Vibrio cholerae O139 isolated from different countries, as well as from different locations within a country, were examined using macrorestriction DNA analysis to determine the clonality of the O139 strains. NotI digests of genomic DNA of representative strains from Nepal, India, Bangladesh, China, Thailand, and Malaysia revealed very similar but not identical patterns. Examinations of the banding patterns generated by pulsed-field gel electrophoresis of strains isolated within countries revealed complete homogeneity. These results further reiterate the spread of an identical clone of V. cholerae O139 although it appears that genetic polymorphism among the O139 strains is becoming apparent.
Allergic rhinitis and rhinosinusitis, common and debilitating conditions, should be managed in accordance with guideline recommendations. Guideline adherence shows regional differences. As of now, there is little data from Asia and none from Malaysia on the current treatment practices and unmet needs in the management of these conditions.
A pair of primers targeting the hlyA gene for Vibrio cholerae which could distinguish the classical from El Tor biotypes was designed and combined with other specific primers for ompW, rfb complex, and virulence genes such as ctxA, toxR, and tcpI in a multiplex PCR (m-PCR) assay. This m-PCR correctly identified 39 V. cholerae from clinical, water and seafood samples. The efficiency of this multiplex PCR (m-PCR) was compared with conventional biochemical and serogrouping methods. One O139 and 25 O1 V. cholerae strains including 10 environmental strains harbored all virulence-associated genes except 1 clinical strain which only had toxR and hlyA genes. Thirteen environmental strains were classified as non-O1/non-O139 and had the toxR and hlyA genes only. The detection limit of m-PCR was 7 x 10(4) cfu/ml. The m-PCR test was reliable and rapid and reduced the identification time to 4 h.
Classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.
Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. In this study, we use vector indices and meteorological data as predictors to develop the ML models. We trained and validated seven ML algorithms, including an ensemble ML method, and compared their performance using the receiver operating characteristic (ROC) with the area under the curve (AUC), accuracy and F1 score. Our results show that an ensemble ML such as XG Boost, AdaBoost and Random Forest perform better than the logistics regression, Naïve Bayens, decision tree, and support vector machine (SVM), with XGBoost having the highest AUC, accuracy and F1 score. Analysis of the importance of the variables showed that the container index was the least important. By removing this variable, the ML models improved their performance by at least 6% in AUC and F1 score. Our result provides a framework for future studies on the use of predictive models in the development of an early warning system.
We present a young adult female with symptoms of acute tonsillitis and tender cervical lymphadenopathy. Despite a full course of oral antibiotics, she had persistent left lower cervical lymphadenopathy measuring 2.0 x 1.5 cm at 2 weeks post-treatment. Rigid and flexible scope examinations did not reveal any abnormalities in the nasopharynx, oropharynx or hypopharynx. Tuberculosis tests were negative and blood index results were normal. Fine needle aspiration cytology revealed a non-specific granulomatous inflammatory process. Excisional lymph node biopsy was performed, and the patient was diagnosed as having Kikuchi's Disease (KD). We would like to highlight the diagnostic challenges in detecting this condition and the importance of differentiating KD from tuberculosis and malignant lymphoma, the latter of which requires aggressive treatment.
Cholera remains a major public health problem in many countries. Poor sanitation and inappropriate clean water supply, insufficient health literacy and community mobilization, absence of national plans and cross-border collaborations are major factors impeding optimal control of cholera in endemic countries. In March 2017, a group of experts from 10 Asian cholera-prone countries that belong to the Initiative against Diarrheal and Enteric Diseases in Africa and Asia (IDEA), together with representatives from the World Health Organization, the US National Institutes of Health, International Vaccine Institute, Agence de médecine préventive, NGOs (Save the Children) and UNICEF, met in Hanoi (Vietnam) to share progress in terms of prevention and control interventions on water, sanitation and hygiene (WASH), surveillance and oral cholera vaccine use. This paper reports on the country situation, gaps identified in terms of cholera prevention and control and strategic interventions to bridge these gaps.