Recent ASA presidents and ‘top’ journals: observed publication patterns, alleged cartels and varying careers

It has been common for studies presented as about American sociology as a whole to rely on data compiled from leading journals (American Sociological Review [ASR] and American Journal of Sociology [AJS]), or about presidents of the American Sociological Association [ASA], to represent it. Clearly those are important, but neither can be regarded as providing a representative sample of American sociology. Recently, Stephen Turner has suggested that dominance in the ASA rests with a ‘cartel’ initially formed in graduate school, and that it favors work in a style associated with the leading journals. The adequacy of these ideas is examined in the light of available data on the last 20 years, which show that very few of the presidents were in the same graduate schools at the same time. All presidents have had distinguished academic records, but it is shown that their publication strategies have varied considerably. Some have had no ASR publications except their presidential addresses, while books and large numbers of other journals not normally mentioned in this context have figured in their contributions, as well as being more prominent in citations. It seems clear that articles in the leading journals have not been as closely tied to prestigious careers as has sometimes been suggested, and that if there is a cartel it has not included all the presidents

Automation of a problem list using natural language processing

BACKGROUND: The medical problem list is an important part of the electronic medical record in development in our institution. To serve the functions it is designed for, the problem list has to be as accurate and timely as possible. However, the current problem list is usually incomplete and inaccurate, and is often totally unused. To alleviate this issue, we are building an environment where the problem list can be easily and effectively maintained. METHODS: For this project, 80 medical problems were selected for their frequency of use in our future clinical field of evaluation (cardiovascular). We have developed an Automated Problem List system composed of two main components: a background and a foreground application. The background application uses Natural Language Processing (NLP) to harvest potential problem list entries from the list of 80 targeted problems detected in the multiple free-text electronic documents available in our electronic medical record. These proposed medical problems drive the foreground application designed for management of the problem list. Within this application, the extracted problems are proposed to the physicians for addition to the official problem list. RESULTS: The set of 80 targeted medical problems selected for this project covered about 5% of all possible diagnoses coded in ICD-9-CM in our study population (cardiovascular adult inpatients), but about 64% of all instances of these coded diagnoses. The system contains algorithms to detect first document sections, then sentences within these sections, and finally potential problems within the sentences. The initial evaluation of the section and sentence detection algorithms demonstrated a sensitivity and positive predictive value of 100% when detecting sections, and a sensitivity of 89% and a positive predictive value of 94% when detecting sentences. CONCLUSION: The global aim of our project is to automate the process of creating and maintaining a problem list for hospitalized patients and thereby help to guarantee the timeliness, accuracy and completeness of this information

Modeling mitochondrial dysfunctions in the brain: from mice to men

The biologist Lewis Thomas once wrote: “my mitochondria comprise a very large proportion of me. I cannot do the calculation, but I suppose there is almost as much of them in sheer dry bulk as there is the rest of me”. As humans, or indeed as any mammal, bird, or insect, we contain a specific molecular makeup that is driven by vast numbers of these miniscule powerhouses residing in most of our cells (mature red blood cells notwithstanding), quietly replicating, living independent lives and containing their own DNA. Everything we do, from running a marathon to breathing, is driven by these small batteries, and yet there is evidence that these molecular energy sources were originally bacteria, possibly parasitic, incorporated into our cells through symbiosis. Dysfunctions in these organelles can lead to debilitating, and sometimes fatal, diseases of almost all the bodies’ major organs. Mitochondrial dysfunction has been implicated in a wide variety of human disorders either as a primary cause or as a secondary consequence. To better understand the role of mitochondrial dysfunction in human disease, a multitude of pharmacologically induced and genetically manipulated animal models have been developed showing to a greater or lesser extent the clinical symptoms observed in patients with known and unknown causes of the disease. This review will focus on diseases of the brain and spinal cord in which mitochondrial dysfunction has been proven or is suspected and on animal models that are currently used to study the etiology, pathogenesis and treatment of these diseases

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Adaptation to Progressive Additive Lenses: Potential Factors to Consider

People develop presbyopia as part of the normal aging process. Most presbyopes adapt to progressive additive lens (PALs), while others do not. This investigation sought to determine whether the ability to modify disparity vergence or phoria was correlated to PALs adaptation. In experiment 1, a double-step paradigm quantified the ability to modify convergence responses in sixteen presbyopes. In experiment 2, thirty-one incipient presbyopes participated in a 5-minute sustained fixation task to evoke phoria adaptation where the magnitude and rate of phoria adaptation were measured. Then, the experiment was repeated after wearing PALs for one month. Linear regression analyses were conducted between the following parameters: near point of convergence, positive fusional vergence at near, vergence facility, net change in the magnitude of phoria adaptation, and the rate of phoria adaptation. The ability to change convergence average peak velocity was significantly greater (p \u3c 0.03) in presbyopic PALs adapters compared to presbyopic PALs non-adapters. The rate of phoria adaptation and vergence facility were significantly greater (p \u3c 0.03) in incipient presbyopic PALs adapters compared to incipient presbyopic PALs non-adapters. Vergence facility and the rate of phoria adaptation may have potential clinical utility in differentiating which patients may adapt to PALs and which ones will have more difficulty

Deficiency of Lipoprotein Lipase in Neurons Decreases AMPA Receptor Phosphorylation and Leads to Neurobehavioral Abnormalities in Mice

Alterations in lipid metabolism have been found in several neurodegenerative disorders, including Alzheimer’s disease. Lipoprotein lipase (LPL) hydrolyzes triacylglycerides in lipoproteins and regulates lipid metabolism in multiple organs and tissues, including the central nervous system (CNS). Though many brain regions express LPL, the functions of this lipase in the CNS remain largely unknown. We developed mice with neuron-specific LPL deficiency that became obese on chow by 16 wks in homozygous mutant mice (NEXLPL-/-) and 10 mo in heterozygous mice (NEXLPL+/-). In the present study, we show that 21 mo NEXLPL+/- mice display substantial cognitive function decline including poorer learning and memory, and increased anxiety with no difference in general motor activities and exploratory behavior. These neurobehavioral abnormalities are associated with a reduction in the 2-amino-3-(3-hydroxy-5-methyl-isoxazol-4-yl) propanoic acid (AMPA) receptor subunit GluA1 and its phosphorylation, without any alterations in amyloid β accumulation. Importantly, a marked deficit in omega-3 and omega-6 polyunsaturated fatty acids (PUFA) in the hippocampus precedes the development of the neurobehavioral phenotype of NEXLPL+/- mice. And, a diet supplemented with n-3 PUFA can improve the learning and memory of NEXLPL+/- mice at both 10 mo and 21 mo of age. We interpret these findings to indicate that LPL regulates the availability of PUFA in the CNS and, this in turn, impacts the strength of synaptic plasticity in the brain of aging mice through the modification of AMPA receptor and its phosphorylation