Shanghai Changning Maternity and Infant Health Hospital

The Editors would like to alert the readers that concerns have been raised regarding similarities between different images in this article.Specifically, the 0 h, SPK-1 assay in Figure 2c appears to overlap with the 0 h, SPK Antagonist miR-543 assay in Figure 2 g; the p-JNK and p-Jun panels in the top row of Figure 6 h appear to overlap partially.

To develop and internally validate a nomogram for predicting the likelihood of depression among adult women with urinary incontinence (UI) using data from a nationally representative survey. This study included 6308 women with UI aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. The women were selected at random: 75% were the training set and the remaining 25% comprised the testing set. Least absolute shrinkage and selection operator (LASSO) binomial and logistic regression models were used to select the optimal predictive variables. The depression probability was calculated using a predictor-based nomogram. Receiver operating characteristics area under the curve (ROC-AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram's performance. The nomogram included 11 predictors: age, education, ratio of family income to poverty, smoking, stroke, sleep time, trouble sleeping, leakage bother level, daily activities affected, number of nighttime urinations, and moderate-vigorous recreational activity. A nomogram model for depression risk was established based on these predictors. The AUC of the nomogram was 0.811 (95% confidence interval [CI] 0.793-0.829) in the training set and 0.810 (95% CI 0.780-0.839) in the testing set. The nomogram was well calibrated according to the calibration curve. The DCA demonstrated that the nomogram was clinically useful. This study established a nomogram that is helpful for screening indivudals with UI at high risk of depression and assisting gynecologists in identifying signs of depression in patients and providing treatment.

BACKGROUNDThyroid dysfunction during pregnancy is an important disease affecting the health of mothers and children. Two-dimensional (2D) shear wave elastography (SWE) is the newest ultrasonic elastography technology and its value in differentiating benign and malignant thyroid nodules has been widely recognized. However, the value of 2D SWE in evaluating and predicting thyroid function is unclear.AIMTo explore prospectively the value of 2D SWE quantitative analysis for the evaluation of thyroid function in the first trimester.METHODSWe included outpatients of reproductive age in the Department of Gynecology in Shanghai Changning Maternity and Infant Health Hospital between March 2023 and March 2024 who had conventional ultrasound examination and 2D SWE of the thyroid. They also underwent transvaginal ultrasound examination to confirm early intrauterine pregnancy and serum thyroid stimulating hormone (TSH) level was measured. The patients were divided into pregnant with normal TSH, pregnant with abnormal TSH, and nonpregnant with normal TSH. Conventional ultrasound and 2D SWE results were compared among the three groups.RESULTSA total of 108 patients were included in the study; 57 in the pregnant with normal TSH group, 18 in the pregnant with abnormal TSH group and 33 were in the nonpregnant with normal TSH group. Thyroid size, thyroid echotexture, 2D SWE quantitative parameters including mean elasticity in the region of interest and maximal elasticity in the region of interest showed no significant differences among the three groups (P > 0.05).CONCLUSIONConventional ultrasound and 2D SWE features could not reflect the level of serum TSH.

Mother-infant skin-to-skin contact (SSC) is a key component of Early Essential Newborn Care (EENC), recommended by the World Health Organization to improve neonatal outcomes. Despite its global adoption, SSC implementation in China remains inconsistent, with limited evidence on its impact in Chinese populations. To explore the effects of mother-infant rooming-in and continuous SSC on newborn weight, breastfeeding rates, and the use of medications for jaundice. A total of 2205 women who delivered at Shanghai Changning District Maternal and Child Health Hospital between January and December 2022, including a routine rooming-in care group (1120 cases) and an rooming-in with continuous SSC group (1,085 cases) retrospectively collected from medical records. Both groups of newborns received early essential neonatal care within 90 min of birth, followed by rooming-in with their mothers. Newborns in the routine rooming-in care group received routine rooming-in care, while those in the rooming-in with continuous SSC group were also subjected to continuous SSC with their mothers. The changes in newborn weight, breastfeeding rates, and the use of jaundice medications were compared between the two groups. There was no statistically significant difference in the birth weight between the two groups (P > 0.05). The weight loss after birth, comparing 7% and 9% weight loss, was lower in the rooming-in with continuous SSC group than in the routine rooming-in care group (P < 0.05), with a statistically significant difference. The breastfeeding rate in the rooming-in with continuous SSC group was higher than that in the routine rooming-in care group (P < 0.05), showing a statistically significant difference. The use of jaundice medication in the rooming-in with continuous SSC group was lower than in the routine rooming-in care group (P < 0.05), with a statistically significant difference. Multivariate analysis of newborn weight loss greater than 7% revealed that cesarean delivery was a risk factor for excessive weight loss. Multivariate analysis of weight loss greater than 9% indicated that continuous SSC was a protective factor, while mixed feeding was a risk factor. Multivariate analysis of jaundice medication use showed that cesarean delivery and mixed feeding were risk factors, while previous deliveries and SSC were protective factors. Mother-infant rooming-in with continuous SSC promotes appropriate weight gain in newborns, increases breastfeeding rates, and reduces the need for jaundice medication.

Heart failure-induced renal tubular epithelial cell fibrosis is an important pathological process that leads to chronic kidney disease. This study is to investigate the regulatory mechanism of over-expression or knock-down SIRT1 gene, alleviating hypoxia-induced HK2 cell fibrosis in heart failure. The focus is on the SIRT1-FoxO1-FoxO3-Autophagy pathway. In vitro experiments are performed by HK2cell line to simulate the normal oxygen state (Normoxia) and the hypoxia state (Hypoxia) caused by heart failure, SIRT1 gene over-expression by transfected vectors, knock-down and Rapamycin (RAPA)-induced cellular autophagy, and the cell models are divided into four subgroups, named control group, oeSIRT1, siSIRT1 and siSIRT1+RAPA. Western blotting (WB), real-time qPCR, immunofluorescence (IF), ELISA, and transmission electron microscopy are used to quantitatively or semi-quantitatively analyze the expression of FoxO1, FoxO3, SIRT1, Beclin1, LC-3, α-SMA, E- Cadherin, and collagen-I in cells or supernatants. It is demonstrated that activation of SIRT1 regulates the expression and activity of FoxO1 and FoxO3, thereby affecting autophagy. This modulation leads to a reduction in HK2 fibrosis markers (α-SMA and E-cadherin) and extracellular matrix deposition (collagen I), which ultimately attenuates renal tubular epithelial cell fibrosis. These findings provide new insights into potential therapeutic strategies for treating heart failure-induced renal tubular epithelial cell fibrosis by targeting the SIRT1-FoxO1-FoxO3-Autophagy pathway.

Medical Hyperspectral Imaging (MHSI) offers potential for computational pathology and precision medicine. However, existing CNN and Transformer struggle to balance segmentation accuracy and speed due to high spatial-spectral dimensionality. In this study, we leverage Mamba’s global context modeling to propose a dual-stream architecture for joint spatial-spectral feature extraction. To address the limitation of Mamba’s unidirectional aggregation, we introduce a recurrent spectral sequence representation to capture low-redundancy global spectral features. Experiments on a public Multi-Dimensional Choledoch dataset and a private Cervical Cancer dataset show that our method outperforms state-of-the-art approaches in segmentation accuracy while minimizing resource usage and achieving the fastest inference speed. Our code will be available at https://github.com/DeepMed-Lab-ECNU/MDN.