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  1. Guo L, Zhu XQ, Hu CH, Ristaino JB
    Phytopathology, 2010 Oct;100(10):997-1006.
    PMID: 20839935 DOI: 10.1094/PHYTO-05-09-0126
    One hundred isolates of Phytophthora infestans collected from 10 provinces in China between 1998 and 2004 were analyzed for mating type, metalaxyl resistance, mitochondrial DNA (mtDNA) haplotype, allozyme genotype, and restriction fragment length polymorphism (RFLP) with the RG-57 probe. In addition, herbarium samples collected in China, Russia, Australia, and other Asian countries were also typed for mtDNA haplotype. The Ia haplotype was found during the first outbreaks of the disease in China (1938 and 1940), Japan (1901, 1930, and 1931), India (1913), Peninsular Malaysia (1950), Nepal (1954), The Philippines (1910), Australia (1917), Russia (1917), and Latvia (1935). In contrast, the Ib haplotype was found after 1950 in China on both potato and tomato (1952, 1954, 1956, and 1982) and in India (1968 and 1974). Another migration of a genotype found in Siberia called SIB-1 (Glucose-6-phosphate isomerase [Gpi] 100/100, Peptidase [Pep] 100/100, IIa mtDNA haplotype) was identified using RFLP fingerprints among 72% of the isolates and was widely distributed in the north and south of China and has also been reported in Japan. A new genotype named CN-11 (Gpi 100/111, Pep 100/100, IIb mtDNA haplotype), found only in the south of China, and two additional genotypes (Gpi 100/100, Pep 100/100, Ia mtDNA haplotype) named CN-9 and CN-10 were identified. There were more diverse genotypes among isolates from Yunnan province than elsewhere. The SIB-1 (IIa) genotype is identical to those from Siberia, suggesting later migration of this genotype from either Russia or Japan into China. The widespread predominance of SIB-1 suggests that this genotype has enhanced fitness compared with other genotypes found. Movement of the pathogen into China via infected seed from several sources most likely accounts for the distribution of pathogen genotypes observed. MtDNA haplotype evidence and RFLP data suggest multiple migrations of the pathogen into China after the initial introduction of the Ia haplotype in the 1930s.
  2. Gao X, Guo L, Li J, Thu HE, Hussain Z
    J Control Release, 2018 12 28;292:29-57.
    PMID: 30359665 DOI: 10.1016/j.jconrel.2018.10.024
    Lung cancer (LC) is the second most prevalent type of cancer and primary cause of mortality among both men and women, worldwide. The most commonly employed diagnostic modalities for LC include chest X-ray (CXR), magnetic-resonance-imaging (MRI), computed tomography (CT-scan), and fused-positron-emitting-tomography-CT (PET-CT). Owing to several limitations associated with the use of conventional diagnostic tools such as radiation burden to the patient, misleading diagnosis ("missed lung cancer"), false staging and low sensitivity and resolution, contemporary diagnostic regimen needed to be employed for screening of LC. In recent decades, nanotechnology-guided interventions have been transpired as emerging nanoimaging probes for detection of LC at advanced stages, while producing signal amplification, better resolution for surface and deep tissue imaging, and enhanced translocation and biodistribution of imaging probes within the cancerous tissues. Besides enormous potential of nanoimaging probes, nanotechnology-based advancements have also been evidenced for superior efficacy for treatment of LC and abolishing pulmonary metastasis (PM). The success of nanotherapeutics is due to their ability to maximise translocation and biodistribution of anti-neoplastic agents into the tumor tissues, improve pharmacokinetic profiles of anti-metastatic agents, optimise target-specific drug delivery, and control release kinetics of encapsulated moieties in target tissues. This review aims to overview and critically discuss the superiority of nanoimaging probes and nanotherapeutics over conventional regimen for early detection of LC and abolishing PM. Current challenges to clinical transition of nanoimaging probes and therapeutic viability of nanotherapeutics for treatment for LC and PM have also been pondered.
  3. Song YZ, Zhang ZH, Lin WX, Zhao XJ, Deng M, Ma YL, et al.
    PLoS ONE, 2013;8(9):e74544.
    PMID: 24069319 DOI: 10.1371/journal.pone.0074544
    The human SLC25A13 gene encodes citrin, the liver-type mitochondrial aspartate/glutamate carrier isoform 2 (AGC2), and SLC25A13 mutations cause citrin deficiency (CD), a disease entity that encompasses different age-dependant clinical phenotypes such as Adult-onset Citrullinemia Type II (CTLN2) and Neonatal Intrahepatic Cholestasis caused by Citrin Deficiency (NICCD). The analyses of SLC25A13 gene and its protein/mRNA products remain reliable tools for the definitive diagnoses of CD patients, and so far, the SLC25A13 mutation spectrum in Chinese CD patients has not been well-characterized yet.
  4. Liu L, Mo Z, Liang Z, Zhang Y, Li R, Ong KC, et al.
    BMC Med, 2015;13:226.
    PMID: 26381232 DOI: 10.1186/s12916-015-0448-7
    To investigate the long-term effects on immunity of an inactivated enterovirus 71 (EV71) vaccine and its protective efficacy.
  5. Chaisson MJP, Sanders AD, Zhao X, Malhotra A, Porubsky D, Rausch T, et al.
    Nat Commun, 2019 04 16;10(1):1784.
    PMID: 30992455 DOI: 10.1038/s41467-018-08148-z
    The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.
  6. 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
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