bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Application of Potential Field Gravity Method in Characterizing Regional-trends of the Earth’s Sequence System over the Sokoto Basin, NW, Nigeria
Authors: Abubakar Adamu , K. Likkason Othniel 
Published: March 2022

In this chapter some preliminaries evaluation were outline briefly based on exploring the use of potential gravity field method in characterizing regional trends of Earth’s sequence system interms of gravitational potentials and fields, viz-a-viz., the background, instrumentation, theoretical model, gravity data reduction, geological framework, Bouguer reduction density, density acceptable models, free-air anomaly and interpretation of Bouguer gravity anomaly. Therefore, application of potential field method (gravity) explore these relationships by focusing on the formation and fill of a continental rift basin in characterizing regional trends of the Earth’s system interms of data processing, interpretation and Earth’s modelling. The study was carried out with the aim to understand and characterized the structural styles and regional trends of the Earth’s sequence beneath the Sokoto Basin and its surroundings. Results from the Bouguer gravity anomaly revealed gravity high of characteristic feature on the Bouguer map with a strong positive oval shape of causative bodies anomaly (> −14.0 mGal) having E-W trend. On contrary a number of gravity minima (−43.31 mGal) and maxima (−39.54 mGal) can be found ENE, N-W parts which are almost defining locations of deep basinal areas. The anomalous features shows negative as well as the lineaments pattern are virtually oriented in the NW-SE, ENE and E-W trends.
Cystic Granulosa Cell Tumors of the Ovary: An Analysis of 80 Cases of an Often Diagnostically Challenging Entity
Authors: Boyraz Baris , Watkins Jaclyn C. , Soubeyran Isabelle , Bonhomme Benjamin , Croce Sabrina , Oliva Esther , Young Robert H. 
Published: March 2022

Context.—
Granulosa cell tumors (GCTs) of both adult (AGCT) and juvenile (JGCT) types can rarely be completely or dominantly cystic, creating diagnostic difficulty because the cyst lining epithelium is often denuded.

Objective.—
To describe clinical, gross, microscopic, immunohistochemical, and molecular features of cystic GCTs with an emphasis on their differential diagnosis.

Design.—
We report 80 cystic GCTs (24 AGCTs and 56 JGCTs) in patients from ages 3 to 83 years (average ages, 35 years for AGCT and 22 years for JGCT).

Results.—
Nineteen of 43 patients with known clinical information (3 AGCT and 16 JGCT) had androgenic manifestations. All tumors were greater than 8 cm (average, 17 cm) with minimal to absent gross solid component. Denudation of cells lining the cysts was prominent. Invagination of the epithelium into the cyst walls was a key diagnostic feature, was present as cords, trabeculae, solid nests, and small and large follicles, and was identified in most tumors (17 AGCTs and 45 JGCTs). Cytologic atypia was essentially absent in AGCTs, whereas 14 JGCTs showed moderate to severe atypia of bizarre type. A theca cell component was present in all tumors and was extensive in 54. A FOXL2 hotspot mutation was identified in 1 of 4 AGCTs tested.

Conclusions.—
Despite extensive denudation, the finding of typical architectural patterns and cytologic features as well as, in some cases, androgenic manifestations helps differentiate cystic GCTs from follicle cysts, the most common and challenging differential diagnosis, as well as other cystic neoplasms that may enter the differential diagnosis. FOXL2 sequencing may show a false-negative result in cystic AGCT because of the limited number of cells present within the tumor sample.
RNA sequencing reveals the emerging role of bronchoalveolar lavage fluid exosome lncRNAs in acute lung injury
Authors: Song Meijuan , Zhang Xiuwei , Gao Yizhou , Wan Bing , Wang Jinqiang , Li Jinghang , Song Yuanyuan , Shen Xiaowei , Wang Li , Huang Mao , Wang Xiaowei 
Published: March 2022

Background
Bronchoalveolar lavage fluid (BALF) exosomes possess different properties in different diseases, which are mediated through microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), among others. By sequencing the differentially expressed lncRNAs in BALF exosomes, we seek potential targets for the diagnosis and treatment of acute lung injury (ALI).

Methods
Considering that human and rat genes are about 80% similar, ALI was induced using lipopolysaccharide in six male Wistar rats, with six rats as control (all weighing 200 ± 20 g and aged 6–8 weeks). BALF exosomes were obtained 24 h after ALI. The exosomes in BALF were extracted by ultracentrifugation. The differential expression of BALF exosomal lncRNAs in BALF was analyzed by RNA sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the functions of differentially expressed lncRNAs, which were confirmed by reverse transcription–polymerase chain reaction.

Results
Compared with the control group, the ALI group displayed a higher wet/dry ratio, tumor necrosis factor-α levels, and interleukin-6 levels (all P < 0.001). The airway injection of exosomes in rats led to significant infiltration by neutrophils. A total of 2,958 differentially expressed exosomal lncRNAs were identified, including 2,524 upregulated and 434 downregulated ones. Five lncRNAs confirmed the reliability of the sequencing data. The top three GO functions were phagocytic vesicle membrane, regulation of receptor biosynthesis process, and I-SMAD binding. Salmonella infection, Toll-like receptor signaling pathway, and osteoclast differentiation were the most enriched KEGG pathways. The lncRNA–miRNA interaction network of the five confirmed lncRNAs could be predicted using miRDB.

Conclusions
BALF-derived exosomes play an important role in ALI development and help identify potential therapeutic targets related to ALI.
Bioinformatical analysis identifies PDLIM3 as a potential biomarker associated with immune infiltration in patients with endometriosis
Authors: Gan Lei , Sun Jiani , Sun Jing 
Published: March 2022

Background
Endometriosis is a chronic systemic disease, whose classic symptoms are pelvic pain and infertility. This disease seriously reduces the life quality of patients. The pathogenesis, recognition and treatment of endometriosis is still unclear, and cannot be over emphasized. The aim of our study was to investigate the potential biomarker of endometriosis for the mechanism and treatment.

Methods
Using GSE11691, GSE23339 and GSE5108 datasets, differentially expressed genes (DEGs) were identified between endometriosis and normal samples. The functions of DEGs were reflected by the analysis of gene ontology (GO), pathway enrichment and gene set enrichment analysis (GSEA). The LASSO regression model was performed to identify candidate biomarkers. The receiver operating characteristic curve (ROC) was used to evaluate discriminatory ability of candidate biomarkers. The predictive value of the markers in endometriosis were further validated in the GSE120103 dataset. Then, the expression level of biomarkers was detected by qRT-PCR and Western blot. Finally, the relationship between candidate biomarker expression and immune infiltration was estimated using CIBERSORT.

Results
A total of 42 genes were identified, which were mainly involved in cytokine–cytokine receptor interaction, systemic lupus erythematosus and chemokine signaling pathway. We confirmed PDLIM3 was a specific biomarker in endometriosis (AUC = 0.955) and validated in the GSE120103 dataset (AUC = 0.836). The mRNA and protein expression level of PDLIM3 in endometriosis tissue was significantly higher than normal. Immune cell infiltration analysis revealed that PDLIM3 was correlated with M2 macrophages, neutrophils, CD4+ memory resting T cells, gamma delta T cells, M1 Macrophages, resting mast cells, follicular helper T cells, activated NK cells, CD8+ T cells, regulatory T cells (Tregs), naive B cells, plasma cells and resting NK cells.
Epidemiology of Musculoskeletal Manifestations in Pediatric Inflammatory Bowel Disease: A Systematic Review
Authors: Ali Aaisham , Schmidt Melanie , Piskin David , Crowley Eileen , Berard Roberta 
Published: March 2022

ObjectivePediatric inflammatory bowel disease (p‐IBD) is a chronic relapsing gastrointestinal disorder of childhood with long‐term morbidity. Several extraintestinal manifestations are described, the most common being joint pain and/or inflammation. However, patient and disease characteristics, treatments, and outcomes of p‐IBD‐associated musculoskeletal disease are not well established. Our study aims to summarize the recent literature on the epidemiology of musculoskeletal manifestations in p‐IBD in the era of biologics.MethodsA systematic search of PubMed, Embase, Cochrane Library, Web of Science Core Collection, and Cumulative Index to Nursing and Allied Health Literature databases was performed with relevant keywords. Studies in English published from January 1, 2000, to December 21, 2020, were included. In total, 3893 articles were identified and screened. Study and population characteristics and outcomes of interest were recorded. Risk of bias assessment was performed using the Joanna Briggs Institute Critical Appraisal Tools.ResultsThirteen studies were included for full review, which were primarily single‐center observational studies with retrospective or cross‐sectional designs. The diagnostic criteria and definitions used for musculoskeletal manifestations varied. Musculoskeletal manifestation prevalence ranged from 2% to 35%. Only one study assessed the response of musculoskeletal manifestations to biologics. Risk of bias demonstrated heterogeneity in study quality.ConclusionThis is the first systematic review of musculoskeletal manifestations in p‐IBD. Analysis was limited because of variability in study design and data‐reporting methods. Definitions varied among included studies, with a clear lack in standardization. Our study demonstrates the need for standardized assessment of musculoskeletal manifestations of p‐IBD and further research to explore optimal management to advance care for this group of children.
Chronic airway disease in primary ciliary dyskinesia—spiced with geno–phenotype associations
Authors: Nielsen Kim G , Holgersen Mathias G , Crowley Suzanne , Marthin June K 
Published: March 2022

AbstractPrimary ciliary dyskinesia (PCD) can be defined as a multiorgan ciliopathy with a dominant element of chronic airway disease affecting the nose, sinuses, middle ear, and in particular, the lower airways. Although most patients with PCD are diagnosed during preschool years, it is obvious that the chronic lung disease starts its course already from birth. The many faces of the clinical picture change, as does lung function, structural lung damage, the burden of infection, and of treatment throughout life. A markedly severe neutrophil inflammation in the respiratory tract seems pervasive and is only to a minimal extent ameliorated by a treatment strategy, which is predominantly aimed at bacterial infections. An ever‐increasing understanding of the different aspects, their interrelationships, and possible different age courses conditioned by the underlying genotype is the focus of much attention. The future is likely to offer personalized medicine in the form of mRNA therapy, but to that end, it is of utmost importance that all patients with PCD be carefully characterized and given a genetic diagnosis. In this narrative review, we have concentrated on lower airways and summarized the current understanding of the chronic airway disease in this motile ciliopathy. In addition, we highlight the challenges, gaps, and opportunities in PCD lung disease research.
Stability of conformable stochastic systems depending on a parameter
Authors: Ben Makhlouf Abdellatif , Mchiri Lassaad , Rhaima Mohamed , Hammami Mohamed Ali 
Published: March 2022

AbstractIn this work, we study the almost sure exponential stability (A.S.E.S) and the exponential stability in p‐th moment (E.S.P.M) of conformable stochastic systems depending on a parameter (CSSP) by using the Lyapunov methods and the classical stochastic analysis techniques. In the last section, we apply the main result for an illustrative example.
Membrane Anchorage‐Induced (MAGIC) Knockdown of Non‐synonymous Point Mutations**
Authors: Ulaganathan Vijay Kumar 
Published: March 2022

AbstractThe promise of personalized medicine for monogenic and complex polygenic diseases depends on the availability of strategies for targeted inhibition of disease‐associated polymorphic protein variants. Loss of function variants, including non‐synonymous single nucleotide variants (nsSNVs) and insertion/deletion producing a frameshift, account for the vast majority of disease‐related genetic changes. Because it is challenging to interpret the functional consequences of nsSNVs, they are considered a big barrier for personalized medicine. A method for inhibiting the specific expression of nsSNVs without editing the human genome will facilitate the elucidation of the biology of nsSNVs, but such a method is currently lacking. Here, I describe the phenomenon of membrane anchorage‐induced (MAGIC) knockdown and allele‐specific inhibition of protein and mRNA expression upon inner membrane tethering of point mutation‐specific monoclonal antibodies (mAb). This phenomenon is likely mediated by a mechanism distinct from the protein degradation pathways, as the epitope‐specific knockdown is replicated upon intracellular expression of a membrane‐anchored single domain intrabody that lacks the Fc domain of the mAb. By harnessing the MAGIC knockdown of epitope‐containing protein targets, I report a novel approach for inhibiting the expression of amino‐acid‐altering germline and somatic nsSNVs. As a proof‐of‐concept, I show the inhibition of human disease‐associated variants namely, FGFR4 p.G388R, KRAS p.G12D and BRAF p.V600E protein variants. This method opens up a new avenue for not just therapeutic suppression of undruggable protein variants, but also for functional interrogation of the nsSNVs of unknown significance.
Internet of medical things‐based multitiered and hybrid architectural framework for effective heart disease prediction model
Authors: Raghavan Nair Lalitha Priya , Jinny S. Vinila 
Published: March 2022

AbstractCardiovascular and chronic respiratory diseases are becoming a global threat. The alarming fact about Cardio‐vascular diseases (CVD) is that rural areas are recording a high number of heart failures compared to urban areas. The proposed research work intends to create an effective medical setup in country‐wide through Internet of Medical Things (IoMT)‐based multitiered and hybrid architectural framework and Machine Learning (ML) model. The proposed architecture collects the medical data using the IoMT devices. During data preprocessing, categorical data are encoded using one‐hot mechanism and is normalized using standard scalar technique. In addition, feature selection mechanisms are applied to choose the best significant features using hybrid sequence of Filter—Wrapper—Ensemble approach. To reduce the diagnostic barriers in health prediction model, an efficient method of Bayesian optimization for hyperparameter tuning and k‐fold cross‐validation resampling technique is applied to evaluate various conventional and ensemble ML techniques. The prediction results show the high accuracy of 86.47% and 85.81% using Logistic Regression and Extreme Gradient Boosting (XGBoosting) algorithm, respectively. In particular, the accuracy obtained using decision tree for the proposed approach is higher (80.53%) than that of existing approach (73.22%).
Aggregation‐Induced Emission, Mechanofluorochromism, and Selective Fluoride Detection by a Tripodal Salicylaldimine
Authors: Marandi Parvati , Tyagi Nidhi , Neelakandan Prakash P. 
Published: March 2022

AbstractFluoride ions are indispensable in biology and environmental science and hence the selective and sensitive detection of fluoride is important. This work reports the design and synthesis of a tripodal Schiff's base 1 through a simple condensation reaction between a commercially available aldehyde and an amine. Single crystal X‐ray crystallography revealed that compound 1 is a planar entity with the three salicylidene derivatives on the three arms of the central phenyl moiety linked by imine groups. Compound 1 forms a molecular dimer that resembles a six‐petal flower and is stabilized through multiple intermolecular interactions such as C−H.π and π.π interactions. Compound 1 exhibited moderately good emission in the solid state with aggregation induced emission and reversible mechanofluorochromic properties. Moreover, 1 was observed to selectively detect fluoride among various anions with a limit of detection of ∼9 ppm. Compound 1 was also capable of detecting fluoride under a variety of conditions such as in thin films and under cellular conditions.
An automated machine learning methodology for the improved prediction of reference evapotranspiration using minimal input parameters
Authors: Mangalath Ravindran Sowmya , Moorakkal Bhaskaran Santosh Kumar , K. Ambat Sooraj , Balakrishnan Kannan , Manguttathil Gopalakrishnan Manoj 
Published: March 2022

AbstractAn accurate and minimal meteorological parameter‐based reference evapotranspiration (ETo) computational model is highly essential to design a cost‐effective and automated solution for precise water allocation in various agricultural and hydrological applications. Automated machine learning (AutoML), a substantially progressive machine learning (ML) paradigm, expedites the data science applications in these domains by automating and alleviating the tedious tasks of developing ML pipelines, particularly in non‐linear hydrological process modelling. This paper proposes an AutoML solution for daily EToprediction in a limited input parameter scenario, for the first time in EToestimation research. Two AutoML frameworks, AutoGluon‐Tabular (AGT) and H2O AutoML were implemented using daily meteorological data of a humid tropical climatic region of Kerala, India and evaluated its performance with the radiation‐based empirical methods and traditional ML methods. The developed AutoML models imitated the input parameter combinations of radiation‐based empirical models such as Priestley‐Taylor, Makkink, Turc and Ritchie, with the Penman‐Monteith EToserving as the target for modelling process. An improvement of mean absolute error from 0.119 to 0.078 mm/day, mean squared error from 0.035 to 0.017 mm/day, root mean squared error from 0.186 to 0.129 mm/day, root mean squared logarithmic error from 0.078 to 0.026 mm/day, and coefficient of determination (R2) from 0.971 to 0.985 observed in the AutoML model, AGT relative to the empirical model, Turc describes its enhanced performance capability. For demonstrating the superiority of AutoML to traditional ML techniques, another set of AutoML models were also developed based on California Irrigation Management Information System datasets and evaluated them with existing study results in literature. The overall result analysis demonstrated the superiority of AGT model in EToprediction in all the weather stations considered in this study. The results of the study confirm that AutoML techniques can be applied to any hydrological dataset and provide an effective automated solution for hydrological process modelling.
The effect of smart fertigation systems on chilli grown in a greenhouse for urban farming
Authors: Cui Hairu , Hanafi Marsyita , Fazlil Ilahi Wan Fazilah , Zamri Mohd Amir Sabrin , Shafie Siti Mariam , Mashohor Syamsiah 
Published: March 2022

AbstractReasonable fertigation methods are essential for plant growth, as excessive or inadequate water and fertilizer supply can lead to plant diseases, resource consumption, or even crop production reduction. These problems are common to local farmers in Malaysia, especially for large‐scale chilli cultivation using traditional irrigation approaches in rural areas. These problems need to be addressed, as chilli are one of Malaysia's high‐cash crops with massive local demands. Realizing an efficient irrigation control approach using an innovative fertigation method is a potential solution to tackle such problems. This paper proposes a smart fertigation system for chilli cultivation in greenhouses in urban areas to increase chilli production and improve irrigation management. The proposed system utilized the fuzzy logic method for intelligent irrigation decisions, where the decision is based on the input data provided by soil moisture, temperature, and humidity sensors. In addition, the proposed system can monitor and control irrigation in the greenhouse remotely through a website that was developed using the Hostinger platform. The results showed that the fuzzy‐based fertigation approach produced approximately 50% irrigation application efficiency and a higher growth gradient and chilli yield than the traditional approach in both cycles.
Social media: An essential capability for business effectiveness?
Authors: Rodríguez Gutiérrez Paola Isabel , Pastor Pérez María del Pilar , Collado Agudo Jesús 
Published: March 2022

AbstractThe issue of social media is rather new and unexplored in comprehending how this capability can improve effectiveness in emerging economies, in particular, that of the companies classified as micro, small and medium‐sized (MSMEs). It is argued that some company and manager characteristics may affect the role of social media in business performance, therefore this research attempts to answer the following questions: Does the use of social media contribute to improving performance of MSMEs? How does the relationship behave according to the characteristics of the company and those of the manager? For this purpose, the resource‐based view of the firm is used as a framework of the analysis, which was carried out with data collected before the COVID pandemic. To validate the proposed hypotheses, we used Structural Equation Model (SEM) with a sample of 229 Mexican enterprises. The main contribution of this study is twofold: providing empirical evidence on the existence of influence from social media capability to the business performance and effectiveness of MSMEs in a Latin American emergent economy, even before the imposition of radical constraints by the pandemic; and the key theoretical implication is a better understanding of the nature of this influence.