Burning the Candle at Both Ends: How and Why Academic Librarians Who are Parents Experience and Combat Burnout at Work

Academic librarians already wear many hats, juggling a multitude of skills and duties in order to meet the needs of their patrons. When one of those hats is parenthood, however, balancing work and home life can sometimes seem like an insurmountable task. In this chapter we explore how and why academic librarians who are also parents experience burnout, as well as methods used to combat burnout by examining the results of a nationally distributed mixed-methods survey. The survey also addresses practices to combat and prevent burnout, both on a personal and institutional level, and the perceptions of their effectiveness

Burning the Candle at Both Ends How and Why Academic Librarians Who Are Parents Experience and Combat Burnout at Work

Academic librarians already wear many hats, juggling a multitude of skills and duties in order to meet the needs of their patrons. When one of those hats is parenthood, however, balancing work and home life can sometimes seem like an insurmountable task. In this chapter we explore how and why academic librarians who are also parents experience burnout, as well as methods used to combat burnout by examining the results of a nationally distrib­uted mixed-methods survey. The survey also addresses practices to combat and prevent burnout, both on a personal and institutional level, and the perceptions of their effectiveness

LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding

Deductive coding is a widely used qualitative research method for determining the prevalence of themes across documents. While useful, deductive coding is often burdensome and time consuming since it requires researchers to read, interpret, and reliably categorize a large body of unstructured text documents. Large language models (LLMs), like ChatGPT, are a class of quickly evolving AI tools that can perform a range of natural language processing and reasoning tasks. In this study, we explore the use of LLMs to reduce the time it takes for deductive coding while retaining the flexibility of a traditional content analysis. We outline the proposed approach, called LLM-assisted content analysis (LACA), along with an in-depth case study using GPT-3.5 for LACA on a publicly available deductive coding data set. Additionally, we conduct an empirical benchmark using LACA on 4 publicly available data sets to assess the broader question of how well GPT-3.5 performs across a range of deductive coding tasks. Overall, we find that GPT-3.5 can often perform deductive coding at levels of agreement comparable to human coders. Additionally, we demonstrate that LACA can help refine prompts for deductive coding, identify codes for which an LLM is randomly guessing, and help assess when to use LLMs vs. human coders for deductive coding. We conclude with several implications for future practice of deductive coding and related research methods

Racism and the Pinkerton syndrome in Singapore: effects of race on hiring decisions

The aim of the study was to examine racism and the Pinkerton syndrome in Singapore. Specifically, the study examined the effects of race on hiring decisions in a simulated hiring decision task. Participants were 171 (61% males) Singaporean Chinese undergraduates from a private university in Singapore. They were randomly assigned into one of nine groups and asked to review a resume of a job applicant. The study used a 3 (Academic qualifications: strong, moderate, or weak) × 3 (Race: White, Chinese, or Malay) between-subjects design with perceived warmth, competence, applicant suitability and recommended salary as the dependent variables. The results showed that while Chinese participants discriminated against Malay applicants (racism), they discriminated in favor of White applicants (the Pinkerton syndrome). The results provided a potential explanation to the economic disparities between Malays and the other races, and first experimental evidence for racism and the Pinkerton syndrome in Singapore

Health-related quality of life in pediatric patients with leukemia in Singapore: a cross-sectional pilot study

There has been a paradigm shift in health service delivery to a more holistic approach, which considers Quality of Life (QoL) and overall functioning. Health-Related Quality of Life (HRQoL) is a multidimensional construct that encompasses physical functioning as well as psychosocial aspects of emotional and social functioning. This study explored factors related to HRQoL in Asian pediatric patients with leukemia in Singapore. The available variables included: age, treatment duration, household income, gender, ethnicity, religion, diagnosis, and phase of treatment. It is hypothesized that the relationships will be significant. In the current study, there were 60 patients (60% males) with leukemia; their ages ranged from 1 to 21 years (Mean = 8.03, Standard Deviation = 4.55). The hypothesis was partially supported. Age had a significant positive relationship with physical functioning, r(60) = 0.28, p < 0.05, physical health, r(60) = 0.28, p < 0.05, and the total HRQoL score, r(60) = 0.29, p < 0.05. Treatment duration had a positive relationship with school functioning, r(60) = 0.28, p < 0.05. All other correlations were statistically non-significant. The effects of the available psychosocial variables of gender, ethnicity, and religion were examined on scores from the Pediatric Quality of Life Inventory (PedsQL). Ethnicity had a significant effect on social functioning, U = 292.00, p < 0.05, r = 0.3 (medium effect size). Specifically, Chinese (Median = 85.00, n = 33) had significantly higher scores on social functioning than others (Median = 70.00, n = 27). The remaining comparisons were statistically non-significant. The current findings added to QoL research, and provided an impetus for more research in the area of HRQoL for children with leukemia in Singapore

A genome-wide CRISPR-Cas9 knockout screen identifies essential and growth-restricting genes in human trophoblast stem cells

The recent derivation of human trophoblast stem cells (hTSCs) provides a scalable in vitro model system of human placental development, but the molecular regulators of hTSC identity have not been systematically explored thus far. Here, we utilize a genome-wide CRISPR-Cas9 knockout screen to comprehensively identify essential and growth-restricting genes in hTSCs. By cross-referencing our data to those from similar genetic screens performed in other cell types, as well as gene expression data from early human embryos, we define hTSC-specific and -enriched regulators. These include both well-established and previously uncharacterized trophoblast regulators, such as ARID3A, GATA2, and TEAD1 (essential), and GCM1, PTPN14, and TET2 (growth-restricting). Integrated analysis of chromatin accessibility, gene expression, and genome-wide location data reveals that the transcription factor TEAD1 regulates the expression of many trophoblast regulators in hTSCs. In the absence of TEAD1, hTSCs fail to complete faithful differentiation into extravillous trophoblast (EVT) cells and instead show a bias towards syncytiotrophoblast (STB) differentiation, thus indicating that this transcription factor safeguards the bipotent lineage potential of hTSCs. Overall, our study provides a valuable resource for dissecting the molecular regulation of human placental development and diseases

Spatial proteomics defines the content of trafficking vesicles captured by golgin tethers.

Intracellular traffic between compartments of the secretory and endocytic pathways is mediated by vesicle-based carriers. The proteomes of carriers destined for many organelles are ill-defined because the vesicular intermediates are transient, low-abundance and difficult to purify. Here, we combine vesicle relocalisation with organelle proteomics and Bayesian analysis to define the content of different endosome-derived vesicles destined for the trans-Golgi network (TGN). The golgin coiled-coil proteins golgin-97 and GCC88, shown previously to capture endosome-derived vesicles at the TGN, were individually relocalised to mitochondria and the content of the subsequently re-routed vesicles was determined by organelle proteomics. Our findings reveal 45 integral and 51 peripheral membrane proteins re-routed by golgin-97, evidence for a distinct class of vesicles shared by golgin-97 and GCC88, and various cargoes specific to individual golgins. These results illustrate a general strategy for analysing intracellular sub-proteomes by combining acute cellular re-wiring with high-resolution spatial proteomics

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell

A recommended “minimum data set” framework for SD-OCT retinal image acquisition and analysis from the Atlas of Retinal Imaging in Alzheimer’s Study (ARIAS)

Introduction: We propose a minimum data set framework for the acquisition and analysis of retinal images for the development of retinal Alzheimer\u27s disease (AD) biomarkers. Our goal is to describe methodology that will increase concordance across laboratories, so that the broader research community is able to cross‐validate findings in parallel, accumulate large databases with normative data across the cognitive aging spectrum, and progress the application of this technology from the discovery stage to the validation stage in the search for sensitive and specific retinal biomarkers in AD. Methods: The proposed minimum data set framework is based on the Atlas of Retinal Imaging Study (ARIAS), an ongoing, longitudinal, multi‐site observational cohort study. However, the ARIAS protocol has been edited and refined with the expertise of all co‐authors, representing 16 institutions, and research groups from three countries, as a first step to address a pressing need identified by experts in neuroscience, neurology, optometry, and ophthalmology at the Retinal Imaging in Alzheimer\u27s Disease (RIAD) conference, convened by the Alzheimer\u27s Association and held in Washington, DC, in May 2019. Results: Our framework delineates specific imaging protocols and methods of analysis for imaging structural changes in retinal neuronal layers, with optional add‐on procedures of fundus autofluorescence to examine beta‐amyloid accumulation and optical coherence tomography angiography to examine AD‐related changes in the retinal vasculature. Discussion: This minimum data set represents a first step toward the standardization of retinal imaging data acquisition and analysis in cognitive aging and AD. A standardized approach is essential to move from discovery to validation, and to examine which retinal AD biomarkers may be more sensitive and specific for the different stages of the disease severity spectrum. This approach has worked for other biomarkers in the AD field, such as magnetic resonance imaging; amyloid positron emission tomography; and, more recently, blood proteomics. Potential context of use for retinal AD biomarkers is discussed