Effects of GnRH vaccination in wild and captive African Elephant bulls (Loxodonta africana) on reproductive organs and semen quality

OBJECTIVES: Although the African elephant (Loxodonta africana) is classified as endangered by the International Union for Conservation of Nature (IUCN), in some isolated habitats in southern Africa, contraception is of major interest due to local overpopulation. GnRH vaccination has been promoted as a non-invasive contraceptive measure for population management of overabundant wildlife. We tested the efficacy of this treatment for fertility control in elephant bulls. METHODS: In total, 17 male African elephants that were treated with a GnRH vaccine were examined in two groups. In the prospective study group 1 (n = 11 bulls, ages: 8±36 years), semen quality, the testes, seminal vesicles, ampullae and prostate, which were all measured by means of transrectal ultrasound, and faecal androgen metabolite concentrations were monitored over a three-year period. Each bull in the prospective study received 5 ml of Improvac® (1000 μg GnRH conjugate) intramuscularly after the first examination, followed by a booster six weeks later and thereafter every 5±7 months. In a retrospective study group (group 2, n = 6, ages: 19±33 years), one examination was performed on bulls which had been treated with GnRH vaccine for 5±11 years. RESULTS: In all bulls of group 1, testicular and accessory sex gland sizes decreased significantly after the third vaccination. In six males examined prior to vaccination and again after more than five vaccinations, the testis size was reduced by 57.5%. Mean testicular height and length decreased from 13.3 ± 2.6 cm x 15.2 ± 2.8 cm at the beginning to 7.6 ± 2.1 cm x 10.2 ± 1.8 cm at the end of the study. Post pubertal bulls (>9 years, n = 6) examined prior to vaccination produced ejaculates with viable spermatozoa (volume: 8±175 ml, sperm concentration: 410-4000x106/ml, total motility: 0±90%), while after 5±8 injections, only 50% of these bulls produced ejaculates with a small number of immotile spermatozoa. The ejaculates of group 2 bulls (vaccinated >8 times) were devoid of spermatozoa. Faecal androgen metabolite concentrations measured in captive males decreased significantly after the fourth vaccination. None of the males entered musth during the treatment period. CONCLUSIONS: Our results showed a marked decrease in semen quality, testicle and secondary sex gland sizes following repeated GnRH vaccinations. After 2±4 years of continuous treatment every 5±7 months, the effects were similar to surgical castration.ISIScopu

Protective and Enhancing HLA Alleles, HLA-DRB1*0901 and HLA-A*24, for Severe Forms of Dengue Virus Infection, Dengue Hemorrhagic Fever and Dengue Shock Syndrome

Dengue has become one of the most common viral diseases transmitted by infected mosquitoes (with any of the four dengue virus serotypes: DEN-1, -2, -3, or -4). It may present as asymptomatic or illness, ranging from mild to severe disease. Recently, the severe forms, dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS), have become the leading cause of death among children in Southern Vietnam. The pathogenesis of DHF/DSS, however, is not yet completely understood. The immune response, virus virulence, and host genetic background are considered to be risk factors contributing to disease severity. Human leucocyte antigens (HLA) expressed on the cell surface function as antigen presenting molecules and those polymorphism can change individuals' immune response. We investigated the HLA-A, -B (class I), and -DRB1 (class II) polymorphism in Vietnamese children with different severity (DHF/DSS) by a hospital-based case-control study. The study showed persons carrying HLA-A*2402/03/10 are about 2 times more likely to have severe dengue infection than others. On the other hand, HLA-DRB1*0901 persons are less likely to develop DSS with DEN-2 virus infection. These results clearly demonstrated that HLA controlled the susceptibility to severe forms of DV infection

Automated Detection of Retinopathy of Prematurity Using Quantum Machine Learning and Deep Learning Techniques

Retinopathy of prematurity (ROP) is a vasoproliferative retinal disease that affects premature infants and causes permanent blindness if left untreated. Automated retinal diagnosis from the Retinal fundus images aid in the early detection of many pathological conditions. The low-level statistical features used in literatures have not provided the complete ROP-specific profile, and hence it has to be replaced by high-level features. The proposed system involves extracting Scale Invariant Feature Transform (SIFT) - Speeded Up Robust Features (SURF) combined high-level features from the SegNet segmented retinal vessels and classified using the Quantum Support Vector Machine (QSVM) classifier. This study aims (i) to segment retinal vessels from the acquired fundus images using SegNet and extract their features using the SURF and SIFT Feature Extraction method, (ii) to classify the Normal and ROP retinal vessels using four classical machine learning classifiers such as Support Vector Machine (SVM), Reduced Error Pruning (REP) tree, K-Star, and LogitBoost and Quantum SVM classifier, (iii) to develop a novel transformer-based Swin-T ROP model to classify ROP from normal Neonatal fundus images, (iv) to compare the performance characteristics of the proposed QSVM model with the Resnet50, DarkNet19, and classical machine learning classifiers. The study is conducted using 200 fundus images, including 100 normal and 100 ROP-positive neonatal retinal images. The machine learning classifiers such as SVM, REP Tree, K-Star, and Logit Boost Classifiers attained accuracy of 86.7%, 75%, 74%, and 76.5%, respectively, in classifying ROP from normal retinal images. The deep learning networks such as ResNet50 and DarkNet19 classified ROP from normal fundus images with an accuracy of 92.87% and 89%, respectively. The Quantum machine learning classifier outperforms the classical machine learning classifiers, Pre-trained Convolutional Neural Networks (CNN) and SwinT-ROP in terms of classification accuracy (95.5%), sensitivity (93%), and specificity (98%). The proposed system accurately diagnoses ROP from the neonatal fundus images and could be used in point-of-care diagnosis to access diagnostic expertise in underserved regions

HLA-A AND HLA-B ALLELES ASSOCIATED IN PSORIASIS PATIENTS FROM MUMBAI, WESTERN INDIA

Background: Psoriasis, a common autoimmune disorder characterized by T cell-mediated keratinocyte hyperproliferation, is known to be associated with the presence of certain specific Human Leukocyte Antigen (HLA) alleles. Aim: To evaluate distribution of HLA-A and HLA-B alleles and hence identify the susceptible allele of psoriasis from patients in Western India. Materials and Methods: The study design included 84 psoriasis patients and 291 normal individuals as controls from same geographical region. HLA-A and HLA-B typing was done using Serology typing. Standard statistical analysis was followed to identify the odds ratio (OR), allele frequencies, and significant P value using Graphpad software. Results: The study revealed significant increase in frequencies of HLA-A2 (OR-3.976, P<0.0001), B8 (OR-5.647, P<0.0001), B17 (OR-5.452, P<0.0001), and B44 (OR-50.460, P<0.0001), when compared with controls. Furthermore, the frequencies of HLA-A28 (OR-0.074, P=0.0024), B5 (OR-0.059, P<0.0001), B12 (OR-0.051, P=0.0002), and B15 (OR-0.237, P=0.0230) were significantly decreased in psoriasis patients. Conclusion: This study shows the strong association of HLA-A2, B8, and B17 antigens with psoriasis conferring susceptibility to psoriasis patients from Western India, while the antigens HLA-A28, B5, and B12 show strong negative association with the disease

Design for business innovation: Linking the value chains of logistics service and cargo insurance companies by designing a collaborative service infrastructure

Both, the logistics and insurance companies rely on software intensive systems and IT-infrastructure to run their core business operational. In recent years IT-improvements have resulted e.g. in better tracking and tracing capabilities for the whole logistics industry. Designing an interface in this case between the logistics and insurance value chain further enhances visibility and transparency on transportation. Though, the design of a large collaborative service infrastructure is a complex task. In this paper, we investigate whether design science supports this. The research follows design science guidelines creating a message hub based on sensor telematics technologies, which physically links the two value chains. The described IT-artefact enables logistics and insurance companies to improve their respective products and solutions with e.g. integrated risk management or active process control. This demonstrates how design science projects eventually facilitate real business innovation within networked enterprises