Immunology and Homeopathy. 5. The Rationale of the ‘Simile’

The foundation of homeopathic medicine is the ‘Similia Principle’, also known as the ‘Principle of Similarity’ or also as the ‘Simile’, which reflects the inversion of pharmacological effects in healthy subjects as compared with sick ones. This article describes the inversion of effects, a widespread medical phenomenon, through three possible mechanisms: non-linearity of dose–response relationship, different initial pathophysiological states of the organism, and pharmacodynamics of body response to the medicine. Based on the systemic networks which play an important role in response to stress, a unitary and general model is designed: homeopathic medicines could interact with sensitive (primed) regulation systems through complex information, which simulate the disorders of natural disease. Reorganization of regulation systems, through a coherent response to the medicine, could pave the way to the healing of the cellular, tissue and neuro-immuno-endocrine homeodynamics. Preliminary evidence is suggesting that even ultra-low doses and high-dilutions of drugs may incorporate structural or frequency information and interact with chaotic dynamics and physical-electromagnetic levels of regulation. From the clinical standpoint, the ‘simile’ can be regarded as a heuristic principle, according to which the detailed knowledge of pathogenic effects of drugs, associated with careful analysis of signs and symptoms of the ill subject, could assist in identifying homeopathic remedies with high grade of specificity for the individual case

The Interplay among PINK1/PARKIN/Dj-1 Network during Mitochondrial Quality Control in Cancer Biology: Protein Interaction Analysis

PARKIN (E3 ubiquitin ligase PARK2), PINK1 (PTEN induced kinase 1) and DJ-1 (PARK7) are proteins involved in autosomal recessive parkinsonism, and carcinogenic processes. In damaged mitochondria, PINK1's importing into the inner mitochondrial membrane is prevented, PARKIN presents a partial mitochondrial localization at the outer mitochondrial membrane and DJ-1 relocates to mitochondria when oxidative stress increases. Depletion of these proteins result in abnormal mitochondrial morphology. PINK1, PARKIN, and DJ-1 participate in mitochondrial remodeling and actively regulate mitochondrial quality control. In this review, we highlight that PARKIN, PINK1, and DJ-1 should be regarded as having an important role in Cancer Biology. The STRING database and Gene Ontology (GO) enrichment analysis were performed to consolidate knowledge of well-known protein interactions for PINK1, PARKIN, and DJ-1 and envisage new ones. The enrichment analysis of KEGG pathways showed that the PINK1/PARKIN/DJ-1 network resulted in Parkinson disease as the main feature, while the protein DJ-1 showed enrichment in prostate cancer and p53 signaling pathway. Some predicted transcription factors regulating PINK1, PARK2 (PARKIN) and PARK7 (DJ-1) gene expression are related to cell cycle control. We can therefore suggest that the interplay among PINK1/PARKIN/DJ-1 network during mitochondrial quality control in cancer biology may occur at the transcriptional level. Further analysis, like a systems biology approach, will be helpful in the understanding of PINK1/PARKIN/DJ-1 network.Peer reviewedFinal Published versio

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology

An Aggregation of Aggregation Methods in Computational Pathology

Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide images (WSIs) often process a large number of tiles (sub-images) and require aggregating predictions from the tiles in order to predict WSI-level labels. In this paper, we present a review of existing literature on various types of aggregation methods with a view to help guide future research in the area of computational pathology (CPath). We propose a general CPath workflow with three pathways that consider multiple levels and types of data and the nature of computation to analyse WSIs for predictive modelling. We categorize aggregation methods according to the context and representation of the data, features of computational modules and CPath use cases. We compare and contrast different methods based on the principle of multiple instance learning, perhaps the most commonly used aggregation method, covering a wide range of CPath literature. To provide a fair comparison, we consider a specific WSI-level prediction task and compare various aggregation methods for that task. Finally, we conclude with a list of objectives and desirable attributes of aggregation methods in general, pros and cons of the various approaches, some recommendations and possible future directions.Comment: 32 pages, 4 figure

2010 Conference Abstracts: Annual Undergraduate Research Conference at the Interface of Biology and Mathematics

Abstract book for the Second Annual Undergraduate Research Conference at the Interface of Biology and Mathematics Date: November 19 - 20, 2010Plenary speaker: Abdul-Aziz Yakubu, Professor and Chair of the Department of Mathematics, Howard UniversityFeatured speaker: Jory Weintraub, Assistant Director Education and Outreach, National Evolutionary Synthesis Cente