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Background and Aims This study aimed atinvestigating the relationship between speech-frequency hearing loss (SFHL), high-frequency hearing loss (HFHL), and cognitive impairment (CI) and then to determine whether there are any differences in gender among older community dwellers in China. Methods 1012 adults aged ≥ 60 years (428 males; average age, 72.61 ± 5.51 years) and living in Chongming District, Shanghai were enrolled in the study. We used the audiometric definition of hearing loss (HL) adopted by the World Health Organization (WHO). Speech-frequencies were measured at 0.5 kHz, 1 kHz, 2 kHz, and 4 kHz; high-frequencies were measured at 4 kHz and 8 kHz. Pure tone average (PTA) was measured as hearing sensitivity. Cognitive performance was measured using the mini mental state examination (MMSE). Results Our studies demonstrated a 37.6% prevalence of HL in males and a 36.0% prevalence of HL in females. Adjusted for confounding variables, the results from a multivariate analysis showed that SFHL was associated with CI in females (OR = 2.922, 95% Confidence Interval = 1.666–5.124) and males (OR = 2.559, 95% Confidence Interval = 1.252–5.232). However, HFHL was associated with CI only in females (OR = 3.490, 95% Confidence Interval = 1.834–6.643). HL was associated with poorer cognitive scores (P P Conclusions The associations between HL and CI varied according to gender in older community-dwellers, suggesting that different mechanisms are involved in the etiology of HL. Moreover, hearing sensitivity was negatively associated with cognition scores; therefore, early screening for HL and CI among older community-dwelling adults is advised.

Both sarcopenia and loss of teeth are associated with aging. The purpose of this study was to investigate potential relationships between tooth loss and sarcopenia and its components in suburban community-dwelling older adults of Shanghai and Tianjin, China. The subjects were 1494 people over 60 years of age (40.7% men; aged 71.64 ± 5.97 years) from Chongming District of Shanghai and Hangu District of Tianjin. Asian Working Group for Sarcopenia(AWGS) criteria were used to define sarcopenia. Muscle mass, muscle strength, and physical performance were assessed using a bioelectrical impedance analyzer, a grip strength test, and a four-meter walk test, respectively. The subjects were divided into groups depending on self-reported loss of teeth. Our studies found no correlation between tooth loss and sarcopenia or muscle mass. However, the walking speed of female participants with at least 10 teeth lost was 0.059 m/s slower than that of participants with fewer than 10 teeth lost (p p = 0.023). These results are consistent with the importance of good oral hygiene in preventing declines of physical performance in older adults.

Bacillus thuringiensis (Bt) is efficient, strongly specific, and avirulent to humans, making it one of the most popular biopesticides in the world. Bt LLP29 is a mosquitocidal strain that was first isolated from Magnolia denudata. To understand its molecular mechanism against mosquitoes, the genome of Bt LLP29 was sequenced and annotated in this study. The LLP29 genome was found to have a total length of 5.99 Mb, with an average G + C content of 35.21%. A total of 6107 coding sequences were also detected, together with 42 rRNAs and 124 tRNAs and 135 other RNAs. With the help of annotation databases, including GO, COG, KEGG, Nr and Swiss-Prot, most unigene functions were identified. At the same time, a collinear analysis was performed on the genome of LLP29. There were also some virulence genes detected, including cry, chitinase, zwittermicin and vip.

BackgroundLeaves of the medicinal plantAmpelopsis grossedentata, which is commonly known as vine tea, are used widely in the traditional Chinese beverage in southwest China. The leaves contain a large amount of dihydromyricetin, a compound with various biological activities. However, the transcript profiles involved in its biosynthetic pathway in this plant are unknown.ResultsWe conducted a transcriptome analysis of both young and old leaves of the vine tea plant using Illumina sequencing. Of the transcriptome datasets, a total of 52.47 million and 47.25 million clean reads were obtained from young and old leaves, respectively. Among 471,658 transcripts and 177,422 genes generated, 7768 differentially expressed genes were identified in leaves at these two stages of development. The phenylpropanoid biosynthetic pathway of vine tea was investigated according to the transcriptome profiling analysis. Most of the genes encoding phenylpropanoid biosynthesis enzymes were identified and found to be differentially expressed in different tissues and leaf stages of vine tea and also greatly contributed to the biosynthesis of dihydromyricetin in vine tea.ConclusionsTo the best of our knowledge, this is the first formal study to explore the transcriptome ofA. grossedentata.The study provides an insight into the expression patterns and differential distribution of genes related to dihydromyricetin biosynthesis in vine tea. The information may pave the way to metabolically engineering plants with higher flavonoid content.

Heavy metals in the agricultural soils of reclaimed mining areas can contaminate food and endanger human health. The objective of this study is to effectively estimate the concentrations of heavy metals, such as zinc, chromium, arsenic, and lead, using hyperspectral sensor data and the random forest (RF) algorithm in the study area of Xuzhou, China. The RF's built-in feature selection ability and modeling expressive ability in heavy metal estimation of soil were explored. After the preprocessing of the spectrum obtained by an ASD (analytical spectral device) field spectrometer, the random forest algorithm was carried out to establish the estimation model based on the correlation-selected features and the full-spectrum features respectively. Results of all the different processes were compared with classical approaches, such as partial least squares (PLS) regression and support vector machine (SVM). In all the experimental results, from the perspective of models, the best estimation model for Zn (R2 = 0.9061; RMSE = 6.5008) is based on the full-spectrum data of continuum removal (CR) pretreatment, and the best models for Cr (R2 = 0.9110; RMSE = 4.5683), As (R2 = 0.9912; RMSE = 0.5327), and Pb (R2 = 0.9756; RMSE = 1.1694) are all derived from the correlation-selected features. And these best models of these heavy metals are all established by the RF method. The experiments in this paper show that random forests can make full use of the input spectral data in the estimation of four kinds of heavy metals, and the obtained models are superior to those established by traditional methods.