bluuebunny/crossref_metadata_2025_split huggingface dataset:
CRIB: A Novel Method for Device-Based Physical Behavior Analysis
Authors: Hibbing Paul R. , Creasy Seth A. , Carlson Jordan A. 
Published: September 2022

Physical behaviors (e.g., sleep, sedentary behavior, and physical activity) often occur in sustained bouts that are punctuated with brief interruptions. To detect and classify these interrupted bouts, researchers commonly use wearable devices and specialized algorithms. Most algorithms examine the data in chronological order, initiating and terminating bouts whenever specific criteria are met. Consequently, the bouts may encapsulate or overlap with later periods that also meet the activation and termination criteria (i.e., alternative bout solutions). In some cases, it is desirable to compare these alternative bout solutions before making a final classification. Thus, comparison-focused algorithms are needed, which can be used in isolation or in concert with their chronology-focused counterparts. In this technical note, we present a comparison-focused algorithm called CRIB (Clustered Recognition of Interrupted Bouts). It uses agglomerative hierarchical clustering to facilitate the comparison of different bout solutions, with the final classification being made in favor of the smallest number of bouts that comply with user-specified criteria (i.e., limits on the number, individual duration, and cumulative duration of interruptions). For demonstration, we use CRIB to assess bouts of moderate to vigorous physical activity in accelerometer data from the National Health and Nutrition Examination Survey, and we include a comparison against results from two established chronology-focused algorithms. Our discussion explores strengths and limitations of CRIB, as well as potential considerations and applications for using it in future studies. An online vignette (https://github.com/paulhibbing/PBpatterns/blob/main/vignettes/CRIB.pdf) is available to assist users with implementing CRIB in R.
Impact of different nebulisation systems on patient comfort in bronchiolitis: a randomised controlled cross-over trial
Authors: Valencia-Ramos Juan , Ochoa Sangrador Carlos , García María , Oyagüez Pablo , Arnaez Juan 
Published: September 2022

ObjectiveTo test the hypothesis that greater comfort is achieved using a nebuliser integrated into a high-flow nasal cannula (nebulisation system integrated in high-flow nasal cannula (NHF)) than using a jet nebuliser (JN), and to explore differences in analgesia requirement and the possibility of feeding during nebulisation.DesignRandomised cross-over trial.SettingPaediatric intensive care unit.PatientsChildren aged <24 months diagnosed with bronchiolitis between November 2016 and May 2017.InterventionsNebulisations using NHF and JN.Main outcome measuresCOMFORT–Behaviour Scale (CBS) and Numerical Rating Comfort Scale (NRSc) were used to measure comfort, and Numerical Rating Satisfaction Scale (NRSs) was used to assess satisfaction before, during and after nebulisation. Other variables included feeding, analgesia, need for being held and respiratory and heart rates.ResultsThirty-three children with 233 nebulisations were included in the study. The median age was 3.0 (IQR 2–9) months. Comfort and satisfaction were greater with NHF than with JN. The median staff-recorded CBS, NRSc and NRSs scores for NHF versus JN were 13 (IQR 9–15) vs 17 (IQR 13–23), 8 (IQR 7–0) vs 7 (IQR 4–8), and 4 (IQR 3–4) vs 2 (IQR 2–3), respectively; and caregiver-recorded scores were 12 (IQR 10–15) vs 19 (IQR 13–24), 9 (IQR 7–10) vs 4 (IQR 1–6), and 4 (IQR 3–4) vs 2 (IQR 1–3), respectively (p<0.001). Children who received NHF had lower cardiac and respiratory rates, needed to be held less often during therapy and required less analgesia (p<0.001).ConclusionNebulisation through NHF appears to be a better alternative to JN in terms of comfort and satisfaction as well as making feeding possible during nebulisation.
Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study
Authors: Yang Xin , Eriksson Mikael , Czene Kamila , Lee Andrew , Leslie Goska , Lush Michael , Wang Jean , Dennis Joe , Dorling Leila , Carvalho Sara , Mavaddat Nasim , Simard Jacques , Schmidt Marjanka K , Easton Douglas F , Hall Per , Antoniou Antonis C 
Published: September 2022

BackgroundThe multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort.MethodsWe validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45–63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes:BRCA1,BRCA2,PALB2,CHEK2,ATM,RAD51C,RAD51DandBARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC).ResultsAmong the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%).ConclusionThe multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.
Correlation between SAP2 and CAP1 in clinical strains of Candida albicans at planktonic and biofilm states
Authors: Feng Wenli , Yang Jing , Ma Yan , Liu Yinglu , Yin Rong , Qiao Zusha , Ji Ying , Zhou Yong'an 
Published: September 2022

This study aimed to explore the influences of SAP2 and CAP1 on itraconazole (ITR) resistance of Candida albicans at different states. A total of 10 ITR-resistant strains and 10 ITR-sensitive strains were used for SAP2 sequencing and CAP1 sequencing. SAP2 sequencing showed no missense mutation, and three synonymous mutations. CAP1 gene sequencing identified two missense mutations M140I (8) and K191Q (4), and 14 synonymous mutations G201A (1), A246C (5), C282T (6), G288A (6), C321T (7), A399C (16), C432T (16), C465T (11), G552A (16), G669T (1), G672A (1), G681T (2), T783C (1), and T819A (2). The biofilm formation capacity of resistant C. albicans strains, including the CAP1∆/∆ strain, was stronger. Afterward, real-time quantitative PCR was used to analyze the expression of SAP2 and CAP1. Compared with the sensitive strains, SAP2 and CAP1 expressions were both significantly upregulated in resistant strains at planktonic and biofilm states ( P < 0.05). Compared with the strains at planktonic state, SAP2 was significantly upregulated, while CAP1 was significantly downregulated at biofilm states ( P < 0.05). Additionally, SAP2 expression in the CAP1 knocked down strain of C. albicans was significantly upregulated, and SAP2 expression was evidently downregulated in the CAP1∆/∆ strain at biofilm states compared with that at planktonic states ( P < 0.05). Loss of CAP1 can increase SAP2 level and may influence the biofilm formation of C. albicans, thus increasing ITR resistance of C. albicans.
Intratumoral Therapy to Make a “Cold” Tumor “Hot”: The Jury Is Still Out
Authors: Punekar Salman R. , Weber Jeffrey S. 
Published: September 2022

Tilsotolimod, an oligodeoxynucleotide TLR9 agonist, administered intratumorally, has been clinically evaluated. This compound has demonstrated the ability to induce changes within the tumor microenvironment, to convert noninflamed cold tumors into inflamed hot tumors, with the hope that these tumors will be more responsive to immune checkpoint blockade.See related article by Babiker et al., p. 5079
Familial Hypercholesterolemia Identification by Machine Learning Using Lipid Profile Data Performs as Well as Clinical Diagnostic Criteria
Authors: Hesse Reinhardt , Raal Frederick J. , Blom Dirk J. , George Jaya A. 
Published: September 2022

Background:
Familial hypercholesterolemia (FH) is a common genetic disorder and, if not diagnosed and treated early, results in premature cardiovascular disease. Most individuals with FH are undiagnosed and machine learning offers a new prospect to improve FH identification. Our objective was to create a machine learning model from basic lipid profile data with better screening performance than LDL-C (low-density lipoprotein cholesterol) cutoff levels and diagnostic performance comparable to the Dutch Lipid Clinic Network criteria.

Methods:
The model was developed combining logistic regression, deep learning, and random forest classification and trained on a 70% split of a data set of individuals clinically suspected of having FH. Model performance, as well as that of the LDL-C cutoff and Dutch Lipid Clinic Network criteria, were assessed on the internal 30% testing data set and an external data set by comparing the area under the receiver operator characteristic (AUROC) curves. All methodologies were measured against the gold standard of FH diagnosis by mutation identification. Furthermore, the model was also tested on 2 lower prevalence data sets.

Results:
The machine learning model achieved an AUROC curve of 0.711 on the external data set (n=1376; FH prevalence=64%), which was superior to the LDL-C cutoff (AUROC=0.642) and comparable to the Dutch Lipid Clinic Network criteria (AUROC=0.705). The model performed even better when tested on the medium-prevalence (n=2655; FH prevalence=20%) and low-prevalence (n=1616; FH prevalence=1%) data sets, with AUROC curve values of 0.801 and 0.856, respectively.

Conclusions:
Despite absence of clinical information, the model better identified genetically confirmed FH in a cohort of individuals suspected of having FH than LDL-C cutoff values and was comparable to the Dutch Lipid Clinic Network criteria. The model achieved higher accuracy when tested on 2 cohorts with lower FH prevalence. The application of machine learning is, therefore, a promising tool in both the screening for, and diagnosis of, individuals with FH.
“Etiquette-Observing” Emotional Actions
Authors: Hao Shaoyi , Zhu Zhiyong 
Published: September 2022

Abstract
The development of the Sociology of Emotions proves the potential correlation between emotion and reason. This study draws on the perspective of the Sociology of Emotions, follows the academic development of the symbolic interaction theory, and adopts the qualitative case study methodology to explore the elements and methods of emotional actions by Xiaomin, the pre-employment preschool teacher during her internship. Our analysis of data collected through observations, interviews, and artifacts finds that an emotional action involves six major elements, namely, emotional subject, emotional symbol, situational condition, emotional meaning, focus and entrainment (mutual focus and emotional entrainment) and emotional object. Based on this finding, this study distinguishes four types of emotional actions, namely, integrative emotional action, divergent emotional action, disintegrative emotional action, and convergent emotional action. Focusing on the composing elements, this study offers a new microscopic way of interpreting emotional actions different from the macroscopic approach that stresses institutional and cultural structures. It is also a useful application of the studies of emotions of the symbolic interaction theory.
Teachers’ Emotional Labor in the Context of New College Entrance Exam Reform in Mainland China
Authors: Wang Xi , Bian Fuyu 
Published: September 2022

Abstract
This study was designed as an explorative qualitative study aiming to investigate Chinese high school teachers’ emotional labor when implementing policies related to the New College Entrance Exam (ncee). Findings are mainly generated from analysis of in-depth interviews. First, as a by-product of the ncee reform, disruptive changes in curricula and school management have brought about negative emotions on the part of teachers. The negative emotions led to teachers’ pessimist attitude towards the ongoing ncee reform. Second, teachers’ negative emotions were intentionally managed and controlled by themselves for different reasons. On the one hand, teachers inhibited negative feelings for building a compassionate climate in classroom teaching. On the other hand, teachers performed to be “emotional-free” in front of students’ parents and school managers. The study suggests that the intensified external institutional pressures, rather than changed classroom teaching, made teaching an alienated labor, depriving teachers’ sustainable commitment to the ncee reform.
Correlation Analysis between Precipitation and Precipitable Water Vapor over China Based on 1999–2015 Ground-Based GPS Observations
Authors: Zhang Zhixuan , Lou Yidong , Zhang Weixing , Liang Hong , Bai Jingna , Song Weiwei 
Published: September 2022

Abstract
Correlation analysis between precipitable water vapor (PWV) and precipitation over China was conducted by combining high-quality PWV data based on 1999–2015 ground-based global positioning system (GPS) observations with the measurements at matched meteorological stations in the same period. The mean correlation coefficient at all the stations is approximately 0.73, indicating that there is a significant positive correlation between PWV content and precipitation measurements, and the comparison of correlation among different climate types suggests that the distribution characteristics of the correlation coefficients are distinctively related to different climate types. There is also some positive correlation between PWV and precipitation long-term trends, with the correlation coefficients of monthly anomalies ranging generally from 0.2 to 0.6. Furthermore, the intensity of both PWV and precipitation extremes shows a long-term upward trend overall, with the most-intense events showing more significant increases. The extreme precipitation–temperature scaling rate of changes can reach above Clausius–Clapeyron (CC) scaling, whereas that of the extreme PWV-temperature is sub-CC overall, with regional differences in the specific scaling values. The correlation analysis in this work is of great significance for long-term climate analysis and extreme weather understanding, which provides a valuable reference for better utilizing the advantages of PWV data to carry out the studies above.

Significance Statement
Atmospheric water vapor is crucial to the climate system, especially in the context of global warming, and accurate knowledge of the correlation between precipitable water vapor (PWV) and precipitation is of great significance for long-term climate analysis and extreme precipitation weather forecasting. We take full advantage of the long-term homogeneity of ground-based GPS to conduct long-term correlation analysis between GPS-derived PWV and precipitation over China. Results show a significant positive correlation between them, and the degree of correlation is related to different climate types. The correlation of monthly anomalies is also positive, and, over the long-term, both water vapor and precipitation extremes have been increasing in intensity, with more significant increases occurring in the most-intense events. Extreme precipitation might increase beyond thermodynamic expectations, whereas PWV increases below expectations.
Explicitly Modeling the Effects of Cloud Condensation Nuclei on Warm Rain Initiation
Authors: Zeng Xiping , Li Xiaowen 
Published: September 2022

Abstract
A bin (or spectral) model is developed to investigate the sensitivity of warm rain initiation to cloud condensation nuclei (CCN). It explicitly represents CCN with a formula whose parameters come from the Twomey relationship (or CCN measurements). By seamlessly integrating CCN activation and drop collection with thousands of bins, the model can replicate the effect of CCN on rain initiation, providing a benchmark to test the process parameterizations in rain initiation. The model is used to simulate two extreme cases with CCN parameters of maritime and continental clouds, respectively, where other actual cases usually lie between these two extreme cases. Its simulations show that rain can initiate within half an hour or less as observed in cumulus clouds. The fast rain initiation modeled is attributed mainly to a new process: the condensational conversion of cloud drops to raindrops via collision–coalescence initiators (or drops with radius between 28 and 100 μm). Since the new process is more important in rain initiation than the autoconversion of cloud drops to raindrops when large CCN exist, it is suggested that the process be parameterized into the weather and climate models to better represent CCN and subsequently remove the common bias of “too dense clouds.”

Significance Statement
The current weather and climate models represent aerosols via implicit parameterizations and have a bias of “too dense clouds.” Their implicit parameterizations of aerosols usually overlook (or misrepresent) some cloud processes. In this paper and its preceding part (Zeng and Li 2020) we proposed a new framework to explicitly parameterize one subset of aerosols: cloud condensation nuclei (CCN). To embody an explicit parameterization of CCN, we still need quantitative information to connect CCN activation and rain initiation, which motivates this study. In the study we developed an accurate microphysical model to simulate the growth of small CCN to large raindrops, providing information on the sensitivity of rain initiation to CCN. We performed many sensitivity simulations and found the condensational conversion of cloud drops to raindrops via collision–coalescence initiators is a vital process in warm rain initiation. Since the process has been overlooked by all the weather and climate models, the study suggests that the process be introduced in the weather and climate models to properly represent the fast warm rain initiation observed and subsequently remove the bias of “too dense clouds.”
The Influence of Demographic and Place Variables on Personalized Tornado Risk Area
Authors: Sherman-Morris Kathleen , Vaughn Cole , Senkbeil Jason C. , Wooten Stephen 
Published: September 2022

Abstract
Although there is clear evidence that proximity to a tornado or forecast tornado increases an individual’s risk perception, the specific relationships between risk personalization and spatial variables are unclear. It has also been established that one’s own evaluation of distance does not always match objective measurement. This study sought to explain the differences in the distance at which an individual would personalize the risk from a tornado across personally relevant geospatial factors such as the distance between places frequented (e.g., home and work), urban/rural classification of the area, and the length of residence in the county. A survey of 1023 respondents across eight states (Alabama, Arkansas, Georgia, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee) was used to obtain risk personalization distances, which were distinguished as “worry distances” (the distances at which one would worry about their house or loved ones, or take protective action) and “confirmation distances” (the distances at which one would expect to see, hear, or feel the effects of a tornado). We found that individuals who traveled greater distances and traveled more frequently to the grocery store and another location, those who self-defined their area as urban, and those with advanced degrees had increased risk personalization distances. Lengthier residency in the county influenced these distances as well. Future research is required to better comprehend the relationship of place, risk perception, and geographic mobility on protective action when a tornado occurs.

Significance Statement
Greater tornado risk personalization distances were associated with self-defining as urban, having an advanced degree, and driving farther and more frequently to the grocery store and to another location. Longer length of residence was associated with shorter risk personalization distances. With rural participants expressing shorter tornado risk personalization distances, warning communicators with the ability to tailor messages to multiple communities may wish to adjust messages no the basis of whether they are targeted to rural communities or to urban communities.
Enasidenib as maintenance following allogeneic hematopoietic cell transplantation for IDH2-mutated myeloid malignancies
Authors: Fathi Amir T. , Kim Haesook T. , Soiffer Robert J. , Levis Mark J. , Li Shuli , Kim Annette S. , Mims Alice S. , DeFilipp Zachariah , El-Jawahri Areej , McAfee Steven L. , Brunner Andrew M. , Narayan Rupa , Knight Laura W. , Kelley Devon , Bottoms AJ S. , Perry Lindsey H. , Wahl Jonathan L. , Brock Jennifer , Breton Elayne , Ho Vincent T. , Chen Yi-Bin 
Published: September 2022

Abstract
IDH2 (isocitrate dehydrogenase 2) mutations occur in approximately 15% of patients with acute myeloid leukemia (AML). The IDH2 inhibitor enasidenib was recently approved for IDH2-mutated relapsed or refractory AML. We conducted a multi-center, phase I trial of maintenance enasidenib following allogeneic hematopoietic cell transplantation (HCT) in patients with IDH2-mutated myeloid malignancies. Two dose levels, 50mg and 100mg daily were studied in a 3 × 3 dose-escalation design, with 10 additional patients treated at the recommended phase 2 dose (RP2D). Enasidenib was initiated between days 30 and 90 following HCT and continued for twelve 28-day cycles. Twenty-three patients were enrolled, of whom 19 initiated post-HCT maintenance. Two had myelodysplastic syndrome, and 17 had AML. All but 3 were in first complete remission. No dose limiting toxicities were observed, and the RP2D was established at 100mg daily. Attributable grade ≥3 toxicities were rare, with the most common being cytopenias. Eight patients stopped maintenance before completing 12 cycles, due to adverse events (n=3), pursuing treatment for graft-vs-host disease (GVHD) (n=2), clinician choice (n=1), relapse (n=1), and COVID infection (n=1). No cases of grade ≥3 acute GVHD were seen, and 12-month cumulative incidence of moderate/severe chronic GVHD was 42% (20-63%). Cumulative incidence of relapse was 16% (95% CI: 3.7-36%); 1 subject relapsed while receiving maintenance. Two-year progression-free and overall survival were 69% (95% CI: 39-86%) and 74% (95% CI, 44-90%), respectively. Enasidenib is safe, well-tolerated, with preliminary activity as maintenance therapy following HCT, and merits additional study. The study was registered at www.clinicaltrials.gov (#NCT03515512).