bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monocyte subsets and monocyte-related chemokines in Takayasu arteritis
Authors: Aguiar Mariana Freitas , Torquato Heron , Salu Bruno Ramos , Oliveira Ana Cecília Diniz , Oliva Maria Luiza Vilela , Paredes-Gamero Edgar Julian , Abdulahad Wayel H. , Brouwer Elisabeth , Souza Alexandre W. S. 
Published: September 2022

Abstract

Background: The pathogenesis of Takayasu arteritis (TAK) is poorly understood. Although a macrophage-rich vessel wall granulomatous inflammation is a hallmark of TAK pathology, no previous studies have analyzed the monocytes’ role in the pathogenesis of the disease. This study aims to evaluate the distribution of monocyte subsets and the monocyte-related chemokines profile in the peripheral blood of TAK patients and age & sex matched healthy controls (HC).
Methods: TAK patients were evaluated for current disease activity and current therapy. Monocyte subsets were identified by flow cytometry according to the surface expression of CD14 and CD16 as classical (CD14+CD16-), intermediate (CD14+CD16dim), and non-classical (CD14dimCD16high) in the peripheral blood. Multiplex Luminex assay was used to measure serum monocytes-related chemokines including CCL2, CCL3, CCL4, CCL5, CCL7, CXCL10 and CX3CL1.
Results: Thirty-two consecutive TA patients and 30 HC were evaluated. TAK patients had a higher number of circulating intermediate monocytes compared to HC [25.01 cells x 106/L (16.7-52.0) vs. 17.2 cells x 106/L (9.2-25.3); p = 0.014]. Active disease was associated with monocytosis (p = 0.004) along with the increase of the classical (p = 0.003) and intermediate (p < 0.001) subsets compared to HC. No significant differences were found in the distribution of monocyte subsets between active disease and the remission state. Prednisone use reduced the percentage of non-classical monocytes (p = 0.011). TAK patients had lower CCL3 (p = 0.033) and CCL4 (p = 0.023) levels than HC, whereas CCL22 levels were higher in active TAK compared to the remission state (p = 0.008). Therapy with immunosuppressive agents or biologics did not impact serum chemokines, but glucocorticoids were associated with lower CXCL10 levels (p = 0.012). In TAK patients, CCL4 concentration correlated with the number of total monocytes (Rho = 0.489; p = 0.005) and classical and intermediate monocytes (Rho = 0.448; p = 0.010 and Rho = 0.412; p = 0.019) in the peripheral blood.
Conclusions: TAK is associated with altered counts of monocyte subsets in the peripheral blood compared to HC and CCL22 is the chemokine with the strongest association with active disease in TAK.
Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of multiple clinical data types.
Authors: Gordan John D. , Zack Travis , Venook Alan , Wild Jennifer , Butte Atul , Maisel Samantha , Yaqubie Amin , Abou-Alfa Ghassan , Knox Jennifer J , Mayer Robert , O’Neill Allison 
Published: September 2022

Abstract
Importance: The incidence and biochemical consequences of rare tumor subtypes are often hard to study. Fibrolamellar liver cancer (FLC) is one such rare malignancy affecting adolescents and young adults. To better characterize the incidence and biochemical consequences of this disease, we combined a comprehensive analysis of electronic medical record and national payee data and find that FLC incidence is likely 6–8 times higher than previous estimates. By deploying unsupervised learning modes on clinical laboratory data on patients with hyperammonemia, we find that FLC-associated hyperammonemia mirrors metabolic dysregulation in Urea Cycle Disorders. We demonstrate that advanced computational analysis of rich clinical datasets can provide key clinical and biochemical insights into rare cancers.
Montane Grassland Resources Drive Gorilla (Gorilla Gorilla) Nesting Behaviours in the Ebo Forest, Littoral Region, Cameroon
Authors: Mfossa Daniel Mbouombouo , Gazagne Eva , Gray Russell J. , Ketchen Marcel Eyong. , Abwe Ekwoge Enang , Beudels-Jamar Roseline C. , Tchouamo Roger Isaac , Brotcorne Fany 
Published: September 2022

Abstract

Great apes show strong attachment to their nesting sites which provides them with substantial survival elements. Their nesting behaviors are influenced by geographical and ecological variables including habitat type, slope, elevation gradients, and sometimes anthropogenic pressures. This study aimed to assess environmental variables that influenced the Ebo gorilla (Gorilla gorilla) nesting behavior in relation to nesting site selection, nest types, and nesting materials. We collected data from January 2013 to November 2017 along reconnaissance tracks (recce, hereafter) using the marked nest counting method. We recorded 0.16 nesting sites per km as an encounter rate, with an average number of four nests per gorilla group. The mean nest diameter was 90.33 ± 23.92 cm (n = 640, range 25–199 cm). Ebo gorillas preferred nesting sites at high altitude located in the grassland areas with open canopy, ligneous undergrowth composition and very closed visibility. Ebo gorillas used more than 281 plant species as materials for nesting with Marantaceae and Zingiberaceae species being the most common material used. Terrestrial herbaceous nests were the most common nest type (55%). During the dry season, gorillas visited more often the mature forest habitat and mostly constructed arboreal nests. Finally, reuse of nesting sites by Ebo gorillas was minimal (16%), and visitation period occurred from 3 days to 33 months. Our study provides the first systematic investigation of gorilla nesting behavior within the Ebo forest constituting therefore an essential starting point for the long-term conservation planning of this little-known population.
Validation of a Thai semiquantitative food frequency questionnaire (semi-FFQ) for people at risk of metabolic syndrome
Authors: Nirdnoy Nattvara , Sranacharoenp Kitti , Surawit Apinya , Pinsawas Bonggochpass , Mongkolsucharitkul Pichanun , Pongkunakorn Tanyaporn , Manosan Thamonwan , Ophakas Suphawan , Suta Sophida , Pumeiam Sureeporn , Mayurasakorn Korapat , Group Siriraj Health Study 
Published: September 2022

Abstract
Background
Food frequency questionnaires (FFQ) are a useful dietary assessment tool to determine relationships between diet and non-communicable diseases (NCDs). Our purpose was to validate a semiquantitative FFQ (semi-FFQ) for Thais at risk of metabolic syndrome (MS).
Methods
The study identified 345 men and women aged 30 to 65 years were enrolled and invited to participate in data collection for 4 weeks. They were asked to maintain a 4-day food record and partook in a semi-FFQ interview during week 4. Urine samples and biochemical results related to MS were collected. Validation results were associated with 3 primary nutrients for MS (sugar, fat, and sodium) and biochemical results (blood glucose, lipid profiles, blood pressure, and 24-hour urine sodium).
Results
Ninety-four participants were enrolled (54 in a “urine-collection not-required” group and 40 in a “urine collection” group). The level of each key MS nutrient significantly increased commensurate with rises in semi- FFQ estimated intakes. Correlation coefficients (r) were as follows: fasting blood glucose, r = 0.293 (fruits) and r = 0.285 (desserts); triglycerides, r = 0.252 (a la carte-dishes); LDL-cholesterol, r = 0.205 (rice-with-topping dishes); systolic blood pressure, r = 0.272 (snacks) and r = 0.190 (a la carte dishes).
Conclusions
The semi-FFQ helps assess dietary patterns of Thai populations at risk of NCDs.
Air pollution, residential greenness and medical expenditure in older adults
Authors: Zhou Wensu , Li Rui , Wang Wenjuan , Zhou Fenfen , Ling Li 
Published: September 2022

Abstract
Background: Environmental factors have been thought of as potential determinants for human health and would plausibly affect health expenditures. However, little is known about the association between air pollution, greenness, and their combined effect on medical expenditures, let alone, related evidence in older adults is rarely.
Method: We used data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Medical expenditures were defined as out-of-pocket medical expenditures in the 12 months preceding the survey. A two-year average of PM2.5 concentrations prior to medical expenditures was collected as PM2.5 exposures. Greenness exposure was contemporaneous with PM2.5 and evaluated by residential units’ NDVI value in 250 m buffer. The two-part models were performed to assess the independent influences of PM2.5, greenness, and its combined influence. The first model was a logistic regression model based on the whole sample, called the participation models. Then a log-transformed linear regression model was fitted using samples with nonzero medical expenditures, named intensity models.
Result: We found that each 10-µg/m3 increment in PM2.5 increased the odds of incurring any costs (coefficient=0.80, P <0.001) according to the participation models. PM2.5 was associated with an increase in expenditure based on intensity models (coefficient=0.08, P <0.001). Each 0.1-unit increase in greenness decreased the odds of incurring any costs in the participation models (coefficient=-0.77, P <0.05). The risk of increasing medical expenditures attributed to PM2.5was higher in areas with a low level of greenness (coefficient=0.16, P <0.001). While greenness did not present a protective effect for increasing costs in the low level of PM2.5 (coefficient=0.21, P <0.05), increasing greenness could reduce costs in the high and medium level of PM2.5. Uneducated participants and others without pensions were vulnerable to the combined effect.
Conclusion: Air pollution is a potential source of medical expenditures; in comparison, expanding greenspace is associated with these societal costs saved. Suppose the combined impact of greenness and PM2.5 was to be replicated in a future study, which would improve the utility of current evidence.
Variations of water use efficiency, C, N concentration in Chinese fir under climate change based on carbon stable isotope analysis
Authors: You Ren , Liu Yang , Deng Xiangwen , Hu Yanting , Ouyang Shuai , Chen Liang , Xiang Wenhua 
Published: September 2022

Abstract
Water use efficiency (WUEi) can strongly influence the growth of individual tree diameter, and drought caused by increasing temperatures can profoundly affect the water use strategy of red-heart Chinese fir. The differences in WUE of red-heart Chinese fir juveniles under different ages and meteorological conditions have not been studied yet. Here, the standardized precipitation evapotranspiration index (SPEI) was calculated to determine the extent of drought and studied the relationship between WUEi and other ecological factors through path analysis. Compared with 1981–2020, the mean monthly temperature and annual total precipitation in 2015–2020 increased by 0.7 ° C and 177mm, respectively. Significant differences in WUEi at different leaf and branch ages. WUEi and N concentration decreased with the age increase, but C concentration increased. Carbon isotope increased with the increase of relative tree height. N concentration and C/N did not change significantly with the increase in relative tree height. There were significant differences in WUEi under different SPEI. In 2020 (SPEI = 0.12), the WUEi of branches and leaves was the highest, which were 92.7% and 88.4%, respectively. WUEi and C concentration have a significant negative relationship (-0.516). Tree basic area increment (BAI) was significantly negatively correlated with precipitation (-0.777) and relative humidity (-0.488) and significantly positively correlated with temperature (0.871). Our results show that red-heart Chinese fir has a high demand for water and nutrients in the juvenile stage, which could further provide a theoretical basis for the directed cultivation and sustainable management of red-heart Chinese fir.
Brown bear skin-borne secretions display evidence of individuality and age-sex variation
Authors: Clapham Melanie , Wilson Abbey E. , Williams Candace L. , Sergiel Agnieszka 
Published: September 2022

Abstract
Scent originates from excretions and secretions, and its chemical complexity in mammals translates into a diverse mode of signalling. Identifying how information is encoded can help to establish the mechanisms of olfactory communication and explore the use of odours as chemical signals. Building upon existing behavioural and histological literature, we sought to examine the chemical profile of secretions used for scent marking by a solitary, non-territorial carnivore, the brown bear (Ursus arctos). We investigated the incidence, abundance, and uniqueness of volatile organic compounds (VOCs) from cutaneous glandular secretions of 12 wild brown bears, and assessed whether age-sex class, body site, and individual identity explained profile variation. The average number of compounds varied by age, but not solely by sex or body site. VOC profiles varied in composition and structure by age and individual identity (when individuals were grouped by sex), but not solely by sex or body site. Individual compound uniqueness varied by body site and age for both males and females and across individuals. Our results indicate that brown bear skin-borne secretions may facilitate age-sex class and individual recognition, which can contribute towards further understanding of mating systems and social behaviour.
Algorithms for team formation based on the degree distribution of the social networks
Authors: Addanki Bobby Ramesh , S Durga Bhavani 
Published: September 2022

Abstract
The problem of choosing a team for a given project/task with minimum communication cost is known as team formation problem for which many algorithms have been proposed in the literature. The skill-centric algorithms in the literature start by searching for suitable experts for each skill. These algorithms are very slow as the search requires shortest path calculations. We propose that by considering the topology of the underlying social network, the algorithms can be made more efficient. We contribute two algorithms in this paper for team formation, namely, TPLRandom and TPLClosest which exploit the power law of the degree distribution of the social network to form a team. The proposed algorithm is based on the idea that is generally adopted while a team is being formed for the real world challenges. A team leader is identified first who then sets about choosing the team members possessing the necessary skills required for the task. The algorithms choose high degree nodes from the heavy tail of the degree distribution to act as leaders. The leaders form teams from their own neighbourhoods and the one with the lowest communication cost is chosen as the best team. This is an entirely novel approach to team formation problem. We show that these high degree experts and their neighbours cover a large number of skills required for the task, reducing the expensive computations and thus yielding a fast and scalable algorithm. The experimentation is carried out on the well-known DBLP data set. We build a much larger benchmark data set from DBLP for experimentation. Our algorithms TPLClosest and TPLRandom provide teams with significantly lower communication costs. They also surpass the other conventional algorithms such as MinLD and MinSD in terms of the execution time.
An exhaustive evaluation of modeling ecological niches above species level to predict marine biological invasions
Authors: Reyes Kevin Alejandro Lopez , Olvera Luis Osorio , Soto Octavio Rojas , Chiappa-Carrara Xavier , Rivero Carlos Patrón , Arenas Carlos Yáñez 
Published: September 2022

Abstract
Identifying the areas of the world with suitable environmental conditions for the establishment of invasive species represents a fundamental basis for preventing their impacts. One of the most widely used tools for this is ecological niche modeling. Nonetheless, this approach may underestimate the specie’s physiological tolerances since wildlife populations of species usually do not occupy their entire environmental tolerance. Recently, it has been suggested that incorporating occurrences of phylogenetically related species improves the prediction of biological invasions. However, the reproducibility of this technique is unclear. Here, we evaluated the generality of this protocol by assessing whether the construction of modeling units above species level improves the capacity of niche models to predict the distribution of 26 target marine invasive species. For each, we constructed supraspecific modeling units based on published phylogenies by grouping the native occurrence records of each invasive species with the records of its phylogenetically closest relative. We also considered units at the species level, including only the presence of records in the native areas of the target species. We generated ecological niche models for each unit with two methods (minimum volume ellipsoids – MVE and machine learning algorithms – Maxent). In addition, we grouped the 26 target species based on whether or not their niches are unfilled. Our results suggest that the construction of supraspecific units improves the predictive capacity of correlative models to estimate the invasion area of our target species. However, this modeling approach consistently generated models with the higher predictive ability for species with unfilled niches.
Data pipeline for GTFS transit arrival and departure information
Authors: Chin Teck Kean , Xian Tingsen (Tim) , Marks Benjy , Nelson John D. , Moylan Emily 
Published: September 2022

Abstract
Cities generate large volumes of data daily through digital services and smart city applications, these include Public Transport Authorities which generate big data as part of their daily operations, such as vehicle positions, counts of passengers and user travel patterns. The General Transit Feed Specification (GTFS) is a data format that allows public transport data to be consumed by a wide variety of software applications. This paper presents a data pipeline developed to manipulate the GTFS feeds into a general and flexible dataset of realtime transit arrivals. There are three barriers to widespread access to the information addressed by creating a one-size-fits-all data pipeline for realtime operations from GTFS. First, the protocol buffer format is not human readable and requires processing before use in most transport applications. Secondly, the general specificationdoes vary place-to-place and the conditionally required and optional fields are inconsistent between locations. Thirdly, the raw data may contain errors including missing stop sequence or a reverse direction bus being detected in the bus stop area. The pipeline is constructed of set of data cleaning and transformation steps to address these challenges. The paper briefly presents a potential use cases of the processed data to illustrate its relevance to researchers and practitioners.
Glomerular disease after renal transplantation: a multi-center protocol biopsy study in an Iberoamerican population.
Authors: Torres Rodolfo , Reina Maricely , Montero Camilo , Andrade David , Rosselli Carlos , Agudelo Estefy , Flechas Jonth , Rodriguez Laura , Trujillo Ana , yomayusa Nancy , Quintana Luis Fernando 
Published: September 2022

Abstract

Background
Renal transplantation is the treatment of choice in end-stage renal disease (ESRD)(1, 2), nonetheless; there are still limitations in improving long-term renal graft survival in a significant way, post-transplant glomerular disease being one of the main causes of renal graft loss (3, 4).
Methods
A retrospective cohort study, with renal transplant patients in 3 centers in the city of Bogota D.C
Results
399 patients were included, 61.15% predominantly male, with a median age of 44.3 years, interquartile range (IQR) (32.9–55.9). Post-transplant glomerular
The Cardinal Role of Digital Marketing in Morocco's Agricultural Sustainable Development
Authors: PIERRE BILIVOGUI , WENFANG FENG 
Published: September 2022

Abstract

With a contribution to the national economy of more than 14%, Moroccan agricultural sector today is a strong pillar for the economic growth of the Kingdom with its many advantages not only among rural populations, but also among agricultural businesses. Agriculture is an essential pillar of the country's economy and society growth, and its performance even determines the status of the entire economy. Moreover, the country's growth rate is strongly linked to of the agricultural production. However, Morocco's agricultural sector employs almost half of the working force and provides more than 23% of the country's exports. The dynamism of the agricultural export sector has enabled the Kingdom to become one of the world's leading exporters of agricultural products. This article aims to study the benefits of Digital Marketing to Moroccan farmers, whom struggling to profits from their production at the expense of agricultural products imported from other countries that taking the advantage of Digital marketing. The conducted study is of the qualitative and descriptive type, and a documentary to analyze the role of digital marketing in the Moroccan agricultural sector, beside an indicator for the unhealthy practices derived by certain actors in the field of digital marketing. The data are collected through semi-structured interviews with communication agencies and influencers (50), agricultural companies (50), and rural farmers (300) to investigate the issue.
COVID-19 Pandemi Döneminde Eğitimde Derin Öğrenmeye Dayalı Duygu Analizi
Authors: KARGA Kemal , TOÇOĞLU Mansur Alp , ONAN Aytuğ 
Published: September 2022

Keywords: Deep Learning, Sentiment Analysis, Text Mining, COVID-19, Higher Education

Öz
2020 yılında küresel COVID-19 pandemisi, ciddi ekonomik ve toplumsal kesintilere yol açtı. Pandemi sağlık, gıda, iş organizasyonları ve eğitim dahil olmak üzere hayatımızın neredeyse her alanını etkiledi. Eğitimin dijitalleştirilmesi ile birlikte yükseköğretim alanında önemli bir değişiklik yaşanmıştır. Pandemi ile mücadele amacıyla, dünya çapında birçok yükseköğretim kurumu, eş zamanlı veya eş zamansız olarak lisans ve lisansüstü derslerini çevrimiçi olarak sunmaya başlamıştır. Bu süre zarfında insanlar haber, bilgi, destek almak için ve sosyal bağlantılar kurmak için sosyal medyadan ciddi ölçüde yararlanmaktadırlar. Bu sayede, COVID-19 ile ilgili olarak Web'de çok miktarda elektronik metin belgesi paylaşılmıştır. Bu makalede, COVID-19 salgınının yüksek öğrenim üzerindeki etkisini analiz etmek için derin öğrenime dayalı bir duygu analizi yaklaşımı sunuyoruz. Bu bağlamda, geleneksel makine öğrenimi algoritmalarının (vektör destek makineleri, naive bayes, lojistik regresyon ve rastgele orman) ve derin sinir ağlarının (evrişimli sinir ağı, tekrarlı sinir ağı, uzun süreli bellek ve gated tekrarlı birim) performansları karşılaştırılmıştır. Buna ek olarak, transformerlardan gelen çift yönlü enkoder gösterimleri (BERT) tarafından elde edilen ampirik sonuçlar da değerlendirilmiştir. Farklı metin gösterim modelleri ve sınıflandırma algoritmalarına sahip kapsamlı ampirik sonuçlar, derin sinir ağlarının COVID-19 ile ilgili metin belgelerinin yüksek eğitim üzerindeki etkisini analiz etme görevi için umut verici sonuçlar verebileceğini göstermektedir.