bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of fetal diaphragm excursion and thickness in term pregnancies complicated with pre-gestational and gestational diabetes mellitus
Authors: Acmaz Gokhan , Ozdemir Fatma , Acmaz Banu , Madendağ Yusuf , Madendag Ilknur Çöl , Muderris Iptisam Ipek 
Published: April 2022

Abstract
Background
Both pre-gestational (PGDM) and gestational diabetes mellitus (GDM) make pregnancy complicated. Moreover in the literature GDM and PGDM have been held responsible for respiratory morbidity in newborns. Diaphragm ultrasound (DUS) is a valuable and noninvasive method that provides an opportunity to examine the diaphragmatic morphology and function. This study examined the quality of fetal diaphragmatic contractions in pregnant women complicated with GDM and PGDM.

Methods
A total of 105 volunteers who were separated into three groups; (1) A GDM group (n = 35), (2) a PGDM group (n = 35), and (3) a healthy non-diabetic control group (n = 35). All volunteers with the cephalic presentation and only male fetuses were examined in the 37th week of gestation. This cross sectional and case controlled study was performed at the perinatology clinic of the Erciyes University School of Medicine between 15.01.2020 and 01.08.2021. The thickness of fetal diaphragm (DT), diaphragmatic excursion (DE), diaphragm thickening fraction (DTF) and costodiaphragmatic angle (CDA) was measured and recorded by ultrasound and examined on the video frame during the inspiration and expiration phases of respiration.

Results
Especially the PGDM group represented adversely affected diaphragm function parameters. DT inspiration, DT expiration, DE, CDA inspiration and DTF values were significantly different between PGDM and the control group. Neonatal intensive care unit (NICU) admission was high among babies who were born to pregnancies complicated with PGDM or GDM.

Conclusions
The quality of fetal diaphragm movements is affected in pregnancies complicated with GDM and PGDM. The prolonged duration of diabetes may have additional adverse effects on diaphragm morphology and its function.
Rapid monitoring of flavonoid content in sweet tea (Lithocarpus litseifolius (Hance) Chun) leaves using NIR spectroscopy
Authors: Tian Zhaoxia , Tan Zifeng , Li Yanjie , Yang Zhiling 
Published: April 2022

Abstract
Background
Sweet tea, which functions as tea, sugar and medicine, was listed as a new food resource in 2017. Flavonoids are the main medicinal components in sweet tea and have significant pharmacological activities. Therefore, the quality of sweet tea is related to the content of flavonoids. Flavonoid content in plants is normally determined by time-consuming and expensive chemical analyses. The aim of this study was to develop a methodology to measure three constituents of flavonoids, namely, total flavonoids, phloridin and trilobatin, in sweet tea leaves using near-infrared spectroscopy (NIR).

Results
In this study, we demonstrated that the combination of principal component analysis (PCA) and NIR spectroscopy can distinguish sweet tea from different locations. In addition, different spectral preprocessing methods are used to establish partial least squares (PLS) models between spectral information and the content of the three constituents. The best total flavonoid prediction model was obtained with NIR spectra preprocessed with Savitzky–Golay combined with second derivatives (SG + D2) (RP2 = 0.893, and RMSEP = 0.131). For trilobatin, the model with the best performance was developed with raw NIR spectra (RP2 = 0.902, and RMSEP = 2.993), and for phloridin, the best model was obtained with NIR spectra preprocessed with standard normal variate (SNV) (RP2 = 0.818, and RMSEP = 1.085). The coefficients of determination for all calibration sets, validation sets and prediction sets of the best PLS models were higher than 0.967, 0.858 and 0.818, respectively.

Conclusions
The conclusion indicated that NIR spectroscopy has the ability to determine the flavonoid content of sweet tea quickly and conveniently.
Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology
Authors: Gunashekar Deepa Darshini , Bielak Lars , Hägele Leonard , Oerther Benedict , Benndorf Matthias , Grosu Anca-L. , Brox Thomas , Zamboglou Constantinos , Bock Michael 
Published: April 2022

AbstractAutomatic prostate tumor segmentation is often unable to identify the lesion even if multi-parametric MRI data is used as input, and the segmentation output is difficult to verify due to the lack of clinically established ground truth images. In this work we use an explainable deep learning model to interpret the predictions of a convolutional neural network (CNN) for prostate tumor segmentation. The CNN uses a U-Net architecture which was trained on multi-parametric MRI data from 122 patients to automatically segment the prostate gland and prostate tumor lesions. In addition, co-registered ground truth data from whole mount histopathology images were available in 15 patients that were used as a test set during CNN testing. To be able to interpret the segmentation results of the CNN, heat maps were generated using the Gradient Weighted Class Activation Map (Grad-CAM) method. The CNN achieved a mean Dice Sorensen Coefficient 0.62 and 0.31 for the prostate gland and the tumor lesions -with the radiologist drawn ground truth and 0.32 with whole-mount histology ground truth for tumor lesions. Dice Sorensen Coefficient between CNN predictions and manual segmentations from MRI and histology data were not significantly different. In the prostate the Grad-CAM heat maps could differentiate between tumor and healthy prostate tissue, which indicates that the image information in the tumor was essential for the CNN segmentation.
Tree diet: reducing the treewidth to unlock FPT algorithms in RNA bioinformatics
Authors: Marchand Bertrand , Ponty Yann , Bulteau Laurent 
Published: April 2022

AbstractHard graph problems are ubiquitous in Bioinformatics, inspiring the design of specialized Fixed-Parameter Tractable algorithms, many of which rely on a combination of tree-decomposition and dynamic programming. The time/space complexities of such approaches hinge critically on low values for the treewidth tw of the input graph. In order to extend their scope of applicability, we introduce the Tree-Diet problem, i.e. the removal of a minimal set of edges such that a given tree-decomposition can be slimmed down to a prescribed treewidth $$tw'$$

t

w
′

. Our rationale is that the time gained thanks to a smaller treewidth in a parameterized algorithm compensates the extra post-processing needed to take deleted edges into account. Our core result is an FPT dynamic programming algorithm for Tree-Diet, using $$2^{O(tw)}n$$

2

O
(
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time and space. We complement this result with parameterized complexity lower-bounds for stronger variants (e.g., NP-hardness when $$tw'$$

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or $$tw-tw'$$

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-
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is constant). We propose a prototype implementation for our approach which we apply on difficult instances of selected RNA-based problems: RNA design, sequence-structure alignment, and search of pseudoknotted RNAs in genomes, revealing very encouraging results. This work paves the way for a wider adoption of tree-decomposition-based algorithms in Bioinformatics.
Genome wide noninvasive prenatal testing detects microduplication of the distal end of chromosome 15 in a fetus: a case report
Authors: Sahinbegovic Hana , Andres Stephanie , Langer-Freitag Sabine , Divane Aspasia , Ieremiadou Fotini , Mehmedbasic Senad , Catic Aida 
Published: April 2022

Abstract
Background
Noninvasive prenatal testing (NIPT) is the most recent modality widely used in prenatal diagnostics. Commercially available NIPT has high sensitivity and specificity for the common fetal chromosomal aneuploidies. As future advancements in NIPT sequencing technology are becoming promising and more reliable, the ability to detect beyond aneuploidies and to expand detection of submicroscopic genomic alterations, as well as single-gene disorders might become possible.

Case presentation
Here we present a case of a 34-year-old pregnant woman, G2P1, who had NIPT screening which detected a terminal microduplication of 10.34 Mb on the long arm of chromosome 15 (15q26.1q26.3). Subsequent prenatal diagnostic testing including karyotype, microarray and fluorescence in situ hybridization (FISH) analyses were performed. Microarray testing confirmed and particularized a copy number gain of 10.66 Mb of the distal end of the long arm of chromosome 15. The G-banding cytogenetic studies yielded results consistent with unbalanced translocation between chromosome 15 and 18. To further characterize the abnormality involving the long arm of chromosome 18 and to map the genomic location of the duplicated 15q more precisely, FISH analysis using specific sub-telomeric probes was performed. FISH analysis confirmed that the extra duplicated segment of chromosome 15 is translocated onto the distal end of the long arm of chromosome 18 at band 18q23. Parental karyotype and FISH studies were performed to see if this unbalanced rearrangement was inherited from a healthy balanced translocation carrier versus being a de novo finding. Parental chromosomal analysis provided no evidence of a rearrangement between chromosome 15 and chromosome 18. The final fetal karyotype was reported as 46,XX,der(18)t(15;18)(q26.2;q23)dn.

Conclusions
In this case study, the microduplication of fetal chromosome 15q26.1q26.3 was accurately detected using NIPT. Our results suggest that further refinements in NIPT have the potential to evolve to a powerful and efficient screening method, which might be used to detect a broad range of chromosomal imbalances. Since microduplications and microdeletions are a potential reportable result with NIPT, this must be included in pre-test counseling. Prenatal diagnostic testing of such findings is strongly recommended.
miR-378-mediated glycolytic metabolism enriches the Pax7Hi subpopulation of satellite cells
Authors: Li Hu , Kang Lin , Wu Rimao , Li Changyin , Zhang Qianying , Zhong Ran , Jia Lijing , Zhu Dahai , Zhang Yong 
Published: April 2022

AbstractAdult skeletal muscle stem cells, also known satellite cells (SCs), are a highly heterogeneous population and reside between the basal lamina and the muscle fiber sarcolemma. Myofibers function as an immediate niche to support SC self-renewal and activation during muscle growth and regeneration. Herein, we demonstrate that microRNA 378 (miR-378) regulates glycolytic metabolism in skeletal muscle fibers, as evidenced by analysis of myofiber-specific miR-378 transgenic mice (TG). Subsequently, we evaluate SC function and muscle regeneration using miR-378 TG mice. We demonstrate that miR-378 TG mice significantly attenuate muscle regeneration because of the delayed activation and differentiation of SCs. Furthermore, we show that the miR-378-mediated metabolic switch enriches Pax7HiSCs, accounting for impaired muscle regeneration in miR-378 TG mice. Mechanistically, our data suggest that miR-378 targets the Akt1/FoxO1 pathway, which contributes the enrichment of Pax7HiSCs in miR-378 TG mice. Together, our findings indicate that miR-378 is a target that links fiber metabolism to muscle stem cell heterogeneity and provide a genetic model to approve the metabolic niche role of myofibers in regulating muscle stem cell behavior and function.
The analysis of financial market risk based on machine learning and particle swarm optimization algorithm
Authors: Liu Tao , Yu Zhongyang 
Published: April 2022

AbstractThe financial industry is a key to promoting the development of the national economy, and the risk it takes is also the largest hidden risk in the financial market. Therefore, the risk existing in the current financial market should be deeply explored under blockchain technology (BT) to ensure the functions of financial markets. The risk of financial markets is analyzed using machine learning (ML) and random forest (RF). First, the clustering method is introduced, and an example is given to illustrate the RF classification model. The collected data sets are divided into test sets and training sets, the corresponding rules are formulated and generated, and the branches of the decision tree (DT) are constructed according to the optimization principle. Finally, the steps of constructing the branches of DT are repeated until they are not continued. The results show that the three major industries of the regional economy account for 3.5%, 51.8%, 3.2%, 3.4%, and 3.8% of the regional GDP, respectively, the secondary industry makes up 44.5%, 43%, 45.1%, 44.8%, and 43.6%, respectively, and the tertiary industry occupies 20%, 3.7%, 52.3%, 52.9%, 54%, and 54.6%, respectively. This shows that with the development of the industrial structure under BT, the economic subject gradually shifts from the primary industry to the tertiary industry; BT can improve the efficiency of the financial industry and reduce operating costs and dependence on media. Meanwhile, the financial features of BT can provide a good platform for business expansion. The application of BT to the supply chain gives a theoretical reference for promoting the synergy between companies.
Epidemiology of Campylobacter infections among children of 0–24 months of age in South Africa
Authors: Samie Amidou , Moropeng Resoketswe Charlotte , Tanih Nicoline Fri , Dillingham Rebecca , Guerrant Richard , Bessong Pascal Obong 
Published: April 2022

Abstract
Background
Campylobacter spp. are one of the most frequent causes of diarrhoeal disease in humans throughout the world. This study aimed at determining the prevalence and the genotypic distribution of Campylobacter spp. and their association with diarrhoea and child growth in children of less than the age of two in the Limpopo Province of South Africa.

Methods
A total of 4280 diarrheal and non-diarrheal stool samples were collected on a monthly basis from children recruited at birth and followed up to 24 months. All stool samples were screened for the presence Campylobacter antigen using ELISA technique after which CAH 16S primer was used on the positive samples to confirm the presence of Campylobacter. Subsequently, the PCR positive samples were further characterised using species specific primers for Campylobacter jejuni and Campylobacter coli.

Results
Campylobacter antigen was detected in 564/4280 (13.2%). Campylobacter was more commonly found in diarrheal stools (20.4%) compared to non-diarrheal stools (12.4%) with a statistically significant difference (χ2 = 7.345; p = 0.006). Throughout the year there were two main peaks of Campylobacter infection one in December- January and the second peak in June. The prevalence of Campylobacter increased with the age of the children up to 11 months after which the prevalence decreased. Out of 564 positive ELISA samples, 257 (45.6%) were confirmed to have 16S rRNA gene for Campylobacter spp. Furthermore, C. jejuni was found to be more prevalent (232/257) than C. coli (25/257) with a prevalence of 90.3% and 9.7%, respectively. Both C. jejuni and C. coli were significantly associated with diarrhea with statistical values of (χ2 = 22.224; p < 0.001) and (χ2 = 81.682; p < 0.001) respectively. Sequences generated from the analysis of hip gene confirmed the PCR positives samples were C. jejuni positive.

Conclusions
This study has delineated a high prevalence of Campylobacter spp. in the study cohort. Moreover, C. jejuni was found to be more prevalent than C. coli both of which were associated with diarrhea. These findings are of clinical and epidemiological significance.
Household expenditure on non-Covid hospitalisation care during the Covid-19 pandemic and the role of financial protection policies in India
Authors: Garg Samir , Bebarta Kirtti Kumar , Tripathi Narayan 
Published: April 2022

Abstract
Background
Despite global guidance for maintaining essential non-Covid health services during the pandemic, there is a concern that existing services faced a major disruption. The access as well as affordability of healthcare could have suffered during the pandemic, especially in developing countries including India. There are no population based studies available in India on changes in access and financial risk for non-Covid hospitalisation during the pandemic. India has a policy of Publicly Funded Health Insurance (PFHI) to ensure access and financial protection for hospital care but no information is available on its performance during the pandemic. The current study was aimed to find out the change in access and financial protection for non-Covid hospitalisations during the Covid-19 pandemic and to examine the performance of PFHI in this context.

Methods
Panel data was analyzed, from two rounds of annual household surveys conducted in Chhattisgarh state for year 2019 and 2020. The survey followed a two-stage population based sample of around 3000 households, representative for the state. Two kinds of measures of catastrophic health expenditure were used – based on annual household consumption expenditure and on non-food consumption expenditure. Multivariate analysis was carried out to find determinants of utilisation and spending. In addition, Propensity Score Matching method was applied to find effect of PFHI schemes.

Results
Utilisation of hospital care per 1000 population reduced from 58.2 in 2019 to 36.6 during the pandemic i.e. in 2020. The share of public hospitals in utilisation increased from 60.1% in 2019 to 67.0% in 2020. Incidence of catastrophic expenditure was significantly greater during the pandemic. The median Out of Pocket Expenditure (OOPE) in private hospitals doubled from 2019 to 2020. The size of OOPE and occurrence of catastrophic expenditure were significantly associated with utilisation in private hospitals. Enrolment under PFHI schemes including the Ayushman Bharat-Pradhan Mantri Jan Arogaya Yojana (PMJAY) was not effective in reducing OOPE or catastrophic expenditure.

Conclusion
While the utilisation of hospital care dropped during the pandemic, the private hospitals became further unaffordable. The government policy for financial protection through health insurance remained ineffective during the pandemic.
A 1-year cross-sectional study on the predominance of influenza among hospitalized children in a tropical area, Kota Kinabalu, Sabah
Authors: Lim Kai Joo , John Jecelyn Leaslie , Rahim Syed Sharizman Syed Abdul , Avoi Richard , Hassan Mohd Rohaizat , Jeffree Mohammad Saffree , Ibrahim Mohd Yusof , Ahmed Kamruddin 
Published: April 2022

Abstract
Background
Children are at higher risk of influenza virus infection, and it is difficult to diagnose. They are also responsible for the transmission of influenza because of their longer viral shedding compared to adults. In Malaysia, studies on influenza in children are scarce, and as a result, policy decisions cannot be formulated to control the infection. Hence, the objective of this study is to determine the prevalence and epidemiological characteristics of influenza among children with upper respiratory symptoms in the Sabah state of Malaysia.

Methods
A cross-sectional study with a simple random sampling was conducted among children with upper respiratory symptoms in Sabah from 1 March 2019 to 29 February 2020. Patients admitted to a pediatric ward of Sabah Women and Children’s Hospital who presented with a fever >38 °C and cough within 48 h of admission were enrolled in this study. A nasopharyngeal swab was taken, and influenza was diagnosed by lateral flow test. Clinical features of influenza-positive children were compared with children whose results were negative.

Results
A total of 323 nasopharyngeal samples were collected, and 66 (20.4%) of them were positive for influenza. Fifty-six (85%) were infected by influenza A whereas ten (15%) were by influenza B virus. Higher temperature (aOR 2.03, 95% CI 1.296–3.181), less activity (aOR 2.07, 95% CI 1.158–3.693), and seizure (aOR 4.2, 95% CI 1.614–10.978) on admission were significant risk factors associated with influenza in children. Meteorology parameters such as humidity and rainfall amount were statistically significant at 95% CI [1.133 (1.024–1.255)] and 95% CI [0.946 (0.907–0.986)].

Conclusion
The prevalence of influenza was high among children with upper respiratory symptoms, and they were infected predominantly with the influenza A virus. Children presented with seizures, less activity, and fever were the significant risk factors for influenza. Influenza vaccination should be prioritized as preventive measures for children.
Single-nucleotide polymorphisms as important risk factors of diabetes among Middle East population
Authors: Akhlaghipour Iman , Bina Amir Reza , Mogharrabi Mohammad Reza , Fanoodi Ali , Ebrahimian Amir Reza , Khojasteh Kaffash Soroush , Babazadeh Baghan Atefeh , Khorashadizadeh Mohammad Erfan , Taghehchian Negin , Moghbeli Meysam 
Published: April 2022

AbstractDiabetes is a chronic metabolic disorder that leads to the dysfunction of various tissues and organs, including eyes, kidneys, and cardiovascular system. According to the World Health Organization, diabetes prevalence is 8.8% globally among whom about 90% of cases are type 2 diabetes. There are not any significant clinical manifestations in the primary stages of diabetes. Therefore, screening can be an efficient way to reduce the diabetic complications. Over the recent decades, the prevalence of diabetes has increased alarmingly among the Middle East population, which has imposed exorbitant costs on the health care system in this region. Given that the genetic changes are among the important risk factors associated with predisposing people to diabetes, we examined the role of single-nucleotide polymorphisms (SNPs) in the pathogenesis of diabetes among Middle East population. In the present review, we assessed the molecular pathology of diabetes in the Middle East population that paves the way for introducing an efficient SNP-based diagnostic panel for diabetes screening among the Middle East population. Since, the Middle East has a population of 370 million people; the current review can be a reliable model for the introduction of SNP-based diagnostic panels in other populations and countries around the world.
Demographic biases and assessment fairness in classroom: insights from Iranian university teachers
Authors: Rezai Afsheen , Namaziandost Ehsan , Miri Mowla , Kumar Tribhuwan 
Published: April 2022

AbstractThe literature indicates that the effects of sources of demographic biases on fairness in classroom assessment (CA) are under-researched in the Iranian higher education context. Hence, this study aims to explore the Iranian university teachers’ perceptions of the effects of demographic biases (e.g., gender, ethnicity, and socioeconomic (SES)) on their assessment fairness. With this aim, fifteen university teachers were selected using a criterion sampling method at Ayatollah Borujerdi University, Iran. To gather the required data, a reflective written statement was completed by the participants. The participants’ responses were translated verbatim into English and subjected to a standard thematic coding analysis. Findings yielded three recurring themes: ‘gender bias is prevalent in assessment practices’, ethnicity bias affects adversely assessment practices, and ‘SES bias jeopardizes fairness in assessment practices’. The results evidenced that gender, ethnicity, and SES biases can act as a major source of score pollution in CA. This study ends with proposing a range of implications for different testing stakeholders.