Burnout and Quality of Life among Active Member Physicians of the Medical Society of Sedgwick County

Introduction. The medical literature suggests disturbingly high ratesof burnout among US physicians. The objective of this study was todetermine the rates of burnout, other forms of distress, and overallquality of life among physicians in Sedgwick County.Methods.xThe study involved a convenience sample of 197 physicianswho were active member physicians of the Medical Society of SedgwickCounty (MSSC). Between July and August 2018, we surveyed872 physicians who were active members of the MSSC. The surveyassessed manifestations of burnout, symptoms of depression and suicidalideation, fatigue, and quality of life. The authors used standarddescriptive summary statistics, Mann-Whitney U test/independentsamples t-Test, Fisher’s exact test, and correlations to analyze thedata.Results. The participation rate was 44.6%, with 49.5% of therespondents reporting manifestations of burnout. Although 85% ofthe participants rated their overall quality of life as good/very good,45% screened positive for depression, 5% had thoughts of suicideduring the past year, and 44% reported excessive fatigue during thepast week. Those with manifestations of burnout were 2.13 (100%vs 46.9%, p < 0.01) times more likely to report thoughts of suicidalideation, 2.43 (72.6% vs 30.4%; p < 0.001) times more likely to screenpositive for depression, and 1.89 (67.5% vs 35.8%; p < 0.001) timesmore likely to have high degrees of fatigue. All of the participants whohad suicidal ideation reported manifestations of burnout.Conclusions. Burnout was prevalent among active member physiciansof the MSSC. Burnout among the participants was associatedwith symptoms of depression, fatigue, suicidal ideation, and intentionof leaving the medical profession via early retirement and/or careerchange. Kans J Med 2019;12(2):33-39

Wet Corn Gluten Feed Levels for Steam-flaked Corn Based Finishing Diets

A finishing trial was conducted to evaluate level of wet corn gluten feed in steam-flaked corn based finishing diets. Feed efficiency and daily gain were similar among all levels (10, 20, 25, 30, and 35%, DM basis) of inclusion of Sweet Bran® wet corn gluten feed evaluated in this trial. These data indicate wet corn gluten feed is similar in energy content to steam-flaked corn based on animal performance

Effects of Corn Processing Method and Crude Protein Level with the Inclusion of Wet Corn Gluten Feed on Finishing Steer Performance

Three hundred twenty crossbred steer calves were used to evaluate corn processing method and crude protein level in finishing diets that included wet corn gluten feed. There was no response due to crude protein level (14 vs 15%) observed in this trial. As corn processing method became more intensive (fine-grinding, high-moisture ensiling, and steam-flaking corn) compared to dry-rolling, daily intake was reduced. Daily gain was similar across corn processing methods. Feed efficiency and cost of gain improved as corn processing method intensity increased

Reel Notes

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Organization of the Drosophila larval visual circuit

Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on the types of photoreceptor neurons (PR) present, the organization of the eye and the wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create parallel circuits potentially underlying the computation of absolute light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the LON suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors

Quantitative neuroanatomy for connectomics in Drosophila

Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.Publisher PDFPeer reviewe

Second language anxiety among Latino American immigrants in Australia

Research into second language anxiety (SLA) has largely focused on second language learners rather than immigrants. However, living in an environment where the target language (TL) is the language of everyday communication may constitute a significant source of anxiety that generalizes beyond the language classroom [Pappamihiel, N. E. 2001. “Moving from the ESL Classroom into the Mainstream: An Investigation of English Language Anxiety in Mexican Girls.” Bilingual Research Journal 25: 31–39. doi:10.1080/15235882.2001.10162783; Rose, Glenda. 2008. “Language Acculturation Anxiety in Spanish Apeaking Adult Immigrants Learning English in the United States.” PhD diss., University of Texas. Available from ProQuest Dissertations and Theses database (UMI No. 3315370); Woodrow, L. 2006. “Anxiety and Speaking English as a Second Language.” RELC Journal 37: 308–328. doi:10.1177/0033688206071315]. This study explored SLA across different social contexts in a sample of 190 adult immigrants from Latin America to Australia who spoke Spanish as their first language (L1) and English as their second language (L2). The aims were to (a) investigate the presence and severity of SLA among L2 long-term immigrants, and (b) examine sources of individual differences in SLA. Results indicated that SLA exists among L2 immigrants at moderate, high and very high levels, and that levels of anxiety vary significantly across social contexts. Self perceived L2 proficiency was found to be the strongest predictor of SLA followed by extroversion and age, with higher scores on all three variables associated with lower SLA. Gender, education level, duration of residency in Australia, and emotional stability did not predict SLA in any of the contexts. These findings suggest that SLA is a significant problem for adult immigrants, permeating most aspects of their everyday lives. Practical implications and recommendations for future research are discussed

Delineating reef fish trophic guilds with global gut content data synthesis and phylogeny

Understanding species' roles in food webs requires an accurate assessment of their trophic niche. However, it is challenging to delineate potential trophic interactions across an ecosystem, and a paucity of empirical information often leads to inconsistent definitions of trophic guilds based on expert opinion, especially when applied to hyperdiverse ecosystems. Using coral reef fishes as a model group, we show that experts disagree on the assignment of broad trophic guilds for more than 20% of species, which hampers comparability across studies. Here, we propose a quantitative, unbiased, and reproducible approach to define trophic guilds and apply recent advances in machine learning to predict probabilities of pairwise trophic interactions with high accuracy. We synthesize data from community-wide gut content analyses of tropical coral reef fishes worldwide, resulting in diet information from 13,961 individuals belonging to 615 reef fish. We then use network analysis to identify 8 trophic guilds and Bayesian phylogenetic modeling to show that trophic guilds can be predicted based on phylogeny and maximum body size. Finally, we use machine learning to test whether pairwise trophic interactions can be predicted with accuracy. Our models achieved a misclassification error of less than 5%, indicating that our approach results in a quantitative and reproducible trophic categorization scheme, as well as high-resolution probabilities of trophic interactions. By applying our framework to the most diverse vertebrate consumer group, we show that it can be applied to other organismal groups to advance reproducibility in trait-based ecology. Our work thus provides a viable approach to account for the complexity of predator-prey interactions in highly diverse ecosystems.Peer reviewe