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Paratuberculosis (PTB) is a chronic granulomatous enteritis caused by Mycobacterium avium subsp. paratuberculosis (Map). Vaccination is one of the most cost-effective tools for PTB control, although alternative treatments like the probiotic Dietzia have been explored with promising results. Using a rabbit model, we investigated the association of immunological and microbiota profiles in Gut Associated Lymphoid Tissue (GALT) with the effects in protection induced by the administration of Dietzia spp., the commercial vaccine (Silirum ® ) and the combination of both. The treatment with the probiotic diminished inflammation, but failed to control Map burden, suggesting a detrimental effect. Rabbits treated with the probiotic presented the highest rates of tissue lesion extension, although the immunological profile was not suggestive of an inflammatory state. Map load in both vaccinated groups was similar indicating that both treatments are equally effective in eliminating the infection, suggesting the role of vaccination in eliminating the infection prevails over the immunomodulatory effects of the probiotic. There were slight variations in the presence of some taxonomic groups depending on the treatment, highlighting the complexity of microbial interactions and the need to optimise treatment combinations in the context of each disease and animal species.

This work reports the preparation of two polymorphs of MnO 2 such as α -MnO 2 and β -MnO 2 by simple microwave method using natural Moringa oleifera gum. The concentration of M. oleifera gum solution influences the formation of α -MnO 2 and β -MnO 2 , and the structural formation of the metal oxides was confirmed by powder X-ray diffraction analysis. According to the surface analysis of the prepared materials studied through scanning electron microscopy and transmission electron microscopy, nanocacti α -MnO 2 and rice husk shaped β -MnO 2 nanorod morphology were observed. The fabricated α -MnO 2 and β -MnO 2 electrode materials on Ni foam showed good electrochemical behaviours in the cyclic voltammogram using a three-electrode system and exhibited a specific capacitance of 150 Fg −1 and 92.8 Fg −1 at a current density of 0.5 Ag −1 in the galvanic charge–discharge studies, respectively. Furthermore, cycling stability study of the α -MnO 2 material showed capacitance retention of 95.4% at a current density of 6 Ag −1 after 2000 galvanostatic charge–discharge cycles.

On 11 March 2020, the World Health Organization announced the Corona Virus Disease-2019 (COVID-19) as a global pandemic, which originated in China. At the host level, COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), affects the respiratory system, with the clinical symptoms ranging from mild to severe or critical illness that often requires hospitalization and oxygen support. There is no specific therapy for COVID-19, as is the case for any common viral disease except drugs to reduce the viral load and alleviate the inflammatory symptoms. Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (Mtb), also primarily affects the lungs and has clinical signs similar to pulmonary SARS-CoV-2 infection. Active TB is a leading killer among infectious diseases and adds to the burden of the COVID-19 pandemic worldwide. In immunocompetent individuals, primary Mtb infection can also lead to a non-progressive, asymptomatic latency. However, latent Mtb infection (LTBI) can reactivate symptomatic TB disease upon host immune-suppressing conditions. Importantly, the diagnosis and treatment of TB are hampered and admixed with COVID-19 control measures. The US-Center for Disease Control (US-CDC) recommends using antiviral drugs, Remdesivir or corticosteroid (CST), such as dexamethasone either alone or in-combination with specific recommendations for COVID-19 patients requiring hospitalization or oxygen support. However, CSTs can cause immunosuppression, besides their anti-inflammatory properties. The altered host immunity during COVID-19, combined with CST therapy, poses a significant risk for new secondary infections and/or reactivation of existing quiescent infections, such as LTBI. This review highlights CST therapy recommendations for COVID-19, various types and mechanisms of action of CSTs, the deadly combination of two respiratory infectious diseases COVID-19 and TB. It also discusses the importance of screening for LTBI to prevent TB reactivation during corticosteroid therapy for COVID-19.

Pulmonary diseases due to mycobacteria cause significant morbidity and mortality to human health. In addition to tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), recent epidemiological studies have shown the emergence of non-tuberculous mycobacteria (NTM) species in causing lung diseases in humans. Although more than 170 NTM species are present in various environmental niches, only a handful, primarily Mycobacterium avium complex and M. abscessus , have been implicated in pulmonary disease. While TB is transmitted through inhalation of aerosol droplets containing Mtb, generated by patients with symptomatic disease, NTM disease is mostly disseminated through aerosols originated from the environment. However, following inhalation, both Mtb and NTM are phagocytosed by alveolar macrophages in the lungs. Subsequently, various immune cells are recruited from the circulation to the site of infection, which leads to granuloma formation. Although the pathophysiology of TB and NTM diseases share several fundamental cellular and molecular events, the host-susceptibility to Mtb and NTM infections are different. Striking differences also exist in the disease presentation between TB and NTM cases. While NTM disease is primarily associated with bronchiectasis, this condition is rarely a predisposing factor for TB. Similarly, in Human Immunodeficiency Virus (HIV)-infected individuals, NTM disease presents as disseminated, extrapulmonary form rather than as a miliary, pulmonary disease, which is seen in Mtb infection. The diagnostic modalities for TB, including molecular diagnosis and drug-susceptibility testing (DST), are more advanced and possess a higher rate of sensitivity and specificity, compared to the tools available for NTM infections. In general, drug-sensitive TB is effectively treated with a standard multi-drug regimen containing well-defined first- and second-line antibiotics. However, the treatment of drug-resistant TB requires the additional, newer class of antibiotics in combination with or without the first and second-line drugs. In contrast, the NTM species display significant heterogeneity in their susceptibility to standard anti-TB drugs. Thus, the treatment for NTM diseases usually involves the use of macrolides and injectable aminoglycosides. Although well-established international guidelines are available, treatment of NTM disease is mostly empirical and not entirely successful. In general, the treatment duration is much longer for NTM diseases, compared to TB, and resection surgery of affected organ(s) is part of treatment for patients with NTM diseases that do not respond to the antibiotics treatment. Here, we discuss the epidemiology, diagnosis, and treatment modalities available for TB and NTM diseases of humans.

Conventionally, immunity in humans has been classified as innate and adaptive, with the concept that only the latter type has an immunological memory/recall response against specific antigens or pathogens. Recently, a new concept of trained immunity (a.k.a. innate memory response) has emerged. According to this concept, innate immune cells can exhibit enhanced responsiveness to subsequent challenges, after initial stimulation with antigen/pathogen. Thus, trained immunity enables the innate immune cells to respond robustly and non-specifically through exposure or re-exposure to antigens/infections or vaccines, providing enhanced resistance to unrelated pathogens or reduced infection severity. For example, individuals vaccinated with BCG to protect against tuberculosis were also protected from malaria and SARS-CoV-2 infections. Epigenetic modifications such as histone acetylation and metabolic reprogramming (e.g. shift towards glycolysis) and their inter-linked regulations are the key factors underpinning the immune activation of trained cells. The integrated metabolic and epigenetic rewiring generates sufficient metabolic intermediates, which is crucial to meet the energy demand required to produce proinflammatory and antimicrobial responses by the trained cells. These factors also determine the efficacy and durability of trained immunity. Importantly, the signaling pathways and regulatory molecules of trained immunity can be harnessed as potential targets for developing novel intervention strategies, such as better vaccines and immunotherapies against infectious (e.g., sepsis) and non-infectious (e.g., cancer) diseases. However, aberrant inflammation caused by inappropriate onset of trained immunity can lead to severe autoimmune pathological consequences, (e.g., systemic sclerosis and granulomatosis). In this review, we provide an overview of conventional innate and adaptive immunity and summarize various mechanistic factors associated with the onset and regulation of trained immunity, focusing on immunologic, metabolic, and epigenetic changes in myeloid cells. This review underscores the transformative potential of trained immunity in immunology, paving the way for developing novel therapeutic strategies for various infectious and non-infectious diseases that leverage innate immune memory.

Diabetes is a chronic disorder that disrupts the body’s ability to regulate blood glucose (BG) levels, leading to dangerous fluctuations such as hypoglycemia and hyperglycemia. In managing Type 1 Diabetes (T1D), the Dual Hormone Artificial Pancreas (DHAP) has emerged as a promising solution for maintaining optimal BG levels by administering both insulin and glucagon. However, the major challenges in DHAPs are slow dynamics in glucose sensing and delayed insulin absorption. In this paper, a Smart Dual Hormone Artificial Pancreas (SDHAP) with Event-triggered Feed-Back (FB)-Feed Forward (FF) control schemes are proposed to control the BG level of diabetic individuals and reject external disturbance due to food intake or exercise. Firstly, the classification of blood glucose level was performed with features extracted from the T1DiabetesGranada dataset using Machine Learning (ML) algorithms like K-Nearest Neighbor (KNN) and Support Vector Machine (SVM), and BG levels were predicted using time-series analysis. Secondly, the Event -Triggered Proportional-Integral feedback controllers: Proportional Integral (PI) and Model Predictive Control are designed based on the Bergman Minimal Model (BMM) model to deliver appropriate hormones namely insulin/glucagon based on predicted results. Finally, the FF controller was designed to reject external disturbances under hypoglycemia and hyperglycemia conditions. The results show the proposed SDHAP is more effective in controlling blood glucose by delivering patient-specific drugs with appropriate dosages based on individualized pathological conditions of T1D patients.