Tuberculosis (TB) remains a major global health challenge, particularly in the context of multidrug-resistant (MDR) Mycobacterium tuberculosis (Mtb). Host-directed therapies (HDTs) have been proposed as adjunctive therapy to enhance immune control of infection. Recently, one such HDT, pharmacologic modulation of myeloid-derived suppressor cells (MDSCs), has been proposed to treat MDR-TB. While MDSCs have been well characterized in cancer, their role in TB pathogenesis remains unclear. To investigate whether MDSCs or other myeloid suppressor populations contribute to TB granuloma microenvironments (GME), we performed spatial transcriptional profiling and single-cell immunophenotyping on eighty-four granulomas in lung specimens from three individuals with active disease. Granulomas were histologically classified based on H&E staining, and transcriptional signatures were compared across regions of interest (ROIs) at different states of granuloma maturation. Our analysis revealed that immune suppression within granuloma was not primarily driven by classical MDSCs but rather by multiple myeloid cell subsets, including dendritic cells expressing indoleamine 2,3 dioxygenase-1 expressing (IDO1+ DCs). IDO1+ DCs were the most frequently observed suppressive myeloid cells, particularly in cellular regions, and their spatial proximity to activated T cells suggested localized immunosuppression. Importantly, granulomas at different stages contained distinct proportions of suppressor myeloid cells, with necrotic and cellular regions showing different myeloid phenotypes that may influence granuloma progression. Gene set enrichment analysis (GSEA) further indicated that elevated IDO1 expression was associated with a complex immune response that balanced suppressive signaling, immune activation, and cellular metabolism. These findings suggest that classical MDSCs, as defined in tumor microenvironments, likely play a minor role in TB, whereas IDO1+ DCs may be key regulators of immune suppression in granulomas influencing local Mtb control in infected lung. A deeper understanding of the role of IDO1+ suppressive myeloid cells in TB granulomas is essential to assessing their potential as therapeutic targets in TB treatment.

Single-cell technologies have enhanced our knowledge of molecular and cellular heterogeneity underlying disease. As the scale of single-cell datasets expands, linking cell-level phenotypic alterations with clinical outcomes becomes increasingly challenging. To address this, we introduce CellPhenoX, an eXplainable machine learning method to identify cell-specific phenotypes that influence clinical outcomes. CellPhenoX integrates classification models, explainable AI techniques, and a statistical framework to generate interpretable, cell-specific scores that uncover cell populations associated with relevant clinical phenotypes and interaction effects. We demonstrated the performance of CellPhenoX across diverse single-cell designs, including simulations, binary disease-control comparisons, and multi-class studies. Notably, CellPhenoX identified an activated monocyte phenotype in COVID-19, with expansion correlated with disease severity after adjusting for covariates and interactive effects. It also uncovered an inflammation-associated gradient in fibroblasts from ulcerative colitis. We anticipate that CellPhenoX holds the potential to detect clinically relevant phenotypic changes in single-cell data with multiple sources of variation, paving the way for translating single-cell findings into clinical impact.

Background  The new severe acute respiratory syndromecoronavirus 2 (SARS-CoV-2) causes severe acute respiratory illness accountable for causing the coronavirus disease 2019 (COVID-19) illness. Thrombotic issues, acute respiratory distress syndrome (ARDS), and cytokine storm are significant contributors to morbidity and mortality in patients with COVID-19. Elevated D-dimer levels and prothrombin times are further indicators of abnormal coagulation parameters in COVID-19 patients. This study aimed to study the platelet indices as prognostic markers in COVID-19 infection. Methods In this prospective observational study, 150 real-time reverse transcription-polymerase chain reaction (RT-PCR)-positive COVID-19 patients were enrolled between October 2020 and September 2021. All the subjects were screened and explained the study procedure in their native language. Following enrolment, a detailed history and physical examination were performed. Subsequently, laboratory investigations were performed, and patients were subjected to high-resolution computed tomography (HRCT) examination to classify patients into mild, moderate, and severe according to the severity of the illness. The platelet indices taken into account were plateletcrit (PCT) in percentage, platelet count (PLT) in lakh per microlitre, mean platelet volume (MPV) in femtolitres, and platelet distribution width (PDW) in femtolitres. Results The mean PLT was significantly greater among survivors than non-survivors (2.03 ± 0.72 versus 1.76 ± 0.47; p-value = 0.018). The mean MPV (10.42 ± 0.53 versus 9.22 ± 0.64; p-value <0.0001) and PDW (17.99 ± 1.53 versus 16.54 ± 0.91 fl; p-value <0.0001) were significantly greater among non-survivors than survivors. However, the mean PCT was significantly greater among survivors than non-survivors (0.22 ± 0.03% versus 0.18 ± 0.33%; p-value <0.0001). At a cut-off of 0.213, the sensitivity and specificity of PCT in predicting death were found to be 79.2% and 74.5%, respectively. At a cut-off of 16.75, the sensitivity and specificity of PDW in predicting death were found to be 68.8% and 59.8%, respectively. The findings demonstrated a relationship between elevated MPV and PDW and mortality and severe COVID-19 infection. Increased PCT was connected to higher survival, with a specificity and sensitivity of 87.5% and 75.5%, respectively, and MPV >9.75 may predict death. PDW >16.75 exhibited a specificity and sensitivity of 68.8% and 59.8%, respectively, in predicting death. With comparable sensitivity and specificity of 79.2% and 74.5%, PCT >0.213 may predict death. Conclusion In severely sick COVID-19 patients, platelet indices should be routinely calculated and can be utilized as simple, low-cost prognostic indicators.

The coronavirus 2019 (COVID-19) pandemic was caused by a positive sense single-stranded RNA (ssRNA) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, other human coronaviruses (hCoVs) exist. Historical pandemics include smallpox and influenza, with efficacious therapeutics utilized to reduce overall disease burden through effectively targeting a competent host immune system response. The immune system is composed of primary/secondary lymphoid structures with initially eight types of immune cell types, and many other subtypes, traversing cell membranes utilizing cell signaling cascades that contribute towards clearance of pathogenic proteins. Other proteins discussed include cluster of differentiation (CD) markers, major histocompatibility complexes (MHC), pleiotropic interleukins (IL), and chemokines (CXC). The historical concepts of host immunity are the innate and adaptive immune systems. The adaptive immune system is represented by T cells, B cells, and antibodies. The innate immune system is represented by macrophages, neutrophils, dendritic cells, and the complement system. Other viruses can affect and regulate cell cycle progression for example, in cancers that include human papillomavirus (HPV: cervical carcinoma), Epstein-Barr virus (EBV: lymphoma), Hepatitis B and C (HB/HC: hepatocellular carcinoma) and human T cell Leukemia Virus-1 (T cell leukemia). Bacterial infections also increase the risk of developing cancer (e.g., Helicobacter pylori). Viral and bacterial factors can cause both morbidity and mortality alongside being transmitted within clinical and community settings through affecting a host immune response. Therefore, it is appropriate to contextualize advances in single cell sequencing in conjunction with other laboratory techniques allowing insights into immune cell characterization. These developments offer improved clarity and understanding that overlap with autoimmune conditions that could be affected by innate B cells (B1+ or marginal zone cells) or adaptive T cell responses to SARS-CoV-2 infection and other pathologies. Thus, this review starts with an introduction into host respiratory infection before examining invaluable cellular messenger proteins and then individual immune cell markers.

The literature presents several reports of the impact of glycemic control and diabetes in the inflammatory and coagulatory response during coronavirus disease 2019 (COVID-19). Nevertheless, the long-term impact of the COVID-19 in diabetic patients is still to be explored. Therefore, we recruited 128 patients and performed a longitudinal analysis on COVID-19-associated biomarkers of patients with COVID-19, tree and 6 months after COVID-19 recovery and put into perspective the possible long-term complication generated after COVID-19. In our investigation, we failed to verify any long-term modification on inflammatory biomarkers, but detected an increase in the glycemia and glycated hemoglobin in patients without any pre-existing history or diagnosis of diabetes (non-diabetic patients). Although diabetic and non-diabetic patients presented elevated levels of glycated hemoglobin, the c-peptide test indicated a normal beta cell function in all patients.

The expansion of myeloid-derived suppressor cells (MDSCs), known as heterogeneous population of immature myeloid cells, is enhanced during several pathological conditions such as inflammatory or viral respiratory infections. It seems that the way MDSCs behave in infection depends on the type and the virulence mechanisms of the invader pathogen, the disease stage, and the infection-related pathology. Increasing evidence showing that in correlation with the severity of the disease, MDSCs are accumulated in COVID-19 patients, in particular in those at severe stages of the disease or ICU patients, contributing to pathogenesis of SARS-CoV2 infection. Based on the involved subsets, MDSCs delay the clearance of the virus through inhibiting T-cell proliferation and responses by employing various mechanisms such as inducing the secretion of anti-inflammatory cytokines, inducible nitric oxide synthase (iNOS)-mediated hampering of IFN-γ production, or forcing arginine shortage. While the immunosuppressive characteristic of MDSCs may help to preserve the tissue homeostasis and prevent hyperinflammation at early stages of the infection, hampering of efficient immune responses proved to exert significant pathogenic effects on severe forms of COVID-19, suggesting the targeting of MDSCs as a potential intervention to reactivate T-cell immunity and thereby prevent the infection from developing into severe stages of the disease. This review tried to compile evidence on the roles of different subsets of MDSCs during viral respiratory infections, which is far from being totally understood, and introduce the promising potential of MDSCs for developing novel diagnostic and therapeutic approaches, especially against COVID-19 disease.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can generate a systemic disease named coronavirus disease-2019 (COVID-19). Currently, the COVID-19 pandemic has killed millions worldwide, presenting huge health and economic challenges worldwide. Several risk factors, such as age, co-infections, metabolic syndrome, and smoking have been associated with poor disease progression and outcomes. Alcohol drinking is a common social practice among adults, but frequent and/or excessive consumption can mitigate the anti-viral and anti-bacterial immune responses. Therefore, we investigated if patients with self-reported daily alcohol consumption (DAC) presented alteration in the immune response to SARS-CoV-2. We investigated 122 patients with COVID-19 (101 male and 46 females), in which 23 were patients with DAC (18 men and 5 women) and 99 were non-DAC patients (58 men and 41 women), without other infections, neoplasia, or immunodeficiencies. Although with no difference in age, patients with DAC presented an increase in severity-associated COVID-19 markers such as C-reactive protein (CRP), neutrophil count, and neutrophil-to-lymphocyte ratio. In addition, patients with DAC presented a reduction in the lymphocytes and monocytes counts. Importantly, the DAC group presented an increase in death rate in comparison with the non-DAC group. Our results demonstrated that, in our cohort, DAC enhanced COVID-19-associated inflammation, and increased the number of deaths due to COVID-19.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can progress to a severe respiratory and systemic disease named coronavirus disease-2019 (COVID-19). The most common symptoms are fever and respiratory discomfort. Nevertheless, gastrointestinal infections have been reported, with symptoms such as diarrhea, nausea, vomiting, abdominal pain, and lack of appetite. Importantly, SARS-CoV-2 can remain positive in fecal samples after nasopharyngeal clearance. After gastrointestinal SARS-CoV-2 infection and other viral gastrointestinal infections, some patients may develop alterations in the gastrointestinal microbiota. In addition, some COVID-19 patients may receive antibiotics, which may also disturb gastrointestinal homeostasis. In summary, the gastrointestinal system, gut microbiome, and gut-lung axis may represent an important role in the development, severity, and treatment of COVID-19. Therefore, in this review, we explore the current pieces of evidence of COVID-19 gastrointestinal manifestations, possible implications, and interventions.

The severe respiratory and systemic disease named coronavirus disease-2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, the COVID-19 pandemic presents a huge social and health challenge worldwide. Many different risk factors are associated with disease severity, such as systemic arterial hypertension, diabetes mellitus, obesity, older age, and other co-infections. Other respiratory diseases such as chronic obstructive pulmonary disease (COPD) and smoking are common comorbidities worldwide. Previous investigations have identified among COVID-19 patients smokers and COPD patients, but recent investigations have questioned the higher risk among these populations. Nevertheless, previous reports failed to isolate smokers and COPD patients without other comorbidities. We performed a longitudinal evaluation of the disease course of smokers, former smokers, and COPD patients with COVID-19 without other comorbidities, from hospitalization to hospital discharge. Although no difference between groups was observed during hospital admission, smokers and COPD patients presented an increase in COVID-19-associated inflammatory markers during the disease course in comparison to non-smokers and former smokers. Our results demonstrated that smoking and COPD are risk factors for severe COVID-19 with possible implications for the ongoing pandemic.