Recent updates in click and computational chemistry for drug discovery and development

Drug discovery is a costly and time-consuming process with a very high failure rate. Recently, click chemistry and computer-aided drug design (CADD) represent popular areas for new drug development. Herein, we summarized the recent updates in click and computational chemistry for drug discovery and development including clicking to effectively synthesize druggable candidates, synthesis and modification of natural products, targeted delivery systems, and computer-aided drug discovery for target identification, seeking out and optimizing lead compounds, ADMET prediction as well as compounds synthesis, hopefully, inspires new ideas for novel drug development in the future

Transient low T3 syndrome in patients with COVID-19: a new window for prediction of disease severity

ObjectiveTo investigate the relationship of low T3 syndrome with disease severity in patients with COVID-19.MethodsThe clinical data of 145 patients with COVID-19 were retrospectively collected, and patients were divided into a low T3 group and a normal T3 group. Logistic regression models were used to assess predictive performance of FT3. Receiver operating characteristic (ROC) analysis was used to evaluate the use of low T3 syndrome in predicting critical disease. Kaplan-Meier analysis was used to analyze the impact of low T3 syndrome on mortality.ResultsThe prevalence of low T3 level among COVID-19 patients was 34.48%. The low T3 group was older, and had lower levels of hemoglobin, lymphocytes, prealbumin, and albumin, but higher levels of white blood cells, neutrophils, CRP, ESR, and D-dimer (all p<0.05). The low T3 group had greater prevalences of critical disease and mortality (all p <0.05). Multivariate logistic regression analysis showed that the Lymphocytes, free T3 (FT3), and D-dimer were independent risk factors for disease severity in patients with COVID-19. ROC analysis showed that FT3, lymphocyte count, and D-dimer, and all three parameters together provided reliable predictions of critical disease. Kaplan-Meier analysis showed the low T3 group had increased mortality (p<0.001). Six patients in the low T3 group and one patient in the normal T3 group died. All 42 patients whose T3 levels were measured after recovery had normal levels after discharge.ConclusionPatients with COVID-19 may have transient low T3 syndrome at admission, and this may be useful for predicting critical illness

Demonstration of coherent terahertz transition radiation from relativistic laser-solid interactions

Coherent transition radiation in the terahertz (THz) region with energies of sub-mJ/pulse has been demonstrated by relativistic laser-driven electron beams crossing the solid-vacuum boundary. Targets including mass-limited foils and layered metal-plastic targets are used to verify the radiation mechanism and characterize the radiation properties. Observations of THz emissions as a function of target parameters agree well with the formation-zone and diffraction model of transition radiation. Particle-in-cell simulations also well reproduce the observed characteristics of THz emissions. The present THz transition radiation enables not only a potential tabletop brilliant THz source, but also a novel noninvasive diagnostic for fast electron generation and transport in laser-plasma interactions

Review of advanced road materials, structures, equipment, and detection technologies

As a vital and integral component of transportation infrastructure, pavement has a direct and tangible impact on socio-economic sustainability. In recent years, an influx of groundbreaking and state-of-the-art materials, structures, equipment, and detection technologies related to road engineering have continually and progressively emerged, reshaping the landscape of pavement systems. There is a pressing and growing need for a timely summarization of the current research status and a clear identification of future research directions in these advanced and evolving technologies. Therefore, Journal of Road Engineering has undertaken the significant initiative of introducing a comprehensive review paper with the overarching theme of “advanced road materials, structures, equipment, and detection technologies”. This extensive and insightful review meticulously gathers and synthesizes research findings from 39 distinguished scholars, all of whom are affiliated with 19 renowned universities or research institutions specializing in the diverse and multidimensional field of highway engineering. It covers the current state and anticipates future development directions in the four major and interconnected domains of road engineering: advanced road materials, advanced road structures and performance evaluation, advanced road construction equipment and technology, and advanced road detection and assessment technologies

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P <1 x 10(-6)) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P <5 x 10(-8) using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Ecological Learning Space Teaching Mode Based on Investigative Study – Case Study of Computer Image Processing

Computer Image Processing is a foundation course of computer specialty. Due to the problem of teaching method and students’ ability problem, the teaching process is boring and students are absent-minded in class, thus leading to low teaching efficiency of Computer Image Processing and low teaching quality. As well, the learning effect and level cannot meet the requirement of market and society. On this basis, Computer Image Processing was chosen as the teaching case to construct ecological learning space mode meeting the course requirements on the basis of investigative study and under the guidance of interactive theory. Besides, the students of computer major were chosen as the objects of study for one-semester teaching practice. Questionnaire survey and interview were combined for empirical research in order to innovate for teaching mode of Computer Image Processing and provide higher-quality computer talents for the society. The investigation found that the teaching mode is well welcomed by students and greatly improves their learning initiative and learning effect

Ecological Learning Space Teaching Mode Based on Investigative Study – Case Study of Computer Image Processing

Computer Image Processing is a foundation course of computer specialty. Due to the problem of teaching method and students’ ability problem, the teaching process is boring and students are absent-minded in class, thus leading to low teaching efficiency of Computer Image Processing and low teaching quality. As well, the learning effect and level cannot meet the requirement of market and society. On this basis, Computer Image Processing was chosen as the teaching case to construct ecological learning space mode meeting the course requirements on the basis of investigative study and under the guidance of interactive theory. Besides, the students of computer major were chosen as the objects of study for one-semester teaching practice. Questionnaire survey and interview were combined for empirical research in order to innovate for teaching mode of Computer Image Processing and provide higher-quality computer talents for the society. The investigation found that the teaching mode is well welcomed by students and greatly improves their learning initiative and learning effect