Serological detection of anti-leptospira antibodies among animal caretakers, dogs and cats housed in animal shelters in Peninsular Malaysia

Leptospirosis is a worldwide zoonotic disease caused by Leptospira spp. and it has emerged as one of the major public health issues worldwide. Despite extensive studies, information regarding leptospirosis in animal shelters in Malaysia is still scarce. The aim of this study was to determine anti-Leptospira antibodies and the most common circulating serogroups among humans and animals in animal shelters in west and south parts of Peninsular Malaysia. Blood samples were obtained from 58 humans, 127 dogs, and 47 cats, that were recruited from two shelters. All humans and dogs appeared healthy, except few cats showed clinical signs of mild feline upper respiratory disease. Microscopic Agglutination Test (MAT) was used to detect anti-Leptospira antibodies against 20 pathogenic serovars. Based on the cut-off antibody titre ≥ 1:100, the sero-detection of Leptospira spp. in human, dogs, and cats were as 8.62%, 20.47%, and 14.89%, respectively. Serogroup Bataviae was found in human, dogs and cats, whereas Bataviae, Javanica, and Ballum were the common serogroups among dogs and cats. Anti-Leptospira antibodies titres were in the range from 1:100 to 1:200 in human and 1:100 to 1:400 in sheltered animals. Sero-detection studies of anti-Leptospira antibodies in shelters environment worldwide and regionally is necessary to increase the public health awareness and to understand the risk of this zoonotic disease. Furthermore, data regarding the predominant serogroups is needed in a local setting for further vaccination development studies. More studies are warranted to investigate the role of sheltered animals in leptospiral transmission in its environment

MANUAL FOR IBADAH CAMP ORGANIZER A PART OF THE IIUM FLAGSHIP ENTITLED “GENDER DYSPHORIA”

Maknyah or male-to-female transgender are those who transform their identity biologically from male to female through crossdressing and their lifestyle associated with homosexuality. Crossdressing and homosexuality are unlawful in accordance with Islamic practices. Often, these transgenders are associated with being sex workers in major hotspots such as in Federal Territory Kuala Lumpur, Selangor, Negeri Sembilan, Pulau Pinang, Pahang and Sarawak.1 It is estimated that the population size of sex workers in Malaysia in 2018 is 37,000 (22,000 Female Sex Workers and 15,000 Transgender Sex Workers). Despite the reducing number of transgender sex workers in Malaysia (as compared to previous Key Population Estimates in 2010), it is still a concern to Muslims and this trend needs to be relieved promptly

First report of pathogenic Leptospira spp. isolated from urine and kidneys of naturally infected cats

Leptospirosis is one of the most widespread zoonotic diseases and can infect both humans and animals worldwide. Healthy cat, as a potential source of exposure to humans, are likely underestimated owing to the lack of overt clinical signs associated with Leptospira spp. infection in this species. The aim of the study was to determine the exposure, shedding, and carrier status of leptospires in shelter cats in Malaysia by using serological, molecular, and bacteriological methods. For this study, 82 healthy cats from two shelters were sampled. The blood, urine, and kidneys were tested using the microscopic agglutination test (MAT), polymerase chain reaction (PCR), and bacterial culture. On the basis of serological, molecular, and/or culture techniques, the total detection of leptospiral infection was 29.3% (n = 24/82). Through culture techniques, 16.7% (n = 4/24) of the cats that tested positive were carriers with positive kidney cultures, and one cat was culture positive for both urine and kidney. The Leptospira spp. isolates were identified as pathogenic L. interrogans serovar Bataviae through serological and molecular methods. Through serological techniques, 87.5% (n = 21/24) had positive antibody titers (100–1600) and most of the Bataviae serogroup (n = 19/21). Using PCR, 16.7% (n = 4/24) of cats were shown to have pathogenic Leptospira spp. DNA in their urine. Furthermore, three out of four culture positive cats were serology negative. The present study reports the first retrieval of pathogenic leptospires from urine and kidneys obtained from naturally infected cats. The results provide evidence of the potential role of naturally infected cats in the transmission of leptospires. Additionally, leptospiral infection occurs sub-clinically in cats. The culture isolation provides evidence that healthy cats could be reservoirs of leptospiral infection, and this information may promote the development of disease prevention strategies for the cat population

Hand Gesture Recognition Based on Continuous Wave (CW) Radar Using Principal Component Analysis (PCA) and K-Nearest Neighbor (KNN) Methods

Human-computer interaction (HCI) is a field of study studying how people and computers interact. One of the most critical branches of HCI is hand gesture recognition, with most research concentrating on a single direction. A slight change in the angle of hand gestures might cause the motion to be misclassified, thereby degrading the performance of hand gesture detection. Therefore, to improve the accuracy of hand gesture detection, this paper focuses on analyzing hand gestures based on the reflected signals from two directions, which are front and side views. The radar system employed in this paper is equipped with two sets of 24 GHz continuous wave (CW) monostatic radar sensors with a sampling rate of 44.1 kHz. Four different hand gestures, namely close hand, open hand, OK sign, and pointing down, are collected using SignalViewer software. The data is stored as a waveform audio file format (WAV) where one data consists of 20 segments, and the data is then examined by using MATLAB software to be segmented. To evaluate the effectiveness of the classification system, principal component analysis (PCA) and k-nearest neighbor (KNN) are integrated. The PCA findings are depicted in Pareto and 2-D scatter plot for both radar directions. The Leave-One-Out (LOO) method is then used in this analysis to verify the accuracy of the classification method, which is represented in the confusion matrix. At the end of the analysis, the classification results indicated that both angles achieved near-perfect accuracy for most hand gestures