bluuebunny/crossref_metadata_2025_split huggingface dataset:
miR-146a-5p-mediated suppression on trophoblast cell progression and epithelial-mesenchymal transition in preeclampsia
Authors: Peng Pingping , Song Huamei , Xie Chenghong , Zheng Wenfei , Ma Huigai , Xin Dandan , Zhan Jingqiong , Yuan Xiaoqing , Chen Aihua , Tao Jing , Qin Jufang 
Published: September 2021

Abstract
Objective
This study aims to identify the effect of miR-146a-5p on trophoblast cell invasion as well as the mechanism in preeclampsia (PE).

Methods
Expression levels of miR-146a-5p and Wnt2 in preeclamptic and normal placentae were quantified. Trophoblast cells (HTR-8) were separately transfected with miR-146a-5p mimic, miR-146a-5p inhibitor, pcDNA3.1-Wnt2 or sh-Wnt2, and then the expression levels of miR-146a-5p, Wnt2, and epithelial-mesenchymal transition (EMT)-related proteins (Vimentin, N-cadherin and E-cadherin) were measured. Moreover, the proliferative, migratory and invasive capacities of trophoblast cells were detected, respectively. Dual luciferase reporter assay determined the binding of miR-146a-5p and Wnt2.

Results
Compared with normal placental tissues, the placentae from PE patients showed higher miR-146a-5p expression and lower Wnt2 expression. Transfection of miR-146a-5p inhibitor or pcDNA3.1-Wnt2 exerted pro-migratory and pro-invasive effects on HTR-8 cells and encouraged EMT in HTR-8 cells; transfection with miR-146a-5p mimic or sh-Wnt2 weakened the proliferative, migratory and invasive capacities as well as reduced EMT process of HTR-8 cells. Moreover, Wnt2 overexpression could partially counteract the suppressive effects of miR-146a-5p overexpression on the progression and EMT of HTR-8 cells.

Conclusion
miR-146a-5p mediates trophoblast cell proliferation and invasion through regulating Wnt2 expression.
Non-invasive health prediction from visually observable features
Authors: Khong Fan Yi , Connie Tee , Goh Michael Kah Ong , Wong Li Pei , Teh Pin Shen , Choo Ai Ling 
Published: September 2021

Background: The unprecedented development of Artificial Intelligence has revolutionised the healthcare industry. In the next generation of healthcare systems, self-diagnosis will be pivotal to personalised healthcare services. During the COVID-19 pandemic, new screening and diagnostic approaches like mobile health are well-positioned to reduce disease spread and overcome geographical barriers. This paper presents a non-invasive screening approach to predict the health of a person from visually observable features using machine learning techniques. Images like face and skin surface of the patients are acquired using camera or mobile devices and analysed to derive clinical reasoning and prediction of the person’s health. Methods: In specific, a two-level classification approach is presented. The proposed hierarchical model chooses a class by training a binary classifier at the node of the hierarchy. Prediction is then made using a set of class-specific reduced feature set. Results: Testing accuracies of 86.87% and 76.84% are reported for the first and second-level classification. Empirical results demonstrate that the proposed approach yields favourable prediction results while greatly reduces the computational time. Conclusions: The study suggests that it is possible to predict the health condition of a person based on his/her face appearance using cost-effective machine learning approaches.
Individual-level variations in malaria susceptibility and acquisition of clinical protection
Authors: Valletta John Joseph , Addy John W.G. , Reid Adam J. , Ndungu Francis M. , Bediako Yaw , Mwacharo Jedida , Said Khadija , Musyoki Jennifer , Ngoi Joyce Mwongeli , Wambua Joshua , Otieno Edward , Berriman Matt , Bejon Philip , Marsh Kevin , Langhorne Jean , Newbold Chris I. , Recker Mario 
Published: September 2021

After decades of research, our understanding of when and why individuals infected with Plasmodium falciparum develop clinical malaria is still limited. Correlates of immune protection are often sought through prospective cohort studies, where measured host factors are correlated against the incidence of clinical disease over a set period of time. However, robustly inferring individual-level protection from these population-level findings has proved difficult due to small effect sizes and high levels of variance underlying such data. In order to better understand the nature of these inter-individual variations, we analysed the long-term malaria epidemiology of children ≤12 years old growing up under seasonal exposure to the parasite in the sub-location of Junju, Kenya. Despite the cohort’s limited geographic expanse (ca. 3km x 10km), our data reveal a high degree of spatial and temporal variability in malaria prevalence and incidence rates, causing individuals to experience varying levels of exposure to the parasite at different times during their life. Analysing individual-level infection histories further reveal an unexpectedly high variability in the rate at which children experience clinical malaria episodes. Besides exposure to the parasite, measured as disease prevalence in the surrounding area, we find that the birth time of year has an independent effect on the individual’s risk of experiencing a clinical episode. Furthermore, our analyses reveal that those children with a history of an above average number of episodes are more likely to experience further episodes during the upcoming transmission season. These findings are indicative of phenotypic differences in the rates by which children acquire clinical protection to malaria and offer important insights into the natural variability underlying malaria epidemiology.
Protocol for a prospective cohort study of open tibia fractures in Malawi with a nested implementation of open fracture guidelines
Authors: Schade Alexander Thomas , Nyamulani Nohakhelha , Banza Leonard Ngoe , Metcalfe Andrew John , Leather Andrew , Madan Jason J. , Lallloo David G. , Harrison Williams James , MacPherson Peter 
Published: September 2021

Background: Road traffic injury (RTI) is the largest cause of death amongst 15–39-year-old people worldwide, and the burden of injuries such as open tibia fractures are rapidly increasing in Malawi. This study aims to investigate disability and economic outcomes of people with open tibia fractures in Malawi and improve these with locally delivered implementation of open fracture guidelines. Methods: This is a prospective cohort study describing function, quality of life and economic burden of open tibia fractures in Malawi. In total, 160 participants will be recruited across six centres and will be followed-up with face-to-face interviews at six weeks, three months, six months and one year following injury. The primary outcome will be function at one year measured by the short musculoskeletal functional assessment (SMFA) score. Secondary outcomes will include quality of life measured by EuroQol EQ-5D-3L, catastrophic loss of income and implementation outcomes (acceptability, adoption, appropriateness, costs, feasibility, fidelity, penetration, and sustainability) at one year. A nested pilot pre-post implementation study of an interventional bundle for all open fractures will be developed based on other implementation studies from low- and middle-income countries (LMICs). Regression analysis will be used to model and investigate associations between SMFA score and fracture severity, infection and the pre- and post-training course period. Outcome: This prospective cohort study will report patient reported outcomes from open tibia fractures in low-resource settings. Subsequent detailed evaluation of both the clinical and implementation components of the study will promote sustainability of improved open fractures management in the study sites and further scale-up of open fracture management guidelines. Ethics: Ethics approval has been obtained from the Liverpool School of Tropical Medicine and College of Medicine Research and Ethics committee.
Radiation-Hygienic Monitoring in Potentially Radon-Hazardous Territories
Authors: Laschenova Tat'yana , Karl L. , Marennyy A. 
Published: September 2021

Modern radioecological studies to assess the effect of natural radiation on the human body have shown that at the moment of development of society, the main contribution to the exposure of the population is made by natural sources of ionizing radiation, while from 50 to 90 % of the dose load are caused by the gas radon-222 (222Rn) and daughter products of its decay.
This paper presents the results of radiation-hygienic monitoring of the potentially radon-hazardous territory of the city of Baley, Trans-Baikal Territory. The measurement of the volumetric activity of radon (OARn) was carried out in the premises of residential and public buildings by the integral method using track exposure meters REI-4. According to the indicator of the equivalent equilibrium volumetric activity of radon (EROARn), a radiation-hygienic assessment of the premises and the calculation of potential dose loads on the population living in this territory were carried out.
Studies have shown that OARn in residential and public buildings depends on the geological characteristics of the territory, on the design and design of buildings and structures, and on the building materials used. It was found that the main criterion for assessing the potential radon hazard of territories is the value of OARn in rooms on the 1st floors of buildings. According to the degree of potential radon hazard, the territory of the city of Baley can be conditionally divided into 3 types: 1 type – the territory located on a geological fault; Type 2 – the southern part of the city, represented by sedimentary rocks; Type 3 – the northern part of the city, represented by rocks of the basic gabbroid group with a low content of natural radionuclides. The types of buildings and structures and the type of building materials affect the dose load, but do not determine it.
Personalized Robo-Advising: Enhancing Investment Through Client Interaction
Authors: Capponi Agostino , Ólafsson Sveinn , Zariphopoulou Thaleia 
Published: September 2021

Automated investment managers, or robo-advisors, have emerged as an alternative to traditional financial advisors. The viability of robo-advisors crucially depends on their ability to offer personalized financial advice. We introduce a novel framework in which a robo-advisor interacts with a client to solve an adaptive mean-variance portfolio optimization problem. The risk-return tradeoff adapts to the client’s risk profile, which depends on idiosyncratic characteristics, market returns, and economic conditions. We show that the optimal investment strategy includes both myopic and intertemporal hedging terms that reflect the dynamic risk profile of the client. We characterize the optimal portfolio personalization via a tradeoff faced by the robo-advisor between receiving information from the client in a timely manner and mitigating behavioral biases in the communicated risk profile. We argue that the optimal portfolio’s Sharpe ratio and return distribution improve if the robo-advisor counters the client’s tendency to reduce market exposure during economic contractions when the market risk-return tradeoff is more favorable. This paper was accepted by David Simchi-Levi, stochastic models and simulation.
Complex Kernel-based spectrum reconstruction algorithm for cascaded Fabry–Perot interferometric spectrometer
Authors: ElZeiny Walid ElSayed , Sabry Yasser M. , Khalil Diaa A. 
Published: September 2021

A method to calculate the spectrum of the light incident on a cascaded Fabry–Perot interferometric spectrometer from the detector signal versus the scanning mirror position is presented. The method is based on modifying the Fabry–Perot integral equation to reduce possible spectrum reconstruction errors that arise due to inaccurate determination of the optical path difference reference position and the dependence on the dispersion of the cavity material. A transformation algorithm that employs the suggested kernel modification is derived and tested. The presented algorithm is then compared to the conventional kernel, showing spectral error reductions by larger than 20 dB.
Full-silica metamaterial wave plate for high-intensity UV lasers
Authors: Bonod Nicolas , Brianceau Pierre , Neauport Jérôme 
Published: September 2021

Bringing light–matter interactions into novel standards of high-energy physics is a major scientific challenge that motivated the funding of ambitious international programs to build high-power laser facilities. The major issue to overcome is to avoid laser intensity heterogeneities over the target that weaken the light–matter interaction strength. Laser beam smoothing aims at homogenizing laser intensities by superimposing on the target laser speckle intensities produced by orthogonal left and right circularly polarized beams. Conventional wave plates based on anisotropic crystals cannot support the laser fluences of such lasers, and the challenge is now to design wave plates exhibiting a high laser induced damage threshold (LIDT). Fused silica exhibits high LIDT, but its isotropic dielectric permittivity prevents effects on polarization retardance. Metamaterials have been widely investigated to tailor the phase and polarization of light but with plasmonic or high-refractive-index materials, and applying this approach with silica is highly challenging due to the weak optical contrast between silica and air or vacuum. Here we design and fabricate a silica-based metasurface acting almost like a quarter-wave plate in the UV spectral range, fulfilling the numerous constraints inherent to high-power laser beamlines, in particular, high LIDT and large sizes. We numerically and experimentally demonstrate that fused silica etched by deep grooves with a period shorter than the wavelength at 351 nm operates the linear-to-quasi circular polarization conversion together with a high transmission efficiency and a high LIDT. The high aspect ratio of the grooves due to the short period imposed by the short wavelength and the deepness of the grooves required to overcome the weak optical contrast between silica and air is experimentally obtained through a CMOS compatible process.
The possible mediatory role of adipokines in the association between low carbohydrate diet and depressive symptoms among overweight and obese women
Authors: Setayesh Leila , Ebrahimi Reyhane , Pooyan Sara , Yarizadeh Habib , Rashidbeygi Elaheh , Badrooj Negin , Imani Hossein , Mirzaei Khadijeh 
Published: September 2021

Background
Previous studies showed the possible association between obesity, dietary pattern, and depressive symptoms. Due to the lack of enough data to confirm the association of obesity and depression in the Middle East, here, we aimed to explore the possible mediatory role of adipokines Galectin-3, transforming growth factor-beta (TGF-β), and endothelial plasminogen activator inhibitor (PAI-1) in the association between low carbohydrate diet (LCD) and depressive symptoms.

Methods
A total of 256 women aged 17–56 years old were grouped based on their LCD score. Depression anxiety stress scales-21 (DASS-21) self-administered questionnaire was used to evaluate the three negative emotional states of stress, depressive symptoms, and anxiety. Body composition and dietary intake were assessed. Enzyme-linked immunosorbent assay (ELISA) was used to measure the serum levels of Galectin-3, TGF-β, and PAI-1.

Results
No significant difference was observed regarding Galectin-3, TGF-β, and PAI-1 levels between the groups with dissimilar adherence to LCD or the groups with different levels of depressive symptoms (P>0.05). However, there was a negative association between LCD score as a covariant and depressive symptoms as an independent variable (P = 0.02) and remarkably, a regression model linear analysis using Galectin-3, TGF-β, and PAI-1 as confounding variables indicated the mediatory role of these adipokines in this association (P>0.05). In other words, adipokines eliminated the significance of the relationship between adherence to LCD and depressive symptoms.

Conclusion
It seems that higher adherence to LCD is probably associated with a lower prevalence of depressive symptoms in obese adults through the mediatory role of adipokines.
Implementation of the logistics train in the intralogistics system: A case study
Authors: Strnad David , Fedorko Gabriel , Dribnak Juraj 
Published: September 2021

AbstractIntralogistics contributes significantly to the proper functioning of business processes. When designing and solving intralogistics systems, it is necessary to take into account the specific conditions in the given enterprise. The technical design, as well as the composition of the trolleys in the design of the transport system, must respect the specificities of the goods transported as well as shelf life and quantity. The study presents, for example, the implementation of a tugger train into an intercompany system with a solution procedure that is adapted to specific operating conditions and ensures the smooth functioning of the supply process. It is a principle based on the use of a simulation model. During its creation, three original sequences were developed in the programming language SimTalk. Their application decreases the use of blocks from the simulation program by up to 65% and it was possible to model more detailed processes that would not be possible in terms of functionality by using classical blocks. Fifteen directions of the language SimTalk were applied in their creation. Two variables of the type Integer, two variables of the type Object, and one variable of the type Real were defined.
Bayesian optimization based machine learning approaches for prediction of plug-in electric vehicle state-of-charge
Authors: Deb Subhasish , Goswami Arup Kumar , Chetri Rahul Lamichane , Roy Rajesh 
Published: September 2021

Abstract
The growing popularity of plug-in electric vehicle (PEV) around the world makes complexity in power sector. The distribution system is subjected to overload due to the random penetration of PEVs in charging depending on their level of state-of-charge (SOC). The accurate calculation and prediction of SOC considering their travel distance makes significant impact on the level of SOC. Therefore, the accurate SOC prediction of PEVs is need of the hour in transportation sector. However, the prediction of SOC allows the PEVs owners to decide the charging/discharging mode or priority based charging. Recently, machine learning techniques are gaining popularity in prediction analysis of different parameters. This article proposes machine learning approaches in combination with Bayesian optimization (BO) for prediction analysis of PEVs SOC. The gradient boosting method (GBM) and random forest method (RFM) are used as machine learning approaches in this work. The energy consumption pattern, different battery capacities and total trip distance of PEVs are included in calculation for the estimation of accurate SOC. A satisfactory result of SOC prediction has been observed using both GBM-BO and RFM-BO. The comparative study of results reveals the performance and efficacy of GBM-BO against RFM-BO in the PEVs SOC prediction analysis. Moreover, the hybrid machine learning techniques with BO performs better than individual machine learning techniques in the prediction analysis of PEVs SOC.
Chondroblastoma of mandibular condyle: Case report and literature review
Authors: Yang Xiaoqin , Wang Manyi , Gao Wenfeng , Wan Di , Zheng Junfa , Zhang Zhaoqiang 
Published: September 2021

Abstract
Chondroblastoma is one of the uncommon benign bone tumors, particularly when located in the mandibular condyle. Such a location makes its diagnosis difficult when based on only its clinical presentation and radiographic features. Herein the current report presents a case of chondroblastoma of the mandibular condyle: its clinical presentation, radiographic features, and immediate condylar reconstruction after resection. Additionally, the relevant literature is discussed to provide clinical recommendations for its diagnosis and treatment. Chondroblastoma has been reported so infrequently in the temporomandibular joint (TMJ), more common entities should first be considered in the differential diagnosis of masses in this location. Osteochondroma is the most frequent bone neoplasm in the TMJ. Since a correct diagnosis is difficult, additional tools, such as magnetic resonance imaging (MRI) and immunohistochemical analyses, should be used for diagnostics and surgical planning.
Hygrothermal environment effect on the critical buckling load of FGP microbeams with initial curvature integrated by CNT-reinforced skins considering the influence of thickness stretching
Authors: Alkhedher Mohammad 
Published: September 2021

Abstract
Due to the need for structures with refined properties to bear against different loading conditions, recently, carbon nanotubes (CNTs) have been used widely to reinforce them. The extremely high stiffness of CNTs makes them significant as one of the best reinforcements to improve the mechanical behaviors of structures. This work focuses on microbeam buckling response with an initial curvature that includes three layers. The mid-layer that is known as the core is constituted of functionally graded porous (FGP) materials and two CNT-reinforced composite skins are bonded to the core to integrate it. The whole structure is affected by the hygrothermal environment and springs and shear layers are put below it. For the first time, for such a structure, a refined shear deformation theory (RSDT) as a higher-order theory that considers thickness stretching effect in polar coordinates is used that presents more accurate results, especially for deeply curved beams. Modified couple stress theory (MCST) in combination with the virtual displacement principle is utilized to establish the governing equations. The obtained results demonstrate the significance of porosity percentage and CNTs’ addition to the skins on the critical nanotubes buckling load. Also, the different behaviors of the microstructure at various temperatures are analyzed and discussed in detail.
Consumption, aggregate wealth and expected stock returns: a quantile cointegration approach
Authors: Quineche Ricardo 
Published: September 2021

AbstractThis paper empirically examines the long-run relationship between consumption, asset wealth and labor income (i.e.,cay) in the United States through the lens of a quantile cointegration approach. The advantage of using this approach is that it allows for a nonlinear relationship between these variables depending on the level of consumption. We estimate the coefficients using a Phillips–Hansen type fully modified quantile estimator to correct for the presence of endogeneity in the cointegrating relationship. To test for the null of cointegration at each quantile, we apply a quantile CUSUM test. Results show that: (i) consumption is more sensitive to changes in labor income than to changes in asset wealth for the entire distribution of consumption, (ii) the elasticity of consumption with respect to labor income (asset wealth) is larger at the right (left) tail of the consumption distribution than at the left (right) tail, (iii) the series are cointegrated around the median, but not in the tails of the distribution of consumption, (iv) using the estimatedcayobtained for the right (left) tail of the distribution of consumption improves the long-run (short-run) forecast ability on real excess stock returns over a risk-free rate.