bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Investigation of Tone Production in Relation to Management of Bow Weight and Speed among Beginning and Intermediate String Players: A Pilot Study
Authors: Taylor Skip 
Published: March 2023

Management of the bow to the point of achieving the most efficient physical interaction between the hair and strings is crucial to successful stringed instrument achievement and performance. Inferior tone production often restricts string students from achieving a totality of musically-acceptable performance skills. A spectral analysis of open string bowing was performed with middle school and high school string players in grades 6–10. Each subject bowed two separate down bows on the open violin A string. The specific objective was to investigate student control of bowed weight and speed management skills among a small sample of middle school and high school string players. Visual graphs were produced and analyzed from the digital analog recordings and are discussed in terms of amplitude across time in relation to management of weight and speed. The findings indicate that inferior tone production may be the result of inconsistency among young string players’ ability to maintain an appropriate balance between weight and speed.
The diagnostic utility of creatine kinase-MB versus total creatine phosphokinase ratio in patients with non-ST elevation myocardial infarction from unstable angina
Authors: Motamed Hassan , Mohammadi Mohammad , Tayebi Zahra , Rafati Navaei Alireza 
Published: March 2023

Objective: The present study seeks to find a way to quickly and correctly differentiate myocardial infarction from unstable angina by measuring the creatine kinase-MB/creatine phosphokinase ratio and comparing in non-ST elevation myocardial infarction patients with unstable angina at different time intervals, to improve the health quality of patients with coronary artery disease. Methods: The present study is a retrospective epidemiological analysis of 260 patients with non-ST elevation myocardial infarction and 260 patients with unstable angina, including age, sex, creatine kinase-MB, and creatine phosphokinase biomarkers at two-time intervals, including referral (4–8 h from the onset of pain) as the first interval, and 8 h after the first sampling was extracted as the second interval. Moreover, the delta of the creatine kinase-MB/creatine phosphokinase ratio during two interval times was measured. Results: In non-ST elevation myocardial infarction patients in the first and second intervals, creatine kinase-MB/creatine phosphokinase ratio was 32.7 and 33.8% higher than the normal laboratory cutoff (positive), respectively, and in the group of unstable angina patients, this index was positive in 31.9 and 30.4% of patients, respectively. There was no significant difference between the mean creatine kinase-MB to creatine phosphokinase index between the patients with non-ST elevation myocardial infarction and unstable angina ( p = 0.507). In the first interval, the sensitivity and specificity of this index in differentiating non-ST elevation myocardial infarction from unstable angina were 51.5 and 57.3% (area under the curve = 0.518), respectively. While in the second interval, the sensitivity and specificity of this index were 17.7 and 87.8% (area under the curve = 0.519), respectively. The creatine kinase-MB/creatine phosphokinase delta in the non-ST elevation myocardial infarction group was significantly higher than in patients with unstable angina during different time intervals ( p = 0.01). Conclusion: According to our results, creatine kinase-MB/creatine phosphokinase index cannot help differentiate the two groups of non-ST elevation myocardial infarction and unstable angina. However, the findings show that higher levels of creatine kinase-MB enzyme and creatine kinase-MB/creatine phosphokinase delta in the early hours, 4–16 h after the onset of pain in non-ST elevation myocardial infarction patients, can be used to differentiate between non-ST elevation myocardial infarction and unstable angina.
Epidemiology, Risk Factors, and Outcome of Cardiac Dysrhythmias in a Noncardiac Intensive Care Unit
Authors: Savaie Mohsen , Sheikhi Yasaman , Baghbanian Reza , Soltani Farhad , Amiri Fereshteh , Hesam Saeed 
Published: March 2023

Introduction Several extrinsic factors contribute to the development of cardiac dysrhythmias. In intensive care unit (ICU) settings and among critically ill patients who are exposed to a large number of risk factors, cardiac disturbances are more common. Objectives This study aimed to examine the epidemiology, risk factors, and outcome of cardiac dysrhythmias in a non-cardiac ICU. Methods This is a retrospective, single-center, observational study conducted in a tertiary noncardiac ICU at Imam Khomeini Hospital in Ahvaz, Iran. Out of the 360 adult patients aged 18 years and older who were admitted to ICU for longer than 24 h, 340 cases who met the study inclusion criteria were recruited between March 2018 until October 2018. Results The most common nonsinus dysrhythmias were new-onset atrial fibrillation (NOAF) (12.9%) and ventricular tachycardia (21 patients—6.2%). According to our results, previous percutaneous coronary instrumentation, acute kidney injury, sepsis, and hyperkalemia act as risk factors in the development of cardiac dysrhythmias. Additionally, we found out that thyroid dysfunction and pneumonia can predict the development of NOAF in critically ill patients. The estimated mortality rate among patients with NOAF in this study was 15.7% ( p < .05). Conclusion Cardiac dysrhythmias are common in ICU patients and treating the risk factors can help to prevent their development and improve patient management and outcome.
Pickaxe: a Python library for the prediction of novel metabolic reactions
Authors: Shebek Kevin M. , Strutz Jonathan , Broadbelt Linda J. , Tyo Keith E. J. 
Published: March 2023

Abstract
Background
Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user’s application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation.

Results
Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset.

Conclusion
Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package (https://pypi.org/project/minedatabase/) or on GitHub (https://github.com/tyo-nu/MINE-Database). Documentation and examples can be found on Read the Docs (https://mine-database.readthedocs.io/en/latest/). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.
Bayesian kinetic modeling for tracer-based metabolomic data
Authors: Zhang Xu , Su Ya , Lane Andrew N. , Stromberg Arnold J. , Fan Teresa W. M. , Wang Chi 
Published: March 2023

Abstract
Background
Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly $$^{13}C$$

13

C

-enriched glucose ($$^{13}C_6$$

13

C
6

-Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups.

Results
We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts’ knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux.

Conclusions
Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data.
Performance of heart rate adjusted heart rate variability for risk stratification of sudden cardiac death
Authors: Yan Su-Peng , Song Xin , Wei Liang , Gong Yu-Shun , Hu Hou-Yuan , Li Yong-Qin 
Published: March 2023

Abstract
Purpose
As a non-invasive tool for the assessment of cardiovascular autonomic function, the predictive value of heart rate variability (HRV) for sudden cardiac death (SCD) risk stratification remains unclear. In this study, we investigated the performance of the individualized heart rate (HR) adjusted HRV (HRVI) for SCD risk stratification in subjects with diverse risks.

Methods
A total of 11 commonly used HRV metrics were analyzed in 192 subjects, including 88 healthy controls (low risk group), 82 hypertrophic cardiomyopathy (HCM) patients (medium risk group), and 22 SCD victims (high risk group). The relationship between HRV metrics and HR was examined with long-term and short-term analysis. The performance HRVI was evaluated by area under the receiver operating characteristic curve (AUC) and covariance of variation (CV).

Results
Most of the HRV metrics were exponentially decayed with the increase of HR, while the exponential power coefficients were significantly different among groups. The HRVI metrics discriminated low, medium and high risk subjects with a median AUC of 0.72[0.11], which was considerably higher than that of the traditional long-term (0.63[0.04]) and short-term (0.58[0.05]) HRV without adjustment. The average CV of the HRVI metrics was also significantly lower than traditional short-term HRV metrics (0.09 ± 0.02 vs. 0.24 ± 0.13, p < 0.01).

Conclusions
Subjects with diverse risks of SCD had similar exponential decay relationship between HRV metrics and HR, but with different decaying rates. HRVI provides reliable and robust estimation for risk stratification of SCD.
Prevalence of potentially inappropriate medication use in older population: comparison of the Finnish Meds75+ database with eight published criteria
Authors: Paulamäki Jasmin , Jyrkkä Johanna , Hyttinen Virva , Jämsen Esa 
Published: March 2023

Abstract
Background
There are several national and international criteria available for identifying potentially inappropriate medications (PIMs) for older people. The prevalence of PIM use may vary depending on the criteria used. The aim is to examine the prevalence of potentially inappropriate medication use in Finland according to the Meds75+ database, developed to support clinical decision-making in Finland, and to compare it with eight other PIM criteria.

Methods
This nationwide register study consisted of Finnish people aged 75 years or older (n = 497,663) who during 2017–2019 purchased at least one prescribed medicine considered as a PIM, based on any of the included criteria. The data on purchased prescription medicines was collected from the Prescription Centre of Finland.

Results
The annual prevalence of 10.7–57.0% was observed for PIM use depending on which criteria was used. The highest prevalence was detected with the Beers and lowest with the Laroche criteria. According to the Meds75+ database, annually every third person had used PIMs. Regardless of the applied criteria, the prevalence of PIM use decreased during the follow-up. The differences in the prevalence of medicine classes of PIMs explain the variance of the overall prevalence between the criteria, but they identify the most commonly used PIMs quite similarly.

Conclusion
PIM use is common among older people in Finland according to the national Meds75+ database, but the prevalence is dependent on the applied criteria. The results indicate that different PIM criteria emphasize different medicine classes, and clinicians should consider this issue when applying PIM criteria in their daily practice.
Predicting outcomes in chronic kidney disease: needs and preferences of patients and nephrologists
Authors: van der Horst Dorinde E. M. , Engels Noel , Hendrikx Jos , van den Dorpel Marinus A. , Pieterse Arwen H. , Stiggelbout Anne M. , van Uden–Kraan Cornelia F. , Bos Willem jan W. 
Published: March 2023

Abstract
Introduction
Guidelines on chronic kidney disease (CKD) recommend that nephrologists use clinical prediction models (CPMs). However, the actual use of CPMs seems limited in clinical practice. We conducted a national survey study to evaluate: 1) to what extent CPMs are used in Dutch CKD practice, 2) patients’ and nephrologists’ needs and preferences regarding predictions in CKD, and 3) determinants that may affect the adoption of CPMs in clinical practice.

Methods
We conducted semi-structured interviews with CKD patients to inform the development of two online surveys; one for CKD patients and one for nephrologists. Survey participants were recruited through the Dutch Kidney Patient Association and the Dutch Federation of Nephrology.

Results
A total of 126 patients and 50 nephrologists responded to the surveys. Most patients (89%) reported they had discussed predictions with their nephrologists. They most frequently discussed predictions regarded CKD progression: when they were expected to need kidney replacement therapy (KRT) (n = 81), and how rapidly their kidney function was expected to decline (n = 68). Half of the nephrologists (52%) reported to use CPMs in clinical practice, in particular CPMs predicting the risk of cardiovascular disease. Almost all nephrologists (98%) reported discussing expected CKD trajectories with their patients; even those that did not use CPMs (42%). The majority of patients (61%) and nephrologists (84%) chose a CPM predicting when patients would need KRT in the future as the most important prediction. However, a small portion of patients indicated they did not want to be informed on predictions regarding CKD progression at all (10–15%). Nephrologists not using CPMs (42%) reported they did not know CPMs they could use or felt that they had insufficient knowledge regarding CPMs. According to the nephrologists, the most important determinants for the adoption of CPMs in clinical practice were: 1) understandability for patients, 2) integration as standard of care, 3) the clinical relevance.

Conclusion
Even though the majority of patients in Dutch CKD practice reported discussing predictions with their nephrologists, CPMs are infrequently used for this purpose. Both patients and nephrologists considered a CPM predicting CKD progression most important to discuss. Increasing awareness about existing CPMs that predict CKD progression may result in increased adoption in clinical practice. When using CPMs regarding CKD progression, nephrologists should ask whether patients want to hear predictions beforehand, since individual patients’ preferences vary.
Acceptability and user experiences of a patient-held smart card for antenatal services in Nigeria: a qualitative study
Authors: Itanyi Ijeoma Uchenna , Iwelunmor Juliet , Olawepo John Olajide , Gbadamosi Semiu , Ezeonu Alexandra , Okoli Adaeze , Ogidi Amaka Grace , Conserve Donaldson , Powell Byron , Onoka Chima Ariel , Ezeanolue Echezona Edozie 
Published: March 2023

Abstract
Background
Poor maternal, newborn and child health outcomes remain a major public health challenge in Nigeria. Mobile health (mHealth) interventions such as patient-held smart cards have been proposed as effective solutions to improve maternal health outcomes. Our objectives were to assess the acceptability and experiences of pregnant women with the use of a patient-held smartcard for antenatal services in Nigeria.

Methods
Using focus group discussions, qualitative data were obtained from 35 pregnant women attending antenatal services in four Local Government Areas (LGAs) in Benue State, Nigeria. The audio-recorded data were transcribed and analyzed using framework analysis techniques such as the PEN-3 cultural model as a guide.

Results
The participants were 18–44 years of age (median age: 24 years), all were married and the majority were farmers. Most of the participants had accepted and used the smartcards for antenatal services. The most common positive perceptions about the smartcards were their ability to be used across multiple health facilities, the preference for storage of the women’s medical information on the smartcards compared to the usual paper-based system, and shorter waiting times at the clinics. Notable facilitators to using the smartcards were its provision at the “Baby showers” which were already acceptable to the women, access to free medical screenings, and ease of storage and retrieval of health records from the cards. Costs associated with health services was reported as a major barrier to using the smartcards. Support from health workers, program staff and family members, particularly spouses, encouraged the participants to use the smartcards.

Conclusion
These findings revealed that patient-held smart card for maternal health care services is acceptable by women utilizing antenatal services in Nigeria. Understanding perceptions, barriers, facilitators, and supportive systems that enhance the use of these smart cards may facilitate the development of lifesaving mobile health platforms that have the potential to achieve antenatal, delivery, and postnatal targets in a resource-limited setting.
Magnitude of depression and associated risk factors among patients with musculoskeletal disorder treated in physiotherapy outpatient department in Amhara region comprehensive specialized hospital in Ethiopia: a prospective cross-sectional study
Authors: Yalew Ermias Solomon , Melese Ashenafi Zemed , Guadie Yisak Girma , Abich Yohannes , Kassa Tesfa , Gashaw Moges 
Published: March 2023

Abstract
Background
The state of depression that can lead to substance and drug abuse, as well as an increased risk of suicide. Without a doubt, the link between musculoskeletal pain and depression compromises a person’s health and drastically lowers their quality of life, resulting in increased incapacity. Depression and musculoskeletal discomfort are two well-known risk factors for long-term sickness absence, which is defined as a period of sickness lasting more than a week, which means chronic musculoskeletal pains, particularly multiple pains, are linked to depression. And early diagnosis and care of depression in musculoskeletal disorder are critical to patients’ physical, functional, and occupational results. This study aimed to assess the magnitude of depression and associated risk factors among patients with musculoskeletal disorder.

Method
Multi-institution cross-sectional study conducted in Amhara region Comprehensive specialized Hospitals from April 1st to May 30th, 2021. The data was collected from 217 participants through interview administrative questioner and patient medical record review. Binary logistic regression was used to identify associated risk factors of depression. The strength of the association was detected by the adjusted odds ratio.

Result
A total of 217 participate in this study with the age range of 18–80 years. Among the study participants, 57.1% (n = 124) (AOR: 95% CI: 50.7–63.6) were had depression. Treatment duration, and social support were significantly association with depression among patient with musculoskeletal disorder with P < 0.05.

Conclusion
The magnitude of depression was relatively high among musculoskeletal disorder patients treated in physiotherapy out-patient department. The length of treatment duration (hospital stay) and the status of social support from families and friends were significantly associated with depression among patients with musculoskeletal disorders. A multidisciplinary strategy is required for diagnosing and treating depression in patients with musculoskeletal disorder.
Depression, anxiety, stress, and PTSD symptoms during the first and second COVID-19 waves: a comparison of elderly, middle-aged, and young people in Iran
Authors: Pasha Hajar , Omidvar Shabnam , Faramarzi Mahbobeh , Bakhtiari Afsaneh 
Published: March 2023

Abstract
Background
A widespread outbreak of epidemics like Covid-19 is a lethal threat to physical and mental health. Recent studies reported a higher prevalence of mental problems in younger individuals, contrary to the general assumption expected in older people. Therefore, it is necessary to compare anxiety, stress, depression and PTSD (post-traumatic stress disorder) symptoms in different age groups during the Covid-19 crisis.

Methods
A cross-sectional online survey was performed (from Dec. 2020 to Feb. 2021) on three age groups of elderly, middle-aged and young people. Data were collected by DASS-21 (Depression, Anxiety and Stress Scale) and IES-R (Impact of Event Revised Scale) and analyzed using ANOVA, χ2 test and logistic regression analysis.

Results
Overall, 601 participants completed the questionnaires, including 23.3% of the elderly (≥ 60 years), 29.5% of the young (18–29 years) and 47.3% of the middle-aged (30–59 years) with 71.4% of women. The logistic regression analysis revealed that the risk of PTSD in young people was higher than in the elderly (β = 2.242, CI: 1.03–4.87, P = 0.041), while the risk of depression, anxiety and stress did not differ significantly among the three age groups. Female gender, occupation, lower economic status, solitary life, and chronic disease were risk factors for psychological symptoms during the Covid-19 pandemic.

Conclusion
Findings on the higher odds ratio of PTSD symptoms in younger individuals have interestingly potential implications to meet the needs of mental health services during Covid-19.