Mindfulness Training and Practice in Physician Assistant Education

Purpose: The purpose of this study was to integrate mindfulness, as a compassionate pedagogy, into a physician assistant (PA) program and assess its effects on student depression, anxiety, and stress at the conclusion of the first semester. Method: Fifty-five of 60 first-semester students provided consent. Mindfulness instruction and practice began with a six-hour intensive workshop spread over two days during the first week of the semester. This was followed by seven, brief, 10 to15 minute mindfulness practices integrated across one course. Students completed a demographic questionnaire at the beginning of the project and the DASS 21 survey which measures a range of symptoms common to depression, anxiety, and stress at weeks 1 and 16 of the semester. After the course concluded, 10 students were randomly selected from those who had identified as interested in participating in a focus group to discuss their experiences and offer suggestions for improvement. Results: DASS 21 subscale scores revealed no change in depression, anxiety, nor stress. In contrast, the focus group results revealed that student anxiety and stress levels diminished through learning about mindfulness and practicing mindful meditations. Conclusions: The incorporation of mindfulness training was generally well received by first-semester PA students. Students in the focus group reported decreased levels of anxiety and stress, while the DASS 21 revealed no change. The authors suggest that the experience could be strengthened by modifying the workshop material and extending the mindfulness practice across the didactic and clinical years to allow students more opportunities to develop their personal mindfulness practice and integrate it throughout their career

‘We shouldn’t have to ask’: exploring the realities of minority ethnic women football spectators

Research Question: Women’s football is experiencing significant growth, but is it fully inclusive? Little research explores the experiences of minority ethnic women spectators. For women’s football to capitalise on its success and be welcoming for all, it is critical to explore the barriers facing women intersectionally. This paper seeks answers to the following questions: What influenced minority ethnic women’s decisions to watch the UWE, and what challenges exist to their spectatorship? Research Methods: An online survey and three focus groups explored United Kingdom respondents’ thoughts around spectatorship at the 2022 UEFA Women’s Euros. Topics included the marketing before the event, their experiences, and future intentions. Results and Findings: Analysis of the results resulted in the following themes: the importance of supporting the England women’s team vs. a lack of diversity, lack of cultural awareness, performativity and the FA, and women’s football being different to men’s football. Minority ethnic women face numerous challenges, including perceptions of tokenism, a lack of representation on and off the pitch, and religious observances, including a lack of prayer rooms and no-alcohol zones. Implications: Governing bodies must take action to diversify the sport at all levels, especially grassroots, including consulting and listening to the voices of minority ethnic women. The creation of role models will increase feelings of connectedness. While this work has focused on women’s football, leaders in the men’s game and other governing bodies could embrace our suggestions to encourage more minority ethnic spectators

Loss and the Experience of Emotional Distress in Childhood

The objective of this study was to investigate loss and the experience of emotional distress through a series of three studies. In Study 1, results indicated that when controlling for the total number of traumas experienced, children with loss traumas did not differ significantly from children with other types of traumas in terms of the level of PTSD symptoms reported and diurnal cortisol levels. In Study 2, results indicated that youth with loss traumas had significantly higher parent-reported internalizing and externalizing symptoms than control participants. In Study 3, we replicated and extended findings from Study 1 using an independent sample of non-clinic-referred youth. Findings are discussed in terms of how loss events may constitute a traumatic stressor in youth

Testing models for molecular gas formation in galaxies: hydrostatic pressure or gas and dust shielding?

Stars in galaxies form in giant molecular clouds that coalesce when the atomic hydrogen is converted into molecules. There are currently two dominant models for what property of the galactic disk determines its molecular fraction: either hydrostatic pressure driven by the gravity of gas and stars, or a combination of gas column density and metallicity. To assess the validity of these models, we compare theoretical predictions to the observed atomic gas content of low-metallicity dwarf galaxies with high stellar densities. The extreme conditions found in these systems are optimal to distinguish the two models, otherwise degenerate in nearby spirals. Locally, on scales <100 pc, we find that the state of the interstellar medium is mostly sensitive to the gas column density and metallicity rather than hydrostatic pressure. On larger scales where the average stellar density is considerably lower, both pressure and shielding models reproduce the observations, even at low metallicity. We conclude that models based on gas and dust shielding more closely describe the process of molecular formation, especially at the high resolution that can be achieved in modern galaxy simulations or with future radio/millimeter arrays.Comment: 20 pages, 12 figures. Accepted for publication in Ap

Radio spectral properties of star-forming galaxies between 150-5000MHz in the ELAIS-N1 field

By combining high-sensitivity LOFAR 150MHz, uGMRT 400MHz and 1,250MHz, GMRT 610MHz, and VLA 5GHz data in the ELAIS-N1 field, we study the radio spectral properties of radio-detected star-forming galaxies (SFGs) at observer-frame frequencies of 150-5,000MHz. We select ~3,500 SFGs that have both LOFAR 150MHz and GMRT 610MHz detections, and obtain a median two-point spectral index of $\alpha_{150}^{610}=-0.51\pm0.01$. The photometric redshift of these SFGs spans $z=0.01-6.21$. We also measure the two-point radio spectral indices at 150-400-610-1,250MHz and 150-610-5,000MHz respectively for the GMRT 610-MHz-detected SFGs, and find that, on average, the radio spectrum of SFGs is flatter at low frequency than at high frequency. At observer-frame 150-5,000MHz, we find that the radio spectrum slightly steepens with increasing stellar mass. However, we only find that the radio spectrum flattens with increasing optical depth at $V$-band at $\nu<1$GHz. We suggest that spectral ageing due to the energy loss of CR electrons and thermal free-free absorption could be among the possible main physical mechanisms that drive the above two correlations respectively. In addition, both of these mechanisms could physically explain why the radio spectrum is flatter at low frequency than at high frequency.Comment: 17 pages, 12 figures, 1 table, published in MNRA

The Spitzer View of Low-Metallicity Star Formation: III. Fine Structure Lines, Aromatic Features, and Molecules

We present low- and high-resolution Spitzer/IRS spectra, supplemented by IRAC and MIPS measurements, of 22 blue compact dwarf (BCD) galaxies. The BCD sample spans a wide range in oxygen abundance [12+Log(O/H) between 7.4 and 8.3], and hardness of the interstellar radiation field (ISRF). The IRS spectra provide us with a rich set of diagnostics to probe the physics of star and dust formation in very low-metallicity environments. We find that metal-poor BCDs have harder ionizing radiation than metal-rich galaxies: [OIV] emission is roughly 4 times as common as [FeII] emission. They also have a more intense ISRF, as indicated by the 71 to 160micron luminosity ratio. Two-thirds of the sample (15 BCDs) show PAH features, although the fraction of PAH emission normalized to the total infrared (IR) luminosity is considerably smaller in metal-poor BCDs (~0.5%) than in metal-rich star-forming galaxies (~10%). We find several lines of evidence for a deficit of small PAH carriers at low metallicity, and attribute this to destruction by a hard, intense ISRF, only indirectly linked to metal abundance. Our IRS spectra reveal a variety of H2 rotational lines, and more than a third of the objects in our sample (8 BCDs) have >=3sigma detections in one or more of the four lowest-order transitions. The warm gas masses in the BCDs range from 10^3 to 10^8 Msun, and can be comparable to the neutral hydrogen gas mass; relative to their total IR luminosities, some BCDs contain more H2 than SINGS galaxies.Comment: Accepted by ApJ: 70 pages in draft form, 6 tables, 22 figure

Amino acid classification based spectrum kernel fusion for protein subnuclear localization

<p>Abstract</p> <p>Background</p> <p>Prediction of protein localization in subnuclear organelles is more challenging than general protein subcelluar localization. There are only three computational models for protein subnuclear localization thus far, to the best of our knowledge. Two models were based on protein primary sequence only. The first model assumed homogeneous amino acid substitution pattern across all protein sequence residue sites and used BLOSUM62 to encode <it>k</it>-mer of protein sequence. Ensemble of SVM based on different <it>k</it>-mers drew the final conclusion, achieving 50% overall accuracy. The simplified assumption did not exploit protein sequence profile and ignored the fact of heterogeneous amino acid substitution patterns across sites. The second model derived the <it>PsePSSM </it>feature representation from protein sequence by simply averaging the profile PSSM and combined the <it>PseAA </it>feature representation to construct a kNN ensemble classifier <it>Nuc-PLoc</it>, achieving 67.4% overall accuracy. The two models based on protein primary sequence only both achieved relatively poor predictive performance. The third model required that GO annotations be available, thus restricting the model's applicability.</p> <p>Methods</p> <p>In this paper, we only use the amino acid information of protein sequence without any other information to design a widely-applicable model for protein subnuclear localization. We use <it>K</it>-spectrum kernel to exploit the contextual information around an amino acid and the conserved motif information. Besides expanding window size, we adopt various amino acid classification approaches to capture diverse aspects of amino acid physiochemical properties. Each amino acid classification generates a series of spectrum kernels based on different window size. Thus, (I) window expansion can capture more contextual information and cover size-varying motifs; (II) various amino acid classifications can exploit multi-aspect biological information from the protein sequence. Finally, we combine all the spectrum kernels by simple addition into one single kernel called <it>SpectrumKernel+ </it>for protein subnuclear localization.</p> <p>Results</p> <p>We conduct the performance evaluation experiments on two benchmark datasets: <it>Lei </it>and <it>Nuc-PLoc</it>. Experimental results show that <it>SpectrumKernel+ </it>achieves substantial performance improvement against the previous model <it>Nuc-PLoc</it>, with overall accuracy <it>83.47% </it>against <it>67.4%</it>; and <it>71.23% </it>against <it>50% </it>of <it>Lei SVM Ensemble</it>, against 66.50% of <it>Lei GO SVM Ensemble</it>.</p> <p>Conclusion</p> <p>The method <it>SpectrumKernel</it>+ can exploit rich amino acid information of protein sequence by embedding into implicit size-varying motifs the multi-aspect amino acid physiochemical properties captured by amino acid classification approaches. The kernels derived from diverse amino acid classification approaches and different sizes of <it>k</it>-mer are summed together for data integration. Experiments show that the method <it>SpectrumKernel</it>+ significantly outperforms the existing models for protein subnuclear localization.</p

Robust grasping under object pose uncertainty

This paper presents a decision-theoretic approach to problems that require accurate placement of a robot relative to an object of known shape, such as grasping for assembly or tool use. The decision process is applied to a robot hand with tactile sensors, to localize the object on a table and ultimately achieve a target placement by selecting among a parameterized set of grasping and information-gathering trajectories. The process is demonstrated in simulation and on a real robot. This work has been previously presented in Hsiao et al. (Workshop on Algorithmic Foundations of Robotics (WAFR), 2008; Robotics Science and Systems (RSS), 2010) and Hsiao (Relatively robust grasping, Ph.D. thesis, Massachusetts Institute of Technology, 2009).National Science Foundation (U.S.) (Grant 0712012

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction &gt; 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD