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In late December 2019, a cluster of cases with 2019 Novel Coronavirus pneumonia (SARS-CoV-2) in Wuhan, China, aroused worldwide concern. Previous studies have reported epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19). The purpose of this brief review is to summarize those published studies as of late February 2020 on the clinical features, symptoms, complications, and treatments of COVID-19 and help provide guidance for frontline medical staff in the clinical management of this outbreak.

The family Toxoderidae (Mantodea) contains an ecologically diverse group of praying mantis species that have in common greatly elongated bodies. In this study, we sequenced and compared the complete mitochondrial genomes of two Toxoderidae species, Paratoxodera polyacantha and Toxodera hauseri , and compared their mitochondrial genome characteristics with another member of the Toxoderidae, Stenotoxodera porioni ( KY689118 ) . The lengths of the mitogenomes of T. hauseri and P. polyacantha were 15,616 bp and 15,999 bp, respectively, which is similar to that of S. porioni (15,846 bp). The size of each gene as well as the A+T-rich region and the A+T content of the whole genome were also very similar among the three species as were the protein-coding genes, the A+T content and the codon usages. The mitogenome of T. hauseri had the typical 22 tRNAs, whereas that of P. polyacantha had 26 tRNAs including an extra two copies of trnA - trnR . Intergenic regions of 67 bp and 76 bp were found in T. hauseri and P. polyacantha , respectively, between COX2 and trnK ; these can be explained as residues of a tandem duplication/random loss of trnK and trnD. This non-coding region may be synapomorphic for Toxoderidae. In BI and ML analyses, the monophyly of Toxoderidae was supported and P. polyacantha was the sister clade to T. hauseri and S. porioni .

The prevalence of cardiomyopathy is higher in diabetic patients than those without diabetes. Diabetic cardiomyopathy (DCM) is defined as a clinical condition of abnormal myocardial structure and performance in diabetic patients without other cardiac risk factors, such as coronary artery disease, hypertension, and significant valvular disease. Multiple molecular events contribute to the development of DCM, which include the alterations in energy metabolism (fatty acid, glucose, ketone and branched chain amino acids) and the abnormalities of subcellular components in the heart, such as impaired insulin signaling, increased oxidative stress, calcium mishandling and inflammation. There are no specific drugs in treating DCM despite of decades of basic and clinical investigations. This is, in part, due to the lack of our understanding as to how heart failure initiates and develops, especially in diabetic patients without an underlying ischemic cause. Some of the traditional anti-diabetic or lipid-lowering agents aimed at shifting the balance of cardiac metabolism from utilizing fat to glucose have been shown inadequately targeting multiple aspects of the conditions. Peroxisome proliferator-activated receptor α (PPARα), a transcription factor, plays an important role in mediating DCM-related molecular events. Pharmacological targeting of PPARα activation has been demonstrated to be one of the important strategies for patients with diabetes, metabolic syndrome, and atherosclerotic cardiovascular diseases. The aim of this review is to provide a contemporary view of PPARα in association with the underlying pathophysiological changes in DCM. We discuss the PPARα-related drugs in clinical applications and facts related to the drugs that may be considered as risky (such as fenofibrate, bezafibrate, clofibrate) or safe (pemafibrate, metformin and glucagon-like peptide 1-receptor agonists) or having the potential (sodium–glucose co-transporter 2 inhibitor) in treating DCM.

Gene tagging with fluorescent proteins is essential for investigations of the dynamic properties of cellular proteins. CRISPR-Cas9 technology is a powerful tool for inserting fluorescent markers into all alleles of the gene of interest (GOI) and allows functionality and physiological expression of the fusion protein. It is essential to evaluate such genome-edited cell lines carefully in order to preclude off-target effects caused by (i) incorrect insertion of the fluorescent protein, (ii) perturbation of the fusion protein by the fluorescent proteins or (iii) nonspecific genomic DNA damage by CRISPR-Cas9. In this protocol, we provide a step-by-step description of our systematic pipeline to generate and validate homozygous fluorescent knock-in cell lines.We have used the paired Cas9D10A nickase approach to efficiently insert tags into specific genomic loci via homology-directed repair (HDR) with minimal off-target effects. It is time-consuming and costly to perform whole-genome sequencing of each cell clone to check for spontaneous genetic variations occurring in mammalian cell lines. Therefore, we have developed an efficient validation pipeline of the generated cell lines consisting of junction PCR, Southern blotting analysis, Sanger sequencing, microscopy, western blotting analysis and live-cell imaging for cell-cycle dynamics. This protocol takes between 6 and 9 weeks. With this protocol, up to 70% of the targeted genes can be tagged homozygously with fluorescent proteins, thus resulting in physiological levels and phenotypically functional expression of the fusion proteins.

We determined 15 complete and two nearly complete mitogenomes of Heptageniidae belonging to three subfamilies (Heptageniinae, Rhithrogeninae, and Ecdyonurinae) and six genera (Afronurus, Epeorus, Leucrocuta, Maccaffertium, Stenacron, and Stenonema). Species of Rhithrogeninae and Ecdyonurinae had the same gene rearrangement of CR-I-M-Q-M-ND2, whereas a novel gene rearrangement of CR-I-M-Q-NCR-ND2 was found in Heptageniinae. Non-coding regions (NCRs) of 25–47 bp located between trnA and trnR were observed in all mayflies of Heptageniidae, which may be a synapomorphy for Heptageniidae. Both the BI and ML phylogenetic analyses supported the monophyly of Heptageniidae and its subfamilies (Heptageniinae, Rhithrogeninae, and Ecdyonurinae). The phylogenetic results combined with gene rearrangements and NCR locations confirmed the relationship of the subfamilies as (Heptageniinae + (Rhithrogeninae + Ecdyonurinae)). To assess the effects of low-temperature stress on Heptageniidae species from Ottawa, Canada, we found 27 positive selection sites in eight protein-coding genes (PCGs) using the branch-site model. The selection pressure analyses suggested that mitochondrial PCGs underwent positive selection to meet the energy requirements under low-temperature stress.

Background The high prevalence of diabetic kidney disease (DKD) in the United States necessitates further investigation into its impact on complications associated with total hip arthroplasty (THA). This study utilizes a large nationwide database to explore risk factors in DKD cases undergoing THA. Methods This research utilized a case–control design, leveraging data from the national inpatient sample for the years 2016 to 2019. Employing propensity score matching (PSM), patients diagnosed with DKD were paired on a 1:1 basis with individuals free of DKD, ensuring equivalent age, sex, race, Elixhauser Comorbidity Index (ECI), and insurance coverage. Subsequently, comparisons were drawn between these PSM-matched cohorts, examining their characteristics and the incidence of post-THA complications. Multivariate logistic regression analysis was then employed to evaluate the risk of early complications after surgery. Results DKD's prevalence in the THA cohort was 2.38%. A 7-year age gap separated DKD and non-DKD patients (74 vs. 67 years, P  < 0.0001). Additionally, individuals aged above 75 exhibited a substantial 22.58% increase in DKD risk (49.16% vs. 26.58%, P  < 0.0001). Notably, linear regression analysis yielded a significant association between DKD and postoperative acute kidney injury (AKI), with DKD patients demonstrating 2.274-fold greater odds of AKI in contrast with non-DKD individuals (95% CI: 2.091–2.473). Conclusions This study demonstrates that DKD is a significant risk factor for AKI in patients undergoing total hip arthroplasty. Optimizing preoperative kidney function through appropriate interventions might decrease the risk of poor prognosis in this population. More prospective research is warranted to investigate the potential of targeted kidney function improvement strategies in reducing AKI rates after THA. The findings of this study hold promise for enhancing preoperative counseling by surgeons, enabling them to provide DKD patients undergoing THA with more precise information regarding the risks associated with their condition.

Diabetic neuropathy is one of the clinical syndromes characterized by pain and substantial morbidity primarily due to a lesion of the somatosensory nervous system. The burden of diabetic neuropathy is related not only to the complexity of diabetes but also to the poor outcomes and difficult treatment options. There is no specific treatment for diabetic neuropathy other than glycemic control and diligent foot care. Although various metabolic pathways are impaired in diabetic neuropathy, enhanced cellular oxidative stress is proposed as a common initiator. A mechanism-based treatment of diabetic neuropathy is challenging; a better understanding of the pathophysiology of diabetic neuropathy will help to develop strategies for the new and correct diagnostic procedures and personalized interventions. Thus, we review the current knowledge of the pathophysiology in diabetic neuropathy. We focus on discussing how the defects in metabolic and vascular pathways converge to enhance oxidative stress and how they produce the onset and progression of nerve injury present in diabetic neuropathy. We discuss if the mechanisms underlying neuropathy are similarly operated in type I and type II diabetes and the progression of antioxidants in treating diabetic neuropathy.

BackgroundCigarette smoking is a common risk factor for diseases and cancers. Oral microbiota is also associated with diseases and cancers. However, little is known about the impact of cigarette smoking on the oral microbiota, especially among ethnic minority populations.MethodsWe investigated cigarette smoking in relationship with the oral microbiota in a large population of predominately low-income and African-American participants. Mouth rinse samples were collected from 1616 participants within the Southern Community Cohort Study, including 592 current-smokers, 477 former-smokers and 547 never-smokers. Oral microbiota was profiled by 16S ribosomal RNA gene deep sequencing.ResultsCurrent-smokers showed a different overall microbial composition from former-smokers (p=6.62×10−7) and never-smokers (p=6.00×10−8). The two probiotic genera, Bifidobacterium and Lactobacillus, were enriched among current-smokers when compared with never-smokers, with Bonferroni-corrected p values (PBonferroni ) of 1.28×10−4 and 5.89×10−7, respectively. The phylum Actinobacteria was also enriched in current-smokers when compared with never-smokers, with a median relative abundance of 12.35% versus 9.36%, respectively, and with a PBonferroni =9.11×10−11. In contrast, the phylum Proteobacteria was depleted in current smokers (PBonferroni =5.57×10−13), with the relative abundance being almost three times that of never-smokers (7.22%) when compared with that of current-smokers (2.47%). Multiple taxa within these two phyla showed differences in abundance/prevalence between current-smokers and never-smokers at PBonferroni <0.05. The differences in the overall microbial composition and abundance/prevalence of most taxa were observed among both African-Americans and European-Americans. Meanwhile, such differences were not observed between former-smokers and never-smokers.ConclusionSmoking has strong impacts on oral microbial community, which was recovered after smoking cessation.

This study explores the regulatory mechanism of the miR‐128‐3p in diabetic retinopathy (DR)‐associated inflammatory injury. A cellular model of DR was established by inducing immortalized human retinal endothelial cells (IM‐HRECs) with high‐glucose (HG). Cell viability was evaluated by CCK‐8 assay, and the levels of TNF‐α, IL‐1β, and IL‐10 were measured by ELISA. RT‐qPCR was performed to determine miR‐128‐3p expression, and miR‐128‐3p mimics were transfected into cells to verify its regulatory role in DR‐associated inflammatory injury. miR‐128‐3p was predicted by Starbase to bind to the 3′ UTR of KDM3A, which was verified by dual‐luciferase assay. The expressions of KDM3A and NLRP3 in cells were examined by Western blotting, and the enrichment of KDM3A and H3K9me2 on the NLRP3 promoter was measured by Ch‐IP assay. The results revealed that HG treatment significantly reduced both IM‐HREC viability and IL‐10 levels, increased the levels of TNF‐α and IL‐1β, and downregulated the expression of miR‐128‐3p. Overexpression of miR‐128‐3p reduced inflammation in IM‐HRECs induced by HG. The proposed mechanism involves targeting of the KDM3A 3′ UTR by miR‐128‐3p, leading to reduced KDM3A expression, while KDM3A increased NLRP3 expression by reducing H3K9me2. In conclusion, upregulation of miR‐128‐3p increases the histone H3K9me2 level by inhibiting KDM3A expression, thereby reducing NLRP3 expression and suppressing DR inflammatory injury.

The possibility of moving objects accessing different types of points of interest (POIs) at specific times is not always the same, so quantitative time geography research needs to consider the actual POI semantic information, including POI attributes and time information. Existing methods allocate probabilities to position points, including POIs, based on space–time position information, but ignore the semantic information of POIs. The accessing activities of moving objects in different POIs usually have obvious time characteristics, such as dinner usually taking place around 6 PM. In this paper, building upon existing probabilistic time geographic methods, we introduce POI attributes and their time preferences to propose a probabilistic time geographic model for assigning probabilities to POI accesses. This model provides a comprehensive measure of position probability with space–time uncertainty between known trajectory points, incorporating time, space, and semantic information, thereby avoiding data gaps caused by single-dimensional information. Experimental results demonstrate the effectiveness of the proposed method.