The immune system protects against viruses and diseases and produces antibodies to kill pathogens. This review presents a brief overview of the immune system regarding its protection of the human body from COVID-19; illustrates the process of the immune system, how it works, and its mechanism to fight virus; and presents information on the most recent COVID-19 treatments and experimental data. Various types of potential challenges for the immunes system are also discussed. At the end of the article, foods to consume and avoid are suggested, and physical exercise is encouraged. This article can be used worldwide as a state of the art in this critical moment for promising alternative solutions related to surviving the coronavirus.

Raw milk contains wide microbial diversity, composed mainly of lactic acid bacteria (LAB), which are used as probiotics in both human and animal husbandry. We isolated, characterized, and evaluated LAB from indigenous Bangladeshi raw milk to assess probiotic potential, including antagonistic activity (against Escherichia coli O157: H7, Enterococcus faecalis, Salmonella Typhimurium, Salmonella Enteritidis, and Listeria monocytogenes), survivability in simulated gastric juice, tolerance to phenol and bile salts, adhesion to ileum epithelial cells, auto-and co-aggregation, hydrophobicity, α-glucosidase inhibitory activity, and antibiotic susceptibility tests. The 4 most promising LAB strains showed probiotic potential and were identified as Lactobacillus casei, Lactobacillus plantarum (which produced plantaricin EF), Lactobacillus fermentum, and Lactobacillus paracasei. These strains inhibited all pathogens tested at various degrees, and competitively excluded pathogens with viable counts of 3.0 to 6.0 log cfu/mL. Bacteriocin, organic acids, and low-molecular-weight substances were mainly responsible for antimicrobial activity by the LAB strains. All 4 LAB strains were resistant to oxacillin and 3 were resistant to vancomycin and streptomycin, with multiple antibiotic resistance indices >0.2. After further in vivo evaluation, these LAB strains could be considered probiotic candidates with application in the food industry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.

Despite success in tuberculosis control, multi-drug resistant tuberculosis in Bangladesh is increasing and currently multi-drug-resistant tuberculosis rate is 3.6% in new cases and 19% in re-treatment cases. This study focused on determination of multi-drug-resistant tuberculosis which is warranted for effective prevention strategy. An unmatched case control study was conducted in 2010. Purposively recruited 136 culture-proved multi-drug-resistant- tuberculosis cases and 152 cured tuberculosis patients were interviewed. Associations between exposure and outcome variables were initially tested by chi2-test, t-test. A result was considered significant at p value < 0.05. Effects of exposure variables were also assessed after adjusting for other variables by binary logistic regression models. Crude and adjusted Odds Ratio with 95% Confidence Interval was computed. Younger age (p = 0.008) and, peri-urban locality (p = 0.002) were associated with multi-drug-resistant tuberculosis. History of contact (p < 0.001) and tuberculosis in the past (p < 0.001) were four and eight times, respectively, more likely to influence multi-drug-resistant tuberculosis. Regularity [Odds Ratio 0.05; 95% Confidence Interval (0.01 to 0.39)] and always observation of treatment [Odds Ratio 0.25; 95% Confidence Interval (0.10 to 0.61)], sputum conversion [Odds Ratio 0.02; 95% Confidence Interval (0.01 to 0.08)] negatively associated with multi-drug-resistant tuberculosis. Gender and socio-economic status did not show any influence. Treatment course and sputum conversion was the best predictors. Like other developing countries adequacy of treatment is the most important exposure variable. Strengthening of control activities might contribute in preventing development of resistance in tuberculosis patients.

Purpose – The purpose of this paper is to analyze the impact of individual logistics-related factors, namely, supplier involvement (SI), length of supplier relationship (LSR), use of information technology (IT), and logistics integration (LI) on a firm's supply chain performance (SCP) and test for the mediating effect of LI in a multi-country survey conducted in Brazil, Korea and India. The paper also develops a composite variable, supply chain competency (SCC), as an overall measure of the quality of a firm's supply chain and demonstrate its effect on a firm's SCP. Design/methodology/approach – The research methodology was based on designing and administering a survey instrument. Data collected from 187 organizations in Brazil, Korea and India were analyzed using the partial least squares structural equation modeling methodology. Findings – Results show that for the combined data, the direct effects of SI, LSR and IT on SCP are insignificant while LI has a very significant direct effect on SCP. On the other hand, except for SI, LSR and IT have significant effects on SCP through LI establishing the mediating role of LI. The paper also finds that SCC has a significant effect on SCP. Further, when countries are considered individually the paper finds that IT has a significant indirect effect on SCP in the case of all the countries while LSR has a significant indirect effect on SCP, both in the case of Brazil and Korea. Additionally, in the case of Korea SI has a significant indirect effect on SCP. Research limitations/implications – Like other survey-based research, the findings of this paper are also limited by the sample size. Especially, the observations specific to individual countries are as good as the respective sample sizes. Also, since all the respondents belonged to manufacturing firms, the findings of this paper are relevant for the manufacturing sector. Practical implications – This paper establishes the mediating effect of LI in assessing the impact of logistics-related factors on a firm's SCP. It confirms that although logistics-related factors are necessary for a firm's superior SCP, they are not sufficient unless their interactions are taken into consideration, as evidenced by the significant positive relationship between SCC and SCP. Originality/value – To the best of the authors’ knowledge, this paper is the first paper to study the effect of logistics-related factors on a firm's SCP and establish the mediating role of LI in a multi-country setting. This paper also develops a composite variable SCC and examines its effect on SCP.