An accurate understanding of the distributional implications of public health policies is critical for ensuring equitable responses to the COVID-19 pandemic and future public health threats.
 
  To identify and quantify the association of race/ethnicity-based, sex-based, and income-based inequities of state-specific lockdowns with 6 well-being dimensions in the United States.
 
  This pooled, repeated cross-sectional study used data from 14 187 762 households who participated in phase 1 of the population-representative US 2020 Household Pulse Survey (HPS). Households were invited to participate by email, text message, and/or telephone as many as 3 times. Data were collected via an online questionnaire from April 23 to July 21, 2020, and participants lived in all 50 US states and the District of Columbia.
 
  Indicators of race/ethnicity, sex, and income and their intersections.
 
  Unemployment; food insufficiency; mental health problems; no medical care received for health problems; default on last month's rent oranket public health policies ignoring existing distributions of risk to well-being may be associated with increased race/ethnicity-based, sex-based, and income-based inequities.
 In this cross-sectional study, African American and Hispanic individuals, women, and households with low income had higher odds of experiencing adverse outcomes associated with the COVID-19 pandemic and stay-at-home orders. Blanket public health policies ignoring existing distributions of risk to well-being may be associated with increased race/ethnicity-based, sex-based, and income-based inequities.Nanotechnology has received considerable attention and interest over the past few decades in the field of biomedicine due to the wide range of applications it provides in disease diagnosis, drug design and delivery, biomolecules detection, tissue engineering and regenerative medicine.  https://www.selleckchem.com/  Ultra-small size and large surface area of nanomaterials prove to be greatly advantageous for their biomedical applications. Moreover, the physico-chemical and thus, the biological properties of nanomaterials can be manipulated depending on the application. However, stability, efficacy and toxicity of nanoparticles remain challenge for researchers working in this area. This mini-review highlights the recent advances of various types of nanoparticles in biomedicine and will be of great value to researchers in the field of materials science, chemistry, biology and medicine.To keep up with the pace of rapid discoveries in biomedicine, a plethora of research endeavors had been directed toward Rational Drug Development that slowly gave way to Structure-Based Drug Design (SBDD). In the past few decades, SBDD played a stupendous role in identification of novel drug-like molecules that are capable of altering the structures and/or functions of the target macromolecules involved in different disease pathways and networks. Unfortunately, post-delivery drug failures due to adverse drug interactions have constrained the use of SBDD in biomedical applications. However, recent technological advancements, along with parallel surge in clinical research have led to the concomitant establishment of other powerful computational techniques such as Artificial Intelligence (AI) and Machine Learning (ML). These leading-edge tools with the ability to successfully predict side-effects of a wide range of drugs have eventually taken over the field of drug design. ML, a subset of AI, is a robust computational tool that is capable of data analysis and analytical model building with minimal human intervention. It is based on powerful algorithms that use huge sets of 'training data' as inputs to predict new output values, which improve iteratively through experience. In this review, along with a brief discussion on the evolution of the drug discovery process, we have focused on the methodologies pertaining to the technological advancements of machine learning. This review, with specific examples, also emphasises the tremendous contributions of ML in the field of biomedicine, while exploring possibilities for future developments.The objective of this study was to evaluate the effect of long-term feeding of graded levels of deoxynivalenol (DON) on performance, nutrient utilization, and organ health of grower-finisher pigs. A total of 240 mixed-sex grower-finisher pigs (35.9 ± 1.1 kg initial body weight, BW) were randomly assigned to 1 of 4 dietary treatments (6 pigs/pen; 10 pens/treatment) for 77 d. Diets consisted of a control diet without DON (CONT) and diets containing 1, 3, or 5 ppm DON (DON1, DON3, or DON5). Nitrogen-balance was determined in 1 pig/pen during weeks 6 and 12 of the study. Growth performance measures were taken weekly for average daily feed intake (ADFI), average daily gain (ADG), and gainfeed (GF) until day 77. Blood samples were collected on days 0, 14, 42, 56, and 84 from 1 pig/pen for analysis of indicators of liver and kidney function. On day 7, ADG and ADFI for pigs fed DON3 and DON5 diets were lower (P 1 ppm DON had reduced growth performance with little or no effect on nitrogen utilization, organ health, or carcass characteristics, suggesting that the negative effects of DON may be largely due to depressed feed intake.
  There is accumulating evidence of aberrant expression of miR-143 and miR-145 and their target gene KRAS in colorectal cancer (CRC). We hypothesize that single nucleotide polymorphisms (SNPs) within or near mRNA-microRNA (miRNA) binding sites may affect miRNA/target gene interaction, resulting in differential mRNA/protein expression and promoting the development and progression of CRC.
 
  We conducted a case-control study of 507 patients with CRC recruited from a tertiary hospital and 497 population-based controls to assess the association of genetic polymorphisms in miR-143/145 and the KRAS 3' untranslated region (3'UTR) with susceptibility to CRC and patients' survival. In addition, genetic variations of genomic regions located from 500 bp upstream to 500 bp downstream of the miR-143/miR-145 gene and the 3'UTR of KRAS were selected for analysis using the Haploview and HaploReg software.
 
  Using publicly available expression profiling data, we found that miR-143/145 and KRAS expression were all reduced in rectal cancer tissue compared with adjacent non-neoplastic large intestinal mucosa.