bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of Long-COVID in children: a large cohort study
Authors: Hersh Ziv , Weisband Yiska Loewenberg , Bogan Ariel , Leibovich Adir , Obolski Uri , Nevo Daniel , Gilad-Bachrach Ran 
Published: April 2024

Abstract
Background
The impact of long-term Coronavirus disease 2019 (COVID-19) on the pediatric population is still not well understood. This study was designed to estimate the magnitude of COVID-19 long-term morbidity 3–6 months after the date of diagnosis.

Methods
A retrospective study of all Clalit Health Services members in Israel aged 1–16 years who tested positive for SARS-CoV-2 between April 1, 2020 and March 31, 2021. Controls, who had no previous diagnosis of COVID-19, were one-to-one matched to 65,548 COVID-19-positive children and teens, and were assigned the infection dates of their matches as their index date. Matching included age, sex, socio-economic score, and societal sector. Individuals were excluded from the study if they had severe medical conditions before the diagnosis such as cancer, diabetes, chronic respiratory diseases, and/or abnormal physiological development. Generalized Estimating Equations were used to estimate the associations between COVID-19 and the use of medical services. The analysis focused on the 3–6 months after the infection date. Adjustments were made for demographics and for the use of medical services 6–12 and 3–6 months before the infection date. The latter was necessary because of observed disparities in medical service utilization between the groups before the COVID-19 diagnosis, despite the matching process.

Results
Statistically significant differences were only found for referrals for mental health services [adjusted relative-risk (RR) 1·51, 95%CI 1·15 − 1·96; adjusted risk-difference (RD) 0·001, 95%CI 0·0006 − 0·002], and medication prescriptions of any kind (RR 1·03, 95%CI 1·01–1·06; RD 0·01 95%CI 0·004 − 0·02).

Conclusions
The significant increase in medication prescriptions and mental health service referrals support the hypothesis that COVID-19 is associated with long-lasting morbidities in children and adolescents aged 1–16 years. However, the risk difference in both instances was small, suggesting a minor impact on medical services.
The impact of resveratrol on the outcome of the in vitro fertilization: an exploratory randomized placebo-controlled trial
Authors: Conforti A. , Iorio G. G. , Di Girolamo R. , Rovetto M. Y. , Picarelli S. , Cariati F. , Gentile R. , D’Amato A. , Gliozheni O. , Fioretti B. , Alviggi C. 
Published: April 2024

Abstract
Background
Resveratrol is a natural polyphenolic compound present in plants and red wine with many potential health benefits. This compound has various anti-inflammatory and anti-tumor properties and can improve cellular mitochondrial activity. This trial was designed to evaluate the effect on the outcome of IVF of Resveratrol supplementation in women > 35 years with good ovarian reserve (AMH > 1.2 ng/ml). Women were randomized to receive or placebo or Resveratrol (150 mg per day) for three months preceding the ovarian stimulation (OS). All patients were stimulated with a starting dose of recombinant FSH ranging between 150 and 300 IU according to age and ovarian reserve. GnRH antagonist flexible protocol was adopted for pituitary suppression. Triggering was performed with urinary hCG (10.000 IU).

Results
The study was conducted between January 2019 and December 2022 with aa total of 37 cases and 33 controls were recruited. No statistically significant differences in the number of oocytes retrieved, biochemical pregnancy, clinical pregnancy and live birth rates were observed between women treated with resveratrol and control group. A statistically significant increase in the follicle output rate (FORT) and follicle-to oocyte index (FOI) was observed in women treated with resveratrol-based nutraceutical (0.92 versus 0.77 [p = 0.02], and 0.77 versus 0.64 [p = 0.006], respectively).

Conclusions
Preliminary results from this study indicate that pre-treatment with resveratrol may improve ovarian sensitivity to exogenous FSH, which in turn may decrease the risk of hypo-response to OS in advanced reproductive age women.
Benchmarking bioinformatic virus identification tools using real-world metagenomic data across biomes
Authors: Wu Ling-Yi , Wijesekara Yasas , Piedade Gonçalo J. , Pappas Nikolaos , Brussaard Corina P. D. , Dutilh Bas E. 
Published: April 2024

Abstract
Background
As most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs. As all these tools measure different biological signals, and use different algorithms and training and reference databases, it is imperative to conduct an independent benchmarking to give users objective guidance.

Results
We compare the performance of nine state-of-the-art virus identification tools in thirteen modes on eight paired viral and microbial datasets from three distinct biomes, including a new complex dataset from Antarctic coastal waters. The tools have highly variable true positive rates (0–97%) and false positive rates (0–30%). PPR-Meta best distinguishes viral from microbial contigs, followed by DeepVirFinder, VirSorter2, and VIBRANT. Different tools identify different subsets of the benchmarking data and all tools, except for Sourmash, find unique viral contigs. Performance of tools improved with adjusted parameter cutoffs, indicating that adjustment of parameter cutoffs before usage should be considered.

Conclusions
Together, our independent benchmarking facilitates selecting choices of bioinformatic virus identification tools and gives suggestions for parameter adjustments to viromics researchers.
The (cost-)effectiveness of early intervention (MBT-early) versus standard protocolized treatment (CBT) for emerging borderline personality disorder in adolescents (the EARLY study): a study protocol for a randomized controlled trial
Authors: Remeeus Melissa G. A. , Clarke Sharon L. , Feenstra Dine J. , Van Eeren Hester , Smits Maaike L. , Debruyne Sara , Kouijzer Mirjam E. J. , Luyten Patrick , Scholte Ron H. J. , Hutsebaut Joost 
Published: April 2024

Abstract
Background
Although clinical guidelines prioritize the treatment of depression and anxiety in young persons, there is accumulating evidence that the presence of symptoms of borderline personality disorder (BPD) is associated with the limited effectiveness of these standard treatments. These findings stress the need for interventions addressing early-stage BPD in young people with presenting symptoms of anxiety and depressive disorders. The aim of this study is to investigate the (cost-)effectiveness of an early intervention programme for BPD (MBT-early) compared to first-choice psychological treatment for depression and anxiety according to Dutch treatment guidelines (CBT), in adolescents with either depression, anxiety, or both, in combination with early-stage BPD.

Methods
This study is a multi-centre randomized controlled trial. A total of 132 adolescents, presenting with either depression, anxiety, or both and significant BPD features will be randomized to either MBT-early or CBT. The severity of BPD, symptoms of depression and anxiety, personality, social and academic functioning, and quality of life will be assessed at baseline, end of treatment, and at 12-, 18-, and 24-month follow-up, along with medical costs and costs of productivity losses for cost-effectiveness analyses.

Discussion
This study will provide an empirical evaluation of the potential surplus value of early intervention in young people for whom treatment oriented at common mental disorders like anxiety and depression may be insufficient given their underlying personality problems.

Trial registration
Netherlands Trial Register, NL9569. Registered on June 15, 2021.
Early prediction of gestational diabetes mellitus using maternal demographic and clinical risk factors
Authors: Wu Yanqi , Hamelmann Paul , van der Ven Myrthe , Asvadi Sima , van der Hout-van der Jagt M. Beatrijs , Oei S. Guid , Mischi Massimo , Bergmans Jan , Long Xi 
Published: April 2024

Abstract
Objective
To build and validate an early risk prediction model for gestational diabetes mellitus (GDM) based on first-trimester electronic medical records including maternal demographic and clinical risk factors.

Methods
To develop and validate a GDM prediction model, two datasets were used in this retrospective study. One included data of 14,015 pregnant women from Máxima Medical Center (MMC) in the Netherlands. The other was from an open-source database nuMoM2b including data of 10,038 nulliparous pregnant women, collected in the USA. Widely used maternal demographic and clinical risk factors were considered for modeling. A GDM prediction model based on elastic net logistic regression was trained from a subset of the MMC data. Internal validation was performed on the remaining MMC data to evaluate the model performance. For external validation, the prediction model was tested on an external test set from the nuMoM2b dataset.

Results
An area under the receiver-operating-characteristic curve (AUC) of 0.81 was achieved for early prediction of GDM on the MMC test data, comparable to the performance reported in previous studies. While the performance markedly decreased to an AUC of 0.69 when testing the MMC-based model on the external nuMoM2b test data, close to the performance trained and tested on the nuMoM2b dataset only (AUC = 0.70).
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction
Authors: Zhao Xinwei , Xu Junqing , Shui Youyuan , Xu Mengdie , Hu Jie , Liu Xiaoyan , Che Kai , Wang Junjie , Liu Yun 
Published: April 2024

Abstract
Motivation
Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening due to the vast space of potential combinations. Although a number of computational methods for drug synergy prediction have proven successful in narrowing down this space, fusing drug pairs and cell line features effectively still lacks study, hindering current algorithms from understanding the complex interaction between drugs and cell lines.

Results
In this paper, we proposed a Permutable feature fusion network for Drug-Drug Synergy prediction, named PermuteDDS. PermuteDDS takes multiple representations of drugs and cell lines as input and employs a permutable fusion mechanism to combine drug and cell line features. In experiments, PermuteDDS exhibits state-of-the-art performance on two benchmark data sets. Additionally, the results on independent test set grouped by different tissues reveal that PermuteDDS has good generalization performance. We believed that PermuteDDS is an effective and valuable tool for identifying synergistic drug combinations. It is publicly available at https://github.com/littlewei-lazy/PermuteDDS.

Scientific contribution
First, this paper proposes a permutable feature fusion network for predicting drug synergy termed PermuteDDS, which extract diverse information from multiple drug representations and cell line representations. Second, the permutable fusion mechanism combine the drug and cell line features by integrating information of different channels, enabling the utilization of complex relationships between drugs and cell lines. Third, comparative and ablation experiments provide evidence of the efficacy of PermuteDDS in predicting drug-drug synergy.
Performance evaluation of lung sounds classification using deep learning under variable parameters
Authors: Wang Zhaoping , Sun Zhiqiang 
Published: April 2024

AbstractIt is desired to apply deep learning models (DLMs) to assist physicians in distinguishing abnormal/normal lung sounds as quickly as possible. The performance of DLMs depends on feature-related and model-related parameters heavily. In this paper, the relationship between performance and feature-related parameters of a DLM, i.e., convolutional neural network (CNN) is analyzed through experiments. ICBHI 2017 is selected as the lung sounds dataset. The sensitivity analysis of classification performance of the DLM on three parameters, i.e., the length of lung sounds frame, overlap percentage (OP) of successive frames and feature type, is performed. An augmented and balanced dataset is acquired by the way of white noise addition, time stretching and pitch shifting. The spectrogram and mel frequency cepstrum coefficients of lung sounds are used as features to the CNN, respectively. The results of training and test show that there exists significant difference on performance among various parameter combinations. The parameter OP is performance sensitive. The higher OP, the better performance. It is concluded that for fixed sampling frequency 8 kHz, frame size 128, OP 75% and spectrogram feature is optimum under which the performance is relatively better and no extra computation or storage resources are required.
Dyslipidemia and associated factors among adult cardiac patients: a hospital-based comparative cross-sectional study
Authors: Abera Alemayehu , Worede Abebaw , Hirigo Agete Tadewos , Alemayehu Rahel , Ambachew Sintayehu 
Published: April 2024

Abstract
Background
Atherosclerotic vascular diseases are a leading global cause of morbidity and mortality. Dyslipidemia, a major modifiable risk factor for cardiovascular disease, remains poorly understood among adult cardiac patients in in the study area. This study aims to determine the prevalence of dyslipidemia and identify associated factors in this population.

Methods
Hospital-based comparative cross-sectional study was conducted from May to August 2021. A total of 319 participants (153 cardiac cases, 166 healthy controls, aged ≥ 18) were included in the study. Socio-demographic, anthropometric, behavioral, and clinical data were collected using the WHO STEPS survey instrument through systematic sampling. Overnight fasting blood samples were obtained, and serum lipid profiles were analyzed using a COBAS 6000 analyzer. Data were analyzed with SPSS version 20.0, employing bivariable and multivariable logistic regression. Statistical significance was set at p < 0.05.

Results
The overall prevalence of dyslipidemia, encompassing at least one lipid abnormality, was 80.3% among 256 participants. Among cardiac cases, the prevalence rates were as follows: 72.5% for low HDL-cholesterol, 12.4% for hypercholesterolemia, 9.8% for elevated LDL-cholesterol, and 30.1% for hypertriglyceridemia. In controls, corresponding rates were 69.9%, 9.6%, 7.2%, and 32.5%. Significant factors linked to low HDL- cholesterol were female gender (AOR: 2.8, 95% CI 1.7–4.7) and obesity (AOR: 2.8, 95% CI 1.1–7.5). Abdominal obesity was associated with hypercholesterolemia (AOR: 5.2, 95% CI 1.9–14.3) and elevated LDL-cholesterol (AOR: 5.1, 95% CI 1.6–15.8). High blood pressure, overweight, and abdominal obesity were significantly linked to hypertriglyceridemia (p < 0.05).

Conclusion
Dyslipidemia was high among the study participants. Overweight, obesity, central adiposity, and high blood pressure were significantly associated with dyslipidemia in cardiac patients. This alarms the need for lipid profile assessment for patients periodically, with treatment follow-up to monitor any rising patterns and cardiovascular-related risks.
Studying animal locomotion with multiple data loggers: quantifying time drift between tags
Authors: White Connor F. , Lauder George V. 
Published: April 2024

AbstractTemporal accuracy is a fundamental characteristic of logging technology and is needed to correlate data streams. Single biologgers sensing animal movement (accelerometers, gyroscope, magnetometers, collectively inertial measurement unit; IMU) have been extensively used to study the ecology of animals. To better capture whole body movement and increase the accuracy of behavior classification, there is a need to deploy multiple loggers on a single individual to capture the movement of multiple body parts. Yet due to temporal drift, accurately aligning multiple IMU datasets can be problematic, especially as deployment duration increases. In this paper we quantify temporal drift and errors in commercially available IMU data loggers using a combination of robotic and animal borne experiments. The variance in drift rate within a tag is over an order of magnitude lower (σ = 0.001 s h−1) than the variance between tags (σ = 0.015 s·h−1), showing that recording frequency is a characteristic of each tag and not a random variable. Furthermore, we observed a large offset (0.54 ± 0.016 s·h−1) between two groups of tags that had differing recording frequencies, and we observed three instances of instantaneous temporal jumps within datasets introducing errors into the data streams. Finally, we show that relative drift rates can be estimated even when deployed on animals displaying various behaviors without the tags needing to be simultaneously moved. For the tags used in this study, drift rates can vary significantly between tags, are repeatable, and can be accurately measured in the field. The temporal alignment of multiple tag datasets allows researchers to deploy multiple tags on an individual animal which will greatly increase our knowledge of movement kinematics and expand the range of movement characteristics that can be used for behavioral classification.
Complex PTSD symptom clusters and executive function in UK Armed Forces veterans: a cross-sectional study
Authors: Biscoe Natasha , New Emma , Murphy Dominic 
Published: April 2024

Abstract
Background
Less is known about complex posttraumatic stress disorder (CPTSD) than postrraumatic stress disorder (PTSD) in military veterans, yet this population may be at greater risk of the former diagnosis. Executive function impairment has been linked to PTSD treatment outcomes. The current study therefore aimed to explore possible associations between each CPTSD symptom cluster and executive function to understand if similar treatment trajectories might be observed with the disorder.

Methods
A total of 428 veterans from a national charity responded to a self-report questionnaire which measured CPTSD symptom clusters using the International Trauma Questionnaire, and executive function using the Adult Executive Function Inventory. Single and multiple linear regression models were used to analyse the relationship between CPTSD symptom clusters and executive function, including working memory and inhibition.

Results
Each CPTSD symptom cluster was significantly associated with higher executive function impairment, even after controlling for possible mental health confounding variables. Emotion dysregulation was the CPTSD symptom cluster most strongly associated with executive function impairment.

Conclusions
This is the first study to explore the relationship between executive function and CPTSD symptom clusters. The study builds on previous findings and suggests that executive function could be relevant to CPTSD treatment trajectories, as is the case with PTSD alone. Future research should further explore such clinical implications.
The washback of the National Matriculation English Test on senior high school English learning outcomes: do test takers from different provinces think alike?
Authors: Zhang Hao 
Published: April 2024

AbstractThe Chinese National Matriculation English Test (NMET) has a test purpose of producing beneficial washback to promote senior high school English teaching and learning. This article presents a large-scale nationwide survey research on student perceptions of the NMET’s before-test washback on their English learning outcomes in senior high school and the influence of the factor of home province on their views. The research participants were 20,062 first-year undergraduates from 103 universities in the Chinese mainland, and findings showed that the NMET facilitated their senior high school English learning outcomes in the surveyed skills both tested and not tested in the NMET. However, there were noticeable differences between students’ expectations and realities. It was also found that home province was a significant predictor of student perceptions, though the strengths of the relationships varied. Furthermore, in order for more beneficial NMET washback, the students suggested making the NMET speaking and listening subtests mandatory across all provincial regions and administering a nationally unified NMET form. This study calls on future researchers to hold a close lens to the complexity and dynamism of the NMET washback over time and across situations.
Extraction and restoration of scratched murals based on hyperspectral imaging—a case study of murals in the East Wall of the sixth grotto of Yungang Grottoes, Datong, China
Authors: Qiao Kezhen , Hou Miaole , Lyu Shuqiang , Li Lihong 
Published: April 2024

Abstract
Restoring the murals' various kinds of deteriorations is urgently necessary given the growing awareness of the need to protect cultural relics. Virtual restoration starts with an accurate extraction of deterioration. It is challenging to precisely extract scratches from murals because of their intricate information. Hyperspectral images are used to accentuate scratches of mural in this paper. First, a technique for improving information was put forth that involved the transformation of Principal Component Analysis (PCA) and a high-pass filter. Second, by using multi-scale bottom hat transformation, Otsu threshold segmentation, and non-deterioration mask, the deterioration information was extracted from the enhanced result. Third, the morphological transformation and connected component analysis were used to denoise the extracted results. Additionally, the scratched image was repaired using an improved exemplar-based region filling method. The results of deterioration information under different enhancement methods were discussed, and the deterioration extraction method proposed in this paper was contrasted with other deterioration extraction methods. The extraction accuracy was greatly increased by the suggested method. Additionally, we assessed the accuracy of various virtual restoration techniques for image restoration and discovered that our suggested restoration method did a good job of maintaining the structural integrity of the mural's information.
Hyperoxemia and hypoxemia impair cellular oxygenation: a study in healthy volunteers
Authors: Hilderink Bashar N. , Crane Reinier F. , van den Bogaard Bas , Pillay Janesh , Juffermans Nicole P. 
Published: April 2024

Abstract
Introduction
Administration of oxygen therapy is common, yet there is a lack of knowledge on its ability to prevent cellular hypoxia as well as on its potential toxicity. Consequently, the optimal oxygenation targets in clinical practice remain unresolved. The novel PpIX technique measures the mitochondrial oxygen tension in the skin (mitoPO2) which allows for non-invasive investigation on the effect of hypoxemia and hyperoxemia on cellular oxygen availability.

Results
During hypoxemia, SpO2 was 80 (77–83)% and PaO2 45(38–50) mmHg for 15 min. MitoPO2 decreased from 42(35–51) at baseline to 6(4.3–9)mmHg (p < 0.001), despite 16(12–16)% increase in cardiac output which maintained global oxygen delivery (DO2). During hyperoxic breathing, an FiO2 of 40% decreased mitoPO2 to 20 (9–27) mmHg. Cardiac output was unaltered during hyperoxia, but perfused De Backer density was reduced by one-third (p < 0.01). A PaO2 < 100 mmHg and > 200 mmHg were both associated with a reduction in mitoPO2.

Conclusions
Hypoxemia decreases mitoPO2 profoundly, despite complete compensation of global oxygen delivery. In addition, hyperoxemia also decreases mitoPO2, accompanied by a reduction in microcirculatory perfusion. These results suggest that mitoPO2 can be used to titrate oxygen support.