Adipose tissue derived stem cells (ADSCs) are mesenchymal stem cells identified within subcutaneous tissue at the base of the hair follicle (dermal papilla cells), in the dermal sheets (dermal sheet cells), in interfollicular dermis, and in the hypodermis tissue. These cells are expected to play a major role in regulating skin regeneration and aging-associated morphologic disgraces and structural deficits. ADSCs are known to proliferate and differentiate into skin cells to repair damaged or dead cells, but also act by an autocrine and paracrine pathway to activate cell regeneration and the healing process. During wound healing, ADSCs have a great ability in migration to be recruited rapidly into wounded sites added to their differentiation towards dermal fibroblasts (DF), endothelial cells, and keratinocytes. Additionally, ADSCs and DFs are the major sources of the extracellular matrix (ECM) proteins involved in maintaining skin structure and function. Their interactions with skin cells are involved in regulating skin homeostasis and during healing. The evidence suggests that their secretomes ensure: (i) The change in macrophages inflammatory phenotype implicated in the inflammatory phase, (ii) the formation of new blood vessels, thus promoting angiogenesis by increasing endothelial cell differentiation and cell migration, and (iii) the formation of granulation tissues, skin cells, and ECM production, whereby proliferation and remodeling phases occur. These characteristics would be beneficial to therapeutic strategies in wound healing and skin aging and have driven more insights in many clinical investigations. Additionally, it was recently presented as the tool key in the new free-cell therapy in regenerative medicine. Nevertheless, ADSCs fulfill the general accepted criteria for cell-based therapies, but still need further investigations into their efficiency, taking into consideration the host-environment and patient-associated factors.
The nonclassic clinical presentation of celiac disease (CD) becomes increasingly common in physician's daily practice, which requires an awareness of its many clinical faces with atypical, silent, and latent forms. Besides the common genetic background (HLA DQ2/DQ8) of the disease, other non-HLA genes are now notably reported with a probable association to atypical forms. The availability of high-sensitive and specific serologic tests such as antitissue transglutuminase, antiendomysium, and more recent antideamidated, gliadin peptide antibodies permits to efficiently uncover a large portion of the submerged CD iceberg, including individuals having conditions associated with a high risk of developing CD (type 1 diabetes, autoimmune diseases, Down syndrome, family history of CD, etc.), biologic abnormalities (iron deficiency anemia, abnormal transaminase levels, etc.), and extraintestinal symptoms (short stature, neuropsychiatric disorders, alopecia, dental enamel hypoplasia, recurrent aphtous stomatitis, etc.). Despite the therapeutic alternatives currently in developing, the strict adherence to a GFD remains the only effective and safe therapy for CD.
We read with interest the recent article by Terpos et al. 1 They reviewed different hematologic findings and complications of COVID-19. Especially, we are interested in lymphopenia in severe COVID-19 patients, which is a predictor factor of severity and mortality. We aimed to report the occurrence of lymphopenia, lymphocyte subsets, and its impact on ICU mortality in critically ill patients with COVID-19. In this single-center cohort, we included adult patients with confirmed COVID-19 infection by a positive reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of a nasopharyngeal swab, admitted in the intensive care unit (ICU) of the Mohammed VIth university hospital of the Marrakech region (Morocco), from March 19, 2020 to May 15, 2020. We collected demographic data, comorbidities, clinical signs at the ICU admission, laboratory findings, chest CT scan if available, outcomes, time from onset of the first symptom to ICU admission, and sequential organ failure assessment (SOFA) scores. We expressed continuous variables as medians and interquartile (IQR) ranges or means (standard deviations (SD)), as appropriate, and compared using independent group Student's t test or the Mann-Whitney U test. Categorical variables were described using percentages and compared using the χ 2-test, although Fisher's exact test was used when the data were sparse. We performed univariable to evaluate the risk factors of mortality. The analysis was processed by spss 10.0 for Windows (SPSS, Chicago, IL, USA). A Pvalue of <.05 was considered statistically significant. Patients CD3+ CD4+ CD8+ CD4+/ CD8+ B cells NK cells Outcome
Real-time genome monitoring of the SARS-CoV-2 pandemic outbreak is of utmost importance for designing diagnostic tools, guiding antiviral treatment and vaccination strategies. In this study, we present an accurate method for temporal and geographical comparison of mutational events based on GISAID database genome sequencing. Among 42523 SARS-CoV-2 genomes analyzed, we found 23202 variants compared to the reference genome. The Ti/Tv (transition/transversion) ratio was used to filter out possible false-positive errors. Transition mutations generally occurred more frequently than transversions. Our clustering analysis revealed remarkable hotspot mutation patterns for SARS-CoV-2. Mutations were clustered based on how their frequencies changed over time according to each geographical location. We observed some clusters showing a clear variation in mutation frequency and continuously evolving in the world. However, many mutations appeared in specific periods without a clear pattern over time. Various important nonsynonymous mutations were observed, mainly in Oceania and Asia. More than half of these mutations were observed only once. Four hotspot mutations were found in all geographical locations at least once: T265I (NSP2), P314L (NSP12), D614G (S), and Q57H (ORF3a). The current analysis of SARS-CoV-2 genomes provides valuable information on the geographical and temporal mutational evolution of SARS-CoV-2.
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