Effects of high CD4 cell counts on death and attrition among HIV patients receiving antiretroviral treatment: an observational cohort study

Current WHO guidelines recommend initiating ART regardless of CD4+ cell count. In response, we conducted an observational cohort study to assess the effects of pre-ART CD4+ cell count levels on death, attrition, and death or attrition in HIV treated patients. This large HIV treatment cohort study (n = 49,155) from 2010 to 2015 was conducted in Guangxi, China. We used a Cox regression model to analyze associations between pre-ART CD4+ cell counts and death, attrition, and death or attrition. The average mortality and ART attrition rates among all treated patients were 2.63 deaths and 5.32 attritions per 100 person-years, respectively. Compared to HIV patients with 500 CD4+ cells/mm 3 at ART initiation had a significantly lower mortality rate (Adjusted hazard ratio: 0.56, 95% CI: 0.40-0.79), but significantly higher ART attrition rate (AHR: 1.17, 95% CI: 1.03-1.33). Results from this study suggest that HIV patients with high CD4+ cell counts at the time of ART initiation may be at greater risk of treatment attrition. To further reduce ART attrition, it is imperative that patient education and healthcare provider training on ART adherence be enhanced and account for CD4 levels at ART initiation

The Endophytic Fungus Piriformospora Indica-Assisted Alleviation of Cadmium in Tobacco

Increasing evidence suggests that the endophytic fungus Piriformospora indica helps plants overcome various abiotic stresses, especially heavy metals. However, the mechanism of heavy metal tolerance has not yet been elucidated. Here, the role of P. indica in alleviating cadmium (Cd) toxicities in tobacco was investigated. It was found that P. indica improved Cd tolerance to tobacco, increasing Cd accumulation in roots but decreasing Cd accumulation in leaves. The colonization of P. indica altered the subcellular repartition of Cd, increasing the Cd proportion in cell walls while reducing the Cd proportion in membrane/organelle and soluble fractions. During Cd stress, P. indica significantly enhanced the peroxidase (POD) activity and glutathione (GSH) content in tobacco. The spatial distribution of GSH was further visualized by Raman spectroscopy, showing that GSH was distributed in the cortex of P. indica-inoculated roots while in the epidermis of the control roots. A LC-MS/MS-based label-free quantitative technique evaluated the differential proteomics of P. indica treatment vs. control plants under Cd stress. The expressions of peroxidase, glutathione synthase, and photosynthesis-related proteins were significantly upregulated. This study provided extensive evidence for how P. indica enhances Cd tolerance in tobacco at physiological, cytological, and protein levels

Multi-Point Seawall Settlement Prediction with Limited Data Volume Using an Improved Fractional-Order Grey Model

Settlement prediction based on monitoring data holds significant importance for engineering maintenance of seawalls. In practical engineering, the volume of the collected monitoring data is often limited due to the restrictions of devices and engineering budgets. Previous studies have applied the fractional-order grey model to time series prediction under the situation of limited data volume. However, the performance of the fractional-order grey model is easily affected by the inappropriate settings of fractional order. Also, the model cannot make dynamic predictions due to the characteristic of fixed step size. To solve the above problems, in this paper, the genetic algorithm with enhanced search capabilities was employed to solve the premature convergence problem. Additionally, to solve the problem of the fractional-order grey model associated with fixed step size, the real-time tracing algorithm was introduced to conduct equal-dimensionally recursive calculation. The proposed model was validated using monitoring data of four monitoring points at Haiyan seawall in Zhejiang province, China. The prediction performance of the proposed model was then compared with those of the fractional-order GM(1,1), integer-order GM(1,1), and fractal theory model. Results indicate that the proposed model significantly improves the prediction performance compared to other models

Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks

Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874–1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA) scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA) was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN), evolutionary neural network (ENN), extreme learning machine (ELM), general regression neural network (GRNN) and radial basis neural network (RBNN) were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts

Interconversion between Methoxylated and Hydroxylated Polychlorinated Biphenyls in Rice Plants: An Important but Overlooked Metabolic Pathway

To date, there is limited knowledge on the methoxylation of polychlorinated biphenyls (PCBs) and the relationship between hydroxylated polychlorinated biphenyls (OH-PCBs) and methoxylated polychlorinated biphenyls (MeO-PCBs) in organisms. In this study, rice (Oryza sativa L.) was chosen as the model organism to determine the metabolism of PCBs in plants. Limited para-substituted 4′-OH-CB-61 (major metabolite) and 4′-MeO-CB-61 (minor metabolite) were found after a 5-day exposure to CB-61, while ortho- and meta-substituted products were not detected. Interconversion between OH-PCBs and MeO-PCBs in organisms was observed for the first time. The demethylation ratio of 4′-MeO-CB-61 was 18 times higher than the methylation ratio of 4′-OH-CB-61, indicating that formation of OH-PCBs was easier than formation of MeO-PCBs. The transformation products were generated in the roots after 24 h of exposure. The results of in vivo and in vitro exposure studies show that the rice itself played a key role in the whole transformation processes, while endophytes were jointly responsible for hydroxylation of PCBs and demethylation of MeO-PCBs. Metabolic pathways of PCBs, OH-PCBs, and MeO-PCBs in intact rice plants are proposed. The findings are important in understanding the fate of PCBs and the source of OH-PCBs in the environment

Additional file 1: of Genome-wide comparative analysis of putative Pth11-related G protein-coupled receptors in fungi belonging to Pezizomycotina

Chromosomal distribution of putative F. graminearum Pth11-related GPCR genes. Chromosome numbers are shown at the top of the chromosomes. (TIFF 39 kb