Humans ; Infant, Newborn ; Neonatal Screening

BACKGROUND: As tuberculous and nontuberculous mycobacterial infections are increasing, it is very important to differentiate the myobacterial species. High performance liquid chromatography (HPLC) method has been proven to be a useful technique for the identification of mycobacteria. The purpose of this study was to investigate the identification rate using HPLC and to know nontuberculous mycobacterial distribution in Ulsan University Hospital. METHOD: Mycobacteria grew in 959 clinical specimens, which were analyzed by HPLC, and their distribution was reviewed by retrospective studies. RESULTS: The patterns of HPLC were divided into single, double, and triple cluster groups which consist of 9, 20, and 4 species of mycobacteria respectively. The identification rate of mycobacteria by HPLC was 98.9%, And the rate of nontuberculous mycobacteria in mycobacterial culture positive specimens was 12.2%. CONCLUSION: HPLC is an excellent tool for mycobacterial identification. And the culture rate of nontuberculous mycobacteria in clinical specimens is increasing in Korea.
Chromatography, High Pressure Liquid ; Chromatography, Liquid* ; Korea ; Mycobacterium tuberculosis ; Nontuberculous Mycobacteria ; Retrospective Studies ; Ulsan

BACKGROUND: Infections caused by mycobacteria have been significantly increasing. Due to the difficulty of making a decision about the pathogenicity of mycobacteria, species-level identification is very important for patients' diagnosis and treatment. The purpose of this study was to identify mycobacteria species using a high performance liquid chromatography (HPLC) method and to provide an initial database for the distribution of mycobacteria in Korea. METHODS: Acid fast bacteria isolated from 3,107 clinical specimens were identified by mycolic acid analysis using HPLC. The HPLC patterns were compared with those of standard mycobacteria species. RESULTS: The HPLC patterns were divided into single, double, and triple cluster groups, each group comprising 9, 20, and 4 species, respectively. Mycobacteria and non-tuberculous mycobacteria (NTM) were identifies by HPLC at the rates of 99.5% and 95.6%, respectively. NTM was isolated in 12.4% of the mycobacteria positive specimens. This study also found that there were 20 different NTM species with the distribution of each species ranging from 0.3% to 15.9% of the total NTM. While the rate of NTM has been increasing in Korea, M. avium-intracellulare, M. fortuitum, and M. chelonae are relatively decreasing, and M. kansasii and M. gordonae are relatively increasing. CONCLUSIONS: HPLC method was highly discriminative for the identification of NTM in clinical specimens.
Bacterial Typing Techniques ; Chromatography, High Pressure Liquid/*methods ; Hospitals, University ; Humans ; Korea ; Mycobacteria, Atypical/chemistry/*isolation & purification ; Mycobacterium Infections, Atypical/drug therapy/microbiology ; Mycolic Acids/analysis

BACKGROUND: Infections caused by nontuberculous mycobacteria (NTM) are significantly increasing over the last decade. Due to the uncertainty in the clinical significance of these organisms, their effective diagnosis and treatment has been challenging. The purpose of this study was to investigate the distribution and clinical significance of NTM in clinical specimens. METHODS: Acid-fast culture positive 3,107 clinical specimens were identified by mycolic acid analysis using high performance liquid chromatography (HPLC.) The HPLC patterns of 384 NTM strains were compared with those of standard mycobacterium species. Clinical significance of NTM was investigated by a retrospective study including acid-fast stain and culture, medical history, symptoms and signs, radiological and other laboratory findings, pathologic findings, response to treatment, and follow-up study, and was confirmed according to the guideline of American Thoracic Society. RESULTS: Among the 3,107 Mycobacterium-positive specimens, 384 (12.4%) were found to be positive for NTM. Of these, 367 (95.6%) were successfully identified by HPLC as 19 different species, each of which comprising 0.3% to 15.9% of the total NTM, Studies on the pathogenic role of NTM showed that 0~79.6% of each species or 0~100% of isolates from each specimen could be considered clinically significant. CONCLUSION: HPLC method is highly discriminative for the identification of NTM in clinical specimens. When NTM is isolated from clinical specimens in the Ulsan area, the findings from this study could serve as a database on which to determine its clinical significance depending on species type and also specimen type.
Chromatography, High Pressure Liquid ; Chromatography, Liquid ; Follow-Up Studies ; Mycobacterium ; Mycolic Acids ; Nontuberculous Mycobacteria ; Retrospective Studies ; Uncertainty

No abstract available.
Child* ; Hematuria* ; Humans ; Jeollabuk-do* ; Prevalence*

No abstract available.
Antibody Formation* ; Chickenpox*

Cystitis ; diagnosis ; Cystoscopy ; methods ; Diagnosis, Differential ; Female ; Humans ; Middle Aged ; Tomography, X-Ray Computed ; Xanthomatosis ; diagnosis

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer’s disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer’s Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.