bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring Teaching Efforts in a Medical School Department or Division: A Scoping Review
Authors: Burke Kimberly , Jackson Kevin M 
Published: March 2023

ABSTRACT

Purpose
The desire to measure faculty’s teaching productivity has led many medical school departments to create academic productivity metrics and evaluation systems to track clinical and/or nonclinical teaching efforts. The authors investigated these metrics and their impact on teaching productivity and quality in the literature.

Methods
The authors performed a scoping review using keywords to query three publication databases. A total of 649 articles were identified. The search strategy resulted in the screening of a total of 496 articles after the removal of duplicate articles, of which 479 were excluded. A total of 17 papers met the criteria.

Results
Four of the 17 institutions exclusively measured clinical teaching productivity, and all four reported 11-20% gains in teaching or clinical productivity. Four of the six institutions that tracked only nonclinical teaching productivity shared quantitative data and experienced a variety of gains from measuring teaching productivity that centered on greater participation in teaching. The six institutions that monitored both clinical and nonclinical teaching productivity provided quantitative data. The reported effects ranged from greater learner attendance at teaching events to increases in clinical throughput and teaching hours per faculty member. Five of the 17 institutions tracked quality using qualitative measures, and none of these institutions observed a decrease in teaching quality.

Conclusions
Setting metrics and measurement of teaching seems to have had a generally positive effect on amounts of teaching; however, their impacts on the quality of teaching are less clear. The diversity of metrics reported makes it difficult to generalize the impact of these teaching metrics.
MRI-based classification of IDH mutation and 1p/19q codeletion status of gliomas using a 2.5D hybrid multi-task convolutional neural network
Authors: Chakrabarty Satrajit , LaMontagne Pamela , Shimony Joshua , Marcus Daniel S , Sotiras Aristeidis 
Published: March 2023

Abstract

Background
IDH mutation and 1p/19q codeletion status are important prognostic markers for glioma that are currently determined using invasive procedures. Our goal was to develop artificial intelligence-based methods to noninvasively determine molecular alterations from MRI.

Methods
Pre-operative MRI scans of 2648 glioma patients were collected from Washington University School of Medicine (WUSM; n = 835) and publicly available Brain Tumor Segmentation (BraTS; n = 378), LGG 1p/19q (n = 159), Ivy Glioblastoma Atlas Project (Ivy GAP; n = 41), The Cancer Genome Atlas (TCGA; n = 461), and the Erasmus Glioma Database (EGD; n = 774) datasets. A 2.5D hybrid convolutional neural network was proposed to simultaneously localize glioma and classify its molecular status by leveraging MRI imaging features and prior knowledge features from clinical records and tumor location. The models were trained on 223 and 348 cases for IDH and 1p/19q tasks, respectively, and tested on one internal (TCGA) and two external (WUSM and EGD) test sets.

Results
For IDH, the best-performing model achieved areas under the receiver operating characteristic (AUROC) of 0.925, 0.874, 0.933 and areas under the precision-recall curves (AUPRC) of 0.899, 0.702, 0.853 on the internal, WUSM, and EGD test sets, respectively. For 1p/19q, the best model achieved AUROCs of 0.782, 0.754, 0.842, and AUPRCs of 0.588, 0.713, 0.782, on those three data-splits, respectively.

Conclusions
The high accuracy of the model on unseen data showcases its generalization capabilities and suggests its potential to perform “virtual biopsy” for tailoring treatment planning and overall clinical management of gliomas.
China's TOP10 breakthroughs in science and technology in 2022
Authors: Zhu He 
Published: March 2023

Abstract
The members of Chinese Academy of Sciences (CAS) and Chinese Academy of Engineering have, for 29 years, selected every year's top 10 advancements in science and technology by domestic researchers. For 2022, the list was announced on 12 January, 2023 in China Science Daily. This year's collection includes 4 entries in space exploration and observation, 2 in biotechnology related to agriculture, 2 in earth and environmental sciences, and 2 in fundamental physics.
Clinical Prediction Rule to Guide Diagnostic Testing forShigellosisand Improve Antibiotic Stewardship for Pediatric Diarrhea
Authors: Ahmed Sharia M , Brintz Ben J , Pavlinac Patricia B , Hossain Md Iqbal , Khan Ashraful Islam , Platts-Mills James A , Kotloff Karen L , Leung Daniel T 
Published: March 2023

AbstractBackgroundDiarrheal diseases are a leading cause of death for children aged &lt;5 years. Identification of etiology helps guide pathogen-specific therapy, but availability of diagnostic testing is often limited in low-resource settings. Our goal is to develop a clinical prediction rule (CPR) to guide clinicians in identifying when to use a point-of-care (POC) diagnostic for Shigella in children presenting with acute diarrhea.MethodsWe used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) study to build predictive models for diarrhea of Shigella etiology in children aged ≤59 months presenting with moderate to severe diarrhea in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using cross-validation. We used the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) study to externally validate our GEMS-derived CPR.ResultsOf the 5011 cases analyzed, 1332 (27%) had diarrhea of Shigella etiology. Our CPR had high predictive ability (area under the receiver operating characteristic curve = 0.80 [95% confidence interval, .79–.81]) using the top 2 predictive variables, age and caregiver-reported bloody diarrhea. We show that by using our CPR to triage who receives diagnostic testing, 3 times more Shigella diarrhea cases would have been identified compared to current symptom-based guidelines, with only 27% of cases receiving a POC diagnostic test.ConclusionsWe demonstrate how a CPR can be used to guide use of a POC diagnostic test for diarrhea management. Using our CPR, available diagnostic capacity can be optimized to improve appropriate antibiotic use.
A Macro-Finance Model with Sentiment
Authors: Maxted Peter 
Published: March 2023

Abstract
This paper incorporates diagnostic expectations into a general equilibrium macroeconomic model with a financial intermediary sector. Diagnostic expectations are a forward-looking model of extrapolative expectations that overreact to recent news. Frictions in financial intermediation produce non-linear spikes in risk premia and slumps in investment during periods of financial distress. The interaction of sentiment with financial frictions generates a short-run amplification effect followed by a long-run reversal effect, termed the feedback from behavioural frictions to financial frictions. The model features sentiment-driven financial crises characterized by low pre-crisis risk premia and neglected risk. The conflicting short-run and long-run effect of sentiment produces boom–bust investment cycles. The model also identifies a stabilizing role for diagnostic expectations. Under the baseline calibration, financial crises are less likely to occur when expectations are diagnostic than when they are rational.
High-Quality Complete Genome Resource of Pectobacterium brasiliense Strain TS20HJ1 Causing Rhizome Rot on Ginger
Authors: Zhang Shangqing , Wu Beibei , Di Dianping , Lu Yuxiang , Yang Dongxu , Sun Xiangrui , Han Xiaoqing , Wang Jinhui 
Published: March 2023

Pectobacterium brasiliense is a worldwide distributed bacterial pathogen causing soft rot and blackleg of a wide range of economically important crops. Here, we present the complete, high-quality genome of P. brasiliense strain TS20HJ1, which was isolated from a ginger ( Zingiber officinale) rhizome showing soft rot symptoms. The genome assembly consists of a circular 4,766,353-bp chromosome with 52.1% GC content. The genome harbors 4,128 protein-coding genes, 22 rRNA genes, and 77 tRNA genes. We believe that the complete genome sequence of P. brasiliense TS20HJ1 will provide a valuable resource for understanding the molecular basis of host adaptation and evolution of pathogenesis. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Mavacamten—A Targeted Therapy for Hypertrophic Cardiomyopathy
Authors: Schenk Ashley , Fields Nathan 
Published: March 2023

Abstract:
The pathophysiology of hypertrophic cardiomyopathy is primarily comprised of dynamic left ventricular outflow tract obstruction, mitral regurgitation, and diastolic dysfunction. Symptoms such as dyspnea, angina, or syncope can occur because of left ventricular (LV) hypertrophy and reduced LV cavity size. Currently, focus on symptom relief through optimizing LV preload and reducing inotropy is the mainstay of therapy through the use of β-blockers, nondihydropyridine calcium channel blockers, and disopyramide. Mavacamten is a novel cardiac myosin inhibitor recently approved by the Food and Drug Administration for the treatment of obstructive hypertrophic cardiomyopathy. Mavacamten normalizes myosin and actin cross-bridging to decrease contractility and ultimately reduce LV outflow tract gradients to maximize cardiac output. In this review, we report on the mechanism of action of mavacamten, safety profile, and phase 2 and 3 clinical trial data. Because of the risk of heart failure resulting from systolic dysfunction, careful patient selection and close monitoring are key for implementing this therapy into cardiovascular practice.
A State-of-the-Art Review of Teach-Back for Patients and Families With Heart Failure
Authors: Howie-Esquivel Jill , Bidwell Julie T. 
Published: March 2023

Background
Heart failure (HF) prevalence has risen for more than a decade. Effective patient and family education strategies for HF are needed on a global scale. One widely used method of education is the teach-back method, where learners are provided information, then their understanding assessed by “teaching it back” to the educator.

Purpose
This state-of-the-art review article seeks to examine the evidence focusing on the teach-back method of patient education and patient outcomes. Specifically, this article describes (1) the teach-back process, (2) teach-back's effect on patient outcomes, (3) teach-back in the context of family care partners, and (4) recommendations for future research and practice.

Conclusions
Study investigators report the use of teach-back, but few describe how teach-back was utilized. Study designs vary widely, with few having a comparison group, making conclusions across studies challenging. The effect of teach-back on patient outcomes is mixed. Some studies showed fewer HF readmissions after education using teach-back, but different times of measurement obscure understanding of longitudinal effects. Heart failure knowledge improved across most studies after teach-back interventions; however, results related to HF self-care were mixed. Despite family care partner involvement in several studies, how they were included in teach-back or the associated effects are unclear.

Clinical implications
Future clinical trials that evaluate the effect of teach-back education on patient outcomes, such as short- and long-term readmission rates, biomarkers, and psychological measures, are needed, as patient education is the foundation for self-care and health-related behaviors.
Prominent 68Ga-FAPI Uptake in Renal Parenchyma Caused by Immunoglobulin G4–Related Nephropathy
Authors: Zhang Hongzhe , Pan Qingqing , Luo Yaping 
Published: March 2023

Abstract
A 57-year-old man presented with a dry cough and renal insufficiency. Serum immunoglobulin G4 (IgG4) level was markedly elevated, and IgG4-related disease was clinically considered. 18F-FDG PET/CT revealed mild uptake in salivary glands and also moderately increased activity in renal parenchyma and prostate. 68Ga-FAPI PET/CT detected prominent and evenly distributed 68Ga-FAPI uptake in the kidney, and the pancreas, salivary gland, and prostate also showed intense activity, consistent with IgG4-related disease involving the kidney, pancreas, salivary gland, and prostate.
Extraction of biological signals by factorization enables the reliable analysis of single-cell transcriptomics
Authors: Zeng Feng , Kong Xuwen , Yang Fan , Chen Ting , Han Jiahuai 
Published: March 2023

AbstractAccurately and reliably capturing actual biological signals from single-cell transcriptomics is vital for achieving legitimate scientific results, which is unfortunately hindered by the presence of various kinds of unwanted variations. Here we described a deep auto-regressive factor model known as scPhenoXMBD, demonstrated that each gene’s expression can be split into discrete components that represent biological signals and unwanted variations, which effectively mitigated the effects of unwanted variations in the data of single-cell sequencing. Using scPhenoXMBD, we evaluated various factors affecting IFNβ-stimulated immune cells and demonstrated that biological signal extraction facilitates the identification of IFNβ-responsive pathways and genes. Numerous experiments were conducted to show that scPhenoXMBDcould be utilized successfully in enhancing cell clustering stability, obtaining identical cell populations from diverse data sources, advancing the single-cell CRISPR screening of functional elements, and minimizing the influence of inter-subject discrepancies in the cell-disease relationships. scPhenoXMBDis anticipated to be a dependable and repeatable method for the precise analysis of single-cell data.
A hybrid intelligent gearbox fault diagnosis method based on EWCEEMD and whale optimization algorithm-optimized SVM
Authors: Men Zhihui , Hu Chaoqun , Li Yong-Hua , Bai Xiaoning 
Published: March 2023

PurposeThis paper proposes an intelligent fault diagnosis method, which aims to obtain the outstanding fault diagnosis results of the gearbox.Design/methodology/approachAn intelligent fault diagnosis method based on energy entropy-weighted complementary ensemble empirical mode decomposition (EWCEEMD) and support vector machine (SVM) optimized by whale optimization algorithm (WOA) is proposed. The raw signal is first denoised by the wavelet noise reduction method. Then, complementary ensemble empirical mode decomposition (CEEMD) is used to generate several intrinsic mode functions (IMFs). Next, energy entropy is used as an indicator to measure the sensibility of the IMF and converted into a weight coefficient by function. After that, IMFs are linearly weighted to form the reconstruction signal, and several features are extracted from the new signal. Finally, the support vector machine optimized by the whale optimization algorithm (WOA-SVM) model is used for gearbox fault classification using feature vectors.FindingsThe fault features extracted by this method have a better clustering effect and clear boundaries under each fault mode than the unimproved method. At the same time, the accuracy of fault diagnosis is greatly improved.Originality/valueIn most studies of fault diagnosis, the sensitivity of IMF has not been appreciated. In this paper, energy entropy is chosen to quantify sensitivity. In addition, high classification accuracy can be achieved by applying WOA-SVM as the final classification model, improving the efficiency of fault diagnosis as well.
Understanding civil servants' intentions to open data: factors influencing behavior to disclose data
Authors: Kleiman Fernando , Jansen Sylvia J.T. , Meijer Sebastiaan , Janssen Marijn 
Published: March 2023

PurposeThe opening of government data is high on the policy agenda of governments worldwide. However, data release faces barriers due to limited support of civil servants, whereas the literature neglects civil servants' role in opening data. This paper aims at understanding why civil servants can be reluctant to support the disclosure of data. The authors developed a model to explain civil servants' behavioral intention to open data.Design/methodology/approachThe authors test a series of hypotheses by collecting and analyzing survey data from 387 civil servants and by applying multivariate hierarchical regression.FindingsThe results indicate the factors influencing the behavior of civil servants. Social influences, performance expectancy, data management knowledge and risks have a significant influence. Personal characteristics control these effects.Research limitations/implicationsCaution is needed to generalize the findings towards the support to open data provision by civil servants. Though the analyzed sample was limited to Brazil, other countries and cultures might yield different outcomes. Larger and more diversified samples might indicate significant effects on variables not found in this research.Practical implicationsThe insights can be used to develop policies for increasing the support of civil servants towards governmental data disclosure.Originality/valueThis study suggests factors of influence to civil servants' behavior intentions to disclose governmental data. It results in a model of factors, specifically for their behavioral intention at the individual level.
How low can you go: An investigation of depth sensitivity and resolution using towed marine controlled‐source electromagnetic systems
Authors: King Roslynn B. , Constable Steven 
Published: March 2023

AbstractUnderstanding the depth of investigation for electromagnetic and electrical methods is important in experimental design and for interpreting inversions. Many studies have defined the depth of investigation for electromagnetic sounding methods, but none have included continuously towed controlled‐source electromagnetic methods. Nodal controlled‐source electromagnetic surveys using ocean‐bottom electromagnetic receivers have generally been found to have a depth of investigation limited to about half the maximum source‐receiver spacing, but experience using continuously towed arrays suggests sensitivity to targets at depths approaching the source‐receiver spacing. We test this on two‐dimensional synthetic data using two methods. A rigorous approach is to re‐invert data as a highly conductive or resistive basement is included at successively shallower depths. When the data misfit becomes unacceptably high we can conclude that the maximum depth of inference has been passed. Rather than rely on overall misfit, we note that it is more realistic to preferentially examine those data most sensitive to largest depths (longest offsets and lowest frequencies). A more practical approach is to determine the depth at which a conductivity contrast can be imaged by inversion, noting that knowledge of a contrast is geologically useful even if the actual conductivities cannot be recovered. Both approaches confirm that the increased data density of towed electromagnetic systems at longest offset increases the depth of investigation to about the maximum offset distance.
Photoperiod affects growth, seed production, and biochemical composition in Salicornia species under salinity
Authors: Izadi Yazdan , Nabipour Majid , Ranjbar Gholamhassan 
Published: March 2023

AbstractThe current study was conducted in two separate factorial experiments based on completely randomized block design with three replicates and three destructive samples for each replication. The first experiment consisted of two parts. The first part aimed to determine the effect of four photoperiod levels (10‐, 12‐, 14‐, and 16‐h daylight length) on fresh and dry mass, 1000‐seed weight, and seed yield of four ecotypes of Salicornia persica (Gorgan, Central plateau, Urmia, and Bushehr) along with two Salicornia species (S. bigelovii and S. europaea L.). The second part aimed to investigate the chemical properties of the shoots and seeds of Salicornia plants under short‐ and long‐day (10‐ and 16‐h daylight length) photoperiod treatments. The second trial intended to test the eight levels of salinity stress (control, 10, 20, 30, 40, 50, 60, and 70 dS/m with NaCl) on seedling growth traits of three native ecotypes of S. persica (Urmia, Bushehr, and Central plateau) under the best photoperiod treatment resulting from previous experiments (16‐h daylight length). The results showed that fresh mass and dry mass of Salicornia plants are promoted by long days. The maximum values of 1000‐seed weight (0.41 g) and seed yield (7.19 g/plant) were obtained at 16‐h daylight length for S. bigelovii. Nearly in all Salicornia plants, the maximum values of chemical traits were due to exposure to 16‐h daylight length except for seed and shoot flavonoids. In the second experiment, results revealed that S. persica ecotypes positively responded to salinity levels in the range of 10–30 dS/m, while seedling growth was inhibited at 70 dS/m of salinity stress except for S. persica Central plateau.
Adult tiger beetles Cicindela gemmata modify their foraging strategy in different hunting contexts
Authors: Wang Shumin , Fei Panshuai , Wu Zifeng , Luo Zeyi , Wu Yichen , Sun Ningning , Wang Yujie , Zi Shumei , Gao Lifang , Du Bo 
Published: March 2023

AbstractPredator–prey interaction has long been an interesting item in the research of animal behaviors. Given that live prey can damage their predators, predators must trade foraging efficiency for safety while hunting, but the extent of this trade‐off is not yet clear. Tiger beetles display diversity in their diets and hunting strategies, and hence, they become an ideal system to address how self‐security affects foraging efficiency. We addressed this question in captive adult tiger beetles Cicindela gemmata. By offering several types of arthropod and plant foods, we confirmed that C. gemmata is carnivorous. We found that C. gemmata hunt by either ambushing or chasing their prey, and that they switch between strategies based on differences in the number of prey, the prey status and encounter rate, and the number of predators. Ambushing success increased with the number of prey but decreased with prey encounter rate. Chasing success decreased as prey body size and encounter rate increased. Foraging Cicindela gemmata often gave up an attack when it was nonfatal. This active giving up of hunting may be a consequence of a trade‐off between foraging efficiency and self‐security. Therefore, it is an adaptive response to the risk of injury when hunting for larger live prey.