bluuebunny/crossref_metadata_2025 huggingface dataset:
Consumption of Spinach and Tomato Modifies Lipid Metabolism, Reducing Hepatic Steatosis in Rats
Authors: Elvira-Torales Laura Inés , Navarro-González Inmaculada , Rodrigo-García Joaquín , Seva Juan , García-Alonso Javier , Periago-Castón María Jesús
Published: October 2020

Non-alcoholic fatty liver disease (NAFLD) is currently a serious and growing clinical problem in developed and developing countries and is considered one of the most frequent chronic liver diseases in the world. The aim of this study was to evaluate the functionality of dietary carotenoids provided by tomato and spinach in the dietary treatment of steatosis. Twenty-two Sprague-Dawley rats with induced steatosis were grouped into three groups and fed standard diet (CD group) and two experimental diets supplemented with 12.75% (LC12.75 group) and 25.5% (HC25.5 group) of a mixture of spinach and tomato powder. Rats fed carotenoid-rich feeds showed an improvement in the plasma biomarkers of steatosis, with lower levels of glucose, total cholesterol, VLDL, TG, proteins, ALT and AST. Likewise, a decrease in oxidative stress was observed, with a significant reduction of malondialdehyde (MDA) in plasma (up to 54%), liver (up to 51.42%) and urine (up to 78.89%) (p < 0.05) and an increase in plasma antioxidant capacity (ORAC) (up to 73.41%) (p < 0.05). Furthermore, carotenoid-rich diets led to an accumulation of carotenoids in the liver and were inversely correlated with the content of total cholesterol and hepatic triglycerides, increasing the concentrations of MUFA and PUFA (up to 32.6% and 48%, respectively) (p < 0.05). The accumulation of carotenoids in the liver caused the modulation of genes involved in lipid metabolism, and we particularly observed an overexpression of ACOX1, APOA1 and NRIH2 (LXR) and the synthesis of the proteins. This study suggests that dietary carotenoids from spinach and tomato aid in the dietary management of steatosis by reversing steatosis biomarkers.
Comparative Effects of Pterostilbene and Its Parent Compound Resveratrol on Oxidative Stress and Inflammation in Steatohepatitis Induced by High-Fat High-Fructose Feeding
Authors: Gómez-Zorita Saioa , González-Arceo Maitane , Trepiana Jenifer , Aguirre Leixuri , Crujeiras Ana B , Irles Esperanza , Segues Nerea , Bujanda Luis , Portillo María Puy
Published: October 2020

Different studies have revealed that oxidative stress and inflammation are crucial in NAFLD (Non-alcoholic fatty liver disease). The aim of this study is to analyze whether pterostilbene and resveratrol are able to either avoid or delay the progression of non-alcoholic liver steatosis towards steatohepatitis. This has been performed by examining their effects on oxidative stress, inflammation, fibrosis and pre-carcinogenic stages. Rats were distributed into five experimental groups and were fed with either a standard diet or a high-fat high-fructose diet, supplemented or not with pterostilbene (15 or 30 mg/kg/d) or resveratrol (30 mg/kg/d), for 8 weeks. Liver histological analysis was carried out by haematoxylin–eosin staining. Serum and hepatic oxidative stress-related parameters were assessed using spectrophotometry, and the expression of genes related to inflammation, fibrosis and cancer by qRT-PCR. The dietary model used in this study led to the development of steatohepatitis, where rats displayed oxidative stress, inflammation and ballooning, although not fibrosis. It also modified the expression of hepatocarcinoma-related genes. The results show, for the first time, that pterostilbene was able to partially prevent these alterations, with the exception of changes in hepatocarcinoma-related genes, mainly at 30 mg/kg/d. Pterostilbene was more effective than its parent compound resveratrol, probably due to its high bioavailability and higher anti-oxidant and anti-inflammatory activities, attributable to its different chemical structure.
Transverse Crack Behavior in Continuously Reinforced Concrete Pavement with Basalt Fiber Reinforcement
Authors: Zhang Yating , Huang Zhiyi
Published: October 2020

Continuously reinforced concrete pavement (CRCP) is a pavement structure with a high performance and long service life. However, the corrosion of the longitudinal steel can result in a poor bond relationship between the steel and the concrete, affecting the load transfer efficiency between the adjacent panels and being responsible for the development of CRCP distresses. Basalt fiber-reinforced polymer (BFRP) is corrosion-resistant and has the potential to be used in CRCP. In this paper, the layout of a CRCP test section with BFRP bars constructed on G330 National Road in Zhejiang Province, China, is presented. An analytical model is proposed to predict the crack behavior of CRCP with BFRP reinforcement, with the predicted results are compared to field-measured ones. A sensitivity analysis of the BFRP design parameters on the crack spacing and crack width is conducted as well. The results show that the mean values for field-measured crack spacing and crack width are 4.85 m and 1.30 mm, respectively, which are higher than the results for traditional CRCP with steel due to the lower elastic modulus of BFRP. The analytical predictions agree reasonably well with the crack survey results. The higher the elastic modulus of BFRP, the reinforcement content (with both BFRP spacing and diameter related), and the bond stiffness coefficient between the BFRP and concrete, the less the crack spacing and crack width will be. Given the same or similar reinforcement content, a lower diameter with a smaller spacing is recommended because of its contribution to a smaller crack spacing and width.
Convolution-GRU Based on Independent Component Analysis for fMRI Analysis with Small and Imbalanced Samples
Authors: Wang Shan , Duan Feng , Zhang Mingxin
Published: October 2020

Functional magnetic resonance imaging (fMRI) is a commonly used method of brain research. However, due to the complexity and particularity of the fMRI task, it is difficult to find enough subjects, resulting in a small and, often, imbalanced dataset. A dataset with small samples causes overfitting of the learning model, and the imbalance will make the model insensitive to the minority class, which has been a problem in classification. It is of great significance to classify fMRI data with small and imbalanced samples. In the present study, we propose a 3-step method on a small and imbalanced fMRI dataset from a word-scene memory task. The steps of the method are as follows: (1) An independent component analysis is performed to reduce the dimension of data; (2) The synthetic minority oversampling technique is used to generate new samples of the minority class to balance data; (3) A convolution-Gated Recurrent Unit (GRU) network is used to classify the independent component signals, indicating whether the subjects are performing episodic memory tasks. The accuracy of the proposed method is 72.2%, which improves the classification performance compared with traditional classifiers such as support vector machines (SVM), logistic regression (LGR), linear discriminant analysis (LDA) and k-nearest neighbor (KNN), and this study gives a biomarker for evaluating the reactivation of episodic memory.
Observer-Based Distributed Fault Detection for Heterogeneous Multi-Agent Systems
Authors: Jia Wenhao , Wang Jinzhi
Published: October 2020

This paper solves the distributed fault detection (FD) problem for heterogeneous multi-agent systems (MAS). For a heterogeneous MAS, we adopt a distributed control law to realise cooperative output regulation (COR) when no fault occurs in the MAS, and propose a state-feedback-based FD scheme, where the adopted distributed control law and proposed FD scheme all utilise state information. Furthermore, we consider the condition that state information is unmeasurable, the output-feedback-based distributed FD scheme is proposed, and the adopted distributed control law also utilises measurement output. Finally, two numerical examples are utilised to verify that the proposed distributed FD schemes could locate and remove the faulty agent in time.
A Novel Chaos-Based Image Encryption Scheme by Using Randomly DNA Encode and Plaintext Related Permutation
Authors: Li Zhen , Peng Changgen , Tan Weijie , Li Liangrong
Published: October 2020

To ensure the security and privacy of digital image when its transmitting online or storing in the cloud, we proposed a novel chaos based image encryption scheme by using randomly DNA encode and plaintext related permutation. In our scheme, we first randomly encode plain image into a nucleotide sequence under the control by the piecewise linear chaotic map(PWLCM). After that, the plaintext related permutation would be done under the control sequence which generated by hyper chaotic Lorenz system (HCLS). Next, we make diffusion processing with key DNA sequence which is generated by another PWLCM system and also encoded randomly. Finally, we decode DNA sequence into cipher image matrix. In addition, we used many common security analysis methods to test our scheme, and the result compared with other works. The tests and comparison results are shown that our proposed image cryptosystem has excellent security performance to ensure the digital image security on communication.
Classifying Thermal Degradation of Polylactic Acid by Using Machine Learning Algorithms Trained on Fourier Transform Infrared Spectroscopy Data
Authors: Zhang Sung-Uk
Published: October 2020

Polylactic acid (PLA) is the most common polymeric material in the 3D printing industry but degrades under harsh environmental conditions such as under exposure to sunlight, high-temperatures, water, soil, and bacteria. An understanding of degradation phenomena of PLA materials is critical to manufacturing robust products by using 3D printing technologies. The objective of this study is to evaluate four machine learning algorithms to classify the degree of thermal degradation of heat-treated PLA materials based on Fourier transform infrared spectroscopy (FTIR) data. In this study, 3D printed PLA specimens were subjected to high-temperatures for extended periods of time to simulate thermal degradation and subsequently examined by using two types of FTIR spectrometers: desktop and portable spectrometers. Classifiers created by multi-class logistic regression and multi-class neural networks were appropriate prediction models for these datasets.
Design and Evaluation of a New Fuzzy Control Algorithm Applied to a Manipulator Robot
Authors: Urrea Claudio , Kern John , Alvarado Johanna
Published: October 2020

In this article, we propose a new scheme for a fuzzy logic controller, which includes acceleration as one of its linguistic variables, as opposed to other techniques and approaches that have been developed and reported in the literature. This method is used for controlling the tracking of the trajectory followed by the joints of a 2-DoF manipulator robot. To this end, a complete simulation environment is developed through the MatLab/Simulink® software. The dynamic model of the manipulator robot includes a vector that consists of the estimate of the friction forces present in the joints. Then, a controller based on fuzzy logic is designed and implemented for each joint. Finally, the performance of the developed system is assessed and then compared to the performance of a classic PID controller. The incorporation of the fuzzy variable acceleration significantly improved the system’s response.
Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements
Authors: Zhao Hua , Tan Chengjun , OBrien Eugene J. , Uddin Nasim , Zhang Bin
Published: October 2020

Accurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usually strain gauges, placed at particular locations on the underside of the bridge. To improve axle detection in the measured signals, this paper proposes a wavelet transform and Shannon entropy with a correlation factor. The proposed approach is first verified by numerical simulation and is then tested in two field trials. The fidelity of the proposed approach is investigated including noise in the measurement, multiple presence, different vehicle velocities, different types of vehicle and in real traffic flow.
Salivary Extracellular DNA and DNase Activity in Periodontitis
Authors: Konečná Barbora , Gaál Kovalčíková Alexandra , Pančíková Alexandra , Novák Bohuslav , Kovaľová Eva , Celec Peter , Tóthová Ľubomíra
Published: October 2020

Extracellular DNA (ecDNA) is a potential marker and predictor in several inflammatory diseases. Periodontitis, a chronic inflammatory disease, is associated with epithelial cell death and could lead to release of DNA. Our aim was to analyze salivary DNA concentration and deoxyribonuclease (DNase) activity in periodontitis patients. We hypothesized that salivary ecDNA will be higher than in controls and could serve as a marker of periodontitis severity. Samples of saliva were collected from 25 patients with chronic periodontitis and 29 age-matched controls. DNA was quantified fluorometrically in whole saliva, as well as in supernatants after centrifugation (depletion of cells at 1600× g) and in double-centrifuged supernatants (depletion of cell debris at 1600× g and 16,000× g). The subcellular origin of ecDNA was assessed using real-time PCR. In comparison to controls, patients with periodontitis had twofold higher salivary DNA (p < 0.01), higher mitochondrial DNA in centrifuged supernatants (p < 0.05) and lower nuclear ecDNA in double-centrifuged samples (p < 0.05). No correlations were found between salivary DNA and oral health status, but mitochondrial DNA positively correlated with papillary bleeding index in centrifuged samples. Salivary DNase activity was comparable between the groups. In conclusion, we proved that salivary DNA is higher in periodontitis. The source of the higher mitochondrial DNA in cell-free saliva and the causes of lower nuclear ecDNA remain to be elucidated. Further studies should focus on the role of mitochondrial DNA as a potential driver of inflammation in periodontitis.
Integrated Multifunctional Laryngoscope for Medical Diagnosis and Treatment
Authors: Liang Shanshan , Li Xinyu , Kang Jiajing , Zou Jiebin , Liang Faya , Zhang Jun
Published: October 2020

Laryngeal lesions can cause great inconvenience to patients. Early diagnosis and corresponding treatments are critical to the survival of patients. However, the diagnosis and precise removal of tumors remain a challenge under the use of a white light laryngoscope. In this work, an integrated, multifunctional laryngoscope was designed and tested for the imaging evaluation and precision laser surgery for laryngeal tissue. This integrated diagnostic and therapeutic endoscopic system included two imaging modes (i.e., optical coherence tomography and white light endoscopy) and a laser ablation treatment mode. The endoscope had a common-path design to ensure that the same position could be imaged and treated simultaneously. The ex vivo porcine larynx experimental results showed that the system imaging modes could simultaneously acquire both superficial and cross-sectional images of the sample tissue, and the ablation treatment could be performed under imaging guidance. This multifunctional laryngoscope has great potential for the early diagnosis of and accurate laser ablation surgery for laryngeal tumors.
Dual Functional Composite of Montmorillonite-Rich/Chitosan (MCC) for Decolorizing the Water Used in Joss Paper Process: Thermodynamic, Isotherm, and Kinetic Studies
Authors: Muangrak Witsarut , Thouchprasitchai Nutthavich , Phongboonchoo Yuththaphan , Pongstabodee Sangobtip
Published: October 2020

A hybrid montmorillonite (Mt)-rich/chitosan composite (MCC) with high adsorption performance was synthesized for the decolorization of water used in the joss paper process. The performance was reported in terms of the dye removal. The composite expressed higher performance than chitosan or Mt-rich clay, respectively. The optimum condition for complete dye removal was achieved when using at least 0.6 g of the composite over a wide pH range (3–10) and initial dye concentration (10–100 mg L−1). The composite showed good reusability without the requirement of regeneration, adsorbing the dye completely for up to eight successive cycles of adsorption (>1.33 gdye gMCC−1). Thermodynamic analyses revealed the degree of spontaneity and the endothermic adsorption process. From the isotherm studies, the Koble–Corrigan isotherm model fitted very well to the experimental data, revealing that the composite had a heterogeneous surface with various active sites to adsorb the dye molecules. This also evidenced the synergistic electrostatic attraction and hydrophobic interaction between the dye and the composite. The pseudo-second-order model best explained the kinetic rate of adsorption. From evaluation of the adsorption process using the Webber and Morris equation and Boyd model, the rate-limiting step consisted of film diffusion and intra-particle diffusion.
Application of Advanced Measuring Methods for Identification of Stresses and Deformations of Automotive Structures
Authors: Pástor Miroslav , Živčák Jozef , Puškár Michal , Lengvarský Pavol , Klačková Ivana
Published: October 2020

In the automotive industry, 3D laser scanning is the most frequently used method to check the geometry of the shape and dimensions of a body in individual stages of production, where the scanned model is compared in a computer model. This procedure identifies excessive deformations around the roof antenna of an SUV. The manufacturer assumed that these deformations occurred during the antenna assembly process. An analysis of possible causes of deformation occurrence was performed based on the comparison of results obtained by numerical and experimental modelling. Experimental measurements using tensometry performed on a painted and unpainted roof structure showed the effect of paint reinforcement on deformations around the antenna. Based on the analysis of results obtained directly under operational load, it was found that the installation of the antenna was carried out on the already deformed roof plate and the installation process itself was not the primary cause of the identified excessive deformations. The presented results of deformation and stress analysis document deeper connections between the measured displacements of 3D scanning and the technological process of component production itself. The use of the achieved results should especially help designers, calculators, technologists as well as production quality controllers.
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic
Authors: Rezaei Mahdi , Azarmi Mohsen
Published: October 2020

Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national health authorities have set the 2-m physical distancing as a mandatory safety measure in shopping centres, schools and other covered areas. In this research, we develop a hybrid Computer Vision and YOLOv4-based Deep Neural Network (DNN) model for automated people detection in the crowd in indoor and outdoor environments using common CCTV security cameras. The proposed DNN model in combination with an adapted inverse perspective mapping (IPM) technique and SORT tracking algorithm leads to a robust people detection and social distancing monitoring. The model has been trained against two most comprehensive datasets by the time of the research—the Microsoft Common Objects in Context (MS COCO) and Google Open Image datasets. The system has been evaluated against the Oxford Town Centre dataset (including 150,000 instances of people detection) with superior performance compared to three state-of-the-art methods. The evaluation has been conducted in challenging conditions, including occlusion, partial visibility, and under lighting variations with the mean average precision of 99.8% and the real-time speed of 24.1 fps. We also provide an online infection risk assessment scheme by statistical analysis of the spatio-temporal data from people’s moving trajectories and the rate of social distancing violations. We identify high-risk zones with the highest possibility of virus spread and infection. This may help authorities to redesign the layout of a public place or to take precaution actions to mitigate high-risk zones. The developed model is a generic and accurate people detection and tracking solution that can be applied in many other fields such as autonomous vehicles, human action recognition, anomaly detection, sports, crowd analysis, or any other research areas where the human detection is in the centre of attention.
When Deep Learning Meets Data Alignment: A Review on Deep Registration Networks (DRNs)
Authors: Villena-Martinez Victor , Oprea Sergiu , Saval-Calvo Marcelo , Azorin-Lopez Jorge , Fuster-Guillo Andres , Fisher Robert B.
Published: October 2020

This paper reviews recent deep learning-based registration methods. Registration is the process that computes the transformation that aligns datasets, and the accuracy of the result depends on multiple factors. The most significant factors are the size of input data; the presence of noise, outliers and occlusions; the quality of the extracted features; real-time requirements; and the type of transformation, especially those defined by multiple parameters, such as non-rigid deformations. Deep Registration Networks (DRNs) are those architectures trying to solve the alignment task using a learning algorithm. In this review, we classify these methods according to a proposed framework based on the traditional registration pipeline. This pipeline consists of four steps: target selection, feature extraction, feature matching, and transform computation for the alignment. This new paradigm introduces a higher-level understanding of registration, which makes explicit the challenging problems of traditional approaches. The main contribution of this work is to provide a comprehensive starting point to address registration problems from a learning-based perspective and to understand the new range of possibilities.
A Novel Precipitate-Type Architected Metamaterial Strengthened via Orowan Bypass-Like Mechanism
Authors: Lu Zhehao , Yan Wenyuan , Yan Pengfei , Yan Biao
Published: October 2020

The objective of the study is to investigate the strengthening mechanism of embedded meta-precipitates in the design of architected metamaterials. Four precipitate-type architected metamaterials are designed and prepared by fused deposition modelling (FDM). The difference of mechanical properties and deformation mode of these structures is analyzed. The strengthening effect of the introduced meta-precipitates is then compared with Orowan bypass strengthening mechanism. The similarities and discrepancies of metallurgical hardening principles and that found in architected metamaterials are established. It is found that due to the introduction of embedded meta-precipitates, the deformation of the structure changes significantly from diagonal crushing to a meander route, thus improves the mechanical properties and energy absorption abilities. The hindering effect and the influence of volume fraction of meta-precipitates is similar to Orowan bypass mechanism.
Cloning of Thalassiosira pseudonana’s Mitochondrial Genome in Saccharomyces cerevisiae and Escherichia coli
Authors: Cochrane Ryan R. , Brumwell Stephanie L. , Shrestha Arina , Giguere Daniel J. , Hamadache Samir , Gloor Gregory B. , Edgell David R. , Karas Bogumil J.
Published: October 2020

Algae are attractive organisms for biotechnology applications such as the production of biofuels, medicines, and other high-value compounds due to their genetic diversity, varied physical characteristics, and metabolic processes. As new species are being domesticated, rapid nuclear and organelle genome engineering methods need to be developed or optimized. To that end, we have previously demonstrated that the mitochondrial genome of microalgae Phaeodactylum tricornutum can be cloned and engineered in Saccharomyces cerevisiae and Escherichia coli. Here, we show that the same approach can be used to clone mitochondrial genomes of another microalga, Thalassiosira pseudonana. We have demonstrated that these genomes can be cloned in S. cerevisiae as easily as those of P. tricornutum, but they are less stable when propagated in E. coli. Specifically, after approximately 60 generations of propagation in E. coli, 17% of cloned T. pseudonana mitochondrial genomes contained deletions compared to 0% of previously cloned P. tricornutum mitochondrial genomes. This genome instability is potentially due to the lower G+C DNA content of T. pseudonana (30%) compared to P. tricornutum (35%). Consequently, the previously established method can be applied to clone T. pseudonana’s mitochondrial genome, however, more frequent analyses of genome integrity will be required following propagation in E. coli prior to use in downstream applications.
Kin-Mediated Male Choice and Alternative Reproductive Tactics in Spider Mites
Authors: Schausberger Peter , Sato Yukie
Published: October 2020

Optimal outbreeding and kin selection theories state that the degree of kinship is a fundamental determinant in any mating system. However, the role of kinship in male choice and alternative reproductive tactics (ARTs) is poorly known. We assessed the influence of kinship on male choice and expression of ARTs in two populations of two-spotted spider mites Tetranychus urticae. Male spider mites guard premature females, which is an indicator of mate choice, and may conditionally adopt fighting or sneaking tactics to secure access to females. Males competing with kin or non-kin were offered one kin or non-kin female (experiment 1) and single males were presented a choice of kin and non-kin females (experiment 2). Under kin competition, males of both populations were more prone to guard non-kin than kin females at a 3:1 fighter:sneaker ratio. Under non-kin competition, all males were fighters. Under no-choice, males used novelty as indicator of genetic dissimilarity, serving as absolute decision rule for outbreeding. Under choice, comparative evaluation allowed males to preferentially guard females with higher reproductive potential. Overall, our study suggests that male spider mites can assess kinship of rivals and prospective mates. Kin discrimination allows adaptive, context-specific non-random mating preference and adjustment of ARTs.
Enhanced Enrichment of Medaka Ovarian Germline Stem Cells by a Combination of Density Gradient Centrifugation and Differential Plating
Authors: Ryu Jun Hyung , Gong Seung Pyo
Published: October 2020

Fish ovarian germline stem cells (OGSCs) have great potential in various biological fields due to their ability to generate large numbers of mature eggs. Therefore, selective enrichment of OGSCs is a prerequisite for successful applications. To determine the optimal conditions for the enrichment of OGSCs from Japanese medaka (Oryzias latipes), we evaluated the effects of Percoll density gradient centrifugation (PDGC), differential plating (DP), and a combination of both methods. Based on cell morphology and gene expression of germ cell-specific Vasa and OGSC-specific Nanos2, we demonstrated that of seven density fractions obtained following PDGC, the 30–35% density fraction contained the highest proportion of OGSCs, and that Matrigel was the most effective biomolecule for the enrichment of Oryzias latipes OGSCs by DP in comparison to laminin, fibronectin, gelatin, and poly-l-lysine. Furthermore, we confirmed that PDGC and DP in combination significantly enhanced the efficiency of OGSC enrichment. The enriched cells were able to localize in the gonadal region at a higher efficiency compared to non-enriched ovarian cells when transplanted into the developing larvae. Our approach provides an efficient way to enrich OGSCs without using OGSC-specific surface markers or transgenic strains expressing OGSC-specific reporter proteins.
Protective Effects of Epigallocatechin Gallate (EGCG) on Endometrial, Breast, and Ovarian Cancers
Authors: Huang Yun-Ju , Wang Kai-Lee , Chen Hsin-Yuan , Chiang Yi-Fen , Hsia Shih-Min
Published: October 2020

Green tea and its major bioactive component, (−)-epigallocatechin gallate (EGCG), possess diverse biological properties, particularly antiproliferation, antimetastasis, and apoptosis induction. Many studies have widely investigated the anticancer and synergistic effects of EGCG due to the side effects of conventional cytotoxic agents. This review summarizes recent knowledge of underlying mechanisms of EGCG on protective roles for endometrial, breast, and ovarian cancers based on both in vitro and in vivo animal studies. EGCG has the ability to regulate many pathways, including the activation of nuclear factor erythroid 2-related factor 2 (Nrf2), inhibition of nuclear factor-κB (NF-κB), and protection against epithelial–mesenchymal transition (EMT). EGCG has also been found to interact with DNA methyltransferases (DNMTs) and histone deacetylases (HDACs), which affect epigenetic modifications. Finally, the action of EGCG may exert a suppressive effect on gynecological cancers and have beneficial effects on auxiliary therapies for known drugs. Thus, future clinical intervention studies with EGCG will be necessary to more and clear evidence for the benefit to these cancers.
Deep Brain Stimulation for Chronic Pain: Time to Reconsider the Skeptical Attitude?
Authors: Slavin Konstantin V. , Isagulayn Emil D. , Rzaev Dzhamil A.
Published: October 2020

Despite continuous advancements in systematic treatment of chronic pain there is still a subset of clinical conditions where the standard medical and surgical approaches are not uniformly effective [...]
Relations between Sensory Responsiveness and Features of Autism in Children
Authors: Feldman Jacob , Cassidy Margaret , Liu Yupeng , Kirby Anne , Wallace Mark , Woynaroski Tiffany
Published: October 2020

Autism is a neurodevelopmental condition defined by differences in social communication and by the presence of restricted and repetitive patterns of behavior, interests, and activities (RRBs). Individuals with autism also commonly present with atypical patterns of sensory responsiveness (i.e., hyporesponsiveness, hyperresponsiveness, and sensory seeking), which are theorized to produce cascading effects across other domains of development. The purpose of this study was to examine differences in sensory responsiveness in children with and without autism (ages 8–18 years), as well as relations between patterns of sensory responsiveness and core and related features of autism. Participants were 50 children with autism and 50 non-autistic peers matched on age and sex. A comprehensive clinical battery included multiple measures of sensory responsiveness, core features of autism, adaptive behavior, internalizing behaviors, cognitive ability, and language ability. Groups significantly differed on all three patterns of sensory responsiveness. Some indices of core and related autism features were robustly associated with all three patterns of sensory responsiveness (e.g., RRBs), while others were more strongly associated with discrete patterns of sensory responsiveness (i.e., internalizing problem behaviors and hyperresponsiveness, language and sensory seeking). This study extends prior work to show that differences in sensory responsiveness that are linked with core and related features of autism persist in older children and adolescents on the spectrum.
hATTR Pathology: Nerve Biopsy Results from Italian Referral Centers
Authors: Luigetti Marco , Romozzi Marina , Bisogni Giulia , Cardellini Davide , Cavallaro Tiziana , Di Paolantonio Andrea , Fabrizi Gian Maria , Fenu Silvia , Gentile Luca , Grandis Marina , Marucci Gianluca , Massucco Sara , Mazzeo Anna , Pareyson Davide , Romano Angela , Russo Massimo , Schenone Angelo , Tagliapietra Matteo , Tozza Stefano , Vita Giuseppe , Sabatelli Mario
Published: October 2020

Pathological evidence of amyloid on nerve biopsy has been the gold standard for diagnosis in hereditary transthyretin amyloidosis polyneuropathy (hATTR-PN) for a long time. In this article, we reviewed the pathological findings of a large series of sural nerve biopsies from a cohort of hATTR-PN patients, collected by different Italian referral centers. Patients and Methods: We reviewed clinical and pathological data from hATTR-PN patients, diagnosed and followed in five Italian referral centers for peripheral neuropathies. Diagnosis was formulated after a positive genetic test for transthyretin (TTR) mutations. Sural nerve biopsy was performed according to standard protocols. Results: Sixty-nine sural nerve biopsies from hATTR-PN patients were examined. Congo red positive deposits were found in 73% of cases. Only the Phe64Leu mutation failed to show amyloid deposits in a high percentage of biopsies (54%), as already described. Unusual pathological findings, such as myelin abnormalities or inflammatory infiltrates, were detected in occasional cases. Conclusions: Even if no longer indicated to confirm hATTR-PN clinical suspicion, nerve biopsy remains, in expert hands, a rapid and inexpensive tool to detect amyloid deposition. In Italy, clinicians should be aware that a negative biopsy does not exclude hATTR-PN, particularly for Phe64Leu, one of the most frequent mutations in this country.
An Optimal Time for Treatment—Predicting Circadian Time by Machine Learning and Mathematical Modelling
Authors: Hesse Janina , Malhan Deeksha , Yalҫin Müge , Aboumanify Ouda , Basti Alireza , Relógio Angela
Published: October 2020

Tailoring medical interventions to a particular patient and pathology has been termed personalized medicine. The outcome of cancer treatments is improved when the intervention is timed in accordance with the patient’s internal time. Yet, one challenge of personalized medicine is how to consider the biological time of the patient. Prerequisite for this so-called chronotherapy is an accurate characterization of the internal circadian time of the patient. As an alternative to time-consuming measurements in a sleep-laboratory, recent studies in chronobiology predict circadian time by applying machine learning approaches and mathematical modelling to easier accessible observables such as gene expression. Embedding these results into the mathematical dynamics between clock and cancer in mammals, we review the precision of predictions and the potential usage with respect to cancer treatment and discuss whether the patient’s internal time and circadian observables, may provide an additional indication for individualized treatment timing. Besides the health improvement, timing treatment may imply financial advantages, by ameliorating side effects of treatments, thus reducing costs. Summarizing the advances of recent years, this review brings together the current clinical standard for measuring biological time, the general assessment of circadian rhythmicity, the usage of rhythmic variables to predict biological time and models of circadian rhythmicity.
Thyroid Cancer and Circadian Clock Disruption
Authors: Malaguarnera Roberta , Ledda Caterina , Filippello Agnese , Frasca Francesco , Francavilla Vincenzo Cristian , Ramaci Tiziana , Parisi Maria Chiara , Rapisarda Venerando , Piro Salvatore
Published: October 2020

Thyroid cancer (TC) represents the most common malignancy of the endocrine system, with an increased incidence across continents attributable to both improvement of diagnostic procedures and environmental factors. Among the modifiable risk factors, insulin resistance might influence the development of TC. A relationship between circadian clock machinery disfunction and TC has recently been proposed. The circadian clock machinery comprises a set of rhythmically expressed genes responsible for circadian rhythms. Perturbation of this system contributes to the development of pathological states such as cancer. Several clock genes have been found deregulated upon thyroid nodule malignant transformation. The molecular mechanisms linking circadian clock disruption and TC are still unknown but could include insulin resistance. Circadian misalignment occurring during shift work, jet lag, high fat food intake, is associated with increased insulin resistance. This metabolic alteration, in turn, is associated with a well-known risk factor for TC i.e., hyperthyrotropinemia, which could also be induced by sleep disturbances. In this review, we describe the mechanisms controlling the circadian clock function and its involvement in the cell cycle, stemness and cancer. Moreover, we discuss the evidence supporting the link between circadian clockwork disruption and TC development/progression, highlighting its potential implications for TC prevention, diagnosis and therapy.
Subtraction Maps Derived from Longitudinal Magnetic Resonance Imaging in Patients with Glioma Facilitate Early Detection of Tumor Progression
Authors: Sollmann Nico , Gutbrod-Fernandez Magaly , Burian Egon , Riederer Isabelle , Meyer Bernhard , Hock Andreas , Gempt Jens , Zimmer Claus , Kirschke Jan S.
Published: October 2020

Progression of glioma is frequently characterized by increases or enhanced spread of a hyperintensity in fluid attenuated inversion recovery (FLAIR) sequences. However, changes in FLAIR signal over time can be subtle, and conventional (CONV) visual reading is time-consuming. The purpose of this monocentric, retrospective study was to compare CONV reading to reading of subtraction maps (SMs) for serial FLAIR imaging. FLAIR datasets of cranial 3-Tesla magnetic resonance imaging (MRI), acquired at two different time points (mean inter-scan interval: 5.4 ± 1.9 months), were considered per patient in a consecutive series of 100 patients (mean age: 49.0 ± 13.7 years) diagnosed with glioma (19 glioma World Health Organization [WHO] grade I and II, 81 glioma WHO grade III and IV). Two readers (R1 and R2) performed CONV and SM reading by assessing overall image quality and artifacts, alterations in tumor-associated FLAIR signal over time (stable/unchanged or progressive) including diagnostic confidence (1—very high to 5—very low diagnostic confidence), and time needed for reading. Gold-standard (GS) reading, including all available clinical and imaging information, was performed by a senior reader, revealing progressive FLAIR signal in 61 patients (tumor progression or recurrence in 38 patients, pseudoprogression in 10 patients, and unclear in the remaining 13 patients). SM reading used an officially certified and commercially available algorithm performing semi-automatic coregistration, intensity normalization, and color-coding to generate individual SMs. The approach of SM reading revealed FLAIR signal increases in a larger proportion of patients according to evaluations of both readers (R1: 61 patients/R2: 60 patients identified with FLAIR signal increase vs. R1: 45 patients/R2: 44 patients for CONV reading) with significantly higher diagnostic confidence (R1: 1.29 ± 0.48, R2: 1.26 ± 0.44 vs. R1: 1.73 ± 0.80, R2: 1.82 ± 0.85; p < 0.0001). This resulted in increased sensitivity (99.9% vs. 73.3%) with maintained high specificity (98.1% vs. 98.8%) for SM reading when compared to CONV reading. Furthermore, the time needed for SM reading was significantly lower compared to CONV assessments (p < 0.0001). In conclusion, SM reading may improve diagnostic accuracy and sensitivity while reducing reading time, thus potentially enabling earlier detection of disease progression.
MicroRNA in Papillary Thyroid Carcinoma: A Systematic Review from 2018 to June 2020
Authors: Hitu Liviu , Gabora Katalin , Bonci Eduard-Alexandru , Piciu Andra , Hitu Adriana-Cezara , Ștefan Paul-Andrei , Piciu Doina
Published: October 2020

The involvement of micro-ribonucleic acid (microRNAs) in metabolic pathways such as regulation, signal transduction, cell maintenance, and differentiation make them possible biomarkers and therapeutic targets. The purpose of this review is to summarize the information published in the last two and a half years about the involvement of microRNAs in papillary thyroid carcinoma (PTC). Another goal is to understand the perspective offered by the new findings. Main microRNA features such as origin, regulation, targeted genes, and metabolic pathways will be presented in this paper. We interrogated the PubMed database using several keywords: “microRNA” + “thyroid” + “papillary” + “carcinoma”. After applying search filters and inclusion criteria, a selection of 137 articles published between January 2018–June 2020 was made. Data regarding microRNA, metabolic pathways, gene/protein, and study utility were selected and included in the table and later discussed regarding the matter at hand. We found that most microRNAs regularly expressed in the normal thyroid gland are downregulated in PTC, indicating an important tumor-suppressor action by those microRNAs. Moreover, we showed that one gene can be targeted by several microRNAs and have nominally described these interactions. We have revealed which microRNAs can target several genes at once.
Role of Haematopoietic Stem Cell Transplantation in Peripheral T-Cell Lymphoma
Authors: Abeyakoon Chathuri , van der Weyden Carrie , Harrop Sean , Khot Amit , Dickinson Michael , Yannakou Costas K. , Prince H. Miles
Published: October 2020

Peripheral T-cell lymphomas (PTCLs) are distinct pathological entities with clinical advancements lagging behind their B-cell lymphoma counterpart. Frequently aggressive in their clinical behaviour, clinicians are constantly challenged with low complete remission rates, early relapses and failure to achieve long-term responses despite aggressive first-line chemotherapy, resulting in poor overall survival in the majority of patients. There is currently no consensus regarding the optimal therapy for PTCL and treatment approaches are mainly derived from prospective phase II studies, registry data and retrospective studies. Despite its biological heterogeneity, a less than satisfactory “one-size-fits-all” approach has been adopted to date. Although its role remains controversial, for many years, haematopoietic stem cell transplantation has been adopted by clinicians with the aim of overcoming poor outcomes by consolidating responses. In this review, we aim to define the role of both autologous and allogeneic stem cell transplantation in PTCL in both frontline and salvage settings, especially in the context of recent advancements in this field.
Olaparib Synergizes the Anticancer Activity of Daunorubicin via Interaction with AKR1C3
Authors: Tavares Tássia S. , Hofman Jakub , Lekešová Alžběta , Želazková Jana , Wsól Vladimír
Published: October 2020

Olaparib is a potent poly (ADP-ribose) polymerase inhibitor currently used in targeted therapy for treating cancer cells with BRCA mutations. Here we investigate the possible interference of olaparib with daunorubicin (Daun) metabolism, mediated by carbonyl-reducing enzymes (CREs), which play a significant role in the resistance of cancer cells to anthracyclines. Incubation experiments with the most active recombinant CREs showed that olaparib is a potent inhibitor of the aldo–keto reductase 1C3 (AKR1C3) enzyme. Subsequent inhibitory assays in the AKR1C3-overexpressing cellular model transfected human colorectal carcinoma HCT116 cells, demonstrating that olaparib significantly inhibits AKR1C3 at the intracellular level. Consequently, molecular docking studies have supported these findings and identified the possible molecular background of the interaction. Drug combination experiments in HCT116, human liver carcinoma HepG2, and leukemic KG1α cell lines showed that this observed interaction can be exploited for the synergistic enhancement of Daun’s antiproliferative effect. Finally, we showed that olaparib had no significant effect on the mRNA expression of AKR1C3 in HepG2 and KG1α cells. In conclusion, our data demonstrate that olaparib interferes with anthracycline metabolism, and suggest that this phenomenon might be utilized for combating anthracycline resistance.
The Mechanisms of PD-L1 Regulation in Non-Small-Cell Lung Cancer (NSCLC): Which Are the Involved Players?
Authors: Lamberti Giuseppe , Sisi Monia , Andrini Elisa , Palladini Arianna , Giunchi Francesca , Lollini Pier-Luigi , Ardizzoni Andrea , Gelsomino Francesco
Published: October 2020

Treatment with inhibition of programmed cell death 1 (PD-1) or its ligand (PD-L1) improves survival in advanced non-small-cell lung cancer (NSCLC). Nevertheless, only a subset of patients benefit from treatment and biomarkers of response to immunotherapy are lacking. Expression of PD-L1 on tumor cells is the primary clinically-available predictive factor of response to immune checkpoint inhibitors, and its relevance in cancer immunotherapy has fostered several studies to better characterize the mechanisms that regulate PD-L1 expression. However, the factors associated with PD-L1 expression are still not well understood. Genomic alterations that activate KRAS, EGFR, and ALK, as well as the loss of PTEN, have been associated with increased PD-L1 expression. In addition, PD-L1 expression is reported to be increased by amplification of CD274, and decreased by STK11 deficiency. Furthermore, PD-L1 expression can be modulated by either tumor extrinsic or intrinsic factors. Among extrinsic factors, the most prominent one is interferon-γ release by immune cells, while there are several tumor intrinsic factors such as activation of the mechanistic target of rapamycin (mTOR), mitogen-activated protein kinase (MAPK) and Myc pathways that can increase PD-L1 expression. A deeper understanding of PD-L1 expression regulation is crucial for improving strategies that exploit inhibition of this immune checkpoint in the clinic, especially in NSCLC where it is central in the therapeutic algorithm. We reviewed current preclinical and clinical data about PD-L1 expression regulation in NSCLC.