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To investigate the relationship between depression in early pregnancy and sleep quality in mid-pregnancy, and explore whether sleep disorders independently predicts depression across the perinatal period within women with or without depression in early pregnancy. Data were collected at 7 time points from 12 weeks of pregnancy to 6 weeks postpartum. Multiple logistic regression and survival analysis were used to explore the relationship between sleep quality in mid-pregnancy and perinatal depression within women with or without depression in early pregnancy. 390 women were included. Women with depression in early pregnancy were more likely to have sleep disorders and perinatal depression. Women with sleep disorders had a higher risk of perinatal depression compared to women without sleep disorders in mid-pregnancy. Stratified analysis based on whether depressed at 12 weeks of pregnancy found that among women without depression, those with sleep disorders in mid-pregnancy were more likely to have subsequent perinatal depression and appeared earlier; whereas, among women with depression, mid-pregnancy sleep disorders was not a predictor of subsequent perinatal depression. High rates of missed visits may lead to sample bias, with depression and sleep quality being assessed by self-report. Women with depression in early pregnancy are more likely to have sleep disorders in mid-pregnancy. There is a strong correlation between sleep quality in mid-pregnancy and perinatal depression among women without depression in early pregnancy. Routine screening and intervention for sleep disorders should be a priority in perinatal care to reduce the incidence of perinatal depression. • Women with depression were more likely to have sleep disorders in mid-pregnancy. • Depression in early pregnancy predicted the presence of depression from mid-pregnancy to 6 weeks postpartum. • Among non-depressed in early pregnancy, women with mid-pregnancy sleep disorders had a higher risk of perinatal depression. [ABSTRACT FROM AUTHOR]

A novel breast ultrasound tomography system based on a circular array of capacitive micromechanical ultrasound transducers (CMUT) has broad application prospects. However, the images produced by this system are not suitable as input for the training phase of the super-resolution (SR) reconstruction algorithm. To solve the problem, this paper proposes an improved medical image super-resolution (MeSR) method based on the sparse domain. First, we use the simultaneous algebraic reconstruction technique (SART) with high imaging accuracy to reconstruct the image into a training image in a sparse domain model. Secondly, we denoise and enhance the contrast of the SART images to obtain improved detail images before training the dictionary. Then, we use the original detail image as the guide image to further process the improved detail image. Therefore, a high-precision dictionary was obtained during the testing phase and applied to filtered back projection SR reconstruction. We compared the proposed algorithm with previously reported algorithms in the Shepp Logan model and the model based on the CMUT background. The results showed significant improvements in peak signal-to-noise ratio, entropy, and average gradient compared to previously reported algorithms. The experimental results demonstrated that the proposed MeSR method can use noisy reconstructed images as input for the training phase of the SR algorithm and produce excellent visual effects. [ABSTRACT FROM AUTHOR]

Background. Postpartum depression (PPD) is common after childbirth. Previous reviews on the prevalence of PPD have mainly included results that relied on screening instruments or a mixture of such instruments and diagnostic interviews. In this study, we aimed to assess the prevalence of PPD based exclusively on studies using diagnostic interviews, as they provide the most reliable and valid approach for defining "caseness." Methods. Using PubMed, Web of Science, Cochrane Library, Embase, CNKI, WANFANG DATA, and CBM up to September 18, 2022, we searched for original articles reporting data that could be used to calculate the prevalence of PPD based on diagnostic interviews. A random-effect meta-analysis model was then used to estimate the pooled prevalence. In addition, we assessed quality, heterogeneity, and publication bias across studies. Also, we did subgroup analyses to explore the pooled prevalence at different time points and settings. This study was registered with PROSPERO, CRD42021244539. Results. Of 17,115 articles retrieved, 54 studies were included (total sample size = 15,586 women). The pooled prevalence of all depression and major depression within one year postpartum was 12.1% (95% CI 10.3%-14.1%; I 2 = 91.0 %) and 7.0% (95% CI 5.7%-8.4%; I 2 = 83.0 %), respectively. The peaks of all depression occurred during the first 6 months postpartum, especially 2-3 weeks and 6-8 weeks. Subgroup analyses showed that the prevalence of major depression was associated with the income level of countries (higher in low- and middle-income countries (LMICs) than in high-income countries (HICs)) and diagnostic criteria (higher using ICD than using DSM and RDC). No evidence of publication bias was found. Conclusions. Approximately one in eight postpartum women experiences a depressive condition, with one in fifteen suffering major depression. The pooled prevalence based on diagnostic interviews was lower than the existing consensus, which was largely based on self-reported screening instruments. The higher prevalence in LMICs underlines the importance of strengthening research and service provision among these populations. [ABSTRACT FROM AUTHOR]

Simple Summary: The meat quality of small ruminants is adversely affected when the feeding mode is changed from grazing to captivity. We found that adding probiotics to lamb feed regulated the intestinal metabolites (SCFAs) of Sunit lambs, acting as signaling factors that affected the gene mRNA expression of MyHC isoforms and the activity of metabolic enzymes, thereby promoting the transformation of muscle fiber types and increasing the proportion of oxidative muscle fibers. Finally, the tenderness of the meat was improved. The development of animal husbandry is closely related to the meat quality of small ruminants. Intestinal metabolites and the muscle fiber types of lambs are important factors that affect their meat quality, but few studies have examined the regulation of the "intestinal muscle axis" by probiotics. In this study, 12 Sunit lambs were divided into a control group (C) and a probiotics group (P). The gene expressions of the myosin heavy chain, metabolic enzyme activity, and short-chain fatty acids in the intestines were analyzed using gas chromatography-mass spectrometry (GC-MS) and quantitative real-time PCR. The results showed that levels of propionic acid and butyric acid in the intestines of group P were significantly higher than in group C (p < 0.05). In addition, probiotics increased the number and area ratio of type I muscle fibers. They also increased the mRNA expression of MyHC IIA and the activity of malate dehydrogenase (MDH) and succinate dehydrogenase (SDH). Propionic acid was negatively correlated with the number ratio of type IIB muscle fibers. Butyric acid was found to be significantly positively correlated with the number ratio of type IIA muscle fibers. Cooking loss, pH24h, and shear force decreased significantly in group P. In conclusion, intestinal metabolites (SCFAs) altered the activity of oxidative-myofibril-metabolizing enzymes and the expression of myosin heavy-chain type IIA, reduced the meat shear values, and improved meat tenderness. This study provides a new basis for improving the production and meat quality of small ruminants. [ABSTRACT FROM AUTHOR]

Although computer-aided diagnosis (CAD) have shown excellent performance in Breast cancer (BC) histopathological image, it commonly requires a high-level network, and the recognition efficiency is frequently unsatisfied due to the complex structure of histopathological image. In this study, a ten-layers convolutional neural network (CNN) model called "ColorDeep" is used to extract color features corresponding to the different tissue parts in cell, pure color image slices obtained by a three-channel separation and reconstruction method are used as model input. Two models are tested on the BreaKHis dataset show that images under four magnifications achieved the recognition accuracy of 96.89%–99.67% at the image level, which is better than many state-of-the-art methods. The characteristics contained by the B channel have the largest effect on BC recognition, and compared to other research results, the proposed model improves the recognition speed on a single image by about 0.1s. More importantly, instead of using large histopathological images to input into the model for BC diagnosis, and instead of segmenting the nuclei, only the reconstructed B-channel features containing the nuclei region in the stained BC image need to be input into the model to enable accurate diagnosis of BC. • Three-channel reconstructed slices contain better color features of breast cancer. • Reconstructed B-channel features contain more information about the cell nucleus. • Using color features to diagnose breast cancer can avoid segmentation of nuclei. • Reconstructed color slices enable low-complexity model to identify breast cancer. • Considering recognition accuracy and speed, feature fusion model is more suitable for breast cancer diagnosis. [ABSTRACT FROM AUTHOR]

A wide beam miniaturized broadband omnidirectional circularly polarized antenna operating at S‐band is proposed. It is composed of a hub‐shaped circular horizontally polarized radiator, a vertically polarized radiator consisting of a monopole and eight shorting‐circuited pins, and a coupling feed device. The measured results indicate that the impedance matching band of |S11| < −10 dB is from 2.15 to 2.75 GHz (24.4%), and the band of the axial ratio <3 dB is from 2.2 to 2.7 GHz (20.4%). The gain of the antenna is about 1 dB, and the noncircularity in the azimuth plane is <1.2 dB. In addition, the antenna has the characteristics of wide axis ratio beam in the pitch plane with sizes of 0.68 λ0 × 0.68 λ0 × 0.14 λ0. The antenna is very suitable for satellite receiving system and short‐range wireless communication system. [ABSTRACT FROM AUTHOR]

In this paper, a novel ultra-wideband (UWB) all-metal Vivaldi antenna with an inclined groove is proposed. The antenna structure is very simple, and it consists of Vivaldi metal plate, 2.4 mm-K connector and supporting ground. The machining of the antenna is very convenient, and the Vivaldi metal plate can be easily processed by wire cutting technology. To verify the design, the metal Vivaldi plate was machined and measured. From the measured results, the Vivaldi antenna achieves a wide impedance bandwidth of 25:1 from 2 to 50 GHz with a return loss better than 10 dB. Moreover, the gain of the Vivaldi antenna is 4−12dBi, and the radiation pattern is also symmetric and stable over the whole frequency range of 2–50 GHz. [ABSTRACT FROM AUTHOR]

There have been reports of association between psoriasis and psychological illnesses. Nevertheless, it is not easy to draw conclusions with high quality causality from conventional observational studies. The objective of this study was to evaluate the causality of psoriasis and psychological illnesses. All summary-level data from genome-wide association studies for psoriasis and psychological illnesses were collected from Neale Lab and MRC Integrative Epidemiology Unit. Bidirectional Mendelian randomization analysis was performed to determine the random orientation with an independent genetic variation. The main estimated effects are derived using Inverse-Variance Weighted, weighted median, and MR Egger methods. Multiple data sets were validated against each other, and a series of sensitivity studies were conducted to ensure the reliability of the results. Mendelian randomization analysis revealed a causal effect of psoriasis [odds ratio (OR) 1·34, 95% confidence interval (CI) 1·21–1·46, P < 0.001; and OR 1.28, CI 1.17–1.39, P < 0.001] on psychological illnesses, and vice versa (OR 1.23, CI 1.14–1.31, P < 0.001; and OR 1.21, CI 1.11–1.31, P < 0.001). The results were supported by a series of sensitivity analyses. The findings of this Mendelian randomization study support a causal effect between psoriasis and psychological illnesses, and vice versa. [ABSTRACT FROM AUTHOR]

Due to the complex underwater environment and the selective absorption and scattering effect of water on light waves, underwater images often suffer from issues such as low contrast, color distortion, and blurred details. This paper presents a stable and effective algorithm for enhancing underwater images to address these challenges. Firstly, an improved color correction algorithm based on the gray world and minimum information loss is employed to remove the blue-green bias present in the images. Secondly, a contrast enhancement algorithm is based on the guided filter and wavelet decomposition to make the texture details of the image clearer. Then, the normalized weight map of the image is obtained to carry out multi-scale fusion. Finally, the fused image is applied to perform the multi-scale decomposition. The experimental results show that the algorithm proposed in this paper can correct the image color deviation, improve the image contrast and enhance the image details. [ABSTRACT FROM AUTHOR]

Linseed as a common oil crop that has been implicated in regulating the meat quality of animals. The aim of this investigation was to establish the effects of dietary linseed supplementation on carcass traits, meat quality, muscle fiber characteristics, volatile compounds and antioxidant capacity of sheep. Twenty‐four Sunit sheep were distributed into 2 groups with different diet: control (CO) fed a standard diet and linseed (LS, 8% of extruded linseed). The results showed that linseed not only increased M. longissimus thoracis (LT) increased the loin‐eye area but also decreased pH24h, L* and shear force. Meanwhile, linseed increased mRNA expression of MyHCI and MyHCIIx and decreased in cross‐sectional area (CSA) and muscle fiber diameter. In addition, linseed altered the composition of meat volatile flavor compounds, such as Z‐10‐Pentadecen‐1‐ol, pentanal, 2‐Octenal, (E)‐, decanal, butane, and 2‐heptanone. Moreover, linseed increased total antioxidative capacity (T‐AOC) activity, the mRNA expression of glutathione peroxidase (GSH‐Px) and catalase (CAT), decreased malondialdehyde (MDA) content. Overall, the results suggest that linseed is an effective feed additive in improving meat quality and flavor. The underlying mechanisms for its effectiveness may be partly due to a change in muscle fiber characteristics and antioxidant capacity. [ABSTRACT FROM AUTHOR]

It was reported that within the head and neck cancer (HNC) cell line CAL21 the epithelial-mesenchymal transition (EMT) and cell proliferation were promoted by Urokinase-Type Plasminogen Activator (PLAU) proteinase through TNFRSF12A. Additionally, in this paper HNC cell lines refer to Fadu and Tu686. A novel PLAU-STAT3 axis was found to be involved in HNC cell line proliferation and metastasis. PLAU expression in HNC samples was upregulated, besides, the elevated expression of PLAU was linked to the lower overall survival (OS) and disease-free survival (DFS). Ectopic PLAU expression promoted cell proliferation and migration, while PLAU knockdown exhibited opposite results. RNA-seq data identified the JAK-STAT signaling pathway, confirmed by western blotting. A recovery assay using S3I-201, a selective inhibitor of signal transducer and activator of transcription 3 (STAT3), indicated that PLAU promoted HNC cell line progression via STAT3 signaling in vitro. The oncogenic role of PLAU in HNC tumor growth in vivo was confirmed using xenograft models. In summary, we identified the tumorigenic PLAU function in the HNC progress. PLAU may represent a potential prognostic biomarker of HNC and the PLAU-STAT3 pathway might be considered a therapeutic target of HNC. • High PLAU expression indicates poor overall and disease-free survival of HNC. • PLAU promotes HNC cell proliferation and migration via JAK-STAT signaling pathway. • PLAU suppresses HNC tumor growth in vivo. [ABSTRACT FROM AUTHOR]

Breast cancer is regarded as the leading killer of women today. The early diagnosis and treatment of breast cancer is the key to improving the survival rate of patients. A method of breast cancer histopathological images recognition based on deep semantic features and gray level co-occurrence matrix (GLCM) features is proposed in this paper. Taking the pre-trained DenseNet201 as the basic model, part of the convolutional layer features of the last dense block are extracted as the deep semantic features, which are then fused with the three-channel GLCM features, and the support vector machine (SVM) is used for classification. For the BreaKHis dataset, we explore the classification problems of magnification specific binary (MSB) classification and magnification independent binary (MIB) classification, and compared the performance with the seven baseline models of AlexNet, VGG16, ResNet50, GoogLeNet, DenseNet201, SqueezeNet and Inception-ResNet-V2. The experimental results show that the method proposed in this paper performs better than the pre-trained baseline models in MSB and MIB classification problems. The highest image-level recognition accuracy of 40×, 100×, 200×, 400× is 96.75%, 95.21%, 96.57%, and 93.15%, respectively. And the highest patient-level recognition accuracy of the four magnifications is 96.33%, 95.26%, 96.09%, and 92.99%, respectively. The image-level and patient-level recognition accuracy for MIB classification is 95.56% and 95.54%, respectively. In addition, the recognition accuracy of the method in this paper is comparable to some state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Pathological examination is the gold standard for breast cancer diagnosis. The recognition of histopathological images of breast cancer has attracted a lot of attention in the field of medical image processing. In this paper, on the base of the Bioimaging 2015 dataset, a two-stage nuclei segmentation strategy, that is, a method of watershed segmentation based on histopathological images after stain separation, is proposed to make the dataset recognized to be the carcinoma and non-carcinoma recognition. Firstly, stain separation is performed on breast cancer histopathological images. Then the marker-based watershed segmentation method is used for images obtained from stain separation to achieve the nuclei segmentation target. Next, the completed local binary pattern is used to extract texture features from the nuclei regions (images after nuclei segmentation), and color features were extracted by using the color auto-correlation method on the stain-separated images. Finally, the two kinds of features were fused and the support vector machine was used for carcinoma and non-carcinoma recognition. The experimental results show that the two-stage nuclei segmentation strategy proposed in this paper has significant advantages in the recognition of carcinoma and non-carcinoma on breast cancer histopathological images, and the recognition accuracy arrives at 91.67%. The proposed method is also applied to the ICIAR 2018 dataset to realize the automatic recognition of carcinoma and non-carcinoma, and the recognition accuracy arrives at 92.50%. [ABSTRACT FROM AUTHOR]