Correlation of Myeloid-Derived Suppressor Cell Expansion with Upregulated Transposable Elements in Severe COVID-19 Unveiled in Single-Cell RNA Sequencing Reanalysis.

Some studies have investigated the potential role of transposable elements (TEs) in COVID-19 pathogenesis and complications. However, to the best of our knowledge, there is no study to examine the possible association of TE expression in cell functions and its potential role in COVID-19 immune response at the single-cell level. In this study, we reanalyzed single-cell RNA seq data of bronchoalveolar lavage (BAL) samples obtained from six severe COVID-19 patients and three healthy donors to assess the probable correlation of TE expression with the immune responses induced by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in COVID-19 patients. Our findings indicate that the expansion of myeloid-derived suppressor cells (MDSCs) may be a characteristic feature of COVID-19. Additionally, a significant increase in TE expression in MDSCs was observed. This upregulation of TEs in COVID-19 may be linked to the adaptability of these cells in response to their microenvironments. Furthermore, it appears that the identification of overexpressed TEs by pattern recognition receptors (PRRs) in MDSCs may enhance the suppressive capacity of these cells. Thus, this study emphasizes the crucial role of TEs in the functionality of MDSCs during COVID-19.

Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods.

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients' characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods.

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O 2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

A systems pharmacology approach to identify the autophagy-inducing effects of Traditional Persian medicinal plants.

Aging is correlated with several complex diseases, including type 2 diabetes, neurodegeneration diseases, and cancer. Identifying the nature of this correlation and treatment of age-related diseases has been a major subject of both modern and traditional medicine. Traditional Persian Medicine (TPM) embodies many prescriptions for the treatment of ARDs. Given that autophagy plays a critical role in antiaging processes, the present study aimed to examine whether the documented effect of plants used in TPM might be relevant to the induction of autophagy? To this end, the TPM-based medicinal herbs used in the treatment of the ARDs were identified from modern and traditional references. The known phytochemicals of these plants were then examined against literature for evidence of having autophagy inducing effects. As a result, several plants were identified to have multiple active ingredients, which indeed regulate the autophagy or its upstream pathways. In addition, gene set enrichment analysis of the identified targets confirmed the collective contribution of the identified targets in autophagy regulating processes. Also, the protein-protein interaction (PPI) network of the targets was reconstructed. Network centrality analysis of the PPI network identified mTOR as the key network hub. Given the well-documented role of mTOR in inhibiting autophagy, our results hence support the hypothesis that the antiaging mechanism of TPM-based medicines might involve autophagy induction. Chemoinformatics study of the phytochemicals using docking and molecular dynamics simulation identified, among other compounds, the cyclo-trijuglone of Juglans regia L. as a potential ATP-competitive inhibitor of mTOR. Our results hence, provide a basis for the study of TPM-based prescriptions using modern tools in the quest for developing synergistic therapies for ARDs.

Harnessing the non-specific immunogenic effects of available vaccines to combat COVID-19.

No proven remedy is identified for COVID-19 yet. SARS-CoV-2, the viral agent, is recognized by some endosomal and cytosolic receptors following cell entry, entailing innate and adaptive immunity stimulation, notably through interferon induction. Impairment in immunity activation in some patients, mostly elderlies, leads to high mortalities; thus, promoting immune responses may help. BCG vaccine is under investigation to prevent COVID-19 due to its non-specific effects on the immune system. However, other complementary immune-induction methods at early stages of the disease may be needed. Here, the potentially preventive immunologic effects of BCG and influenza vaccination are compared with the immune response defects caused by aging and COVID-19. BCG co-administration with interferon-α/-ß, or influenza vaccine is suggested to overcome its shortcomings in interferon signaling against COVID-19. However, further studies are highly recommended to assess the outcomes of such interventions considering their probable adverse effects especially augmented innate immune responses and overproduction of proinflammatory mediators.

AICAR and nicotinamide treatment synergistically augment the proliferation and attenuate senescence-associated changes in mesenchymal stromal cells.

BACKGROUND: Mesenchymal stromal cell (MSC) stemness capacity diminishes over prolonged in vitro culture, which negatively affects their application in regenerative medicine. To slow down the senescence of MSCs, here, we have evaluated the in vitro effects of 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR), an AMPK activator, and nicotinamide (NAM), an activator of sirtuin1 (SIRT1). METHODS: Human adipose-derived MSCs were cultured to passage (P) 5. Subsequently, the cells were grown in either normal medium alone (control group), the medium supplemented with AICAR (1 mM) and NAM (5 mM), or in the presence of both for 5 weeks to P10. Cell proliferation, differentiation capacity, level of apoptosis and autophagy, morphological changes, total cellular reactive oxygen species (ROS), and activity of mTORC1 and AMPK were compared among different treatment groups. RESULTS: MSCs treated with AICAR, NAM, or both displayed an increase in proliferation and osteogenic differentiation, which was augmented in the group receiving both. Treatment with AICAR or NAM led to decreased expression of ß-galactosidase, reduced accumulation of dysfunctional lysosomes, and characteristic morphologic features of young MSCs. Furthermore, while NAM administration could significantly reduce the total cellular ROS in aged MSCs, AICAR treatment did not. Moreover, AICAR-treated cells possess a high proliferation capacity; however, they also show the highest level of cellular apoptosis. The observed effects of AICAR and NAM were in light of the attenuated mTORC1 activity and increased AMPK activity and autophagy. CONCLUSIONS: Selective inhibition of mTORC1 by AICAR and NAM boosts autophagy, retains MSCs' self-renewal and multi-lineage differentiation capacity, and postpones senescence-associated changes after prolonged in vitro culture. Additionally, co-administration of AICAR and NAM shows an additive or probably a synergistic effect on cellular senescence.

A Systems Biology Roadmap to Decode mTOR Control System in Cancer.

Mechanistic target of rapamycin (mTOR) is a critical protein in the regulation of cell fate decision making, especially in cancer cells. mTOR acts as a signal integrator and is one of the main elements of interactions among the pivotal cellular processes such as cell death, autophagy, metabolic reprogramming, cell growth, and cell cycle. The temporal control of these processes is essential for the cellular homeostasis and dysregulation of mTOR signaling pathway results in different phenotypes, including aging, oncogenesis, cell survival, cell growth, senescence, quiescence, and cell death. In this paper, we have proposed a systems biology roadmap to study mTOR control system, which introduces the theoretical and experimental modalities to decode temporal and dynamical characteristics of mTOR signaling in cancer.

Aging: A cell source limiting factor in tissue engineering.

Tissue engineering has yet to reach its ideal goal, i.e. creating profitable off-the-shelf tissues and organs, designing scaffolds and three-dimensional tissue architectures that can maintain the blood supply, proper biomaterial selection, and identifying the most efficient cell source for use in cell therapy and tissue engineering. These are still the major challenges in this field. Regarding the identification of the most appropriate cell source, aging as a factor that affects both somatic and stem cells and limits their function and applications is a preventable and, at least to some extents, a reversible phenomenon. Here, we reviewed different stem cell types, namely embryonic stem cells, adult stem cells, induced pluripotent stem cells, and genetically modified stem cells, as well as their sources, i.e. autologous, allogeneic, and xenogeneic sources. Afterward, we approached aging by discussing the functional decline of aged stem cells and different intrinsic and extrinsic factors that are involved in stem cell aging including replicative senescence and Hayflick limit, autophagy, epigenetic changes, miRNAs, mTOR and AMPK pathways, and the role of mitochondria in stem cell senescence. Finally, various interventions for rejuvenation and geroprotection of stem cells are discussed. These interventions can be applied in cell therapy and tissue engineering methods to conquer aging as a limiting factor, both in original cell source and in the in vitro proliferated cells.

Dynamic modeling of signal transduction by mTOR complexes in cancer.

Signal integration has a crucial role in the cell fate decision and dysregulation of the cellular signaling pathways is a primary characteristic of cancer. As a signal integrator, mTOR shows a complex dynamical behavior which determines the cell fate at different cellular processes levels, including cell cycle progression, cell survival, cell death, metabolic reprogramming, and aging. The dynamics of the complex responses to rapamycin in cancer cells have been attributed to its differential time-dependent inhibitory effects on mTORC1 and mTORC2, the two main complexes of mTOR. Two explanations were previously provided for this phenomenon: 1-Rapamycin does not inhibit mTORC2 directly, whereas it prevents mTORC2 formation by sequestering free mTOR protein (Le Chatelier's principle). 2-Components like Phosphatidic Acid (PA) further stabilize mTORC2 compared with mTORC1. To understand the mechanism by which rapamycin differentially inhibits the mTOR complexes in the cancer cells, we present a mathematical model of rapamycin mode of action based on the first explanation, i.e., Le Chatelier's principle. Translating the interactions among components of mTORC1 and mTORC2 into a mathematical model revealed the dynamics of rapamycin action in different doses and time-intervals of rapamycin treatment. This model shows that rapamycin has stronger effects on mTORC1 compared with mTORC2, simply due to its direct interaction with free mTOR and mTORC1, but not mTORC2, without the need to consider other components that might further stabilize mTORC2. Based on our results, even when mTORC2 is less stable compared with mTORC1, it can be less inhibited by rapamycin.

Concomitant use of mesenchymal stem cells and neural stem cells for treatment of spinal cord injury: A combo cell therapy approach.

TREATMENT: with neural stem cells (NSCs) provides a hope to recover the neural damage and compensate for the lost neural structures for restoration of interrupted neural communications above and below the site of injury. However, cell-based therapy approach suffers from many biological barriers and technical caveats which severely hamper the prognosis. The biochemically-rich microenvironment at the site of spinal cord injury (SCI), the continuing neuro-degenerative process and infiltrating immune cells offer a serious barrier to the donor cells. We hypothesized that mesenchymal stem cells (MSCs) concomitantly delivered with NSCs would significantly enhance the effectiveness of cell-based therapy for SCI. In a rodent model of SCI (n = 15 animals/group), MSCs labeled with PKH67 (green fluorescence dye) were delivered on day1 after SCI whereas the same animals were treated with NSCs during the subacute phase on day3 (group-5). In comparison with untreated control (group-1), sham group (without cell treatment; group-2), MSCs alone (group-3) and NSCs alone treated animals (group-4), the combined cell treated animals (group-5) showed significantly higher homing of cells at the site of injury during in vivo imaging. Caspase-3 activity was lower in group-5 (P < 0.05 vs all groups) with concomitant reduction in the pro-inflammatory cytokines IL-1ß and IL-6 (P < 0.05 vs all groups). All cell therapy groups showed significant improvement in neurological function as compared to group-2, however, it was highest in group-5 (P < 0.05 vs all groups). In conclusion, combined treatment with (NSCs + MSCs) enhances NSCs survival and functional recovery in SCI and is superior to the treatment with either of NSCs or MSCs alone.