Neutrophils form sticky web-like structures known as neutrophil extracellular traps (NETs) as part of innate immune response. NETs are decondensed extracellular chromatin filaments comprising nuclear and cytoplasmic proteins. NETs have been implicated in many gastrointestinal diseases including colorectal cancer (CRC). However, the regulatory mechanisms of NET formation and potential pharmacological inhibitors in the context of CRC have not been thoroughly discussed. In this review, we intend to highlight roles of NETs in CRC progression and metastasis as well as the potential of targeting NETs during colon cancer therapy.

BRIP1 (Breast Cancer 1 Interacting Helicase 1) is a tumor suppressor gene that has vital function in preserving the genetic stability by repairing DNA damage though have significant associations with the onset of breast cancer (BC) if mutated or overexpressed. In this study, the prognostic value of BRIP1 gene was evaluated and validated through bioinformatics approaches utilizing transcriptomic (mRNA expression) data from several BC databases. To determine the prognostic value, the expression level of mRNA transcript was analyzed in context of comparison between breast tumor and normal tissues regarding clinical features, breast tumor subtypes, promoter methylation status, correlation level, mutation frequency, and survival of BC patients. BRIP1 expression was found to be significantly overexpressed in various BC molecular subtypes (e.g. PAM50, Sorlie’s) and clinical status (estrogen and progesterone receptor) than associated normal tissues which correlated with prognosis. Also, in promoter methylation level, its expression was observed as upregulated-hypomethylated regarding various clinicopathological features. Multiple data mining exhibited positive correlation between BRIP1 and INTS2 (Integrator Complex Subunit 2) expressions in BC. Further, mutation analysis revealed that BRIP1 gene was altered by acquiring both somatic and germline mutations. In addition, a total of 42 mutations; 24 missense, 8 fusion, 7 truncating, and 3 inframe mutations in BC patients was detected in BRIP1 protein. Moreover, higher BRIP1 expression was found to be correlated with poor disease-specific, disease metastasis-free, relapse-free, and overall survivals of BC patients. Since, overexpression of BRIP1 was identified to be associated with different clinical features, breast tumor subtypes, promoter methylation status, and survival of BC patients that may provide a risk of ensuing malignant transformation. Thus, lower expression of BRIP1 might hinder BC prognosis. We consider that this analysis will present a proof for BRIP1 gene to be a noteworthy molecular biomarker for BC prognosis.

The main concept of this research was forecasting a group of variables simultaneously, thus making use of correlations among the variables. This research aims to check forecasting performance among different VAR and ARIMA models applying some economic indicators of Bangladesh. Data sets were collected from secondary sources of Bangladesh such as Bangladesh bank bulletin, Bangladesh economic review, Monthly economic trends of Bangladesh Bank, and Statistical yearbook of Bangladesh. The stationary VAR and ARIMA models were applied for predicting these financial variables and then checked the accuracy by comparing ME, RMSE, MAE, MPE, MAPE, and MASE of respected the variables. This research found that the VAR model presented a better forecast than ARIMA models for the highly correlated variables such as GDP vs. GNP, Export vs. Import, etc. But ARIMA and VAR models performed almost the same for comparatively low correlated variables. That's means the variables were comparatively low correlated couldn't give a better forecast in the multivariate time series model rather than the univariate time series model. Finally, researchers concluded that before forecasting the authority should check correlations among the variables, and for high correlated variables, the VAR model should be used for forecasting, and otherwise, they can consider any models for both of these correlated and uncorrelated variables.

Introduction: Nepal has one of the highest prevalences of hypertension in South Asia, which also causes other cardiovascular diseases. However, no studies investigated the prevalence and risk factors of hypertension by urban-rural stratification. Methods: We used a machine learning, Boruta algorithm to select risk factors and a tenfold random forest classifier to evaluate their performance. Finally, multivariate logistic regression estimated crude and adjusted odds ratios with 95% confidence intervals for knowledge generation. Results: The study included 7825 participants (urban: 4939; rural: 2886), where rural participants were slightly older (median: 37 years; interquartile range: 26–53) and females were more hypertensive (urban: n = 606, 34.5%; rural: n = 308, 31.2%). The prevalence of hypertension was 35.6% in urban and 34.1% in rural regions. The odds of hypertension increased in rural regions for advancing age, provinces (province 4 and 5), and ecological zones (hill and terai). Overweight and obese participants were more likely to have hypertension in both regions. Conclusion: The study recommends the rigorous improvement of public health programs in rural regions of province 4 and 5, concentrating on Dalit and Janajati older males from hill and terai ecological zones. Overweight and obese people from both regions also need special focus. Finally, policymakers and government officials have to tailor campaigns differently for robust implementation of the essential health-care package and multisectoral action plans to prevent and control hypertension.