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1.
Diagnosis (Berl) ; 9(4): 411-420, 2022 11 01.
Artigo em Inglês | MEDLINE | ID: mdl-36000189

RESUMO

High throughput technological innovations in the past decade have accelerated research into the trillions of commensal microbes in the gut. The 'omics' technologies used for microbiome analysis are constantly evolving, and large-scale datasets are being produced. Despite of the fact that much of the research is still in its early stages, specific microbial signatures have been associated with the promotion of cancer, as well as other diseases such as inflammatory bowel disease, neurogenerative diareses etc. It has been also reported that the diversity of the gut microbiome influences the safety and efficacy of medicines. The availability and declining sequencing costs has rendered the employment of RNA-based diagnostics more common in the microbiome field necessitating improved data-analytical techniques so as to fully exploit all the resulting rich biological datasets, while accounting for their unique characteristics, such as their compositional nature as well their heterogeneity and sparsity. As a result, the gut microbiome is increasingly being demonstrating as an important component of personalised medicine since it not only plays a role in inter-individual variability in health and disease, but it also represents a potentially modifiable entity or feature that may be addressed by treatments in a personalised way. In this context, machine learning and artificial intelligence-based methods may be able to unveil new insights into biomedical analyses through the generation of models that may be used to predict category labels, and continuous values. Furthermore, diagnostic aspects will add value in the identification of the non invasive markers in the critical diseases like cancer.


Assuntos
Microbioma Gastrointestinal , Microbiota , Neoplasias , Humanos , Inteligência Artificial , Neoplasias/diagnóstico
2.
NPJ Parkinsons Dis ; 8(1): 66, 2022 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-35650269

RESUMO

Parkinson's disease (PD) is a neurological disorder that affects the movement of the human body. It is primarily characterized by reduced dopamine levels in the brain. The causative agent of PD is still unclear but it is generally accepted that α-synuclein has a central role to play. It is also known that gap-junctions and associated connexins are complicated structures that play critical roles in nervous system signaling and associated misfunctioning. Thus, our current article emphasizes how, alongside α-synuclein, ion-channels, gap-junctions, and related connexins, all play vital roles in influencing multiple metabolic activities of the brain during PD. It also highlights that ion-channel and gap-junction disruptions, which are primarily mediated by their structural-functional changes and alterations, have a role in PD. Furthermore, we discussed available drugs and advanced therapeutic interventions that target Parkinson's pathogenesis. In conclusion, it warrants creating better treatments for PD patients. Although, dopaminergic replenishment therapy is useful in treating neurological problems, such therapies are, however, unable to control the degeneration that underpins the disease, thereby declining their overall efficacy. This creates an additional challenge and an untapped scope for neurologists to adopt treatments for PD by targeting the ion-channels and gap-junctions, which is well-reviewed in the present article.

3.
Front Neurosci ; 16: 893251, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36685230

RESUMO

Autism spectrum disorder (ASD) is considered a complicated neurodevelopment disorder with rising prevalence globally. ASD is characterized by a series of events including varying degrees of defects in communication, learning, and social interaction which is accompanied by stereotypical behavioral patterns. Despite extensive research, the current diagnosis for ASD is complex and almost solely based on the behavioral assessments of the suspected individuals. The multifactorial etiopathology of this disease along with the diversity of symptoms among different individuals adds to the current intricacies for accurate prognosis of ASD. Hence, there exists a dire need for biologically relevant biomarkers for an early diagnosis and for tracking the efficacy of therapeutic interventions. Until recently, among various biofluids, saliva has gained increasing interest for biomarker identification, the advantages include the non-invasive nature and ease of sample handling. This mini-review aims to provide a succinct summary of recent literature on saliva-based diagnostic modalities for ASD, examine various studies that highlight the potential use of proteomic and/or RNA-based biomarkers. Finally, some conclusive perspectives of using the salivary system for ASD mechanistic details and diagnosis are also discussed.

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