1,190 research outputs found
The \u3cem\u3elet-7\u3c/em\u3e MicroRNA Family Members \u3cem\u3emir\u3c/em\u3e-48, \u3cem\u3emir\u3c/em\u3e-84, and mir-241 Function Together to Regulate Developmental Timing in \u3cem\u3eCaenorhabditis elegans\u3c/em\u3e
The microRNA let-7 is a critical regulator of developmental timing events at the larval-to-adult transition in C. elegans. Recently, microRNAs with sequence similarity to let-7 have been identified. We find that doubly mutant animals lacking the let-7 family microRNA genes mir-48 and mir-84 exhibit retarded molting behavior and retarded adult gene expression in the hypodermis. Triply mutant animals lacking mir-48, mir-84, and mir-241 exhibit repetition of L2-stage events in addition to retarded adult-stage events. mir-48, mir-84, and mir-241 function together to control the L2-to-L3 transition, likely by base pairing to complementary sites in the hbl-1 3′ UTR and downregulating hbl-1 activity. Genetic analysis indicates that mir-48, mir-84, and mir-241 specify the timing of the L2-to-L3 transition in parallel to the heterochronic genes lin-28 and lin-46. These results indicate that let-7 family microRNAs function in combination to affect both early and late developmental timing decisions
Roundtable discussion: reflection on twenty years of bank regulatory reform
In 1986 the American Bankers Association asked five banking academics to assess and recommend policy options to improve the banking system's efficiency, performance, and safety. The report these five economists produced, Perspectives on Safe and Sound Banking: Past, Present, and Future, has in many ways served as a roadmap for ensuing bank regulatory reforms. In this roundtable discussion, each of the five authors reflects on the past twenty years and the current status of the banking industry and, in some cases, shares thoughts about the industry's future direction.Banks and banking ; Bank supervision
Most \u3cem\u3eCaenorhabditis elegans\u3c/em\u3e MicroRNAs are Individually Not Essential for Development or Viability
MicroRNAs (miRNAs), a large class of short noncoding RNAs found in many plants and animals, often act to post-transcriptionally inhibit gene expression. We report the generation of deletion mutations in 87 miRNA genes in Caenorhabditis elegans, expanding the number of mutated miRNA genes to 95, or 83% of known C. elegans miRNAs. We find that the majority of miRNAs are not essential for the viability or development of C. elegans, and mutations in most miRNA genes do not result in grossly abnormal phenotypes. These observations are consistent with the hypothesis that there is significant functional redundancy among miRNAs or among gene pathways regulated by miRNAs. This study represents the first comprehensive genetic analysis of miRNA function in any organism and provides a unique, permanent resource for the systematic study of miRNAs
Changes in Physician Antipsychotic Prescribing Preferences, 2002–2007
Objective
Physician antipsychotic prescribing behavior may be influenced by comparative effectiveness evidence, regulatory warnings, and formulary and other restrictions on these drugs. This study measured changes in the degree to which physicians are able to customize treatment choices and changes in physician preferences for specific agents after these events.
Methods
The study used 2002–2007 prescribing data from the IMS Health Xponent database and data on physician characteristics from the American Medical Association for a longitudinal cohort of 7,399 physicians. Descriptive and multivariable regression analyses were conducted of the concentration of prescribing (physician-level Herfindahl index) and preferences for and likelihood of prescribing two first-generation antipsychotics and six second-generation antipsychotics. Analyses adjusted for prescribing volume, specialty, demographic characteristics, practice setting, and education.
Results
Antipsychotic prescribing was highly concentrated at the physician level, with a mean unadjusted Herfindahl index of .33 in 2002 and .29 in 2007. Psychiatrists reduced the concentration of their prescribing more over time than did other physicians. High-volume psychiatrists had a Herfindahl index that was half that of low-volume physicians in other specialties (.18 versus .36), a difference that remained significant (p<.001) after adjustment for physician characteristics. The share of physicians preferring olanzapine dropped from 29.9% in 2002 to 10.3% in 2007 (p<.001) while the share favoring quetiapine increased from 9.4% to 44.5% (p<.001). Few physicians (<5%) preferred a first-generation antipsychotic in 2002 or 2007.
Conclusions
Preferences for specific antipsychotics changed dramatically during this period. Although physician prescribing remained heavily concentrated, the concentration decreased over time, particularly among psychiatrists.National Institute of Mental Health (U.S.) (Grant R01MH093359)National Institute of Mental Health (U.S.) (Grant P30 MH090333)National Institute of Mental Health (U.S.) (Grant R01MH087488)Agency for Healthcare Research and Quality (Grant R01HS017695)Robert Wood Johnson Foundation (Investigator Award in Health Policy Research
How Quickly Do Physicians Adopt New Drugs? The Case of Second-Generation Antipsychotics
Objective The authors examined physician adoption of second-generation antipsychotic medications and identified physician-level factors associated with early adoption.
Methods The authors estimated Cox proportional-hazards models of time to adoption of nine second-generation antipsychotics by 30,369 physicians who prescribed antipsychotics between 1996 and 2008, when the drugs were first introduced, and analyzed the total number of agents prescribed during that time. The models were adjusted for physicians’ specialty, demographic characteristics, education and training, practice setting, and prescribing volume. Data were from IMS Xponent, which captures over 70% of all prescriptions filled in the United States, and the American Medical Association Physician Masterfile.
Results On average, physicians waited two or more years before prescribing new second-generation antipsychotics, but there was substantial heterogeneity across products in time to adoption. General practitioners were much slower than psychiatrists to adopt second-generation antipsychotics (hazard ratios (HRs) range .10−.35), and solo practitioners were slower than group practitioners to adopt most products (HR range .77−.89). Physicians with the highest antipsychotic-prescribing volume adopted second-generation antipsychotics much faster than physicians with the lowest volume (HR range .15−.39). Psychiatrists tended to prescribe a broader set of antipsychotics (median=6) than general practitioners and neurologists (median=2) and pediatricians (median=1).
Conclusions As policy makers search for ways to control rapid health spending growth, understanding the factors that influence physician adoption of new medications will be crucial in the efforts to maximize the value of care received by individuals with mental disorders as well as to improve medication safety.National Institute of Mental Health (U.S.) (R01 MH093359)Robert Wood Johnson Foundation (Investigator Award in Health Policy Research)Agency for Healthcare Research and Quality (R01HS017695)National Institute of Mental Health (U.S.) ((NIMH) R34 MH082682)National Institute of Mental Health (U.S.) ((NIMH) P30 MH090333)National Institute of Mental Health (U.S.) ((NIMH) R01 MH087488)National Science Foundation (U.S.) (0915674
Regional Variation in Physician Adoption of Antipsychotics: Impact on US Medicare expenditures
Background—Regional variation in US Medicare prescription drug spending is driven by higher prescribing of costly brand-name drugs in some regions. This variation likely arises from differences in the speed of diffusion of newly-approved medications. Second-generation
antipsychotics were widely adopted for treatment of severe mental illness and for several off-label uses. Rapid diffusion of new psychiatric drugs likely increases drug spending but its relationship to non-drug spending is unclear. The impact of antipsychotic diffusion on drug and medical
spending is of great interest to public payers like Medicare, which finance a majority of mental health spending in the U.S.National Institute of Mental Health (U.S.) (R01 MH093359
Receptors and Other Signaling Proteins Required for Serotonin Control of Locomotion in Caenorhabditis elegans
A better understanding of the molecular mechanisms of signaling by the neurotransmitter serotonin is required to assess the hypothesis that defects in serotonin signaling underlie depression in humans. Caenorhabditis elegans uses serotonin as a neurotransmitter to regulate locomotion, providing a genetic system to analyze serotonin signaling. From large-scale genetic screens we identified 36 mutants of C. elegans in which serotonin fails to have its normal effect of slowing locomotion, and we molecularly identified eight genes affected by 19 of the mutations. Two of the genes encode the serotonin-gated ion channel MOD-1 and the G-protein-coupled serotonin receptor SER-4. mod-1 is expressed in the neurons and muscles that directly control locomotion, while ser-4 is expressed in an almost entirely non-overlapping set of sensory and interneurons. The cells expressing the two receptors are largely not direct postsynaptic targets of serotonergic neurons. We analyzed animals lacking or overexpressing the receptors in various combinations using several assays for serotonin response. We found that the two receptors act in parallel to affect locomotion. Our results show that serotonin functions as an extrasynaptic signal that independently activates multiple receptors at a distance from its release sites and identify at least six additional proteins that appear to act with serotonin receptors to mediate serotonin response.National Institutes of Health (U.S.) (Grant GM24663
Crude incidence in two-phase designs in the presence of competing risks.
BackgroundIn many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies. Common examples include the nested case-control and the case-cohort designs. For two-phase studies, appropriate weighted survival estimates have been derived; however, no estimator of cumulative incidence accounting for competing events has been proposed. This is relevant in the presence of multiple types of events, where estimation of event type specific quantities are needed for evaluating outcome.MethodsWe develop a non parametric estimator of the cumulative incidence function of events accounting for possible competing events. It handles a general sampling design by weights derived from the sampling probabilities. The variance is derived from the influence function of the subdistribution hazard.ResultsThe proposed method shows good performance in simulations. It is applied to estimate the crude incidence of relapse in childhood acute lymphoblastic leukemia in groups defined by a genotype not available for everyone in a cohort of nearly 2000 patients, where death due to toxicity acted as a competing event. In a second example the aim was to estimate engagement in care of a cohort of HIV patients in resource limited setting, where for some patients the outcome itself was missing due to lost to follow-up. A sampling based approach was used to identify outcome in a subsample of lost patients and to obtain a valid estimate of connection to care.ConclusionsA valid estimator for cumulative incidence of events accounting for competing risks under a general sampling design from an infinite target population is derived
Reinforcement learning or active inference?
This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain
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