A triplex crystal digital PCR for the detection of genotypes I and II African swine fever virus

African swine fever (ASF) is a highly contagious and lethal viral disease that causes severe hemorrhagic fever in pigs. It keeps spreading around the world, posing a severe socioeconomic risk and endangering biodiversity and domestic food security. ASF first outbroke in China in 2018, and has spread to most provinces nationwide. Genotypes I and II ASF virus (ASFV) as the etiological pathogens have been found in China. In this study, three pairs of specific primers and probes targeting the ASFV B646L gene, F1055L gene, and E183L gene were designed to detect universal, genotype I, and genotype II strains, respectively. A triplex crystal digital PCR (cdPCR) was established on the basis of optimizing various reaction conditions. The assay demonstrated remarkably sensitive with low limits of detection (LODs) of 5.120, 4.218, 4.588 copies/reaction for B646L, F1055L, and E183L gene, respectively; excellent repeatability with 1.24–2.01% intra-assay coefficients of variation (CVs) and 1.32–2.53% inter-assay CVs; good specificity for only detection of genotypes I and II ASFV, without cross-reactivity with PCV2, PRV, SIV, PRRSV, PEDV, FMDV, and CSFV. The triplex cdPCR was used to test 1,275 clinical samples from Guangxi province of China, and the positivity rates were 5.05, 3.22, and 1.02% for genotype I, genotype II, and co-infection of genotypes I and II, respectively. These 1,275 clinical samples were also detected using a reported reference triplex real-time quantitative PCR (qPCR), and the agreements of detection results between these two methods were more than 98.98%. In conclusion, the developed triplex cdPCR could be used as a rapid, sensitive, and accurate method to detect and differentiate genotypes I and II strains of ASFV

Lithium, an anti-psychotic drug, greatly enhances the generation of induced pluripotent stem cells

Somatic cells can be reprogrammed into induced pluripotent stem cells (iPSCs) by defined factors. The low efficiency of reprogramming and genomic integration of oncogenes and viral vectors limited the potential application of iPSCs. Here we report that Lithium (Li), a drug used to treat mood disorders, greatly enhances iPSC generation from both mouse embryonic fibroblast and human umbilical vein endothelial cells. Li facilitates iPSC generation with one (Oct4) or two factors (OS or OK). The effect of Li on promoting reprogramming only partially depends on its major target GSK3β. Unlike other GSK3β inhibitors, Li not only increases the expression of Nanog, but also enhances the transcriptional activity of Nanog. We also found that Li exerts its effect by promoting epigenetic modifications via downregulation of LSD1, a H3K4-specific histone demethylase. Knocking down LSD1 partially mimics Li's effect in enhancing reprogramming. Our results not only provide a straightforward method to improve the iPSC generation efficiency, but also identified a histone demethylase as a critical modulator for somatic cell reprogramming

Subtle distinction in molecular structure of flavonoids leads to vastly different coating efficiency and mechanism of metal-polyphenol networks with excellent antioxidant activities

Metal-polyphenol networks (MPNs) are of immense scientific interest because of their simple and rapid process to deposit on various substrates or particles with different shapes. However, there are rare reports on the effect of polyphenol molecular structure on coating efficiency and mechanism of MPNs. Herein, three typical flavonoid polyphenols, catechin (Cat), epigallocatechin (EGC) and procyanidin (PC), with the same skeleton (C6-C3-C6) but subtle distinction in molecular structure, were selected to build MPN coatings with ferric ions (Fe3+). And various techniques combined with the density functional theory (DFT) were applied to deeply reveal the roles of coordinative phenolic hydroxyl groups as well as noncovalent interactions (hydrogen bonding and π − π stacking) in the formation of flavonoid-based MPNs. We found that more accessible numbers of coordinative phenolic hydroxyl groups, the higher coating efficiency. In these flavonoid-based MPNs, the single-complex is the predominant during the coordinative modes between phenolic hydroxyl and Fe3+, not the previously reported mono-complex, bis-complex and/or tris-complex. Besides coordinative interaction, noncovalent interactions also contribute to MPNs formation, and hydrogen bonds prevail in the noncovalent interaction compared with π-π stacking. And these engineered MPN coatings can endow the substrate with excellent antioxidant activities. This study contributes to in-depth understanding the building mechanism of flavonoid-based MPNs, and increasing coating efficiency by choosing proper polyphenols

Mathematical model under E-health context for diagnosis of head and neck space Gram infection through CT imaging

The study aimed to investigate the head and neck space infection by Gram bacteria using mathematical model-based CT (computer tomography) under e-health (electronic health). Specifically, a total of 180 clinical patients with head and neck space infection were collected as the research subjects. CT/MRI examination was adopted to diagnose the disease. A mathematical model was then established to be applied in CT imaging. The cause and treatment effect were analyzed by summarizing the data, including basic information, bacterial culture, source and extent of infection, serious complications, and other factors. The results showed that the CT/MRI imaging based on the mathematical model can effectively diagnose the disease and assess the disease progress. There were more male patients than female patients with head and neck space infection, and more elderly patients than younger patients. A total of 42 patients had serious complications, accounting for 23.3% of the total patients. The most common one was descending mediastinitis, followed by respiratory obstruction, pneumonia, pericarditis, orbital infection, and multiple organ failure. There were many sources of infection in the head and neck space. The main cause was dental infection, and there were 137 cases, accounting for 76.1% of the total. Among them, odontogenic infections included tooth apical periodontitis, wisdom tooth pericoronitis, and periodontal disease. Other sources of infection included glandular infections, iatrogenic infections, and traumatic foreign bodies. The most common part affected by head and neck space infection was the submandibular space, and other parts included the masseter space, the cheek space, and the sublingual space. Severe complications of head and neck space infection were mainly inferior mediastinitis and respiratory obstruction. In the bacterial culture experiment, a total of 75 bacterial cultures of 180 patients were positive, and 62 strains of bacteria were cultured, including 11 kinds of gram-positive bacteria and 4 kinds of gram-negative bacteria. The main pathogens cultivated were Streptococcus viridans, Staphylococcus aureus, and Klebsiella pneumoniae. In laboratory tests, the values of WBC and hs-CRP in patients with severe complications were significantly higher than those in patients with common head and neck space infection. Imipenem and ornidazole were the most commonly used antibiotics in the clinical treatment of patients with severe complications. In conclusion, head and neck space infection is a serious infectious disease that may be life-threatening and requires timely and effective treatment

Metabolomics Characterize the Differential Metabolic Markers between Bama Xiang Pig and Debao Pig to Identify Pork

The Bama Xiang pig (BM) is a unique pig species in Guangxi Province, China. Compared to other breeds of domestic pig, such as the Debao pig (DB), it is smaller in size, better in meat quality, resistant to rough feeding and strong in stress resistance. These unique advantages of Bama Xiang pigs make them of great edible value and scientific research value. However, the differences in muscle metabolites between Bama Xiang pigs (BM) and Debao pigs (DB) are largely unexplored. Here, we identified 214 differential metabolites between these two pig breeds by LC-MS. Forty-one such metabolites are enriched into metabolic pathways, and these metabolites correspond to 11 metabolic pathways with significant differences. In Bama pigs, the abundance of various metabolites such as creatine, citric acid, L-valine and hypoxanthine is significantly higher than in Debao pigs, while the abundance of other metabolites, such as carnosine, is significantly lower. Among these, we propose six differential metabolites: L-proline, citric acid, ribose 1-phosphate, L-valine, creatine, and L-arginine, as well as four potential differential metabolites (without the KEGG pathway), alanyl-histidine, inosine 2′-phosphate, oleoylcarnitine, and histidinyl hydroxyproline, as features for evaluating the meat quality of Bama pigs and for differentiating pork from Bama pigs and Debao pigs. This study provides a proof-of-concept example of distinguishing pork from different pig breeds at the metabolite level and sheds light on elucidating the biological processes underlying meat quality differences. Our pork metabolites data are also of great value to the genomics breeding community in meat quality improvement

Data_Sheet_1_Higher remnant cholesterol is associated with an increased risk of amnestic mild cognitive impairment: a community-based cross-sectional study.docx

Background and aimsAmnestic mild cognitive impairment (aMCI) is the most common subtype of MCI, which carries a significantly high risk of transitioning to Alzheimer’s disease. Recently, increasing attention has been given to remnant cholesterol (RC), a non-traditional and previously overlooked risk factor. The aim of this study was to explore the association between plasma RC levels and aMCI.MethodsData were obtained from Brain Health Cognitive Management Team in Wuhan (https://hbtcm.66nao.com/admin/). A total of 1,007 community-dwelling elders were recruited for this project. Based on ten tools including general demographic data, cognitive screening and some exclusion scales, these participants were divided into the aMCI (n = 401) and normal cognitive groups (n = 606). Physical examinations were conducted on all participants, with clinical indicators such as blood pressure, blood sugar, and blood lipids collected.ResultsThe aMCI group had significantly higher RC levels compared to the normal cognitive group (0.64 ± 0.431 vs. 0.52 ± 0.447 mmol/L, p ConclusionHigher RC levels were identified as an independent indicator for aMCI, particularly in the naming cognitive domain among older individuals. Further longitudinal studies are necessary to validate the predictive efficacy of RC.</p

Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility.

Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery

Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility.

Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery

Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility.

Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery