bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sonochemical synthesis of Cu x O/Ag nanoparticles on exfoliated graphite: Application for enhanced electrochemical detection of H 2 O 2 in milk
Authors: Song Jie , Wan Yating , Yang Chen , Deng Qiuju , Cui Yingde , Yan Zhihong , Liu Yi 
Published: December 2022

Abstract
In this paper, a novel composite is constructed as a non-enzymatic hydrogen peroxide (H2O2) sensor by liquid-phase exfoliation method, which is composed of silver, copper oxide and cuprous oxide-doped a few layers graphene (CuxO/Ag@FLG). Its surface morphology and composition are analyzed by scanning electron microscopy (SEM) and X-ray photo spectroscopy (XPS), and its H2O2 sensing performance include catalytic reduction and quantitative detection is studied with electrochemical method. Our sensor had a high sensitivity of about 1272.62 μA mM-1 cm-2 (R2=0.9923) in a extremely wide range of concentrations from 10 μM to 20 mM H2O2, a fast response (about 5 s) and low limit of detection (S/N=3) of 2.13 μM. The sensor exhibits outstanding selectivity in the presence of various biological interference, such as dopamine, ascorbic acid, uric acid, citric acid, etc. In addition, the constructed sensor continued 95% current responsiveness after one month of storage further points to its long-term stability. Last but not least, it has a good recovery rate in the milk sold on the open market, indicating that it has a wide range of application possibilities in the food industry and biological medicine.
Effective Connectivity in a Duration Selective Cortico-Cerebellar Network
Authors: Protopapa Foteini , Kulashekhar Shrikanth , Hayashi Masamichi J. , Kanai Ryota , Bueti Domenica 
Published: December 2022

Abstract
How the human brain represents millisecond unit of time is far from clear. A recent neuroimaging study revealed the existence in the human premotor cortex of a topographic representation of time i.e., neuronal units selectively responsive to specific durations and topographically organized on the cortical surface. By using high resolution functional Magnetic Resonance Images here, we go beyond this previous work, showing duration preferences across a wide network of cortical and subcortical brain areas: from cerebellum to primary visual, parietal, premotor and prefrontal cortices. Most importantly, we identify the effective connectivity structure between these different brain areas and their duration selective neural units. The results highlight the role of the cerebellum as the network hub and that of medial premotor cortex as the final stage of duration recognition. Interestingly, when a specific duration is presented, only the communication strength between the units selective to that specific duration and to the neighboring durations is affected. These findings link for the first time, duration preferences within single brain region with connectivity dynamics between regions, suggesting a communication mode that is partially duration specific.
Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence
Authors: Zhang Chao , Qi Lisha , Cai Jun , Wu Haixiao , Xu Yao , Lin Yile , Li Zhijun , Chekhonin Vladimir P. , Peltzer Karl , Cao Manqing , Yin Zhuming , Wang Xin , Ma Wenjuan 
Published: December 2022

Abstract
Background: Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis.
Methods: We retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data.
Results: Three clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients.
Conclusion: Our study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.
Higher Dietary Cost Is Associated with Higher Diet Quality: A Cross-Sectional Study among Adults from Henan province
Authors: Zhai Junya , Ma Baihui , Lyu Quanjun , Guo Lijun , Khatun Pipasha , Cong Minghua , Kong Yongxia 
Published: December 2022

Abstract

Objectives:Food price is a determining factor in food choices. However, its relationship with diet quality is unclear in Chinese adults. This study aimed to examine daily energy-adjusted dietary cost (CNY/2000kcal) concerning diet quality in northeast central Chinese adults.Design:Cross-sectional study. The food consumed by 680 Chinese adults from Henan province during the year 2020 was recorded by 24-h dietary recalls. Three dietary quality indices, namely the nutrient-rich foods (NRF) index, the mean adequacy ratio (MAR), and the energy density (ED), were adopted. Daily energy-adjusted diet cost was calculated by dividing the estimated daily diet costs (CNY/day) by the energy intake per day (kcal/day) and multiplying 2000.Setting:Three communities in Zhengzhou city, Henan province, China.Participants:A total of 680 adults were recruited from Henan as the subjects.Results: Subjects who closely adhered to the NRF9.2, MAR, and ED paid daily ¥8.92, ¥13.17, and ¥14.34 more for food consumption, respectively, than those who weakly adhered to these dietary patterns. Furthermore, adjusted linear regression analysis revealed that an increase in ¥1 of the energy-adjusted diet cost per day was associated with a change of 0.494 units (P< 0.001), 0.003 units (P<0.001), and -0.018 units (P<0.001) in the NRF9.2, MAR, and ED, respectively.Conclusion:Higher energy-adjusted diet costs were associated with higher-quality diets. This might be of importance for public health policies in an effort to develop strategies to promote healthy diets by regulating food and diet costs.
Micropatterned Primary Hepatocyte Co-Culture (HEPATOPAC) for Fatty Liver Disease Modeling and Drug Screening
Authors: Cottier Karissa E. , Bhalerao Devika , Lewis Candice , Gaffney Jeannemarie , Heyward Scott A. 
Published: December 2022

Abstract
Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent, progressive disorder and growing public health concern. To date, no treatments exist for NAFLD. To address this issue, considerable research has been undertaken in pursuit of new NAFLD therapeutics. Development of effective, high-throughput in vitro models are an important aspect of drug discovery. Here, a micropatterned hepatocyte coculture (MPCC) was used to model liver steatosis and NAFLD. The MPCC model (HEPATOPAC) involves cells patterned onto a standard 96-well plate, increasing throughput and allowing the cultures can be handled and imaged like 2D cultures. Treatment of MPCC with free fatty acids (FFA), high glucose and fructose (HGF), or a combination of both induces hepatic steatosis. Additionally, inclusion of Kupffer cells to generate a tri-culture (MPTC) increased lipid loading induced by steatotic media. MPCC treatment with ACC1/ACC2 inhibitors, as either a preventative or reversal agent showed efficacy against FFA induced hepatic steatosis. Drug induced steatosis was also evaluated. Treatment with valproic acid showed steatosis induction in a lean background, which was significantly potentiated in a fatty liver background. Additionally, these media treatments changed expression of fatty liver related genes. Treatment of MPCC with FFA, HGF, or a combination reversibly altered expression of genes involved in fatty acid metabolism, insulin signaling, and lipid transport. These changes were largely consistent with data from other clinical or in vivo fatty liver studies. Together, these data demonstrate that MPCC and MPTC are easy to use long-term functional in vitro models of NAFLD. MPCC and MPTC are able to replicate numerous clinical and in vivo NAFLD observations, allowing their broad utility for compound screening, drug toxicity evaluation and assessment of gene expression changes.
The best location for the application of static magnetic fields based on biokinetic coefficients in complete-mix activated sludge process
Authors: Asgari Ghorban , Seid-Mohammadi Abdolmotaleb , Shokoohi Reza , Samarghandi Mohammad Reza , Diger Glen T , Malekolkalami Behrooz , Khoshniyat Ramin 
Published: December 2022

Abstract
The use of kinetic coefficients for the mathematical expression of biochemical processes and the relationship between effective parameters is importance. Change of biokinetic coefficients in the complete-mix activated sludge processes were calculated for 1 month operation in three series of activated sludge model (ASM) in a pilot-scale. 15 mT intensity of static magnetic fields (SMFs) applied on the aeration reactor (ASM 1), clarifier reactor (ASM 2) and, return sludge pipe (ASM 3) for 1 hour, daily. During the operation of systems five basic biokinetic coefficients such as maximum specific substrate utilization rate (k), heterotrophic half-saturation substrate concentration (Ks), decay coefficient (kd), yield coefficient (Y) and, maximum specific microbial growth rate (μmax) were determined. The rate of k (g COD/g Cells.d) in ASM 1 was 2.69% and, 22.79% higher than ASM 2 and, ASM 3. The value of Ks (mg COD/L) was 54.44 and, 71.13 (mg/L) lower than the ASM 2 and, ASM 3. The rate of kd ASM 1, ASM 2 and, ASM 3 were 0.070, 0.054 and, 0.516 (d-1). The value of Y (kg VSS/kg COD) in ASM 1 was 0.58% and, 0.48% lower than ASM 2 and, ASM 3. The rate of μmax (d−1) in ASM 1 was 0.197 this value for ASM 2 and ASM 3 were 0.324 and 0.309 (d-1). Related to biokinetic coefficients the best location for application of 15 mT SMFs was the aeration reactor where the present of oxygen, substrate and, SMFs have the greatest impact on the positive changes of these coefficients.
Glycosylation of the antimicrobial peptide LL-III: Effects on membrane perturbation, protease stability, and biological activity
Authors: Tortorella Attila , Leone Linda , Lombardi Angelina , Pizzo Elio , Bosso Andrea , Winter Roland , Petraccone Luigi , Vecchio Pompea Del , Oliva Rosario 
Published: December 2022

Abstract
The misuse of antibiotics has led to the emergence of drug-resistant pathogens. Antimicrobial peptides (AMPs) may represent valuable alternative to antibiotics; nevertheless, the easy degradation due to environmental stress and proteolytic enzyme action, limits their use. So far, different strategies have been developed to overcome this drawback. Among them, glycosylation of AMPs represents a promising approach. In this work, we synthesized and characterized the N-glycosilated form of the antimicrobial peptide LL-III (g-LL-III). The N-acetylglucosamine (NAG) was covalently linked to the Asn residue and the interaction of g-LL-III with bacterial model membranes, together with its resistance to proteases, were investigated. Glycosylation did not affect the peptide mechanism of action and its biological activity against both bacteria and tumor cells. Interestingly, a higher resistance to the activity of proteolytic enzymes was achieved. The reported results pave the way for the successful application of AMPs in medicine and biotechnological fields.
Construction of a ring strongly coupled Lorenz-like oscillators: detection of weak pulse signal, synchronization mutation and circuit realization
Authors: Zhao Zhijie , Yang Ruyue , Wang Xiaodong 
Published: December 2022

Abstract
A ring strongly coupled Lorenz-like oscillators is constructed to identify the Gaussian pulse signals similar to the weak Coulter signals. The Coulter signals generated by particles whose sizes belong to [10μm, 60μm] are calculated through the Wheatstone bridge principle, and the Gaussian pulse signals are used to fit these signals. The dynamics of the oscillators are explored by using the nonlinear analysis method. The white Gaussian noise is used to fit the noise in the measurement and make it annihilate the Gaussian pulse signals. Then the test signals composed of these weak Gaussian pulse signals and white Gaussian noise are added to the oscillators, and continuous synchronization mutation phenomena are analyzed. After the amplification factor is introduced, the weak pulse signals can be detected by using the maximum values of these phenomena in the periodic or chaotic oscillators. The nonlinear circuit of the oscillators is made, and experiments on detection of Gaussian pulse signals annihilated in noise with different amplitudes and frequencies are carried out. The proposed method can effectively detect weak pulse signals, which has made a useful exploration for the detection of Coulter signals annihilated in noise.
A novel approach for detecting outliers by using Isolation Forest with reducing under fitting issue
Authors: Goad Prashant Maganlal , Deore Pramod J , Patil Vaishali Bhagwat 
Published: December 2022

Abstract
The effectiveness of machine learning for a particular activity depends on a variety of parameters. The incident database's description and validity come first and primary. Information retrieval even during training cycle is more challenging if there is a lot of repetitious, unimportant information or incomplete information available. It is well knowledge that running time for ML tasks is significantly impacted by conditions are as follows and sorting stages. To increase the accuracy of any model data cleansing is essential. Without sufficient data scrubbing, no predictive model accuracy can begin. EDA, or exploratory data analysis, is the name of this procedure. In this study, we discussed outlier’s identification, one of many EDA processes for complete perfect data. In this research, we attempted to use the isolation forest approach to calculate the outlier factor. Then a model known as an outlier finding model is created. The problem of outlier detection leads to a collection of connected supervised learning for binary classification. We carry out in-depth tests on various datasets and demonstrate that in our latest outlier finding technique compare with the old way. Our approach yields superior outcomes in terms of accuracy, precision, recall & F-1 score. Additionally, we successfully lowered the machine learning algorithms' under fitting issue.
Virtualized Intelligent Genetic Load Balancer for Federated Hybrid Cloud Environment using Deep Belief Network Classifier
Authors: sriniva rajkumar , katiravan jeevaa 
Published: December 2022

Abstract
Load balancing is major issue in federated cloud environment. Various services can be offered by different cloud service providers. As per current working environment cloud computing is used in major applications such as education, online shopping, multimedia services, etc. Dynamic load balancing is required to handle the resources. Federated cloud has various services offering system with computing resources, resource pooling, internet access services and storage. In this paper we propose Intelligent Genetic algorithm to provide efficient load balancing service in hybrid cloud environment. Enhanced Load Balancer is used to preserve the load and minimize the span time based on resource provisioning method. In this work we analyze automated virtual machine services by using runtime resource provision. In this case we measure the performance by calculating virtual machine placements, resource utilization and automated quality requirements. We used Deep belief network approach to measure the accuracy of Load balancers and test the cloud environment using TensorFlow. Our proposed system is achieving the accuracy of 95% based on overall capacity requirements. We compare our proposed system performance with existing simulations results.
Lung Inflammation in Alpha-1-Antitrypsin Deficient Individuals with Normal Lung Function
Authors: Kokturk Nurdan , Khodayari Nazli , Lascano Jorge , Riley E. Leonard , Brantly Mark L. 
Published: December 2022

Abstract
Background: Alpha-1-antitrypsin deficient (AATD) individuals are prone to develop early age of onset chronic obstructive pulmonary disease (COPD) which is more severe than non-genetic COPD. In this study, we investigated the characteristics of lower respiratory tract inflammation in AATD individuals prior to the onset of clinically significant COPD.
Methods: Bronchoalveolar lavage was performed on 22 AATD individuals with normal lung function and 14 healthy individuals. Cell counts and concentrations of proteases, alpha-1-antitrypsin, proinflammatory cytokines, and leukotriene B4 were determined in the bronchoalveolar lavage fluid from AATD and healthy individuals. In order to determine the characteristics of airway inflammation in this cohort, we also analyzed immune cell components of the large airways from bronchial biopsies using immunohistochemistry in both study subjects. Finally, we made comparisons between airway inflammation and lung function rate of decline using four repeated lung function tests over one year in AATD individuals.
Results: AATD individuals with normal lung function had significantly higher neutrophil counts, levels of proteases, IL-8, IL-6, IL-1b, and leukotriene B4 in their epithelial lining fluid compared to control subjects. A positive correlation was noted between the levels of IL-8, neutrophils, and concentration of neutrophil elastase in epithelial lining fluid of AATD individuals. AATD individuals also showed a negative correlation of baseline FEV1 with neutrophil count, neutrophil elastase, and cytokine levels in epithelial lining fluid. In addition, we found that the airways of AATD individuals have increased lymphocytes, macrophages, neutrophils, and mast cells in epithelial lining fluid compared to control subjects.
Conclusion: Inflammation is present in the lower respiratory tract and airways of AATD individuals despite having normal lung function. A declining trend was also noticed in the lung function of AATD individuals which was correlated with inflammatory phenotype of their lower respiratory tract. This results provide new evidence for the presence of early inflammation in the lungs of AATD individuals. This suggests that early anti-inflammatory therapies may be a potential strategy to prevent progression of lung disease in individuals with AATD.
A Self-powered Aptasensor for Isocarbophos Determination Based on Nanozyme-catalytic Photoelectrochemical Fuel Cell
Authors: Zhou Chunhong , Wen Ruiting , Tian Jiuying , Lu Jusheng 
Published: December 2022

Abstract
In the present work, we developed a nanozyme-catalytic photoelectrochemical fuel cell (PNFC) to determine isocarbophos in food sample, in which ZIF-67 nanozyme exhibited an excellent glucose dehydrogenase-mimic performance and was assembled in-situ on g-C3N4 modified TiO2 nanotube arrays (TNA/g-C3N4) to form a TNA/g-C3N4/ZIF-67 photoanode, Fe-N-C nanozyme was used for catalytic oxygen reduction reaction and coated uniformly on indium tin oxide conductive glass (ITO) to form an ITO/Fe-N-C cathode. Under visible light irradiation, the as-constructed PNFC produced a high output response with a maximum output power of 0.376 mW·cm− 2 and an output voltage of 0.66 V. Due to the specific recognition of target isocarbophos by its aptamer and high output power of the PNFC, a PNFC-based self-powered aptasensor was constructed for determining isocarbophos based on the catalytic mercapto-inhibition effect and exonuclease I-assisted target recycling signal amplification, which had a quantitative range of 0.01–100 ng mL− 1, a low detection limit of 3.5 pg mL− 1 and good selectivity for isocarbophos determination, being applied for real food sample analysis with good precision of the relative standard deviation less than 5.4% and good accuracy of the recoveries from 96.2–108%.
Dehydration accelerates cytogenesis and cyst growth in Pkd1 −/− mice by regulating macrophage M2 polarization
Authors: Yang Yang , Song Minghui , Zhang Dongjuan , Wang Chao , Zhou Jie , Yi Lvjia , Chen Meihan , Mei Changlin 
Published: December 2022

Abstract
Adult autosomal dominant polycystic kidney disease (ADPKD) has been shown to be related as a “third hit” to the occurrence of acute or chronic kidney injury. Here, we examined whether dehydration, as a common kidney risk factor, could cause cystogenesis in chronic-onset Pkd1−/− mice by regulating macrophage activation. First, we confirmed that dehydration accelerated cytogenesis in Pkd1−/− mice and that macrophages infiltrated the kidney tissues even earlier than macroscopic cyst formation. Then, microarray analysis suggested that glycolysis pathway may be involved in macrophage activation in Pkd1−/− kidneys under conditions of dehydration. Further, we confirmed glycolysis pathway was activated and lactic acid (L-LA) was overproduced in the Pkd1−/− kidney under conditions of dehydration. We have already proved that L-LA strongly stimulated M2 macrophage polarization and overproduction of polyamine in macrophage in vitro; and in the present study, we further discovered that M2 polarization-induced polyamine production shortened the primary cilia length by disrupting the PC1/PC2 complex. Finally, the activation of L-LA—arginase 1—polyamine pathway contributed to cystogenesis and progressive cyst growth in Pkd1−/− mice recurrently exposed to dehydration.
Integrated gut metabolome and microbiome fingerprinting reveals that dysbiosis precedes allergic inflammation in IgE-mediated pediatric cow’s milk allergy
Authors: De Paepe Ellen , Plekhova Vera , Vangeenderhuysen Pablo , Baeck Nele , Bullens Dominique , Claeys Tania , De Graeve Marilyn , Kamoen Kristien , Notebaert Anneleen , de Wiele Tom Van , Broeck Wim Van Den , Vanlede Koen , Winckel Myriam Van , Vereecke Lars , Cox Eric , Vanhaecke Lynn 
Published: December 2022

Abstract
Understanding the underlying mechanisms behind IgE-mediated cow’s milk allergy (IgE-CMA) is imperative for the discovery of novel biomarkers and the design of innovative treatment and prevention strategies. Here, we report data on the gut microbiome, metabolome, and lipidome of 81 children affected by food allergies, including CMA and healthy controls. Moreover, we developed a mouse model that mimicked IgE CMA best, BALB/c mice sensitized with ß-lactoglobulin using cholera toxin. During sensitization, we observed multiple microbially derived metabolic alterations, most importantly bile acid and tryptophan metabolites, that preceded allergic inflammation, while this inflammation was reflected in a disturbed sphingomyelin and histamine metabolism. We endorsed the microbial origin of these metabolites by in vitro colonic digestions and confirmed the microbial dysbiosis in our patient cohort, which was accompanied by metabolic signatures of low-grade inflammation. Our results suggest that gut dysbiosis precedes allergic inflammation, opening new opportunities for future prevention and treatment strategies. Trial: NCT04249973.