Using C. elegans to discover therapeutic compounds for ageing-associated neurodegenerative diseases

Age-associated neurodegenerative disorders such as Alzheimer’s disease are a major public health challenge, due to the demographic increase in the proportion of older individuals in society. However, the relatively few currently approved drugs for these conditions provide only symptomatic relief. A major goal of neurodegeneration research is therefore to identify potential new therapeutic compounds that can slow or even reverse disease progression, either by impacting directly on the neurodegenerative process or by activating endogenous physiological neuroprotective mechanisms that decline with ageing. This requires model systems that can recapitulate key features of human neurodegenerative diseases that are also amenable to compound screening approaches. Mammalian models are very powerful, but are prohibitively expensive for high-throughput drug screens. Given the highly conserved neurological pathways between mammals and invertebrates, Caenorhabditis elegans has emerged as a powerful tool for neuroprotective compound screening. Here we describe how C. elegans has been used to model various human ageing-associated neurodegenerative diseases and provide an extensive list of compounds that have therapeutic activity in these worm models and so may have translational potential

Screening out irrelevant cell-based models of disease

The common and persistent failures to translate promising preclinical drug candidates into clinical success highlight the limited effectiveness of disease models currently used in drug discovery. An apparent reluctance to explore and adopt alternative cell-and tissue-based model systems, coupled with a detachment from clinical practice during assay validation, contributes to ineffective translational research. To help address these issues and stimulate debate, here we propose a set of principles to facilitate the definition and development of disease-relevant assays, and we discuss new opportunities for exploiting the latest advances in cell-based assay technologies in drug discovery, including induced pluripotent stem cells, three-dimensional (3D) co-culture and organ-on-a-chip systems, complemented by advances in single-cell imaging and gene editing technologies. Funding to support precompetitive, multidisciplinary collaborations to develop novel preclinical models and cell-based screening technologies could have a key role in improving their clinical relevance, and ultimately increase clinical success rates

NMR Metabolomics Protocols for Drug Discovery

Drug discovery is an extremely difficult and challenging endeavor with a very high failure rate. The task of identifying a drug that is safe, selective and effective is a daunting proposition because disease biology is complex and highly variable across patients. Metabolomics enables the discovery of disease biomarkers, which provides insights into the molecular and metabolic basis of disease and may be used to assess treatment prognosis and outcome. In this regard, metabolomics has evolved to become an important component of the drug discovery process to resolve efficacy and toxicity issues, and as a tool for precision medicine. A detailed description of an experimental protocol is presented that outlines the application of NMR metabolomics to the drug discovery pipeline. This includes: (1) target identification by understanding the metabolic dysregulation in diseases, (2) predicting the mechanism of action of newly discovered or existing drug therapies, (3) and using metabolomics to screen a chemical lead to assess biological activity. Unlike other OMICS approaches, the metabolome is “fragile”, and may be negatively impacted by improper sample collection, storage and extraction procedures. Similarly, biologically-irrelevant conclusions may result from incorrect data collection, pre-processing or processing procedures, or the erroneous use of univariate and multivariate statistical methods. These critical concerns are also addressed in the protocol

Transitoriness in cancer patients: a cross-sectional survey of lung and gastrointestinal cancer patients.

Despite earlier diagnosis and advancements in treatment, cancer remains a leading cause of death in the world (13% of all deaths according to the World Health Organization) among men and women. Cancer accounts for approximately 20% of the deaths in the USA every year. Here, we report the findings from a cross-sectional survey of psychosocial factors in lung and gastrointestinal cancer patients. The aim of the study was to explore the associations among transitoriness, uncertainty, and locus of control (LOC) with quality of life. Transitoriness is defined as a person's confrontation with life's finitude due to a cancer diagnosis. A total of 126 patients with lung or gastrointestinal cancer completed eight self-reporting questionnaires addressing demographics, spiritual perspective, symptom burden, transitoriness, uncertainty, LOC, and quality of life. Transitoriness, uncertainty, and LOC were significantly associated with one another (r = 0.3267, p = 0.0002/r = 0.1994, p = 0.0252, respectively). LOC/belief in chance has a significant inverse relationship with patients' quality of life (r = -0.2505, p = 0.0047). Transitoriness, uncertainty, and LOC were found to have a significant inverse relationship with patients' quality of life (transitoriness state: r = -0.5363, p = 0.0000/trait: r = -0.4629, p = 0.0000/uncertainty: r = -0.4929, p = 0.0000/internal LOC: r = 0.1759, p = 0.0489/chance LOC: r = -0.2505, p = 0.0047). Transitoriness, uncertainty, and LOC are important concepts as they adversely influence patients' quality of life. Incorporating this finding into the care of cancer patients may provide them with the support they need to cope with treatment and maintenance of a positive quality of life

Crossover equation of state models applied to the critical behavior of Xenon

The turbidity ( τ ) measurements of Güttinger and Cannell (Phys Rev A 24:3188–3201, 1981) in the temperature range 28mK≤T−Tc≤29K along the critical isochore of homogeneous xenon are reanalyzed. The singular behaviors of the isothermal compressibility ( κT ) and the correlation length ( ξ ) predicted from the master crossover functions are introduced in the turbidity functional form derived by Puglielli and Ford (Phys Rev Lett 25:143–146, 1970). We show that the turbidity data are thus well represented by the Ornstein–Zernike approximant, within 1 % precision. We also introduce a new crossover master model (CMM) of the parametric equation of state for a simple fluid system with no adjustable parameter. The CMM model and the phenomenological crossover parametric model are compared with the turbidity data and the coexisting liquid–gas density difference ( ΔρLV ). The excellent agreement observed for τ , κT , ξ , and ΔρLV in a finite temperature range well beyond the Ising-like preasymptotic domain confirms that the Ising-like critical crossover behavior of xenon can be described in conformity with the universal features estimated by the renormalization-group methods. Only 4 critical coordinates of the vapor–liquid critical point are needed in the (pressure, temperature, molecular volume) phase surface of xenon