Supply Chain Joint Inventory Management and Cost Optimization Based on Ant Colony Algorithm and Fuzzy Model

With the advancement of the marketization process, inventory management has transformed from a single backup protection function to an essential function for enterprises, which helps to survive and develop. Inventory control in supply chain management is the important content of supply chain management. The new management mode makes inventory management present many new characteristics and problems compared with traditional inventory management. From the view of system theory and integration theory, it is imperative to re-examine the problem of inventory control, put forward new inventory management strategies adapted to integrated supply chain management, and improve the integration of the whole supply chain, which can enhance the agility and market response speed of enterprises. Based on the in-depth study of the joint inventory management model, this paper analyzed the current situation of the joint inventory management to optimize the inventory. In view of the achievements and shortcomings of the current research, a more systematic and improved optimization model of the supply chain inventory was proposed by using the basic ideas of ant colony algorithm and fuzzy model

Spatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management

Blocking Nuclear Factor-Kappa B Protects against Diet-Induced Hepatic Steatosis and Insulin Resistance in Mice

Inflammation critically contributes to the development of various metabolic diseases. However, the effects of inhibiting inflammatory signaling on hepatic steatosis and insulin resistance, as well as the underlying mechanisms remain obscure. In the current study, male C57BL/6J mice were fed a chow diet or high-fat diet (HFD) for 8 weeks. HFD-fed mice were respectively treated with p65 siRNA, non-silence control siRNA or vehicle every 4th day for the last 4 weeks. Vehicle-treated (HF) and non-silence siRNA-treated (HFNS) mice displayed overt inflammation, hepatic steatosis and insulin resistance compared with chow-diet-fed (NC) mice. Upon treatment with NF-κB p65 siRNA, HFD-fed (HFPS) mice were protected from hepatic steatosis and insulin resistance. Furthermore, Atg7 and Beclin1 expressions and p-AMPK were increased while p-mTOR was decreased in livers of HFPS mice in relative to HF and HFNS mice. These results suggest a crosslink between NF-κB signaling pathway and liver AMPK/mTOR/autophagy axis in the context of hepatic steatosis and insulin resistance

The brief overview, antivirus and anti-SARS-CoV-2 activity, quantitative methods, and pharmacokinetics of cepharanthine: a potential small-molecule drug against COVID-19

To effectively respond to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an increasing number of researchers are focusing on the antiviral activity of cepharanthine (CEP), which is a clinically approved drug being used for over 70 years. This review aims to provide a brief overview of CEP and summarize its recent findings in quantitative analysis, pharmacokinetics, therapeutic potential, and mechanism in antiviral and anti-SARS-CoV-2 activity. Given its remarkable capacity against SARS-CoV-2 infection in vitro and in vivo, with its primary target organ being the lungs, and its good pharmacokinetic profile; mature and stable manufacturing technique; and its advantages of safety, effectiveness, and accessibility, CEP has become a promising drug candidate for treating COVID-19 despite being an old drug

Metformin Uniquely Prevents Thrombosis by Inhibiting Platelet Activation and mtDNA Release

Thrombosis and its complications are the leading cause of death in patients with diabetes. Metformin, a first-line therapy for type 2 diabetes, is the only drug demonstrated to reduce cardiovascular complications in diabetic patients. However, whether metformin can effectively prevent thrombosis and its potential mechanism of action is unknown. Here we show, metformin prevents both venous and arterial thrombosis with no significant prolonged bleeding time by inhibiting platelet activation and extracellular mitochondrial DNA (mtDNA) release. Specifically, metformin inhibits mitochondrial complex I and thereby protects mitochondrial function, reduces activated platelet-induced mitochondrial hyperpolarization, reactive oxygen species overload and associated membrane damage. In mitochondrial function assays designed to detect amounts of extracellular mtDNA, we found that metformin prevents mtDNA release. This study also demonstrated that mtDNA induces platelet activation through a DC-SIGN dependent pathway. Metformin exemplifies a promising new class of antiplatelet agents that are highly effective at inhibiting platelet activation by decreasing the release of free mtDNA, which induces platelet activation in a DC-SIGN-dependent manner. This study has established a novel therapeutic strategy and molecular target for thrombotic diseases, especially for thrombotic complications of diabetes mellitus

The utilization of nanopore targeted sequencing proves to be advantageous in the identification of infections present in deceased donors

BackgroundNanopore Target Sequencing (NTS) represents a novel iteration of gene sequencing technology; however, its potential utility in the detection of infection in deceased donors has yet to be documented. The present study endeavors to assess the applicability of NTS in this domain.MethodsThis retrospective study comprised a cohort of 71 patients who were under intensive care at Renmin Hospital of Wuhan University between June 2020 and January 2022. The specimens were subjected to microbiological tests utilizing NTS, culture, and other techniques, and subsequently, the diagnostic accuracy of NTS was compared with conventional methods.ResultsBlood NTS exhibited a better agreement rate of 52.11% and a greater positive rate of pathogen detection than blood culture (50.70% vs. 5.63%, p < 0.001). In NTS of deceased donors, Klebsiella pneumoniae, Escherichia coli, and Acinetobacter baumannii were the most frequently found bacteria, and Candida was the most frequently found fungus. Blood NTS had a considerably better sensitivity for detecting clinical bloodstream infection than blood culture (62.50%: 7.14%, p < 0.001). These findings were supported by comparisons between blood NTS and conventional microbial detection methods (such as blood culture, glucan testing, galactomannan testing, T cell spot testing for tuberculosis infection, smear, etc.).ConclusionThe pathogen detection technology NTS has a high sensitivity and positive rate. It can more accurately and earlier detect infection in deceased donors, which could be very important for raising the donation conversion rate

A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the “Chinese Data-sharing Warehouse for In-vivo Imaging Brain” in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank