bluuebunny/crossref_metadata_2025_split huggingface dataset:
PELO CAMINHO DE TIJOLOS AMARELOS: OS AFETOS EM RELAÇÃO À MATEMÁTICA NA FORMAÇÃO INICIAL DE PEDAGOGAS
Authors: Maffei Letícia de Queiroz , Silva João Alberto da 
Published: March 2023

Este artigo apresenta resultados de uma pesquisa, realizada sob um viés fenomenológico que buscou verificar como se mostram os afetos em relação à Matemática a partir da análise da escritade acadêmicas de um curso de Pedagogia. Os sujeitos de pesquisa foram as estudantes que cursaram a disciplina de Metodologia do Ensino de Matemática, durante o ano de 2016, em um curso dePedagogia de uma universidade pública do sul do Estado do Rio Grande do Sul, no Brasil. A coleta de dados ocorreu com a condução de escritas, ao longo da disciplina, em uma caderneta de metacognição, a qual aproxima-se da escrita de um diário de acompanhamento das aulas. Para o tratamento das escritas, que constituíram o corpus de análise do estudo, foi utilizada a Análise Textual Discursiva. A análise gerou quatro categorias: percepção e metodologias; utilização e finalidades; cognição e saberes; emoção e sentimentos. O estudo mostra, dentre outros aspectos, a representatividade do papel do professor na construção das relações de afetos quanto à Matemática e a presença dos mesmos,fortemente atrelada, às questões cognitivas.
CONSIDERAÇÕES SOBRE O CONCEITO DE EQUAÇÃO PRESENTE NOS CADERNOS DO PROFESSOR E AS ZONAS DE PERFIL CONCEITUAL DE EQUAÇÃO
Authors: Lozada Claudia de Oliveira , D´'Ambrosio Ubiratan 
Published: March 2023

Neste artigo, trazemos uma análise da noção de equação presente nos Cadernos do Professor (Matemática) que compõem a Proposta Curricular de Matemática do Estado de São Paulo. Esta análise constitui elemento essencial, uma vez que buscamos compreender a maneira com que o currículo oficial e o material didático utilizado pela rede estadual de ensino tece e/ou abre possibilidades de desenvolvimento de zonas de perfil conceitual de equação e de que modo pode contribuir para a aprendizagem eficaz do conteúdo de equação. Em seguida, discorremos sobre os termos utilizados para nomear e/ou qualificar as questões de Matemática presentes nos Cadernos do Professor, fazendo uma diferenciação e de que forma podem contribuir para o desenvolvimento das zonas de equação, além de trazer reflexões sobre a prova do SARESP do Ensino Médio. Os resultados constataram que o material relativo ao conteúdo de equação embora apresente alguns equívocos de abordagem na parte introdutória, as questões, contudo, possibilitam o desenvolvimento de diversas zonas de perfil conceitual de equação, uma vez que são de tipos variados que possibilitam manifestarvárias formas de resolução.
Satellite-derived bathymetry combined with Sentinel-2 and ICESat-2 datasets using machine learning
Authors: Xie Congshuang , Chen Peng , Zhang Zhenhua , Pan Delu 
Published: March 2023

Most satellite-derived bathymetry (SDB) methods developed thus far from passive remote sensing data have required in situ water depth, thus limiting their utility in areas with no in situ data. Recently, new Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) observations have shown great potential in providing high-precision a priori water depth benefits from range-resolved lidar. In this study, we propose a combined active and passive remote sensing SDB method using only satellite data. An adaptive ellipse DBSCAN (AE-DBSCAN) algorithm is introduced to derive a priori bathymetric data from ICESat-2 data to automatically adapt to the terrain change complexity, and then we use these a priori bathymetric data in Sentinel-2 images to help build a model between remote sensing reflectance (Rrs) and water depth. Three machine learning (ML) methods are then employed, and the performances compared with conventional empirical SDB models are presented. After that, the results using different Sentinel-2 Rrs band combinations and the effects with and without atmospheric correction on ML-based SDB are discussed. The results showed that our AE-DBSCAN method performs better than the standard DBSCAN method, and the ML-based SDB can achieve an overall RMSE of less than 1.5 m in St. Thomas better than the traditional SDB method. They also indicate that ML-based SDB can obtain a relatively high-precision water depth without atmospheric correction, which helps to improve processing efficiency by avoiding a complex atmospheric correction process.
Analysis of an accessibility strategy for deaf people: Videos on a traveling science center
Authors: Ferreira Alessandra Teles Sirvinskas , Alves Gustavo Henrique Varela Saturnino , Vasconcelos Iara Alves Hooper , Souza Thaís Varandas de Azeredo , Fragel-Madeira Lucianne 
Published: March 2023

IntroductionBrazilian traveling science centers have difficulties in providing sign language accessibility to the deaf people that visit them. The main objective of this study was to analyze the contribution of accessible video guides in Brazilian Sign Language (BSL) in helping deaf visitors understand the activities proposed by the traveling science center “Ciências Sob Tendas”.MethodsThis research used a critical quali-quantitative approach that involved 128 deaf students from middle and high schools. Data were gathered via an online survey and video recording.Results and discussionThe results indicated successful use of the video guides by deaf participants. Within this specific research, in which 745 questionnaires were answered, we found that the videos, along with interactive activities, contributed to the interest, curiosity, and understanding of the themes presented. Furthermore, the return visits of deaf people to revisit activities a second and third time may indicate the potential of this science communication strategy to stimulate their interest in scientific knowledge. However, 15% of responses showed that they had some difficulty understanding the video's explanation. This may indicate that, although videos are a well-accepted alternative for accessibility, the presence of an interpreter guide or a deaf visitor guide, when possible, is ideal. Essentially, a professional interpreter can use several BSL resources and strategies to make themselves understood.ConclusionThus, we considered that accessible video guides in BSL are a viable resource for providing accessibility to deaf people in traveling science centers.
Serum fatty acid profiles associated with metabolic risk in women with polycystic ovary syndrome
Authors: Tian Ye , Zhang Jingjing , Li Mingyue , Shang Jie , Bai Xiaohong , Zhang Huijuan , Wang Yanxia , Chen Haitao , Song Xueru 
Published: March 2023

PurposeDyslipidemia is a feature of polycystic ovary syndrome (PCOS) that may augment metabolic disturbances. Serum fatty acids are important biomedical indicators of dyslipidemia. The aim of this study was to determine the distinct serum fatty acids in various PCOS subtypes and their association with metabolic risk in women with PCOS.MethodsFatty acids in the serum of 202 women with PCOS were measured using gas chromatography-mass spectrometry. Fatty acids were compared between PCOS subtypes and correlated with glycemic parameters, adipokines, homocysteine, sex hormones, and sex hormone-binding globulin (SHBG).ResultsThe levels of total monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) in the reproductive subtype of PCOS were lower than those in the metabolic subtype. Docosahexaenoic acid, a PUFA, was associated with higher SHBG after correction for multiple comparisons. Eighteen species of fatty acids emerged as potential biomarkers associated with the metabolic risk factors measured, independent of body mass index (BMI). Among them, myristic acid (C14:0), palmitoleic acid (C16:1), oleic acid (C18:1n-9C), cis-vaccenic acid (C18:1n-7), and homo-gamma-linolenic acid (C20:3n-6) were the strongest lipid species that were consistently associated with metabolic risk factors, particularly insulin-related parameters in women with PCOS. As for adipokines, 16 fatty acids were positively associated with serum leptin. Among them, C16:1 and C20:3n-6were significantly associated with leptin levels.ConclusionOur data demonstrated that a distinct fatty acid profile comprising high C14:0, C16:1, C18:1n-9C, C18:1n-7, and C20:3n-6levels is associated with metabolic risk in women with PCOS, independent of BMI.
Identifying TNF and IL6 as potential hub genes and targeted drugs associated with scleritis: A bio-informative report
Authors: Yan Feiyue , Liu Yizong , Zhang Tianlu , Shen Yin 
Published: March 2023

BackgroundScleritis is a serious inflammatory eye disease that can lead to blindness. The etiology and pathogenesis of scleritis remain unclear, and increasing evidence indicates that some specific genes and proteins are involved. This study aimed to identify pivotal genes and drug targets for scleritis, thus providing new directions for the treatment of this disease.MethodsWe screened candidate genes and proteins associated with scleritis by text-mining the PubMed database using Python, and assessed their functions by using the DAVID database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to identify the functional enrichment of these genes and proteins. Then, the hub genes were identified with CytoHubba and assessed by protein-protein interaction (PPI) network analysis. And the serum from patients with active scleritis and healthy subjects were used for the validation of hub genes. Finally, the DGIdb database was used to predict targeted drugs for the hub genes for treating scleritis.ResultsA total of 56 genes and proteins were found to be linked to scleritis, and 65 significantly altered pathways were identified in the KEGG analysis (FDR &lt; 0.05). Most of the top five pathways involved the categories “Rheumatoid arthritis,” “Inflammatory bowel disease”, “Type I diabetes mellitus,” and “Graft-versus-host disease”. TNF and IL6 were considered to be the top 2 hub genes through CytoHubba. Based on our serum samples, hub genes are expressed at high levels in active scleritis. Five scleritis-targeting drugs were found among 88 identified drugs.ConclusionsThis study provides key genes and drug targets related to scleritis through bioinformatics analysis. TNF and IL6 are considered key mediators and possible drug targets of scleritis. Five drug candidates may play an important role in the diagnosis and treatment of scleritis in the future, which is worthy of the further experimental and clinical study.
Development and validation of a new prognostic immune–inflammatory–nutritional score for predicting outcomes after curative resection for intrahepatic cholangiocarcinoma: A multicenter study
Authors: Zhu Jiang , Wang Denghui , Liu Chang , Huang Rui , Gao Fengwei , Feng Xuping , Lan Tian , Li Hui , Wu Hong 
Published: March 2023

BackgroundImmune function, nutrition status, and inflammation influence tumor initiation and progression. This was a retrospective multicenter cohort study that investigated the prognostic value and clinical relevance of immune-, inflammatory-, and nutritional-related biomarkers to develop a novel prognostic immune–inflammatory–nutritional score (PIIN score) for patients with intrahepatic cholangiocarcinoma (ICC).MethodsThe clinical data of 571 patients (406 in the training set and 165 in the validation set) were collected from four large hepato-pancreatico-biliary centers of patients with ICC who underwent surgical resection between January 2011 and September 2017. Twelve blood biomarkers were collected to develop the PIIN score using the LASSO Cox regression model. The predictive value was further assessed using validation datasets. Afterward, nomograms combining the PIIN score and other clinicopathological parameters were developed and validated based on the calibration curve, time-dependent AUC curves, and decision curve analysis (DCA). The primary outcomes evaluated were overall survival (OS) and recurrence-free survival (RFS) from the day of primary resection of ICC.ResultsBased on the albumin–bilirubin (ALBI) grade, neutrophil- to- lymphocyte ratio (NLR), prognostic nutritional index (PNI), and systemic immune- inflammation index (SII) biomarkers, the PIIN score that classified patients into high-risk and low-risk groups could be calculated. Patients with high-risk scores had shorter OS (training set, p &lt; 0.001; validation set, p = 0.003) and RFS (training set, p &lt; 0.001; validation set, p = 0.002) than patients with low-risk scores. The high PIIN score was also associated with larger tumors (≥5 cm), lymph node metastasis (N1 stage), multiple tumors, and high tumor grade or TNM (tumor (T), nodes (N), and metastases (M)) stage. Furthermore, the high PIIN score was a significant independent prognostic factor of OS and RFS in both the training (p &lt; 0.001) and validation (p = 0.003) cohorts, respectively. A PIIN-nomogram for individualized prognostic prediction was constructed by integrating the PIIN score with the clinicopathological variables that yielded better predictive performance than the TNM stage.ConclusionThe PIIN score, a novel immune–inflammatory–nutritional-related prognostic biomarker, predicts the prognosis in patients with resected ICC and can be a reliable tool for ICC prognosis prediction after surgery. Our study findings provide novel insights into the role of cancer-related immune disorders, inflammation, and malnutrition.
Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: A systematic review
Authors: Moazemi Sobhan , Vahdati Sahar , Li Jason , Kalkhoff Sebastian , Castano Luis J. V. , Dewitz Bastian , Bibo Roman , Sabouniaghdam Parisa , Tootooni Mohammad S. , Bundschuh Ralph A. , Lichtenberg Artur , Aubin Hug , Schmid Falko 
Published: March 2023

BackgroundArtificial intelligence (AI) and machine learning (ML) models continue to evolve the clinical decision support systems (CDSS). However, challenges arise when it comes to the integration of AI/ML into clinical scenarios. In this systematic review, we followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), the population, intervention, comparator, outcome, and study design (PICOS), and the medical AI life cycle guidelines to investigate studies and tools which address AI/ML-based approaches towards clinical decision support (CDS) for monitoring cardiovascular patients in intensive care units (ICUs). We further discuss recent advances, pitfalls, and future perspectives towards effective integration of AI into routine practices as were identified and elaborated over an extensive selection process for state-of-the-art manuscripts.MethodsStudies with available English full text from PubMed and Google Scholar in the period from January 2018 to August 2022 were considered. The manuscripts were fetched through a combination of the search keywords including AI, ML, reinforcement learning (RL), deep learning, clinical decision support, and cardiovascular critical care and patients monitoring. The manuscripts were analyzed and filtered based on qualitative and quantitative criteria such as target population, proper study design, cross-validation, and risk of bias.ResultsMore than 100 queries over two medical search engines and subjective literature research were developed which identified 89 studies. After extensive assessments of the studies both technically and medically, 21 studies were selected for the final qualitative assessment.DiscussionClinical time series and electronic health records (EHR) data were the most common input modalities, while methods such as gradient boosting, recurrent neural networks (RNNs) and RL were mostly used for the analysis. Seventy-five percent of the selected papers lacked validation against external datasets highlighting the generalizability issue. Also, interpretability of the AI decisions was identified as a central issue towards effective integration of AI in healthcare.
Characterization of the oral microbiome and gut microbiome of dental caries and extrinsic black stain in preschool children
Authors: Zheng Luoyuan , Cao Tingting , Xiong Puling , Ma Yulian , Wei Limin , Wang Jianfeng 
Published: March 2023

IntroductionA lower prevalence of dental caries (hereafter termed “caries”) has been observed in children with dental extrinsic black stain (EBS).MethodsWe investigated the epidemiologic characterization of EBS and explored the possible role of the oral microbiome (OM) and gut microbiome (GM) in EBS formation and caries prevention. In an epidemiologic survey, 2,675 children aged 3–6 years were included. Thirty-eight of these children (7 children had both caries and EBS, 10 had EBS only, 11 had caries only, and 10 were healthy children) were recruited for 16S rRNA sequencing and collection of samples of supragingival plaque and feces. Collected plaque samples were divided into four groups: BCP (EBS+, caries+), BP (EBS+, caries−), CP (EBS−, caries+), and P (EBS−, caries−). Fecal samples were also divided into four groups: BCF (EBS+, caries+), BF (EBS+, caries−), CF (EBS−, caries+), and F (EBS−, caries−).ResultsEBS was observed in 12.10% of this population. Children with EBS had a significantly reduced prevalence of caries and a lower mean value of decayed–missing–filled teeth (dmft; p &lt; 0.01). According to analyses of dental plaque, the P group had the most complex microbiome. The BCP group exhibited greater operational taxonomic unit (OTU) richness but a reduced evenness compared with the BP group, and the CP group showed greater OTU richness than the BP group. At the genus level, higher abundance of Actinomyces and Cardiobacterium species was observed in the BCP group. Higher abundance of Lautropia and Pesudopropionibacteriumin species was observed in the BP group compared with P and CP groups, respectively (p &lt; 0.05). Veillonella species were significantly more common in P and CP groups than in BP groups, whereas Porphyromonas and Fusobacterium species were more common in the CP group (p &lt; 0.05). With regard to the GM, the CF group exhibited greater OTU diversity than the BF group. The GM in the BCF group exhibited the most complex relationships across all fecal groups. GM groups could be distinguished by various unique biomarkers, such as Escherichia and Shigella species in the BCF group, Agathobacter and Ruminococcus species in the CF group, Lactobacillus species in the BF group, and Roseburia species in the F group. Our results suggest that EBS is a possible protective factor against early-childhood caries. Dental plaque and the GM may be relevant to EBS in primary dentition.
Predicting the recurrence and overall survival of patients with glioma based on histopathological images using deep learning
Authors: Luo Chenhua , Yang Jiyan , Liu Zhengzheng , Jing Di 
Published: March 2023

BackgroundA deep learning (DL) model based on representative biopsy tissues can predict the recurrence and overall survival of patients with glioma, leading to optimized personalized medicine. This research aimed to develop a DL model based on hematoxylin-eosin (HE) stained pathological images and verify its diagnostic accuracy.MethodsOur study retrospectively collected 162 patients with glioma and randomly divided them into a training set (n = 113) and a validation set (n = 49) to build a DL model. The HE-stained slide was segmented into a size of 180 × 180 pixels without overlapping. The patch-level features were extracted by the pre-trained ResNet50 to predict the recurrence and overall survival. Additionally, a light-strategy was introduced where low-size digital biopsy images with clinical information were inputted into the DL model to ensure minimum memory occupation.ResultsOur study extracted 512 histopathological features from the HE-stained slides of each glioma patient. We identified 36 and 18 features as significantly related to disease-free survival (DFS) and overall survival (OS), respectively, (P &lt; 0.05) using the univariate Cox proportional-hazards model. Pathomics signature showed a C-index of 0.630 and 0.652 for DFS and OS prediction, respectively. The time-dependent receiver operating characteristic (ROC) curves, along with nomograms, were used to assess the diagnostic accuracy at a fixed time point. In the validation set (n = 49), the area under the curve (AUC) in the 1- and 2-year DFS was 0.955 and 0.904, respectively, and the 2-, 3-, and 5-year OS were 0.969, 0.955, and 0.960, respectively. We stratified the patients into low- and high-risk groups using the median hazard score (0.083 for DFS and−0.177 for OS) and showed significant differences between these groups (P &lt; 0.001).ConclusionOur results demonstrated that the DL model based on the HE-stained slides showed the predictability of recurrence and survival in patients with glioma. The results can be used to assist oncologists in selecting the optimal treatment strategy in clinical practice.
Associations between diet and incidence risk of lung cancer: A Mendelian randomization study
Authors: Yan Haihao , Jin Xiao , Zhang Changwen , Zhu Changjun , He Yucong , Du Xingran , Feng Ganzhu 
Published: March 2023

BackgroundObservational studies have revealed associations between diet and lung cancer. However, it is unclear whether the association is disturbed by confounding factors. We used a two-sample Mendelian randomization (MR) method to characterize the associations between diet and the lung cancer risk (including 3 subtypes: lung adenocarcinoma (LA), squamous cell lung carcinoma (SqCLC), and small cell lung cancer (SCLC)).Materials and methodsData on 20 diets were screened from the UK Biobank. Lung cancer data came from a large meta-analysis of 85,716 individuals. The inverse-variance weighted method was used as the main analysis. Sensitivity analysis was also used to explain the different multiplicity patterns of the final model.ResultsOur results showed significant evidence that 3 diets were associated with lung cancer [odds ratio (OR): 0.271, 95% confidence interval (CI): 0.150–0.488, p = 1.46 × 10−4, dried fruit; OR: 3.010, 95% CI: 1.608–5.632, p = 5.70 × 10−4, beer] and SqCLC (OR: 0.135, 95% CI: 0.062–0.293, p = 2.33 × 10−5, dried fruit; OR: 0.485, 95% CI: 0.328–0.717, p = 2.9 × 10−4, cheese). There were also suggestive correlations between 5 dietary intakes and lung cancer (OR: 0.441, 95% CI: 0.250–0.778, p = 0.008, cereal; OR: 2.267, 95% CI: 1.126–4.564, p = 0.022, beef), LA (OR: 0.494, 95% CI: 0.285–0.858, p = 0.012, dried fruit; OR: 3.536, 95% CI: 1.546–8.085, p = 0.003, beer) and SCLC (OR: 0.006, 95% CI: 0.000–0.222, p = 0.039, non-oily fish; OR: 0.239, 95% CI: 0.086–0.664, p = 0.006, dried fruit). No other association between diet and lung cancer was observed.ConclusionOur study preliminary found that cheese, dried fruit, and beer intake were significantly associated with the risk of lung cancer or its subtypes, while cereal, beef, and non-oily fish intake were suggestively associated with the risk of lung cancer or its subtypes. Well-designed prospective studies are still needed to confirm our findings in the future.