The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The Role of Adipocytes and Adipocyte‐Like Cells in the Severity of COVID‐19 Infections
Open accessAbstract
Coronavirus disease‐2019 (COVID‐19), caused by the highly pathogenic severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), demonstrates high morbidity and mortality caused by development of a severe acute respiratory syndrome connected with extensive pulmonary fibrosis. In this Perspective, we argue that adipocytes and adipocyte‐like cells, such as pulmonary lipofibroblasts, may play an important role in the pathogenic response to SARS‐CoV‐2. Expression of angiotensin‐converting enzyme 2 (the functional receptor for SARS‐CoV) is upregulated in adipocytes of patients with obesity and diabetes, which turns adipose tissue into a potential target and viral reservoir. This may explain why obesity and diabetes are potential comorbidities for COVID‐19 infections. Similar to the recently established adipocyte‐myofibroblast transition, pulmonary lipofibroblasts located in the alveolar interstitium and closely related to classical adipocytes demonstrate the ability to transdifferentiate into myofibroblasts that play an integral part of pulmonary fibrosis. This may significantly increase the severity of the local response to SARS‐CoV‐2 in the lung. To reduce the severity and mortality associated with COVID‐19, we propose to probe for the clinical response to thiazolidinediones, peroxisome proliferator activated receptor γ agonists that are well‐known antidiabetic drugs. Thiazolidinediones are able to stabilize lipofibroblasts in their “inactive” state, preventing the transition to myofibroblasts and thereby reducing the development of pulmonary fibrosis and stimulating its resolution.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation
Wrapp, D., Wang, N., Corbett, K. S., Goldsmith, J. A., Hsieh, C.-L., Abiona, O., Graham, B. S., & McLellan, J. S. (2020) · Science · doi:10.1126/science.abb2507 · Cited by 8,897
Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy
Onder, G., Rezza, G., & Brusaferro, S. (2020) · JAMA · doi:10.1001/jama.2020.4683 · Cited by 4,171
In search of the elusive lipofibroblast in human lungs
Ahlbrecht, K., & McGowan, S. E. (2014) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00230.2014 · Cited by 37
Cited by
Popkin, B. M., Du, S., Green, W. D., Beck, M. A., Algaith, T., Herbst, C. H., Alsukait, R. F., Alluhidan, M., Alazemi, N., & Shekar, M. (2020) · Obesity Reviews · doi:10.1111/obr.13128 · Cited by 1,150
Beyerstedt, S., Casaro, E. B., & Rangel, É. B. (2021) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-020-04138-6 · Cited by 897
Obesity and diabetes as high‐risk factors for severe coronavirus disease 2019 (Covid‐19)
Zhou, Y., Chi, J., Lv, W., & Wang, Y. (2021) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.3377 · Cited by 490
Singh, R., Rathore, S. S., Khan, H., Karale, S., Chawla, Y., Iqbal, K., Bhurwal, A., Tekin, A., Jain, N., Mehra, I., et al. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.780872 · Cited by 193
The association between obesity and peak antibody titer response in COVID‐19 infection
Soffer, S., Glicksberg, B. S., Zimlichman, E., Efros, O., Levin, M. A., Freeman, R., Reich, D. L., & Klang, E. (2021) · Obesity · doi:10.1002/oby.23208 · Cited by 48
Metadata
- Authors
- Kruglikov, I. L., & Scherer, P. E.
- Venue
- Obesity
- Publisher
- Wiley
- Published
- 2020-06-10
- Volume
- 28
- Issue
- 7
- Pages
- 1187-1190
- ISSN
- 1930-7381 (ISSN-L)
- 1930-739X
- OpenAlex
- W3019088671
- Cited by
- 252
- References
- 3
- FWCI
- 6.52
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.