Molluscan memory of injury: evolutionary insights into chronic pain and neurological disorders.

Molluscan preparations have yielded seminal discoveries in neuroscience, but the experimental advantages of this group have not, until now, been complemented by adequate molecular or genomic information for comparisons to genetically defined model organisms in other phyla. The recent sequencing of the transcriptome and genome of Aplysia californica, however, will enable extensive comparative studies at the molecular level. Among other benefits, this will bring the power of individually identifiable and manipulable neurons to bear upon questions of cellular function for evolutionarily conserved genes associated with clinically important neural dysfunction. Because of the slower rate of gene evolution in this molluscan lineage, more homologs of genes associated with human disease are present in Aplysia than in leading model organisms from Arthropoda (Drosophila) or Nematoda (Caenorhabditis elegans). Research has hardly begun in molluscs on the cellular functions of gene products that in humans are associated with neurological diseases. On the other hand, much is known about molecular and cellular mechanisms of long-term neuronal plasticity. Persistent nociceptive sensitization of nociceptors in Aplysia displays many functional similarities to alterations in mammalian nociceptors associated with the clinical problem of chronic pain. Moreover, in Aplysia and mammals the same cell signaling pathways trigger persistent enhancement of excitability and synaptic transmission following noxious stimulation, and these highly conserved pathways are also used to induce memory traces in neural circuits of diverse species. This functional and molecular overlap in distantly related lineages and neuronal types supports the proposal that fundamental plasticity mechanisms important for memory, chronic pain, and other lasting alterations evolved from adaptive responses to peripheral injury in the earliest neurons. Molluscan preparations should become increasingly useful for comparative studies across phyla that can provide insight into cellular functions of clinically important genes.

Prophylactic mastectomy and oophorectomy for women at risk of breast and ovarian cancer: Incorporating preferences in a decision analysis

The discoveries of the BRCA1 and BRCA2 genes have made it possible for women of families with hereditary breast/ovarian cancer to determine if they carry cancer-predisposing genetic mutations. Women with germline mutations have significantly higher probabilities of developing both cancers than the general population. Since the presence of a BRCA1 or BRCA2 mutation does not guarantee future cancer development, the appropriate course of action remains uncertain for these women. Prophylactic mastectomy and oophorectomy remain controversial since the underlying premise for surgical intervention is based more upon reduction in the estimated risk of cancer than on actual evidence of clinical benefit. Issues that are incorporated in a woman's decision making process include quality of life without breasts, ovaries, attitudes toward possible surgical morbidity as well as a remaining risk of future development of breast/ovarian cancer despite prophylactic surgery. The incorporation of patient preferences into decision analysis models can determine the quality-adjusted survival of different prophylactic approaches to breast/ovarian cancer prevention. Monte Carlo simulation was conducted on 4 separate decision models representing prophylactic oophorectomy, prophylactic mastectomy, prophylactic oophorectomy/mastectomy and screening. The use of 3 separate preference assessment methods across different populations of women allows researchers to determine how quality adjusted survival varies according to clinical strategy, method of preference assessment and the population from which preferences are assessed. ^

Lethal giant discs, a novel C2 domain protein, restricts Notch activation during endocytosis

The Notch signaling pathway plays a central role in metazoan growth and patterning, and its deregulation leads to many human diseases, including cancer. It is therefore important to understand the modes of Notch signaling regulation. Recent discoveries have demonstrated that mutations in conserved endosomal pathway components such as Erupted and Vps25 can ectopically activate Notch signaling in Drosophila. Mutations in the tumor suppressor lethal giant discs (lgd) display similar but even stronger and more specific Notch activation than in the erupted and vps25 mutant animals. This Notch activation in lgd mutant tissues causes hyperplastic overgrowth of the Drosophila imaginal discs, and the eventual lethality of the animal. However, the gene that encodes Lgd, and its function in the Notch pathway have not yet been identified. ^ I have found that Lgd is a novel, conserved C2 domain protein that regulates Notch trafficking. Lgd cell-autonomously restricts Notch signaling in the Drosophila wing disc to the target cells in the D/V boundary. The function of Lgd lies at or upstream of Notch S3 activation, but Lgd doesn't affect the binding affinities between Notch and Delta. Lgd is also not required for cis-inhibition of Notch signaling by ligands. Notch accumulates on the early endosome in lgd mutant cells and signals in a ligand-independent manner, a result that has previously been seen in endosomal pathway mutants. Interestingly, Notch activation in lgd mutant cells is dependent on the endosomal protein Hrs, and Lgd activity appears to be downstream of Hrs function in endocytosis. Taken together, my data identify Lgd as a novel tumor suppressor protein that regulates Notch signaling by targeting Notch for degradation or recycling. ^

MicroRNA Regulation of Prostate Cancer Stem/Progenitor Cells and Prostate Cancer Development

Most human tumors contain a population of cells with stem cell properties, called cancer stem cells (CSCs), which are believed to be responsible for tumor establishment, metastasis, and resistance to clinical therapy. It’s crucial to understand the regulatory mechanisms unique to CSCs, so that we may design CSC-specific therapeutics. Recent discoveries of microRNA (miRNA) have provided a new avenue in understanding the regulatory mechanisms of cancer. However, how miRNAs may regulate CSCs is still poorly understood. Here, we present miRNA expression profiling in six populations of prostate cancer (PCa) stem/progenitor cells that possess distinct tumorigenic properties. Six miRNAs were identified to be commonly and differentially expressed, namely, four miRNAs (miR-34a, let-7b, miR-106a and miR-141) were under-expressed, and two miRNAs (miR-301 and miR-452) were over-expressed in the tumorigenic subsets compared to the corresponding marker-negative subpopulations. Among them, the expression patterns of miR-34, let-7b, miR-141 and miR-301 were further confirmed in the CD44+ human primary prostate cancer (HPCa) samples. We then showed that miR-34a functioned as a critical negative regulator in prostate CSCs and PCa development and metastasis. Over-expression of miR-34a in either bulk or CD44+ PCa cells significantly suppressed clonal expansion, tumor development and metastasis. Systemic delivery of miR-34a in tumor-bearing mice demonstrated a potent therapeutic effect again tumor progression and metastasis, leading to extended animal survival. Of great interest, we identified CD44 itself as a direct and relevant downstream target of miR-34a in mediating its tumor-inhibitory effects. Like miR-34a, let-7 manifests similar tumor suppressive effects in PCa cells. In addition, we observed differential mechanisms between let-7 and miR-34a on cell cycle, with miR-34a mainly inducing G1 cell-cycle arrest followed by cell senescence and let-7 inducing G2/M arrest. MiR-301, on the other hand, exerted a cell type dependent effect in regulating prostate CSC properties and PCa development. In summary, our work reveals that the prostate CSC populations display unique miRNA expression signatures and different miRNAs distinctively and coordinately regulate various aspects of CSC properties. Altogether, our results lay a scientific foundation for developing miRNA-based anti-cancer therapy.

Microbe Hunters Revisited – Paul de Kruif and the Beginning of Popular Science Writing

Paul de Kruif is credited with being one of the first popular science writers for the general public. He received his Ph.D. from the University of Michigan in 1916 and worked at the Rockefeller Institute under Simon Flexner. After being fired in 1922 for publishing a scathing article on medical research, de Kruif caught the attention of Sinclair Lewis, who used his scientific background to write his Pulitzer Prize winning novel, Arrowsmith. In 1926, de Kruif published Microbe Hunters which recounted the exploits and discoveries of 14 renowned microbiologists from von Leeuwenhoek to Pasteur, Ross, Paul Ehrlich and Walter Reed. Microbe Hunters became a best seller, was translated into 18 languages, and formed the basis of two Hollywood movies, "Yellow Jack" and "The Magic Bullet." Generations of young readers were captivated by the vivid protrayal of these men and their discoveries.

William Osler: Original Papers 1881-1897

Part 1: 1881-1888 On Some Points in the Etiology and Pathology of Ulcerative Endocarditis, 1881 On Certain Parasites in the Blood of the Frog, 1883 The Third Corpuscle of the Blood, 1883 On the Use of Arsenic in Certain Forms of Anaemia, 1886 Antifebrin, 1887 Case of Arterio-Venous Aneurism of the Axillary Artery and Vein of Fourteen Year's Duration, 1887 Typhilitis and Appendicitis, 1888 Part 2: 1889-1892 Annual Address - License to Practice 1889 Case of Syphiloma of the Cord of the Cauda Equina-Death From Diffuse Central Myelitis, 1889 On a Case of Simple Idiopathic Muscular Atrophy, Involving the Face and the Scapulo-Humeral Muscles, 1889 Note on Intra-Thoracic Growths Developing from the Thyroid Gland, 1889 On the Value of Laveran's Organisms in the Diagnosis of Malaria, 1889 On the Form of Convulsive Tic Associated with Corprolalia, Etc., 1890 A Case of Sensory Aphasia Word-blindness with Hemianopsia, 1891 Rudolf Virchow: The Man and the Student, 1891 The Healing of Tuberculosis, 1892 The Cold-Bath Treatment of Typhoid Fever, 1892 Part 3: 1893 Remarks on the Varieties of Chronic Chorea, and a Report Upon Two Families of the Hereditary Form, With One Autopsy, 1893 Note on Arsenical Neuritis Following the use of Fowler's Solution, 1893 Note on a Remarkable House Epidemic of Typhoid Fever, 1893 Cases of Sub-Phrenic Abscess, 1893 On Sporadic Cretinism in America, 1893 Notes on Tuberculosis in Children, 1893 Part 4: 1849-1895 Parotitis in Pneumonia, Case of Pericarditis Treated by Incision and Drainage, 1894 The Army Surgeon, 1894 Introductory Remarks to Course of Clinical Demonstrations on Typhoid Fever, 1894 Cancer of the Stomach with Very Rapid Course, 1895 Case of Sporadic Cretinism (Infantile Myxcedema) Treated Successfully with Thyroid Extract, 1895 Visible Contractile Tumour of the Pylorus Following Ulcer of the Stomach, 1895 On the Association of Enormous Heart Hypertrophy, Chronic Proliferative Peritonitis, and Recurring Ascites, with Adherent Pericardium, 1895 Teaching and Thinking the Two Functions of a Medical School, 1895 The Practical Value of Laveran's Discoveries, 1895 Part 5 1896 Addison's Disease, 1896 On Six Cases of Addison's Disease, 1896 Hemiplegia in Typhoid Fever Thomas Dover (of Dover's Powder) Physician and Buccaneer, 1896 John Keats The Apothecary Poet, 1896 On The Classification of the Tics or Habit Movements, 1896 The Cerebral Complication of Raynaud's Disease, 1896 Part 6: 1897 On Certain Features in the Prognosis of Pneumonia, 1897 Clinical Lecture on Mitral Stenosis - Sudden Death - Ball Thrombus in the Left Auricle, 1897 The Diagnosis of Malarial Fever, 1897 The Functions of a State Faculty (President's Address), 1897 A Clinical Lecture on The Ball-Valve Gall-Stone in the Common Duct, 1897 Pneumonia (Review of Cases studied), 1897 Internal Medicine as a Vocation, 1897 Back Notes

INTERACTION OF BACILLUS ANTHRACIS EXOSPORIUM PROTEIN BCLA WITH COMPLEMENT FACTOR H AND SPORE PERSISTENCE IN THE LUNG

Anthrax outbreaks in the United States and Europe and its potential use as a bioweapon have made Bacillus anthracis an interest of study. Anthrax infections are caused by the entry of B. anthracis spores into the host via the respiratory system, the gastrointestinal tract, cuts or wounds in the skin, and injection. Among these four forms, inhalational anthrax has the highest lethality rate and persistence of spores in the lungs of animals following pulmonary exposure has been noted for decades. However, details or mechanisms of spore persistence were not known. In this study, we investigated spore persistence in a mouse model. The results suggest that B. anthracis spores have special properties that promote persistence in the lung, and that there may be multiple mechanisms contributing to spore persistence. Moreover, recent discoveries from our laboratory suggest that spores evolved a sophisticated mechanism to interact with the host complement system. The complement system is a crucial part of the host defense mechanism against foreign microorganisms. Knowledge of the specific interactions that occur between the complement system and B. anthracis was limited. Studies performed in our laboratory have suggested that spores of B. anthracis can target specific proteins, such as Factor H (fH) of the complement system. Spores of B. anthracis are enclosed by an exosporium, which consists of a basal layer surrounded by a nap of hair-like filaments. The major structural component of the filaments is called Bacillus collagen-like protein of anthracis (BclA), which comprises a central collagen-like region and a globular C-terminal domain. BclA is the first point of contact with the innate system of an infected host. In this study, we investigated the molecular details of BclA-fH interaction with respect to the specific binding mechanism and the functional significance of this interaction in a murine model of anthrax infection. We hypothesized that the recruitment of fH to the spore surface by BclA limits the extent of complement activation and promotes pathogen survival and persistence in the infected host. Findings from this study are significant to understanding how to treat post-exposure prophylaxis and improve our knowledge of spores with the host immune system.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.