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Fulltext DeepSplice: a deep learning approach for accurate prediction of alternative splicing events in the human genome

Abrar M, Hussain D, Khan IA, Ullah F, Haq MA, Aleisa MA, et al.

Front Genet, 2024;15:1349546.
PMID: 38974384 DOI: 10.3389/fgene.2024.1349546

Alternative splicing (AS) is a crucial process in genetic information processing that generates multiple mRNA molecules from a single gene, producing diverse proteins. Accurate prediction of AS events is essential for understanding various physiological aspects, including disease progression and prognosis. Machine learning (ML) techniques have been widely employed in bioinformatics to address this challenge. However, existing models have limitations in capturing AS events in the presence of mutations and achieving high prediction performance. To overcome these limitations, this research presents deep splicing code (DSC), a deep learning (DL)-based model for AS prediction. The proposed model aims to improve predictive ability by investigating state-of-the-art techniques in AS and developing a DL model specifically designed to predict AS events accurately. The performance of the DSC model is evaluated against existing techniques, revealing its potential to enhance the understanding and predictive power of DL algorithms in AS. It outperforms other models by achieving an average AUC score of 92%. The significance of this research lies in its contribution to identifying functional implications and potential therapeutic targets associated with AS, with applications in genomics, bioinformatics, and biomedical research. The findings of this study have the potential to advance the field and pave the way for more precise and reliable predictions of AS events, ultimately leading to a deeper understanding of genetic information processing and its impact on human physiology and disease.
Fulltext Is Serum Uric Acid Level Associated with Disease Activity in Rheumatoid Arthritis Patients

Alkhudir D, Al-Herz A, Saleh K, Alawadhi A, Al-Kandari W, Hasan E, et al.

Open Access Rheumatol, 2023;15:223-230.
PMID: 38026718 DOI: 10.2147/OARRR.S418814

BACKGROUND: An association between serum uric acid (UA) and disease activity in rheumatoid arthritis (RA) patients has not been well studied. We describe RA patients with high and normal UA and study its association with RA activity.
METHODS: Adult RA patients from the Kuwait Registry for Rheumatic Diseases (KRRD) were studied from February 2012 through March 2022. Patients with documented UA levels were included. UA of >357 µmol/L (6mg/dL) was considered high. Statistical comparison and correlation were made using multivariate logistic regression.
RESULTS: Overall, 1054 patients with documented UA. A total of 158 patients (15%) had high UA level with a mean of 409± 44.4µmol/L. The mean age for the high UA group and low UA group were 59.3 ± 10.7 years and 54.5 ± 12.4 years, respectively (p<0.001). 49.4% were female in high UA group, and 62.2% were female in low UA group, respectively (p<0.05). Logistic analysis showed an inverse relation between DAS28 and UA, as lower DAS28 score was associated with higher UA level (p=0.032) OR 1.39. There was a direct relation with HAQ, creatinine and UA. A higher HAQ is associated with a higher UA level (p=0.019) OR 0.78. High creatinine level is also associated with high UA level (p<0.001) OR 0.24. The use of antirheumatic drugs was similar among patients with high and normal UA.
CONCLUSION: RA patients with a higher UA had a lower disease activity despite using similar antirheumatic drugs. The reasons behind this association need to be further studied.
Fulltext Therapeutic role of immunomodulators during the COVID-19 pandemic- a narrative review

Al-Hajeri H, Baroun F, Abutiban F, Al-Mutairi M, Ali Y, Alawadhi A, et al.

Postgrad Med, 2022 Mar;134(2):160-179.
PMID: 35086413 DOI: 10.1080/00325481.2022.2033563

The emergency state caused by COVID-19 saw the use of immunomodulators despite the absence of robust research. To date, the results of relatively few randomized controlled trials have been published, and methodological approaches are riddled with bias and heterogeneity. Anti-SARS-CoV-2 antibodies, convalescent plasma and the JAK inhibitor baricitinib have gained Emergency Use Authorizations and tentative recommendations for their use in clinical practice alone or in combination with other therapies. Anti-SARS-CoV-2 antibodies are predominating the management of non-hospitalized patients, while the inpatient setting is seeing the use of convalescent plasma, baricitinib, tofacitinib, tocilizumab, sarilumab, and corticosteroids, as applicable. Available clinical data also suggest the potential clinical benefit of the early administration of blood-derived products (e.g. convalescent plasma, non-SARS-CoV-2-specific immunoglobins) and the blockade of factors implicated in the hyperinflammatory state of severe COVID-19 (Interleukin 1 and 6; Janus Kinase). Immune therapies seem to have a protective effect and using immunomodulators alone or in combination with viral replication inhibitors and other treatment modalities might prevent progression into severe COVID-19 disease, cytokine storm and death. Future trials should address existing gaps and reshape the landscape of COVID-19 management.

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