bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on bogie traction seat crack identification based on OvO multi-feature fusion
Authors: Chang Qi , Liu Yi , Li Lin , Man Junfeng , Peng Cheng , Liu Kai , Wu Han , Shen Yiping
Published: June 2021

Aimed at the problems of unsatisfactory feature extraction and low diagnostic accuracy in the identification process during train bogie traction seat operation status , an optimized method of the neural network model of back propagation based on OvO multi-feature fusion is proposed. Firstly, a simulated experimental platform is built to collect vibration signals, and the collected original vibration data are analyzed in time domain, frequency domain and time-frequency. Secondly, the principal component analysis is carried out on the proposed high-dimensional feature sets. Finally, the reduced dimensional features are fused into the optimal feature set based on OvO algorithm. The back propagation neural network model is constructed, and the time domain, frequency domain, time-frequency and optimal feature sets are taken as inputs respectively, and the results of output recognition are compared. The experimental results show that the recognition accuracy of back propagation neural network model based on OvO multi-feature fusion is higher, and the running state of bogie traction seat can be recognized accurately.
Investigating the Immune Function and Proteomic Profiles of Plasmal Exosomes in Lactobacillus Plantarum-treated Immunosuppressive Broilers
Authors: Liu Huawei , Zhao Fan , Zhang Kai , Zhao Jinshan , Wang Yang
Published: June 2021

Background: Exosomes are extracellular membranous nanovesicles that carry functional molecules, such as proteins, to mediate local and systemic cell-to-cell communication. Exosomes released by cells can present in the plasma and involved in the regulation of immunity. Probiotics play a beneficial role in improving the immune function of host through many mechanisms. However, whether probiotics can increase the immune function of broilers by regulating plasmal exosomal cargo is unclear. Methods: Three hundred broilers were allocated to three treatments: control diet (CON group), control diet + dexamethasone (DEX) injection (DEX group), control diet containing 1 × 108 cfu/g Lactobacillus plantarum P8 + DEX injection (P8+DEX group). The immune function of broilers was detected by measuring the levels of inflammatory cytokines and immunoglobulins in plasma and jejunal mucosa. Exosomes were isolated from the plasma via EIQ3 isolation kits and characterized via transmission electron microscopy, nanoparticle tracking analysis, and Western blot. Then, exosomal protein profile was determined by proteomic. At last, correlation analysis was performed to figure out the potential role of exosomal proteins in regulating immune function of P8-treated broilers.Results: P8+DEX treatment improved the immune function of DEX-induced immunosuppressive broiler through decreasing plasmal IL-1β, IL-6, TNF-α and jejunal IL-1β, as well as increasing plasmal IL-10 and jejunal IgM. The isolated extracellular vesicles had an average diameter of 125.8 nm, exhibited a cup-shaped morphology and expressed exosomal markers. A total of 784 proteins were identified in the exosomes. Among the 784 proteins, 126 differentially expressed proteins (DEPs) were found between DEX and CON groups, 102 DEPs were found between P8+DEX and DEX groups. Gene Ontology analysis indicated that DEPs between DEX and CON groups are mainly involved in metabolic process, cellular anatomical entity, cytoplasm, extracellular region and binding. DEPs between P8+DEX and DEX are mainly involved in multicellular organismal process, response to stimulus, cytoplasm, cell periphery, membrane, binding, protein binding and ion binding. Further, pathway analysis revealed that most of the DEPs between DEX and CON participated in the ECM-receptor interaction, focal adhesion, regulation of actin cytoskeleton, endocytosis and phagosome. Most of the DEPs between P8+DEX and DEX participated in the ErbB and PPAR signaling pathways. Moreover, many immunity-related DEPs were correlated with the altered immune parameters in plasma and jejunal in broilers fed with P8.Conclusions: Our findings demonstrated that plasmal exosomes in immunosuppressive broilers fed with P8 carry proteins related to immune function, and may have immunomodulatory effects on the plasma and intestinal immunity.
The Effects of Mismatch between SPECT and CT Images on Quantitative Activity Estimation – A Simulation Study
Authors: Lyu Yingqing , Chen Yue , Mok Greta
Published: June 2021

Background: Quantitative activity estimation is essential in targeted radionuclide therapy dosimetry. Misregistration between SPECT and CT images at the same imaging time point due to patient movement degrades accuracy. This work aims to study the mismatch effects between CT and SPECT data on attenuation correction (AC), volume-of-interest (VOI) delineation and registration for activity estimation.Methods: Nine 4D XCAT phantoms were generated at 1, 24, and 144 hrs post In-111 Zevalin injection, varying in activity distributions, body and organ sizes. Realistic noisy SPECT projections were generated by an analytical projection and reconstructed with quantitative OS-EM method. CT images were shifted from -5 to 5 voxels as well as according to clinical reference corresponding to SPECT images at each time point. For AC effect, mismatched CT images were used for AC in SPECT reconstruction while VOIs were mapped out from matched CTs. For VOI effect, target organs were mapped out using mismatched CTs with matched CTs for AC. For registration effect, non-rigid registrations were performed on sequential mismatched CTs to align corresponding SPECT images, with no AC and VOI mismatch. Bi-exponential curve fitting was performed to obtain time-integrated activity (TIA). Organ activity errors (%OAE) and TIA errors (%TIAE) were calculated.Results: According to clinical reference, %OAE was larger for organs near ribs for AC effect, e.g., -2.58%±0.81% for liver. For VOI effect, %OAE was larger for small and low uptake organs, e.g., -11.94%±10.34% for spleen. %OAE was proportional to mismatch magnitude, e.g., 4.77%±1.41%, 12.01%±3.97% and 42.81%±6.38% for 1-, 2-, and 5-voxel mismatch for lungs. For registration effect, %TIAE were larger when mismatch existed in more numbers of SPECT/CT images, while no substantial difference was observed when using mismatched CT at different time points for registration reference. %TIAE was highest for VOI, followed by registration and AC, e.g., 37.61%±5.08%, 14.25%±7.07% and 1.13%±0.90% respectively for kidneys.Conclusions: The mismatch between CT and SPECT images poses a significant impact on accuracy of quantitative activity estimation in dosimetry, attributed particularly from VOI delineation errors. It is recommended to perform registration between emission and transmission images at the same time point to ensure dosimetric accuracy.
Spatiotemporal single-cell analysis reveals critical roles of mechano-sensing genes at the border zone in remodeling after myocardial infarction
Authors: Yamada Shintaro , Ko Toshiyuki , Hatsuse Satoshi , Nomura Seitaro , Zhang Bo , Dai Zhehao , Inoue Shunsuke , Kubota Masayuki , Sawami Kosuke , Yamada Takanobu , Sassa Tatsuro , Katagiri Mikako , Fujita Kanna , Katoh Manami , Ito Masamichi , Harada Mutsuo , Toko Haruhiro , Takeda Norifumi , Morita Hiroyuki , Aburatani Hiroyuki , Komuro Issei
Published: June 2021

The left ventricular remodeling after myocardial infarction (MI) causes heart failure, but its underlying mechanisms remain largely unknown. Here, we performed an integrative analysis of spatial transcriptomics and single cell RNA-seq in murine MI model and found that mechanical stress-response genes are expressed at the border zone and play a critical role in left ventricular remodeling after MI. Single-cardiomyocyte RNA-seq of the heart after MI divided cardiomyocytes into 8 clusters. We identified the cell cluster which was specifically derived from the ischemic area in an early stage after MI and expressed mechano-sensing genes such as Csrp3, Ankrd1 and Ankrd2. Spatial transcriptomic analysis demonstrated that cardiomyocytes with this gene expression profile were specifically localized at the border zone in post-MI day 1. AAV9-mediated gene silencing of Csrp3 exacerbated cardiac dilatation and dysfunction after MI. Collectively, our datasets and findings not only provide an insight into spatiotemporal molecular pathogenesis of myocardial infarction but also highlight mechano-sensing genes at the border zone as an adaptive regulator of left ventricular remodeling.
Ghrelin pretreatment enhanced the protective effect of bone marrow-derived mesenchymal stem cell conditioned medium on lipopolysaccharide-induced endothelial cells injury
Authors: Ge Shanhui , He Wanmei , Zhang Lishan , Lin Shan , Luo Yuling , Chen Qingui , Zeng Mian
Published: June 2021

Background
Lung endothelial barrier injury plays a crucial role in the pathophysiology of acute respiratory distress syndrome, and it has been demonstrated that bone marrow-derived mesenchymal stem cells conditioned medium (BMSCs-CM) and ghrelin both exert a potential protective impact. The study aimed to investigate whether ghrelin pretreatment enhanced the protective effect of BMSCs-CM on lipopolysaccharide (LPS)-induced endothelial cells injury.
Methods
BMSCs were isolated from rat bone marrow and used for the experiment after expanded and meeting the phenotypic criteria for defining MSCs identified by flow cytometry. The effect of conditioned medium derived from ghrelin pretreated BMSCs (BMSCsGhrelin pretreated-CM) on LPS injured endothelial cells was evaluated by examing its impact on the migration capability, apoptosis, and the release of pro-inflammatory factors (TNF-α, IL-1β, and IL-6) of endothelial cells. To further clarify the potential mechanisms, the activation of the AKT/GSK3β pathway in endothelial cells was examined by western blot and the gene expression profiles of BMSCs pretreated by ghrelin were examined by RNA sequencing.
Results
BMSCsGhrelin pretreated-CM showed a grtear protective effect on LPS-induced endothelial cells injury than BMSCs-CM by improving cell migration, alleviating apoptosis, and reducing the release of pro-inflammatory factors of endothelial cells. The mechanism partly related to the activation of the AKT/GSK3β pathway after BMSCsGhrelin pretreated-CM treatment. Five upregulated candidate genes (Wnt5a, S100b, Bmp2, Id4, and Pthlh) were identified in BMSCs after ghrelin treatment which were associated with the activation of AKT pathways and endothelial function.
Conclusions
Ghrelin pretreatment enhanced the protective effect of BMSCs-CM on LPS-induced endothelial cells injury partly by activating the AKT/GSK3β pathway.
Nonlinear Dynamic Analysis of Variable lead Preloaded Single Nut Ball Screw Considering the Variation of Working Parameters
Authors: Liu zhendong , xu mengtao , zhang hongzhuang , Li Changyou , Yao Guo , li zhenyuan , miao Huihui , wang chenyu , zhang yimin
Published: June 2021

In this study, a 5-degrees-of-freedom dynamic model of variable lead preloaded single nut ball screw is proposed. The proposed model considers the effect of excitation amplitude, deflection angle, the number of balls, and the preload into consideration. Moreover, to study the effect of working parameters on nonlinear dynamics, bifurcation diagram, 3-D frequency spectrum, phase diagram and Poincaré section with different system parameters are shown in discussion section. The numerical analysis indicates that the system can exhibits different motion states, and the continuous frequency component can be observed. Moreover, a series of experiments are conducted to estimate the dynamic parameters and validate the proposed dynamic model.
Characteristics and Potential Quality Indicators for Evaluating Pre-travel Consultations in Japan Hospitals: the Japan Pretravel Consultation Registry (J-PRECOR)
Authors: Yamamoto Kei , Asai Yusuke , Nakatani Issaku , Hayashi Kenichi , Nakagawa Hidenori , Shinohara Koh , Kanai Shinichiro , Shimatani Michitsugu , Yamato Masaya , Shimono Nobuyuki , Kitaura Tsuyoshi , Komiya Nobuhiro , Nagasaka Atsushi , Mikawa Takahiro , Manabe Akihiro , Matono Takashi , Yamamoto Yoshihiro , Ogawa Taku , Kutsuna Satoshi , Ohmagari Norio
Published: June 2021

BackgroundAwareness of pre-travel consultation (PTC) and prevention methods of overseas travel-related diseases is low in Japan, and understanding of PTC among Japanese travelers and medical professionals remains low. A multicenter registry was established to examine PTC in Japan. This study assessed the PTC implementation rate and examined indicators to be used as criteria for data-quality evaluation.MethodsClients who presented for PTC at 17 facilities registered between February 1, 2018, and May 31, 2020, were included. Medical information was retrospectively extracted via a web-based system. Correlations between vaccination risk categories and advice/intervention proportions by facility were evaluated by Spearman’s ordered phase relations (α=0.05).ResultsOf 9,700 eligible clients (median age, 32 years; 880 (9.1%) aged <16 years and 549 (5.7%) aged ≥65 years), the most common travel duration was ≥181 days (35.8%), higher among younger clients. The most common reason for travel was business (40.5%); the US (1,118 [11.5%]) and Asia (4,008 [41.3%]) were the most common destination and continent, respectively. Vaccine number (median 3 per person) increased after PTC except for tetanus toxoid. Only 60.8% of clients recommended for malaria prophylaxis received anti-malarial agents. The gross national income, incidence of human rabies, typhoid fever, and falciparum malaria, and dengue risk category were associated with the percentage of hepatitis-A vaccine, explaining rabies post-exposure prophylaxis, typhoid-fever vaccination, malaria-prophylaxis prescription, and mosquito repellants, respectively.ConclusionsAlthough the characteristics of travelers differ, the quality of PTC should improve to address, for example, the lower rate of acceptance of malaria prophylaxis in Japan.
Hormone Replacement Therapy With GnRH Agonist Pretreatment Improves Pregnancy Outcomes in Patients With Previous Intrauterine Adhesions: a Retrospective Study
Authors: Mo Meilan , Zheng Qizhen , Zhang Hongzhan , Xu Shiru , Xu Fen , Wang Yan , Zeng Yong
Published: June 2021

Objective: This retrospective study aimed to explore the optimal endometrial preparation method in women with intrauterine adhesions (IUAs).Method: A total of 882 frozen-thawed embryo transfer (FET) cycles from patients with history of IUAs were categorized into three groups based on endometrial preparation methods: hormone replacing therapy cycle (HRT, n=636), natural cycle (NC n=174), and HRT with GnRH-a pretreatment (HRT+GnRH-a, n=72. Logistic regression was performed to investigate the association between cycle regimens and pregnancy outcomes. Subgroup analysis of IUAs combined with thin endometrium (≤7mm) was also performed.Results: HRT with GnRH-a pretreatment was associated with higher incidences of clinical pregnancy, ongoing pregnancy, and live birth, but lower early miscarriage compared with either HRT or NC. Logistic regression indicated that after controlling for potential confounders, the incidences of live birth (HRT+GnRH-a as reference; NC: aOR=0.577, 95%CI 0.304-1.093; HRT: aOR=0.434, 95%CI 0.247-0.765) and ongoing pregnancy (NC: aOR=0.614, 95%CI 0.324-1.165; HRT: aOR=0.470, 95%CI 0.267-0.829) remained significantly higher in HRT+GnRH-a compared to those in HRT, but comparable to those in NC. While there was no significant difference with respect to the clinical pregnancy rate (NC: aOR=0.695, 95%CI 0.374-1.291; HRT: aOR=0.650, 95%CI 0.374-1.127) and early miscarriage rate (NC: aOR=1.734, 95%CI 0.417-7.175; HRT: aOR=2.594, 95%CI 0.718-9.378) between groups. Subgroup analysis suggested there was no superiority of endometrial preparation method in IUAs combined with thin endometrium.Conclusion: HRT with GnRH-a pretreatment improves pregnancy outcomes in women with history of IUAs. GnRH-a may restore the endometrial receptivity in the FET cycles in IUAs.
An Effector Index to Predict Target Genes at GWAS Loci
Authors: Forgetta Vincenzo , Jiang Lai , Vulpescu Nicholas , Hogan Meganq , Chen Siyuan , Morris John , Grinek Stepan , Benner Christian , Jang Dong-Keun , Hoang Quy , Burtt Noel , Flannick Jason , McCarthy Mark , Fauman Eric , Greenwood Celia , Maurano Matthew , Richards Brent
Published: June 2021

Drug development and biological discovery require effective strategies to map existing genetic associations to causal genes. To approach this problem, we selected 12 common diseases and quantitative traits for which highly powered genome-wide association studies (GWAS) were available. For each disease or trait, we systematically curated positive control gene sets from Mendelian forms of the disease and from targets of medicines used for disease treatment. We found that these positive control genes were highly enriched in proximity of GWAS-associated single nucleotide variants (SNVs). We then performed quantitative assessment of the contribution of commonly used genomic features, including open chromatin maps, expression quantitative trait loci (eQTL), and chromatin conformation data. Using these features, we trained and validated an Effector Index (Ei), to map target genes for these 12 common diseases and traits. Ei demonstrated high predictive performance, both with cross-validation on the training set, and an independently derived set for type 2 diabetes. Key predictive features included coding or transcript altering SNVs, distance to gene, and open chromatin-based metrics. This work outlines a simple, understandable approach to prioritize genes at GWAS loci for functional follow-up and drug development, and provides a systematic strategy for prioritization of GWAS target genes.
Antibiotic Resistance Prediction and Biomarker Discovery in Neisseria Gonorrhoeae
Authors: Goyal Rushank , Chowdhary Rashmi
Published: June 2021

Antibiotic resistance is a global problem projected to kill 10 million each year by 2050 and the CDC lists Neisseria gonorrhoeae among the most urgent threats in this area. There also exists a severe lack of efficient resistance detection techniques as only a handful of mutations have been identified as causing resistance thus far. In this study, eight models were trained on three datasets containing data regarding azithromycin, ciprofloxacin and cefixime, three drugs of choice against N. gonorrhoeae. Each dataset had 3000+ samples and their corresponding resistance values; each sample consisted of a binary series representing the presence/absence of certain base pair sequences within that sample's genome. The base pair sequences were special regions called unitigs (short sequence reads of the genome) that were also designed to have biological relevance. This novel technique differs from the standard research in this field, which has almost exclusively used whole-genome sequences. Once the models were trained, their accuracies, sensitivities and specificities were compared and analyzed. Maximum accuracies of 97.6%, 95.9% and 100% were achieved on azithromycin, ciprofloxacin and cefixime training data respectively. Secondly, Fisher's exact test was used to test for the existence of genetic signatures i.e. biomarkers that had a statistically significant correlation with antibiotic resistance. The feature importances of the top models from the first step were used to create a ranking of these genetic signatures, again a novel concept. Out of 584,362 unitigs, 191, 3304 and 1 were identified as statistically significant for azithromycin, ciprofloxacin and cefixime respectively. Lastly, protein biomarkers were also identified for the top 10 genetic signatures, resulting in several new discoveries not described before in scientific literature. Overall, this study led to the development of a new technique for biomarker discovery and resistance prediction in bacteria along with the creation of highly accurate machine learning models and identification of genetic and protein biomarkers for resistance against three drugs in N. gonorrhoeae. The model can be used for genotype-based resistance diagnosis and the biomarkers can be further developed for point-of-care testing in the future.
A Data-driven Model of the COVID-19 Spread among Interconnected Populations: Epidemiological and Mobility Aspects Following the Lock-down in Italy
Authors: GIAMBERARDINO Paolo DI , Iacoviello Daniela , Papa Federico , Sinisgalli Carmela
Published: June 2021

An epidemic multi-group model formed by interconnected SEIR-like structures is formulated and used for data fitting to gain insight into the COVID-19 dynamics and into the role of non-pharmaceutical control actions implemented to limit the infection spread since its outbreak in Italy. The single submodels provide a rather accurate description of the COVID-19 evolution in each subpopulation by an extended SEIR model including the class of asymptomatic infectives, which is recognized as a determinant for disease diffusion. The multi-group structure is specifically designed to investigate the effects of the interregional mobility restored at the end of the first strong lock-down in Italy (June 3, 2020). In its time-invariant version, the model is shown to enjoy some analytical stability properties which provide significant insights on the efficacy of the implemented control measurements. In order to highlight the impact of human mobility on the disease evolution in Italy between the first and second wave onset, the model is applied to fit real epidemiological data of three geographical macro-areas in the period March-October 2020, including the mass departure for summer holidays. The simulation results are in good agreement with the data, so that the model can represent a useful tool for predicting the effects of the combination of containment measures in triggering future pandemic scenarios. Particularly, the simulation shows that, although the unrestricted mobility alone appears to be insufficient to trigger the second wave, the human transfers were crucial to make uniform the spatial distribution of the infection throughout the country and, combined with the restart of (production, trade and education) activities, determined a time advance of the contagion increase (autumn 2020).
Right Ventricular Strain in Repaired Tetralogy of Fallot After Pulmonary Valve Replacement With Reconstructed Radial Long-axis Cine Magnetic Resonance Images
Authors: Kawakubo Masateru , Yamasaki Yuzo , Toyomura Daisuke , Yamamura Kenichiro , Sakamoto Ichiro , Moriyama Tetsuhiro , Yabuuchi Hidetake , Ishigami Kousei
Published: June 2021

Objectives: To investigate changes in right ventricular (RV) strain after pulmonary valve replacement (PVR) in repaired tetralogy of Fallot (TOF) by applying a novel postprocessing technique to conventional short-axis cine MRI to measure RV strains before and after PVR.Methods: Twenty-four patients with repaired TOF who underwent PVR and 16 healthy controls were enrolled. Global maximum and minimum principal strains (GPSmax, GPSmin) and global circumferential and longitudinal strains (GCS, GLS) were measured from short-axis cine images reconstructed radially along the long axis. Strain parameters before and after PVR were compared using paired t-tests. One-way ANOVA with Tukey post-hoc analysis was used for comparisons between the before and after PVR groups and the control group. Results: There were no differences in strain parameters before and after PVR. The GPSmax before PVR was lower than that in the control group (P=0.002). Before and after PVR, GCSs were higher and GLSs were lower than those in the control group (before and after GCSs: P=0.002 for both, before and after GLSs: P<0.0001 and P=0.0003). Conclusions: RV strains from radially reconstructed short-axis cine images revealed impaired myocardial motion after PVR. When compared to the control group, changes in GCS and GLS in TOF patients before and after PVR might be due to RV remodeling.
Redefining Homogeneous Climate Regions in Bangladesh Using Multivariate Clustering Approaches
Authors: Mahmud Sultan , Sumana Ferdausi Mahojabin , Mohsin Md. , Khan Md Hasinur Rahaman
Published: June 2021

The knowledge of the climate pattern for a particular region is important to alleviate the impact of climate change and protect the environment by taking appropriate actions based on geographical knowledge. It is also equally important for water resources planning and management. In this study, the regional disparities and similarities have been revealed among different climate stations or regions in Bangladesh based on different climatological factors such as rainfall, temperatures, relative humidity, sea level pressure, cloud cover, wind speed, the sunshine hour. We have selected one of the best-fitted algorithms for particular climate data from three multivariate clustering approaches named hierarchical clustering, partitioning around medoids (PAM), and K-means clustering by using different validation tests. Four homogeneity tests (Mann-Kendall Test, Pettitt's test, Buishand Range Test, Standard Normal Homogeneity Test) also have been performed for each of the clusters created based on several factors. The results suggest that the climate regions or meteorological stations of Bangladesh can be clustered into two groups based on a combination of climatological variables. According to the findings, there is a huge variation between the two groups in terms of climatological factors. The first group (cluster 1) is located in the northern part of the country that includes drought-prone and vulnerable regions, whereas, the second group (cluster 2) contains rain-prone and hilly regions, which are mostly situated in the southern part. All newly defined clusters show homogeneous behavior with few exceptions such as clusters based on sea level pressure are not homogeneous.
Design and Application of Diamond Bit Water Passage System, Seafloor Drill Parameters
Authors: Wang Jialiang , Qian Dilei , Sun Yang , Peng Fenfei
Published: June 2021

The operation and formation characteristics of a seafloor drill are utilized to design a water passage system for bottom-jetting diamond bits based on the multi-objective optimization theory. Fluid dynamics theory and the effects of bit rotation on the flow field at the hole bottom are used to analyze the impact of structural and drilling parameters of the HQ-size bit on the flow field of the waterway system. Considering the effect of the grinding length ratio of the bit on the lopsided wear of the inner and outer diameters, the water passage system parameter design and maximum projection area of the cutting tooth are effective optimization goals to improve the normal service life of the bit. The flow field of the drilling fluid at the hole bottom becomes more turbulent and the efficiency of carrying cuttings return decreases as the waterway height of the bit increases. The optimal bit rotation speed is 250–400 rpm. When drilling into conventional formations, the pump displacement should be controlled within the range of 50–80 L/min. When drilling into sediment formations, the pump displacement should be controlled within the range of 50–65 L/min. An on-site drilling test verified the rationality of the bit water passage system design and corresponding drilling parameters.
Lacidipine Attenuates Symptoms of Nicotine-Withdrawal in Mice
Authors: Khurana Kunal , Kumar Manish , Bansal Nitin
Published: June 2021

Nicotine-withdrawal after daily exposure manifests somatic and affective symptom including a range of cognitive deficits. Earlier studies suggested participation of L-type calcium channels (LTCCs) in development of nicotine dependence and expression of withdrawal signs. An upsurge in Ca2+-induced oxidative stress in brain underlies the biochemical events and behavioral signs of nicotine-withdrawal. The present study is aimed to explore the effects of lacidipine (LTCC antagonist) against nicotine-withdrawal. Swiss albino mice were administered (−)-nicotine hydrogen tartrate (3.35 mg/kg, t.i.d.) from day 1 to 7 and alongside lacidipine (0.3, 1 and 3 mg/kg, i.p.) given from day 1 to 14. Somatic withdrawal signs were noted 48 h after last dose of nicotine. Bay-K8644 (LTCC agonist) was administered in mice subjected to nicotine-withdrawal and lacidipine (3 mg/kg) treatments. Behavioral tests of memory, anxiety, and depression were conducted on day 13 and 14 to assess the effects of lacidipine on affective symptoms of nicotine-withdrawal. Biomarkers of oxido-nitrosative were quantified in the whole brain. Nicotine-withdrawal significantly enhanced somatic signs and symptoms of anxiety, depression, and memory impairment in mice. Lacidipine (1 and 3 mg/kg) attenuated nicotine-withdrawal induced somatic symptoms and also ameliorated behavioral abnormalities. Nicotine-withdrawal triggered an upsurge in brain lipid peroxidation, total nitrite content, and decline in antioxidants and these effects were attenuated by lacidipine. Bay-K8644 significantly abolished improvement in somatic and affective symptoms, and antioxidant effects by lacidipine in mice subjected to nicotine-withdrawal. Lacidipine mitigated nicotine-withdrawal triggered somatic and affective symptoms owing to decrease in brain oxido-nitrosative stress.
Arthroscopic Microfracture Alone or Combined Application of Acellular Scaffold: Which One is More Effective in the Treatment of Osteochondral Lesions of the Talus
Authors: Cengiz Bertan , Moradi Ramin
Published: June 2021

The authors have requested that this preprint be removed from Research Square.
ZnO and CuO nanoparticles prepared via the co-precipitation method: the evaluation of morphology and formation mechanism
Authors: Johari Narges , Zohari Faezeh , Rafati Fatemeh
Published: June 2021

The morphology of nanomaterials is an important factor to determine their properties. In this study, zinc oxide (ZnO) and cupric oxide (CuO) nanoparticles were synthesized via the co-precipitation method with the same protocols. Zinc nitrate and copper sulfate were selected as ZnO and CuO precursors, respectively. Then, the phase structure and morphology of both prepared nanoparticles were investigated and showed that ZnO and CuO were prepared without any impurities and with different morphologies. The obtained ZnO and CuO nanoparticles illustrated sphere-like and hierarchical flower-like structures, respectively, due to their various phase structure and electrostatic interactions.
Predicting short-term survival after total resection in glioblastomas by machine learning-based radiomic analysis of preoperative MRI
Authors: Cepeda Santiago , Perez-Nuñez Angel , Garcia-Garcia Sergio , Garcia-Perez Daniel , Arrese Ignacio , Jimenez-Roldan Luis , Garcia-Galindo Manuel , Gonzalez Pedro , Velasco-Casares Maria , Zamora Tomas , Sarabai Rosario
Published: June 2021

Background Radiomics, in combination with artificial intelligence, emerges as a powerful tool for the development of predictive models in neuro-oncology. Our study aims to find an answer to a clinically relevant question: is there a radiomic profile that can identify glioblastoma (GBM) patients with short-term survival after complete tumor resection?Methods A retrospective study of GBM patients who underwent surgery was conducted in two institutions between January 2019 and January 2020, along with cases from public databases. Cases with gross total or near-total tumor resection were included. Preoperative structural multiparametric magnetic resonance imaging (mpMRI) sequences were pre-processed, and a total of 15720 radiomic features were extracted. After feature reduction, machine learning-based classifiers were used to predict early mortality (< 6 months). Also, a survival analysis was performed using the Random Survival Forest (RSF) algorithm. Results A total of 203 patients were enrolled in this study. In the classification task, the Naive Bayes classifier obtained the best results in the testing cohort, with an area under the curve (AUC) of 0.769 and classification accuracy of 80%. RSF model allowed the stratification of patients into low and high-risk groups. In the validation set, this model obtained values of C-Index = 0.61, IBS = 0.123 and integrated AUC at six months of 0.761.Conclusion In this study, we have developed a reliable predictive model of short-term survival in GBM applying open-source and user-friendly computational means. These new tools will assist clinicians in adapting our therapeutic approach considering the individual patient characteristics.
High-performance Cardiovascular Medicine: Artificial Intelligence for Coronary Artery Disease
Authors: Herath H.M.K.K.M.B. , Karunasena G.M.K.B. , Priyankara H.D.N.S. , Madhusanka B.G.D.A.
Published: June 2021

Cardiovascular disease (CVD) is identified as the leading cause of death globally, according to the World Health Organization (WHO). Approximately 17.9 million people are dying due to cardiovascular disease, which is an estimation of 31% of all deaths worldwide. CVDs are generally affecting the heart and blood vessels in the human body. Since healthcare is an essential factor for a country and its economy, researchers are looking for solutions to predict disease before getting into serious problems. This research introduces a method to development of an algorithm to predict coronary artery disease based on artificial intelligence. The algorithm was tested with 72 random subjects, which covered 11 attributes such as age, gender, height, weight, systolic and diastolic blood pressure, cholesterol, glucose, smoking, alcohol intake, and physical activities. According to the results, the prediction accuracy of the system was 81.62% at 0.879 precision.
Teilhabe lehren und lernen. Zur Bedeutung moralischer Kompetenz in der Lehrkräftebildung
Authors: Müller Kathrin , Pfrang Agnes
Published: June 2021

Das Lernen von Teilhabe an der Gesellschaft als ein erklärtes Ziel einer jeden Pädagogik bleibt in der Diskussion um inklusiven Unterricht seltsam unberücksichtigt. So führt eine rein formal-organisatorische Teilnahme am Unterricht nicht selbstverständlich zu einer größeren Chancengleichheit, Chancengerechtigkeit und in Konsequenz auch Bildungsgerechtigkeit. Um Teilhabe zu lehren und zu lernen bedarf es eines vielperspektivischen, pädagogischen Zugangs zu Teilhabe. Entsprechend wird dieselbe als sozial-ethisches Handeln definiert und als Bildungsziel konkretisiert. Durch diese praxeologisch-pädagogische Betrachtungsweise von Teilhabe bedarf es für das Lernen und Lehren von Teilhabe moralische Kompetenzen, deren Förderung auch in der Lehrkräftebildung bedeutsam erscheint. Die Überlegungen werden zusammenfassend am Beispiel des Einsatzes der Konstanzer Methode der Dilemma-Diskussion konkretisiert, die vielversprechend für die Stärkung moralischer Kompetenzen von Teilhabeorientierung in der Lehrkräftebildung sein könnte.
Abstract
The learning of participation in society as a declared objective of any pedagogy remains strangely unconsidered in the discussion about inclusive education. Thus, a purely formal-organisational participation in teaching does not naturally lead to greater equality of opportunity, equity of opportunity and, as a consequence, educational equity. In order to teach and learn participation, a multi-perspective, pedagogical approach to participation is needed. Accordingly, we define it as a social-ethical act and concretise it as a central objective in education. Through the praxeological-pedagogical approach to participation moral competences are required for learning and teaching participation. Therefore, the advancement of moral competences seems to be significant in teacher training programs. The considerations are summarised using the example of the Konstanz method of dilemma discussion, which could be promising for strengthening the moral competences of participation orientation in teacher training programs.
ELECTROSPINNING PBAT (POLY (BUTYLENE-ADIPATE-CO-TEREPHTHALATE))/PCL (POLY(ε-CAPROLACTONE) BLEND CONTAINING PROPOLIS FOR THE PREPARATION OF A SMART WOUND DRESSING
Authors: Zanella Heloisa , Rossin Ariane , Hardt Janice , Rosenberger Andressa , Wiggers Juliana , Caetano Josiane , Dragunski Douglas
Published: June 2021

The electrospinning has been widely used in tissue engineering for the preparation of wound dressing with the most varied polymers and drugs. Considering that propolis has antimicrobial and anti-inflammatory characteristics, the aim was to develop electrospun fibers from PBAT (poly (butylene-adipate-co-terephthalate)/PCL (poly(e-caprolactone) containing propolis in order to promote antimicrobial action and the healing of wounds. By the optical microscopy analysis, the best parameter for obtaining the fibers was chosen: 16.5% (v/v) of propolis extract alcoholic solution, 14.0 cm needle-collector distance, 17.0 kV of voltage and 0.5 mL h-1 flow rate. The scanning electron microscopy demonstrated fiber diameters of 0.51 ± 0.12 μm for the polymer blend and 1.16 ± 0.98 μm for the blend with propolis. The Fourier transform infrared spectroscopy (FTIR) results showed no evidence of chemical interaction with propolis, this being a physical interaction. This interaction was corroborated by the differential scanning calorimetry (DSC) due to the variation in the heats involved, mainly in the aromatic part of the polymer blend, indicating a better interaction in the PBAT group. Finally, it was found that fibers presents propolis antimicrobial activity against the bacteria Pseudomonas Aeruginosa. The results indicate that this blend has a great potential to be used as a cutaneous dressing.
DA FAMA AO OSTRACISMO: OITO REAGENTES QUE DEIXARAM O AMBIENTE LABORATORIAL
Authors: Paulino Jéssica , Afonso Júlio
Published: June 2021

FROM FAME TO OSTRACISM: EIGHT REAGENTS THAT LEFT THE LABORATORY ENVIRONMENT. Historical aspects related to eight reagents that were present in analytical chemistry laboratories in the first decades of the twentieth century are described. They have peculiarities that are based on their curious names or the purposes for which they were intended. Their presence in the laboratory environment reflected their industrial applications and the chemical analysis procedures used at that time. From the mid XXth century, with the migration of qualitative analysis to the chemistry teaching, these reagents have been replaced by others that today serve the same purposes as those previously used. However, many of them still retain their industrial importance. This historical overview emphasizes the importance of the evolution of chemicals and chemical assays for security and efficiency reasons. Learning from past experiences develops a critical spirit and laboratory behavior more committed to occupational hygiene and safety, without losing sight the learning power that qualitative analytical chemistry offers.
Decentralized calibration process for distributed water resources systems using the self-adaptive multi-memory melody search algorithm
Authors: Ashrafi Seyed Mohammad , Mahmoudi Maral
Published: June 2021

Having systematic simulation and optimization models with high computational accuracy is one of the most important problems in developing decision support systems. In the present research, a specific methodology was proposed for decentralized calibration of complex water resources system models by using the structural capabilities of the melody search algorithm. This methodology was implemented in the framework of a self-adaptive simulation–optimization model that helps fine-tune complex water resources models by introducing a new definition of the way sub-memories are related to each. The introduced structure aims to achieve the highest possible level of consistency, which is estimated by using different criteria, between model results and observed data at several control points of surface flows. The introduced strategy was put to the test in developing a water resources model for the Great Karun Watershed, Iran, and was found to produce accurate results compared to some other well-known optimization algorithms such as GA, HS, PSO, SGHS, EMPSO, and SaMeS. In an attempt to determine the effect of calibration on water resources system modeling, 16 calibration models of different dimensions are developed and their computational costs are compared in terms of their computation time and effects on the accuracy of the results.
A Technique for Mimicking Soft Tissue Manipulation from Experimental Data to a Wave Equation Model for a New Laparoscopic Virtual Reality Training System
Authors: Nillahoot Nantida , Patel Sneha , Suthakorn Jackrit
Published: June 2021

Background:

The difficulty of laparoscopic procedures and the specific psychomotor skills required support the need for a training system for intensive and repetitive practice to acquire the specific skills. The present VR training systems have some limitations with respect to the soft tissue models in the training system. This is associated with the need for a real-time simulation, which requires a balance between computational cost and accuracy.

Objective:

The primary objective of the study is to develop a two dimensional wave equation model that closely mimics the soft tissue manipulation in a laparoscopic procedure for a VR training system.

Methods:

A novel mathematical model based on the wave equation is prepared to represent the interaction between the laparoscopic tool and the soft tissue. The parameters within the model are determined through experimental analysis of a soft tissue phantom. The experimental setup involves a linear actuator applying force to the soft tissue phantom to generate deformation. Data acquisition is conducted through a camera and a robotic force acquisition system which measures force, displacement of the linear actuator and records a video. Through image processing, the displacements of the markers on the phantom’s x-y plane during its deformation are determined and these parameters are used to develop the model, which finally is validated through a comparative analysis.

Results:

The results from the developed model are observed and compared statistically as well as graphically with the finite element model based on deformation data. The results show that the deformation data between the developed model and the available model is significantly similar.

Conclusion:

This study demonstrates the adaptability of the wave equation to meet the needs of the specific surgical procedure through modification of the model based on the experimental data. Moreover, the comparative analysis further corroborates the relevance and validity of the model for the surgical training system.
Effectiveness of Using Mobile Technology to Improve Cognitive and Social Skills Among Individuals With Autism Spectrum Disorder: Systematic Literature Review
Authors: Leung Phil Wai Shun , Li Shirley Xin , Tsang Carmen Sze Oi , Chow Bellavista Long Ching , Wong William Chi Wai
Published: June 2021

Background

Mobile technology has become a necessity in the lives of people in many countries. Its characteristics and advantages also make it a potential medium of intervention for people with autism spectrum disorder (ASD).

Objective

The objective of this review was to evaluate previous evidence, obtained in randomized controlled trials (RCTs), on the effectiveness of using mobile devices as the medium of intervention targeting social and cognitive skills among individuals with ASD.

Methods

Literature search was conducted on electronic databases including Medline, PsycInfo, PsycArticles, Education Resources Information Centre, and Social Science Citation Index. Only RCTs published in English and after year 2000 were included for this review. Data extraction was carried out by 2 independent reviewers using constant comparative methods.

Results

Totally 10 RCTs were identified. Most of the findings indicated that mobile devices could be an effective medium of intervention for people with ASD, among which 6 indicated significant intervention effects and 2 showed mixed findings. Effective intervention was more likely to be achieved in the studies that recruited older participants (aged over 9 years), targeting practical skills that could be readily applied in real life, or using pictures or materials that were highly relevant in daily life in the apps or mobile devices. Furthermore, the use of mobile devices was also reported to promote participation in the intervention among individuals with ASD.

Conclusions

The results suggested that mobile devices could be a promising means for the delivery of interventions targeting people with ASD. Although including a small number of studies was a limitation of this review, the results provided useful implications for designing effective mobile technology–assisted interventions for the ASD population in future studies.
Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study (Preprint)
Authors: Mehta Ashish , Niles Andrea Nicole , Vargas Jose Hamilton , Marafon Thiago , Couto Diego Dotta , Gross James Jonathan
Published: June 2021

BACKGROUND

Youper is a widely used, commercially available mobile app that uses artificial intelligence therapy for the treatment of anxiety and depression.

OBJECTIVE

Our study examined the acceptability and effectiveness of Youper. Further, we tested the cumulative regulation hypothesis, which posits that cumulative emotion regulation successes with repeated intervention engagement will predict longer-term anxiety and depression symptom reduction.

METHODS

We examined data from paying Youper users (N=4517) who allowed their data to be used for research. To characterize the acceptability of Youper, we asked users to rate the app on a 5-star scale and measured retention statistics for users’ first 4 weeks of subscription. To examine effectiveness, we examined longitudinal measures of anxiety and depression symptoms. To test the cumulative regulation hypothesis, we used the proportion of successful emotion regulation attempts to predict symptom reduction.

RESULTS

Youper users rated the app highly (mean 4.36 stars, SD 0.84), and 42.66% (1927/4517) of users were retained by week 4. Symptoms decreased in the first 2 weeks of app use (anxiety: d=0.57; depression: d=0.46). Anxiety improvements were maintained in the subsequent 2 weeks, but depression symptoms increased slightly with a very small effect size (d=0.05). A higher proportion of successful emotion regulation attempts significantly predicted greater anxiety and depression symptom reduction.

CONCLUSIONS

Youper is a low-cost, completely self-guided treatment that is accessible to users who may not otherwise access mental health care. Our findings demonstrate the acceptability and effectiveness of Youper as a treatment for anxiety and depression symptoms and support continued study of Youper in a randomized clinical trial.
Dominasi Rosatom Rusia Dalam Pasar Energi Nuklir Global
Authors: Bukhari Ahmad Saifuddin
Published: June 2021

In recent years, Rosatom has dominated the world nuclear energy market. This Russian state-owned company has around 36 portfolios of new nuclear power plants (NPP) in various countries. In addition, Rosatom also controls about 17% of the nuclear fuel market. This research aims to find out how Rosatom can dominate the global nuclear energy market. To answer that, this study used a qualitative descriptive research method with the neomerkantilism concept approach. The data collection technique is done by means of literature study or literature study. The results of this study indicate that Rosatom can dominate the global nuclear energy market due to the influence and support of the Russian state. Russia made Rosatom a state-owned company aimed at pursuing maximum revenue through exports of nuclear energy for the sake of increasing the national economy as well as its global political influence.