bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hormone Replacement Therapy is associated with improved cognition and larger brain volumes in at risk APOE4 women: results from the European Prevention of Alzheimer’s Disease (EPAD) cohort
Authors: Saleh Rasha , Hornberger Michael , Ritchie Craig W , Minihane Anne Marie 
Published: July 2022

Abstract
Background:The risk of dementia is higher in women than men. The metabolic consequences of estrogen decline during menopause accelerates neuropathology in women. The use of hormone replacement therapy (HRT) in the prevention of cognitive decline has shown conflicting results. Here we investigate the modulating role of APOE genotype and age at HRT initiation on the heterogeneity in cognitive response to HRT. Methods: The analysis used baseline data from participants in the European Prevention of Alzheimer’s Dementia (EPAD) cohort (total n= 1906, women= 1178, 61.8%). Analysis of covariate (ANCOVA) models were employed to test the independent and interactive impact of APOE genotype and HRT on select cognitive tests, such as MMSE, RBANS, dot counting, Four Mountain Test (FMT) and the supermarket trolley test (SMT), together with volumes of the medial temporal lobe (MTL) regions by MRI. Multiple linear regression models were used to examine the impact of age of HRT initiation according to APOE4 carrier status on these cognitive and MRI outcomes. Results: APOE4 HRT users had the highest RBANS delayed memory index score (P-APOE*HRT interaction = 0.009) compared to APOE4 non-users and to non-APOE4 carriers, with 6-10% larger entorhinal (left) and amygdala (right and left) volumes (P-interaction= 0.002, 0.003, and 0.005 respectively). Earlier introduction of HRT was associated with larger right (standardized β= -0.555, p=0.035) and left hippocampal volumes (standardized β= -0.577, p=0.028) only in APOE4 carriers. Conclusion:HRT introduction is associated with improved delayed memory and larger entorhinal and amygdala volumes in APOE4 carriers only. This may represent an effective targeted strategy to mitigate the higher life-time risk of AD in this large at-risk population subgroup. Confirmation of findings in a fit for purpose RCT with prospective recruitment based on APOE genotype is needed to establish causality.
Structural Isomer Switching in Silver Nanoparticles due to Air Exposure
Authors: Vernieres Jerome , Tarrat Nathalie , Lethbridge Sean , Watchorn-Rokutan Erica , Stock Sarah , Slater Thomas , Loffreda David , Palmer Richard 
Published: July 2022

Abstract
Silver clusters up to 1000 atoms in size, on an amorphous carbon film, have been exposed to ambient air and investigated by atomic resolution imaging in the aberration-corrected Scanning Transmission Electron Microscope (ac-STEM). Ordered structures comprise more than half the population, the rest are amorphous. Of ordered isomer structures the most common is the icosahedron. The results contrast with the published behaviour of silver clusters protected from atmospheric exposure, where the predominant ordered isomer is face-centred cubic. We propose that the formation of surface oxide or sulphide species resulting from air exposure can account for this isomer switching. This interpretation is consistent with density functional theory calculations based on silver nanoclusters, in the size range 147-201 atoms, on which methanethiol molecules are adsorbed. An understanding of the effects of ambient exposure on the atomic structure and therefore functional properties of nanoparticles is highly relevant to their real-world performance and applications.
Drug addiction mutations unveil a repressive methylation ceiling in EZH2-mutant lymphoma
Authors: Kwok Hui Si , Freedy Allyson , Siegenfeld Allison , Morriss Julia , Waterbury Amanda , Kissler Stephen , Liau Brian 
Published: July 2022

Abstract
Drug addiction, a phenomenon where cancer cells paradoxically depend on continuous drug treatment for survival, has uncovered cell signaling mechanisms and cancer co-dependencies. Here, we discover mutations that confer drug addiction to inhibitors of the transcriptional repressor Polycomb Repressive Complex 2 (PRC2) in diffuse large B-cell lymphoma (DLBCL). Drug addiction is mediated by hypermorphic mutations in the CXC domain of the catalytic subunit EZH2, which maintain H3K27me3 levels even in the presence of PRC2 inhibitors. Drug discontinuation leads to overspreading of H3K27me3, surpassing a repressive methylation ceiling compatible with lymphoma cell survival. Exploiting this vulnerability, we show that inhibition of SETD2 induces H3K27me3 spreading and blocks lymphoma growth. Collectively, our findings demonstrate that fundamental constraints on chromatin landscapes can yield biphasic dependencies in epigenetic signaling in cancer cells. More broadly, we highlight how approaches to identify drug addiction mutations can be leveraged to discover cancer vulnerabilities and cell signaling thresholds.
Intertemporal Elasticity of Substitution with Leisure Margin†
Authors: Yagihashi Takeshi , Du Juan 
Published: July 2022

Abstract
This paper investigates households’ consumption smoothing behavior by estimating the intertemporal elasticity of substitution of consumption (IES) while allowing labor / leisure to vary. To this end, we adopt a utility specification that allows non-separability between consumption and leisure. Using this specification, we define a leisure margin as the gap between the IES that allows leisure to vary and the IES that keeps leisure constant. We find a positive and statistically significant leisure margin throughout the paper and in addition the leisure margin becomes larger when the spouse’s leisure is taken into consideration. This result indicates that family labor supply plays an important role in households’ consumption decisions. We further explore the heterogeneous nature of nonmarket time and show that consumption-leisure substitutability could be explained largely by home production. Our findings demonstrate the importance of time allocation when households make decisions on consumption and saving.JEL code: E21 (Consumption), D91 (Intertemporal household choice), J22 (Time allocation and labor supply)
Accurate delivery of pristimerin and paclitaxel by folic acid-linked nano-micelles for enhancing chemosensitivity in cancer therapy
Authors: Chen Chao , Du Shiyu , Zhong Wu , Liu Kunguo , Qu Lihua , Chu Feiyi , Yang Jingjing , Han Xin 
Published: July 2022

Abstract
Chemoresistance remains a huge challenge for effective treatment of non-small cell lung cancer (NSCLC). Previous studies have shown Chinese herbal extracts possess great potential in ameliorating tumor chemoresistance, however, the efficacy is clinically limited mainly because of the poor tumor-targeting and in vivo stability. In this study, a folic acid (FA)-modified nano-herb micelle was developed for codelivery of pristimerin (PRI) and paclitaxel (PTX) to enhance chemosensitivity of NSCLC, in which PRI could synergistically enhance PTX-induced growth inhibition of A549 cancer cell. PTX was firstly grafted with the FA-linked polyethylene glycol (PEG) and then encapsulated with PRI to construct the PRI@FA-PEG-PTX (P@FPP) nano-micelles (NMs), which exhibited improved tumor-targeting and in vivo stability. This active-targeting P@FPP NMs displayed excellent tumor-targeting characteristics without obvious toxicity. Moreover, inhibition of tumor growth and metastasis induced by P@FPP NMs were significantly enhanced compared with the combined effects of the two drugs (PRI in combination of PTX), which associated with epithelial mesenchymal transition inhibition to some extent. Overall, this active-targeting NMs provides a versatile nano-herb strategy for improving tumor-targeting of Chinese herbal extracts, which may help in the promotion of enhancing chemosensitivity of NSCLC in clinical applications.
Can blood lipid profile monitoring warn of adverse psychiatric conditions and suicidal ideation in patients with acne vulgaris under isotretinoin treatment?
Authors: Gürok Neşe Göçer , Gürok Mehmet Gürkan , Demir Betül , Atmaca Murad 
Published: July 2022

Abstract
Previous studies demonstrated that lipids could play a role in suicidal ideation and the pathogenesis of psychiatric diseases. The present study aims to investigate the correlation between variations in serum lipid concentration, a side effect of isotretinoin (ITT), psychiatric symptoms and suicidal ideation in acne vulgaris patients under ITT treatment. Study was completed with 41 acne patients. Patients were analyzed with the socio-demographic and clinical data form, Beck depression inventory (BDI), Beck anxiety inventory (BAI), Beck suicidal ideation scale (BSS), Brief psychiatric rating (BPRS) scale at the beginning and on the third month of treatment. A statistically significant correlation was determined between the BSS scores and total cholesterol (TC), triglyceride (TG) and low-density lipoprotein (LDL) parameters at the beginning of treatment and the control date. Thus, it was determined that there was a negative weak correlation between BSS and TC parameters (r:-0.403; p:0.009<0.01), a moderate negative correlation between BSS and TG (r:-0.526; p:0.000<0.01), and a weak negative correlation between BSS and LDL (r:-0.421; p:0.006<0.01). Furthermore, there were statistically significant changes between the BDI and BAI scores at beginning of treatment and the 3rd month (t:-2.257; p:0.016<0.05, t:-3.654; p:0.001<0.01, respectively). Although an increase was observed in BSS and BPRS after the treatment compared to pre-treatment, the increase was not statistically significant. The present study findings revealed that serum lipid levels could be associated with psychiatric side effects in patients under ITT treatment. But, this must not be the unique way to detect the risk, when we consider that serum lipid levels that have been associated with suicidal ideation, depression and several psychiatric diseases have the potential to be an important indicator. In this context, our preliminary results open the doors of a new perspective in this regard, using the concept of blood lipid optimization. These findings need to be considered preliminary and supported by large samples.
Origin identification of Cornus officinalis based on PCA-SVM combined model
Authors: Jin Yueqiang , Liu Bing , Li Chaoning , Shi Shasha 
Published: July 2022

Abstract
Infrared spectroscopy can quickly and non-destructively extract analytical information from samples. It can be applied to the authenticity identification of various Chinese herbal medicines, the prediction of the mixing amount of defective products, and the analysis of the origin. In this paper, the spectral information of Cornus officinalis from 11 origins was used as the research object, and the origin identification model of Cornus officinalis based on mid-infrared spectroscopy was established. First, principal component analysis was used to extract the absorbance data of Cornus officinalis in the wavenumber range of 551~3998 cm–1. The extracted principal components contain more than 99.8% of the information of the original data. Second, the extracted principal component information was used as input, and the origin category was used as output, and the origin identification model was trained with the help of support vector machine. In this paper, this combined model is called PCA-SVM combined model. Finally, the generalization ability of the PCA-SVM model is evaluated through an external test set. The three indicators of Accuracy, F1-Score, and Kappa coefficient are used to compare this model with other commonly used classification models such as naive Bayes model, decision trees, linear discriminant analysis, radial basis function neural network and partial least square discriminant analysis. The results show that the PCA-SVM model outperforms several other commonly used models in terms of Accuracy, F1-Score, or Kappa coefficient. Using this model to identify the origin of Cornus officinalis, the accuracy rate is 84.8%.
Incidence of Galactic Cosmic Ray Fluxes at Polar and Middle Latitude Regions
Authors: Hanson Esther A. , Okeke Francisca N. 
Published: July 2022

Abstract
Galactic Cosmic Rays (GCRs) incidence on the Earth’s near space environment is of major concern to humankind as it affects space weather. Upon entering Earth’s atmosphere, GCRs collide with atoms and molecules, and subsequently decay into muons and neutrinos which propagates through the earth’s surface. Theory and observations affirm that penetration of GCR from the Heliospheric Magnetic Field (HMF) to Earth’s atmosphere is leveraged by the earth’s magnetic force lines predominant at the polar regions. We used facilities at NASA Goddard Space Flight Center, Greenbelt, Maryland USA and analyzed GCR particles recorded by Neutron Monitors (NM) at Thule, Newark, Mc Murdo and South Pole hosted at Bartol Research Institute, University of Delaware, USA. Geomagnetic aa index was obtained from World Data Center for Geomagnetism, Kyoto, Japan. This work investigates the degree to which GCRs are modulated by Geomagnetic activities using Geomagnetic aa-index as a proxy to Geomagnetic activity. We studied GCRs incident at four Neutron Monitor (NM) Stations at; Thule in the Arctic region, McMurdo and South Pole in the Antarctica, and Newark in the Middle Latitude region across five solar cycles timescale (1964 to 2016). We performed Regression Analysis of GCR and Geomagnetic aa-index to observe the impact of geomagnetic activity on GCR flux at the designated regions of the Earth’s surface. Also, we carried out Time Series Analysis to observe GCR intensities at the four NM Stations for the period of study. Results from Regression Analysis revealed a weak association between GCR and Geomagnetic aa index, where Coefficient of Determination R2 is less than 0.5. The Time Series Analysis revealed highest fluxes of GCR at Thule, McMurdo and South Pole as compared to incidence at the Mid-Latitude region in Newark. Our model indicate that GCR fluxes are controlled by Geomagnetic Field structure.
Development of prognosis and diagnosis model for osteosarcoma based on oxidative stress-related genes
Authors: Li Dongli , Ma Tianjun , Wu Hong , Sun Wen , He Mei , Song Qingfeng , Cui Ying 
Published: July 2022

Abstract
The most frequently malignant bone tumor in children and teenagers is osteosarcoma. However, it is unclear how oxidative stress (OS) affects osteosarcoma. The purpose of this investigation was to determine how OS genes affected osteosarcoma development and prognosis. The Therapeutically Applicable Research to Generate Effective Treatments (TARGET), GenotypeTissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases were used to obtain sample gene expression profiles and clinical data for this investigation. Based on distinct OS gene expression patterns, nonnegative matrix factorization (NMF) clustering was performed to identify molecular groupings. A multivariate Cox regression analysis was used to build the prognostic model. More thorough estimate of immune cells in malignant tumor tissues and prediction of treatment response. Functional analyses include Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and Gene Set Variation Analysis (GSVA). An in-vitro investigation of OD, a Chinese medication, has been substantial. Using network pharmacology to research the possible therapeutic targets and molecular processes of Oldenlandia diffusa (OD) in the treatment of osteosarcoma, basing on high - and low-risk prognostic risk groups. The diagnostic models were built using multilayer perceptron (MLP) neural networks. To predict the survival of patients with osteosarcoma, a prognostic model and a nomogram were created. OS-related genes were shown to be closely linked to the immune state and predictive survival of osteosarcoma patients, according to the GSVA and Gene functional enrichment analyses. 7 active ingredients and 233 target genes were identified from OD, and 25 of the target genes intersected with osteosarcoma-related genes were thought to be prospective therapeutic targets. Network pharmacological analysis showed that the active ingredients for the treatment of osteosarcoma was closely connected with regulation of immune cells. The diagnostic models were constructed based on a 9-gene signature showing excellent recognition ability of osteosarcoma patients. The interplay between OS-related genes and immunology in the development of osteosarcoma might generate new insights into molecular processes and targeted therapeutics for patients with the disease.
StackBox: An improved framework for precise polyp detection
Authors: Albuquerque Carina , Henriques Roberto , Castelli Mauro 
Published: July 2022

Abstract
Polyp detection through colonoscopy is a widely used method to prevent colorectal cancer. The automation of this process aided by artificial intelligence allows faster and improved detection of polyps that can be missed during a standard colonoscopy. In this work, we propose implementing different object detection algorithms for polyp detection. To improve the mean average precision (mAP) of the detection, we combine the baseline models through a stacking approach. The experiments demonstrate the potential of this new methodology, which can reduce the workload for oncologists and increase the precision of the localization of polyps. Our proposal achieves an mAP of 0.86, translated into an improvement of 34.9% compared to the best baseline model and 28.8% with respect to the weighted boxes fusion ensemble technique.
Generating the General Linear Group of degree two over a field of Integer modulo 3, GL2(Z3) and deriving its properties
Authors: Ajiboye Ayomide Ayomikun 
Published: July 2022

Abstract
The General Linear Group of degree two over a field of Integer modulo 3, GL2(Z3) and Special Linear Group of degree two over a field of Integer modulo 3, SL2(Z3) are generated. The order of GL2(Z3), SL2(Z3) and the order of each of the elements of GL2(Z3) are determined. The inverse of each of the elements of the General Linear Group of degree two over a field of Integer modulo 3, GL2(Z3) is investigated. General linear group is important for representation.
Exploring telediagnostic procedures in child neuropsychiatry: addressing ADHD diagnosis and autism symptoms through supervised machine learning
Authors: Grazioli Silvia , Crippa Alessandro , Rosi Eleonora , Candelieri Antonio , Ceccarelli Silvia Busti , Mauri Maddalena , Manzoni Martina , Mauri Valentina , Trabattoni Sara , Molteni Massimo , Colombo Paola , Nobile Maria 
Published: July 2022

Abstract
Recently there has been an increase in telemedicine applied to child neuropsychiatry, such as the use of online platforms to remotely collect anamnestic and behavioral information. In the present proof-of-concept study, we aimed to understand to what extent information provided by parents and teachers through online questionnaires overlaps with clinicians’ diagnostic conclusions on Attention-Deficit/Hyperactivity Disorder (ADHD). Moreover, we intended to explore a possible role played by autism spectrum disorders (ASD) symptoms in this process. We examined parent-and teacher-rated questionnaires collected remotely and an on-site evaluation of intelligence quotients from 342 subjects (18% females), aged 3 to 16 years, referred for suspected ADHD. A machine learning model (decision tree, DT) was built to simulate the clinical process of classifying ADHD/non-ADHD. Differences in ASD symptoms in the DT-identified classes were tested to address their role in performing a diagnostic error using the DT model. The DT identified the decision rules adopted by clinicians to classify ADHD diagnosis and proved accurate in 82% of our subjects. The caregiver-reported ADHD core symptom severity proved the most discriminative information for clinicians during the diagnostic decision process. However, ASD symptoms were a confounding factor when ADHD severity had to be established. Telehealth procedures proved effective in obtaining an automated output regarding a diagnostic risk, reducing the time delay between symptom detection and diagnosis. However, this should not be considered as an alternative to on-site procedures but as automated support for clinical practice, enabling clinicians to allocate more resources to the most complex cases.
Decision-making and ageing: everyday life situations under risk and under ambiguity
Authors: Gaubert Fanny , Borg Céline , Roux Jean-Christophe , Chainay Hanna 
Published: July 2022

Abstract
Cognitive modifications over ageing can affect decision making competence (DMC). As it is a core ability in autonomy preservation, our study aims to investigate its changes in old adults and to determine if they are linked to the deterioration of executive functions and working memory. For this purpose, 50 young adults and 50 old adults were assessed with executive, working memory and DMC tasks. The latter comprised the Iowa Gambling task (IGT) and a scenarii task based on daily life-inspired situations, under risk and under ambiguity conditions. Results revealed lower performances in old adults compared to young adults for updating, inhibition and working memory tasks. The IGT failed to distinguish the two groups of age, but the scenarii task did it, as young adults were more risk and ambiguity seekers than old adults. Moreover, updating and inhibition capacities appeared to influence DMC.