Awareness levels of breast cancer among female university and medical college students in Sylhet city of Bangladesh.

BACKGROUND: Breast cancer has become a concerning health problem worldwide due to its increasing incidence rate. Women from developing countries are dying off due to the lack of knowledge on breast cancer and its different early detection programs. AIMS: This study explores the level of knowledge about breast cancer risk factors, early warning signs, screening, and therapeutic approaches and their influential determinants among university and medical college students. METHODS: A cross-sectional study was conducted, including 567 female university-level students (343 female students from 1 university and 224 female students from 1 medical college). This study used a semi-structured questionnaire about four aspects (risk factors, early warning signs, screening, and therapeutic approaches) of breast cancer, latent class analysis (LCA), and latent class regression (LCR) for investigation. RESULTS: The percent of knowing correct answers of risk factors, early warning signs, screening approaches, and therapeutic methods were 86.3%, 69.8%, 70.2%, and 51.2%, respectively for medical students who had a high level of awareness and those for university students were 73.0%, 66.8%, 35.9%, and 24.7%. On the other hand, only 37.95% of medical students had been practicing Breast self-examination (BSE), while it was 18.37% for university students. The most effective predictors of the high level of awareness were age, advertisements (ad) promoting awareness about breast cancer, programs/campaign related to breast cancer, and personal breast problem history. CONCLUSIONS: Taken together, the awareness level about four aspects of breast cancer is low among university students and is moderately high among medical students. Therefore, relevant health education programs in every educational institute are urgently needed to improve the awareness levels among female students to improve women's health at home and abroad.

Chikungunya outbreak in Bangladesh (2017): Clinical and hematological findings.

INTRODUCTION: A massive outbreak of chikungunya virus (CHIKV) occurred in Bangladesh during the period of April-September 2017, and over two million people were at risk of getting infected by the virus. A prospective cohort of viremic patients was constituted and analyzed to define the clinical, hematological, and long-term aspects of this outbreak. METHODS: A 35-day long comprehensive survey was conducted in two major, neighboring cities, Dhaka and Mymensingh. One-hundred and eighty-seven laboratory-confirmed CHIKV cases were enrolled in the cross-sectional cohort study. Additionally, a smaller group of 48 chikungunya patients was monitored for post-infection effects for 12 months. RESULTS: Clinical data revealed that a combination of fever and arthralgia (oligoarthralgia and/or polyarthralgia) was the cardinal hallmark (97.9% of cases) of the infection. Hematological analysis showed that irrespective of age and sex groups, CHIKV patients had a decreased level of hemoglobin (n = 64, p < 0.01) and elevated erythrocyte sedimentation rate (n = 131, p < 0.01). Besides, a significant portion of the patients represented abnormal values for RBC (n = 38, p = 0.0005) and WBC (n = 63, p < 0.01) counts. The post-infection study revealed that children had an early recovery from the infection compared to the adults. Moreover, post-infection weakness, successive relapse of arthralgic pain, and memory problems were the most significant aftereffects, which had an impact on the daily activities of patients. CONCLUSIONS: This study represents a comprehensive overview of clinical and epidemiological features of the 2017 outbreak of CHIKV in Bangladesh as well as its chronic outcomes till the 12th month. It provides insights into the natural history of this disease, which may help to improve the management of CHIKV patients.

An Integrated Statistical Approach to Compare Transcriptomics Data Across Experiments: A Case Study on the Identification of Candidate Target Genes of the Transcription Factor PPARα.

An effective strategy to elucidate the signal transduction cascades activated by a transcription factor is to compare the transcriptional profiles of wild type and transcription factor knockout models. Many statistical tests have been proposed for analyzing gene expression data, but most tests are based on pair-wise comparisons. Since the analysis of microarrays involves the testing of multiple hypotheses within one study, it is generally accepted that one should control for false positives by the false discovery rate (FDR). However, it has been reported that this may be an inappropriate metric for comparing data across different experiments. Here we propose an approach that addresses the above mentioned problem by the simultaneous testing and integration of the three hypotheses (contrasts) using the cell means ANOVA model. These three contrasts test for the effect of a treatment in wild type, gene knockout, and globally over all experimental groups. We illustrate our approach on microarray experiments that focused on the identification of candidate target genes and biological processes governed by the fatty acid sensing transcription factor PPARα in liver. Compared to the often applied FDR based across experiment comparison, our approach identified a conservative but less noisy set of candidate genes with same sensitivity and specificity. However, our method had the advantage of properly adjusting for multiple testing while integrating data from two experiments, and was driven by biological inference. Taken together, in this study we present a simple, yet efficient strategy to compare differential expression of genes across experiments while controlling for multiple hypothesis testing.