The COVID-19 pandemics caused an unprecedented mortality, distress, and globally poses a challenge to mental resilience. To our knowledge, this is the first study that aimed to investigate the psychological distress among the adult general population across 13 countries. This cross-sectional study was conducted through online survey by recruiting 7091 respondents. Psychological distress was evaluated with COVID-19 Peritraumatic Distress Index (CPDI). The crude prevalence of psychological distress due to COVID-19 is highest in Vietnam, followed by Egypt, and Bangladesh. Through Multivariate Logistic Regression Analysis, the respondents from Vietnam holds the highest level of distress, while the respondents from Sri Lanka holds the lowest level of distress with reference to Nepal.Female respondents had higher odds of having reported psychological distress, and those with tertiary education were less likely to report psychological distress compared to those with lower level of education. The findings indicate that psychological distress is varies across different countries. Therefore, different countries should continue the surveillance on psychological consequences through the COVID-19 pandemic to monitor the burden and to prepare for the targeted mental health support interventions according to the need. The coping strategies and social support should be provided especially to the lower educational attainment group.

Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed which is easy, cost effective and time saving. Materials and Methods: Initially 400 cancer and non-cancer patients' data were collected from different diagnostic centres, pre-processed and clustered using a K-means clustering algorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered using AprioriTid and a decision tree algorithm. Results: Finally using the significant pattern prediction tools for a lung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful in detection of a person's predisposition for lung cancer. Conclusions: Most of people of Bangladesh do not even know they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible. Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effective preventive strategy.

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Many natural products such as fruits and vegetables are promising amends as safe, effective and affordable approaches to control cancer development and progression, since they are inexpensive and available without any hazards. For instance, the aqueous extract of Ajwa dates (Phoenix dactilyfera) has been found to improve liver function through the restoration of anti-oxidant enzymes, liver enzymes, and cytokines balance and gene expression to normal levels. As the treatment and prognosis of Hepatocellular carcinoma, one of the leading causes of cancer associated deaths globally, has been found to be better if the liver function of the patient can be preserved, Ajwa date extract has been used together with the conventional therapeutics for the treatment of this disease. However, no study has been conducted so far on the anticancer activity of Bangladeshi wild date palm fruits (Phoenix sylvestris) despite the fact that it contains apigenin, quercetin, glucans, luteolin, and iron and vitamin complex. Therefore, in this review we discussed an idea that potential anticancer agents can be isolated from the extract of these fruits, which can eventually be used as an indigenous substance for the treatment of Hepatocellular carcinoma in our country and also the liver cancer inhibitory effects of the aqueous extract of these dates can be evaluated in rat model. Int. J. Appl. Sci. Biotechnol. Vol 9(1): 32-37