bluuebunny/crossref_metadata_2025_split huggingface dataset:
On Rotation Distance of Rank Bounded Trees
Authors: Anoop S.K.M. , Sarma Jayalal 
Published: May 2024

Computing the rotation distance between two binary trees with n internal nodes efficiently (in poly( n) time) is a long standing open question in the study of height balancing in tree data structures. In this paper, we initiate the study of this problem bounding the rank of the trees given at the input (defined in [1] in the context of decision trees). We define the rank-bounded rotation distance between two given full binary trees T1 and T2 (with n internal nodes) of rank at most r = max{rank( T1), rank( T2)}, denoted by dR( T1, T2), as the length of the shortest sequence of rotations that transforms T1 to T2 with the restriction that the intermediate trees must be of rank at most r. We show that the rotation distance problem reduces in polynomial time to the rank bounded rotation distance problem. This motivates the study of the problem in the combinatorial and algorithmic frontiers. Observing that trees with rank 1 coincide exactly with skew trees (full binary trees where every internal node has at least one leaf as a child), we show the following results in this frontier: We present an O( n2) time algorithm for computing dR( T1, T2). That is, when the given full binary trees are skew trees (we call this variant the skew rotation distance problem) - where the intermediate trees are restricted to be skew as well. In particular, our techniques imply that for any two skew trees dR( T1, T2) ≤ n2. We show the following upper bound: for any two full binary trees T1 and T2 of rank r1 and r2 respectively, we have that: dR( T1, T2) ≤ n2(1 + (2 n + 1)( r1 + r2 – 2)) where r = max{ r1, r2}. This bound is asymptotically tight for r = 1. En route to our proof of the above theorems, we associate full binary trees to permutations and relate the rotation operation on trees to transpositions in the corresponding permutations. We give exact combinatorial characterizations of permutations that correspond to full binary trees and full skew binary trees under this association. We also precisely characterize the transpositions that correspond to the set of rotations in full binary trees. We also study bi-variate polynomials associated with binary trees (introduced by [2]), and show characterizations and algorithms for computing rotation distances for the case of full skew trees using them.
Evaluation of the quality of Internet information on masseter botox injection for bruxism
Authors: Terzi Mithat , Buyuk Suleyman Kutalmış , Akdemir Hale 
Published: May 2024

BACKGROUND: Botulinum toxin, commonly referred to as botox, is frequently used in facial aesthetics, but also has therapeutic applications in various medical and surgical conditions such as bruxism treatment. OBJECTIVE: The aim of this research is to evaluate the information quality of only English resources available on the Internet regarding the use of botulinum toxin in the treatment of bruxism. METHODS: The terms “Botox + Tooth Grinding” selected for this study were searched on the Internet using the Google Search Engine, and the URLs of the top 150 websites containing only English pages were recorded and examined. The websites were assessed using DISCERN tools, the Journal of the American Medical Association (JAMA) benchmark, and HONcode tools. The website readability evaluation involved utilizing the Flesch Reading Ease Score (FRES) and the Flesch-Kincaid Grade Level (FKGL). RESULTS: A total of 130 websites met the inclusion criteria. The total mean DISCERN score (section 1 + section 2) for all websites was 39.75/75 (range: 15–67). The average FRES of all websites was 52.79, and the average FKGL score of all websites was 10.72. Internet blog websites had significantly higher DISCERN (Section 1) scores than other websites (p= 0.007). Only one website had the HON code. Internet blog websites showed better compliance with JAMA (authorship and currency) benchmarks. No statistically significant difference was determined related to FRES and FKGL scores between groups (p> 0.05). CONCLUSIONS: There is moderate and difficult-to-read information on the Internet about masseter botox injection for bruxism. Relevant guidelines are needed to improve the quality of websites about botulinum toxin for the treatment of bruxism.
Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN)
Authors: Udayakumar P. , Subhashini R. 
Published: May 2024

BACKGROUND: Connectome is understanding the complex organization of the human brain’s structural and functional connectivity is essential for gaining insights into cognitive processes and disorders. OBJECTIVE: To improve the prediction accuracy of brain disorder issues, the current study investigates dysconnected subnetworks and graph structures associated with schizophrenia. METHOD: By using the proposed structural connectivity-deep graph neural network (sc-DGNN) model and compared with machine learning (ML) and deep learning (DL) models.This work attempts to focus on eighty-eight subjects of diffusion magnetic resonance imaging (dMRI), three classical ML, and five DL models. RESULT: The structural connectivity-deep graph neural network (sc-DGNN) model is proposed to effectively predict dysconnectedness associated with schizophrenia and exhibits superior performance compared to traditional ML and DL (GNNs) methods in terms of accuracy, sensitivity, specificity, precision, F1-score, and Area under receiver operating characteristic (AUC). CONCLUSION: The classification task on schizophrenia using structural connectivity matrices and experimental results showed that linear discriminant analysis (LDA) performed 72% accuracy rate in ML models and sc-DGNN performed at a 93% accuracy rate in DL models to distinguish between schizophrenia and healthy patients.
Analysis of approaches to identification of trend in the structure of the time series
Authors: Mokhnatkina U S. , Parfenov D. V. , Petrusevich D. A. 
Published: May 2024

Objectives. The study set out to compare the forecasting quality of time series models that describe the trend in different ways and to form a conclusion about the applicability of each approach in describing the trend depending on the properties of the time series.Methods. A trend can be thought of as the tendency of a given quantity to increase or decrease over the long term. There is also an approach in which a trend is viewed as some function, reflecting patterns in the behavior of the time series. In this case, we discuss the patterns that characterize the behavior of the series for the entire period under consideration, rather than short-term features. The experimental part involves STL decomposition, construction of ARIMA models (one of the stages of preparation for which includes differentiation, i.e., removal of the trend and transition to a weakly stationary series), construction of ACD models (average conditional displacement) and other approaches. Time-series models based on various trend models are compared with respect to the value of the maximum likelihood function. Many of the combinations have not been constructed before (Fourier series as a trend model, combination of ACD model for trend with seasonal models). Example forecasts of macroeconomic statistics of the Russian Federation and stock prices of Sberbank on the Moscow Exchange in the time range of 2000–2021 are presented.Results. In the experiments, The LOESS method obtained the best results. A combination of polynomial model for trend description and ARIMA for seasonally description and combination of ACD algorithm for trend and ETS for seasonal model obtained good forecasts in case of seasonal time series, while Fourier time series as a trend model also achieved close quality of prediction.Conclusions. Since the LOESS method for groups of seasonal and non-seasonal series gives the best results for all indicators, this method can be recommended for obtaining the most accurate results for series of different nature. Trend modeling using Fourier series decomposition leads to quite accurate results for time series of different natures. For seasonal series, one of the best results is given by the combination of modeling a trend on the basis of a polynomial and seasonality in the form of the ARIMA model.
Potential molecular and cellular mechanisms of the effects of cuproptosis-related genes in the cardiomyocytes of patients with diabetic heart failure: a bioinformatics analysis
Authors: Chen Jinhao , Yang Xu , Li Weiwen , Lin Ying , Lin Run , Cai Xianzhen , Yan Baoxin , Xie Bin , Li Jilin 
Published: May 2024

BackgroundDiabetes mellitus is an independent risk factor for heart failure, and diabetes-induced heart failure severely affects patients’ health and quality of life. Cuproptosis is a newly defined type of programmed cell death that is thought to be involved in the pathogenesis and progression of cardiovascular disease, but the molecular mechanisms involved are not well understood. Therefore, we aimed to identify biomarkers associated with cuproptosis in diabetes mellitus-associated heart failure and the potential pathological mechanisms in cardiomyocytes.MaterialsCuproptosis-associated genes were identified from the previous publication. The GSE26887 dataset was downloaded from the GEO database.MethodsThe consistency clustering was performed according to the cuproptosis gene expression. Differentially expressed genes were identified using the limma package, key genes were identified using the weighted gene co-expression network analysis(WGCNA) method, and these were subjected to immune infiltration analysis, enrichment analysis, and prediction of the key associated transcription factors. Consistency clustering identified three cuproptosis clusters. The differentially expressed genes for each were identified using limma and the most critical MEantiquewhite4 module was obtained using WGCNA. We then evaluated the intersection of the MEantiquewhite4 output with the three clusters, and obtained the key genes.ResultsThere were four key genes: HSDL2, BCO2, CORIN, and SNORA80E. HSDL2, BCO2, and CORIN were negatively associated with multiple immune factors, while SNORA80E was positively associated, and T-cells accounted for a major proportion of this relationship with the immune system. Four enriched pathways were found to be associated: arachidonic acid metabolism, peroxisomes, fatty acid metabolism, and dorsoventral axis formation, which may be regulated by the transcription factor MECOM, through a change in protein structure.ConclusionHSDL2, BCO2, CORIN, and SNORA80E may regulate cardiomyocyte cuproptosis in patients with diabetes mellitus-associated heart failure through effects on the immune system. The product of the cuproptosis-associated gene LOXL2 is probably involved in myocardial fibrosis in patients with diabetes, which leads to the development of cardiac insufficiency.
Bioelectrical impedance parameters add incremental value to waist-to-hip ratio for prediction of metabolic dysfunction associated steatotic liver disease in youth with overweight and obesity
Authors: Song Kyungchul , Seol Eun Gyung , Yang Hyejin , Jeon Soyoung , Shin Hyun Joo , Chae Hyun Wook , Kim Eun-Kyung , Kwon Yu-Jin , Lee Ji-Won 
Published: May 2024

IntroductionMetabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing health concern in pediatric populations due to its association with obesity and metabolic syndrome. Bioelectrical impedance analysis (BIA) offers a non-invasive and potentially effective alternative for identifying MASLD risk in youth with overweight or obesity. Therefore, this study aimed to assess the utility of BIA for screening for MASLD in the youth.MethodThis retrospective, cross-sectional study included 206 children and adolescents aged &lt;20 years who were overweight and obese. The correlations between anthropometric measurements and BIA parameters and alanine aminotransferase (ALT) levels were assessed using Pearson’s correlation analysis. Logistic regression analysis was performed to examine the associations between these parameters and ALT level elevation and MASLD score. Receiver operating characteristic (ROC) curves were generated to assess the predictive ability of the parameters for MASLD.ResultsPearson’s correlation analysis revealed that waist-to-hip ratio (WHR), percentage body fat (PBF), and BIA parameters combined with anthropometric measurements were correlated with ALT level. Logistic regression revealed that WHR, skeletal muscle mass/WHR, PBF-WHR, fat-free mass/WHR, and appendicular skeletal muscle mass/WHR were correlated with ALT level elevation after adjusting for age, sex, and puberty. WHR, PBF-WHR, and visceral fat area (VFA)-WHR were positively correlated with the MASLD score in the total population after adjusting for age, sex, and puberty. PBF-WHR and VFA-WHR were correlated with the MASLD score even in youth with a normal ALT level. The cutoff points and area under the ROC curves were 34.6 and 0.69 for PBF-WHR, respectively, and 86.6 and 0.79 for VFA-WHR, respectively.DiscussionThis study highlights the utility of combining BIA parameters and WHR in identifying the risk of MASLD in overweight and obese youth, even in those with a normal ALT level. BIA-based screening offers a less burdensome and more efficient alternative to conventional MASLD screening methods, facilitating early detection and intervention in youth at risk of MASLD.
Extracellular electrophysiology on clonal human β-cell spheroids
Authors: Puginier Emilie , Leal-Fischer Karen , Gaitan Julien , Lallouet Marie , Scotti Pier-Arnaldo , Raoux Matthieu , Lang Jochen 
Published: May 2024

BackgroundPancreatic islets are important in nutrient homeostasis and improved cellular models of clonal origin may very useful especially in view of relatively scarce primary material. Close 3D contact and coupling between β-cells are a hallmark of physiological function improving signal/noise ratios. Extracellular electrophysiology using micro-electrode arrays (MEA) is technically far more accessible than single cell patch clamp, enables dynamic monitoring of electrical activity in 3D organoids and recorded multicellular slow potentials (SP) provide unbiased insight in cell-cell coupling.ObjectiveWe have therefore asked whether 3D spheroids enhance clonal β-cell function such as electrical activity and hormone secretion using human EndoC-βH1, EndoC-βH5 and rodent INS-1 832/13 cells.MethodsSpheroids were formed either by hanging drop or proprietary devices. Extracellular electrophysiology was conducted using multi-electrode arrays with appropriate signal extraction and hormone secretion measured by ELISA. ResultsEndoC-βH1 spheroids exhibited increased signals in terms of SP frequency and especially amplitude as compared to monolayers and even single cell action potentials (AP) were quantifiable. Enhanced electrical signature in spheroids was accompanied by an increase in the glucose stimulated insulin secretion index. EndoC-βH5 monolayers and spheroids gave electrophysiological profiles similar to EndoC-βH1, except for a higher electrical activity at 3 mM glucose, and exhibited moreover a biphasic profile. Again, physiological concentrations of GLP-1 increased AP frequency. Spheroids also exhibited a higher secretion index. INS-1 cells did not form stable spheroids, but overexpression of connexin 36, required for cell-cell coupling, increased glucose responsiveness, dampened basal activity and consequently augmented the stimulation indexConclusionIn conclusion, spheroid formation enhances physiological function of the human clonal β-cell lines and these models may provide surrogates for primary islets in extracellular electrophysiology.
Cathepsins and cancer risk: a Mendelian randomization study
Authors: Deng Tingting , Lu Xixue , Jia Xuemin , Du Jinxin , Wang Lijuan , Cao Baorui , Yang Meina , Yin Ying , Liu Fanjie 
Published: May 2024

BackgroundPrevious observational epidemiological studies reported an association between cathepsins and cancer, however, a causal relationship is uncertain. This study evaluated the causal relationship between cathepsins and cancer using Mendelian randomization (MR) analysis.MethodsWe used publicly available genome-wide association study (GWAS) data for bidirectional MR analysis. Inverse variance weighting (IVW) was used as the primary MR method of MR analysis.ResultsAfter correction for the False Discovery Rate (FDR), two cathepsins were found to be significantly associated with cancer risk: cathepsin H (CTSH) levels increased the risk of lung cancer (OR = 1.070, 95% CI = 1.027–1.114, P = 0.001, PFDR= 0.009), and CTSH levels decreased the risk of basal cell carcinoma (OR = 0.947, 95% CI = 0.919–0.975, P = 0.0002, PFDR= 0.002). In addition, there was no statistically significant effect of the 20 cancers on the nine cathepsins. Some unadjusted low P-value phenotypes are worth mentioning, including a positive correlation between cathepsin O (CTSO) and breast cancer (OR = 1.012, 95% CI = 1.001–1.025, P = 0.041), cathepsin S (CTSS) and pharyngeal cancer (OR = 1.017, 95% CI = 1.001–1.034, P = 0.043), and CTSS and endometrial cancer (OR = 1.055, 95% CI = 1.012–1.101, P = 0.012); and there was a negative correlation between cathepsin Z and ovarian cancer (CTSZ) (OR = 0.970, 95% CI = 0.949–0.991, P = 0.006), CTSS and prostate cancer (OR = 0.947, 95% CI = 0.902–0.944, P = 0.028), and cathepsin E (CTSE) and pancreatic cancer (OR = 0.963, 95% CI = 0.938–0.990, P = 0.006).ConclusionOur MR analyses showed a causal relationship between cathepsins and cancers and may help provide new insights for further mechanistic and clinical studies of cathepsin-mediated cancer.
Mediators of the association between depression and migraine: a mendelian randomization study
Authors: Li Yang , Luo Ge , Zhou Liwang , Wang Xuena , Liu Hui , Zhang Yang , Yan Min 
Published: May 2024

BackgroundAn association between depression and migraine has been reported in observational studies; however, conventional observational studies are prone to bias. This study aims to investigate the causal relationship between depression and migraine and to quantify the mediating effects of known risk factors.MethodsWe applied two-sample Mendelian randomization and utilized single nucleotide polymorphisms as genetic instruments for exposure (depression) and mediators (sleep traits). We utilized summary data on genome-wide association studies for depression, sleep-related traits mediators and migraine. For depression, genome-wide association studies (depression) were utilized as a test cohort for the primary analysis. Moreover, genome-wide association studies (major depressive disorder) were utilized to test the stability of the results for the validation cohort. IVW and MR-Egger regression were applied to test the heterogeneity, and Cochran’s Q statistics were calculated to quantitatively evaluate the heterogeneity. MR-PRESSO analyses were utilized to examine and correct possible horizontal pleiotropy through removing outliers, and leave-one-out analyses were utilized to identify outlier SNPs.ResultsGenetically predicted depression was associated with migraine (OR = 1.321, 95% CI: 1.184–1.473, p &lt; 0.001). Furthermore, risk factors insomnia was associated with migraine risk (OR = 1.766, 95% CI: 1.120–2.784, p = 0.014). The mediator insomnia accounted for 19.5% of the total effect of depression on migraine.ConclusionThese results support a potential causal effect of depression on migraine, partly mediated by insomnia. Therefore, the enhancement of sleep quality and difficulty in falling asleep may reduce the migraine burden occasioned by depression.
Case report: Late-onset MELAS syndrome with mtDNA 5783G>A mutation diagnosed by urinary sediment genetic testing
Authors: Cai Hao , Li Li-Min , Zhang Miao , Zhou Yuying , Li Pan 
Published: May 2024

BackgroundPatients with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) usually present with multisystemic dysfunction with a wide range of clinical manifestations. When the tests for common mitochondrial DNA (mtDNA) point mutations are negative and the mtDNA defects hypothesis remains, urine epithelial cells can be used to screen the mitochondrial genome for unknown mutations to confirm the diagnosis.Case presentationA 66-year-old Chinese woman presented with symptoms of MELAS and was initially misdiagnosed with acute encephalitis at another institution. Although genetic analysis of blood lymphocyte DNA was negative, brain imaging, including magnetic resonance imaging, magnetic resonance spectroscopy, and clinical and laboratory findings, were all suggestive of MELAS. Finally, the patient was eventually diagnosed with MELAS with the mtDNA 5783G&gt;A mutation in the MT-TC gene with a urinary sediment genetic test.ConclusionThis case report expands the genetic repertoire associated with MELAS syndrome and highlights the importance that full mtDNA sequencing should be warranted beside the analysis of classical variants when a mitochondrial disorder is highly suspected. Furthermore, urine sediment genetic testing has played a crucial role in the diagnosis of MELAS.
Role of recombinant human granulocyte colony-stimulating factor in development of cancer-associated venous thromboembolism in lung cancer patients who undergo chemotherapy
Authors: Cheng Yi , Zhao Yunfeng , Xu Mei , Du He , Sun Jinyuan , Yao Qihuan , Qu Jianmin , Liu Song , Guo Xuejun , Xiong Wei 
Published: May 2024

BackgroundThe role of recombinant human granulocyte colony-stimulating factor (rhG-CSF), especially the long-acting factor in the development of cancer-associated venous thromboembolism (VTE) in lung cancer patients who undergo chemotherapy has been understudied, although the use of rhG-CSF has been reported to be associated with an increased risk of VTE.MethodsWe retrospectively reviewed 1,673 lung cancer patients who underwent hospitalized chemotherapy. We performed propensity score matching to offset confounding factors related to cancer-associated VTE development and classified the patients into short-acting (N = 273), long-acting (N = 273), and no rhG-CSF (N = 273) groups. The primary outcome was cumulative cancer-associated VTE development three months after all cycles of chemotherapy.ResultsThe overall VTE incidence in the short-acting, long-acting, and no rhG-CSF groups was 5.5%, 10.3%, and 2.2%, respectively (P &lt;0.001). The VTE incidence in the long-acting rhG-CSF group was higher than that in the short-acting (P = 0.039) and no rhG-CSF groups (P &lt;0.001). The VTE incidence in the short-acting rhG-CSF group was higher than that in the no rhG-CSF group (P = 0.045). The use of rhG-CSF (hazard ratio [HR] 2.337; 95% confidence interval [CI] [1.236–5.251], P = 0.006) was positively correlated with VTE development among all patients, whereas the use of long-acting rhG-CSF (HR 1.917, 95% CI [1.138–4.359]; P = 0.016), was positively correlated with VTE development in patients receiving rhG-CSF.ConclusionThe use of rhG-CSF, especially long-acting rhG-CSF, increases the risk of cancer-associated VTE development compared to no rhG-CSF use in lung cancer patients who undergo hospitalized chemotherapy.