bluuebunny/crossref_metadata_2025_split huggingface dataset:
The value of Bayesian predictive projection for variable selection: an example of selecting lifestyle predictors of young adult well-being
Authors: Bartonicek A. , Wickham S. R. , Pat N. , Conner T. S. 
Published: April 2021

AbstractBackgroundVariable selection is an important issue in many fields such as public health and psychology. Researchers often gather data on many variables of interest and then are faced with two challenging goals: building an accurate model with few predictors, and making probabilistic statements (inference) about this model. Unfortunately, it is currently difficult to attain these goals with the two most popular methods for variable selection methods: stepwise selection and LASSO. The aim of the present study was to demonstrate the use predictive projection feature selection – a novel Bayesian variable selection method that delivers both predictive power and inference. We apply predictive projection to a sample of New Zealand young adults, use it to build a compact model for predicting well-being, and compare it to other variable selection methods.MethodsThe sample consisted of 791 young adults (ages 18 to 25, 71.7% female) living in Dunedin, New Zealand who had taken part in the Daily Life Study in 2013–2014. Participants completed a 13-day online daily diary assessment of their well-being and a range of lifestyle variables (e.g., sleep, physical activity, diet variables). The participants’ diary data was averaged across days and analyzed cross-sectionally to identify predictors of average flourishing. Predictive projection was used to select as few predictors as necessary to approximate the predictive accuracy of a reference model with all 28 predictors. Predictive projection was also compared to other variable selection methods, including stepwise selection and LASSO.ResultsThree predictors were sufficient to approximate the predictions of the reference model: higher sleep quality, less trouble concentrating, and more servings of fruit. The performance of the projected submodel generalized well. Compared to other variable selection methods, predictive projection produced models with either matching or slightly worse performance; however, this performance was achieved with much fewer predictors.ConclusionPredictive projection was used to efficiently arrive at a compact model with good predictive accuracy. The predictors selected into the submodel – felt refreshed after waking up, had less trouble concentrating, and ate more servings of fruit – were all theoretically meaningful. Our findings showcase the utility of predictive projection in a practical variable selection problem.
Sickness absence and disability pension among women with breast cancer: a population-based cohort study from Sweden
Authors: Kvillemo Pia K. , Chen Lingjing , Bottai Matteo , Frumento Paolo , Almondo Gino , Mittendorfer-Rutz Ellenor , Friberg Emilie , Alexanderson Kristina A. E. 
Published: April 2021

Abstract
Background
Women’s return to work after diagnosis of breast cancer (BC) is becoming more prevalent. However, register-based national investigation on sickness absence (SA) and disability pension (DP) in BC women is lacking. The aim of the study was to explore SA and DP before and after a first BC diagnosis and the possibility to predict new cancer-related SA by using disease-related and sociodemographic factors.

Methods
A longitudinal register study of the 3536 women in Sweden aged 19–64 with a first BC diagnosis in 2010 was conducted by linkage of five nationwide registers. Particularly, detailed information on SA and DP was obtained from the National Social Insurance Agency. Descriptive statistics on SA and DP 2 years before through 3 years after the BC diagnosis were performed. The risk of having a new SA spell due to BC or BC-related diagnoses was modeled using logistic regression.

Results
The proportion of women with SA increased during the year following the BC diagnosis date and declined over the next 2 years to proportions before diagnosis. At the time of BC diagnosis, half of the women began a new SA spell > 14 days with cancer, cancer-related, or mental diagnosis. Disease-related and sociodemographic factors including occupational sector, living area, age, cancer stage, educational level, and number of previous SA days showed statistical significance (p < 0.05) in predicting a new SA around BC diagnosis. By using these factors, it was possible to correctly predict 67% of the new SA spell.

Conclusions
SA among women with BC was elevated mainly in the first year after diagnosis. New SA following BC diagnosis can accurately be predicted.
The efficacy and safety of indocyanine green-hyaluronic acid mixture (LuminoMark™) for localization in patients with non-palpable breast lesions: a multi-center open-label parallel phase-2 clinical trial
Authors: Kim Isaac , Choi Hee Jun , Ryu Jai Min , Lee Se Kyung , Yu Jong Han , Lee Jeong Eon , Nam Seok Jin , Shin Hyuk Jai , Kim Seok Won 
Published: April 2021

Abstract
Background
Increasing rates of breast cancer screening have been associated with an increasing frequency of non-palpable breast lesions detection. Preoperative breast lesion localization is essential for optimizing excision accuracy. This study aimed to evaluate the efficacy and safety of indocyanine green (ICG) hyaluronic acid injection as a novel mixture for localization.

Methods
We performed a prospective clinical trial with female patients who underwent surgery for non-palpable breast lesions. All patients were sequentially assigned to the control group (localization with activated charcoal), Test Group 1 (ICG-hyaluronic acid mixture 0.1 mL), or Test Group 2 (ICG-hyaluronic acid mixture 0.2 mL) by 1:1:1 ratio.

Results
A total of 44 patients were eligible for this study (Control Group = 14, Test Group 1 = 15, Test Group 2 = 15 patients). Fibroadenoma (n = 17, 38.6%) accounted for the largest proportion of diagnoses, and five patients (11.4%) were diagnosed with malignancies. There were no statistically significant differences in baseline characteristics among the three groups. The marking rate was over 86% in all groups, with no significant intergroup differences. Skin pigmentation was only observed in the control group. The mean accuracy of resection (the greatest diameter of the excised specimen divided by the greatest diameter of the preoperative lesion as observed using ultrasonography, with values closer to 1 reflecting a higher accuracy) was 3.7 in the control group, 2.2 in Test Group 1, and 2.1 in Test Group 2 (p = 0.037 between Controls and Test Group 1, p = 0.744 between Test Group 1 and Test Group 2, and p = 0.026 between Controls and Test Group 2).

Conclusion
ICG-hyaluronic acid injection is a novel method that was shown to accurately localize non-palpable breast lesions and was associated with no skin pigmentation. Further research is required to apply this method to malignant breast lesions.
Trial registration “A Multicenter Open-label, Parallel, Phase 2 Clinical Trial to Evaluate the Efficacy and Safety of LuminoMark™ Inj. (Conc. for Fluorescence) Localization in Patients with Non-palpable Breast Lesions” was prospectively registered as a trial (ClinicalTrials. gov Identifier: NCT03743259, date of registration: May 29, 2018, https://clinicaltrials.gov/ct2/show/NCT03743259)
Risk factors for postoperative nausea and vomiting after the removal of impacted third molars: a cross-sectional study
Authors: Hasegawa Hiroaki , Abe Atsushi , Hayashi Hiroki , Furuta Hiroshi , Ishihama Takanori 
Published: April 2021

Abstract
Background
A better understanding of the risk factors for postoperative nausea and vomiting (PONV) could improve patient outcomes. This study aimed to analyze the risk factors for PONV and its onset after third molar impaction surgery, and to demonstrate the importance of controlling anesthesia-related factors regardless of patient-specific factors.

Methods
We included patients who reported nausea and vomiting within 12 h of extubation. Patients with incomplete data, those who could not communicate, and those with gastrointestinal disorders were excluded. We evaluated patient-specific risk factors, and the use of volatile anesthetics and intraoperative fentanyl anesthetic-related factors. Multiple logistic regression analysis was performed taking patient background factors into account.

Results
In total, 182 patients who underwent disimpaction of the third molar under general anesthesia between January 2017 and December 2018 at Nagoya Ekisaikai Hospital, were included. Approximately 12.6% (n = 23) patients experienced PONV, with no significant difference in terms of sex, smoking status, age, and body mass index compared to patients without PONV. Multiple logistic regression analysis revealed no interaction between fentanyl and volatile anesthetics. The major risk factor for PONV was the use of volatile anesthetics. Patients in whom anesthesia was maintained by volatile anesthetics were 13.35 times more likely to have PONV than those in whom total intravenous anesthesia was induced (P < 0.001).

Conclusion
Maintenance of anesthesia with volatile anesthetics is a risk factor for PONV.
Survey of the triple-mentoring program for students at a religious medical school
Authors: Tseng Ting-Chun , Chen Tsung-Ying , Chu Shao-Yin , Wang Hung-Che , Chang Ching-Yuan 
Published: April 2021

Abstract
Background
Tzu Chi University in Taiwan offers a unique mentoring program. This program differs from others as it comprises triple mentorship, namely, faculty mentors, Tzu Cheng/Yi De (TC/YD; senior volunteers), and school counselors. This study aimed to survey the role functions of the mentors from the perspective of medical students.

Methods
The Role Functions of the Mentoring Program Scale (RFMPS) was developed on the basis of literature reviews and focus groups and it underwent exploratory factor analysis for internal consistency and reliability. RFMPS comprises four role functions, namely, mental, educational, career, and humanistic/moral guidance counseling. The survey was distributed to 171 medical students via an online network with two-month intervals and was analyzed using multivariate analysis of variance.

Results
The overall response rate was 64% (116/171). The mean scores of the four role functions in descending order belonged to faculty mentors, TC/YD, and school counselors. For humanistic/moral guidance, students had an equal preference for the faculty mentors and TC/YD over school counselors. As for educational, career, and mental guidance counseling, students preferred faculty mentors over TC/YD and school counselors. Faculty mentors provided students with the required guidance counseling for all the four role functions, especially educational guidance; TC/YD in particular offered prominent humanistic/moral guidance and career counseling; school counselors were less preferred but guided students in need.

Conclusions
Medical students value different role functions provided by faculty mentors, TC/YD, and school counselors. A diversified focus could be provided by the faculty mentors, particularly in educational, career, mental, and humanistic/moral counseling; TC/YD specialized in humanistic/moral guidance; and the school counselors carried out their role function only when needed. Humanistic/moral guidance is equally preferred to other types of guidance, which can be equally valuable in future mentoring programs.
Using Markov chain model to evaluate medical students’ trajectory on progress tests and predict USMLE step 1 scores---a retrospective cohort study in one medical school
Authors: Wang Ling , Laird-Fick Heather S. , Parker Carol J. , Solomon David 
Published: April 2021

Abstract
Background
Medical students must meet curricular expectations and pass national licensing examinations to become physicians. However, no previous studies explicitly modeled stages of medical students acquiring basic science knowledge. In this study, we employed an innovative statistical model to characterize students’ growth using progress testing results over time and predict licensing examination performance.

Methods
All students matriculated from 2016 to 2017 in our medical school with USMLE Step 1 test scores were included in this retrospective cohort study (N = 358). Markov chain method was employed to: 1) identify latent states of acquiring scientific knowledge based on progress tests and 2) estimate students’ transition probabilities between states. The primary outcome of this study, United States Medical Licensing Examination (USMLE) Step 1 performance, were predicted based on students’ estimated probabilities in each latent state identified by Markov chain model.

Results
Four latent states were identified based on students’ progress test results: Novice, Advanced Beginner I, Advanced Beginner II and Competent States. At the end of the first year, students predicted to remain in the Novice state had lower mean Step 1 scores compared to those in the Competent state (209, SD = 14.8 versus 255, SD = 10.8 respectively) and had more first attempt failures (11.5% versus 0%). On regression analysis, it is found that at the end of the first year, if there was 10% higher chance staying in Novice State, Step 1 scores will be predicted 2.0 points lower (95% CI: 0.85–2.81 with P < .01); while 10% higher chance in Competent State, Step 1scores will be predicted 4.3 points higher (95% CI: 2.92–5.19 with P < .01). Similar findings were also found at the end of second year medical school.

Conclusions
Using the Markov chain model to analyze longitudinal progress test performance offers a flexible and effective estimation method to identify students’ transitions across latent stages for acquiring scientific knowledge. The results can help identify students who are at-risk for licensing examination failure and may benefit from targeted academic support.
S-ketamine and intranasal application: alternatives for the castration of male suckling piglets?
Authors: Becker Sabrina , Maier Anna , Peters Saskia , Büttner Kathrin , Reiner Gerald 
Published: April 2021

Abstract
Background
The intramuscular injection of ketamine and azaperone was proposed as a suitable anaesthesia for male suckling piglets for surgical castration. However, this can be opposed by massive defensive movements, hypothermia and tachycardia during castration and a long recovery period. The aim of the present study was to test whether the use of S-ketamine and/or a change in the route of application from intramuscular to intranasal could reduce stress responses and the duration of recovery compared to the intramuscular route and the use of racemic ketamine. Seventy-eight healthy, five-day-old male piglets were randomized to six treatment groups in a blinded experimental study, matched by litter and weight. Experimental groups were A (15 mg kg-1 S-ketamine + 2 mg kg-1 azaperone, i.m., surgical castration), B (15 mg kg-1 R/S-ketamine racemate + 2 mg kg-1 azaperone, i.m., surgical castration), C (30 mg kg-1 S-ketamine + 2 mg kg-1 azaperone, i.n., surgical castration), D (15 mg kg-1 R/S-ketamine racemate + 2 mg kg-1 azaperone, i.m.; not castrated), E (positive control group; no anesthesia, surgical castration) and F (negative control group; no anesthesia, not castrated).

Results
S-ketamine reduced the defensive movement score during castration to a similar extent to racemic ketamine when administered intramuscularly but not via the intranasal route. However, the effects of S-ketamine (both routes) on the increase in cortisol levels and decrease in body temperature were similar to those induced by racemic ketamine. A reduction of the long recovery time known for ketamine-azaperone anaesthesia could not be achieved with S-ketamine in the given dosage, regardless of the route of application. The intranasal administration of ketamine was difficult with the available formulation as the necessary amount exceeded the capacity of the nose cavity.

Conclusions
Neither the use of S-ketamine nor intranasal administration can be suitable alternatives for the anaesthesia of male suckling piglets for castration.
The informed consent process in health research with under-served populations: a realist review protocol
Authors: Hoverd Eleanor , Staniszewska Sophie , Dale Jeremy 
Published: April 2021

AbstractBackgroundThe informed consent process aims to provide potential participants with information about health research that enables them to make an informed decision as to whether they choose to participate, or not. However, it remains unclear as to whether the process is effective for those who are under-served in health research. It is a pivotal issue within health research that the diversity of people who participate is broadened. The National Institute for Health Research (NIHR) pledges to support equality, diversity and inclusion, actively creating opportunities for all citizens whom are eligible, to take part in health research.MethodsIn order to understand how the informed consent process for under-served populations in health research works, under what circumstances and in what respects, a realist review approach will be undertaken. Searches will be carried out using electronic databases (EMBASE, MEDLINE, Web of Science and PsycINFO), along with selected websites and grey literature. Development of initial rough programme theory(ies) will lead to a more refined programme theory that will provide an explanation of context, mechanism and outcomes. Stakeholder involvement by NIHR (Public) Research Champions, health professionals and clinical academics will provide expert opinion about concepts and programme theory.DiscussionFindings of this realist review will highlight how the informed consent process in health research affects the experience and decision-making process of potential participants from under-served populations. They will be written up in accordance with RAMESES guidelines and disseminated to patients and the public, health researchers, health professionals and policymakers through peer-reviewed publication, presentations and discussions. The review will contribute to our understanding of the mechanisms that cause both positive and negative outcomes in the informed consent process for those whom are often under-represented in health research to inform policy, study design and delivery.
Extruded breakfast meal from malted finger millet (Eleusine coracana) and watermelon (Citrullus lanatus) seed flour: in-vivo nutritional qualities study
Authors: Owheruo Joseph Oghenewogaga , Oluwajuyitan Timilehin David , Ifesan Beatrice Olawunmi , Bolade Matthew Kolawole 
Published: April 2021

Abstract
Background
The study aimed at evaluating the in-vivo nutritional qualities of extruded breakfast meal produced from flour blends of malted finger millet and watermelon seed.

Results
The proximate compositions of the flour blends revealed that there was progressive increase in protein (12.83–15.14) %, with increase in the watermelon substitution. The protein quality evaluation of the extrudate showed that the protein efficiency ratio ranged from 0.64 to 89.75, while the biological values were between (87.82–89.75)%. The relative organs weight of rats fed with extruded breakfast meal showed that, the weights of the kidney and liver of rats fed with extruded breakfast meal were significantly lower compared with rats fed with goldenmorn. The hematological indices showed that the packed cell volume and the red blood cell counts of rats fed with the formulated diets were significantly lower compared with those fed with goldenmorn but significantly higher than rats fed with basal. Meanwhile, the values of the white blood cells count for the formulated diet shows no significant difference compared with rats fed with goldenmorn.

Conclusions
Evidently, the growth performance of the rats fed with the extruded breakfast meal revealed that the formulated diets promote growth status of the animals with relatively low effect on organs of experimental rat used in this study. Hence, formulated diet may serve as alternative to expensive commercial breakfast meal.
Depressive symptoms are associated with impaired sleep, fatigue, and disease activity in women with rheumatoid arthritis
Authors: Lopes Fernando Henrique Azevedo , Freitas Max Victor Carioca , de Bruin Veralice Meireles Sales , de Bruin Pedro Felipe Carvalhedo 
Published: April 2021

Abstract
Objectives
To investigate the associations between sleep quality, fatigue, disease activity and depressive symptoms in women with rheumatoid arthritis (RA).

Methods
Female patients with previous diagnosis of RA from a Rheumatology Outpatient Clinic at a tertiary referral centre, in Fortaleza, Brazil, were consecutively recruited into the study. Sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI); fatigue by the Fatigue Severity Scale (FSS); daytime sleepiness by the Epworth Sleepiness Scale (ESS); and depressive symptoms by the Beck Depression Inventory II (BDI-II). RA activity was measured by the disease activity score (DAS28).

Results
One hundred ten women (mean age ± SD = 51.1 ± 13.0 y) were included in the study. On average, patients with depressive symptoms (BDI-II > 13), as compared to those without, showed poorer sleep quality (PSQI: 10.09 ± 4.1 vs 7.33 ± 3.55; p = 0.001 respectively), more fatigue (FSS: 4.69 ± 1.89 vs 3.34 ± 1.8; p = 0.001) and higher disease activity level (DAS28: 4.36 ± 1.53 vs 3.7 ± 1.39; p = 0,047). The logistic regression analysis showed that sleep quality is an independent predictor of depressive symptom severity.

Conclusion
Depressive symptoms, impaired sleep and fatigue are common in women with RA. Poor sleep is associated with greater frequency and severity of depressive symptoms in these patients, suggesting that screening for sleep and mood problems may be relevant both in clinical research and routine patient care. Future studies investigating the impact of measures to promote healthy sleep on depressive symptom control in this patient population are warranted.
ChannelSeg3D: Channel simulation and deep learning for channel interpretation in 3D seismic images
Authors: Gao Hang , Wu Xinming , Liu Guofeng 
Published: April 2021

Seismic channel interpretation involves detecting channel structures, which often appear as meandering shapes in 3D seismic images. Many conventional methods are proposed for delineating channel structures using different seismic attributes. However, these methods are often sensitive to seismic discontinuities (e.g., noise and faults) that are not related to channels. We have adopted a convolutional neural network (CNN) method to improve automatic channel interpretation. The key problem in applying the CNN method into channel interpretation is the absence of labeled field seismic images for training the CNNs. To solve this problem, we adopt a workflow to automatically generate numerous synthetic training data sets with realistic channel structures. In this workflow, we first randomly simulate various meandering channel models based on geologic numerical simulation. We further simulate structural deformation in the form of stratigraphic folding referred to as “folding structures” and combine them with the previously generated channel models to create reflectivity models and the corresponding channel labels. Convolved with a wavelet, the reflectivity models can be transformed into learnable synthetic seismic volumes. By training the designed CNN with synthetic seismic data, we obtain a CNN that learns the characterization of channel structures. Although trained on only synthetic seismic volumes, this CNN shows outstanding performance on field seismic volumes. This indicates that the synthetic seismic images created in this workflow are realistic enough to train the CNN for channel interpretation in field seismic images.