Displaying all 6 publications

Abstract:
Sort:
  1. Chen X, Li J, Xiao S, Liu X
    Gene, 2016 Jan 15;576(1 Pt 3):537-43.
    PMID: 26546834 DOI: 10.1016/j.gene.2015.11.001
    Paphia textile is an important, aquaculture bivalve clam species distributed mainly in China, Philippines, and Malaysia. Recent studies of P. textile have focused mainly on artificial breeding and nutrition analysis, and the transcriptome and genome of P. textile have rarely been reported. In this work, the transcriptome of P. textile foot tissue was sequenced on an Illumina HiSeq™ 2000 platform. A total of 20,219,795 reads were generated, resulting in 4.08 Gb of raw data. The raw reads were cleaned and assembled into 54,852 unigenes with an N50 length of 829 bp. Of these unigenes, 38.92% were successfully annotated based on their matches to sequences in seven public databases. Among the annotated unigenes, 14,571 were assigned Gene Ontology terms, 5448 were classified to Clusters of Orthologous Groups categories, and 6738 were mapped to 228 pathways in the Kyoto Encyclopedia of Genes and Genomes database. For functional marker development, 5605 candidate simple sequence repeats were identified in the transcriptome and 80 primer pairs were selected randomly and amplified in a wild population of P. textile. A total of 36 loci that exhibited obvious repeat length polymorphisms were detected. The transcriptomic data and microsatellite markers will provide valuable resources for future functional gene analyses, genetic map construction, and quantitative trait loci mapping in P. textile.
  2. Gu Y, Liu L, Guo J, Xiao S, Fang F, Yu X, et al.
    Artif Cells Nanomed Biotechnol, 2021 Dec;49(1):30-37.
    PMID: 33467925 DOI: 10.1080/21691401.2020.1865992
    This research is focussed to quantify IGF1 by electroanalytical analysis on InterDigitated electrode surface and characterized by the microscopic observations. For the detection, antibody and aptamer were used to analyze the level of IGF1. The sandwich pattern (aptamer-IGF1-antibody) was designed on the chemically modified IDE surface and reached the limit of detection to 10 fM with 100 folds enhancement in the sensitivity. Different control experiments (absence of IGF1, binding with IGF2 and with non-complementary aptamer) were failed to show the current changes, discriminated the specific detection. A good detection strategy is to complement the currently following imaging systems for AAA.
  3. Xiao S, Jian-Feng L, Fang-Fang WAN, Xuan YU, Xiaoxiao S, Lu-Yao HAN, et al.
    Mar Environ Res, 2022 Dec;182:105727.
    PMID: 36334558 DOI: 10.1016/j.marenvres.2022.105727
    Red tide caused severe impacts on marine fisheries, ecology, economy and human life safety. The formation mechanism of the red tide is rather complicated; thus, red tide prediction and forecasting have long been a research hotspot around the globe. This study collected ocean monitoring data before and after the occurrence of red tides in Xiamen sea area from 2009 to 2017. The Pearson correlation coefficient method was used to obtain the associated factors of red tide occurrence, including water temperature, saturated dissolved oxygen, dissolved oxygen, chlorophyll-aand potential of hydrogen. Then, we built a short-time red tide prediction model based on the combination of multiple feature factors. chlorophyll-a, dissolved oxygen, saturated dissolved oxygen, potential of hydrogen, water temperature, salinity, turbidity, wind speed, wind direction and Air pressure were used as the input variables, building a short-time prediction model based on the combination of multiple feature factors to forecast red tide in the next 6 h by using the monitoring data. The accuracy of different forecast models with different feature combinations was compared. Results show that the distinguishing factors which have the most significant influence on red tide prediction in Xiamen are chlorophyll-a, dissolved oxygen, saturated dissolved oxygen, potential of hydrogen, and water temperature. the convergence speed of the Gated Recurrence Unit (GRU) prediction model based on the main feature factor proposed in this paper was faster and obtained the expected result, and the accuracy rates of the buoys are above 92%. The research shows the feasibility to use GRU network model to predict the occurrence of red tide with multi-feature factors as input parameters. the paper provides an effective method for the red tide early warning in Xiamen sea area.
  4. Gong J, Harris K, Lipnicki DM, Castro-Costa E, Lima-Costa MF, Diniz BS, et al.
    Alzheimers Dement, 2023 Aug;19(8):3365-3378.
    PMID: 36790027 DOI: 10.1002/alz.12962
    INTRODUCTION: Sex differences in dementia risk, and risk factor (RF) associations with dementia, remain uncertain across diverse ethno-regional groups.

    METHODS: A total of 29,850 participants (58% women) from 21 cohorts across six continents were included in an individual participant data meta-analysis. Sex-specific hazard ratios (HRs), and women-to-men ratio of hazard ratios (RHRs) for associations between RFs and all-cause dementia were derived from mixed-effect Cox models.

    RESULTS: Incident dementia occurred in 2089 (66% women) participants over 4.6 years (median). Women had higher dementia risk (HR, 1.12 [1.02, 1.23]) than men, particularly in low- and lower-middle-income economies. Associations between longer education and former alcohol use with dementia risk (RHR, 1.01 [1.00, 1.03] per year, and 0.55 [0.38, 0.79], respectively) were stronger for men than women; otherwise, there were no discernible sex differences in other RFs.

    DISCUSSION: Dementia risk was higher in women than men, with possible variations by country-level income settings, but most RFs appear to work similarly in women and men.

  5. Klionsky DJ, Abdelmohsen K, Abe A, Abedin MJ, Abeliovich H, Acevedo Arozena A, et al.
    Autophagy, 2016;12(1):1-222.
    PMID: 26799652 DOI: 10.1080/15548627.2015.1100356
  6. Klionsky DJ, Abdel-Aziz AK, Abdelfatah S, Abdellatif M, Abdoli A, Abel S, et al.
    Autophagy, 2021 Jan;17(1):1-382.
    PMID: 33634751 DOI: 10.1080/15548627.2020.1797280
    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links