bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of the progressive taper enlargement of buccal root canals of three‐rooted maxillary molars: A stepwise micro‐CT study
Authors: Barbosa Ana Flávia Almeida , de Lima Carolina Oliveira , Antunes Bernardo Rempto , Sassone Luciana Moura , Versiani Marco Aurélio , da Silva Emmanuel João Nogueira Leal 
Published: July 2023

AbstractThis study evaluated unprepared canal areas, volume of dentine removal, and dentine thickness after the progressive enlargement of the buccal canals of 22 maxillary molars, with and without the MB2, using instruments with the same tip size (0.25 mm) but 4 different tapers (0.03, 0.05, 0.06 and 0.08 v). Micro‐CT scans were performed after each instrument. Data were compared using a general linear mixed model post hoc comparisons with Kenward‐Roger for Wald F tests (α = 5%). After each treatment step, it was observed an increase in the percentage volume of removed dentine and a decrease in the unprepared areas and dentine thickness at the pericervical region of all canals (p < 0.05). The percentage reduction of dentine thickness in MB2 canal was higher than in the mesiobuccal and distobuccal canals (p < 0.05). Knowledge of pre‐operative dimensions and dentine thickness before enlargement of buccal canals of maxillary molars is an important factor to avoid excessive dentine removal.
Depleted by Debt: “Green” Microfinance, Over‐Indebtedness, and Social Reproduction in Climate‐Vulnerable Cambodia
Authors: Guermond Vincent , Iskander Dalia , Michiels Sébastien , Brickell Katherine , Fay Gráinne , Ly Vouch Long , Natarajan Nithya , Parsons Laurie , Picchioni Fiorella , Green W. Nathan 
Published: July 2023

AbstractThe operations of microfinance are exalted in mainstream development thinking as a key means of supporting smallholder farmers facing growing crises of agricultural productivity in the context of daily, ongoing, and often slow‐onset climate disasters. Microfinance products and services are claimed to enhance coping and adaptative capacity by facilitating both risk recovery and reduction. Challenging the status quo, this paper brings together original and mixed‐method data collected between 2020 and 2022 in Cambodia to critically examine the “green finance” agenda by highlighting the ways in which microfinance contributes to reproducing and exacerbating climate precarity and harm for many. We evidence how credit‐taking can lead to more dangerous and individualised efforts to cope with, and adapt to, existing conditions at home, often at the cost of emotional and bodily depletion. By doing so, we contribute to answering calls for connecting literatures and thinking on social reproduction, depletion, and climate change adaptation.
One nation, under war: Did the language of Fox News and MSNBC converge during the invasion of Ukraine?
Authors: Wetherell Geoffrey , Thompson Jordan L. , Vallejo Isabella , Lanning Kevin 
Published: July 2023

AbstractEvidence suggests that political differences have increased markedly in the United States in recent decades. Differences may also emerge in the way that partisans express themselves through language, and it is possible that language differences vary in times of crisis and war. In the current work we examined over a decade's worth of transcripts from a liberal (MSNBC) and conservative (Fox) news network. More specifically, we examined evidence for two competing perspectives on language differences during the Russian invasion of Ukraine in 2022. One perspective, the depolarization perspective, suggests that we should see decreased differences, or parity in language styles between the two networks leading up to and during the invasion. Another perspective, the polarization perspective, suggests we should see increased differences in language styles between networks leading up to and during the early stages of the invasion. We examined an index of personalizing and formalizing language as well as 77 Linguistic Inquiry and Word Count (LIWC) dictionaries plus noun frequency using smoothed curves and linear discriminant function analyses (LDA) to examine the pattern of results in our data. Our results provide more support for the depolarization perspective, showing that both Fox News and MSNBC became more similar than different leading up to and during the invasion. Implications are discussed.
Bayesian Functional Data Analysis Over Dependent Regions and Its Application for Identification of Differentially Methylated Regions
Authors: Chatterjee Suvo , Chowdhury Shrabanti , Ryu Duchwan , Basu Sanjib 
Published: July 2023

AbstractWe consider a Bayesian functional data analysis for observations measured as extremely long sequences. Splitting the sequence into several small windows with manageable lengths, the windows may not be independent especially when they are neighboring each other. We propose to utilize Bayesian smoothing splines to estimate individual functional patterns within each window and to establish transition models for parameters involved in each window to address the dependence structure between windows. The functional difference of groups of individuals at each window can be evaluated by the Bayes factor based on Markov Chain Monte Carlo samples in the analysis. In this paper, we examine the proposed method through simulation studies and apply it to identify differentially methylated genetic regions in TCGA lung adenocarcinoma data.
Multifaced roles of desmoplastic reaction and fibrosis in pancreatic cancer progression: Current understanding and future directions
Authors: Sato Hiromichi , Hara Tomoaki , Meng Sikun , Tsuji Yoshiko , Arao Yasuko , Saito Yoshiko , Sasaki Kazuki , Kobayashi Shogo , Doki Yuichiro , Eguchi Hidetoshi , Ishii Hideshi 
Published: July 2023

AbstractDesmoplastic reaction is a fibrosis reaction that is characterized by a large amount of dense extracellular matrix (ECM) and dense fibrous stroma. Fibrotic stroma around the tumor has several different components, including myofibroblasts, collagen, and other ECM molecules. This stromal reaction is a natural response to the tissue injury process, and fibrosis formation is a key factor in pancreatic cancer development. The fibrotic stroma of pancreatic cancer is associated with tumor progression, metastasis, and poor prognosis. Reportedly, multiple processes are involved in fibrosis, which is largely associated with the upregulation of various cytokines, chemokines, matrix metalloproteinases, and other growth factors that promote tumor growth and metastasis. Fibrosis is also associated with immunosuppressive cell recruitment, such as regulatory T cells (Tregs) with suppressing function to antitumor immunity. Further, dense fibrosis restricts the flow of nutrients and oxygen to the tumor cells, which can contribute to drug resistance. Furthermore, the dense collagen matrix can act as a physical barrier to block the entry of drugs into the tumor, thereby further contributing to drug resistance. Thus, understanding the mechanism of desmoplastic reaction and fibrosis in pancreatic cancer will open an avenue to innovative medicine and improve the prognosis of patients suffering from this disease.
Baicalein enhances immune response in TNBC by inhibiting leptin expression of adipocytes
Authors: Liu Mengjie , Li Chaofan , Qu Jingkun , Sun Shiyu , Zhao Zitong , Wang Weiwei , Lv Wei , Zhang Yu , Cai Yifan , Zhao Fang , Wu Fei , Zhang Shuqun , Zhao Xixi 
Published: July 2023

AbstractTriple‐negative breast cancer (TNBC) is a special pathological type of breast cancer (BC) with poor prognosis. Obesity is shown to be involved in TNBC tumor progression. The interaction between obesity and BC has generated great attention in recent years, however, the mechanism is still unclear. Here, we showed that leptin secreted by adipocytes upregulated PD‐L1 expression in TNBC through the p‐STAT3 signaling pathway and that baicalein inhibited PD‐L1 expression in tumor microenvironment by suppressing leptin transcription of adipocytes. Collectively, our findings suggest that leptin may be the key factor participating in obesity‐related tumor progression and that baicalein can break through the dilemma to boost the anti‐tumor immune response.
Farnesoid X receptor represses human sulfotransferase 1A3 expression through direct binding to the promoter
Authors: Dou Yuanyuan , Pei Shuhua , Li Yingying , Wang Mengqing , Liu Zhuangzhuang , Li Jiqin , Cao Jinlan , Qin Jia , Zhang Mingzhu , Hou Lili , Sun Hua 
Published: July 2023

AbstractHuman sulfotransferases 1A3 (SULT1A3) has received particular interest, due to their functions of catalyzing the sulfonation of numerous phenolic substrates, including bioactive endogenous molecules and therapeutic agents. However, the regulation of SULT1A3 expression and the underlying mechanism remain unclear. Here, we aimed to investigate the regulation effects of bile acid‐activated farnesoid X receptor (FXR) on SULT1A3 expression, and to shed light on the mechanism thereof. Our results demonstrated that FXR agonists (CDCA and GW4064) significantly inhibit the expression of SULT1A3 at mRNA and protein levels. In addition, overexpression of FXR led to decrease in SULT1A3 expression and knockdown of FXR significantly induced the expression of SULT1A3 in protein and mRNA levels, confirming that FXR expression manifestly showed negative regulatory effect on basal SULT1A3 expression. Furthermore, a combination of luciferase reporter gene and CHIP assays showed that FXR repressed SULT1A3 transcription through direct binding to the region at base pair positions −664 to −654. In conclusion, this study for the first time confirmed FXR was a negative transcriptional regulator of human SULT1A3 enzyme.
Social determinants of self‐reported oral health among Sámi in Sweden
Authors: Yekkalam Negin , Storm Mienna Christina , Stoor Jon Petter Anders , San Sebastian Miguel 
Published: July 2023

AbstractObjectivesTo investigate the prevalence of poor self‐reported oral health and to identify socio‐demographic, socio‐economic and cultural‐related risk factors associated with poor oral health among Sámi in Sweden.MethodsA Sámi sample frame was constructed drawing from three pre‐existing registers. All identified persons aged 18–84 were invited to participate in the study during February–May 2021. Among the 9249 invitations, 3779 answered the survey. The frequencies of the independent variables in terms of socio‐economic, socio‐demographic and cultural‐related factors as well as the outcome, self‐reported oral health, were calculated first. Prevalence ratios (PRs) and their 95% confidence interval (95% CI) were estimated to assess the relationship between the independent variables and the outcome.ResultsOverall, 32.5% of the participants reported a poor oral health with a higher prevalence among men compared to women. Among the socio‐demographic factors, being old (PR: 1.99; 95% CI: 1.59–2.51), unmarried (PR: 1.17; 95% CI: 1.03–1.33) and divorced or widow‐er (PR: 1.27; 95% CI: 1.09–1.46) were statistically associated to poor self‐reported oral health. Among the socio‐economic factors, a low education level (PR: 1.56; 95% CI: 1.29–1.89), belonging to the poorest quintile (PR: 1.63; 95% CI: 1.35–1.96), and experiencing difficulties to make ends meet several times during the last 12 months (PR: 1.74; 95% CI: 1.51–1.99) were statistically significant related to poor oral health.ConclusionsThe self‐reported oral health among Sámi in Sweden appears to be worse than that of the general Swedish population. Several socio‐economic and socio‐demographic factors were found to be strongly associated with poor self‐reported oral health. Targeted interventions addressing these social determinants are needed to reduce inequalities in oral health among the Sámi population.
An attention‐based deep learning model for credibility assessment of online health information
Authors: Padhy Swarup , Rathore Santosh Singh 
Published: July 2023

AbstractWith the surge of searching and reading online health‐based articles, maintaining the quality and credibility of online health‐based articles has become crucial. The circulation of deceptive health information on numerous social media sites can mislead people and can potentially cause adverse effects on people's health. To address these problems, this work uses deep learning approaches to automate the assessment and scoring of online health‐related articles' credibility. The paper proposed an Attention‐based Recurrent Multichannel Convolutional Neural Network (ARMCNN) model. The proposed model incorporates a BiLSTM layer, a multichannel CNN layer, and an attention layer and predicts the credibility of online health information. To perform a reliable evaluation of the presented model, we utilize the health articles reviewed by the experts, compiled in a labeled dataset termed “Pubhealth,” which consists of thousands of health articles. The results are evaluated using five performance measures, accuracy, precision, recall, f1‐score, and area under the ROC curve (AUC). Furthermore, we extensively compared the proposed model with different deep learning and machine learning models such as Long short‐term memory (LSTM), Bidirectional LSTM, CNN (Convolutional neural network), and RNN‐CNN. The experimental results showed that the proposed model produced state‐of‐the‐art performance on the used dataset by achieving an accuracy of 0.88, precision of 0.92, recall of 0.87, f1‐score of 0.90, and AUC of 0.94. Further, the proposed model yielded better performance than other benchmarked techniques for the credibility assessment of online health articles.
Investigations of the distant metastatic non‐small cell lung cancer without local lymph node involvement: Real world data from a large database
Authors: Huang Bao‐Wen , Wang Wen‐Qin , Cai Jing‐Sheng , Zhang Su‐Wen 
Published: July 2023

AbstractIntroductionThis study aimed to investigate the presentations and survival outcomes of the distant metastatic non‐small cell lung cancer (NSCLC) without lymph node involvement to obtain a clearer picture of this special subgroup of metastatic NSCLC.MethodA least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis was used to select the prognostic variables. A nomogram and corresponding risk‐classifying systems were constructed. The C‐index and calibration curves were used to evaluate the performance of the model. Overall survival (OS) curves were plotted using the Kaplan–Meier method, and the log‐rank test was used to compare OS differences between groups. Propensity score matching (PSM) was performed to reduce bias.ResultA total of 12 610 NSCLC patients with M1 category (N0 group: 3045 cases; N1‐3 group: 9565 cases) were included. Regarding the N0 group, multivariate analysis demonstrated that age, sex, race, surgery, grade, tumor size, and M category were independent prognostic factors. A nomogram and corresponding risk‐classifying systems were formulated. Favorable validation results were obtained from the C‐index, calibration curves, and survival comparisons. Survival curves demonstrated that N0 NSCLC patients had better survival than N1‐3 NSCLC patients both before and after PSM. Furthermore, the survival of resected N0M1 patients was superior to that of those without surgery.ConclusionIn this study, a prognostic nomogram and risk‐classifying systems designed for the T1‐4N0M1 NSCLC patients showed acceptable performance. Primary lung tumor resection might be a feasible treatment for this population subset. Additionally, we proposed that lymph node stage might have a place in the forthcoming tumor‐node‐metastasis (TNM) staging proposal for NSCLC patients with M1 category.
Classification of events contributing to postneonatal cerebral palsy: Development, reliability, and recommendations for use
Authors: Pudig Luise , Delobel‐Ayoub Malika , Horridge Karen , Gergeli Anja Troha , Sellier Elodie , Ehlinger Virginie , Hollody Katalin , Virella Daniel , Vik Torstein , Arnaud Catherine 
Published: July 2023

AbstractAimThis paper introduces the Surveillance of Cerebral Palsy in Europe (SCPE) classification of events contributing to postneonatally acquired cerebral palsy, presents its interrater reliability, and describes the cases identified in the SCPE database.MethodThe development of the classification, based on literature review and expert discussions, resulted in six main categories and 19 subcategories. The first chronological event designated as the primary event was mainly reported. Interrater reliability was assessed through online exercise providing 24 clinical vignettes representing single/complex pathways. Percent agreement and Gwet's AC1 index of reliability were estimated. Primary events were described using data of 221 children born between 2008 and 2012.ResultsThirty‐nine professionals (21 registries) participated in the reliability exercise. Substantial overall agreement was reached (0.75), with some contrast between complex (0.48, moderate agreement) and single events involved (0.89, almost perfect). The distribution of primary events showed that 32.1% were infections (category A), 23.1% head injuries (B), 15.4% related to surgery or medical interventions (C), 13.1% cerebrovascular accidents (D), 9.1% hypoxic brain damaging events of other origins (E), and 7.2% miscellaneous (F).InterpretationThis classification allows all the events involved to be recorded while consistently reporting the primary event, and may be used in different settings.What this paper adds

A standardized classification enables the description of the events contributing to postneonatal cerebral palsy (CP).
The first chronological event in complex pathway leading to CP is coded.
Category choice and coding of the primary event identify preventable situations.
The detailed 2‐level classification is easy to use in various settings.
Substantial overall interrater reliability shows that main categories can be consistently differentiated.
Heterogeneous predictive association of CO2 with global warming
Authors: Chen Liang , Dolado Juan J. , Gonzalo Jesús , Ramos Andrey 
Published: July 2023

AbstractGlobal warming is a non‐uniform process across space and time. This opens the door to a heterogeneous relationship between and temperature that needs to be explored going beyond the standard analysis based on mean temperature. We revisit this topic through the lens of a new class of factor models for high‐dimensional panel data, called quantile factor models. This technique extracts quantile‐dependent factors from the distributions of temperature across a wide range of stable weather stations in the northern and southern hemispheres over 1959–2018. In particular, we test whether the (detrended) growth rate of concentrations helps to predict the underlying factors of the different quantiles of the distribution of (detrended) temperatures in the time dimension. We document that predictive association is greater at the lower and medium quantiles than at the upper quantiles of temperature in all stations, and provide some conjectures about what could be behind this non‐uniformity. These findings complement recent results in the literature documenting steeper trends in lower temperature levels than in other parts of the spatial distribution.
Evaluation of problem‐based learning in dental trauma education: An observational cohort study
Authors: Puranik Chaitanya P. , Pickett Kaci , de Peralta Tracy 
Published: July 2023

AbstractBackground/AimProblem‐based learning (PBL) allows higher thinking among dental students and has improved first‐time pass‐rates in predoctoral pediatric dentistry education. The aim of this retrospective observational cohort study was to evaluate the impact of PBL‐based, traumatic dental injuries case discussions on predoctoral dental trauma education.Materials and MethodsStudent performance and perceptions after receiving dental trauma curriculum with or without PBL‐based dental trauma case discussions were evaluated. All the students challenged their simulated patient‐based assessments. Three recall‐based, objective structured clinical examinations, and critical thinking competencies assessed student knowledge about management of traumatic injuries affecting primary or permanent dentition including avulsion. The scores and number of attempts for each competency were compared between the study cohorts using t‐tests. Student's self‐perceived learning outcomes were measured through a voluntary, five‐question survey. Mantel–Haenszel ordinal Chi‐square tests were used to assess for differences in rates of agreement on survey responses from the students. Linear regression was used to assess effect of training on scores adjusting for student type (predoctoral or advanced standing). Pearson's correlations were used to assess association between scores. Significance was set at 0.05.ResultsFor the PBL cohort, there was a significant (p > 0.05) improvement in the first‐time pass‐rates and scores in three out of four competencies. A higher proportion of students in the PBL cohort perceived that their dental trauma education improved their radiographic and diagnostic skills compared to the cohort that did not receive PBL (p > 0.05). There was no correlation between recall‐memory versus critical thinking competencies (r < 0.5).ConclusionThe PBL‐based dental trauma case discussion had a positive impact on predoctoral student learning and perceived benefits while managing simulated traumatic dental injuries. Due to a lack of correlation between recall‐memory and critical thinking assessments, evaluation of predoctoral student's dental trauma competencies should involve multi‐model assessment.
Paraneoplastic or not? Sirtuin 2 in anti‐N‐methyl‐d‐aspartate receptor encephalitis
Authors: Stevens‐Jones Oskar , Mojzisova Hana , Elisak Martin , Constantinescu Radu , Hanzalova Jitka , Axelsson Markus , Krysl David 
Published: July 2023

AbstractBackground and purposeN‐methyl‐d‐aspartate receptor (NMDAR) and leucine‐rich glioma‐inactivated protein 1 (LGI1) encephalitis are important types of autoimmune encephalitis (AE) with significant morbidity. In this study, we used a proteomic approach in search of novel clinically relevant biomarkers in these types of encephalitides.MethodsSwedish and Czech tertiary neuroimmunology centers collaborated in this retrospective exploratory study. Fifty‐eight cerebrospinal fluid (CSF) samples of 28 patients with AE (14 definite NMDAR, 14 with definite LGI1 encephalitis) and 30 controls were included. CSF samples were analyzed using proximity extension assay technology (Olink Target 96 Inflammation panel). For each CSF sample, 92 proteins were measured. Clinical variables were retrospectively collected, and correlations with protein levels were statistically analyzed.ResultsPatients and controls differed significantly in the following 18 biomarkers: TNFRSF9, TNFRSF12, TNFRSF14, TNFβ, TNFα, IL7, IL10, IL12B, IFNγ, CD5, CD6, CASP8, MMP1, CXCL8, CXCL10, CXCL11, IL20RA, and sirtuin 2 (SIRT2). In LGI1 encephalitis, no clinically useful association was found between biomarkers and clinical variables. In the NMDAR encephalitis group, SIRT2, TNFβ, and CD5 were significantly associated with ovarian teratoma. For SIRT2, this was true even for the first patients' CSF sample (SIRT2 without vs. with tumor, mean ± SD = 2.2 ± 0.29 vs. 2.88 ± 0.48; p = 0.007, 95% confidence interval = −1.15 to −0.22; r statistic in point‐biserial correlation (rpb) = 0.66, p = 0.011). SIRT2 was positively correlated with age (rpb = 0.39, p = 0.018) and total hospital days (r = 0.55, p = <0.001).ConclusionsSIRT2 should be investigated as a biomarker of paraneoplastic etiology in NMDAR encephalitis.