Personality traits and emotional status affecting academic achievements of medical students: testifying mediating effect of learning strategies

Purpose The purpose of this study is to identify possible causal relationships among personality traits, emotional status, learning strategies, and academic achievements of medical students and to testify mediating effect of learning strategies in these relationships. Methods The study subjects are 424 medical students in the academic year of 2020 at the Gyeongsang National University, Jinju, Korea. Using the Multi-dimensional Learning Strategy Test-II, we assessed the students’ academic achievements with personality traits, emotional status, and learning strategies. This study employed Structural Equation Modelling to explore the causal relationships among the latent variables. Results In the path model, personality traits directly affected academic achievements (β=0.285, p<0.05) and indirectly affected academic achievements via emotional status (β=0.063, p<0.01) and via learning strategies (β=0.244, p<0.05), respectively. Further, personality traits indirectly affected academic achievements via emotional status first and learning strategies next (β=0.019, p<0.05). Personality traits indirectly affected academic achievements through three multiple paths in the model (β=0.326, p<0.05). Learning strategies partially mediated the relationship between personality traits and academic achievements as well as the relationship between emotional status and academic achievements of medical students. Conclusion Study findings proved constructing the causal relationships among personality traits, emotional status, learning strategies, and academic achievements of medical students, thus supporting our hypotheses. Early habits of self-regulated learning are essential for the successful academic achievements of medical students. Therefore, medical students should know how to regulate personality traits and control emotional status, significantly affecting learning strategies

EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records

We present a new text-to-SQL dataset for electronic health records (EHRs). The utterances were collected from 222 hospital staff, including physicians, nurses, insurance review and health records teams, and more. To construct the QA dataset on structured EHR data, we conducted a poll at a university hospital and templatized the responses to create seed questions. Then, we manually linked them to two open-source EHR databases, MIMIC-III and eICU, and included them with various time expressions and held-out unanswerable questions in the dataset, which were all collected from the poll. Our dataset poses a unique set of challenges: the model needs to 1) generate SQL queries that reflect a wide range of needs in the hospital, including simple retrieval and complex operations such as calculating survival rate, 2) understand various time expressions to answer time-sensitive questions in healthcare, and 3) distinguish whether a given question is answerable or unanswerable based on the prediction confidence. We believe our dataset, EHRSQL, could serve as a practical benchmark to develop and assess QA models on structured EHR data and take one step further towards bridging the gap between text-to-SQL research and its real-life deployment in healthcare. EHRSQL is available at https://github.com/glee4810/EHRSQL.Comment: Published as a conference paper at NeurIPS 2022 (Track on Datasets and Benchmarks)

Discovery of new epigenomics-based biomarkers and the early diagnosis of neurodegenerative diseases

Treatment options for many neurodegenerative diseases are limited due to the lack of early diagnostic procedures that allow timely delivery of therapeutic agents to affected neurons prior to cell death. While notable advances have been made in neurodegenerative disease biomarkers, whether or not the biomarkers discovered to date are useful for early diagnosis remains an open question. Additionally, the reliability of these biomarkers has been disappointing, due in part to the large dissimilarities between the tissues traditionally used to source biomarkers and primarily diseased neurons. In this article, we review the potential viability of atypical epigenetic and/or consequent transcriptional alterations (ETAs) as biomarkers of early-stage neurodegenerative disease, and present our perspectives on the discovery and practical use of such biomarkers in patient-derived neural samples using single-cell level analyses, thereby greatly enhancing the reliability of biomarker application. © 2020 The Authors1

Charge Shielding of PIP2 by Cations Regulates Enzyme Activity of Phospholipase C

Hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) of the plasma membrane by phospholipase C (PLC) generates two critical second messengers, inositol-1,4,5-trisphosphate and diacylglycerol. For the enzymatic reaction, PIP2 binds to positively charged amino acids in the pleckstrin homology domain of PLC. Here we tested the hypothesis that positively charged divalent and multivalent cations accumulate around the negatively charged PIP2, a process called electrostatic charge shielding, and therefore inhibit electrostatic PIP2-PLC interaction. This charge shielding of PIP2 was measured quantitatively with an in vitro enzyme assay using WH-15, a PIP2 analog, and various recombinant PLC proteins (β1, γ1, and δ1). Reduction of PLC activity by divalent cations, polyamines, and neomycin was well described by a theoretical model considering accumulation of cations around PIP2 via their electrostatic interaction and chemical binding. Finally, the charge shielding of PIP2 was also observed in live cells. Perfusion of the cations into cells via patch clamp pipette reduced PIP2 hydrolysis by PLC as triggered by M1 muscarinic receptors with a potency order of Mg2+ < spermine4+ < neomycin6+. Accumulation of divalent cations into cells through divalent-permeable TRPM7 channel had the same effect. Altogether our results suggest that Mg2+ and polyamines modulate the activity of PLCs by controlling the amount of free PIP2 available for the enzymes and that highly charged biomolecules can be inactivated by counterions electrostatically

Charge Shielding of PIP2 by Cations Regulates Enzyme Activity of Phospholipase C

Hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) of the plasma membrane by phospholipase C (PLC) generates two critical second messengers, inositol-1,4,5-trisphosphate and diacylglycerol. For the enzymatic reaction, PIP2 binds to positively charged amino acids in the pleckstrin homology domain of PLC. Here we tested the hypothesis that positively charged divalent and multivalent cations accumulate around the negatively charged PIP2, a process called electrostatic charge shielding, and therefore inhibit electrostatic PIP2-PLC interaction. This charge shielding of PIP2 was measured quantitatively with an in vitro enzyme assay using WH-15, a PIP2 analog, and various recombinant PLC proteins (β1, γ1, and δ1). Reduction of PLC activity by divalent cations, polyamines, and neomycin was well described by a theoretical model considering accumulation of cations around PIP2 via their electrostatic interaction and chemical binding. Finally, the charge shielding of PIP2 was also observed in live cells. Perfusion of the cations into cells via patch clamp pipette reduced PIP2 hydrolysis by PLC as triggered by M1 muscarinic receptors with a potency order of Mg2+ < spermine4+ < neomycin6+. Accumulation of divalent cations into cells through divalent-permeable TRPM7 channel had the same effect. Altogether our results suggest that Mg2+ and polyamines modulate the activity of PLCs by controlling the amount of free PIP2 available for the enzymes and that highly charged biomolecules can be inactivated by counterions electrostatically

Stimulation of the Migration and Expansion of Adult Mouse Neural Stem Cells by the FPR2-Specific Peptide WKYMVm

Neural stem cells (NSCs) are multipotent cells capable of self-renewal and differentiation into different nervous system cells. Mouse NSCs (mNSCs) are useful tools for studying neurogenesis and the therapeutic applications of neurodegenerative diseases in mammals. Formyl peptide receptor 2 (FPR2), expressed in the central nervous system and brain, is involved in the migration and differentiation of murine embryonic-derived NSCs. In this study, we explored the effect of FPR2 activation in adult mNSCs using the synthetic peptide Trp-Lys-Tyr-Met-Val-D-Met-NH2 (WKYMVm), an agonist of FPR2. After isolation of NSCs from the subventricular zone of the adult mouse brain, they were cultured in two culture systems—neurospheres or adherent monolayers—to demonstrate the expression of NSC markers and phenotypes. Under different conditions, mNSCs differentiated into neurons and glial cells such as astrocytes, microglia, and oligodendrocytes. Treatment with WKYMVm stimulated the chemotactic migration of mNSCs. Moreover, WKYMVm-treated mNSCs were found to promote proliferation; this result was confirmed by the expansion of mNSCs in Matrigel and the increase in the number of Ki67-positive cells. Incubation of mNSCs with WKYMVm in a supplement-free medium enhanced the survival rate of the mNSCs. Together, these results suggest that WKYMVm-induced activation of FPR2 stimulates cellular responses in adult NSCs. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

Clinical Characteristics of Metastatic Tumors to the Ovaries

Approximately 5-30% of the ovarian cancers are metastatic malignancies. The prevalence of metastatic ovarian tumors varies with the incidence rates and spread patterns of primary malignancies. We evaluated the prevalence, pre- and postoperative characteristics of metastatic ovarian cancer in Korean women. We reviewed the records for 821 ovarian malignancies with pathological consultation from 1996-2006 and recorded patient demographical, radiological, histopathological, and survival data. The study included 112 cases of histologically confirmed metastatic ovarian cancer. Metastatic ovarian cancer accounted for 13.6% of all ovarian malignancy, primarily arising from the gastrointestinal tract. The preoperative detection rate with imaging was 75%, and none of the radiological or serological features were useful for differential diagnosis. In multivariate analysis for prognostic variables, the only significant factor was the primary tumor site (p=0.004). Furthermore, extensive resection increased survival for some patients. The differential diagnosis of metastatic ovarian cancer can be problematic, so multiple diagnostic approaches are necessary. The extent of cytoreductive surgery for this type of tumor must be decided on a case-by-case basis