Methodology: Serum samples from six BAVM patients and three control subjects were analyzed using enzyme-linked immunoabsorbent assay (ELISA) for OPN. A total of 10 BAVM patients and five control subjects were analyzed using Multiplex ELISA for MMPs. A total of 16 BAVM tissue samples and two normal brain tissue samples were analyzed using immunohistochemistry.
Result: MMP-2 and -9 were significantly higher in the serum of BAVM patients before and after treatment than in control patients. There were no significant differences of OPN and MMP-9 serum level in BAVM patients before and after treatment. MMP-2 showed a significant elevation after the treatment. Expression of OPN, MMP-2 and -9 proteins were seen in endothelial cells, perivascular cells and brain parenchyma of BAVM tissues.
Conclusion: Findings revealed that the level of MMP-2 and -9 in the serum correlated well with the expression in BAVM tissues in several cases. Knockdown studies will be required to determine the relationships and mechanisms of action of these markers in the near future. In addition, studies will be required to investigate the expression of these markers' potential applications as primary medical therapy targets for BAVM patients.
OBJECTIVE: This study investigated UTX and JMJD3 protein expression patterns in UC and assess their clinical significance.
PATIENTS AND METHODS: Immunohistochemistry (IHC) method was performed on formalin-fixed paraffin-embedded (FFPE) of UC tissues and compared to the normal bladder tissues from the autopsy specimen. The staining intensity of FFPE tissues were captured with the nuclear and overall positive pixels quantified using Aperio ImageScope software.
RESULTS: JMJD3 protein uptake was present in both nucleus and cytoplasm but UTX protein was predominantly seen in the cytoplasm of UC tissue. UTX was under expressed whereas JMJD3 was over expressed in UC compared to normal bladder. UTX and JMJD3 were not related to clinical stage and grade. However, significant association between JMJD3 expression and invasiveness of tumour (p<0.05) was noted, especially in MIBC group (88.9%). UTX and JMJD3 did not yield any significance as prognostic factors for diseasespecific survival.
CONCLUSIONS: Low expression of UTX protein in UC may indicate possible loss of its tumour suppressor activity and higher JMJD3 protein expression may indicate oncogenic activity. Hence, JMJD3 protein could be a potential diagnostic biomarker in detecting bladder UC of higher stages. Further investigation needed to study the dysregulation of this protein expression with associated gene expression.
MATERIALS AND METHODS: We analysed 122 consecutive patients with spontaneous SAH following intracranial aneurysmal and non-aneurysmal information (including patients' pattern characterisation and their possible risk factor association to pre-operative clinical decision and long-term clinical outcome) was documented and analysed.
RESULTS: The main clinical presentations for spontaneous SAH following ruptured intracranial aneurysm and nonaneurysm were headache (77%) and nausea/vomiting (62.3%). The most common sites for SAH following ruptured intracranial aneurysm rupture were the anterior and posterior communicating arteries (57.5%). Hypertension was the most common cause for SAH at 64.8%. It was found 26.2% (n=32) out of the 122 patients developed CV and DCI. The mean day of vasospasm was 6.0 ± 2.8 (range: 1-14 days) Age, length of stay, nausea/vomiting and visual field defect were significantly associated (p<0.05) with vasospasm. Mortality rate was also higher in the CV group compared to the group without CV in both at discharge and at 6 months; 281 versus 278 per 1000 and 312 vs 300 per 1000, respectively.
CONCLUSION: CV and DCI have a significant incidence among local patients with spontaneous SAH following an intracranial aneurysmal and non-aneurysmal rupture and it is associated with substantial morbidity. Prevention, effective monitoring, and early detection are keys to successful management. Regional investigation using a multicentre cohort to analyse mortality and survival rates may aid in improving national resource management of these patients.
METHODS: A double-blind randomized study was carried out with 140 colorectal cancer patients on chemotherapy. Subjects were separated into two groups to receive either placebo or MCP [30 billion colony-forming unit (CFUs) per sachet] at a dose of two sachets daily for 4 weeks, and omega-3 fatty acid at a dose of 2 g daily for 8 weeks. Outcomes measured were quality of life, side effects of chemotherapy and levels of inflammatory markers such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and C-reactive protein.
RESULTS: The supplementation with MCP and omega-3 fatty acid improved the overall quality of life and alleviated certain side effects of chemotherapy. The supplementation with MCP and omega-3 fatty acid also managed to reduce the level of IL-6 (P = 0.002). There was a significant rise in the placebo group's serum TNF-α (P = 0.048) and IL-6 (P = 0.004).
CONCLUSION: The combined supplementation with MCP and omega-3 fatty acid may improve quality of life, reduce certain inflammatory biomarkers and relieve certain side effects of chemotherapy in colorectal patients on chemotherapy.
METHODS: This is a prospective block randomized, non-blinded study conducted at a single tertiary hospital. Patients undergoing elective laparoscopic cholecystectomy between August 2017 and October 2018 were recruited and randomized into Handout Assisted Consent (HC) and Verbal Consent (VC) group. The HC group was given an adjunct handout on laparoscopic cholecystectomy during consent process in addition to the standard verbal consent. A validated open-ended verbal understanding and recall questionnaire was administered to all patients in both groups at Day 1, 30 and 90 after surgery. Patient satisfaction of the consent process was evaluated with Likert scale.
RESULTS: A total of 79 patients were enrolled, 41 patients and 38 patients in VC and HC groups respectively. Level of understanding among patients were equal and consistent across time in both groups (P > 0.05). There was significant decline (P 0.05).
CONCLUSION: There is good consistent understanding of the surgery in both groups. However, recall of specific surgical consent items decreased significantly over time in both groups. Handouts may have increased satisfaction among patients but did not improve recall in this preliminary study.
TRIAL REGISTRATION: MREC No.:201783-5468.
METHODS: For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. The six different text classification techniques were applied on these 43 master feature vectors to construct a classification model that can predict the cause of death. Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall.
RESULTS: From experiments, it was found that that unigram features obtained the highest performance compared to bigram, trigram, and hybrid-gram features. Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. Furthermore, the chi-square feature reduction approach outperformed Pearson correlation, and information gain approaches. Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier.
CONCLUSION: Our results and comparisons hold practical importance and serve as references for future works. Moreover, the comparison outputs will act as state-of-art techniques to compare future proposals with existing automated text classification techniques.
METHODS: Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system.
RESULTS: Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines.
CONCLUSION: The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.