Placenta praevia: Preach and perception

Placenta praevia is a known obstetric condition that causes complications to mother and fetus. This study was done to evaluate the knowledge of placenta praevia amongst the obstetric patients. A cross sectional study was carried out in Hospital Ipoh, Perak among 323 antenatal and postnatal patients. Socio-demographic parameters (ie age, race, parity, occupation, educational level) and history of placenta praevia were studied in relation to level of knowledge and attitude towards placenta praevia. Twenty (6.2%) from 323 women had current or past history of placenta praevia. Three had history of placenta praevia while 17 had current placenta praevia with prevalence of 5.3%. The mean score of knowledge achieved by patients was 11.8 which indicated overall poor knowledge. Occupation, level of education and history of placenta praevia were found to have a relationship with level of knowledge regarding placenta praevia in all obstetric patients. There was a significant relationship between attitude of patients with current and history of placenta praevia to level of knowledge regarding placenta praevia. (p=0.037, <0.05). In conclusion, the knowledge and attitude towards placenta praevia among obstetric patients in Hospital Ipoh was better in those who had higher education status, white-collar occupation and currently pregnant with placenta praevi

Non-invasive diagnosis of lung tuberculosis in children by single voxel 1H-magnetic resonance spectroscopy

Our previous study showed that 1H-magnetic resonance spectroscopy (1H-MRS) can detect lipid peaks characteristic for Mycobacterium tuberculosis infection in cerebral lesions of young children; therefore, we aimed to extend and validate the application of 1H-MRS for the diagnosis of active pulmonary tuberculosis lesions in three adolescent patients. Here, we document lipid peaks characteristic for M. tuberculosis infection by 1H-MRS from lung tissue surrounding lung cavities of two patients whose sputum samples were positive for acid-fast bacilli by microscopy and positive for M. tuberculosis by genetic testing, indicating active tuberculosis. A similar lipid peak was found also in the pleural effusion of a third patient with concurrent lung cavity compatible with active tuberculosis. However, in a patient with a pyogenic pulmonary abscess, 1H-MRS of the drained pus displayed different characteristic peaks but no lipid peak at all. Conclusion: Our findings further validate 1H-MRS as a rapid, non-invasive, and specific diagnostic tool for active tuberculosis in children with microbiologically documented infection outside the central nervous system, specifically in the lung

Non-invasive diagnosis of lung tuberculosis in children by single voxel ¹H-magnetic resonance spectroscopy

Our previous study showed that (1)H-magnetic resonance spectroscopy ((1)H-MRS) can detect lipid peaks characteristic for Mycobacterium tuberculosis infection in cerebral lesions of young children; therefore, we aimed to extend and validate the application of (1)H-MRS for the diagnosis of active pulmonary tuberculosis lesions in three adolescent patients. Here, we document lipid peaks characteristic for M. tuberculosis infection by (1)H-MRS from lung tissue surrounding lung cavities of two patients whose sputum samples were positive for acid-fast bacilli by microscopy and positive for M. tuberculosis by genetic testing, indicating active tuberculosis. A similar lipid peak was found also in the pleural effusion of a third patient with concurrent lung cavity compatible with active tuberculosis. However, in a patient with a pyogenic pulmonary abscess, (1)H-MRS of the drained pus displayed different characteristic peaks but no lipid peak at all. CONCLUSION: Our findings further validate (1)H-MRS as a rapid, non-invasive, and specific diagnostic tool for active tuberculosis in children with microbiologically documented infection outside the central nervous system, specifically in the lungs

Difference-based clustering of short time-course microarray data with replicates

<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p