bluuebunny/crossref_metadata_2025_split huggingface dataset:
How Can Implementation Science Improve the Care of Familial Hypercholesterolaemia?
Authors: Sarkies Mitchell , Jones Laney K. , Pang Jing , Sullivan David , Watts Gerald F 
Published: February 2023

Abstract
Purpose of Review
Describe the application of implementation science to improve the detection and management of familial hypercholesterolaemia.

Recent Findings
Gaps between evidence and practice, such as underutilization of genetic testing, family cascade testing, failure to achieve LDL-cholesterol goals and low levels of knowledge and awareness, have been identified through clinical registry analyses and clinician surveys. Implementation science theories, models and frameworks have been applied to assess barriers and enablers in the literature specific to local contextual factors (e.g. stages of life). The effect of implementation strategies to overcome these factors has been evaluated; for example, automated identification of individuals with FH or training and education to improve statin adherence. Clinical registries were identified as a key infrastructure to monitor, evaluate and sustain improvements in care.

Summary
The expansion in evidence supporting the care of familial hypercholesterolaemia requires a similar expansion of efforts to translate new knowledge into clinical practice.
Integrating Functional Imaging and Molecular Profiling for Optimal Treatment Selection in Neuroendocrine Neoplasms (NEN)
Authors: Kong Grace , Boehm Emma , Prall Owen , Murray William K. , Tothill Richard W. , Michael Michael 
Published: February 2023

Abstract

Purpose of Review
Gastroenteropancreatic NEN (GEP-NEN) are group of malignancies with significant clinical, anatomical and molecular heterogeneity. High-grade GEP-NEN in particular present unique management challenges.

Recent Findings
In the current era, multidisciplinary management with access to a combination of functional imaging and targeted molecular profiling can provide important disease characterisation, guide individualised management and improve patient outcome. Multiple treatment options are now available, and combination and novel therapies are being explored in clinical trials.

Summary
Precision medicine is highly relevant for a heterogenous disease like NEN. The integration of dual-tracer functional PET/CT imaging, molecular histopathology and genomic data has the potential to be used to gain a more comprehensive understanding of an individual patient’s disease biology for precision diagnosis, prognostication and optimal treatment allocation.
Analytic semi-universal deformations in logarithmic complex geometry
Authors: Caputo Raffaele 
Published: February 2023

AbstractWe show that every compact complex analytic space endowed with a fine logarithmic structure and every morphism between such spaces admit a semi-universal deformation. These results generalize the analogous results in complex analytic geometry first independently proved by A. Douady and H. Grauert in the ’70. We follow Douady’s two steps process approach consisting of an infinite-dimensional construction of the deformation space followed by a finite-dimensional reduction.
A federated learning-enabled predictive analysis to forecast stock market trends
Authors: Pourroostaei Ardakani Saeid , Du Nanjiang , Lin Chenhong , Yang Jiun-Chi , Bi Zhuoran , Chen Lejun 
Published: February 2023

AbstractThis article proposes a federated learning framework to build Random Forest, Support Vector Machine, and Linear Regression models for stock market prediction. The performance of the federated learning is compared against centralised and decentralised learning frameworks to figure out the best fitting approach for stock market prediction. According to the results, federated learning outperforms both centralised and decentralised frameworks in terms of Mean Square Error if Random Forest (MSE = 0.021) and Support Vector Machine techniques (MSE = 37.596) are used, while centralised learning (MSE = 0.011) outperforms federated and decentralised frameworks if a linear regression model is used. Moreover, federated learning gives a better model training delay as compared to the benchmarks if Linear Regression (time = 9.7 s) and Random Forest models (time = 515 s) are used, whereas decentralised learning gives a minimised model training delay (time = 3847 s) for Support Vector Machine.
Application of geophysical techniques for shallow groundwater investigation using 1D-lateral constrained and 2D inversions in Ras Gara area, southwestern Sinai, Egypt
Authors: Genedi Mohamed A. , Youssef Mohamed A. S. 
Published: February 2023

AbstractThere is an urgent need for greater water resources to support sustainable development in Ras Gara area of southwestern Sinai. Determining the water-bearing zones of the shallow Quaternary aquifer of the Araba Formation in the study region is therefore the main objective of the research. This will be done by using a variety of geophysical techniques, such as DC resistivity sounding and shallow seismic refraction surveys. Using the Schlumberger array (max. AB = 1200 m), the DC data were gathered at 27 VES locations along five primary profiles. At the same locations, 27 spreads totaling 115 m in length of seismic data were also performed. One-dimensional laterally constrained (1D-LCI) inversion is only applied to the DC data in order to generate a best-fit model, whereas 2D inversion is applied to other datasets. The area is divided up into five geo-electrical layers based on the results of 1D-LCI inversion of DC data, and the aquifer is classified into fresh (third layer) and saline bearing-zones (fourth layer). The resistivity values of the fresh-zone range from 8.7 to 26.7 Ω.m, with only low values (5–7.5 Ω.m) found at some VES sites, while the resistivity values of the saline-zone range between 0.9 and 3 Ω.m, except for (14.4 Ω.m) at VES-04. At depths of (2.4–15.6 m) and (8.7–28.5 m) for the fresh and saline zones, respectively. In this region, the shallow low resistive (about 10–100 Ω.m) and intermediate high conductive (< 10 Ω.m) layers of the 2D-DC inverted model represent the fresh and saline zones of the aquifer, respectively. The basement rocks were represented by a deep, extremely high resistive layer that can reach 40,000 Ω.m. Three subsurface layers are identified from the results of the 2D inversion of seismic data (VP1 = 400–1100 m.s−1, VP2 = 1200–1900 m.s−1 and VP3 = 2400–5400 m.s−1). The saturated zone of this aquifer is represented by the second layer (depth, 3.7–20.5 m). The basement rocks are also reflected in the last layer of high velocity. The inversion results and the previously available hydro-geological map data show a good degree of concordance. In the eastern portion of the study area, additional water wells could be drilled for additional water resources.
Transcriptomic analysis predicts the risk of progression of premalignant lesions in human tongue
Authors: Zhang Tuo , Kutler David , Scognamiglio Theresa , Gudas Lorraine J. , Tang Xiao-Han 
Published: February 2023

AbstractThe 5-year survival rate for patients with oral squamous cell carcinomas (SCC), including tongue SCC, has not significantly improved over the last several decades. Oral potentially malignant disorders (OPMD), including oral dysplasias, are oral epithelial disorders that can develop into oral SCCs. To identify molecular characteristics that might predict conversion of OPMDs to SCCs and guide treatment plans, we performed global transcriptomic analysis of human tongue OPMD (n = 9) and tongue SCC (n = 11) samples with paired normal margin tissue from patients treated at Weill Cornell Medicine. Compared to margin tissue, SCCs showed more transcript changes than OPMDs. OPMDs and SCCs shared some altered transcripts, but these changes were generally greater in SCCs than OPMDs. Both OPMDs and SCCs showed altered signaling pathways related to cell migration, basement membrane disruption, and metastasis. We suggest that OPMDs are on the path toward malignant transformation. Based on patterns of gene expression, both OPMD and tongue SCC samples can be categorized into subclasses (mesenchymal, classical, basal, and atypical) similar to those seen in human head and neck SCC (HNSCC). These subclasses of OPMDs have the potential to be used to stratify patient prognoses and therapeutic options for tongue OPMDs. Lastly, we identified a gene set (ELF5; RPTN; IGSF10; CRMP1; HTR3A) whose transcript changes have the power to classify OPMDs and SCCs and developed a Firth logistic regression model using the changes in these transcripts relative to paired normal tissue to validate pathological diagnosis and potentially predict the likelihood of an OPMD developing into SCC, as data sets become available.
Circ_0000182 promotes cholesterol synthesis and proliferation of stomach adenocarcinoma cells by targeting miR-579-3p/SQLE axis
Authors: Qian Cui-juan , Zhou Yu-xin , Wu Lin-ken , Wang Yi-chao , Teng Xiao-sheng , Yao Jun 
Published: February 2023

Abstract
Background
Circular RNAs (circRNAs) or cholesterol metabolism have been demonstrated to participate in stomach adenocarcinoma (STAD) progression. However, the relationship between circRNAs and cholesterol metabolism in STAD and its underlined mechanism remain unclear.

Methods
RNA and protein expression levels were detected by qRT-PCR and Western blot. Cell proliferation was assessed by CCK-8, EdU incorporation and colony formation assays. Total cholesterol (TC) and free cholesterol (FC) levels were measured by the corresponding kits. The relationships between circ_0000182 and miR-579-3p or squalene epoxidase (SQLE) mRNA were investigated by bioinformatics analysis, RNA-RNA pull-down, luciferase reporter and RIP assays.

Results
We found that circ_0000182 expression was significantly up-regulated in both STAD tissues and cell lines, and high circ_0000182 expression was correlated with increased tumor size. Circ_0000182 promoted cell proliferation and cholesterol synthesis of STAD cells. Accordingly, cell proliferation, cholesterol synthesis and SQLE expression were significantly inhibited by circ_0000182 knockdown in STAD cells, and these effects were partly reversed by miR-579-3p inhibition or SQLE over-expression. Furthermore, we identified that circ_0000182 acted as a competing endogenous RNA (ceRNA) by sponging miR-579-3p, thereby facilitating SQLE expression, cholesterol synthesis and cell proliferation.

Conclusion
Circ_0000182 promotes cholesterol synthesis and proliferation of STAD cells by enhancing SQLE expression via sponging miR-579-3p.
Prostitution Under Debate in Spain: Citizens’ Perceptions of Its Prohibition
Authors: Méndez-Juez Marta , García-Santamaría Sandra , Pérez-Castaños Sergio 
Published: February 2023

Abstract
Introduction
The debate about prostitution within Spain’s feminist movement has recently, and recurrently, been transferred to the social and political sphere, but without arriving at a clear and shared position. The aim of this research is to verify the characteristics of those who are in favor of banning prostitution in Spain and to what extent there are differences between men and women.

Methods
To do so, we will use our own collected data during 2022 through a prestigious social research company, 40 dB, and by applying advanced statistical techniques—Logit model.

Results
The analysis illustrates three types of profile. The first one depicts the prohibitionist’s supporter profile in general terms. The second and the third ones demonstrate how women and men share similarities but also underlying differences, showing how women are more inclined than men to the prohibitionist approach.

Conclusions
This paper comes to validate, once again, most of the previous theoretical supported evidences, but not the religious element as a defining variable for being a banning supporter. The data also shows the possible consensus of those surveyed on this issue across different political parties.

Policy Implications
The implications of all kinds that arise around prostitution generate different public perceptions about its existence and practice, with its prohibition being one of the most important issues on the Spanish public agenda in recent months. This article depicts how the Spanish society positions itself in this policy agenda.
Moving Beyond Benchmarks and Competitions: Towards Addressing Social Media Challenges in an Educational Context
Authors: Ognibene Dimitri , Donabauer Gregor , Theophilou Emily , Buršić Sathya , Lomonaco Francesco , Wilkens Rodrigo , Hernández-Leo Davinia , Kruschwitz Udo 
Published: February 2023

AbstractNatural language processing and other areas of artificial intelligence have seen staggering progress in recent years, yet much of this is reported with reference to somewhat limited benchmark datasets.We see the deployment of these techniques in realistic use cases as the next step in this development. In particular, much progress is still needed in educational settings, which can strongly improve users’ safety on social media. We present our efforts to develop multi-modal machine learning algorithms to be integrated into a social media companion aimed at supporting and educating users in dealing with fake news and other social media threats.Inside the companion environment, such algorithms can automatically assess and enable users to contextualize different aspects of their social media experience. They can estimate and display different characteristics of content in supported users’ feeds, such as ‘fakeness’ and ‘sentiment’, and suggest related alternatives to enrich users’ perspectives. In addition, they can evaluate the opinions, attitudes, and neighbourhoods of the users and of those appearing in their feeds. The aim of the latter process is to raise users’ awareness and resilience to filter bubbles and echo chambers, which are almost unnoticeable and rarely understood phenomena that may affect users’ information intake unconsciously and are unexpectedly widespread.The social media environment is rapidly changing and complex. While our algorithms show state-of-the-art performance, they rely on task-specific datasets, and their reliability may decrease over time and be limited against novel threats. The negative impact of these limits may be exasperated by users’ over-reliance on algorithmic tools.Therefore, companion algorithms and educational activities are meant to increase users’ awareness of social media threats while exposing the limits of such algorithms. This will also provide an educational example of the limits affecting the machine-learning components of social media platforms.We aim to devise, implement and test the impact of the companion and connected educational activities in acquiring and supporting conscientious and autonomous social media usage.
Metallographic Investigation of the Bronze Sword from Vértesszőlős
Authors: Gyöngyösi Szilvia , Szabó Géza , Barkóczy Péter , Cseh Julianna 
Published: February 2023

AbstractThe area of Vértesszőlős was a populated area during the wide period of the Bronze Age. Artifacts from different cultures, and among them, many bronze objects were found. Most are ornaments, but tools and weapons have also been unearthed. The weapons found are a fragment of a sword, a blade tip fragment, and a dagger. The primary purpose of the study is the metallographic analysis of the objects to reveal the characteristics of their alloys and the manufacturing technique. It is also important from the point of view of identifying the basic copper alloy groups based on many test results. The study of the microstructure also provides new knowledge for this, and it also allows to determine the manufacturing technique. The purpose of the tests shall be to establish a detailed metallographic examination and compositional and manufacturing information.
Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK
Authors: Zhou Junwen , Wu Runguo , Williams Claire , Emberson Jonathan , Reith Christina , Keech Anthony , Robson John , Wilkinson Kenneth , Armitage Jane , Gray Alastair , Simes John , Baigent Colin , Mihaylova Borislava 
Published: February 2023

Abstract
Objectives
The aim of this study was to develop prediction models for the individual-level impacts of cardiovascular events on UK healthcare costs.

Methods
In the UK Biobank, people 40–70 years old, recruited in 2006–2010, were followed in linked primary (N = 192,983 individuals) and hospital care (N = 501,807 individuals) datasets. Regression models of annual primary and annual hospital care costs (2020 UK£) associated with individual characteristics and experiences of myocardial infarction (MI), stroke, coronary revascularization, incident diabetes mellitus and cancer, and vascular and nonvascular death are reported.

Results
For both people without and with previous cardiovascular disease (CVD), primary care costs were modelled using one-part generalised linear models (GLMs) with identity link and Poisson distribution, and hospital costs with two-part models (part 1: logistic regression models the probability of incurring costs; part 2: GLM with identity link and Poisson distribution models the costs conditional on incurring any). In people without previous CVD, mean annual primary and hospital care costs were £360 and £514, respectively. The excess primary care costs were £190 and £360 following MI and stroke, respectively, whereas excess hospital costs decreased from £4340 and £5590, respectively, in the year of these events, to £190 and £410 two years later. People with previous CVD had more than twice higher annual costs, and incurred higher excess costs for cardiovascular events. Other characteristics associated with higher costs included older age, female sex, south Asian ethnicity, higher socioeconomic deprivation, smoking, lower level of physical activities, unhealthy body mass index, and comorbidities.

Conclusions
These individual-level healthcare cost prediction models could inform assessments of the value of health technologies and policies to reduce cardiovascular and other disease risks and healthcare costs. An accompanying Excel calculator is available to facilitate the use of the models.
Urinary nephrin—a potential marker of early glomerular injury: a systematic review and meta-analysis
Authors: Mesfine Belete Biadgo , Vojisavljevic Danica , Kapoor Ranjna , Watson David , Kandasamy Yogavijayan , Rudd Donna 
Published: February 2023

Abstract
Background
Both early recognition of glomerular injury and diagnosis of renal injury remain important problems in clinical settings, and current diagnostic biomarkers have limitations. The aim of this review was to determine the diagnostic accuracy of urinary nephrin for detecting early glomerular injury.

Methods
A search was conducted through electronic databases for all relevant studies published until January 31, 2022. The methodological quality was evaluated using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled sensitivity, specificity, and other estimates of diagnostic accuracy were determined using a random effect model. The Summary Receiver Operating Characteristics (SROC) was used to pool the data and to estimate the area under the curve (AUC).

Results
The meta-analysis included 15 studies involving 1587 participants. Overall, the pooled sensitivity of urinary nephrin for detecting glomerular injury was 0.86 (95% CI 0.83–0.89) and specificity was 0.73 (95% CI 0.70–0.76). The AUC-SROC to summarise the diagnostic accuracy was 0.90. As a predictor of preeclampsia, urinary nephrin showed a sensitivity of 0.78 (95% CI 0.71–0.84) and specificity of 0.79 (95% CI 0.75–0.82), and as a predictor of nephropathy the sensitivity was 0.90 (95% CI 0.87–0.93), and specificity was 0.62 (95% CI 0.56–0.67). A subgroup analysis using ELISA as a method of diagnosis showed a sensitivity of 0.89 (95% CI 0.86–0.92), and a specificity of 0.72 (95% CI 0.69–0.75).

Conclusion
Urinary nephrin may be a promising marker for the detection of early glomerular injury. ELISA assays appear to provide reasonable sensitivity and specificity. Once translated into clinical practice, urinary nephrin could provide an important addition to a panel of novel markers to help in the detection of acute and chronic renal injury.

Graphical abstract
Effect of chemical corrosion on propagation of complex fracture networks under different hydraulic pressures in enhanced geothermal systems
Authors: Liu Lanfu , Li Zhicong , Wu Jiangyu , Yu Liyuan , Li Shuchen , Liu Richeng 
Published: February 2023

AbstractChemical corrosion and hydraulic fracturing are important ways to improve the permeability of the enhanced geothermal systems. In this work, we developed a discrete element code for simulating the hydraulic fracturing of three different fracture network models after chemical corrosion. Mechanisms of the crack extension and coalescence in the field-scale models with fracture network were systematically revealed, in which the effects of corrosion time, inclination of the fracture (γ), pH value and hydraulic pressure were considered. The results show that the simulated cracking behaviors of granites agree well with those obtained through Brazilian tests and triaxial compression tests, verifying the validity of the developed discrete element code. During hydraulic fracturing, the impact of γ on the fracture network connectivity increases with the increment of hydraulic pressure (Pin). With the increase in hydraulic pressure, crack propagation accelerates whereas the connectivity of fracture network models decreases. The reasons are that the excessive hydraulic pressure causes the crack to spread in an unfavorable direction and increases the effect of γ on the connectivity of models of fracture networks. As the pH value increases from 2 to 12, the crack growth rate first decreases and subsequently raises. The numbers of cracks per time step of sparse mixed fracture networks with artificial fractures (SM), dense mixed fracture networks with artificial fractures (DM) and dense mixed fracture networks without artificial fractures (NDM) are in the ranges of 0.06601–0.1259, 0.05176–0.2072 and 0.1727–0.6846, respectively. The connectivity of SM is better than that of NDM under the same hydraulic fracturing conditions, indicating that artificial fractures can greatly improve the fracture network connectivity and the utilization efficiency of EGS.
Design and guidance of a multi-active debris removal mission
Authors: Wijayatunga Minduli C. , Armellin Roberto , Holt Harry , Pirovano Laura , Lidtke Aleksander A. 
Published: February 2023

AbstractSpace debris have become exceedingly dangerous over the years as the number of objects in orbit continues to increase. Active debris removal (ADR) missions have gained significant interest as effective means of mitigating the risk of collision between objects in space. This study focuses on developing a multi-ADR mission that utilizes controlled reentry and deorbiting. The mission comprises two spacecraft: a Servicer that brings debris to a low altitude and a Shepherd that rendezvous with the debris to later perform a controlled reentry. A preliminary mission design tool (PMDT) was developed to obtain time and fuel optimal trajectories for the proposed mission while considering the effect of J2, drag, eclipses, and duty cycle. The PMDT can perform such trajectory optimizations for multi-debris missions with computational time under a minute. Three guidance schemes are also studied, taking the PMDT solution as a reference to validate the design methodology and provide guidance solutions to this complex mission profile.