Different modalities to manage rheumatoid arthritis: an A to Z story.

Aim: To investigate different approaches to RA treatment that might lead to greater efficacy and better safety profiles. Methods: The Search strategy was based on medical subject headings, and screening and selection were based on inclusion/exclusion criteria. Results & discussion: Early therapy is critical for disease control and loss of bodily function. The most promising outcomes came from the development of disease-modifying anti-rheumatic drugs. Different foods have anti-inflammatory and antioxidant qualities that protect against the development of rheumatoid arthritis (RA). Some dietary patterns and supplements have been shown to have potential protective benefits against RA. Conclusion: Improvement in the quality of life of RA patients requires a tailored management approach based on the current patient medical data.

Rheumatoid arthritis is a complex disease with an unclear origin that affects the joints. In this systematic review, we aimed to investigate different effective ways of treating rheumatoid arthritis. Study results indicate that rheumatoid arthritis treatment requires coordination between different healthcare teams. As much as we can, when we start disease treatment early, this will lead to a better disease cure. Different drugs showed promising results in the treatment of rheumatoid arthritis, but the most promising treatment results came from a group of medicinal agents called 'disease-modifying anti-rheumatic drugs'. Different foods have anti-inflammatory and antioxidant effect and help in protection against rheumatoid arthritis, but others, such as red meat and salt, have the opposite effect. Some dietary patterns and supplements, such as the Mediterranean Diet, vitamin D and probiotics, have been shown to have potential protective benefits against rheumatoid arthritis. Improvement in the quality of patient life requires an individualized management roadmap based on current patient medical data.

Mass Spectrometry Applications to Study Human Microbiome.

Microbiotas are an adaptable component of ecosystems, including human ecology. Microorganisms influence the chemistry of their specialized niche, such as the human gut, as well as the chemistry of distant surroundings, such as other areas of the body. Metabolomics based on mass spectrometry (MS) is one of the primary methods for detecting and identifying small compounds generated by the human microbiota, as well as understanding the functional significance of these microbial metabolites. This book chapter gives basic knowledge on the kinds of untargeted mass spectrometry as well as the data types that may be generated in the context of microbiome study. While data analysis remains a barrier, the emphasis is on data analysis methodologies and integrative analysis, particularly the integration of microbiome sequencing data. Mass spectrometry (MS)-based techniques have resurrected culture methods for studying the human gut microbiota, filling in the gaps left by high-throughput sequencing methods in terms of culturing minor populations.

Applications of Proteomics in Probiotics Having Anticancer and Chemopreventive Properties.

Proteomics has grown in importance in molecular sciences because it gives vital information on protein identification, expression levels, and alteration. Cancer is one of the world's major causes of death and is the major focus of much research. Cancer risk is determined by hereditary variables as well as the body's immunological condition. Probiotics have increasing medical importance due to their therapeutic influence on the human body in the prevention and treatment of numerous chronic illnesses, including cancer, with no adverse effects. Several anticancer, anti-inflammatory, and chemopreventive probiotics are studied using different proteomic approaches like two-dimensional gel electrophoresis, liquid chromatography-mass spectrometry, and matrix-assisted laser desorption/ionization mass spectrometry. To gain relevant information about probiotic characteristics, data from the proteomic analysis are evaluated and processed using bioinformatics pipelines. Proteomic studies showed the significance of different proteomic approaches in characterization, comparing strains, and determination of oxidative stress of different probiotics. Moreover, proteomic approaches identified different proteins that are involved in glucose metabolism and the formation of cell walls or cell membranes, and the differences in the expression of critical enzymes in the HIF-1 signaling pathway, starch, and sucrose metabolism, and other critical metabolic pathways.

Associations between Nutrigenomic Effects and Incidences of Microbial Resistance against Novel Antibiotics.

Nutrigenomics is the study of the impact of diets or nutrients on gene expression and phenotypes using high-throughput technologies such as transcriptomics, proteomics, metabolomics, etc. The bioactive components of diets and nutrients, as an environmental factor, transmit information through altered gene expression and hence the overall function and traits of the organism. Dietary components and nutrients not only serve as a source of energy but also, through their interactions with genes, regulate gut microbiome composition, the production of metabolites, various biological processes, and finally, health and disease. Antimicrobial resistance in pathogenic and probiotic microorganisms has emerged as a major public health concern due to the presence of antimicrobial resistance genes in various food products. Recent evidence suggests a correlation between the regulation of genes and two-component and other signaling systems that drive antibiotic resistance in response to diets and nutrients. Therefore, diets and nutrients may be alternatively used to overcome antibiotic resistance against novel antibiotics. However, little progress has been made in this direction. In this review, we discuss the possible implementations of nutrigenomics in antibiotic resistance against novel antibiotics.

Advances in the Applications of Bioinformatics and Chemoinformatics.

Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as "in silico techniques", in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, the incorporation of machine learning has been considered of high importance in the field of drug design, enabling the extraction of chemical data from enormous compound databases to develop drugs endowed with significant biological features. The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals. The virtual libraries address the need to increase the quality of the compounds as well as discover promising ones. On the other hand, various applications of bioinformatics in disease classification, diagnosis, and identification of multidrug-resistant organisms were discussed. The use of ensemble models and brute-force feature selection methodology has resulted in high accuracy rates for heart disease and COVID-19 diagnosis, along with the role of special formulations for targeting meningitis and Alzheimer's disease. Additionally, the correlation between genomic variations and disease states such as obesity and chronic progressive external ophthalmoplegia, the investigation of the antibacterial activity of pyrazole and benzimidazole-based compounds against resistant microorganisms, and its applications in chemoinformatics for the prediction of drug properties and toxicity-all the previously mentioned-were presented in the current review.

Raman Spectroscopy and Machine Learning Enables Estimation of Articular Cartilage Structural, Compositional, and Functional Properties.

OBJECTIVE: To differentiate healthy from artificially degraded articular cartilage and estimate its structural, compositional, and functional properties using Raman spectroscopy (RS). DESIGN: Visually normal bovine patellae (n = 12) were used in this study. Osteochondral plugs (n = 60) were prepared and artificially degraded either enzymatically (via Collagenase D or Trypsin) or mechanically (via impact loading or surface abrasion) to induce mild to severe cartilage damage; additionally, control plugs were prepared (n = 12). Raman spectra were acquired from the samples before and after artificial degradation. Afterwards, reference biomechanical properties, proteoglycan (PG) content, collagen orientation, and zonal (%) thickness of the samples were measured. Machine learning models (classifiers and regressors) were then developed to discriminate healthy from degraded cartilage based on their Raman spectra and to predict the aforementioned reference properties. RESULTS: The classifiers accurately categorized healthy and degraded samples (accuracy = 86%), and successfully discerned moderate from severely degraded samples (accuracy = 90%). On the other hand, the regression models estimated cartilage biomechanical properties with reasonable error (≤ 24%), with the lowest error observed in the prediction of instantaneous modulus (12%). With zonal properties, the lowest prediction errors were observed in the deep zone, i.e., PG content (14%), collagen orientation (29%), and zonal thickness (9%). CONCLUSION: RS is capable of discriminating between healthy and damaged cartilage, and can estimate tissue properties with reasonable errors. These findings demonstrate the clinical potential of RS.

COVID-19 Vaccination in Pediatrics: Was It Valuable and Successful?

BACKGROUND: The mass vaccination of children against coronavirus 2019 disease (COVID-19) has been frequently debated. The risk-benefit assessment of COVID-19 vaccination versus infection in children has also been debated. AIM: This systematic review looked for answers to the question "was the vaccination of our children valuable and successful?". METHODS: The search strategy of different articles in the literature was based on medical subject headings. Screening and selection were based on inclusion/exclusion criteria. RESULTS AND DISCUSSION: The search results revealed that the majority of the reported adverse events after COVID-19 vaccination in pediatrics were mild to moderate, with few being severe. Injection site discomfort, fever, headache, cough, lethargy, and muscular aches and pains were the most prevalent side effects. Few clinical studies recorded significant side effects, although the majority of these adverse events had nothing to do with vaccination. In terms of efficacy, COVID-19 disease protection was achieved in 90-95% of cases for mRNA vaccines, in 50-80% of cases for inactivated vaccines, and in 58-92% of cases for adenoviral-based vaccines in children and adolescents. CONCLUSIONS: Based on available data, COVID-19 immunizations appear to be safe for children and adolescents. Furthermore, multiple studies have proven that different types of vaccines can provide excellent protection against COVID-19 in pediatric populations. The efficacy of vaccines against new SARS-CoV-2 variants and the reduction in vaccine-related long-term adverse events are crucial for risk-benefit and cost-effectiveness assessments; therefore, additional safety studies are required to confirm the long-term safety and effectiveness of vaccinations in children.

COVID-19 signalome: Potential therapeutic interventions.

The COVID-19 pandemic has triggered intensive research and development of drugs and vaccines against SARS-CoV-2 during the last two years. The major success was especially observed with development of vaccines based on viral vectors, nucleic acids and whole viral particles, which have received emergent authorization leading to global mass vaccinations. Although the vaccine programs have made a big impact on COVID-19 spread and severity, emerging novel variants have raised serious concerns about vaccine efficacy. Due to the urgent demand, drug development had originally to rely on repurposing of antiviral drugs developed against other infectious diseases. For both drug and vaccine development the focus has been mainly on SARS-CoV-2 surface proteins and host cell receptors involved in viral attachment and entry. In this review, we expand the spectrum of SARS-CoV-2 targets by investigating the COVID-19 signalome. In addition to the SARS-CoV-2 Spike protein, the envelope, membrane, and nucleoprotein targets have been subjected to research. Moreover, viral proteases have presented the possibility to develop different strategies for the inhibition of SARS-CoV-2 replication and spread. Several signaling pathways involving the renin-angiotensin system, angiotensin-converting enzymes, immune pathways, hypoxia, and calcium signaling have provided attractive alternative targets for more efficient drug development.

COVID-19 signalome: Pathways for SARS-CoV-2 infection and impact on COVID-19 associated comorbidity.

The COVID-19 pandemic has been the focus of research the past two years. The major breakthrough was made by discovering pathways related to SARS-CoV-2 infection through cellular interaction by angiotensin-converting enzyme (ACE2) and cytokine storm. The presence of ACE2 in lungs, intestines, cardiovascular tissues, brain, kidneys, liver, and eyes shows that SARS-CoV-2 may have targeted these organs to further activate intracellular signalling pathways that lead to cytokine release syndrome. It has also been reported that SARS-CoV-2 can hijack coatomer protein-I (COPI) for S protein retrograde trafficking to the endoplasmic reticulum-Golgi intermediate compartment (ERGIC), which, in turn, acts as the assembly site for viral progeny. In infected cells, the newly synthesized S protein in endoplasmic reticulum (ER) is transported first to the Golgi body, and then from the Golgi body to the ERGIC compartment resulting in the formation of specific a motif at the C-terminal end. This review summarizes major events of SARS-CoV-2 infection route, immune response following host-cell infection as an important factor for disease outcome, as well as comorbidity issues of various tissues and organs arising due to COVID-19. Investigations on alterations of host-cell machinery and viral interactions with multiple intracellular signaling pathways could represent a major factor in more effective disease management.