Biological Mechanisms and Evolution

Recent work in philosophy of biology has challenged the traditional assumption in philosophy of science that proper scientific explanations and predictions must be grounded in laws of nature that hold with necessity. Philosophical work on mechanisms in biology and cognitive science has shown that the traditional view, on its own, is too restrictive to account for scientific explanations and predictions in the complex, contingent realm of living systems. In the first part of my dissertation, I defend the view that a mechanistic approach to biology is preferable to the traditional approach, and I defend my own realist account of biological mechanisms. While most authors seem to consider the mechanistic approach in the life sciences to be a heuristic device rather than an objective description of nature, I argue that biological mechanisms are real in the same sense that planets, molecules, and life itself are real. Specifically, I argue that a biological mechanism is a structure or process that is part of and maintained by a living organism, and works to promote continuation of the ongoing living process of which the mechanism is a part. So, as long as organisms and life are real, biological mechanisms are also real. In the second part of my dissertation, I apply the mechanistic approach defended in Part One to the three process that together result in biological evolution: hereditary reproduction, generation of new variations, and natural selection. I show that the mechanistic approach helps clarify our understanding of how each process works (and does not work) on its own, and how each contributes to biological evolution. I consider whether each process, along with the physical realizers that bring it about, meet the criteria for being a biological mechanism as laid out in Part One. All three processes are often referred to as mechanisms, but I conclude that while there are biological mechanisms for achieving heredity and generation of new variations, the process of natural selection does not meet the criteria for being a biological mechanism, nor does the overall process of biological evolution

Transcription factor genetics and biology in predisposition to bone marrow failure and hematological malignancy

Transcription factors (TFs) play a critical role as key mediators of a multitude of developmental pathways, with highly regulated and tightly organized networks crucial for determining both the timing and pattern of tissue development. TFs can act as master regulators of both primitive and definitive hematopoiesis, tightly controlling the behavior of hematopoietic stem and progenitor cells (HSPCs). These networks control the functional regulation of HSPCs including self-renewal, proliferation, and differentiation dynamics, which are essential to normal hematopoiesis. Defining the key players and dynamics of these hematopoietic transcriptional networks is essential to understanding both normal hematopoiesis and how genetic aberrations in TFs and their networks can predispose to hematopoietic disease including bone marrow failure (BMF) and hematological malignancy (HM). Despite their multifaceted and complex involvement in hematological development, advances in genetic screening along with elegant multi-omics and model system studies are shedding light on how hematopoietic TFs interact and network to achieve normal cell fates and their role in disease etiology. This review focuses on TFs which predispose to BMF and HM, identifies potential novel candidate predisposing TF genes, and examines putative biological mechanisms leading to these phenotypes. A better understanding of the genetics and molecular biology of hematopoietic TFs, as well as identifying novel genes and genetic variants predisposing to BMF and HM, will accelerate the development of preventative strategies, improve clinical management and counseling, and help define targeted treatments for these diseases.Jiarna R. Zerella, Claire C. Homan, Peer Arts, Anna L. Brown, Hamish S. Scott, and Christopher N. Hah

The Grizzly, September 17, 2009

Recycling Team Takes Action Against Campus Waste • Annual Activities Fair Starts the Year Off • Campus Safety, Police Relations: Battle of Jurisdiction • Berman\u27s New Exhibit: Muriel\u27s Moores • Is the Power Plant Damaging More Than Our Eardrums? • Restaurant Review: Iron Hill Brewery • Club Spotlight: InterVarsity Christian Fellowship • Hidden Treasures in the Berman and Myrin • Opinion: Liberal Arts, Limited Choices?; Facebook Friends: How Far is Too Far?; Obama\u27s Administration and the Takeover of the Communist Czar Regime; Socialism is the New Word for Progress • UC Men\u27s Soccer Coach Adds Sustainability Coordinator to His Title • Positivity and Friendship Staples of the UC Women\u27s Volleyball Teamhttps://digitalcommons.ursinus.edu/grizzlynews/1791/thumbnail.jp

Diagnostic accuracy of the primary care screener for affective disorder (PC-SAD) in primary care

Background: Depression goes often unrecognised and untreated in non-psychiatric medical settings. Screening has recently gained acceptance as a first step towards improving depression recognition and management. The Primary Care Screener for Affective Disorders (PC-SAD) is a self-administered questionnaire to screen for Major Depressive Disorder (MDD) and Dysthymic Disorder (Dys) which has a sophisticated scoring algorithm that confers several advantages. This study tested its performance against a ‘gold standard’ diagnostic interview in primary care. Methods: A total of 416 adults attending 13 urban general internal medicine primary care practices completed the PC-SAD. Of 409 who returned a valid PC-SAD, all those scoring positive (N=151) and a random sample (N=106) of those scoring negative were selected for a 3-month telephone follow-up assessment including the administration of the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID-I) by a psychiatrist who was masked to PC-SAD results. Results: Most selected patients (N=212) took part in the follow-up assessment. After adjustment for partial verification bias the sensitivity, specificity, positive and negative predictive value for MDD were 90%, 83%, 51%, and 98%. For Dys, the corresponding figures were 78%, 79%, 8%, and 88%. Conclusions: While some study limitations suggest caution in interpreting our results, this study corroborated the diagnostic validity of the PC-SAD, although the low PPV may limit its usefulness with regard to Dys. Given its good psychometric properties and the short average administration time, the PC-SAD might be the screening instrument of choice in settings where the technology for computer automated scoring is available

The astrobiology primer: An outline of general knowledge - Version 1, 2006

Peer reviewe