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The 2019 novel coronavirus (2019-nCoV) causing an outbreak of pneumonia in Wuhan, Hubei province of China was isolated in January 2020. This study aims to investigate its epidemiologic history, and analyze the clinical characteristics, treatment regimens, and prognosis of patients infected with 2019-nCoV during this outbreak. Clinical data from 137 2019-nCoV-infected patients admitted to the respiratory departments of nine tertiary hospitals in Hubei province from December 30, 2019 to January 24, 2020 were retrospectively collected, including general status, clinical manifestations, laboratory test results, imaging characteristics, and treatment regimens. None of the 137 patients (61 males, 76 females, aged 20-83 years, median age 57 years) had a definite history of exposure to Huanan Seafood Wholesale Market. Major initial symptoms included fever (112/137, 81.8%), coughing (66/137, 48.2%), and muscle pain or fatigue (44/137, 32.1%), with other, less typical initial symptoms observed at low frequency, including heart palpitations, diarrhea, and headache. Nearly 80% of the patients had normal or decreased white blood cell counts, and 72.3% (99/137) had lymphocytopenia. Lung involvement was present in all cases, with most chest computed tomography scans showing lesions in multiple lung lobes, some of which were dense; ground-glass opacity co-existed with consolidation shadows or cord-like shadows. Given the lack of effective drugs, treatment focused on symptomatic and respiratory support. Immunoglobulin G was delivered to some critically ill patients according to their conditions. Systemic corticosteroid treatment did not show significant benefits. Notably, early respiratory support facilitated disease recovery and improved prognosis. The risk of death was primarily associated with age, underlying chronic diseases, and median interval from the appearance of initial symptoms to dyspnea. The majority of patients with 2019-nCoV pneumonia present with fever as the first symptom, and most of them still showed typical manifestations of viral pneumonia on chest imaging. Middle-aged and elderly patients with underlying comorbidities are susceptible to respiratory failure and may have a poorer prognosis.

This paper focuses on the parameter estimation problems for multivariate pseudo-linear systems. Based on the parameters coupling characteristic of the system model, a new partially-coupled least squares algorithm is proposed. For convenience of comparison, the traditional least squares algorithm for multivariate systems is given. The proposed algorithm has better performances than the traditional algorithm. The calculation amounts of the two algorithms are analyzed, it is shown that the proposed algorithm has better computational efficiency. Two numerical simulation examples are given, and the results indicate that the proposed algorithm has better parameters identification accuracy.

Background Baicalin, which is isolated from Radix Scutellariae , possesses strong biological activities including an anti-inflammation property. Recent studies have shown that the anti-inflammatory effect of baicalin is linked to toll-like receptor 4 (TLR4), which participates in pathological changes of central nervous system diseases such as depression. In this study, we explored whether baicalin could produce antidepressant effects via regulation of TLR4 signaling in mice and attempted to elucidate the underlying mechanisms. Methods A chronic unpredictable mild stress (CUMS) mice model was performed to explore whether baicalin could produce antidepressant effects via the inhibition of neuroinflammation. To clarify the role of TLR4 in the anti-neuroinflammatory efficacy of baicalin, a lipopolysaccharide (LPS) was employed in mice to specially activate TLR4 and the behavioral changes were determined. Furthermore, we used LY294002 to examine the molecular mechanisms of baicalin in regulating the expression of TLR4 in vivo and in vitro using western blot, ELISA kits, and immunostaining. In the in vitro tests, the BV2 microglia cell lines and primary microglia cultures were pretreated with baicalin and LY292002 for 1 h and then stimulated 24 h with LPS. The primary microglial cells were transfected with the forkhead transcription factor forkhead box protein O 1 (FoxO1)-specific siRNA for 5 h and then co-stimulated with baicalin and LPS to investigate whether FoxO1 participated in the effect of baicalin on TLR4 expression. Results The administration of baicalin (especially 60 mg/kg) dramatically ameliorated CUMS-induced depressive-like symptoms; substantially decreased the levels of interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α) in the hippocampus; and significantly decreased the expression of TLR4. The activation of TLR4 by the LPS triggered neuroinflammation and evoked depressive-like behaviors in mice, which were also alleviated by the treatment with baicalin (60 mg/kg). Furthermore, the application of baicalin significantly increased the phosphorylation of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), and FoxO1. The application of baicalin also promoted FoxO1 nuclear exclusion and contributed to the inhibition of the FoxO1 transactivation potential, which led to the downregulation of the expression of TLR4 in CUMS mice or LPS-treated BV2 cells and primary microglia cells. However, prophylactic treatment of LY294002 abolished the above effects of baicalin. In addition, we found that FoxO1 played a vital role in baicalin by regulating the TLR4 and TLR4-mediating neuroinflammation triggered by the LPS via knocking down the expression of FoxO1 in the primary microglia. Conclusion Collectively, these results demonstrate that baicalin ameliorated neuroinflammation-induced depressive-like behaviors through the inhibition of TLR4 expression via the PI3K/AKT/FoxO1 pathway.

A bstract We perform a perturbative QCD analysis of the gravitational form factors (GFFs) of nucleon at large momentum transfer. We derive the explicit factorization formula of the GFFs in terms of twist-3 and twist-4 light-cone distribution amplitudes of nucleon. Power behaviors for these GFFs are obtained from the leading order calculations. Numeric results of the quark and gluon contributions to various GFFs are presented with model assumptions for the distribution amplitudes in the literature. We also present the perturbative calculations of the scalar form factor 〈 P ′ |  F 2 |  P 〉 for pion and proton at large momentum transfer.

Astragalus membranaceus widely used in traditional Chinese medicine, exhibits multiple pharmacological effects, including immune stimulation, antioxidation, hepatoprotection, diuresis, antidiabetes, anticancer, and expectorant properties. Its main bioactive compounds include flavonoids, triterpene saponins, and polysaccharides. Astragalus polysaccharides (APS), one of its primary bioactive components, have been shown to possess a variety of pharmacological activities, such as antioxidant, immunomodulatory, anti-inflammatory, antitumor, antidiabetic, antiviral, hepatoprotective, anti-atherosclerotic, hematopoietic, and neuroprotective effects. This review provides a comprehensive summary of the molecular mechanisms and therapeutic effects of APS in treating neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS). It discusses how APS improve insulin resistance, reduce blood glucose levels, enhance cognitive function, and reduce Aβ accumulation and neuronal apoptosis by modulating various pathways such as Nrf2, JAK/STAT, Toll, and IMD. For PD, APS protect neurons and stabilize mitochondrial function by inhibiting ROS production and promoting autophagy through the PI3K/AKT/mTOR pathway. APS also reduce oxidative stress and neurotoxicity induced by 6-hydroxydopamine, showcasing their neuroprotective effects. In MS, APS alleviate symptoms by suppressing T cell proliferation and reducing pro-inflammatory cytokine expression via the PD-1/PD-Ls pathway. APS promote myelin regeneration by activating the Sonic hedgehog signaling pathway and fostering the differentiation of neural stem cells into oligodendrocytes. This article emphasizes the significant antioxidant, anti-inflammatory, immunomodulatory, and neuroprotective pharmacological activities of APS, highlighting their potential as promising candidates for the treatment of neurodegenerative diseases.

Chicken products and chickens with colibacillosis are often reported to be a suspected source of extraintestinal pathogenic Escherichia coli (ExPEC) causing several diseases in humans. Such pathogens in healthy chickens can also contaminate chicken carcasses at the slaughter and then are transmitted to humans via food supply; however, reports about the ExPEC in healthy chickens are still rare. In this study, we determined the prevalence and characteristics of ExPEC isolates in healthy chickens in China. A total of 926 E. coli isolates from seven layer farms (371 isolates), one white-feather broiler farm (78 isolates) and 17 live poultry markets (477 isolates from yellow-feather broilers) in 10 cities in China, were isolated and analyzed for antibiotic resistance phenotypes and genotypes. The molecular detection of ExPEC among these healthy chicken E. coli isolates was performed by PCRs, and the serogroups and antibiotic resistance characteristics of ExPEC were also analyzed. Pulsed-field gel electrophoresis (PFGE) and Multilocus sequence typing (MLST) were used to analyze the genetic relatedness of these ExPEC isolates. We found that the resistance rate for each of the 15 antimicrobials tested among E. coli from white-feather broilers was significantly higher than that from brown-egg layers and that from yellow-feather broilers in live poultry markets (p < 0.05). A total of 22 of the 926 E. coli isolates (2.4%) from healthy chickens were qualified as ExPEC, and the detection rate (7.7%, 6/78) of ExPEC among white-feather broilers was significantly higher than that (1.6%, 6/371) from brown-egg layers and that (2.1%, 10/477) from yellow-feather broilers (p < 0.05). PFGE and MLST analysis indicated that clonal dissemination of these ExPEC isolates was unlikely. Serogroup O78 was the most predominant type among the six serogroups identified in this study, and all the six serogroups had been frequently reported in human ExPEC isolates in many countries. All the 22 ExPEC isolates were multidrug-resistant (MDR) and the resistance rates to ampicillin (100%) and sulfamethoxazole-trimethoprim (100%) were the highest, followed by tetracycline (95.5%) and doxycycline (90.9%). blaCTX-M was found in 15 of the 22 ExPEC isolates including 10 harboring additional fosfomycin resistance gene fosA3. Notably, plasmid-borne colistin resistance gene mcr-1 was identified in six ExPEC isolates in this study. Worryingly, two ExPEC isolates were found to carry both mcr-1 and blaNDM, compromising both the efficacies of carbapenems and colistin. The presence of ExPEC isolates in healthy chickens, especially those carrying mcr-1 and/or blaNDM, is alarming and will pose a threat to the health of consumers. To our knowledge, this is the first report of mcr-1-positive ExPEC isolates harboring blaNDM from healthy chickens.

With the rapid development of smart grids and distributed energy sources, the home energy management system (HEMS) is becoming a hot topic of research as a hub for connecting customers and utilities for energy visualization. Accurate forecasting of future short-term residential electricity demand for each major appliance is a key part of the energy management system. This paper aims to explore the current research status of household-level short-term load forecasting, summarize the advantages and disadvantages of various forecasting methods, and provide research ideas for short-term household load forecasting and household energy management. Firstly, the paper analyzes the latest research results and research trends in deep learning load forecasting methods in terms of network models, feature extraction, and adaptive learning; secondly, it points out the importance of combining probabilistic forecasting methods that take into account load uncertainty with deep learning techniques; and further explores the implications and methods for device-level as well as ultra-short-term load forecasting. In addition, the paper also analyzes the importance of short-term household load forecasting for the scheduling of electricity consumption in household energy management systems. Finally, the paper points out the problems in the current research and proposes suggestions for future development of short-term household load forecasting.

Human activities have shaped large-scale distributions of many species, driving both range contractions and expansions. Species differ naturally in range size, with small-range species concentrated in particular geographic areas and potentially deviating ecologically from widespread species. Hence, species’ responses to human activities may be influenced by their geographic range sizes, but if and how this happens are poorly understood. Here, we use a comprehensive distribution database and species distribution modeling to examine if and how human activities have affected the extent to which 9,701 vascular plants fill their climatic potential ranges in China. We find that narrow-ranged species have lower range filling and widespread species have higher range filling in the human-dominated southeastern part of China, compared with their counterparts distributed in the less human-influenced northwestern part. Variations in range filling across species and space are strongly associated with indicators of human activities (human population density, human footprint, and proportion of cropland) even after controlling for alternative drivers. Importantly, narrow-ranged and widespread species show negative and positive range-filling relationships to these human indicators, respectively. Our results illustrate that floras risk biotic homogenization as a consequence of anthropogenic activities, with narrow-ranged species becoming replaced by widespread species. Because narrow-ranged species are more numerous than widespread species in nature, negative impacts of human activities will be prevalent. Our findings highlight the importance of establishing more protected areas and zones of reduced human activities to safeguard the rich flora of China.

Increasing evidence shows that hepatocellular carcinoma (HCC) is a principal cause of cancer-related mortality globally, especially among Asian and African populations. Collagen type I α1 (COL1A1) is the major component of type I collagen. While aberrant expression of COL1A1 and COL1A2 is implicated in numerous cancers, the differential role of COL1A1 in malignant, premalignant and normal tissues remains unclear, and its clinical significance in HCC has not been elucidated. In this study, using bioinformatics analysis of publicly-available HCC microarray data from Gene Expression Omnibus (GEO) and RNAseq data from The Cancer Genome Atlas (TCGA) database, we determined that COL1A1 is significantly upregulated in HCC tumor tissues in comparison to normal tissues. Our analysis also revealed that COL1A1 confers survival advantage and enhanced oncogenicity on HCC cells. Interestingly, the siRNA-mediated silencing of COL1A1 expression (siCOLIA1) suppressed HCC cells clonogenicity, motility, invasiveness and tumorsphere formation. Concomitantly, siCOL1A1 abrogated Slug-dependent epithelial-to-mesenchymal transition (EMT) and HCC stemness gene-signature, by attenuating expression of stemness markers SOX2, OCT4 and CD133. The present study provides some mechanistic insight into COL1A1 activity in HCC and highlights its putative role as an important diagnostic biomarker and potential therapeutic target in early development and metastasis of HCC.

Phosphors emitting visible and near-infrared persistent luminescence have been explored extensively owing to their unusual properties and commercial interest in their applications such as glow-in-the-dark paints, optical information storage, and in vivo bioimaging. However, no persistent phosphor that features emissions in the ultraviolet C range (200–280 nm) has been known to exist so far. Here, we demonstrate a strategy for creating a new generation of persistent phosphor that exhibits strong ultraviolet C emission with an initial power density over 10 milliwatts per square meter and an afterglow of more than 2 h. Experimental characterizations coupled with first-principles calculations have revealed that structural defects associated with oxygen introduction-induced anion vacancies in fluoride elpasolite can function as electron traps, which capture and store a large number of electrons triggered by X-ray irradiation. Notably, we show that the ultraviolet C afterglow intensity of the yielded phosphor is sufficiently strong for sterilization. Our discovery of this ultraviolet C afterglow opens up new avenues for research on persistent phosphors, and it offers new perspectives on their applications in terms of sterilization, disinfection, drug release, cancer treatment, anti-counterfeiting, and beyond.