bluuebunny/crossref_metadata_2025_split huggingface dataset:
A MATLAB-based app to improve LC–MS/MS data analysis for N-linked glycan peak identification
Authors: Dhingra Ashna , Schaeffer Zayla , Majewska Nepomuceno Natalia I. , Au Jennifer , Ahn Joomi 
Published: June 2023

Abstract
Background
Glycosylation is an important modification to proteins that plays a significant role in biological processes. Glycan structures are characterized by liquid chromatography (LC) combined with mass spectrometry (MS), but data interpretation of LC/MS and MS/MS data can be time-consuming and arduous when analyzed manually. Most of glycan analysis requires dedicated glycobioinformatics tools to process MS data, identify glycan structure, and display the results. However, software tools currently available are either too costly or heavily focused on academic applications, limiting their use within the biopharmaceutical industry for implementing the standardized LC/MS glycan analysis in high-throughput manner. Additionally, few tools provide the capability to generate report-ready annotated MS/MS glycan spectra.

Results
Here, we present a MATLAB-based app, GlyKAn AZ, which can automate data processing, glycan identification, and customizable result displays in a streamlined workflow. MS1 and MS2 mass search algorithms along with glycan databases were developed to confirm the fluorescent labeled N-linked glycan species based on accurate mass. A user-friendly graphical user interface (GUI) streamlines the data analysis process, making it easy to implement the software tool in biopharmaceutical analytical laboratories. The databases provided with the app can be expanded through the Fragment Generator functionality which automatically identifies fragmentation patterns for new glycans. The GlyKAn AZ app can automatically annotate the MS/MS spectra, yet this data display feature remains flexible and customizable by users, saving analysts’ time in generating individual report-ready spectra figures. This app accepts both OrbiTrap and matrix-assisted laser desorption/ionization–time of flight (MALDI–TOF) MS data and was successfully validated by identifying all glycan species that were previously identified manually.

Conclusions
The GlyKAn AZ app was developed to expedite glycan analysis while maintaining a high level of accuracy in positive identifications. The app’s customizable user inputs, polished figures and tables, and unique calculated outputs set it apart from similar software and greatly improve the current manual analysis workflow. Overall, this app serves as a tool for streamlining glycan identification for both academic and industrial needs.
Covariance regression with random forests
Authors: Alakus Cansu , Larocque Denis , Labbe Aurélie 
Published: June 2023

AbstractCapturing the conditional covariances or correlations among the elements of a multivariate response vector based on covariates is important to various fields including neuroscience, epidemiology and biomedicine. We propose a new method called Covariance Regression with Random Forests (CovRegRF) to estimate the covariance matrix of a multivariate response given a set of covariates, using a random forest framework. Random forest trees are built with a splitting rule specially designed to maximize the difference between the sample covariance matrix estimates of the child nodes. We also propose a significance test for the partial effect of a subset of covariates. We evaluate the performance of the proposed method and significance test through a simulation study which shows that the proposed method provides accurate covariance matrix estimates and that the Type-1 error is well controlled. An application of the proposed method to thyroid disease data is also presented. is implemented in a freely available R package on CRAN.
Exploration of m6A methylation regulators as epigenetic targets for immunotherapy in advanced sepsis
Authors: Qian Weiwei , Zhou Jian , Shou Songtao 
Published: June 2023

Abstract
Background
This study aims to deeply explore the relationship between m6A methylation modification and peripheral immune cells in patients with advanced sepsis and mine potential epigenetic therapeutic targets by analyzing the differential expression patterns of m6A-related genes in healthy subjects and advanced sepsis patients.

Methods
A single cell expression dataset of peripheral immune cells containing blood samples from 4 patients with advanced sepsis and 5 healthy subjects was obtained from the gene expression comprehensive database (GSE175453). Differential expression analysis and cluster analysis were performed on 21 m6A-related genes. The characteristic gene was identified based on random forest algorithm, and the correlation between the characteristic gene METTL16 and 23 immune cells in patients with advanced sepsis was evaluated using single-sample gene set enrichment analysis.

Results
IGFBP1, IGFBP2, IGF2BP1, and WTAP were highly expressed in patients with advanced sepsis and m6A cluster B. IGFBP1, IGFBP2, and IGF2BP1 were positively correlated with Th17 helper T cells. The characteristic gene METTL16 exhibited a significant positive correlation with the proportion of various immune cells.

Conclusion
IGFBP1, IGFBP2, IGF2BP1, WTAP, and METTL16 may accelerate the development of advanced sepsis by regulating m6A methylation modification and promoting immune cell infiltration. The discovery of these characteristic genes related to advanced sepsis provides potential therapeutic targets for the diagnosis and treatment of sepsis.
Expanding the application of haplotype-based genomic predictions to the wild: A case of antibody response against Teladorsagia circumcincta in Soay sheep
Authors: Vahedi Seyed Milad , Salek Ardetani Siavash , Brito Luiz F. , Karimi Karim , Pahlavan Afshari Kian , Banabazi Mohammad Hossein 
Published: June 2023

Abstract
Background
Genomic prediction of breeding values (GP) has been adopted in evolutionary genomic studies to uncover microevolutionary processes of wild populations or improve captive breeding strategies. While recent evolutionary studies applied GP with individual single nucleotide polymorphism (SNP), haplotype-based GP could outperform individual SNP predictions through better capturing the linkage disequilibrium (LD) between the SNP and quantitative trait loci (QTL). This study aimed to evaluate the accuracy and bias of haplotype-based GP of immunoglobulin (Ig) A (IgA), IgE, and IgG against Teladorsagia circumcincta in lambs of an unmanaged sheep population (Soay breed) based on Genomic Best Linear Unbiased Prediction (GBLUP) and five Bayesian [BayesA, BayesB, BayesCπ, Bayesian Lasso (BayesL), and BayesR] methods.

Results
The accuracy and bias of GPs using SNP, haplotypic pseudo-SNP from blocks with different LD thresholds (0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.00), or the combinations of pseudo-SNPs and non-LD clustered SNPs were obtained. Across methods and marker sets, higher ranges of genomic estimated breeding values (GEBV) accuracies were observed for IgA (0.20 to 0.49), followed by IgE (0.08 to 0.20) and IgG (0.05 to 0.14). Considering the methods evaluated, up to 8% gains in GP accuracy of IgG were achieved using pseudo-SNPs compared to SNPs. Up to 3% gain in GP accuracy for IgA was also obtained using the combinations of the pseudo-SNPs with non-clustered SNPs in comparison to fitting individual SNP. No improvement in GP accuracy of IgE was observed using haplotypic pseudo-SNPs or their combination with non-clustered SNPs compared to individual SNP. Bayesian methods outperformed GBLUP for all traits. Most scenarios yielded lower accuracies for all traits with an increased LD threshold. GP models using haplotypic pseudo-SNPs predicted less-biased GEBVs mainly for IgG. For this trait, lower bias was observed with higher LD thresholds, whereas no distinct trend was observed for other traits with changes in LD.

Conclusions
Haplotype information improves GP performance of anti-helminthic antibody traits of IgA and IgG compared to fitting individual SNP. The observed gains in the predictive performances indicate that haplotype-based methods could benefit GP of some traits in wild animal populations.
Risk of cardiovascular disease in lean patients with nonalcoholic fatty liver disease
Authors: Ishido Shun , Tamaki Nobuharu , Takahashi Yuka , Uchihara Naoki , Suzuki Keito , Tanaka Yuki , Miyamoto Haruka , Yamada Michiko , Matsumoto Hiroaki , Nobusawa Tsubasa , Keitoku Taisei , Takaura Kenta , Tanaka Shohei , Maeyashiki Chiaki , Yasui Yutaka , Tsuchiya Kaoru , Nakanishi Hiroyuki , Kurosaki Masayuki , Izumi Namiki 
Published: June 2023

Abstract
Background
Patients with nonalcoholic fatty liver disease (NAFLD) are highly at risk for cardiovascular disease (CVD). However, the risk of developing CVD in patients with lean NAFLD is not yet fully understood. Therefore, this study aimed to compare the CVD incidence in Japanese patients with lean NAFLD and those with non-lean NAFLD.

Methods
A total of 581 patients with NAFLD (219 with lean and 362 with non-lean NAFLD) were recruited. All patients underwent annual health checkups for at least 3 years, and CVD incidence was investigated during follow-up. The primary end-point was CVD incidence at 3 years.

Results
The 3-year new CVD incidence rates in patients with lean and non-lean NAFLD were 2.3% and 3.9%, respectively, and there was no significant difference between two groups (p = 0.3). Multivariable analysis adjusted for age, sex, hypertension, diabetes, and lean NAFLD/non-lean NAFLD revealed that age (every 10 years) as an independent factor associated with CVD incidence with an odds ratio (OR) of 2.0 (95% confidence interval [CI]: 1.3–3.4), whereas lean NAFLD was not associated with CVD incidence (OR: 0.6; 95% CI: 0.2–1.9).

Conclusions
CVD incidence was comparable between patients with lean NAFLD and those with non-lean NAFLD. Therefore, CVD prevention is needed even in patients with lean NAFLD.
A pilot study of Kangaroo mother care in early essential newborn care in resource-limited areas of China: the facilitators and barriers to implementation
Authors: Wang Wen , Wang Yinghang , Zhang Hanxiyue , Yang Ge , Lin Yun , Wang Chenran , Huang Xiaona , Tian Xiaobo , Xiao Angela Y. , Xu Tao , Tang Kun 
Published: June 2023

Abstract
Background
Implementation of Kangaroo Mother Care (KMC) in resource-limited areas of China may face unique barriers, such as a lack of resources, geographic location and more traditional culture among others. This qualitative study analyses the facilitators and barriers to implementing KMC in county-level health facilities in resource-limited areas of China for the promotion of KMC on a larger scale.

Methods
Participants from 4 of the 18 pilot counties where early essential newborn care was implemented through the Safe Neonatal Project and 4 control counties not enrolled in Safe Neonatal Project were selected using purposive sampling. A total of 155 participants were interviewed, including stakeholders of the Safe Neonatal Project such as national maternal health experts, relevant government officials and medical staff. Thematic analysis was used to process and analyse the interview content in order to summarise the facilitators and barriers to implementing KMC.

Results
KMC was accepted in the pilot areas but still faced certain challenges due to institutional regulation, resource provision and the perceptions of health staff, postpartum mothers and their families as well as COVID-19 prevention and control regulations. The facilitators identified were government officials and medical staff acceptance and the incorporation of KMC into routine clinical care. The barriers identified were a lack of dedicated funding and other resources, the present scope of health insurance and KMC cost-sharing mechanism, providers’ knowledge and practical abilities, parental awareness, postpartum discomfort, fathers’ inadequate involvement, and the impact from COVID-19.

Conclusion
The Safe Neonatal Project pilot experience indicated the feasibility of implementing KMC in more areas of China. Optimising institutional regulations, providing necessary supporting resources and enhancing education and training may help to refine the implementation and scale-up of KMC practice in China.
Post-cesarean section laparoscopic cholecystectomy: a case report
Authors: Abdelmohsen Sarah Magdy , Zidan Mohamed Mahmoud , Fahmy Sherif Salah Eldeen , Baghdady Ahmed Saleh 
Published: June 2023

Abstract
Background
Laparoscopic cholecystectomy at the time of cesarean section is novel in medicine. It is safe, feasible, and cost-effective.

Case presentation
A 29-year-old G3P2 + 0 woman had two previous cesarean sections. She was pregnant at 32 weeks. The fetus had anencephaly. She had acute cholecystitis. Laparoscopic cholecystectomy done at the time of termination of pregnancy by cesarean section.

Conclusions
In a critical period, such as acute cholecystitis, the combination of laparoscopic cholecystectomy immediately post cesarean section is effective if the surgeon is highly qualified and experienced.
Watermelon and dietary advice compared to dietary advice alone following hospitalization for hyperemesis gravidarum: a randomized controlled trial
Authors: Tan Peng Chiong , Ramasandran Gayaithiri , Sethi Neha , Razali Nuguelis , Hamdan Mukhri , Kamarudin Maherah 
Published: June 2023

Abstract
Background
Hyperemesis gravidarum (HG) affects about 2% of pregnancies and is at the severe end of the spectrum of nausea and vomiting of pregnancy. HG causes severe maternal distress and results in adverse pregnancy outcomes long after the condition may have dissipated. Although dietary advice is a common tool in management, trial evidence to base the advice on is lacking.

Methods
A randomized trial was conducted in a university hospital from May 2019 to December 2020. 128 women at their discharge following hospitalization for HG were randomized: 64 to watermelon and 64 to control arm. Women were randomized to consume watermelon and to heed the advice leaflet or to heed the dietary advice leaflet alone. A personal weighing scale and a weighing protocol were provided to all participants to take home. Primary outcomes were bodyweight change at the end of week 1 and week 2 compared to hospital discharge.

Results
Weight change (kg) at end of week 1, median[interquartile range] -0.05[-0.775 to + 0.50] vs. -0.5[-1.4 to + 0.1] P = 0.014 and to the end of week 2, + 0.25[-0.65 to + 0.975] vs. -0.5[-1.3 to + 0.2] P = 0.001 for watermelon and control arms respectively. After two weeks, HG symptoms assessed by PUQE-24 (Pregnancy-Unique Quantification of Emesis and Nausea over 24 h), appetite assessed by SNAQ (Simplified Nutritional Appetite Questionnaire), wellbeing and satisfaction with allocated intervention NRS (0–10 numerical rating scale) scores, and recommendation of allocated intervention to a friend rate were all significantly better in the watermelon arm. However, rehospitalization for HG and antiemetic usage were not significantly different.

Conclusion
Adding watermelon to the diet after hospital discharge for HG improves bodyweight, HG symptoms, appetite, wellbeing and satisfaction.

Trial registration
This study was registered with the center’s Medical Ethics Committee (on 21/05/2019; reference number 2019327–7262) and the ISRCTN on 24/05/2019 with trial identification number: ISRCTN96125404. First participant was recruited on 31/05/ 2019.
Development of a blood proteins-based model for bronchopulmonary dysplasia prediction in premature infants
Authors: Ou Wanting , Lei KeJing , Wang Huanhuan , Ma Hongmei , Deng Xiaojuan , He Pengcheng , Zhao Liping , Lv Youdao , Tang Guohong , Zhang Benjin , Li Jie 
Published: June 2023

AbstractBackgroundBronchopulmonary dysplasia (BPD) is the most common chronic pulmonary disease in premature infants. Blood proteins may be early predictors of the development of this disease.MethodsIn this study, protein expression profiles (blood samples during their first week of life) and clinical data of the GSE121097 was downloaded from the Gene Expression Omnibus. Weighted gene co-expression network analysis (WGCNA) and differential protein analysis were carried out for variable dimensionality reduction and feature selection. Least absolute shrinkage and selection operator (LASSO) were conducted for BPD prediction model development. The performance of the model was evaluated by the receiver operating characteristic (ROC) curve, calibration curve, and decision curve.ResultsThe results showed that black module, magenta module and turquoise module, which included 270 proteins, were significantly correlated with the occurrence of BPD. 59 proteins overlapped between differential analysis results and above three modules. These proteins were significantly enriched in 253 GO terms and 11 KEGG signaling pathways. Then, 59 proteins were reduced to 8 proteins by LASSO analysis in the training cohort. The proteins model showed good BPD predictive performance, with an AUC of 1.00 (95% CI 0.99-1.00) and 0.96 (95% CI 0.90-1.00) in training cohort and test cohort, respectively.ConclusionOur study established a reliable blood-protein based model for early prediction of BPD in premature infants. This may help elucidate pathways to target in lessening the burden or severity of BPD.
Diagnosis of Epstein-Barr and cytomegalovirus infections using decision trees: an effective way to avoid antibiotic overuse in paediatric tonsillopharyngitis
Authors: Takács Andrea Tímea , Bukva Mátyás , Bereczki Csaba , Burián Katalin , Terhes Gabriella 
Published: June 2023

Abstract
Background
The incidence of tonsillopharyngitis is especially prevalent in children. Despite the fact that viruses cause the majority of infections, antibiotics are frequently used as a treatment, contrary to international guidelines. This is not only an inappropriate method of treatment for viral infections, but it also significantly contributes to the emergence of antibiotic-resistant strains. In this study, EBV and CMV-related tonsillopharyngitis were distinguished from other pathogens by using machine learning techniques to construct a classification tree based on clinical characteristics.

Materials and methods
In 2016 and 2017, we assessed information regarding 242 children with tonsillopharyngitis. Patients were categorized according to whether acute cytomegalovirus or Epstein-Barr virus infections were confirmed (n = 91) or not (n = 151). Based on symptoms and blood test parameters, we constructed decision trees to discriminate the two groups. The classification efficiency of the model was characterized by its sensitivity, specificity, positive predictive value, and negative predictive value. Fisher’s exact and Welch’s tests were used to perform univariable statistical analyses.

Results
The best decision tree distinguished EBV/CMV infection from non-EBV/CMV group with 83.33% positive predictive value, 88.90% sensitivity and 90.30% specificity. GPT (U/l) was found to be the most discriminatory variable (p < 0.0001). Using the model, unnecessary antibiotic treatment could be reduced by 66.66% (p = 0.0002).

Discussion
Our classification model can be used as a diagnostic decision support tool to distinguish EBC/CMV infection from non EBV/CMV tonsillopharyngitis, thereby significantly reducing the overuse of antibiotics. It is hoped that the model may become a tool worth considering in routine clinical practice and may be developed to differentiate between viral and bacterial infections.
Predictors of adverse short-term outcomes in late preterm infants
Authors: Mekic Nina , Selimovic Amela , Cosickic Almira , Mehmedovic Majda , Hadzic Devleta , Zulic Evlijana , Mustafic Sehveta , Serak Amra 
Published: June 2023

Abstract
Background
Infants born between 34 weeks and 36 weeks and 6 days of gestation are defined as late preterm infants (LPIs), and they account for approximately 74% of all premature births. Preterm birth (PB) remains the leading cause of infant mortality and morbidity worldwide.

Aim
To analyse short-term morbidity and mortality and identify predictors of adverse outcomes in late preterm infants.

Patients and methods
In this retrospective study, we evaluated adverse short-term outcomes of LPIs admitted to the Intensive Care Unit (ICU), Clinic for Children’s Diseases, University Clinical Center Tuzla, between 01.01.2020 and 31.12.2022. The analysed data included sex, gestational age, parity, birth weight, Apgar score (i.e., assessment of vitality at birth in the first and fifth minutes after birth), and length of hospitalization in NICU, as well as short-term outcome data. Maternal risk factors we observed were: age of mother, parity, maternal morbidity during pregnancy, complications and treatment during pregnancy. LPIs with major anatomic malformations were excluded from the study. Logistic regression analysis was used to identify risk factors for neonatal morbidity among LPIs.

Results
We analysed data from 154 late preterm newborns, most of whom were male (60%), delivered by caesarean Sect. (68.2%) and from nulliparous mothers (63.6%). Respiratory complications were the most common outcome among all subgroups, followed by CNS morbidity, infections and jaundice requiring phototherapy. The rate of almost all of the complications in the late-preterm group decreased as gestational age increased from 34 to 36 weeks. Birth weight (OR: 1,2; 95% CI: 0,9 − 2,3; p = 0,0313) and male sex (OR: 2,5; 95% CI: 1,1–5,4; p = 0,0204) were significantly and independently associated with an increased risk for respiratory morbidity, and gestational weeks and male sex were associated with infectious morbidity. None of the risk factors analysed herein were predictors of CNS morbidity in LPIs.

Conclusion
A younger gestational age at birth is associated with a greater risk of short-term complications among LPIs, thus highlighting the need for increased knowledge about the epidemiology of these late preterm births. Understanding the risks of late preterm birth is critical to optimizing clinical decision-making, enhancing the cost-effectiveness of endeavours to delay delivery during the late preterm period, and reducing neonatal morbidity.
A 9-year-old boy with a nonmalignant forehead tumor – a rare case of pediatric Pott’s puffy tumor
Authors: Amstrup Jesper , Penning Lasse Wedege , Hansen Jonas Kjeldbjerg , Brix Ninna , Andersen Graziella 
Published: June 2023

Abstract
Background
Pott’s puffy tumor (PPT) is a rare and potentially deadly complication of frontal sinusitis consisting of subperiosteal abscess and osteomyelitis of the frontal bone.

Case presentation
We report the case of a 9-year-old boy who presented with fever and soft tissue swelling of the forehead. Magnetic resonance imaging (MRI) depicted an abscess in the subcutaneous tissue frontally and an epidural empyema, while a cranial computed tomography (CT) scan revealed bone erosion as a sign of osteomyelitis. The patient was treated accordingly.

Conclusions
This rare condition is essential to keep in mind as it needs a multidisciplinary approach and relevant imaging to start proper treatment and thus decrease the risk of intracranial complications.