bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep‐learning predicted PET can be subtracted from the true clinical fluorodeoxyglucose PET co‐registered to MRI to identify the epileptogenic zone in focal epilepsy
Authors: Flaus Anthime , Jung Julien , Ostrowky‐Coste Karine , Rheims Sylvain , Guénot Marc , Bouvard Sandrine , Janier Marc , Yaakub Siti N. , Lartizien Carole , Costes Nicolas , Hammers Alexander 
Published: August 2023

AbstractObjectiveNormal interictal [18F]FDG‐PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co‐registered to MRI) can then be used to compare epilepsy patients' predicted and clinical PET. We assessed the ability of SIPCOM to identify the Resection Zone (RZ) in patients with drug‐resistant epilepsy (DRE) with reference to visual and statistical parametric mapping (SPM) analysis.MethodsPatients with complete presurgical work‐up and subsequent SEEG and cortectomy were included. RZ localisation, the reference region, was assigned to one of eighteen anatomical brain regions. SIPCOM was implemented using healthy controls to train a GAN. To compare, the clinical PET coregistered to MRI was visually assessed by two trained readers, and a standard SPM analysis was performed.ResultsTwenty patients aged 17‐50 (32 ± 7.8) years were included, 14 (70%) with temporal lobe epilepsy (TLE). Eight (40%) were MRI‐negative. After surgery, 14 patients (70%) had a good outcome (Engel I‐II). RZ localisation rate was 60% with SIPCOM vs 35% using SPM (P = 0.015) and vs 85% using visual analysis (P = 0.54). Results were similar for Engel I‐II patients, the RZ localisation rate was 64% with SIPCOM vs 36% with SPM. With SIPCOM localisation was correct in 67% in MRI‐positive vs 50% in MRI‐negative patients, and 64% in TLE vs 43% in extra‐TLE. The average number of false‐positive clusters was 2.2 ± 1.3 using SIPCOM vs 2.3 ± 3.1 using SPM. All RZs localized with SPM were correctly localized with SIPCOM. In one case, PET and MRI were visually reported as negative, but both SIPCOM and SPM localized the RZ.SignificanceSIPCOM performed better than the reference computer‐assisted method (SPM) for RZ detection in a group of operated DRE patients. SIPCOM's impact on epilepsy management needs to be prospectively validated.
Optimized configuration with economic evaluation for shrouded vertical axis wind turbines applicable for urban structures
Authors: Rafiei Behnam , Gharali Kobra , Soltani M. 
Published: August 2023

AbstractIn recent urban buildings, there is an interest in using wind turbines inside the buildings. Thus, the rotors of wind turbines are shrouded by the walls of the buildings. A design for using wind turbines in urban areas is to use shrouded turbines on the roof of a building. Since vertical axis wind turbines (VAWTs) with low environmental impacts are recommended for energy supply in urban areas, here, the interaction of two shrouded VAWTs has been studied numerically. Based on the effects of different shroud parts, the diffuser‐shrouded turbines are selected. The arrangement of diffuser‐shrouded VAWTs has been optimized using the response surface method optimization with the Kriging model. The optimization samples are chosen by the design of experiment method to reduce the number of simulations and increase optimization accuracy. The total power coefficient of the optimized cluster is 46.2% higher than the sum of the same individual diffuser‐shrouded turbines and 149.6% higher than the sum of individual bare VAWTs. The economic assessment shows that the levelized cost of energy of the optimized cluster of two diffuser‐shrouded VAWTs is reduced by about 40% compared to two bare VAWTs.
Effect of Ampelopsis brevipedunculata (Maxim.) Trautv extract on a model of atopic dermatitis in HaCaT cells and mice
Authors: Bak Seon Gyeong , Lim Hyung Jin , Won Yeong‐Seon , Park Eun Jae , Kim Young Hee , Lee Seung Woong , Oh Je Hun , Kim Ji Eun , Lee Min Jee , Lee Soyoung , Lee Seung Jae , Rho Mun Chual 
Published: August 2023

AbstractAmpelopsis brevipedunculata (Maxim.) Trautv. has been used for a long time as a folk remedy. According to studies, it possesses anti‐inflammatory, antioxidant, and antibacterial properties. However, its effects on atopic dermatitis (AD) are poorly studied. Thus, we investigated the therapeutic effect of A. brevipedunculata (Maxim.) Trautv. extract (ABE‐M) on 2,4‐dinitrochlorobenzene (DNCB)‐induced AD. For in vitro analysis, keratinocytes cell lines (HaCaT cells) were used. To evaluate the gene and protein expression levels of cytokines and chemokines, TNF‐α/IFN‐γ‐stimulated HaCaT cells were treated with ABE‐M. The cells and the supernatant were collected, then gene and protein levels were analyzed by real‐time polymerase chain reaction and enzyme‐linked immunosorbent assay analysis. For in vivo analysis, BALB/c mice (6 weeks) were randomly separated into five groups (n = 5). The mice were applied DNCB and phosphate‐buffered saline, dexamethasone (DX) or ABE‐M (50, 100, and 200 mg/kg) was orally administrated for 28 days. At the end, ear tissues and blood were collected for histological analysis and evaluation of cytokines and chemokines. In keratinocytes, ABE‐M inhibited the protein and mRNA levels of chemokines, and cytokines exposed by TNF‐α/IFN‐γ. Similarly, the expression of chemokines was suppressed by ABE‐M in AD animal model induced by DNCB and the level of pro‐inflammatory cytokines was decreased in a dose‐dependent manner. Our research indicates that ABE‐M could be a candidate material that can be used to improve skin immunity enhancement, health, and beauty.
Asprosin contributes to nonalcoholic fatty liver disease through regulating lipid accumulation and inflammatory response via AMPK signaling
Authors: Zhang Bo , Lu Jinger , Jiang Yuhua , Feng Yan 
Published: August 2023

AbstractBackgroundNonalcoholic fatty liver disease (NAFLD) is a primary contributor to liver‐related morbidity and mortality. Asprosin has been reported to be implicated in NAFLD.AimsThis work is to illuminate the effects of Asprosin on NAFLD and the possible downstream mechanism.Materials & MethodsThe weight of NAFLD mice induced by a high‐fat diet was detected. Quantitative reverse‐transcription polymerase chain reaction (RT‐qPCR) examined serum Asprosin expression. RT‐qPCR and western blot analysis examined Asprosin expression in mice liver tissues. Intraperitoneal glucose tolerance test (IPGTT) and intraperitoneal insulin tolerance test (IPITT) were implemented. Biochemical kits tested liver enzyme levels in mice serum and liver tissues. Hematoxylin and eosin staining evaluated liver histology. Liver weight was also tested and oil red O staining estimated lipid accumulation. RT‐qPCR and western blot analysis analyzed the expression of gluconeogenesis‐, fatty acid biosynthesis‐, fatty acid oxidation‐, and inflammation‐associated factors. Besides, western blot analysis examined the expression of AMP‐activated protein kinase (AMPK)/p38 signaling‐associated factors. In palmitic acid (PA)‐treated mice hepatocytes, RT‐qPCR and western blot analysis examined Asprosin expression. Lipid accumulation, gluconeogenesis, fatty acid biosynthesis, fatty acid oxidation, and inflammation were appraised again.ResultsAsprosin was overexpressed in the serum and liver tissues of NAFLD mice and PA‐treated mice hepatocytes. Asprosin interference reduced mice body and liver weight, improved glucose tolerance and diminished liver injury in vivo. Asprosin knockdown alleviated lipid accumulation and inflammatory infiltration both in vitro and in vivo. Additionally, Asprosin absence activated AMPK/p38 signaling and AMPK inhibitor Compound C reversed the impacts of Asprosin on lipid accumulation and inflammatory response.ConclusionCollectively, Asprosin inhibition suppressed lipid accumulation and inflammation to obstruct NAFLD through AMPK/p38 signaling.
What drives US consumer confidence? The asymmetric effects of economic uncertainty
Authors: Choudhry Taufiq , Wohar Mark 
Published: August 2023

AbstractThis paper empirically investigates the asymmetric effects of different economic variables including uncertainty caused by government policies on the two main US consumer confidence indices. This paper further investigates whether COVID‐19 has any significant effect on the relationship between US consumer confidence indices and their determinants. The empirical investigation is conducted by means of non‐linear asymmetric autoregressive distributed lag (NARDL) tests, so that the asymmetric effect of uncertainty and other determinants on consumer confidence may be studied. The paper applies monthly data from January 2010 to December 2021. Results indicate that the COVID‐19 pandemic did not alter the stability of the long‐term relationship between the consumer confidence indices and their determinants. Uncertainty imposed by government policies plays a significant role before and, more prominently, during the pandemic. The increased effect of the uncertainty may be due to the jump in economic uncertainty during the COVID era. Our work may help to foster consumer confidence in terms of macroeconomic policy variables. The results can also expand the scope of investors' decision making as it provides an in‐depth understanding of the drivers of consumers' confidence in the US economy.
Nomogram for predicting pulmonary embolism in gynecologic inpatients with isolated distal deep venous thrombosis
Authors: Jin Zhen‐Yi , Li Chun‐Min , Zheng Kai , Qu Hong , Yang Wen‐Tao , Wen Jia‐Hao , Zhang Wang‐De , Ren Hua‐Liang 
Published: August 2023

AbstractObjectiveTo investigate the incidence of isolated distal deep venous thrombosis (IDDVT) concurrent with pulmonary embolism (PE) in gynecologic inpatients, analyze the risk factors for IDDVT with PE, and establish a nomogram model for IDDVT patients with PE.MethodsA total of 260 patients were diagnosed with IDDVT between December 2017 and November 2020. The incidence of PE in these patients was determined using computed tomography pulmonary angiography. Logistic regression analysis was used to identify the related risk factors. On this basis, nomogram risk prediction models were established.ResultsAmong 260 patients with IDDVT, 106 (40.8%) had concurrent PE, of whom 74 (28.5%) experienced silent PE. Univariate logistic analysis demonstrated statistical significance for body mass index (BMI; P = 0.044), glucocorticoid therapy (P = 0.009), hypertension (P < 0.001), and diabetes (P < 0.001). Multivariate logistic analysis revealed that these were independent risk factors for IDDVT with PE that retained statistical significance. A nomogram based on these factors was constructed to predict PE in patients with IDDVT. Its receiver operating characteristic (ROC) showed an area under the curve of 0.710 (95% confidence interval 0.642–0.779), with prediction sensitivity of 64.2% and prediction specificity of 76.6%.ConclusionsIn the present study, a high prevalence of PE was found in gynecologic inpatients with IDDVT. Glucocorticoid therapy, hypertension, diabetes, and BMI were independent risk factors for IDDVT patients with PE. Taking these risk factors into account, a nomogram risk prediction model was developed to help facilitate early detection of concurrent PE.
Multi‐classificationof brain tumor by using deep convolutional neural network model inmagnetic resonance imagingimages
Authors: Singh Ngangbam Herojit , Merlin N. R. Gladiss , Prabu R. Thandaiah , Gupta Deepak , Alharbi Meshal 
Published: August 2023

AbstractBrain tumors are still diagnosed and classified based on the results of histopathological examinations of biopsy samples. The existing method requires extra effort from the user, takes too long, and can lead to blunders. These limitations underline the need of employing a fully automated deep learning system for the multi‐classification of brain tumors. In order to facilitate early detection, this study employs a convolutional neural network (CNN) to multi‐classify brain tumors. In this research, we present three distinct CNN models for use in three separate categorization tasks. The first CNN model can correctly categorize brain tumors 99.74% of the time. The second CNN model is 96.27% accurate in differentiating between normal, glioma, meningioma, pituitary, and metastatic brain tumors. The third CNN model successfully distinguishes between Grades II, III, and IV brain tumors 99.18% of the time. The Hybrid Particle Swarm Grey Wolf Optimization (HPSGWO) technique is used to quickly and accurately determine optimal values for all of CNN models most important hyperparameters. An HPSGWO algorithm is used to fine‐tune all the necessary hyperparameters for optimal classification performance. The results are compared with standard existing CNN models across a range of performance measures. The proposed models are trained using publicly available large clinical datasets. To verify their initial multi‐classification of brain tumors, clinicians and radiologists might use the proposed CNN models.
Deep learning‐based pigment analysis model trained with optical approach and ground truth assistance
Authors: Jung Geunho , Kim Semin , Lee Jongha , Yoo Sangwook 
Published: August 2023

AbstractThis study introduces an integrated training method combining the optical approach with ground truth for skin pigment analysis. Deep learning is increasingly applied to skin pigment analysis, primarily melanin and hemoglobin. While regression analysis is a widely used training method to predict ground truth‐like outputs, the input image resolution is restricted by computational resources. The optical approach‐based regression method can alleviate this problem, but compromises performance. We propose a strategy to overcome the limitation of image resolution while preserving performance by incorporating ground truth within the optical approach‐based learning structure. The proposed model decomposes skin images into melanin, hemoglobin, and shading maps, reconstructing them by solving the forward problem with reference to the ground truth for pigments. Evaluation against the VISIA system, a professional diagnostic equipment, yields correlation coefficients of 0.978 for melanin and 0.975 for hemoglobin. Furthermore, our model can produce pigment‐modified images for applications like simulating treatment effects.
Indocyanine green and iohexol loaded hydroxyapatite in poly(L‐lactide‐co‐caprolactone)‐based composite for bimodal near‐infrared fluorescence‐ and X‐ray‐based imaging
Authors: Górecka Żaneta , Idaszek Joanna , Heljak Marcin , Martinez Diana C. , Choińska Emilia , Kulas Zbigniew , Święszkowski Wojciech 
Published: August 2023

AbstractThis study aimed to develop material for multimodal imaging by means of X‐ray and near‐infrared containing FDA‐ and EMA‐approved iohexol and indocyanine green (ICG). The mentioned contrast agents (CAs) are hydrophilic and amphiphilic, respectively, which creates difficulties in fabrication of functional polymeric composites for fiducial markers (FMs) with usage thereof. Therefore, this study exploited for the first time the possibility of enhancing the radiopacity and introduction of the NIR fluorescence of FMs by adsorption of the CAs on hydroxyapatite (HAp) nanoparticles. The particles were embedded in the poly(L‐lactide‐co‐caprolactone) (P[LAcoCL]) matrix resulting in the composite material for bimodal near‐infrared fluorescence‐ and X‐ray‐based imaging. The applied method of material preparation provided homogenous distribution of both CAs with high iohexol loading efficiency and improved fluorescence signal due to hindered ICG aggregation. The material possessed profound contrasting properties for both imaging modalities. Its stability was evaluated during in vitro experiments in phosphate‐buffered saline (PBS) and foetal bovine serum (FBS) solutions. The addition of HAp nanoparticles had significant effect on the fluorescence signal. The X‐ray radiopacity was stable within minimum 11 weeks, even though the addition of ICG contributed to a faster release of iohexol. The stiffness of the material was not affected by iohexol or ICG, but incorporation of HAp nanoparticles elevated the values of bending modulus by approximately 70%. Moreover, the performed cell study revealed that all tested materials were not cytotoxic. Thus, the developed material can be successfully used for fabrication of FMs.
Influence of heavy metal exposure on gut microbiota: Recent advances
Authors: Kaur Ravidarshdeep , Rawal Rakesh 
Published: August 2023

AbstractGut microbiota plays a functionally important part in retaining the homeostasis of host physiology, however, under exposure of various heavy metals, the composition of gut biota is disturbed in relation to species diversity and richness. Ever since the increase of microbiome‐related studies during the last decade, many research studies have delivered an understanding of the reasons and concerns of gut microbiota‐related modifications. During the past decade, it's been confirmed from various studies that heavy metals poisoning alters the microbial composition, which results in changes in gene expression, alteration in metabolism, immunity, neurological dysfunction, and causes various other disorders. The present comprehensive review is summarizing an attempt to enumerate the key findings from recent clinical or preclinical studies related to the influence of heavy metals on gut microbiota published recently. Google, PubMed, Science Direct, Scopus, and Google Scholar were employed as primary search engines using the keywords such as “heavy metals, gut microbiota, dysbiosis, and intestinal microbiota” for finding relevant research articles from the past 10 years and some old important articles. Here, we tried to provide insight into some of the key timelines and scientific findings from reported literature, like the effects of heavy metals such as arsenic, cadmium, lead, and mercury on the general body and specifically on the gut microbiota of different model organisms. So, it is important to increase awareness against heavy metal‐induced toxicity and formulate guidelines for the benefit of the environment.
polyGraft 1.0: A program for molecular structure and topology generation of polymer‐grafted hybrid nanostructures
Authors: Chen Guang 
Published: August 2023

AbstractPolymer‐grafted hybrid materials have been ubiquitously employed in various engineering applications. The design of these hybrid materials with superior performances requires a molecularly detailed understanding of the structure and dynamics of the polymer brushes and their interactions with the grafting substrate. Molecular dynamics (MD) simulations are very well suited for the study of these materials which can provide molecular insights into the effects of polymer composition and length, grafting density, substrate composition and curvatures, and nanoconfinement. However, few existing tools are available to generate such systems, which would otherwise reduce the barrier of preparation for such systems to enable high throughput simulations. Here polyGraft, a general, flexible, and easy to use Python program, is introduced for automated generation of molecular structure and topology of polymer grafted hybrid materials for MD simulations purposes, ranging from polymer brushes grafted to hard substrates, to densely grafted bottlebrush polymers. polyGraft is openly accessible on GitHub (https://github.com/nanogchen/polyGraft).
A quasi‐experimental trial of narrative reconstruction for prolonged grief disorder: Symptomatic improvement and enhanced memory integration
Authors: Elinger Gali , Hasson‐Ohayon Ilanit , Bar‐Shachar Yael , Peri Tuvia 
Published: August 2023

AbstractBackgroundProlonged grief disorder (PGD) was recently approved as a formal diagnosis in the DSM‐5‐TR. The implementation of bereavement interventions is frequently requested, but their effectiveness has been controversial. Narrative reconstruction (NR) is a time‐limited integrative therapy, originally developed for the treatment of post‐traumatic stress disorder (PTSD) and adapted for the treatment of PGD. NR consists of exposure to the loss memory, a detailed written reconstruction of the loss memory narrative, and an elaboration of the personal significance of that memory for the bereaved.ObjectivesIn this study we evaluated the efficacy of NR for PGD.MethodIn this study, 33 participants with PGD were quasi‐randomized—that is, assigned to an immediate (n = 20) or delayed (n = 13) 16‐session NR intervention. PGD, intrusion, avoidance and depression symptoms, as well as levels of the loss memory integration, were assessed at pretreatment, post‐treatment, and at a 3‐month follow‐up.ResultsMixed linear models showed significant intervention effects for PGD and intrusive symptomatology. Results also showed an increase in integration of the loss memory, and improvements remained stable for all outcomes at follow‐up.ConclusionIn this study we established NR as an effective intervention for PGD and call for further validation in future studies. Integrating this intervention into the routine care of people with PGD seems important and beneficial.
The mediating role of cognitive emotion regulation in the relationship between self‐concealment and quality of life among breast cancer chemotherapy patients
Authors: Qin Qiao‐yun , Li Shu‐wen , Li Wen , Li Yan‐ran 
Published: August 2023

AbstractPurposeThis study aimed to explore whether self‐concealment (SC) affects the quality of life (QOL), and whether cognitive emotion regulation (CER) mediates the relationship between SC and QOL among breast cancer chemotherapy patients.MethodsThis cross‐sectional study was conducted among 228 breast cancer chemotherapy patients from November 2021 to March 2022 in Anhui Province, China. Data were collected using the Self‐Concealment Scale, Cognitive Emotion Regulation Questionnaire, and Short Form 36 Questionnaire. Descriptive statistics, independent‐sample t test, one‐way analysis of variance, and structural equation modeling were used to explore associations among SC, CER, and QOL.ResultsQOL levels differed significantly by participant age, monthly per capita household income and home location. SC was negatively correlated with QOL. SSC was negatively correlated with adaptive‐CER strategies and positively correlated with maladaptive‐CER strategies. Adaptive‐CER strategies were positively correlated with QOL. Maladaptive‐CER strategies were negatively correlated with QOL. CER fully mediated the association between SC and QOL in breast cancer chemotherapy patients.ConclusionNursing staff should help breast cancer chemotherapy patients reduce the use of maladaptive‐CER strategies in the care of patients in the future. Helping patients reduce SC is more conductive to improving the QOL of breast cancer chemotherapy patients.