Mammalian myosin I alpha, I beta, and I gamma: new widely expressed genes of the myosin I family.

A polymerase chain reaction strategy was devised to identify new members of the mammalian myosin I family of actin-based motors. Using cellular RNA from mouse granular neurons and PC12 cells, we have cloned and sequenced three 1.2-kb polymerase chain reaction products that correspond to novel mammalian myosin I genes designated MMI alpha, MMI beta, MMI gamma. The pattern of expression for each of the myosin I's is unique: messages are detected in diverse tissues including the brain, lung, kidney, liver, intestine, and adrenal gland. Overlapping clones representing full-length cDNAs for MMI alpha were obtained from mouse brain. These encode a 1,079 amino acid protein containing a myosin head, a domain with five calmodulin binding sites, and a positively charged COOH-terminal tail. In situ hybridization reveals that MMI alpha is highly expressed in virtually all neurons (but not glia) in the postnatal and adult mouse brain and in neuroblasts of the cerebellar external granular layer. Expression varies in different brain regions and undergoes developmental regulation. Myosin I's are present in diverse organisms from protozoa to vertebrates. This and the expression of three novel members of this family in brain and other mammalian tissues suggests that they may participate in critical and fundamental cellular processes

How Robust Is the Apparent Break‐Down of Northern High‐Latitude Temperature Control on Spring Carbon Uptake?

Vegetation growth in northern high‐latitudes during springtime is strongly temperature limited, and thus anomalously warm springs are expected to result in an increased drawdown of carbon dioxide (CO2). However, a recent analysis of the relationship between spring temperature anomalies and atmospheric CO2 anomalies at Point Barrow, Alaska, suggests that the link between spring carbon uptake by northern ecosystems and temperature anomalies has been weakening over recent decades due to a diminishing control of temperature on plant productivity. Upon further analysis, covering the 1982‐2015 period, we found no significant change in the relationship between spring vegetation productivity derived from remote sensing data and air temperature. We showed that a reduction in spatial coherence of temperature anomalies, alongside a significant sensitivity to atmospheric transport, is likely responsible for the apparent weakening. Our results, therefore, suggest that spring temperature remains as an important control of northern high‐latitude CO2 uptake

Evaluating the informatics for integrating biology and the bedside system for clinical research

<p>Abstract</p> <p>Background</p> <p>Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive.</p> <p>Methods</p> <p>Our evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone.</p> <p>Results</p> <p>We found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc.</p> <p>Conclusion</p> <p>The i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.</p

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

A decade of letrozole: FACE

Third-generation nonsteroidal aromatase inhibitors (AIs), letrozole and anastrozole, are superior to tamoxifen as initial therapy for early breast cancer but have not been directly compared in a head-to-head adjuvant trial. Cumulative evidence suggests that AIs are not equivalent in terms of potency of estrogen suppression and that there may be differences in clinical efficacy. Thus, with no data from head-to-head comparisons of the AIs as adjuvant therapy yet available, the question of whether there are efficacy differences between the AIs remains. To help answer this question, the Femara versus Anastrozole Clinical Evaluation (FACE) is a phase IIIb open-label, randomized, multicenter trial designed to test whether letrozole or anastrozole has superior efficacy as adjuvant treatment of postmenopausal women with hormone receptor (HR)- and lymph node-positive breast cancer. Eligible patients (target accrual, N = 4,000) are randomized to receive either letrozole 2.5 mg or anastrozole 1 mg daily for up to 5 years. The primary objective is to compare disease-free survival at 5 years. Secondary end points include safety, overall survival, time to distant metastases, and time to contralateral breast cancer. The FACE trial will determine whether or not letrozole offers a greater clinical benefit to postmenopausal women with HR+ early breast cancer at increased risk of early recurrence compared with anastrozole

Integrating isotopes and documentary evidence : dietary patterns in a late medieval and early modern mining community, Sweden

We would like to thank the Archaeological Research Laboratory, Stockholm University, Sweden and the Tandem Laboratory (Ångström Laboratory), Uppsala University, Sweden, for undertaking the analyses of stable nitrogen and carbon isotopes in both human and animal collagen samples. Also, thanks to Elin Ahlin Sundman for providing the δ13C and δ15N values for animal references from Västerås. This research (Bäckström’s PhD employment at Lund University, Sweden) was supported by the Berit Wallenberg Foundation (BWS 2010.0176) and Jakob and Johan Söderberg’s foundation. The ‘Sala project’ (excavations and analyses) has been funded by Riksens Clenodium, Jernkontoret, Birgit and Gad Rausing’s Foundation, SAU’s Research Foundation, the Royal Physiographic Society of Lund, Berit Wallenbergs Foundation, Åke Wibergs Foundation, Lars Hiertas Memory, Helge Ax:son Johnson’s Foundation and The Royal Swedish Academy of Sciences.Peer reviewedPublisher PD

Melancholic versus non-melancholic depression: differences on cognitive function. A longitudinal study protocol

<p>Abstract</p> <p>Background</p> <p>Cognitive dysfunction is common among depressed patients. However, the pattern and magnitude of impairment during episodes of major depressive disorder (MDD) through to clinical remission remains unclear. Heterogeneity of depressive patients and the lack of longitudinal studies may account for contradictory results in previous research.</p> <p>Methods/Design</p> <p>This longitudinal study will analyze cognitive differences between CORE-defined melancholic depressed patients (n = 60) and non-melancholic depressed patients (n = 60). A comprehensive clinical and cognitive assessment will be performed at admission and after 6 months. Cognitive dysfunction in both groups will be longitudinally compared, and the persistence of cognitive impairment after clinical remission will be determined.</p> <p>Discussion</p> <p>The study of neuropsychological dysfunction and the cognitive changes through the different phases of depression arise a wide variety of difficulties. Several confounding variables must be controlled to determine if the presence of depression could be considered the only factor accounting for group differences.</p

Pch2 Acts through Xrs2 and Tel1/ATM to Modulate Interhomolog Bias and Checkpoint Function during Meiosis

Proper segregation of chromosomes during meiosis requires the formation and repair of double-strand breaks (DSBs) to form crossovers. Repair is biased toward using the homolog as a substrate rather than the sister chromatid. Pch2 is a conserved member of the AAA+-ATPase family of proteins and is implicated in a wide range of meiosis-specific processes including the recombination checkpoint, maturation of the chromosome axis, crossover control, and synapsis. We demonstrate a role for Pch2 in promoting and regulating interhomolog bias and the meiotic recombination checkpoint in response to unprocessed DSBs through the activation of axial proteins Hop1 and Mek1 in budding yeast. We show that Pch2 physically interacts with the putative BRCT repeats in the N-terminal region of Xrs2, a member of the MRX complex that acts at sites of unprocessed DSBs. Pch2, Xrs2, and the ATM ortholog Tel1 function in the same pathway leading to the phosphorylation of Hop1, independent of Rad17 and the ATR ortholog Mec1, which respond to the presence of single-stranded DNA. An N-terminal deletion of Xrs2 recapitulates the pch2Δ phenotypes for signaling unresected breaks. We propose that interaction with Xrs2 may enable Pch2 to remodel chromosome structure adjacent to the site of a DSB and thereby promote accessibility of Hop1 to the Tel1 kinase. In addition, Xrs2, like Pch2, is required for checkpoint-mediated delay conferred by the failure to synapse chromosomes

Description and validation of a Markov model of survival for individuals free of cardiovascular disease that uses Framingham risk factors

BACKGROUND: Estimation of cardiovascular disease risk is increasingly used to inform decisions on interventions, such as the use of antihypertensives and statins, or to communicate the risks of smoking. Crude 10-year cardiovascular disease risk risks may not give a realistic view of the likely impact of an intervention over a lifetime and will underestimate of the risks of smoking. A validated model of survival to act as a decision aid in the consultation may help to address these problems. This study aims to describe the development of such a model for use with people free of cardiovascular disease and evaluates its accuracy against data from a United Kingdom cohort. METHODS: A Markov cycle tree evaluated using cohort simulation was developed utilizing Framingham estimates of cardiovascular risk, 1998 United Kingdom mortality data, the relative risk for smoking related non-cardiovascular disease risk and changes in systolic blood pressure and serum total cholesterol total cholesterol with age. The model's estimates of survival at 20 years for 1391 members of the Whickham survey cohort between the ages of 35 and 65 were compared with the observed survival at 20-year follow-up. RESULTS: The model estimate for survival was 75% and the observed survival was 75.4%. The correlation between estimated and observed survival was 0.933 over 39 subgroups of the cohort stratified by estimated survival, 0.992 for the seven 5-year age bands from 35 to 64, 0.936 for the ten 10 mmHg systolic blood pressure bands between 100 mmHg and 200 mmHg, and 0.693 for the fifteen 0.5 mmol/l total cholesterol bands between 3.0 and 10.0 mmol/l. The model significantly underestimated mortality in those people with a systolic blood pressure greater than or equal to 180 mmHg (p = 0.006). The average gain in life expectancy from the elimination of cardiovascular disease risk as a cause of death was 4.0 years for all the 35 year-old men in the sample (n = 24), and 1.8 years for all the 35 year-old women in the sample (n = 32). CONCLUSIONS: This model accurately estimates 20-year survival in subjects from the Whickham cohort with a systolic blood pressure below 180 mmHg

Web‐based Weight Management Programs in an Integrated Health Care Setting: A Randomized, Controlled Trial

Objective : To assess the efficacy of a Web‐based tailored behavioral weight management program compared with Web‐based information‐only weight management materials. Research Methods and Procedures : Participants, 2862 eligible overweight and obese (BMI = 27 to 40 kg/m 2 ) members from four regions of Kaiser Permanente's integrated health care delivery system, were randomized to receive either a tailored expert system or information‐only Web‐based weight management materials. Weight change and program satisfaction were assessed by self‐report through an Internet‐based survey at 3‐ and 6‐month follow‐up periods. Results : Significantly greater weight loss at follow‐up was found among participants assigned to the tailored expert system than among those assigned to the information‐only condition. Subjects in the tailored expert system lost a mean of 3 ± 0.3% of their baseline weight, whereas subjects in the information‐only condition lost a mean of 1.2 ± 0.4% ( p < 0.0004). Participants were also more likely to report that the tailored expert system was personally relevant, helpful, and easy to understand. Notably, 36% of enrollees were African‐American, with enrollment rates higher than the general proportion of African Americans in any of the study regions. Discussion : The results of this large, randomized control trial show the potential benefit of the Web‐based tailored expert system for weight management compared with a Web‐based information‐only weight management program.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93691/1/oby.2006.34.pd