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  1. Moy F, Chang E, Kee K
    Iran J Public Health, 2011 Dec;40(4):44-53.
    PMID: 23113102
    BACKGROUND: Reduced handgrip strength is an aging process that significantly influences the living activities of elderly. It is linked to premature mortality, disability and other health complications among elderly. Therefore, we aim to determine the associated predictors with handgrip strength among the free living elderly in Malaysia.

    METHODS: This was a cross sectional study conducted in a rural state in Malaysia. A total of 434 elderly individuals performed handgrip assessment. Socio-demographic characteristics, medical conditions, occupational history, functional ability (ADL) and depression (GDS) were enquired. Anthropometric measurements (weight and height) were also obtained.

    RESULTS: Majority of the respondents were Malays with mean age of 67.9 ± 6.3 years. Maximum handgrip strength of males and females were 28.8±9.2 kg and 18.9±6.9 kg respectively (P<0.05). The aborigines had significantly lower handgrip strength (P<0.05) compared to Malays, Chinese and Indians. Handgrip strength was positively correlated (P<0.05) with weight, height and ADL, while negatively associated (P<0.05) with GDS for both gender. In the multivariate linear regression analysis; weight, height and race significantly predicted handgrip strength among both male and female elderly after adjustment for all potential confounders. However, GDS and ADL were only found to significantly predict handgrip strength among the male elderly; while age was only significant among the females.

    CONCLUSION: Our sample population has significantly lower handgrip strength than the Western counterpart. Weight, height and race significantly predict handgrip strength among both male and female elderly. GDS, ADL are only found to be significant in males while age was only significant among the females.

  2. Park S, Jalaludin I, Hwang H, Ko M, Adelipour M, Hwan M, et al.
    PMID: 37480686 DOI: 10.1016/j.jchromb.2023.123828
    In recent years, extracellular vesicles (EVs) have gained attention for their potential as biomarkers for the early diagnosis and treatment of various diseases. Traditionally, EV isolation has relied exclusively on ultracentrifugation. However, alternative enrichment methods such as size-exclusion chromatography (SEC) and polyethylene glycol-based precipitation have been introduced. This study utilized SEC as a characterization tool to assess the efficiency of EV isolation. Urinary EVs isolated from human urine using centrifugation (40,000 × g) were analyzed using an SEC column with a pore size of 1000 Å, an inner diameter of 7.8 mm, and a length of 300 mm. The EVs were detected sequentially using UV (280 nm) and fluorescence (λex/em = 550 nm/565 nm); the EVs were observed at approximately 6 min, while the proteins were observed at approximately 12 min. The repeated centrifugation enrichment steps resulted in an increase in EV peaks and a decrease in protein peaks. SEC analysis of the enriched EV samples confirmed that a four-cycle repetition of centrifugation is necessary for successful EV enrichment and removal of non-EV proteins from 40 mL of human urine.
  3. Vui-Kee K, Mohd Dali AZ, Mohamed Rose I, Ghazali R, Jamal R, Mokhtar NM
    Kaohsiung J. Med. Sci., 2012 May;28(5):243-50.
    PMID: 22531302 DOI: 10.1016/j.kjms.2011.11.007
    Nonepithelial ovarian cancer (NEOC) is a rare cancer that is often misdiagnosed as other malignant tumors. Research on this cancer using fresh tissues is nearly impossible because of its limited number of samples within a limited time provided. The study is to identify potential genes and their molecular pathways related to NEOC using formalin-fixed paraffin embedded samples. Total RNA was extracted from eight archived NEOCs and seven normal ovaries. The RNA samples with RNA integrity number >2.0, purity >1.7 and cycle count value <28 cycles were hybridized to the Illumina Whole-Genome DASL assay (cDNA-mediated annealing, selection, extension, and ligation). We analyzed the results using the GeneSpring GX11.0 and FlexArray software to determine the differentially expressed genes. Microarray results were validated using an immunohistochemistry method. Statistical analysis identified 804 differentially expressed genes with 443 and 361 genes as overexpressed and underexpressed in cancer, respectively. Consistent findings were documented for the overexpression of eukaryotic translation elongation factor 1 alpha 1, E2F transcription factor 2, and fibroblast growth factor receptor 3, except for the down-regulated gene, early growth response 1 (EGR1). The immunopositivity staining for EGR1 was found in the majority of cancer tissues. This finding suggested that the mRNA level of a transcript did not always match with the protein expression in tissues. The current gene profile can be the platform for further exploration of the molecular mechanism of NEOC.
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