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Perinatal depression (PD), which affects about 10–20 percent of women, often goes unnoticed because related symptoms frequently overlap with those commonly experienced during pregnancy. Moreover, identifying PD currently depends heavily on the use of questionnaires, and objective biological indicators for diagnosis has yet to be identified. This research proposes a safe and non-invasive method for diagnosing PD and aims to delve deeper into its underlying mechanism. Considering the non-invasiveness and clinical convenience of electroencephalogram (EEG) for mothers-to-be and fetuses, we collected the resting-state scalp EEG of pregnant women (with PD/healthy) at the 38th week of gestation. To compensate for the low spatial resolution of scalp EEG, source analysis was first applied to project the scalp EEG to the cortical-space. Afterwards, cortical-space networks and large-scale networks were constructed to investigate the mechanism of PD from two different level. Herein, differences in the two distinct types of networks between PD patients and healthy mothers-to-be were explored, respectively. We found that the PD patients illustrated decreased network connectivity in the cortical-space, while the large-scale networks revealed weaker connections at cerebellar area. Further, related spatial topological features derived from the two different networks were combined to promote the recognition of pregnant women with PD from those healthy ones. Meanwhile, the depression severity at patient level was effectively predicted based on the combined spatial topological features as well. These findings consistently validated that the two kinds of networks indeed played off each other, which thus helped explore the underlying mechanism of PD; and further verified the superiority of the combination strategy, revealing its reliability and potential in diagnosis and depression severity evaluation.

Purpose: To develop and validate deep learning algorithms that can identify and classify angle-closure (AC) mechanisms using anterior segment optical coherence tomography (AS-OCT) images. Methods: This cross-sectional study included participants of the Handan Eye Study aged ≥35 years with AC detected via gonioscopy or on the AS-OCT images. These images were classified by human experts into the following to indicate the predominant AC mechanism (ground truth): pupillary block, plateau iris configuration, or thick peripheral iris roll. A deep learning architecture, known as comprehensive mechanism decision net (CMD-Net), was developed to simulate the identification of image-level AC mechanisms by human experts. Cross-validation was performed to optimize and evaluate the model. Human-machine comparisons were conducted using a held-out and separate test sets to establish generalizability. Results: In total, 11,035 AS-OCT images of 1455 participants (2833 eyes) were included. Among these, 8828 and 2.207 images were included in the cross-validation and held-out test sets, respectively. A separate test was formed comprising 228 images of 35 consecutive patients with AC detected via gonioscopy at our eye center. In the classification of AC mechanisms, CMD-Net achieved a mean area under the receiver operating characteristic curve (AUC) of 0.980, 0.977, and 0.988 in the cross-validation, held-out, and separate test sets, respectively. The best-performing ophthalmologist achieved an AUC of 0.903 and 0.891 in the held-out and separate test sets, respectively. And CMD-Net outperformed glaucoma specialists, achieving an accuracy of 89.9 % and 93.0 % compared to 87.0 % and 86.8 % for the best-performing ophthalmologist in the held-out and separate test sets, respectively. Conclusions: Our study suggests that CMD-Net has the potential to classify AC mechanisms using AS-OCT images, though further validation is needed.

Polygonatum odoratum is widely recognized to conribute to various health benefits, primarily attributed to its polysaccharide (POP). Polysaccharides are not directly and readily absorbed by the gastrointestinal system, but can interact with the gut microbes. This study aims to clarify the mechanism of POP in mitigating and preventing OVA-induced allergic airway inflammation via the gut-lung axis. The results showed that POP improved the symptoms associated with allergic respiratory responses, and the efficacy of POP was impeded due to the disruption of gut microbiota caused by antibiotics. The POP altered gut microbiota effectively alleviated the type 2 inflammation, reduced the number of ILC2s in the lung and gut, and inhibited the movement of intestinal ILC2s towards the lung. Clostridia UCG-014 and Rikenellaceae RC9 were figured out as pathogenic bacteria inhibited by POP. This study provides a reference for therapeutic application of POP in managing allergic airway inflammation via the gut-lung axis.

Background: Retinal health indices were suggested to be related to psychopathological symptoms, such as depressive symptoms. However, large-scale studies using optical coherence tomography (OCT) are missing to investigate the associations among them. Methods: In the META-KLS cohort study, 1456 participants (mean age [standard deviation]= 54.6 [11.91] years; n= 680 [47.8%] women) completed the Patient Health Questionnaire (PHQ-9) to measure depressive symptoms and underwent OCT. Poor-quality OCTs and multivariate outliers were excluded, and principal component analysis was performed to obtain retinal health indices separately for macular (n= 930) and optic nerve head (ONH) thicknesses (n= 800). Linear regressions were run controlling for covariates. Exploratory interaction models were run with demographic, lifestyle and health markers. Results: Although there were no direct significant associations between the retinal indices and depressive symptoms (macular: B= −0.05, 95% CI= [-0.15, 0.05], p= 0.32; ONH index: B= -0.02, 95% CI= [-0.11, 0.08], p= 0.71), their associations were moderated by demographic and health factors, e.g., C-reactive protein (CRP) (macular index: B= −0.03, 95% CI= [-0.05, −0.01], p= 0.002; ONH index: B= 0.05, 95% CI= [0.02, 0.08], p= 0.002). Limitations: Study was cross-sectional and there were no functional assessments of vision. Conclusions: In a large cohort, we observed associations between retinal indices and self-reported depressive symptoms depending on demographic and health factors, notably CRP. Following up, the study will investigate the prospective prediction of retinal health on depressive symptoms, especially in persons who may have chronic inflammation.

Anxiety and depression caused by inflammatory bowel disease (IBD) negatively affect the mental health of patients. Emerging studies have demonstrated that the gut-brain axis (GBA) mediates IBD-induced mood disorders, but the underlying mechanisms of these findings remain unknown. Therefore, it's vital to conduct comprehensive research on the GBA in IBD. Multi-omics studies can provide an understanding of the pathological mechanisms of the GBA in the development of IBD, helping to uncover the mechanisms underlying the onset and progression of the disease. Thus, we analyzed the prefrontal cortex (PFC) of Dextran Sulfate Sodium Salt (DSS)-induced IBD mice using transcriptomics and metabolomics. We observed increased mRNA related to acetylcholine synthesis and secretion, along with decreased phosphatidylcholine (PC) levels in the PFC of DSS group compared to the control group. Fecal metagenomics also revealed abnormalities in the microbiome and lipid metabolism in the DSS group. Since both acetylcholine and PC are choline metabolites, we posited that the DSS group may experience choline deficiency and choline metabolism disorders. Subsequently, when we supplemented CDP-choline, IBD mice exhibited improvements, including decreased anxiety-like behaviors, reduced PC degradation, and increased acetylcholine synthesis in the PFC. In addition, administration of CDP-choline can restore imbalances in the gut microbiome and disruptions in lipid metabolism caused by DSS treatment. This study provides compelling evidence to suggest that choline metabolism plays a crucial role in the development and treatment of mood disorders in IBD. Choline and its metabolites appear to have a significant role in maintaining the stability of the GBA.

Summary: Background: The disease burden of gastrointestinal disease (GD) in China is high, with significant variation across provinces. A comprehensive agreed set of indicators could guide rational resource allocation to support better GD outcomes. Methods: This study collected data from multiple sources, including national surveillance, surveys, registration systems, and scientific research. Literature reviews and Delphi methods were used to obtain monitoring indicators; the analytic hierarchy process was used to determine indicator weights. Findings: The China Gastrointestinal Health Index (GHI) system consisted of four dimensions and 46 indicators. The weight of the four dimensions from high to low included the prevalence of gastrointestinal non-neoplastic diseases and gastrointestinal neoplasms (GN) (0.3246), clinical treatment of GD (0.2884), prevention and control of risk factors (0.2606), and exposure to risk factors (0.1264). The highest indicator weight of GHI rank was the successful smoking cessation rate (0.1253), followed by the 5-year survival rate of GN (0.0905), and the examination rate of diagnostic oesophagogastroduodenoscopy (0.0661). The overall GHI for China in 2019 was 49.89, varying from 39.19 to 76.13 across all sub-regions. The top five sub-regions in the total GHI score were in the eastern region. Interpretation: GHI is the first system designed to monitor gastrointestinal health systematically. In the future, data from sub-regions of China should be used to test and improve the GHI system for its impact. Funding: This research was supported by the National Health Commission of China, the First Affiliated Hospital of Naval Medical University (2019YXK006), and the Science and Technology Commission of Shanghai Municipality (21Y31900100).

Summary: Background: Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to the theory of traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC). Methods: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362. Findings: For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88–0.92 in the internal verification and 0.83–0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers. Interpretation: Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG). Funding: The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).

We theoretically study how to greatly improve the near-infrared light absorption of monolayer graphene through the excitation of magnetic resonance in metamaterials. The absorption maximum of monolayer graphene is able to reach up to about 77% at the communication wavelength of 1550 nm. The conventionally defined absorption bandwidth, i.e., the full width at half maximum (FWHM), is nearly 160 nm. Thanks to the localization nature of magnetic resonance, the broadband high-efficiency absorption of monolayer graphene is insensitive to the incident angle and the light polarization. The absorption maximum, the absorption bandwidth, and the resonance position all have almost no change, when the incident angle is increased to even 60 degrees for both p and s polarizations. By applying an external bias voltage to change Fermi energy, the absorption in graphene can be completely modulated, with a nearly 100% modulation depth. Furthermore, the graphene absorption has an abrupt and large change around the interband transition, which exhibits an electrical switching property. Our work may find potential applications in graphene-based optoelectronic devices such as photodetector and modulator.

Transmission lines are one of the most important infrastructures of energy Internet in China, and the effective detection of fittings is a necessary prerequisite to ensure their safety and stability. The fitting detection method based on classic deep learning only focuses on a single region and extracts the visual features of the region proposal into the classifier to identify the target, but never considers the connection between fittings. There is a certain regularity between fittings when constructing a complete and intact transmission line, interdependent and interact with each other. Therefore, we propose a knowledge-guided aerial transmission line image fitting detection model (KGFD) which uses two modules to learn the regularity of the fittings. The first module is an implicit module, starting from the spatial layout of the fittings on the image and taking the relative geometric features of the region proposal as the input knowledge of the spatial position of the fittings on the image. The second module is an explicit one. By introducing the prior knowledge of the fittings expressed in co-occurrence mode and using the region proposal as the node while the prior knowledge as the edge, a knowledge graph is constructed. The information spreads on the knowledge graph via a gated graph neural network, which realizes a combination of the prior knowledge of the fitting with the features of the region proposal. These two modules are added to the deep learning framework to detect the fitting targets, and the typical fitting data set of aerial transmission lines are used for testing. The AP value increased by 4.4% when IoU={0.5:0.95} and the AP value by 3.9% when IoU=0.5 compared with those of Faster R-CNN classification.

Summary: Background: Functional constipation (FC) is an intractable disease that carries large financial burden as well as emotional and physical stress. We aimed to assess the efficacy and safety of the newly developed smartphone-controlled vibrating capsule (VC) in patients with FC. Methods: From December 2018 to February 2020, we did a multicenter, blinded, placebo-controlled randomised trial in six top general hospitals in China focusing on patients aged 18 to 80 with FC. Patients were randomly assigned in a 1:1 ratio to receive VCs or placebo treatment for six weeks (two capsules per week) after a two-week baseline period. The primary outcome was the responder rate, defined as the proportion of patients with an increase of at least one complete spontaneous bowel movement (CSBM) per week during treatment compared to baseline in the full analysis set. This trial is registered with ClinicalTrials.gov, number NCT04671264, and is completed. Findings: 107 patients aged from 18 to 74 were randomly assigned to receive VC (n = 53) or placebo treatment (n = 54). The responder rate in the VC group was significantly higher than that in the placebo group (64·2% vs. 35·8%; difference, 27·7% [95% CI, 10·4–45·1]; P = 0·005). More patients in the VC group reported weekly CSBMs ≥ 1 for at least four weeks during treatment (difference, 22·7% [95% CI, 8–46]; P = 0·022) and follow-up period (difference, 17.3% [95% CI, 0–35]; P = 0·048). The mean Patient Assessment of Constipation-Symptoms score and Patient Assessment of Constipation-Quality of Life score differed significantly from the baseline in both groups (all P

Purpose: Crohn's disease (CD) has been known to cause both abdominal pain alongside functional and structural alterations in the central nervous system (CNS) in affected patients. This study seeks to determine the alternations of metabolites in the bilateral anterior cingulate cortex (ACC) of CD patients with abdominal pain by using proton magnetic resonance spectroscopy (1H-MRS) to further explore the neural mechanism. Methods: Sixteen CD patients with abdominal pain and 13 CD patients without abdominal pain, were recruited alongside 20 healthy controls (HCs) for this study. Clinical evaluations, including the 0–10 Visual Analogue Scale (VAS) of pain, Hospital Anxiety and Depression Scale (HADS) and Crohn's Disease Activity Index (CDAI), were evaluated prior to MR scanning. This study selected the bilateral ACC as the region of interest (ROI). The metabolites of the bilateral ACC were quantitatively analyzed by LCModel and Gannet. A independent sample t-test and one-way analysis of variance (ANOVA) were performed for statistical analysis. Spearman correlation analyses were performed to examine the relationship between the metabolite levels and clinical evaluations. Results: The results indicated that CD patients with abdominal pain exhibited significantly higher levels of Glutamate (Glu)/(creatine + phosphocreatine, total creatine, tCr) over CD patients without abdominal pain, and HCs (p = 0.003, 0.009, respectively) in the bilateral ACC. The level of (Glutamate + Glutamine, Glx)/tCr of pain CD group was higher than non-pain CD group (p = 0.022). Moreover, within the pain CD group, Glu/tCr and Glx/tCr levels correlated strongly with the VAS scores of pain (ρ = 0.86, 0.59 respectively, p

Transforming growth factor beta 1 (TGF-β1) was of importance in the pathogenesis of porcine reproductive and respiratory syndrome virus (PRRSV). To determine whether knockdown of TGF-β1 gene expression could facilitate the control of PRRSV infection, specific sequences for expressing shRNA targeted to porcine TGF-β1 gene were synthesized and cloned into pSilencer 3.1-H1 neovector. Then they were used to transfect peripheral blood mononuclear cells of Tibetan pig (Tp-PBMCs) followed by PRRSV inoculation. The positive recombinant plasmids were screened for inhibition of TGF-β1 gene expression by real-time quantitative RT-PCR. Conversely, the mRNA level of PRRSV in shRNA treated Tp-PBMCs dramatically decreased, and there were significant increases of the transcription of immune genes, such as interleukin-2 (IL-2), interleukin-4 (IL-4), interferon-alpha (IFN-α), interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), toll-like receptor 3 (TLR3), toll-like receptor 7 (TLR7), Myeloid differentiation primary response gene (88) (MyD88), and interleukin-27p28 (IL-27p28). However, the expressions of IL-8 and IL-10 genes significantly reduced in comparison to the control infected cells. In addition, transfection with the shRNA plasmids significantly elevated the viability of immune cells. Therefore the knockdown of TGF-β1 gene expression by shRNA not only inhibits the replication of PRRSV but also improves immune responsiveness following viral infection, suggesting a novel way to facilitate the control of PRRSV infection in pigs. Keywords: Tibetan pig, RNAi, TGF-β1 gene, PRRSV, Immune genes expression