Trait evaluation and trial cultivation of Dongfang No. 2, the hybrid of a male gametophyte clone of Laminaria longissima (Laminariales, Phaeophyta) and a female one of L. japonica

Direct cultivation of the first filial generation of gametophyte clones from different Laminaria species is a highly effective way of utilizing kelp heterozygous vigor (heterosis). A male gametophyte clone of L. longissima Miyabe and a female one of L. japonica Areschoug were hybridized, generating Dongfang No. 2 hybrid kelp. This hybrid kelp was used directly in trial cultivation, and its agronomical traits were evaluated. L. longissima and L. japonica are obviously different and complement each other in their morphological characteristics and ecological performances. The hybrid of their gametophyte clones, Dongfang No. 2, showed 56.8% heterozygous vigor in yield. It also showed increased yields of 41.0 and 76.4% compared to the widely used commercial kelps Variety 1 and Variety 2, respectively. In large-scale cultivation trials at different locations and in different years, Dongfang No. 2 attained significantly higher yields than Varieties 1 and 2, increasing yield by 26.4% on average over Variety 1 and by 65.0% over the other. Dongfang No. 2 has a robust holdfast and a wide, long and deep-brown uniform blade, which shows a distinct middle groove. In addition to yield, Dongfang No. 2 also demonstrates obvious heterozygous vigor in other agronomic traits. It is resistant to strong irradiance, as the two commercial varieties are, has an appropriate vegetative maturation time, and adapts well to a range of different culture conditions. The parentage analysis using AFLP of total DNA and SNP of the ITS region of ribosomal RNA transcription unit showed that Dongfang No. 2 is the real hybrid of L. japonica and L. longissima

Experimental Study on Coal Seam Gas Desorption Characteristics Caused by Moisture under Stepwise Depressurization

Expansion energy is the main factor of coal and gas outbursts, and the gas desorption around the outburst hole is developed in variable pressure conditions. While studying the impact of moisture on gas desorption characteristics, atmospheric pressure desorption is usually used, but its characteristics under variable pressure conditions have not been thoroughly investigated. In this study, typical outburst coal samples with different water contents from the Jincheng mining area of China were selected as research objects, and the effects of water on gas displacement, desorption, desorption rate, and gas desorption index (K1) of drilling cuttings under step-by-step depressurization were analyzed by means of stepwise depressurization and atmospheric desorption experiments. The research conclusions suggest that (1) the amount of gas replacement, which augments rapidly during the inception, increases with the growth of water content under the experimental conditions, and then the rate decreases; (2) the gas desorption falls gradually at different depressurization stages when the humidity is constant, while the total desorption and the drop amplitude taper with the increasing water content; (3) the additional water enhances the desorption rate significantly only at the initial stage, but scarcely has an impact later on; and (4) the value of the drilling cuttings’ gas desorption index (K1) shows a downward trend with the developing humidity in each stage of stepwise depressurization desorption. We take humidity as a variable to simulate the desorption process of coal gas around the hole when coal and gas outbursts occur in the laboratory and study the influence of water on the desorption characteristics under desorption conditions of stepwise depressurization. This provides a reference for the purpose of studying the mechanism of coal and gas outbursts from the perspective of energy

Luteolin, a natural flavonoid, inhibits methylglyoxal induced apoptosis via the mTOR/4E-BP1 signaling pathway

Methylglyoxal (MG) accumulation has been observed in human cerebrospinal fluid and body tissues under hyperglycaemic conditions. Recent research has demonstrated that MG-induces neuronal cell apoptosis, which promotes the development of diabetic encephalopathy. Our previous animal study has shown that luteolin, a natural flavonoid, attenuates diabetes-associated cognitive dysfunction. To further explore the neuroprotective properties of luteolin, we investigated the inhibitive effect of luteolin on MG-induced apoptosis in PC12 neuronal cells. We found that MG inhibited cell viability in a dose-dependent manner and induced apoptosis in PC12 cells. Pretreatment with Luteolin significantly elevated cell viability, reduced MG-induced apoptosis, inhibited the activation of the mTOR/4E-BP1 signaling pathway, and decreased pro-apoptotic proteins, Bax, Cytochrome C as well as caspase-3. Furthermore, we found that pretreatment with the mTOR inhibitor, rapamycin, significantly reduced the expression of the pro-apoptotic protein Bax. Therefore, these observations unambiguously suggest that the inhibitive effect of Luteolin against MG-induced apoptosis in PC12 cells is associated with inhibition of the mTOR/4E-BP1 signaling pathway

Natural Deep Eutectic Solvent-Based Microwave-Assisted Extraction of Total Flavonoid Compounds from Spent Sweet Potato (<i>Ipomoea batatas</i> L.) Leaves: Optimization and Antioxidant and Bacteriostatic Activity

Natural deep eutectic solvents (NADESs) coupled with microwave-assisted extraction (MAE) were applied to extract total flavonoid compounds from spent sweet potato (Ipomoea batatas L.) leaves. In this study, ten different NADESs were successfully synthesized for the MAE. Based on single-factor experiments, the response surface methodology (RSM) was applied, and the microwave power, extraction temperature, extraction time, and solid–liquid ratio were further evaluated in order to optimize the yields of total flavonoid compounds. Besides, the extracts were recovered by macroporous resin for the biological activity detection of flavonoid compounds. As a result, NADES-2, synthesized by choline chloride and malic acid (molar ratio 1:2), exhibited the highest extraction yield. After that, the NADES-2-based MAE process was optimized and the optimal conditions were as follows: microwave power of 470 W, extraction temperature of 54 °C, extraction time of 21 min, and solid–liquid ratio of 70 mg/mL. The extraction yield (40.21 ± 0.23 mg rutin equivalents/g sweet potato leaves) of the model validation experiment was demonstrated to be in accordance with the predicted value (40.49 mg rutin equivalents/g sweet potato leaves). In addition, flavonoid compounds were efficiently recovered from NADES-extracts with a high recovery yield (>85%) using AB-8 macroporous resin. The bioactivity experiments in vitro confirmed that total flavonoid compounds had good DPPH and O2−· radical-scavenging activity, as well as inhibitory effects on E. coli, S. aureus, E. carotovora, and B. subtilis. In conclusion, this study provides a green and efficient method to extract flavonoid compounds from spent sweet potato leaves, providing technical support for the development and utilization of sweet potato leaves’ waste

Targeting Adults for Supplementary Immunization Activities of Measles Control in Central China: A Mathematical Modelling Study

Abstract Routine immunizations and supplementary immunization activities (SIAs) have significantly improved measles control over the past two decades in China. Progress towards eliminating measles currently faces multiple challenges as the infection age increases, and adult-targeted SIA strategies are being considered. This study developed an age-stratified susceptible-exposed-infectious-recovered model using a recently published contact matrix to depict measles transmissions between individuals in seven age groups. Hubei, a high measles-incidence province in central China, was the selected setting. The baseline scenario was calibrated by fitting with the 2012–2015 age-stratified incidence data. SIAs targeting multiple age groups were simulated. Adult-targeted (>29 years) two-year SIA cycles produced the greatest annual incidence rate decrease, reducing incidences by half over a long timespan with 90% coverage levels. Incidences could remain below 10/100,000 until 2030 if SIAs were provided to individuals ≥6 years old with at least 50% coverage. These findings will help officials prioritize supplementary vaccination strategies. Public health officials in China should consider adult-to-adult transmissions and provide adult-targeted SIAs. Although officials have reported approximately 90% SIA coverage in the past, SIAs for the adult population should be provided on shorter intervals, particularly for the aging population with decreased immunity

Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.

BackgroundElectronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children.Methods and findingsReal-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered.ConclusionsTo our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia

Additional file 1: of Construction and implications of structural equation modeling network for pediatric cataract: a data mining research of rare diseases

The detailed information for potential variables and evaluation indices are presented. (DOCX 16 kb