Association Study of Candidate Gene Polymorphisms and Obesity in a Young Mexican-American Population from South Texas

Background and Aims Obesity is increasingly a health problem and a risk factor for diabetes in young Mexican-American populations. Genetic association studies in older, mostly non-Hispanic populations have reported that polymorphisms in the candidate genes HSD11B1, CRP, ADIPOQ, PPARG, ANKK1, ABCC8 and SERPINF1 are associated with obesity or diabetes. We analyzed the polymorphisms rs846910, rs1205, rs1501299, rs1801282, rs1800497, rs757110 and rs1136287in these candidate genes, for association with obesity and metabolic traits in a young Mexican-American population from south Texas. Methods Genotyping of the seven common SNPs were performed by allelic discrimination assays in 448 unrelated Mexican Americans (median age = 16 years) from south Texas. χ2 tests and regression analyses using additive models were used for genetic association analyses adjusting for covariates; p values were corrected for multiple testing by permutation analyses. Results rs1800497 (ANKK1) shows association with waist circumference (p = 0.009) and retains the association (p = 0.03) after permutation testing. Analysis of metabolic quantitative traits shows that rs846910 (HSD11B1) was associated with HOMA-IR (p = 0.04) and triglycerides (p = 0.03), and rs1205 (CRP) with HOMA-IR (p = 0.03) and fasting glucose levels (p = 0.007). However, the quantitative traits associations are not maintained after permutation analysis. None of the other SNPs in this study showed associations with obesity or metabolic traits in this young Mexican-American population. Conclusions We report a potential association between rs1800497 (linked to changes in brain dopamine receptor levels) and central obesity in a young Mexican-American population

The Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China

For the pandemic of COVID-19, the initial number of infections in Wuhan China has never been known or estimated properly. This data is critical to understand the current pandemic across the world, as well as to eliminate panic from overestimated fatality rate that has biased the public health policies of many countries. By our unique estimation with the data of a number of foreign government evacuations with thorough follow-up and etiological tests, it is safe to say that a large number of infections in Wuhan, China have not been diagnosed (the number of undiagnosed is much more than the final diagnosed number 50,333 to date)

Digital synchronous measurement method for two-dimensional in-plane displacement using check-code

The measurement of two-dimensional displacement is an essential aspect of ultra-precision manufacturing and product design. This paper introduces an innovative method that uses a four-reader probe and a group of check codes to achieve digital synchronous measurement of translational and rotational displacement. The measuring principle and two-dimensional coding method are modelled first, and several reader-code combinations are proposed. And then, the study conducts numerical simulations to investigate the effect of different factors on measurement accuracies, such as check code size, machining tolerance, and reader resolution, and the method’s accuracy and performance are evaluated based on the error distribution to determine the optimal system parameters for various applications. A specialized lab experiment is conducted to validate the accuracy and reliability of the proposed method. In conclusion, the proposed method is innovative and practical, which realizes the synchronous measurement of two-dimensional in-plane displacement instead of a simple combination of two one-dimensional sensors

A distribution-based selective optimization method for eliminating periodic defects in harmonic signals

Due to environmental interference and defects in measured objects, measurement signals are frequently affected by unpredictable noise and periodic defects. Moreover, there is a lack of effective methods for accurately distinguishing defect components from measurement signals. In this study, a distribution-based selective optimisation method (SOM) is proposed to mitigate the effects of noise and defect components. The SOM can be seen as a binary- or multiple-class signal classifier based on an error distribution, which can simultaneously eliminate periodic defect components of measurement signals and proceed with signal-fitting regression. The effectiveness, accuracy, and feasibility of the SOM are verified in theoretical and realworld measurement settings. Based on theoretical simulations under various parameter conditions, some criteria for selecting operation variables among a selection of parameter conditions are explained in detail. The proposed method is capable of separating defect components from measurement signals while also achieving a satisfactory fitting curve for the measurement signals. The proposed SOM has broad application prospects in signal processing and defect detection for mechanical measurements, electronic filtering, instrumentation, part maintenance, and other fields

Structure-guided engineering of transcriptional activator XYR1 for inducer-free production of lignocellulolytic enzymes in Trichoderma reesei

The filamentous fungus Trichoderma reesei is widely used for the production of lignocellulolytic enzymes in industry. XYR1 is the major transcriptional activator of cellulases and hemicellulases in T. reesei. However, rational engineering of XYR1 for improved lignocellulolytic enzymes production has been limited by the lack of structure information. Here, alanine 873 was identified as a new potential target for the engineering of XYR1 based on its structure predicted by AlphaFold2. The mutation of this residue to tyrosine enabled significantly enhanced production of xylanolytic enzymes in the medium with cellulose as the carbon source. Moreover, xylanase and cellulase production increased by 56.7- and 3.3-fold, respectively, when glucose was used as the sole carbon source. Under both conditions, the improvements of lignocellulolytic enzyme production were higher than those in the previously reported V821F mutant. With the enriched hemicellulases and cellulases, the crude enzymes secreted by the A873Y mutant strain produced 51 % more glucose and 52 % more xylose from pretreated corn stover than those of the parent strain. The results provide a novel strategy for engineering the lignocellulolytic enzyme-producing capacity of T. reesei, and would be helpful for understanding the molecular mechanisms of XYR1 regulation