Progress in the functional studies of human olfactory receptors has been largely hampered by the lack of a reliable experimental model system. Although transgenic approaches in mice could characterize the function of individual olfactory receptors, the presence of over 300 functional genes in the human genome becomes a daunting task. Thus, the characterization of individuals with a genetic susceptibility to altered olfaction coupled with the absence of particular olfactory receptor genes will allow phenotype/genotype correlations and vindicate the function of specific olfactory receptors with their cognate ligands. We characterized a 118 kb β-globin deletion and found that its 3' end breakpoint extends to the neighboring olfactory receptor region downstream of the β-globin gene cluster. This deletion encompasses six contiguous olfactory receptor genes (OR51V1, OR52Z1, OR51A1P, OR52A1, OR52A5, and OR52A4) all of which are expressed in the brain. Topology analysis of the encoded proteins from these olfactory receptor genes revealed that OR52Z1, OR52A1, OR52A5, and OR52A4 are predicted to be functional receptors as they display integral characteristics of G-proteins coupled receptors. Individuals homozygous for the 118 kb β-globin deletion are afflicted with β-thalassemia due to a homozygous deletion of the β-globin gene and have no alleles for the above mentioned olfactory receptors genes. This is the first example of a homozygous deletion of olfactory receptor genes in human. Although altered olfaction remains to be ascertained in these individuals, such a study can be carried out in β-thalassemia patients from Malaysia, Indonesia and the Philippines where this mutation is common. Furthermore, OR52A1 contains a γ-globin enhancer, which was previously shown to confer continuous expression of the fetal γ-globin genes. Thus, the hypothesis that β-thalassemia individuals, who are homozygous for the 118 kb deletion, may also have an exacerbation of their anemia due to the deletion of two copies of the γ-globin enhancer element is worthy of consideration.
Inflammatory bowel diseases (IBDs) are immune mediated diseases affecting the gastrointestinal tract. Several environmental factors in concert with genetic susceptibilities can trigger IBDs. Recently, one of the important environmental factors contributing to the development of autoimmune diseases is vitamin D (VitD) deficiency. Furthermore, some new evidence points to VitD deficiency and its receptor dysfunction as an underlying factor for the emergence experimental IBDs. The aim of the current study was to evaluate the correlation between serum 25(OH)D concentrations and IBD activity in patients with ulcerative colitis or Crohn's disease. Sixty patients with confirmed diagnosis of IBD were recruited for a cross sectional study. Most of the identified confounders affecting serum VitD concentrations were excluded. Disease activity was assessed using validated questionnaires, including Truelove for Ulcerative Colitis and Crohn Disease Activity Index (CDAI) for Crohn disease. Serum 25(OH)D concentrations were determined by chemiluminescent assay. Serum 25(OH)D≤10 (ng/ml) was considered as VitD deficiency and 11≤25(OH)D<29(ng/ml) as VitD insufficiency. Mean serum 25(OH)D value was 13.1 ± 11.1(ng/ml) in IBD patients. Almost 95% of patients were vitamin D insufficient or deficient. Forty one percent of IBD patients had active disease. VitD deficiency was not associated with IBD activity (p=0.23). However, VitD deficiency was significantly associated with a history of IBD related intestinal surgery (p=0.001). In conclusion, this cross-sectional prospective study suggested that there is no association between vitamin D deficiency and disease activity in a relatively small number of IBD patients in a short period of time.
This research enhances crowd analysis by focusing on excessive crowd analysis and crowd density predictions for Hajj and Umrah pilgrimages. Crowd analysis usually analyzes the number of objects within an image or a frame in the videos and is regularly solved by estimating the density generated from the object location annotations. However, it suffers from low accuracy when the crowd is far away from the surveillance camera. This research proposes an approach to overcome the problem of estimating crowd density taken by a surveillance camera at a distance. The proposed approach employs a fully convolutional neural network (FCNN)-based method to monitor crowd analysis, especially for the classification of crowd density. This study aims to address the current technological challenges faced in video analysis in a scenario where the movement of large numbers of pilgrims with densities ranging between 7 and 8 per square meter. To address this challenge, this study aims to develop a new dataset based on the Hajj pilgrimage scenario. To validate the proposed method, the proposed model is compared with existing models using existing datasets. The proposed FCNN based method achieved a final accuracy of 100%, 98%, and 98.16% on the proposed dataset, the UCSD dataset, and the JHU-CROWD dataset, respectively. Additionally, The ResNet based method obtained final accuracy of 97%, 89%, and 97% for the proposed dataset, UCSD dataset, and JHU-CROWD dataset, respectively. The proposed Hajj-Crowd-2021 crowd analysis dataset and the model outperformed the other state-of-the-art datasets and models in most cases.