Detection of foot-and-mouth disease viruses from the A/AFRICA/G-I genotype in the Sultanate of Oman.

Rapid identification and characterization of circulating foot-and-mouth disease virus (FMDV) strains is crucial for effective disease control. In Oman, a few serological and molecular studies have been conducted to identify the strains of FMDV responsible for the outbreaks that have been occurring within the country. In this study, 13 oral epithelial tissue samples from cattle were collected from suspected cases of FMD in Ash Sharqiyah North, Al Batinah North, Dhofar and Ad Dhakhyilia governorates of Oman between 2018 and 2021. FMDV RNA was detected in all samples by real-time RT-PCR and viruses were isolated after one- or two-blind passages in the porcine Instituto Biologico-Rim Suino-2 cell line. Antigen capture ELISA characterized all isolates as serotype A and VP1 phylogenetic analysis placed all sequences within a single clade of the G-I genotype within the A/AFRICA topotype. These sequences shared the closest nucleotide identities to viruses circulating in Bahrain in 2021 (93.5% to 99.5%) and Kenya in 2017 (93.4% to 99.1%). To the best of our knowledge, this is the first time that A/AFRICA/G-I viruses have been detected in Oman. Together with the closely related viruses detected recently in Bahrain, these findings reinforce the importance of deploying effective quarantine control measures to minimize the risks of transboundary transmission of FMD associated with the importation of cattle from East Africa.

Machine Learning Approach for Predicting Systemic Lupus Erythematosus in an Oman-Based Cohort.

Objectives: This study aimed to design a machine learning-based prediction framework to predict the presence or absence of systemic lupus erythematosus (SLE) in a cohort of Omani patients. Methods: Data of 219 patients from 2006 to 2019 were extracted from Sultan Qaboos University Hospital's electronic records. Among these, 138 patients had SLE, while the remaining 81 had other rheumatologic diseases. Clinical and demographic features were analysed to focus on the early stages of the disease. Recursive feature selection was implemented to choose the most informative features. The CatBoost classification algorithm was utilised to predict SLE, and the SHAP explainer algorithm was applied on top of the CatBoost model to provide individual prediction reasoning, which was then validated by rheumatologists. Results: CatBoost achieved an area under the receiver operating characteristic curve score of 0.95 and a sensitivity of 92%. The SHAP algorithm identified four clinical features (alopecia, renal disorders, acute cutaneous lupus and haemolytic anaemia) and the patient's age as having the greatest contribution to the prediction. Conclusion: An explainable framework to predict SLE in patients and provide reasoning for its prediction was designed and validated. This framework enables clinicians to implement early interventions that will lead to positive healthcare outcomes.

The Association of Human Leukocyte Antigens Complex with Type 1 Diabetes in the Omani Population.

Objectives: Identification of the high risk alleles, genotypes and haplotypes of the human leukocyte antigens (HLA) in different populations is beneficial for understanding their roles in type 1 diabetes (T1D) pathogenesis and intervention practices. This study aimed to identify T1D-associated HLA gene alleles in the Omani population. Methods: The present case-control study included 73 diabetic seropositive children (mean age 9.08 ± 3.27 years) attending the paediatric clinic at Sultan Qaboos University Hospital in Muscat, Oman, and 110 healthy controls. HLA-A, -B, -C, -DRB1 and -DQB1 genes were genotyped using a sequence-specific primer polymerase chain reaction (SSP-PCR). Results: Two HLA class I alleles (B*08, B*58) and three class II alleles (DQB1*02, DRB1*03 and DRB1*04) were associated with T1D susceptibility, while one class I (B*51) and three class II (DQB1*05, DQB1*06 and DRB1*16) alleles were associated with T1D protection. HLA-DRB1*03 and DQB1*02 alleles showed the strongest risk association among all alleles. Six DRB1 residues (E9, S11, S13, Y30, V70 and K71) were significantly associated with T1D susceptibility. Heterozygous genotypes, HLA-DRB1*03/*04 and DQB1*02/*03 were significantly associated with T1D susceptibility (P <0.0001, odds ratio [OR] = 63.21 and P = 0.02, OR = 3.63, respectively). Furthermore, a significant combined action of DRB1*03-DQB1*02 haplotype in T1D risk (P = 0.000176, OR = 15) and DRB1*16-DQB1*05 haplotype in protection (P = 0.0312, OR = 0.48) was detected. Conclusion: Known HLA class II gene alleles are associated with T1D in Omani children.

Cilia Ultrastructure Associated with Primary Ciliary Dyskinesia in Omani Patients.

Objectives: Primary ciliary dyskinesia (PCD) is a disorder affecting the structure and function of the motile cilia of the respiratory system. Transmission electron microscopy is one method that can be used to examine ciliary ultrastructure in airway biopsies. Although the role of ultrastructural findings in PCD has been described in the literature, this role has not been well-studied in the Middle East or, specifically, Oman. This study aimed to describe ultrastructural features in Omani patients with high suspicion of PCD. Methods: This retrospective cross-sectional study included 129 adequate airway biopsies obtained from Omani patients attending pulmonary clinics at Sultan Qaboos University Hospital and the Royal Hospital, Muscat, Oman, from 2010 to 2020 who were suspected of having PCD. Results: Ciliary ultrastructural abnormalities in the current study population were outer dynein arm (ODA) associated with inner dynein arm (IDA) defects (8%), microtubular disorganisation associated with IDA defect (5%) and isolated ODA defect (2%). Most of the biopsies showed normal ultrastructure (82%). Conclusion: In Omani patients suspected to have PCD, normal ultrastructure was the most common feature.

Detection of Trypanosoma Infection in Dromedary Camels by Using Different Diagnostic Techniques in Northern Oman.

Camel trypanosomoses is considered a devastating disease with severe health consequences that can be caused by different hemoprotozoan parasites. Camel samples (388) from the five regions in Northern Oman were assessed using a thin blood film. In addition, 95 seropositive samples were analyzed using various primers of mechanically transmitted trypanosomes. Out of the 388 blood smears examined, 0.8% (CI 95%, 2/388) were found to be positive for Trypanosoma sp. using a microscope. The parasitologically positive cases were detected in samples from females. The overall molecular prevalences were as follows: TBR was 78/95, 77% (CI 73.1-89.2%); ITS was 30/95, 31.6% (CI 73.1-89.2%); and T. evansi type A (RoTat 1.2) was 8/95, 8.4% (CI 4.0-16.0%). There were two species of trypanosomes that were observed in the camels.

Estimate of the HOMA-IR Cut-off Value for Identifying Subjects at Risk of Insulin Resistance Using a Machine Learning Approach.

OBJECTIVES: This study describes an unsupervised machine learning approach used to estimate the homeostatic model assessment-insulin resistance (HOMA-IR) cut-off for identifying subjects at risk of IR in a given ethnic group based on the clinical data of a representative sample. METHODS: The approach was applied to analyse the clinical data of individuals with Arab ancestors, which was obtained from a family study conducted in Nizwa, Oman, between January 2000 and December 2004. First, HOMA-IR-correlated variables were identified to which a clustering algorithm was applied. Two clusters having the smallest overlap in their HOMA-IR values were retrieved. These clusters represented the samples of two populations, which are insulin-sensitive subjects and individuals at risk of IR. The cut-off value was estimated from intersections of the Gaussian functions, thereby modelling the HOMA-IR distributions of these populations. RESULTS: A HOMA-IR cut-off value of 1.62 ± 0.06 was identified. The validity of this cut-off was demonstrated by showing the following: 1) that the clinical characteristics of the identified groups matched the published research findings regarding IR; 2) that a strong relationship exists between the segmentations resulting from the proposed cut-off and those resulting from the two-hour glucose cut-off recommended by the World Health Organization for detecting prediabetes. Finally, the method was also able to identify the cut-off values for similar problems (e.g. fasting sugar cut-off for prediabetes). CONCLUSION: The proposed method defines a HOMA-IR cut-off value for detecting individuals at risk of IR. Such methods can identify high-risk individuals at an early stage, which may prevent or delay the onset of chronic diseases such as type 2 diabetes.

Bioremediation of copper by active cells of Pseudomonas stutzeri LA3 isolated from an abandoned copper mine soil.

Copper bioremoval efficiency and bioaccumulation capacity of Pseudomonas stutzeri LA3 isolated from copper contaminated soil were investigated. P. stutzeri LA3 removed about 50% of Cu (II) at 50 mg l-1 of concentration and accumulated a maximum of 1.62 mg of Cu g-1 biomass dry weight. Bioremediation by P. stutzeri LA3 partially depended on the production of extracellular polymeric substances, composed of proteins and carbohydrates. Cell surface alterations were observed on the Cu (II) treated biomass through a scanning electron microscope (SEM). Energy dispersive spectrometer (EDX) investigation of Cu (II) treated biomass showed clear signals of Cu, confirming the presence of copper ions on the cell surface. Fourier transform infrared spectroscopy (FTIR) showed the contribution of functional groups such as hydroxyl (-OH), carboxyl (-COOH), amide and amine (-NH2) in the remediation process. Based on the results, the isolated strain P. stutzeri LA3 could serve as a potential candidate for copper due to its significant copper removal effeciency.