Search

Post-translational modifications (PTMs) either enhance a protein's activity in various sub-cellular processes, or degrade their activity which leads toward failure of intracellular processes. Tyrosine nitration (NT) modification degrades protein's activity that initiates and propagates various diseases including neurodegenerative, cardiovascular, autoimmune diseases and carcinogenesis. Identification of NT modification supports development of novel therapies and drug discoveries for associated diseases. Identification of NT modification in biochemical labs is expensive, time consuming and error-prone. To supplement this process, several computational approaches have been proposed. However these approaches fail to precisely identify NT modification, due to the extraction of irrelevant, redundant and less discriminative features from protein sequences. This paper presents the NTpred framework that is competent in extracting comprehensive features from raw protein sequences using four different sequence encoders. To reap the benefits of different encoders, it generates four additional feature spaces by fusing different combinations of individual encodings. Furthermore, it eradicates irrelevant and redundant features from eight different feature spaces through a Recursive Feature Elimination process. Selected features of four individual encodings and four feature fusion vectors are used to train eight different Gradient Boosted Tree classifiers. The probability scores from the trained classifiers are utilized to generate a new probabilistic feature space, which is used to train a Logistic Regression classifier. On the BD1 benchmark dataset, the proposed framework outperforms the existing best-performing predictor in 5-fold cross validation and independent test evaluation with combined improvement of 13.7% in MCC and 20.1% in AUC. Similarly, on the BD2 benchmark dataset, the proposed framework outperforms the existing best-performing predictor with combined improvement of 5.3% in MCC and 1.0% in AUC. NTpred is publicly available for further experimentation and predictive use at: https://sds_genetic_analysis.opendfki.de/PredNTS/. [ABSTRACT FROM AUTHOR]

Summary: Adjuvants, as the name indicates, are adjoined material aimed to assist in functioning as when added to vaccines they are meant to boost the effect and strongly stimulate the immune system. The response of the immune system can be unpredictable, and the autoimmune/inflammatory syndrome induced by adjuvants (ASIA) was developed to address possible adverse reactions of an autoimmune and inflammatory type that may be caused by adjuvants. While ASIA, as a syndrome, was coined and defined in 2011; reports describing patients with vague and nonspecific clinical symptoms following vaccinations appeared much earlier. In other words, ASIA came to define, arrange, and unite the variety of symptoms, related to autoimmunity, caused not by the vaccine itself, rather by the adjuvant part of the vaccine such as aluminum, among others. Accordingly, the introduction of ASIA enabled better understanding, proper diagnosis, and early treatment of the disorder. Furthermore, ASIA was shown to be associated with almost all body systems and various rheumatic and autoimmune diseases such as systemic lupus erythematosus, antiphospholipid syndrome, and systemic sclerosis. In addition, the correlation between COVID-19 and ASIA was noticed during the pandemic. In this review, we summarized the reported effects of adjuvants and medical literature before and after ASIA was defined, the several ways ASIA can manifest and impact different systems of the body, and the incidences of ASIA during the COVID-19 pandemic. It is important to clarify, that vaccines are among, if not the, most effective means of fighting infectious diseases however, we believe that vaccines manufacturing is not above criticism, particularly when it comes to added substances possessing a risk of side effects. Adjuvants such as aluminum, mineral oils, and silicone are added to vaccines in order to trigger a stronger immune response. Autoimmune/inflammatory syndrome induced by adjuvants (ASIA) was introduced in 2011 to address nonspecific symptoms and disorders appearing following vaccinations, which in fact were reported by many papers before the introduction of the syndrome. During the pandemic of COVID-19, a correlation between ASIA, COVID-19, and COVID-19 vaccines has been reported. [ABSTRACT FROM AUTHOR]

Summary: Background: Chronic bullous dermatosis of childhood (CBDC) is a rare autoimmune subepidermal blistering disease, which can develop following vaccination or medication, or with an autoimmune condition or illness, among other causes. Aim: To identify and better understand the clinical features of CBDC by performing a systematic review, in line with the Preferred Reporting Items for Systematic Reviews and Meta‐analyses guidelines. Methods: Eligible studies included publication since 1980, CBDC diagnosis, case studies, subjects aged < 18 years, clinical features and no language restriction. A database search was conducted including Embase, MEDLINE and Scopus on 14 July 2021 (see Appendix for search terms). Data were assessed for risk of bias. Jamovi was used for statistical analysis. Age and sex were compared with mucocutaneous involvement, cutaneous involvement, other symptoms, human leucocyte antigen type and lesion descriptions. Results: After removing duplicate references using Endnote, 351 papers were identified, of which 91 met the inclusion criteria. These papers included 130 cases of CBDC: 110 children and 20 neonates. The ratio of male : female patients was 19 : 1 for neonates and 74:55 for children. χ² analysis with 1 degree of freedom showed that CBDC in neonates was associated with facial (χ²(1) = 9.67, P < 0.01), mouth (χ²(1) = 31.0, P < 0.001), upper airway (χ²(1) = 52.7, P < 0.001), oesophageal (χ²(1) = 34.6, P < 0.001), ophthalmic (χ²(1) = 6.27, P = 0.01) involvement and with respiratory distress (χ²(1) = 22.7 P < 0.001). CBDC in children was associated with genital (χ²(1) = 3.96, P < 0.05), arm (χ²(1) = 6.99, P < 0.01) and leg (χ²(1) = 7.03, P < 0.01) involvement. CBDC in male patients was associated with facial (χ²(1) = 7.01, P < 0.01), scalp (χ²(1) = 5.96, P < 0.02) and perianal (χ²(1) = 7.22, P < 0.01) involvement. Conclusion: Neonates with CBDC are more likely to have a mucocutaneous distribution of lesions, whereas children are more likely to have cutaneous lesions. The limitations of this study include selection bias, and the small neonate sample size makes the study unrepresentative of the population. The review highlights the need for further research into the clinical features of CBDC in neonates. [ABSTRACT FROM AUTHOR]

Therapeutic monoclonal antibodies (MAbs) are biopharmaceuticals prescribed in oncology, rheumatology, and for other chronic and autoimmune diseases. Over the last decade, the demand for MAbs grew significantly in developing countries like Brazil, concomitant to the restructuring of the global biopharmaceutical industry, opening windows of opportunities for catching-up economies. This paper aims to analyze the capacity of a public policy, the so-called Production Development Partnership Program (PDPP), to encourage the generation of national capabilities to the local biopharmaceutical industry and technological upgrading in the biopharmaceutical sector in Brazil. It is a case study supported by qualitative data from twenty-three interviews. By focusing on technology transfer processes rather than on more complex strategies of technological learning and upgrading in domestic agents, the impact of PDPP has been marginal. We draw insights from this empirical appraisal to outline some lessons and challenges involved in the implementation of technology-upgrading policies in developing countries. [ABSTRACT FROM AUTHOR]

This paper presents a model‐based method for clustering multivariate binary observations that incorporates constraints consistent with the scientific context. The approach is motivated by the precision medicine problem of identifying autoimmune disease patient subsets or classes who may require different treatments. We start with a family of restricted latent class models or RLCMs. However, in the motivating example and many others like it, the unknown number of classes and the definition of classes using binary states are among the targets of inference. We use a Bayesian approach to RLCMs in order to use informative prior assumptions on the number and definitions of latent classes to be consistent with scientific knowledge so that the posterior distribution tends to concentrate on smaller numbers of clusters and sparser binary patterns. The paper derives a posterior sampling algorithm based on Markov chain Monte Carlo with split‐merge updates to efficiently explore the space of clustering allocations. Through simulations under the assumed model and realistic deviations from it, we demonstrate greater interpretability of results and superior finite‐sample clustering performance for our method compared to common alternatives. The methods are illustrated with an analysis of protein data to detect clusters representing autoantibody classes among scleroderma patients. [ABSTRACT FROM AUTHOR]

Objectives Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammation, pain, and cartilage and bone damage. There is currently no cure for RA. It is however managed using nonsteroidal anti-inflammatory drugs, corticosteroids and disease-modifying anti-rheumatic drugs, often with severe side effects. Hidden within Africa's lush vegetation are plants with diverse medicinal properties including anti-RA potentials. This paper reviews the scientific literature for medicinal plants, growing in Africa, with reported anti-RA activities and identifies the most abundant phytochemicals deserving research attention. A search of relevant published scientific literature, using the major search engines, such as Pubmed/Medline, Scopus, Google Scholar, etc. was conducted to identify medicinal plants, growing in Africa, with anti-RA potentials. Key findings Twenty plants belonging to 17 families were identified. The plants are rich in phytochemicals, predominantly quercetin, rutin, catechin, kaempferol, etc. known to affect some pathways relevant in RA initiation and progression, and therefore useful in its management. Summary Targeted research is needed to unlock the potentials of medicinal plants by developing easy-to-use technologies for preparing medicines from them. Research attention should focus on how best to exploit the major phytochemicals identified in this review for the development of anti-RA 'green pharmaceuticals'. [ABSTRACT FROM AUTHOR]

Summary: The immune system plays a critical role in protecting the host against infection but is subject to numerous levels of control that are necessary to prevent pathological, tissue-damaging responses. Inappropriate inflammatory immune responses to self-antigens, innocuous commensal microorganisms, or environmental antigens can lead to chronic, debilitating, and degenerative diseases. Regulatory T cells have an essential, non-redundant, and dominant function in preventing pathological immune responses, as shown by the development of systemic fatal autoimmunity in humans and animals with a genetic deficiency in regulatory T cells. In addition to controlling immune responses, there is a growing understanding that regulatory T cells also contribute directly to tissue homeostasis by promoting tissue regeneration and repair. For these reasons, the prospect of enhancing regulatory T-cell numbers and/or function in patients represents an appealing therapeutic opportunity with potential applications in many diseases, including some where the pathological role of the immune system has only recently been recognized. Approaches to enhance regulatory T cells are now starting to be explored in clinical studies in humans. This review series brings together papers highlighting the Treg-enhancing approaches that are most advanced clinically and examples of therapeutic opportunities based on our growing understanding of regulatory T-cell functions. [ABSTRACT FROM AUTHOR]