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- 저자 : Guella, Ilaria (검색결과 3 건)
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Song, Jaewoo,Guella, Ilaria,Kwon, Ki-Yung,Cho, Hyunsoo,Park, Rojin,Asselta, Rosanna,Choi, Jong Rak Lippincott Williams Wilkins, Inc. 2009 Blood coagulation & fibrinolysis Vol.20 No.2
Hereditary coagulation factor V deficiency is a rare bleeding disorder characterized by extremely low levels of functional and immunoreactive factor V in plasma associated with moderate-to-severe bleeding symptoms. The genetic bases of factor V deficiency have been characterized only in a limited number of cases and the majority of causative mutations are truncating mutations providing only limited information about the function of subdomains and of individual residues. Here, we present the first report on a Korean family with inherited factor V deficiency. The proband is a 25-year-old man who showed normal coagulation factor levels except those for factor V antigen and activity (3 and 4%, respectively), and was only suffering from bleeding after tooth extraction. Direct sequencing of the factor V gene disclosed the already known nonsense mutation (R1133X) and a novel in-frame 6-bp deletion (6116-6121delGAACAG, corresponding to the amino-acid deletion N1982-S1983) located in the factor V C1 domain; both mutations were found in the heterozygous state. The structural and functional importance of the in-frame deletion was examined by constructing a molecular model based on the crystal structure of bovine activated factor V that has been inactivated by activated protein C. N1982 and S1983 are located on a loop that is exposed on the surface of the C1 domain, and are in close contact with another loop belonging to the A3 domain. Even though the detailed mechanism of the association of the in-frame deletion of our patient and factor V deficiency needs further investigation, this model suggests the possibility that the N1982-S1983 deletion could destabilize the C1–A3 interaction by preventing the potential formation of hydrogen bonds between K1980 and N1986 of the C1 domain with D1604 of the A3 domain. Also, because N1982 is strongly expected to be N-glycosylated judging from its structural homology to factor VIII, loss of this residue can influence proper folding of factor V, resulting in unstable structure, which is vulnerable to intracellular degradation.
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PSEN1 p.Met233Val in a Complex Neurodegenerative Movement and Neuropsychiatric Disorder
Silke Appel-Cresswell,Ilaria Guella,Anna Lehman,Dean Foti,Matthew J. Farrer 대한파킨슨병및이상운동질환학회 2018 Journal Of Movement Disorders Vol.11 No.1
Mutations in presenilin 1 (PSEN1) are the most common cause of autosomal dominant Alzheimer’s disease. Here, we report a Canadian-Vietnamese family carrying a PSEN1 p.Met233Val mutation with an exceptionally early and severe presentation that includes a wide range of atypical symptoms, including prominent ataxia, Parkinsonism, spasticity, dystonia, action tremor, myoclonus, bulbar symptoms, seizures, hallucinations and behavioral changes. Whole-exome sequencing (WES) was performed on the affected proband after many assessments over several years proved diagnostically inconclusive. The results were analyzed using the AnnEx “Annotated Exomes” browser (http://annex.can.ubc.ca), a web-based platform that facilitates WES variant annotation and interpretation. High-throughput sequencing can be especially informative for complex neurological disorders, and WES warrants consideration as a first-line clinical test. Data analyses facilitated by web-based bioinformatics tools have great potential for novel insight, although confirmatory, diagnostically accredited Sanger sequencing is recommended prior to reporting.
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Improvement of Dialysis Dosing Using Big Data Analytics
Syeda Leena Mumtaz,Abdulrahim Shamayleh,Hussam Alshraideh,Adnane Guella 대한의료정보학회 2023 Healthcare Informatics Research Vol.29 No.2
Objectives: Large amounts of healthcare data are now generated via patient health records, records of diagnosis and treatment,smart devices, and wearables. Extracting insights from such data can transform healthcare from a traditional, symptom-driven practice into precisely personalized medicine. Dialysis treatments generate a vast amount of data, with more than100 parameters that must be regulated for ideal treatment outcomes. When complications occur, understanding electrolyteparameters and predicting their outcomes to deliver the optimal dialysis dosing for each patient is a challenge. This studyfocused on refining dialysis dosing by utilizing emerging data from the growing number of dialysis patients to improve patients’quality of life and well-being. Methods: Exploratory data analysis and data prediction approaches were performed togather insights from patients’ vital electrolytes on how to improve the patients’ dialysis dosing. Four predictive models wereconstructed to predict electrolyte levels through various dialysis parameters. Results: The decision tree model showed excellentperformance and more accurate results than the support vector machine, linear regression, and neural network models. Conclusions: The predictive models identified that pre-dialysis blood urea nitrogen, pre-weight, dry weight, anticoagulation,and sex had the most significant effects on electrolyte concentrations. Such models could fine-tune dialysis dosing levels forthe growing number of dialysis patients to improve each patient’s quality of life, life expectancy, and well-being, and to reducecosts, efforts, and time consumption for both patients and physicians. The study’s results need to be validated on a largerscale.
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