Dr Mohammed Mahmoud Youssif

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AIM: We aimed to assess the populations of lymphocytes: NK cells, NKT cells and T cells, and the expression of the immunoregulatory receptor CD244 (2B4) by each population in rheumatoid arthritis (RA) patients with concomitant hepatitis C virus (HCV) infection.

METHODS: Lymphocyte phenotyping for NK cells (CD3-CD56+), NKT cells (CD3 + CD56+), and T cells (CD3 + CD56-) was analyzed by flow cytometry in patients with HCV positive RA (n = 21), HCV negative RA (n = 20) and controls (n = 11). Surface expression of CD244 by each lymphocyte population was quantified as mean fluorescence intensity and frequency of CD244 expressing cells.

RESULTS: Patients with and without concomitant HCV displayed comparable numbers of NK, NKT, and T cells to controls. We observed that the expression intensity of CD244 was downregulated by the lymphocyte populations in HCV positive and HCV negative RA compared to controls (NK CD244 p < 0.001, NKT CD244 p = 0.047, T CD244 p < 0.001). Yet, the downregulation was more profound in HCV positive RA, as CD244 expression by NK cells and T cells was decreased in HCV positive in relation to negative RA (p < 0.001 and p = 0.003, respectively). In addition, the frequency of CD244-expressing NK and NKT cells in HCV positive RA was lower compared to HCV negative RA and controls (p < 0.001 and p = 0.001, respectively). T cell CD244 expression was significant for discriminating clinically active from less active RA with and without HCV (n = 41), area under the curve = 0.717 (95% CI 0.560-0.873, p = 0.007).

CONCLUSION: Our findings reveal a distinct expression pattern of CD244 by lymphocytes of RA with HCV infection.

Liver fibrosis presents a unique diagnostic challenge in people coinfected with hepatitis C virus (HCV) and human immune deficiency virus (HIV). This study aimed to explore the association between CD4 discordance and liver fibrosis in that population, alongside assessing the predictive power of different models for significant fibrosis. A cross-sectional study was conducted on 198 adult people with HIV/HCV coinfection. Liver fibrosis was noninvasively assessed using transient elastography, and CD4 discordance was defined based on the discrepancy between absolute CD4 cell count and CD4 cell percentage. Multivariate logistic regression and receiver operating characteristic curves were used for analysis. Only 52 (26.3%) individuals had concordant CD4 values. The study found a significant correlation between high CD4 discordance and significant liver fibrosis ( < .001), with a higher prevalence of significant fibrosis in those with high discordance (65.5%) than those with low (14.5%) or concordant (13.5%) CD4 values. High CD4 discordance was strongly associated with significant fibrosis (odds ratio = 11.48, < .001). The CD4-only model showed a high negative predictive value (87.5%), making it suitable for excluding significant fibrosis. In contrast, models incorporating both CD4 count and percentage demonstrated higher positive and negative predictive values (78.6% and 87.6%, respectively), indicating their utility in diagnosing significant fibrosis. This study highlights the complexity of assessing liver fibrosis in HIV/HCV-coinfected individuals and underscores the value of CD4 discordance as a predictive factor. The predictive models, especially those combining CD4 count and percentage, provide an approach for evaluating liver fibrosis. Further research is needed to refine these models and enhance their clinical applicability.

Food industry is one of the major sources of any nation income and is basic for guaranteeing the welfare of its population. Food security is the foremost vital angle of any food and could be a key prerequisite for high-quality foods. Food industry is getting to be progressively critical to both developing and developed nations due to its role in advancing sustainable production and utilization practices, quality of life, competitiveness of businesses, and financial advance. Despite its significance, this industry faces a number of challenges that can be illuminated with Artificial Intelligence (AI) such as upgrading food quality, yield, nutrition values, sparing resources, protect food from microbes and eliminating food waste. With the appropriation of AI technology in the food industry, such as machine learning, deep learning, natural language processing, computer vision, robotics, and cognitive computing, many processes operations are being optimized such as food packaging, product sorting, foreign object detection, new food product development, equipment cleaning, and supply chain management. Also, by using AI in the food industry, we can locate foods using programs on our smartphones, and we can also learn about the manufacturers from them. In this chapter we will discusses how AI is used in various stages of the food industry, such as processing, distributing, food safety, food insecurity, and food wastage, as well as some of the challenges faced by AI adoption in the food industry in light of its future potential.

BACKGROUND: Viral hepatitis B and C are the leading causes of hepatocellular carcinoma (HCC). With obesity, metabolic-related disorders are increasingly associated with a higher incidence of nonviral HCC. This study aimed to investigate the characteristics, tumor features, treatment outcomes, and survival of patients with viral versus nonviral HCC.

METHODS: This multicenter cohort study was conducted at six tertiary care centers. Patients were recruited between February 2007 and June 2022 and follow-up was recorded until death or the study end (July 2023). The patients were divided into viral-related and nonviral HCC groups. We studied baseline patient characteristics, tumor characteristics, treatment, and overall survival (OS).

RESULTS: This study included 2233 patients, 1913 patients with viral and 320 patients with nonviral HCC. Patients with nonviral HCC presented with more advanced Barcelona Clinic Liver Cancer (BCLC) stages (BCLC stage C or D were present in 26.3% and 53.8% of patients with viral and nonviral HCC, respectively) that affected the median OS (19.167 vs. 13.830 months, P-value <0.001 for viral and nonviral HCC, respectively). The OS did not differ between patients with viral and nonviral HCC treated with resection, percutaneous ablation, trans-arterial chemoembolization, or Sorafinib. The independent factors affecting the survival of nonviral HCC were albumin-bilirubin score (hazard ratio = 2.323, 95% confidence interval (CI): 1.696-3.181, P-value <0.001), tumor size (hazard ratio = 1.085, 95% CI: 1.019-1.156, P-value 0.011), and alpha-fetoprotein (hazard ratio = 1.000, 95% CI: 1.000-1.000, P-value 0.042).

CONCLUSION: Patients with nonviral HCC had higher BMI, worse performance status, BCLC stage, and tumor response than those with viral HCC.