Mahidol University

About: Mahidol University is a education organization based out in Bangkok, Nakhon Pathom, Thailand. It is known for research contribution in the topics: Population & Malaria. The organization has 23758 authors who have published 39761 publications receiving 878781 citations.

Spiroindolone KAE609 for Falciparum and Vivax Malaria

Abstract: BACKGROUND KAE609 (cipargamin; formerly NITD609, Novartis Institute for Tropical Diseases) is a new synthetic antimalarial spiroindolone analogue with potent, dose-dependent antimalarial activity against asexual and sexual stages of Plasmodium falciparum. METHODS We conducted a phase 2, open-label study at three centers in Thailand to assess the antimalarial efficacy, safety, and adverse-event profile of KAE609, at a dose of 30 mg per day for 3 days, in two sequential cohorts of adults with uncomplicated P. vivax malaria (10 patients) or P. falciparum malaria (11). The primary end point was the parasite clearance time. RESULTS The median parasite clearance time was 12 hours in each cohort (interquartile range, 8 to 16 hours in patients with P. vivax malaria and 10 to 16 hours in those with P. falciparum malaria). The median half-lives for parasite clearance were 0.95 hours (range, 0.68 to 2.01; interquartile range, 0.85 to 1.14) in the patients with P. vivax malaria and 0.90 hours (range, 0.68 to 1.64; interquartile range, 0.78 to 1.07) in those with P. falciparum malaria. By comparison, only 19 of 5076 patients with P. falciparum malaria (<1%) who were treated with oral artesunate in Southeast Asia had a parasite clearance half-life of less than 1 hour. Adverse events were reported in 14 patients (67%), with nausea being the most common. The adverse events were generally mild and did not lead to any discontinuations of the drug. The mean terminal half-life for the elimination of KAE609 was 20.8 hours (range, 11.3 to 37.6), supporting a once-daily oral dosing regimen. CONCLUSIONS KAE609, at dose of 30 mg daily for 3 days, cleared parasitemia rapidly in adults with uncomplicated P. vivax or P. falciparum malaria. (Funded by Novartis and others; ClinicalTrials.gov number, NCT01524341.)

Plant diversity increases with the strength of negative density dependence at the global scale.

Abstract: Theory predicts that higher biodiversity in the tropics is maintained by specialized interactions among plants and their natural enemies that result in conspecific negative density dependence (CNDD). By using more than 3000 species and nearly 2.4 million trees across 24 forest plots worldwide, we show that global patterns in tree species diversity reflect not only stronger CNDD at tropical versus temperate latitudes but also a latitudinal shift in the relationship between CNDD and species abundance. CNDD was stronger for rare species at tropical versus temperate latitudes, potentially causing the persistence of greater numbers of rare species in the tropics. Our study reveals fundamental differences in the nature of local-scale biotic interactions that contribute to the maintenance of species diversity across temperate and tropical communities.

CNN-based image analysis for malaria diagnosis

Abstract: Malaria is a major global health threat. The standard way of diagnosing malaria is by visually examining blood smears for parasite-infected red blood cells under the microscope by qualified technicians. This method is inefficient and the diagnosis depends on the experience and the knowledge of the person doing the examination. Automatic image recognition technologies based on machine learning have been applied to malaria blood smears for diagnosis before. However, the practical performance has not been sufficient so far. This study proposes a new and robust machine learning model based on a convolutional neural network (CNN) to automatically classify single cells in thin blood smears on standard microscope slides as either infected or uninfected. In a ten-fold cross-validation based on 27,578 single cell images, the average accuracy of our new 16-layer CNN model is 97.37%. A transfer learning model only achieves 91.99% on the same images. The CNN model shows superiority over the transfer learning model in all performance indicators such as sensitivity (96.99% vs 89.00%), specificity (97.75% vs 94.98%), precision (97.73% vs 95.12%), F1 score (97.36% vs 90.24%), and Matthews correlation coefficient (94.75% vs 85.25%).

The Effects of Sericin Cream on Wound Healing in Rats

Abstract: Sericin has good hydrophilic properties, compatibility, and biodegradation, it can be used as a wound-healing agent. We evaluated the effects of sericin on wound healing and wound size reduction using rats by generating two full-thickness skin wounds on the dorsum. Group 1 animals were treated with Betadine on left-side (control) wounds and, with 8% sericin cream on right-side (treated) wounds. Group 2, cream base (formula control) and 8% sericin cream (treated) were topically applied to left-, and right-side wounds respectively. Sericin-treated wounds had much smaller inflammatory reactions, and wound-size reduction was much greater than in the control throughout the inspection period. Mean time in days for 90% healing from sericin-treated wounds was also much less than for cream base-treated wounds. Histological examination after 15 d of treatment with 8% sericin cream revealed complete healing, no ulceration, and an increase in collagen as compared to cream base-treated wounds, which showed some ulceration and acute inflammatory exudative materials.