Evaluation of low-template DNA profiles using peak heights

In recent years statistical models for the analysis of complex (low-template and/or mixed) DNA profiles have moved from using only presence/absence information about allelic peaks in an electropherogram, to quantitative use of peak heights. This is challenging because peak heights are very variable and affected by a number of factors. We present a new peak-height model with important novel features, including over- and double-stutter, and a new approach to dropin. Our model is incorporated in open-source R code likeLTD. We apply it to 108 laboratory-generated crime-scene profiles and demonstrate techniques of model validation that are novel in the field. We use the results to explore the benefits of modeling peak heights, finding that it is not always advantageous, and to assess the merits of pre-extraction replication. We also introduce an approximation that can reduce computational complexity when there are multiple low-level contributors who are not of interest to the investigation, and we present a simple approximate adjustment for linkage between loci, making it possible to accommodate linkage when evaluating complex DNA profiles

The association between web-based or face-to-face lifestyle interventions on the perceived benefits and barriers to exercise in midlife women: Three-arm equivalency study

© 2019 Journal of Medical Internet Research. All rights reserved. Background: Noncommunicable diseases pose a significant threat to women's health globally, with most diseases being attributed to modifiable risk factors such as physical inactivity. Women perceive a range of benefits and barriers to exercise; however, there is little evidence about the effect of different lifestyle intervention delivery modes on perceptions of exercise. Objective: This study aimed to compare the effect of a multiple health behavior change (MHBC) intervention called the Women's Wellness Program. This intervention was delivered in 3 different modes on perceived exercise benefits, perceived exercise barriers, and actual physical activity and exercise in midlife women. Methods: Women aged 45 to 65 years were recruited via the study website. They were assigned in blocks to 3 different treatment groups (A: Web-based independent; B: face-to-face with nurse consultations; and C: Web-based with virtual nurse consultations). All participants received the 12-week intervention that utilizes principles from social-cognitive theory to provide a structured guide to promote healthy lifestyle behaviors with an emphasis on regular exercise and healthy eating. Data were collected using a self-report Web-based questionnaire at baseline (T1) and postintervention (T2) including perceived exercise benefits and barriers and exercise and physical activity. A data analysis examined both within- and between-group changes over time. Results: Participants in this study (N=225) had a mean age of 50.9 years (SD 5.9) and most were married or living with a partner (83.3%, 185/225). Attrition was 30.2% with 157 participants completing the final questionnaire. Women in all intervention groups reported a significant increase in positive perceptions of exercise (P<.05); a significant increase in exercise and overall physical activity (P<.01) with moderate-to-large effect sizes noted for overall physical activity (d=0.5 to d=0.87). Participants receiving support from registered nurses in the face-to-face and Web-based groups had a greater magnitude of change in benefit perceptions and physical activity than those in the Web-based independent group. There was no significant change in exercise barrier perceptions within or between groups over time. Conclusions: The results of this study suggest that the (MHBC) intervention is effective in increasing exercise benefit perceptions, overall physical activity, and exercise in midlife women. Although Web-based programs are cost-effective and flexible and can be delivered remotely, providing a range of options including face-to-face group delivery and personalized electronic health coaching from registered nurses has the potential to enhance participant engagement and motivation

A psychometric evaluation of the Female Sexual Function Index in women treated for breast cancer.

BACKGROUND: We aimed to determine the psychometric properties and factor structure of the 19-item Female Sexual Function Index (FSFI) in 132 sexually active women previously treated for breast cancer. METHODS: Confirmatory factor analysis explored three models: (a) second-order six-factor, (b) six-factor, and (c) five-factor models combining the desire and arousal subscales. RESULTS: Results revealed excellent reliability for the total score (Cronbach's α = 0.94), and domain scores (all Cronbach's αs > 0.90), and good convergent and discriminant validity. The six-factor model provided the best fit of the models assessed, but a marginal overall fit (Tucker-Lewis index = 0.91, comparative fit index = 0.93, root mean square error of approximation = 0.09). Exploratory factor analyses (EFA) supported a four-factor structure, revealing an arousal/orgasm factor alongside the original pain, lubrication, and satisfaction domains. CONCLUSION: The arousal/orgasm factor suggests a "sexual response" construct, potentially arising from an underlying latent factor involving physical and mental stimulation in conceptualizations of arousal and orgasm in women treated for breast cancer. Finally, the EFA failed to capture an underlying desire factor, potentially due to measurement error associated with the small number of items (two) in this domain. Despite evidence that the FSFI has sound psychometric properties, our results suggest that the current conceptualizations of the FSFI might not accurately represent sexual functioning in women previously treated for breast cancer. Further research is required to elucidate the factors that influence desire, arousal, and orgasm in sexually active women in this population, and the reasons underlying sexual inactivity. Practical and theoretical implications for FSFI use in this population are discussed

Choice of population database for forensic DNA profile analysis.

When evaluating the weight of evidence (WoE) for an individual to be a contributor to a DNA sample, an allele frequency database is required. The allele frequencies are needed to inform about genotype probabilities for unknown contributors of DNA to the sample. Typically databases are available from several populations, and a common practice is to evaluate the WoE using each available database for each unknown contributor. Often the most conservative WoE (most favourable to the defence) is the one reported to the court. However the number of human populations that could be considered is essentially unlimited and the number of contributors to a sample can be large, making it impractical to perform every possible WoE calculation, particularly for complex crime scene profiles. We propose instead the use of only the database that best matches the ancestry of the queried contributor, together with a substantial FST adjustment. To investigate the degree of conservativeness of this approach, we performed extensive simulations of one- and two-contributor crime scene profiles, in the latter case with, and without, the profile of the second contributor available for the analysis. The genotypes were simulated using five population databases, which were also available for the analysis, and evaluations of WoE using our heuristic rule were compared with several alternative calculations using different databases. Using FST=0.03, we found that our heuristic gave WoE more favourable to the defence than alternative calculations in well over 99% of the comparisons we considered; on average the difference in WoE was just under 0.2 bans (orders of magnitude) per locus. The degree of conservativeness of the heuristic rule can be adjusted through the FST value. We propose the use of this heuristic for DNA profile WoE calculations, due to its ease of implementation, and efficient use of the evidence while allowing a flexible degree of conservativeness

Crossing into the substellar regime in Praesepe

We present the results of a deep optical 2.6 deg2 survey with near-infrared (NIR) follow-up measurements of the intermediate-aged Praesepe open cluster. The survey is complete to Ic= 21.3, Z= 20.5, corresponding to M∼ 0.06 M⊙ assuming a cluster age of 0.5 Gyr. Using three to five passbands to constrain cluster membership, we identify 32 new low-mass cluster members, at least four of which are likely to be substellar. We use the low-mass census to trace the region where the sequence moves away from the NEXTGEN towards the DUSTY regime at Teff= 2200 K. In doing so, we identify four unresolved binaries, yielding a substellar binary fraction (BF) of ∼30 per cent. The BFs appear to decrease below 0.1 M⊙, in contrast to the rising fractions found in the Pleiades. We also identify a paucity of late M dwarfs, thought to be due to a steepening in the mass-luminosity relation at these spectral types, and compare the properties of this gap in the sequence to those observed in younger clusters. We note an overdensity of faint sources in the region of the so-called subcluster (possibly an older smaller cluster within Praesepe), and subsequently derive the luminosity and mass functions (MFs) for the main Praesepe cluster, revealing a turnover near the substellar boundary. We conclude by presenting astrometric measurements for low-mass Praesepe candidates from the literature and rule out as a likely foreground dwarf RPr1, hitherto thought to be a substellar member

Reduction of the size of datasets by using evolutionary feature selection: the case of noise in a modern city

Smart city initiatives have emerged to mitigate the negative effects of a very fast growth of urban areas. Most of the population in our cities are exposed to high levels of noise that generate discomfort and different health problems. These issues may be mitigated by applying different smart cities solutions, some of them require high accurate noise information to provide the best quality of serve possible. In this study, we have designed a machine learning approach based on genetic algorithms to analyze noise data captured in the university campus. This method reduces the amount of data required to classify the noise by addressing a feature selection optimization problem. The experimental results have shown that our approach improved the accuracy in 20% (achieving an accuracy of 87% with a reduction of up to 85% on the original dataset).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2016-81766-REDT (http://cirti.es), and TIN2017-88213-R (http://6city.lcc.uma.es)

Medical students’ views about having different types of problem-based learning tutors

Background At Norwich Medical School, Year 3 or 4 medical students taking a year out of the 5-year undergraduate MBBS degree to do a master’s degree in clinical education worked as near-peer problem-based learning (PBL) tutors for students in Year 2. Peer-assisted learning has been shown to benefit both peer tutors and tutees; in this study, experiences of students with near-peer PBL tutors were compared to students with other types of PBL tutor. Methods Using existing student evaluation data, we compared student views about PBL tutor performance, PBL group functioning, and overall satisfaction with PBL learning experience according to whether their PBL tutor/s were (1) a single near-peer tutor (later-year MB BS student), (2) a single staff tutor, (3) multiple staff tutors, or (4) multiple newly qualified doctor tutors. Results Results indicated that students’ evaluation of tutor performance was more positive for near-peer PBL tutors compared to both groups of staff tutors for most areas evaluated. Additionally, students’ evaluation of overall satisfaction with PBL was more positive for near-peer PBL tutors compared to multiple staff tutors. Tutor performance for multiple staff tutors was evaluated less positively compared to both single staff and multiple newly qualified doctor groups. But there were no statistically significant differences between the four groups regarding PBL group functioning. Conclusion Near-peer PBL tutors perform comparably or better to staff PBL tutors in salient measures of tutor performance and group functioning. We conclude that medical students find near-peer PBL tutors to be an acceptable addition to the PBL tutor workforce

The scalar gluonium correlator: large-beta_0 and beyond

The investigation of the scalar gluonium correlator is interesting because it carries the quantum numbers of the vacuum and the relevant hadronic current is related to the anomalous trace of the QCD energy-momentum tensor in the chiral limit. After reviewing the purely perturbative corrections known up to next-next-to-leading order, the behaviour of the correlator is studied to all orders by means of the large-beta_0 approximation. Similar to the QCD Adler function, the large-order behaviour is governed by the leading ultraviolet renormalon pole. The structure of infrared renormalon poles, being related to the operator product expansion are also discussed, as well as a low-energy theorem for the correlator that provides a relation to the renormalisation group invariant gluon condensate, and the vacuum matrix element of the trace of the QCD energy-momentum tensor.Comment: 14 pages, references added, discussion of IR renormalon pole at u=3 extended, similar version to appear in JHE

Maximum-Reward Motion in a Stochastic Environment: The Nonequilibrium Statistical Mechanics Perspective

We consider the problem of computing the maximum-reward motion in a reward field in an online setting. We assume that the robot has a limited perception range, and it discovers the reward field on the fly. We analyze the performance of a simple, practical lattice-based algorithm with respect to the perception range. Our main result is that, with very little perception range, the robot can collect as much reward as if it could see the whole reward field, under certain assumptions. Along the way, we establish novel connections between this class of problems and certain fundamental problems of nonequilibrium statistical mechanics . We demonstrate our results in simulation examples

Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles

BACKGROUND: Technological advances have enabled the analysis of very small amounts of DNA in forensic cases. However, the DNA profiles from such evidence are frequently incomplete and can contain contributions from multiple individuals. The complexity of such samples confounds the assessment of the statistical weight of such evidence. One approach to account for this uncertainty is to use a likelihood ratio framework to compare the probability of the evidence profile under different scenarios. While researchers favor the likelihood ratio framework, few open-source software solutions with a graphical user interface implementing these calculations are available for practicing forensic scientists. RESULTS: To address this need, we developed Lab Retriever, an open-source, freely available program that forensic scientists can use to calculate likelihood ratios for complex DNA profiles. Lab Retriever adds a graphical user interface, written primarily in JavaScript, on top of a C++ implementation of the previously published R code of Balding. We redesigned parts of the original Balding algorithm to improve computational speed. In addition to incorporating a probability of allelic drop-out and other critical parameters, Lab Retriever computes likelihood ratios for hypotheses that can include up to four unknown contributors to a mixed sample. These computations are completed nearly instantaneously on a modern PC or Mac computer. CONCLUSIONS: Lab Retriever provides a practical software solution to forensic scientists who wish to assess the statistical weight of evidence for complex DNA profiles. Executable versions of the program are freely available for Mac OSX and Windows operating systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0740-8) contains supplementary material, which is available to authorized users