expression of RTN1 was associated with RFS in UCEC. Immune infiltration analysis of the shared DEGs demonstrated significant differences in the expression of various immune cells between UCEC high and low TMB groups. The seven key prognostic genes in UCEC exhibited regulatory relationships with immune cells. Conclusion: This study identified TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 as the key prognostic DEGs of UCEC. These genes are associated with UCEC survival, TMB, immune cell infiltration, and immune cell regulation. Among them, RTN1 may serve as a potential biomarker for both UCEC and PCOS.

Relationship between Hyponatremia and Peripheral Neuropathy in Patients with Diabetes.

OBJECTIVES: Hyponatremia is a common complication of diabetes. However, the relationship between serum sodium level and diabetic peripheral neuropathy (DPN) is unknown. This study was aimed at investigating the relationship between low serum sodium level and DPN in Chinese patients with type 2 diabetes mellitus. METHODS: A retrospective study was performed on 1928 patients with type 2 diabetes between 2010 and 2018. The multivariate test was used to analyze the relationship between the serum sodium level and the nerve conduction function. A restricted cubic spline was used to flexibly model and visualize the relationship between the serum sodium level and DPN, followed by logistic regression with adjustment. RESULTS: As the serum sodium level increased, the prevalence of DPN had a reverse J-curve distribution with the serum sodium levels (69.6%, 53.7%, 49.6%, 43.9%, and 49.7%; P = 0.001). Significant differences existed between the serum sodium level and the motor nerve conduction velocity, sensory nerve conduction velocity, part of compound muscle action potential, and sensory nerve action potential of the participants. Compared with hyponatremia, the higher serum sodium level was a relative lower risk factor for DPN after adjusting for several potential confounders (OR = 0.430, 95%CI = 0.220-0.841; OR = 0.386, 95%CI = 0.198-0.755; OR = 0.297, 95%CI = 0.152-0.580; OR = 0.376, 95%CI = 0.190-0.743; all P < 0.05). Compared with low-normal serum sodium groups, the high-normal serum sodium level was also a risk factor for DPN (OR = 0.690, 95%CI = 0.526-0.905, P = 0.007). This relationship was particularly apparent in male participants, those aged <65 years, those with a duration of diabetes of <10 years, and those with a urinary albumin - to - creatinine ratio (UACR) < 30 mg/g. CONCLUSIONS: Low serum sodium levels were independently associated with DPN, even within the normal range of the serum sodium. We should pay more attention to avoid the low serum sodium level in patients with type 2 diabetes mellitus.

CircRNA_100395 inhibits cell proliferation and metastasis in ovarian cancer via regulating miR-1228/p53/epithelial-mesenchymal transition (EMT) axis.

Purpose: Circular RNAs (circRNAs) have been reported to regulate the incidence of tumor by regulating the transcriptional level and post-transcriptional level of tumor-related genes, and are significantly correlated with tumor metastasis and progression. CircRNA_100395 (circ_100395) has been reported to suppress lung cancer cell proliferation, and might act as an oncogene in deveopment of various cancers. However, the expression and function of circ_100395 in ovarian cancer has not been systematically researched. Methods: The expression of circ_100395 in ovarian cancer tissues was detected by Real-time Quantitative polymerase chain reaction (RT-qPCR), while the relationship between circ_100395 expression and clinicopathological characteristics was further analyzed. After increasing the expression of circ_100395 by plasmid transfection in ovarian cancer cells, we further investigated the cell proliferation, invasion and migration by cell counting kit-8 (CCK-8), and Transwell assays. Epithelial-mesenchymal transition (EMT) pathway was also measured by western blotting. In addition, the relationship among circ_100395, miR-1228 and p53 in ovarian cancer, was explored by luciferase reporter assay. Results: The expression of circ_100395 was found to be significantly down-regulated in ovarian cancer, while low expression of circ_100395 was highly correlated with the poor outcomes. In addition, upregulation of circ_100395 could significantly inhibit tumor growth, metastasis and EMT signaling pathway in ovarian cancer. Furthermore, the expression level of circ_100395 was negatively correlated with the expression of miR-1228, and with the addition of miR-1228 could reverse anti-cell proliferation effect induced by circ_100395 in ovarian cancer cells. In addition, p53 might be the key target of circ_100395 / miR-1228 axis in ovarian cancer. Conclusion: CircRNA_100395 could inhibit cell growth and metastasis of ovarian cancer cells via regulating the miR-1228/p53/EMT axis.

A preliminary study of uterine scar tissue following cesarean section.

AIM: To compare smooth muscle cells, type I collagen, and apoptosis of the lower uterine segment of women who had/without a prior cesarean delivery. METHODS: Alpha smooth muscle actin (α-SMA), type I collagen, and nuclear apoptosis were compared between the groups from lower uterine segment. Twenty-eight controls and 82 with one prior cesarean delivery were included. The women with a prior cesarean section were classified by time since the surgery: ≤3 years, >3 and ≤5 years, >5 and ≤7 years, >7 and ≤9 years, and >9 years. RESULTS: Smooth muscle volume density (VD) % was significantly lower in women who had cesarean sections in first three groups than in the controls (all, P<0.01). Type I collagen VD% was similar among all groups and the controls. The number of apoptotic nuclei in the lower uterine segment of the scarred group was greater up to 3 years after surgery and less than in the control at 7-9 years. The number of non-apoptotic nuclei in the scarred group was greater than controls up to 7 years after surgery. CONCLUSION: The lower uterine segment scar becomes stable at 3 years after cesarean delivery, and by 9 years, the scar is mature.

Prenatal ultrasonography and Doppler sonography for the clinical investigation of isolated ventricular septal defects in a late second-trimester population.

BACKGROUND: The purpose of this study was to evaluate the efficacy of prenatal ultrasonography and Doppler sonography in detecting isolated ventricular septal defects (VSDs) in a late-second-trimester population. METHODS: Fetal echocardiography, Doppler ultrasound, and biometry were used to evaluate 2,661 singleton fetuses (1,381 male fetuses and 1,280 female fetuses) between 1 August 2006 and 31 May 2010. The efficacy of each fetal biometry, Doppler ultrasound, and nasal bone length (NBL) measurement was evaluated in all of the fetuses. A standard fetal echocardiographic evaluation, including two-dimensional gray-scale imaging and color and Doppler color flow mapping, was performed on all fetuses. RESULTS: We detected isolated VSDs in 124 of the 2,661 singleton fetuses between 19 and 24 weeks of gestation. The prevalence of isolated VSDs in the study population was 4.66%. A multiple logistic regression analysis indicated that short fetal NBL (odds ratio = 0.691, 95% confidence interval: 0.551 to 0.868) and the pulsatility index (PI) of the umbilical artery (odds ratio = 8.095, 95% confidence interval: 4.309 to 15.207) and of the middle cerebral artery (odds ratio = 0.254, 95% confidence interval: 0.120 to 0.538) are significantly associated with isolated VSDs. CONCLUSION: Late-second-trimester fetal NBL, umbilical artery PI, and middle cerebral artery PI are useful parameters for detecting isolated VSDs, and can be used to estimate the a priori risk of VSDs in women at high risk and at low risk of isolated VSDs.