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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.
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Alzheimer's disease (AD) has few effective treatment options and continues to be a major global health concern. AD is a neurodegenerative disease that typically affects elderly people. Alkaloids have potential sources for novel drug discovery due to their diverse chemical structures and pharmacological activities. Alkaloids, natural products with heterocyclic nitrogen-containing structures, are considered potential treatments for AD. This review explores the neuroprotective properties of alkaloids in AD, focusing on their ability to regulate pathways such as amyloid-beta aggregation, oxidative stress, synaptic dysfunction, tau hyperphosphorylation, and neuroinflammation. The FDA has approved alkaloids such as acetylcholinesterase inhibitors like galantamine and rivastigmine. This article explores AD's origins, current market medications, and clinical applications of alkaloids in AD therapy. This review explores the development of alkaloid-based drugs for AD, focusing on pharmacokinetics, blood-brain barrier penetration, and potential adverse effects. Future research should focus on the clinical evaluation of promising alkaloids, developing recently discovered alkaloids, and the ongoing search for novel alkaloids for medical treatment. A pharmaceutical option containing an alkaloid may potentially slow down the progression of AD while enhancing its symptoms. This review highlights the potential of alkaloids as valuable drug leads in treating AD, providing a comprehensive understanding of their mechanisms of action and therapeutic implications.
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Alcaloides , Enfermedad de Alzheimer , Fármacos Neuroprotectores , Humanos , Enfermedad de Alzheimer/tratamiento farmacológico , Enfermedad de Alzheimer/metabolismo , Alcaloides/farmacología , Alcaloides/uso terapéutico , Animales , Fármacos Neuroprotectores/farmacología , Fármacos Neuroprotectores/uso terapéutico , Péptidos beta-Amiloides/metabolismo , Inhibidores de la Colinesterasa/farmacología , Inhibidores de la Colinesterasa/uso terapéutico , Estrés Oxidativo/efectos de los fármacosRESUMEN
Staphylococcus epidermidis is an opportunistic bacterial pathogen. The study screened isolates of S. epidermidis of pediatric origin for genetic markers of discriminatory potential. 103 isolates (n = 75 clinical; n = 28 community) were screened for methicillin resistance (mecA), formate dehydrogenase (fdh) and an array of virulence factors through multiplex PCR and Congo red assay. The isolates were typed in four distinct categories, based on the presence of selected virulent factors. The type A clinical isolates carrying icaADBC operon (n = 22; 29.3%, P = 0.117) were not significantly differentiating the origin of isolates. The type B clinical isolates representing methicillin resistant S. epidermidis (MRSE) (n = 73; 97.3%, P < 0.00001) and the type C clinical isolates lacking formate dehydrogenase fdh (n = 62; 82.6%, P < 0.00001) were having significant discriminatory potential of clinical isolates, respectively. All type D community isolates were carrying fdh (n = 28; 100%, P < 0.00001). MecA and fdh are significant differential markers of pathogenicity and commensalism in S. epidermidis of pediatric origin.
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Infecciones Estafilocócicas , Staphylococcus epidermidis , Niño , Humanos , Staphylococcus epidermidis/genética , Formiato Deshidrogenasas , Virulencia/genética , Infecciones Estafilocócicas/microbiología , Pakistán , Simbiosis , Antibacterianos , Proteínas Bacterianas/genéticaRESUMEN
The clinical management of oral cancer is often frequented with challenges that arise from relapse, recurrence, invasion and resistance towards the cornerstone chemo and radiation therapies. The recent conceptual advancement in oncology has substantiated the role of cancer stem cells (CSC) as a predominant player of these intricacies. CSC are a sub-group of tumor population with inherent adroitness to self-renew with high plasticity. During tumor evolution, the structural and functional reprogramming persuades the cancer cells to acquire stem-cell like properties, thus presenting them with higher survival abilities and treatment resistance. An appraisal on key features that govern the stemness is of prime importance to confront the current challenges encountered in oral cancer. The nurturing niche of CSC for maintaining its stemness characteristics is thought to be modulated by complex multi-layered components encompassing neoplastic cells, extracellular matrix, acellular components, circulatory vessels, various cascading signaling molecules and stromal cells. This review focuses on recapitulating both intrinsic and extrinsic mechanisms that impart the stemness. There are contemplating evidences that demonstrate the role of transcription factors (TF) in sustaining the neoplastic stem cell's pluripotency and plasticity alongside the miRNA in regulation of crucial genes involved in the transformation of normal oral mucosa to malignancy. This review illustrates the interplay between miRNA and various known TF of oral cancer such as c-Myc, SOX, STAT, NANOG and OCT in orchestrating the stemness and resistance features. Further, the cross-talks involved in tumor micro-environment inclusive of cytokines, macrophages, extra cellular matrix, angiogenesis leading pathways and influential factors of hypoxia on tumorigenesis and CSC survival have been elucidated. Finally, external factorial influence of oral microbiome gained due to the dysbiosis is also emphasized. There are growing confirmations of the possible roles of microbiomes in the progression of oral cancer. Given this, an attempt has been made to explore the potential links including EMT and signaling pathways towards resistance and stemness. This review provides a spectrum of understanding on stemness and progression of oral cancers at various regulatory levels along with their current therapeutic knowledge. These mechanisms could be exploited for future research to expand potential treatment strategies.
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Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird's eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.