A phase II trial examining the safety and preliminary efficacy of repetitive transcranial magnetic stimulation (rTMS) for people living with multiple sclerosis.

Background: Multiple sclerosis (MS) is a chronic neurological condition and the leading cause of non-traumatic disability in young adults. MS pathogenesis leads to the death of oligodendrocytes, demyelination, and progressive central nervous system neurodegeneration. Endogenous remyelination occurs in people with MS (PwMS) but is insufficient to repair the damage.

Estimation of Transition Probabilities from a Large Cohort (> 6000) of Australians Living with Multiple Sclerosis (MS) for Changing Disability Severity Classifications, MS Phenotype, and Disease-Modifying Therapy Classifications.

Background: Multiple sclerosis (MS) is a chronic autoimmune/neurodegenerative disease associated with progressing disability affecting mostly women. We aim to estimate transition probabilities describing MS-related disability progression from no disability to severe disability. Transition probabilities are a vital input for health economics models.

Changes in employment status over time in multiple sclerosis following a first episode of central nervous system demyelination, a Markov multistate model study.

Background And Purpose: Understanding predictors of changes in employment status among people living with multiple sclerosis (MS) can assist health care providers to develop appropriate work retention/rehabilitation programs. We aimed to model longitudinal transitions of employment status in MS and estimate the probabilities of retaining employment status or losing or gaining employment over time in individuals with a first clinical diagnosis of central nervous system demyelination (FCD).

Methods: This prospective cohort study comprised adults (aged 18-59 years) diagnosed with FCD (n = 237) who were followed for more than 11 years.

The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study.

The indirect contribution of multiple sclerosis (MS) relapses to disability worsening outcomes, and vice-versa, remains unclear. Disease modifying therapies (DMTs) are potential modulators of this association. Understanding how these endo-phenotypes interact may provide insights into disease pathogenesis and treatment practice in relapse-onset MS (ROMS).

Genetically determined serum serine level has a novel causal effect on multiple sclerosis risk and predicts disability progression.

Background: There are currently no specific biomarkers for multiple sclerosis (MS). Identifying robust biomarkers for MS is crucial to improve disease diagnosis and management.

Methods: This study first used six Mendelian randomisation methods to assess causal relationship of 174 metabolites with MS, incorporating data from European-ancestry metabolomics (n=8569-86 507) and MS (n=14 802 MS cases, 26 703 controls) genomewide association studies.

Ensemble machine learning identifies genetic loci associated with future worsening of disability in people with multiple sclerosis.

Limited studies have been conducted to identify and validate multiple sclerosis (MS) genetic loci associated with disability progression. We aimed to identify MS genetic loci associated with worsening of disability over time, and to develop and validate ensemble genetic learning model(s) to identify people with MS (PwMS) at risk of future worsening. We examined associations of 208 previously established MS genetic loci with the risk of worsening of disability; we learned ensemble genetic decision rules and validated the predictions in an external dataset.

Novel plasma and brain proteins that are implicated in multiple sclerosis.

Understanding how variations in the plasma and brain proteome contribute to multiple sclerosis susceptibility can provide important insights to guide drug repurposing and therapeutic development for the disease. However, the role of genetically predicted protein abundance in multiple sclerosis remains largely unknown. Integrating plasma proteomics (n = 3301) and brain proteomics (n = 376 discovery; n = 152 replication) into multiple sclerosis genome-wide association studies (n = 14 802 cases and 26 703 controls), we employed summary-based methods to identify candidate proteins involved in multiple sclerosis susceptibility.

Developing a clinical-environmental-genotypic prognostic index for relapsing-onset multiple sclerosis and clinically isolated syndrome.

Our inability to reliably predict disease outcomes in multiple sclerosis remains an issue for clinicians and clinical trialists. This study aims to create, from available clinical, genetic and environmental factors; a clinical-environmental-genotypic prognostic index to predict the probability of new relapses and disability worsening. The analyses cohort included prospectively assessed multiple sclerosis cases ( = 253) with 2858 repeated observations measured over 10 years.

Pharmacophore modeling and in silico toxicity assessment of potential anticancer agents from African medicinal plants.

Molecular modeling has been employed in the search for lead compounds of chemotherapy to fight cancer. In this study, pharmacophore models have been generated and validated for use in virtual screening protocols for eight known anticancer drug targets, including tyrosine kinase, protein kinase B β, cyclin-dependent kinase, protein farnesyltransferase, human protein kinase, glycogen synthase kinase, and indoleamine 2,3-dioxygenase 1. Pharmacophore models were validated through receiver operating characteristic and Güner-Henry scoring methods, indicating that several of the models generated could be useful for the identification of potential anticancer agents from natural product databases.

Molecular modeling of potential anticancer agents from African medicinal plants.

Naturally occurring anticancer compounds represent about half of the chemotherapeutic drugs which have been put in the market against cancer until date. Computer-based or in silico virtual screening methods are often used in lead/hit discovery protocols. In this study, the "drug-likeness" of ~400 compounds from African medicinal plants that have shown in vitro and/or in vivo anticancer, cytotoxic, and antiproliferative activities has been explored.