141 research outputs found

    Management of mother-to-child transmission of hepatitis B virus: Propositions and challenges

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    AbstractChronic hepatitis B virus (HBV) infection due to mother-to-child transmission (MTCT) during perinatal period remains an important global health problem. Despite standard passive–active immunoprophylaxis with hepatitis B immunoglobulin (HBIG) and hepatitis B vaccine in neonates, up to 9% of newborns still acquire HBV infection, especially these from hepatitis B e antigen (HBeAg) positive mothers. Management of HBV infection in pregnancy still need to draw careful attention because of some controversial aspects, including the failure of passive-active immunoprophylaxis in a fraction of newborns, the effect and necessity of periodical hepatitis B immunoglobulin (HBIG) injection to the mothers, the safety of antiviral prophylaxis with nucleoside/nucleotide analogs, the benefit of different delivery ways, and the safety of breastfeeding. In this review, we highlight these unsettled issues of preventive strategies in perinatal period, and we further aim to provide an optimal approach to the management of preventing MTCT of HBV infection

    Boosting Unsupervised Contrastive Learning Using Diffusion-Based Data Augmentation From Scratch

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    Unsupervised contrastive learning methods have recently seen significant improvements, particularly through data augmentation strategies that aim to produce robust and generalizable representations. However, prevailing data augmentation methods, whether hand designed or based on foundation models, tend to rely heavily on prior knowledge or external data. This dependence often compromises their effectiveness and efficiency. Furthermore, the applicability of most existing data augmentation strategies is limited when transitioning to other research domains, especially science-related data. This limitation stems from the paucity of prior knowledge and labeled data available in these domains. To address these challenges, we introduce DiffAug-a novel and efficient Diffusion-based data Augmentation technique. DiffAug aims to ensure that the augmented and original data share a smoothed latent space, which is achieved through diffusion steps. Uniquely, unlike traditional methods, DiffAug first mines sufficient prior semantic knowledge about the neighborhood. This provides a constraint to guide the diffusion steps, eliminating the need for labels, external data/models, or prior knowledge. Designed as an architecture-agnostic framework, DiffAug provides consistent improvements. Specifically, it improves image classification and clustering accuracy by 1.6%~4.5%. When applied to biological data, DiffAug improves performance by up to 10.1%, with an average improvement of 5.8%. DiffAug shows good performance in both vision and biological domains.Comment: arXiv admin note: text overlap with arXiv:2302.07944 by other author

    Computed Tomography-Based Radiomics in Predicting T Stage and Length of Esophageal Squamous Cell Carcinoma

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    Background: Because of the superficial and infiltrative spreading patterns of esophageal squamous cell carcinoma (ESCC), an accurate assessment of tumor extent is challenging using imaging-based clinical staging. Radiomics features extracted from pretreatment computed tomography (CT) or magnetic resonance imaging have shown promise in identifying tumor characteristics. Accurate staging is essential for planning cancer treatment, especially for deciding whether to offer surgery or radiotherapy (chemotherapy) in patients with locally advanced ESCC. Thus, this study aimed to evaluate the predictive potential of contrast-enhanced CT-based radiomics as a non-invasive approach for estimating pathological tumor extent in ESCC patients. Methods: Patients who underwent esophagectomy between October 2011 and September 2017 were retrospectively studied and included 116 patients with pathologically confirmed ESCC. Contrast-enhanced CT from the neck to the abdomen was performed in all patients during the 2 weeks before the operation. Radiomics features were extracted from segmentations, which were contoured by radiologists. Cluster analysis was performed to obtain clusters with similar radiomics characteristics, and chi-squared tests were used to assess differences in clinicopathological features and survival among clusters. Furthermore, a least absolute shrinkage and selection operator was performed to select radiomics features and construct a radiomics model. Receiver operating characteristic analysis was used to evaluate the predictive ability of the radiomics signatures. Results: All 116 ESCC patients were divided into two groups according to the cluster analysis. The chi-squared test showed that cluster-based radiomics features were significantly correlated with T stage (p = 0.0254) and tumor length (p = 0.0002). Furthermore, CT radiomics signatures exhibited favorable predictive performance for T stage (area under the curve [AUC] = 0.86, sensitivity = 0.77, and specificity = 0.87) and tumor length (AUC = 0.95, sensitivity = 0.92, and specificity = 0.91). Conclusions: CT contrast radiomics is a simple and non-invasive method that shows promise for predicting pathological T stage and tumor length preoperatively in ESCC patients and may aid in the accurate assessments of patients in combination with the existing examinations

    Effects of 8-Year Nitrogen and Phosphorus Treatments on the Ecophysiological Traits of Two Key Species on Tibetan Plateau

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    Understanding how nitrogen (N) and/or phosphorus (P) addition affects plants carbon- and water- related ecophysiological characteristics is essential for predicting the global change impact on the alpine meadow ecosystem structure and function in carbon and water cycling. The Qinghai-Tibetan Plateau (QTP) with the largest alpine meadow in the world is regarded as the third pole in the earth and has been experiencing increased atmospheric N deposition. In this project, we focused on two key species (Elymus dahuricus and Gentiana straminea) of the alpine meadow on the Tibetan Plateau and investigated the variability of photosynthetic and stomatal responses to 8-year N and/or P treatments through field measurements and modeling. We measured photosynthesis- and gs-response curves to generate parameter estimates from individual leaves with two widely used stomatal models (the BWB model and MED model) for validation of growth and ecosystem models and to elucidate the physiological basis for observed differences in productivity and WUE. We assessed WUE by means of gas exchange measurements (WUEi) and stable carbon isotope composition (Δ13C) to get the intrinsic and integrated estimates of WUE of the two species. P and N+P treatments, but not N, improved the photosynthetic capacity (Anet and Vcmax) for both species. Stomatal functions including instaneous measurements of stomatal conductance, intrinsic water-use efficiency and stomatal slope parameters of the two widely used stomatal models were altered by the addition of P or N+P treatment, but the impact varied across years and species. The inconsistent responses across species suggest that an understanding of photosynthetic, stomatal functions and water-use should be evaluated on species separately. WUE estimated by Δ13C values had a positive relationship with Anet and gs and a negative relationship with WUEi. Our findings should be useful for understanding the underlying mechanisms of the response of alpine plants growth and alpine meadow ecosystem to global change

    Conduction modulation of solution-processed two-dimensional materials

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    Solution-processed two-dimensional (2D) materials hold promise for their scalable applications. However, the random, fragmented nature of the solution-processed nanoflakes and the poor percolative conduction through their discrete networks limit the performance of the enabled devices. To overcome the problem, we report conduction modulation of the solution-processed 2D materials via the Stark effect. Using liquid-phase exfoliated molybdenum disulfide (MoS2) as an example, we demonstrate nonlinear conduction modulation with a switching ratio of >105 by the local fields from the interfacial ferroelectric P(VDF-TrFE). Through density-functional theory calculations and in situ Raman scattering and photoluminescence spectroscopic analysis, we understand the modulation arises from a charge redistribution in the solution-processed MoS2. Beyond MoS2, we show the modulation may be viable for the other solution-processed 2D materials and low-dimensional materials. The effective modulation can open their electronic device applications

    Blood cadmium level as a risk factor for chronic pain: NHANES database 1999–2004

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    ObjectiveThe escalating prevalence of chronic pain poses a substantial socio-economic burden. Chronic pain primarily stems from musculoskeletal and nervous system impairments. Given cadmium's known toxicity to these systems, our study sought to investigate the correlation between blood cadmium levels and chronic pain.MethodsThe cross-sectional study was conducted from the National Health and Nutrition Examination Survey (NHANES, 1999–2004), and comprised US adults who participated in a chronic pain interview. We employed logistic regression models and smooth curve fitting to elucidate the relationship between blood cadmium levels and chronic pain.ResultsOur findings revealed a linear association between blood cadmium levels and chronic pain. Compared to the lower blood cadmium tertile 1 (<0.3 ug/dL), the adjusted odds ratios (ORs) for tertile 2 (0.3–0.4 ug/dL), and tertile 3 (≥0.5 ug/dL), were 1.11 (0.96–1.29) and 1.2 (1.03–1.39), respectively. Sensitivity analyses corroborated these results.ConclusionElevated levels of blood cadmium are associated with a heightened risk of chronic pain among adults in the United States. Mitigating cadmium exposure could potentially decrease the risk of chronic pain, thereby enhancing strategies for chronic pain prevention and management

    m6A Regulator-Based Exosomal Gene Methylation Modification Patterns Identify Distinct Microenvironment Characterization and Predict Immunotherapeutic Responses in Colon Cancer.

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    peer reviewedRecent studies have highlighted the biological significance of exosomes and m6A modifications in immunity. Nonetheless, it remains unclear whether the m6A modification gene in exosomes of body fluid has potential roles in the tumor microenvironment (TME). Herein, we identified three different m6A-related exosomal gene modification patterns based on 59 m6A-related exosomal genes, which instructed distinguishing characteristics of TME in colon cancer (CC). We demonstrated that these patterns could predict the stage of tumor inflammation, subtypes, genetic variation, and patient prognosis. Furthermore, we developed a scoring mode-m6A-related exosomal gene score (MREGS)-by detecting the level of m6A modification in exosomes to classify immune phenotypes. Low MREGS, characterized by prominent survival and immune activation, was linked to a better response to anti-PDL1 immunotherapy. In contrast, the higher MREGS group displayed remarkable stromal activation, high activity of innate immunocytes, and a lower survival rate. Hence, this work provides a novel approach for evaluating TME cell infiltration in colon cancer and guiding more effective immunotherapy strategies

    Analysis of the anti-PCV2 mechanism of Lactobacillus acidophilus based on non-target metabolomics and high-throughput molecular docking

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    Our previous studies have revealed that L. acidophilus possesses inhibitory effects on PCV2 proliferation in vivo, although the underlying mechanisms remain elusive. Probiotics like L. acidophilus are known to exert antiviral through their metabolites. Therefore, in this study, non-targeted metabolomics was used to detect the changes in metabolites of L. acidophilus after 24 h of proliferation. Subsequently, high-throughput molecular docking was utilized to analyze the docking scores of these metabolites with PCV2 Cap and Rep, aiming to identify compounds with potential anti-PCV2 effects. The results demonstrated that 128 compounds such as Dl-lactate were significantly increased. The results of high-throughput molecular docking indicated that compounds such as ergocristine, and telmisartan formed complexes with Cap and Rep, suggesting their potential anti-PCV2 properties. Furthermore, compounds like vitamin C, exhibit pharmacological effects consistent with L. acidophilus adding credence to the idea that L. acidophilus may exert pharmacological effects through its metabolites. These results will provide a foundation for the study of L. acidophilus

    Corrigendum to: The TianQin project: current progress on science and technology

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    In the originally published version, this manuscript included an error related to indicating the corresponding author within the author list. This has now been corrected online to reflect the fact that author Jun Luo is the corresponding author of the article
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