Disease burden of low back pain attributable to ergonomic risk factors in selected Chinese occupational groups

BackgroundAs traditional chemical and physical hazards as well as associated adverse health outcomes in workplace were wildly controlled in the past half century, the prevalence and disease burden of low back pain (LBP) have drawn more and more attention and become one of the important public health problems in the world. ObjectiveTo analyze the health loss and attributable disease burden of ergonomic risk factors for LBP in two major categories of occupations in China, aiming to provide evidence for formulating effective prevention and control policies of LBP in the workplace. MethodsBased on the methodological framework of the Global Burden of Disease Study (GBD), a meta-analysis was firstly applied to summarize relevant literature results and estimate the prevalence of LBP in two occupational groups (including technicians and associate professionals and machine operators and assemblers) by different age groups in China. Then important epidemiologic parameters (including disability weight, remission rate, and incidence) from GBD 2019 were used to estimate mean duration of disease and age at onset using DisMod II software, and to calculate health loss indexes in the selected occupational groups in China in 2013, such as years lived with disability (YLD) and disability-adjusted life year (DALY) of LBP and its attributable fractions by ergonomic risk factors, which were compared to the outcome of GBD 2013. ResultsAfter the adjustment by DisMod II, the prevalence rate of LBP was 13.00% in technicians and associate professionals (11.25% for males and 14.84% for females) and 14.80% in machine operators and assemblers (13.56% for males and 16.10% for females) in 2013, which increased with age. The DALY rate of LBP was 8.02‰ in technicians and associate professionals (7.68‰ for males and 8.33‰ for females) and 10.34‰ in machine operators and assemblers (10.30‰ for males and 10.44‰ for females), which also showed an overall increasing trend with age. In 2013, the population attributable fraction (PAF) of ergonomic risk factors to LBP was 11.42% in technicians and associate professionals and 29.17% in machine operators and assemblers. The DALY of LBP attributable to ergonomics risk factors was 4498 person-years (2108 person-years for males), with the highest DALY in the 45-49 year group (951 person-years), and the attributable DALY rate was 0.92‰ in technicians and associate professionals. The DALY of LBP attributable to ergonomics risk factors was 48529 person-years (33046 person-years for males), with the highest DALY in the 40-44 year group (10852 person-years), and the attributable DALY rate was 3.02‰ in machine operators and assemblers. Regarding LBP-associated DALY rate, in the 20 years of age and above group, both occupational groups (technicians and associate professionals: 8.06‰, machine operators and assemblers: 10.66‰) showed higher values than the general population (3.55‰). In the 20 years of age and above group, the DALY rates attributable to ergonomic risk factors with the order from high to low were machine operators and assemblers (3.11‰), general population (1.10‰) and technicians and associate professionals (0.92‰).ConclusionThe LBP-associated disease burden is heavier in the two Chinese occupational groups than in general population. Reducing the disease burden of LBP by interventions targeting ergonomic risk factors in machine operators and assemblers is more effective than that in technicians and associate professionals as the results of attributable burden of disease suggest

Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places

BackgroundPeople usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations.MethodsIn this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models.ResultsThe final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables.ConclusionIn this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction

Performance improvement of nitride semiconductor-based deep-ultraviolet laser diodes with superlattice cladding layers

A deep-ultraviolet (DUV) laser diode (LD) consisting of specifically designed cladding layers involving superlattice nitride alloy has been proposed. Simulation studies of different cladding layers were carried out using Crosslight software. It was found that the proposed structure effectively suppresses the leakage of the optical field from the active region and the optical confinement coefficient is 1.45 times higher than that of the conventional structure. The proposed structure has a significant increase in laser power with a low threshold current. Moreover, the introduction of novel cladding layer suppresses the electron and hole leakage from the multiple quantum well (MQW) region, which provides an attractive solution for increasing the stimulated recombination rate in the MQW region leading to the improvement in the performance of the DUV LD

Lignin Biodegradation and Its Valorization

Lignin, a rigid polymer composed of phenolic subunits with high molecular weight and complex structure, ranks behind only cellulose in the contribution to the biomass of plants. Therefore, lignin can be used as a new environmentally friendly resource for the industrial production of a variety of polymers, dyes and adhesives. Since laccase was found to be able to degrade lignin, increasing attention had been paid to the valorization of lignin. Research has mainly focused on the identification of lignin-degrading enzymes, which play a key role in lignin biodegradation, and the potential application of lignin degradation products. In this review, we describe the source, catalytic specificity and enzyme reaction mechanism of the four classes of the lignin-degrading enzymes so far discovered. In addition, the major pathways of lignin biodegradation and the applications of the degradative products are also discussed. Lignin-degrading bacteria or enzymes can be used in combination with chemical pretreatment for the production of value-added chemicals from lignin, providing a promising strategy for lignin valorization

RNA Motifs and Modification Involve in RNA Long-Distance Transport in Plants

A large number of RNA molecules have been found in the phloem of higher plants, and they can be transported to distant organelles through the phloem. RNA signals are important cues to be evolving in fortification strategies by long-distance transportation when suffering from various physiological challenges. So far, the mechanism of RNA selectively transportation through phloem cells is still in progress. Up to now, evidence have shown that several RNA motifs including Polypyrimidine (poly-CU) sequence, transfer RNA (tRNA)-related sequence, Single Nucleotide Mutation bound with specific RNA binding proteins to form Ribonucleotide protein (RNP) complexes could facilitate RNA mobility in plants. Furthermore, some RNA secondary structure such as tRNA-like structure (TLS), untranslation region (UTR) of mRNA, stem-loop structure of pre-miRNA also contributed to the mobility of RNAs. Latest researchs found that RNA methylation such as methylated 5′ cytosine (m5C) played an important role in RNA transport and function. These studies lay a theoretical foundation to uncover the mechanism of RNA transport. We aim to provide ideas and clues to inspire future research on the function of RNA motifs in RNA long-distance transport, furthermore to explore the underlying mechanism of RNA systematic signaling

Age Structure and Body Size of The Tibetan Toad (Bufo tibetanus) Populations from Two Different Altitudes in China

Knowledge about the altitudinal patterns in age and body size helps to highlight the evolution of life history parameters in animals. In this study, we investigated the demographic traits of the Tibetan toad (Bufo tibetanus) between populations from low and high altitude habitats (2650 vs 3930m) using skeletochronology. We found 1) the mean age and body size of females were significantly greater than those of males in either population; 2) both sexes of toads from the higher altitude tended to be significantly older in age and larger in body size; 3) a significant positive relationship between age and body size within each sex of the toad at both altitudes; 4) growth rates varied between the two populations, with the higher rate observed in the low-altitude population, and lower in the high-altitude population. Our results suggest that factors other than age can influence altitudinal patterns in body size, such as altitude-associated temperature. Future research should pay attention to these factors and evaluate their influences on the growth patterns of animals.Knowledge about the altitudinal patterns in age and body size helps to highlight the evolution of life history parameters in animals. In this study, we investigated the demographic traits of the Tibetan toad (Bufo tibetanus) between populations from low and high altitude habitats (2650 vs 3930m) using skeletochronology. We found 1) the mean age and body size of females were significantly greater than those of males in either population; 2) both sexes of toads from the higher altitude tended to be significantly older in age and larger in body size; 3) a significant positive relationship between age and body size within each sex of the toad at both altitudes; 4) growth rates varied between the two populations, with the higher rate observed in the low-altitude population, and lower in the high-altitude population. Our results suggest that factors other than age can influence altitudinal patterns in body size, such as altitude-associated temperature. Future research should pay attention to these factors and evaluate their influences on the growth patterns of animals

CUCUME: An RNA methylation database integrating systemic mRNAs signals, GWAS and QTL genetic regulation and epigenetics in different tissues of Cucurbitaceae

As an internal modification of transcripts, RNA methylation determines RNA fate by changing RNA–protein binding affinity. In plants, RNA methylation is ubiquitous and is involved in all aspects of RNA post-transcriptional regulation. For instance, long-distance mobile RNAs, strongly influenced by their methylation status, play important roles in plant growth, development and environmental adaptation. Cucumber/pumpkin heterografts are widely used to improve stress tolerance of cucumber and to study mobile RNA signals due to their strong developed vasculature system. Here, we developed the Cucume (Cucurbit RNA methylation, http://cucume.cn/) database for these two important vegetables, cucumber (Cucumis sativus L.) and pumpkin (Cucurbita moschata) with high productivity worldwide. We identified mRNAs harboring 5-methylcytosine (m5C) and N6-methyladenosine (m6A) sites in pumpkin and cucumber at the whole genome level via Methylated RNA Immunoprecipitation sequencing (MeRIP-seq) of different tissues and the vascular exudates. In addition to RNA methylation sites, the Cucume database includes graft-transmissible systemic mRNAs identified in previous studies using cucumber/pumpkin heterografts. The further integration of cucumber genome-wide association analysis (GWAS) and quantitative trait loci (QTL) allows the study of RNA methylation-related genetic and epigenetic regulation in cucurbits. Therefore, the here developed Cucume database will promote understanding the role of cucurbit RNA methylation in RNA mobility and QTL, ultimately benefitting future breeding of agronomic crop germplasms