The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across > 150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye, and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitute an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.

https://www.embopress.org/doi/pdf/10.15252/msb.20209610

The protein expression profile of ACE2 in human tissues.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), has spread globally in a few short months. Substantial evidence now supports preliminary conclusions about transmission that can inform rational, evidence-based policies and reduce misinformation on this critical topic. This article presents a comprehensive review of the evidence on transmission of this virus. Although several experimental studies have cultured live virus from aerosols and surfaces hours after inoculation, the real-world studies that detect viral RNA in the environment report very low levels, and few have isolated viable virus. Strong evidence from case and cluster reports indicates that respiratory transmission is dominant, with proximity and ventilation being key determinants of transmission risk. In the few cases where direct contact or fomite transmission is presumed, respiratory transmission has not been completely excluded. Infectiousness peaks around a day before symptom onset and declines within a week of symptom onset, and no late linked transmissions (after a patient has had symptoms for about a week) have been documented. The virus has heterogeneous transmission dynamics: Most persons do not transmit virus, whereas some cause many secondary cases in transmission clusters called "superspreading events." Evidence-based policies and practices should incorporate the accumulating knowledge about transmission of SARS-CoV-2 to help educate the public and slow the spread of this virus.

Transmission of SARS-CoV-2: A Review of Viral, Host, and Environmental Factors.

The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is Angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across >150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitutes an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.

https://biorxiv.org/content/10.1101/2020.03.31.016048v1.full.pdf

The protein expression profile of ACE2 in human tissues

Shedding of SARS-CoV-2 in feces and urine and its potential role in person-to-person transmission and the environment-based spread of COVID-19.

Assessment of SARS-CoV-2 in human semen-a cohort study.

In December 2019, an outbreak of pneumonia associated with coronavirus disease 2019 (COVID-19) occurred in Wuhan, China, and rapidly spread to other parts of China and overseas.1 It has been confirmed that COVID-19 has the characteristic of human-to-human transmission, mainly through respiratory droplets and contact. Other routes require further verification. The virus responsible for COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in stool, gastrointestinal tract, saliva, and urine samples.2 However, little is known about SARS-CoV-2 in semen.

/pdf/clinical-characteristics-and-results-of-semen-tests-among-140yfbch28.pdf

Clinical Characteristics and Results of Semen Tests Among Men With Coronavirus Disease 2019.

PURPOSE
To investigate serum leptin levels in patients with type 2 diabetes mellitus (T2DM) and the relationship between leptin levels and T2DM complications and prevalence.


METHODS
A total of 355 patients, 282 cases with T2DM and 73 normal controls, were recruited at 1st Medical Centre, Chinese PLA General Hospital (Beijing, China) between November 2013 and July 2014. Levels of serum leptin, biochemical markers and sexual hormones were measured, and clinical characteristics were retrieved through the electronic medical record system.


RESULTS
Leptin levels in females were higher than that in males. Leptin levels in T2MD patients were positively correlated with body mass index, percent body fat, triglyceride, cystatin C homocysteine and salivary acid, and negatively correlated with glycosylated serum protein and glycosylated albumin levels. Leptin levels in males were positively correlated with systolic pressure and estradiol, and negatively correlated with testosterone and high density lipoprotein cholesterol. Sex (female) was positively correlated with the duration of disease. Leptin levels in T2DM patients with complications such as hypertension, diabetic nephropathy, diabetic peripheral neuropathy and coronary heart disease were higher than that in patients without such complications. Leptin levels in females with diabetic retinopathy and diabetic macroangiopathy were higher than that in patients without such complications, but there was no difference in males.


CONCLUSIONS
Leptin has significant gender differences. Leptin levels are related to body mass index, percent body fat and sex hormone level in T2DM patients and may affect short-term blood glucose control in T2DM patients. Leptin levels are related to complications in patients with T2DM and affect the prevalence rates of complications.

/pdf/effect-of-leptin-levels-of-type-2-diabetes-mellitus-and-rojge1rf.pdf

Effect of Leptin Levels of Type 2 Diabetes Mellitus and Diabetic Complications.


 
 
 Lupus nephritis (LN) is an autoimmune nephropathy associated with systemic lupus erythematosus. Circadian rhythms are involved in the development of several diseases, especially inflammation-related diseases, but their relationship with lupus nephritis is unclear.
 
 
 
 This was an integrative bioinformatics study. The expression profile from glomeruli, tubular interstitium, and renal whole tissue samples was used to assess the expression levels and relevance of circadian-rhythm-related genes. To screen for circadian rhythm-related signatures, we employed the LASSO and SVM-RFE algorithms. A consensus clustering algorithm was used to classify LN patients into two circadian rhythm patterns (cluster A and cluster B). We made immune cell infiltration analysis. We used the WGCNA algorithm to identify cluster-specific differentially expressed genes. Nephroseq data were used to observe the relationship between genes and renal function.
 
 
 
 We found more significant differences in circadian rhythm-related gene expression in LN glomeruli compared to tubulointerstitial and whole kidney tissues. We established a circadian rhythm-related signature, consisting of eight genes that can easily distinguish LN from healthy individuals. Patients in cluster A were associated with B-cell-dominated immunity, whereas patients in cluster B were associated with T-cell-dominated immunity. As most of the patients with proliferative LN combined with membranous LN belonged to cluster B, patients in cluster B may have more severe renal pathology compared to patients in cluster A. Fifteen circadian rhythm-related genes associated with LN and LN typing were screened using the WGCNA algorithm, with COL1A2 and DOCK2 associated with renal prognosis.
 
 
 
 This study found that circadian rhythms are associated with the occurrence of LN, providing new ideas for the development of new LN treatment options from the perspective of circadian rhythms.


Integrative analysis of the association between circadian rhythm and lupus nephritis

Lupus nephritis (LN) is the most common and severe clinical manifestation of systemic lupus erythematosus (SLE). N6-methyladenosine (m6A) is a reversible RNA modification and has been implicated in various biological processes. However, the roles of m6A regulators in LN are not fully demonstrated. We downloaded the kidney tissue transcriptome dataset of LN patients and normal controls from the GEO database and extracted the expression levels of m6A regulators. We constructed and compared Random Forest (RF) and Support Vector Machine (SVM) models, and subsequently selected featured genes to develop nomogram models. The m6A subtypes were identified based on significantly differentially expressed m6A regulators, and the m6A gene subtypes were identified based on m6A-associated differential genes, and the two m6A modification patterns were comprehensively evaluated. We obtained the GSE32591 and GSE112943 datasets from the GEO database, including 78 LN samples and 36 normal control samples. We extracted the expression levels of 20 m6A regulators. By RF analysis we identified 7 characteristic m6A regulators and constructed nomogramh models with these 7 genes. We identified two m6A subtypes based on these seven important m6A regulators, and the immune cell infiltration levels of the two subtype clusters were significantly different. We identified two more m6A gene subtypes based on m6A-associated DEGs. We calculated the m6A scores using the principal component analysis (PCA) algorithm and found that the m6A scores of m6A cluster A and gene cluster A were lower than those of m6A cluster B and gene cluster B. In addition, we found that the levels of inflammatory factors were also significantly different between m6A clusters and gene clusters. This study confirms that m6A regulators are involved in the LN process through different modes of action and provide new diagnostic and therapeutic targets for LN.

Analysis of m6A-regulated genes and subtype classification in lupus nephritis

Three serum miRNAs as potential biomarkers for early diagnosis of cervical cancer

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Meiling Jin

Author Tools

Chat about Author