bluuebunny/crossref_metadata_2025 huggingface dataset:
Animal Welfare Assessment: Can We Develop a Practical, Time-Limited Assessment Protocol for Pasture-Based Dairy Cows in New Zealand?
Authors: Sapkota Sujan , Laven Richard , Müller Kristina , Kells Nikki
Published: October 2020

Despite being a leading producer and exporter of dairy products, New Zealand has no industry-recognised welfare assessment protocol. A New Zealand-specific protocol is essential, as almost all dairy farms in New Zealand are pasture-based and housing is rarely used. Therefore, protocols developed for intensive cows are not suitable. The aim of this study was to develop a simple yet practical welfare assessment protocol that could be used to assess the welfare of a dairy herd during one visit timed to occur around milking. Six welfare assessment protocols and four studies of dairy cattle welfare assessments that had some focus on dairy cattle welfare at pasture were used, along with the New Zealand Dairy Cattle Code of Welfare, to identify potential assessments for inclusion in the protocol. Eighty-four potential assessments (20 record-based and 64 that needed assessing on-farm) were identified by this process of welfare assessments. After screening to exclude on-farm assessments that were not relevant, that had only limited practical application in pasture-based dairy cows or that required more time than available, 28 on-farm assessments remained, which were put together with the 20 record-based assessments and were tested for feasibility, practicality and time on two pasture-based dairy farms. Assessments were then identified as suitable, suitable after modification or not feasible. Suitable and modified assessments were then included in the final protocol alongside additional measures specific to New Zealand dairy farms. The final protocol included 24 on-farm assessments and eight record-based assessments. Further testing of these 32 assessments is needed on more dairy farms across New Zealand before the protocol can be used to routinely assess the welfare of dairy cows in New Zealand.
Aminoglycoside Antibiotics Inhibit Mycobacteriophage Infection
Authors: Jiang Zheng , Wei Junwei , Liang Yunxiang , Peng Nan , Li Yingjun
Published: October 2020

Antibiotic resistance is becoming the biggest threat to global health. At the same time, phage therapy is witnessing a return of interest. The therapeutic use of bacteriophages that infect and kill bacteria is a suitable strategy to combat antibiotic resistance. Furthermore, bacteriophages are increasingly used in combination with standard antibiotics against drug-resistant pathogens. Interestingly, we found that the engineered mycobacteriophage phAE159 and natural phage D29 cannot infect the Mycobacterium tuberculosis in the presence of kanamycin, hygromycin or streptomycin, but the phage infection was not affected in the presence of spectinomycin. Based on a series of studies and structural analysis of the above four aminoglycoside antibiotics, it could be speculated that the amino sugar group of aminoglycoside might selectively inhibit mycobacteriophage DNA replication. Our discovery that broad-spectrum antibiotics inhibit phage infection is of great value. This study will provide guidance for people to combine phage and antibiotics to treat M. tuberculosis.
Antioxidant, Anti-Inflammatory, and Anti-Apoptotic Effects of Azolla pinnata Ethanolic Extract against Lead-Induced Hepatotoxicity in Rats
Authors: Elrasoul Ahmed Shaaban Abd , Mousa Ahmed Abdelmoniem , Orabi Sahar Hassan , Mohamed Mostafa Abd El-Gaber , Gad-Allah Shaban M. , Almeer Rafa , Abdel-Daim Mohamed M. , Khalifa Shaden A. M. , El-Seedi Hesham R. , Eldaim Mabrouk Attia Abd
Published: October 2020

The current study investigated the protective potential of Azolla pinnate ethanolic extract (APE) against lead-induced hepatotoxicity in rats. Sixty male Wistar albino rats were randomly allocated into six groups (n = 10). The control group was orally administrated with saline. The second group received lead acetate (100 mg/kg body weight (BW) orally for 60 days). The third group was fed with APE (10 mg/kg BW orally for 60 days). The fourth group was administrated with lead acetate like the second group and APE like the third group, concomitantly, for 60 days. The fifth group was administrated with APE like the third group for 30 days, then orally administrated with the lead acetate like the second group for another 30 days. The sixth group was administrated with lead acetate like the second group for 30 days, then with APE like the third group for a further 30 days. Phytochemical analysis of APE indicated the presence of peonidin 3-O-glucoside cation, vitexin, rutin, thiamine, choline, tamarixetin, hyperoside, astragalin, and quercetin. The latter has been elucidated using one- and two-dimensional nuclear magnetic resonance (1D and 2D NMR) and liquid chromatography–mass spectrometry (LC–MS-MS). Lead acetate increased the serum levels of alanine and aspartate aminotransferases and that of urea, creatinine, tumor necrosis factor alpha, and interleukin 1β, hepatic tissue malondialdehyde contents, and caspase 3 protein expression, as well as altering the hepatic tissue architecture. However, it decreased the serum levels of interleukin 10 and glutathione (GSH) contents, and the activities of catalase and superoxide dismutase in hepatic tissue. In contrast, the administration of APE ameliorated the lead-induced alterations in liver function and structure, exemplifying the benefits of Azolla’s phytochemical contents. Collectively, A. pinnate extract is a protective and curative agent against lead-induced hepatotoxicity via its antioxidant, anti-inflammatory, and anti-apoptotic impacts.
Chemometric Analysis of Extracts and Fractions from Green, Oxidized, and Microbial Fermented Teas and Their Correlation to Potential Antioxidant and Anticancer Effects
Authors: Rha Chan-Su , Jung Young Sung , Lee Jung-Dae , Jang Davin , Kim Mi-Seon , Lee Min-Seuk , Hong Yong Deok , Kim Dae-Ok
Published: October 2020

Previous reports on phytochemicals in green tea (GT) and processed teas mainly focused on more representative compounds such as catechins. Here, we focus on the insignificantly studied non-catechin components in tea extracts, and explore the multivariate correlation between diverse phenolic compounds in tea and the in vitro antioxidant and anticancer effects. Extracts from GT and four types of processed teas were further divided into hydrophilic and hydrophobic fractions, whose phenolic compositions and antioxidant capacities were quantified using HPLC-MS and three antioxidant assays, respectively. For three types of teas, the anticancer effects of their extracts and fractions were assessed using cancer cell lines. The hydrophobic fractions had lower antioxidant capacities than the corresponding hydrophilic fractions, but exhibited superior antiproliferative effects on cancer cells compared with the whole extract and the hydrophilic fraction. Partial least squares-discriminant analysis revealed a strong correlation between the anticancer effects and the theaflavins and flavonols. Therefore, in addition to catechins, the hydrophobic fraction of tea extracts may have beneficial health effects.
The Effect of Addition of Antioxidant 1,2-dihydro-2,2,4-trimethyl-quinoline on Characteristics of Crepe Rubber Modified Asphalt in Short Term Aging and Long Term Aging Conditions
Authors: Ibrahim Bahruddin , Wiranata Arya , Malik Alfian
Published: October 2020

The use of natural rubber to resist bitumen is usually prone to degradation and aging. One method to overcome this problem is the addition of antioxidants. This study aims to determine the effect of the addition of antioxidants 1,2-dihydro-2,2,4-trimethyl-quinoline (TMQ) on natural rubber modified asphalt crepe rubber and its performance in short-term and long-term aging conditions. The modified rubber asphalt mixture’s manufacture begins by melting the crepe rubber at 200 °C before being mixed in asphalt at 165 °C. Addition of antioxidant TMQ during the stirring process of the mixture of asphalt and melted rubber. The crepe rubber content was 8, 10, and 12% w/w, while the TMQ content was 1, 2, and 3% w/w of the total sample weight. The modified asphalt samples’ characterization included penetration, softening point, weight loss after a rolling thin film oven test (RTFOT), penetration after RTFOT, and Marshall test. Review of the performance of asphalt under short-term aging conditions using a dynamic shear rheometer (DSR). Evaluation of asphalt performance under long-term aging conditions using Fourier-transform infrared spectroscopy (FTIR). The results showed that the fact that the best-modified asphalt product was the addition of 10% crepe rubber and 2% TMQ. The best-modified asphalt characteristics have penetration 68.70 dmm, softening point 55.45 °C, weight loss only 0.0579%, penetration after RTFOT 59.60, Marshall stability 1403.96 kg with optimum asphalt content of 5.50%, and rutting factor (G*/Sinδ) 6.91 kPa and 16.1 kPa before and after RTFOT. Overall, the modified crepe rubber asphalt can improve the performance of the asphalt in terms of durability. Simultaneously, the antioxidant TMQ works very well in increasing the resistance of bitumen to aging in the conditions of short-term aging and long-term aging.
Learning Better Representations for Audio-Visual Emotion Recognition with Common Information
Authors: Ma Fei , Zhang Wei , Li Yang , Huang Shao-Lun , Zhang Lin
Published: October 2020

Audio-visual emotion recognition aims to distinguish human emotional states by integrating the audio and visual data acquired in the expression of emotions. It is crucial for facilitating the affect-related human-machine interaction system by enabling machines to intelligently respond to human emotions. One challenge of this problem is how to efficiently extract feature representations from audio and visual modalities. Although progresses have been made by previous works, most of them ignore common information between audio and visual data during the feature learning process, which may limit the performance since these two modalities are highly correlated in terms of their emotional information. To address this issue, we propose a deep learning approach in order to efficiently utilize common information for audio-visual emotion recognition by correlation analysis. Specifically, we design an audio network and a visual network to extract the feature representations from audio and visual data respectively, and then employ a fusion network to combine the extracted features for emotion prediction. These neural networks are trained by a joint loss, combining: (i) the correlation loss based on Hirschfeld-Gebelein-Rényi (HGR) maximal correlation, which extracts common information between audio data, visual data, and the corresponding emotion labels, and (ii) the classification loss, which extracts discriminative information from each modality for emotion prediction. We further generalize our architecture to the semi-supervised learning scenario. The experimental results on the eNTERFACE’05 dataset, BAUM-1s dataset, and RAVDESS dataset show that common information can significantly enhance the stability of features learned from different modalities, and improve the emotion recognition performance.
Comparative Study of the Bioactive Properties and Elemental Composition of Red Clover (Trifolium pratense) and Alfalfa (Medicago sativa) Sprouts during Germination
Authors: Chiriac Elena Roxana , Chiţescu Carmen Lidia , Sandru Claudia , Geană Elisabeta-Irina , Lupoae Mariana , Dobre Michaela , Borda Daniela , Gird Cerasela Elena , Boscencu Rica
Published: October 2020

Considering the growing interest in functional foods, the identification of the individual species of elements is of great importance in understanding specific nutraceutical properties. The present study aims to compare the dynamic of the elemental content (K, Na, Ca, Mg, Fe, Cu, Zn, Mn, Ni, and Se), total polyphenols, and antioxidant activity of Trifolium pratense L. and Medicago sativa L. sprouts in different germination stages. The elemental profile was established by atomic absorption spectroscopy after the microwave acid digestion of the samples, while total polyphenols and anti-radical activity were evaluated by UV-Vis spectroscopic methods. Phenolic compounds and anti-radical activity of both alfalfa and red clover sprouts varied with germination stages. Germination can significantly increase the anti-radical activity in the first 3 days of germination, followed by a decline in the following days. An increase in total polyphenols was noticed, starting from the second day of germination in both plant species. There were significant (p < 0.05) differences for Ca, Na, Fe, K, Zn, and Mg contents among the sprouts, depending on the germination stage and plant species. The calcium contents of alfalfa ranged between 200.74 µg/g DW (raw seeds) and 2765.31 µg/g DW (sprouted), while in red clover between 250.83 µg/g DW and 601.59 µg/g DW. Maximum selenium content in alfalfa sprouts, reached in the 3rd day of germination (11.42 µg/g DW), exceeded the maximum value measured in red clover (9.42 µg/g DW). The data were subject to statistical processing using analysis of variance (ANOVA), multivariate analysis (PCA) and hierarchical clustering analysis (HCA).
Modeling, Simulation, and Vision-/MPC-Based Control of a PowerCube Serial Robot
Authors: Fehr Jörg , Schmid Patrick , Schneider Georg , Eberhard Peter
Published: October 2020

A model predictive control (MPC) scheme for a Schunk PowerCube robot is derived in a structured step-by-step procedure. Neweul-M2 provides the necessary nonlinear model in symbolical and numerical form. To handle the heavy online computational burden concerning the derived nonlinear model, a linear time-varying MPC scheme is developed based on linearizing the nonlinear system concerning the desired trajectory and the a priori known corresponding feed-forward controller. Camera-based systems allow sensing of the robot on the one hand and monitoring the environments on the other hand. Therefore, a vision-based MPC is realized to show the effects of vision-based control feedback on control performance. A semi-automatic trajectory planning is used to perform two meaningful experimental studies in which the advantages and restrictions of the proposed (vision-based) linear time-varying MPC scheme are pointed out. Everything is implemented on a slim, low-cost control system with a standard laptop PC.
In Vitro and in Silico Analysis of miR-125a with rs12976445 Polymorphism in Breast Cancer Patients
Authors: Lehmann Tomasz P. , Miskiewicz Joanna , Szostak Natalia , Szachniuk Marta , Grodecka-Gazdecka Sylwia , Jagodziński Paweł P.
Published: October 2020

Background: Breast cancer affects over 2 million women yearly. Its early detection allows for successful treatment, which motivates to research factors that enable an accurate diagnosis. miR-125a is one of them, correlating with different types of cancer. For example, the miR-125a level decreases in breast cancer tissues; polymorphisms in the miR-125a encoding gene are related to prostate cancer and the risk of radiotherapy-induced pneumonitis. Methods: In this work, we investigated two variants of rs12976445 polymorphism in the context of breast cancer. We analyzed the data of 175 blood samples from breast cancer patients and compared them with the control data from 129 control samples. Results: We observed the tendency that in breast cancer cases TT genotype appeared slightly more frequent over CC and CT genotypes (statistically nonsignificant). The TT genotype appeared also to be more frequent among human epidermal growth factor receptor 2 (HER2) positive patients, compared to HER2 negative. In silico modelling showed that the presence of uridine (U) diminished the probability of pri-miR-125a binding to NOVA1 and HNRNPK proteins. We demonstrated that U and C -variants could promote different RNA folding patterns and provoke alternative protein binding. Conclusions: U-variant may imply a lower miR-125a expression in breast cancer.
Sub-Picosecond Micromachining of Monocrystalline Silicon for Solar Cell Manufacturing
Authors: Garasz Katarzyna , Kocik Marek
Published: October 2020

In this study a prototype sub-picosecond laser was investigated for cutting and scribing of silicon wafers. The Yb:KYW laser used for this investigation, unlike ultrashort systems used previously, generates pulses of 650 fs, i.e., between the pico and femtosecond range. The laser was placed in a micromachining setup, involving a galvo scanner and a telecentric lens. A study of the influence of the processing parameters on the crater width, depth, and quality of machining was carried out. The optimal parameters were found to be 343 nm, 200 kHz, 7 mm/s, and 15 pattern repetitions. The experiments were performed using samples of a silicon wafer of 210-µm thickness. The experimental results show that the sub-picosecond laser can be a promising and competitive tool for solar cell micromachining. In comparison to the commercially available ultrashort pulse laser systems, we find the sub-picosecond laser to be a more cost efficient and reliable source, than a femtosecond one. In addition, the prototype Yb:KYW design offers some unique parameters, such as repetition rate in the range of 100–400 kHz, UV wavelength or obtainable laser fluence close to the silicon ablation thresholds.
Cavitating Jet: A Review
Authors: Soyama Hitoshi
Published: October 2020

When a high-speed water jet is injected into water through a nozzle, cavitation is generated in the nozzle and/or shear layer around the jet. A jet with cavitation is called a “cavitating jet”. When the cavitating jet is injected into a surface, cavitation is collapsed, producing impacts. Although cavitation impacts are harmful to hydraulic machinery, impacts produced by cavitating jets are utilized for cleaning, drilling and cavitation peening, which is a mechanical surface treatment to improve the fatigue strength of metallic materials in the same way as shot peening. When a cavitating jet is optimized, the peening intensity of the cavitating jet is larger than that of water jet peening, in which water column impacts are used. In order to optimize the cavitating jet, an understanding of the instabilities of the cavitating jet is required. In the present review, the unsteady behavior of vortex cavitation is visualized, and key parameters such as injection pressure, cavitation number and sound velocity in cavitating flow field are discussed, then the estimation methods of the aggressive intensity of the jet are summarized.
First In-Situ Measurements of Plume Chemistry at Mount Garet Volcano, Island of Gaua (Vanuatu)
Authors: Lages Joao , Moussallam Yves , Bani Philipson , Peters Nial , Aiuppa Alessandro , Bitetto Marcello , Giudice Gaetano
Published: October 2020

Recent volcanic gas compilations have urged the need to expand in-situ plume measurements to poorly studied, remote volcanic regions. Despite being recognized as one of the main volcanic epicenters on the planet, the Vanuatu arc remains poorly characterized for its subaerial emissions and their chemical imprints. Here, we report on the first plume chemistry data for Mount Garet, on the island of Gaua, one of the few persistent volatile emitters along the Vanuatu arc. Data were collected with a multi-component gas analyzer system (multi-GAS) during a field campaign in December 2018. The average volcanic gas chemistry is characterized by mean molar CO2/SO2, H2O/SO2, H2S/SO2 and H2/SO2 ratios of 0.87, 47.2, 0.13 and 0.01, respectively. Molar proportions in the gas plume are estimated at 95.9 ± 11.6, 1.8 ± 0.5, 2.0 ± 0.01, 0.26 ± 0.02 and 0.06 ± 0.01, for H2O, CO2, SO2, H2S and H2. Using the satellite-based 10-year (2005–2015) averaged SO2 flux of ~434 t d−1 for Mt. Garet, we estimate a total volatile output of about 6482 t d−1 (CO2 ~259 t d−1; H2O ~5758 t d−1; H2S ~30 t d−1; H2 ~0.5 t d−1). This may be representative of a quiescent, yet persistent degassing period at Mt. Garet; whilst, as indicated by SO2 flux reports for the 2009–2010 unrest, emissions can be much higher during eruptive episodes. Our estimated emission rates and gas composition for Mount Garet provide insightful information on volcanic gas signatures in the northernmost part of the Vanuatu Arc Segment. The apparent CO2-poor signature of high-temperature plume degassing at Mount Garet raises questions on the nature of sediments being subducted in this region of the arc and the possible role of the slab as the source of subaerial CO2. In order to better address the dynamics of along-arc volatile recycling, more volcanic gas surveys are needed focusing on northern Vanuatu volcanoes.
Diagnostics 101: A Tutorial for Fault Diagnostics of Rolling Element Bearing Using Envelope Analysis in MATLAB
Authors: Kim Seokgoo , An Dawn , Choi Joo-Ho
Published: October 2020

This paper presents a MATLAB-based tutorial to conduct fault diagnosis of a rolling element bearing. While there have been so many new developments in this field, no studies have addressed the tutorial aspects in this field to help the engineers learn the concept and implement by their own effort. The three most common techniques—the autoregressive model, spectral kurtosis, and envelope analysis—are selected to demonstrate the bearing diagnosis process. Simulation signal is introduced to help understand the characteristics of fault signal and carry out the process toward the fault identification. The techniques are then applied to the two real datasets to demonstrate the practical applications, one made by the authors and the other by the Case Western Reserve University, which is known as a standard reference in testing the diagnostic algorithms.
Generating Optimized Guessing Candidates toward Better Password Cracking from Multi-Dictionaries Using Relativistic GAN
Authors: Nam Sungyup , Jeon Seungho , Moon Jongsub
Published: October 2020

Despite their well-known weaknesses, passwords are still the de-facto authentication method for most online systems. Due to its importance, password cracking has been vibrantly researched both for offensive and defensive purposes. Hashcat and John the Ripper are the most popular cracking tools, allowing users to crack millions of passwords in a short time. However, their rule-based cracking has an explicit limitation of depending on password-cracking experts to come up with creative rules. To overcome this limitation, a recent trend has been to apply machine learning techniques to research on password cracking. For instance, state-of-the-art password guessing studies such as PassGAN and rPassGAN adopted a Generative Adversarial Network (GAN) and used it to generate high-quality password guesses without knowledge of password structures. However, compared with the probabilistic context-free grammar (PCFG), rPassGAN shows inferior password cracking performance in some cases. It was also observed that each password cracker has its own cracking space that does not overlap with other models. This observation led us to realize that an optimized candidate dictionary can be made by combining the password candidates generated by multiple password generation models. In this paper, we suggest a deep learning-based approach called REDPACK that addresses the weakness of the cutting-edge cracking tools based on GAN. To this end, REDPACK combines multiple password candidate generator models in an effective way. Our approach uses the discriminator of rPassGAN as the password selector. Then, by collecting passwords selectively, our model achieves a more realistic password candidate dictionary. Also, REDPACK improves password cracking performance by incorporating both the generator and the discriminator of GAN. We evaluated our system on various datasets with password candidates composed of symbols, digits, upper and lowercase letters. The results clearly show that our approach outperforms all existing approaches, including rule-based Hashcat, GAN-based PassGAN, and probability-based PCFG. The proposed model was also able to reduce the number of password candidates by up to 65%, with only 20% cracking performance loss compared to the union set of passwords cracked by multiple-generation models.
Aerosol Effective Radiative Forcing in the Online Aerosol Coupled CAS-FGOALS-f3-L Climate Model
Authors: Wang Hao , Dai Tie , Zhao Min , Goto Daisuke , Bao Qing , Takemura Toshihiko , Nakajima Teruyuki , Shi Guangyu
Published: October 2020

The effective radiative forcing (ERF) of anthropogenic aerosol can be more representative of the eventual climate response than other radiative forcing. We incorporate aerosol–cloud interaction into the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System (CAS-FGOALS-f3-L) by coupling an existing aerosol module named the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) and quantified the ERF and its primary components (i.e., effective radiative forcing of aerosol-radiation interactions (ERFari) and aerosol-cloud interactions (ERFaci)) based on the protocol of current Coupled Model Intercomparison Project phase 6 (CMIP6). The spatial distribution of the shortwave ERFari and ERFaci in CAS-FGOALS-f3-L are comparable with that of most available CMIP6 models. The global mean 2014–1850 shortwave ERFari in CAS-FGOALS-f3-L (−0.27 W m−2) is close to the multi-model means in 4 available models (−0.29 W m−2), whereas the assessing shortwave ERFaci (−1.04 W m−2) and shortwave ERF (−1.36 W m−2) are slightly stronger than the multi-model means, illustrating that the CAS-FGOALS-f3-L can reproduce the aerosol radiation effect reasonably well. However, significant diversity exists in the ERF, especially in the dominated component ERFaci, implying that the uncertainty is still large.
Multifractal Cross Correlation Analysis of Agro-Meteorological Datasets (Including Reference Evapotranspiration) of California, United States
Authors: Sankaran Adarsh , Krzyszczak Jaromir , Baranowski Piotr , Devarajan Sindhu Archana , Kumar Nandhineekrishna , Lija Jayaprakash Nityanjali , Thankamani Vandana , Ali Mumtaz
Published: October 2020

The multifractal properties of six acknowledged agro-meteorological parameters, such as reference evapotranspiration (ET0), wind speed (U), incoming solar radiation (SR), air temperature (T), air pressure (P), and relative air humidity (RH) of five stations in California, USA were examined. The investigation of multifractality of datasets from stations with differing terrain conditions using the Multifractal Detrended Fluctuation Analysis (MFDFA) showed the existence of a long-term persistence and multifractality irrespective of the location. The scaling exponents of SR and T time series are found to be higher for stations with higher altitudes. Subsequently, this study proposed using the novel multifractal cross correlation (MFCCA) method to examine the multiscale-multifractal correlations properties between ET0 and other investigated variables. The MFCCA could successfully capture the scale dependent association of different variables and the dynamics in the nature of their associations from weekly to inter-annual time scales. The multifractal exponents of P and U are consistently lower than the exponents of ET0, irrespective of station location. This study found that joint scaling exponent was nearly the average of scaling exponents of individual series in different pairs of variables. Additionally, the α-values of joint multifractal spectrum were lower than the α values of both of the individual spectra, validating two universal properties in the MFCCA studies for agro-meteorological time series. The temporal evolution of cross-correlation determined by the MFCCA successfully captured the dynamics in the nature of associations in the P-ET0 link.
Directly Anodized Sulfur-Doped TiO2 Nanotubes as Improved Anodes for Li-ion Batteries
Authors: Sabaghi Davood , Madian Mahmoud , Omar Ahmad , Oswald Steffen , Uhlemann Margitta , Maghrebi Morteza , Baniadam Majid , Mikhailova Daria
Published: October 2020

TiO2 represents one of the promising anode materials for lithium ion batteries due to its high thermal and chemical stability, relatively high theoretical specific capacity and low cost. However, the electrochemical performance, particularly for mesoporous TiO2, is limited and must be further developed. Elemental doping is a viable route to enhance rate capability and discharge capacity of TiO2 anodes in Li-ion batteries. Usually, elemental doping requires elevated temperatures, which represents a challenge, particularly for sulfur as a dopant. In this work, S-doped TiO2 nanotubes were successfully synthesized in situ during the electrochemical anodization of a titanium substrate at room temperature. The electrochemical anodization bath represented an ethylene glycol-based solution containing NH4F along with Na2S2O5 as the sulfur source. The S-doped TiO2 anodes demonstrated a higher areal discharge capacity of 95 µAh·cm−2 at a current rate of 100 µA·cm−2 after 100 cycles, as compared to the pure TiO2 nanotubes (60 µAh·cm−2). S-TiO2 also exhibited a significantly improved rate capability up to 2500 µA·cm−2 as compared to undoped TiO2. The improved electrochemical performance, as compared to pure TiO2 nanotubes, is attributed to a lower impedance in S-doped TiO2 nanotubes (STNTs). Thus, the direct S-doping during the anodization process is a promising and cost-effective route towards improved TiO2 anodes for Li-ion batteries.
Development of a Minimally Invasive Screening Tool to Identify Obese Pediatric Population at Risk of Obstructive Sleep Apnea/Hypopnea Syndrome
Authors: Calderón José Miguel , Álvarez-Pitti Julio , Cuenca Irene , Ponce Francisco , Redon Pau
Published: October 2020

Obstructive sleep apnea syndrome is a reduction of the airflow during sleep which not only produces a reduction in sleep quality but also has major health consequences. The prevalence in the obese pediatric population can surpass 50%, and polysomnography is the current gold standard method for its diagnosis. Unfortunately, it is expensive, disturbing and time-consuming for experienced professionals. The objective is to develop a patient-friendly screening tool for the obese pediatric population to identify those children at higher risk of suffering from this syndrome. Three supervised learning classifier algorithms (i.e., logistic regression, support vector machine and AdaBoost) common in the field of machine learning were trained and tested on two very different datasets where oxygen saturation raw signal was recorded. The first dataset was the Childhood Adenotonsillectomy Trial (CHAT) consisting of 453 individuals, with ages between 5 and 9 years old and one-third of the patients being obese. Cross-validation was performed on the second dataset from an obesity assessment consult at the Pediatric Department of the Hospital General Universitario of Valencia. A total of 27 patients were recruited between 5 and 17 years old; 42% were girls and 63% were obese. The performance of each algorithm was evaluated based on key performance indicators (e.g., area under the curve, accuracy, recall, specificity and positive predicted value). The logistic regression algorithm outperformed (accuracy = 0.79, specificity = 0.96, area under the curve = 0.9, recall = 0.62 and positive predictive value = 0.94) the support vector machine and the AdaBoost algorithm when trained with the CHAT datasets. Cross-validation tests, using the Hospital General de Valencia (HG) dataset, confirmed the higher performance of the logistic regression algorithm in comparison with the others. In addition, only a minor loss of performance (accuracy = 0.75, specificity = 0.88, area under the curve = 0.85, recall = 0.62 and positive predictive value = 0.83) was observed despite the differences between the datasets. The proposed minimally invasive screening tool has shown promising performance when it comes to identifying children at risk of suffering obstructive sleep apnea syndrome. Moreover, it is ideal to be implemented in an outpatient consult in primary and secondary care.
Anti-Inflammatory Properties of Injectable Betamethasone-Loaded Tyramine-Modified Gellan Gum/Silk Fibroin Hydrogels
Authors: Oliveira Isabel Matos , Gonçalves Cristiana , Shin Myeong Eun , Lee Sumi , Reis Rui Luis , Khang Gilson , Oliveira Joaquim Miguel
Published: October 2020

Rheumatoid arthritis is a rheumatic disease for which a healing treatment does not presently exist. Silk fibroin has been extensively studied for use in drug delivery systems due to its uniqueness, versatility and strong clinical track record in medicine. However, in general, natural polymeric materials are not mechanically stable enough, and have high rates of biodegradation. Thus, synthetic materials such as gellan gum can be used to produce composite structures with biological signals to promote tissue-specific interactions while providing the desired mechanical properties. In this work, we aimed to produce hydrogels of tyramine-modified gellan gum with silk fibroin (Ty–GG/SF) via horseradish peroxidase (HRP), with encapsulated betamethasone, to improve the biocompatibility and mechanical properties, and further increase therapeutic efficacy to treat rheumatoid arthritis (RA). The Ty–GG/SF hydrogels presented a β-sheet secondary structure, with gelation time around 2–5 min, good resistance to enzymatic degradation, a suitable injectability profile, viscoelastic capacity with a significant solid component and a betamethasone-controlled release profile over time. In vitro studies showed that Ty–GG/SF hydrogels did not produce a deleterious effect on cellular metabolic activity, morphology or proliferation. Furthermore, Ty–GG/SF hydrogels with encapsulated betamethasone revealed greater therapeutic efficacy than the drug applied alone. Therefore, this strategy can provide an improvement in therapeutic efficacy when compared to the traditional use of drugs for the treatment of rheumatoid arthritis.
Updating Phospholipase A2 Biology
Authors: Murakami Makoto , Sato Hiroyasu , Taketomi Yoshitaka
Published: October 2020

The phospholipase A2 (PLA2) superfamily contains more than 50 enzymes in mammals that are subdivided into several distinct families on a structural and biochemical basis. In principle, PLA2 has the capacity to hydrolyze the sn-2 position of glycerophospholipids to release fatty acids and lysophospholipids, yet several enzymes in this superfamily catalyze other reactions rather than or in addition to the PLA2 reaction. PLA2 enzymes play crucial roles in not only the production of lipid mediators, but also membrane remodeling, bioenergetics, and body surface barrier, thereby participating in a number of biological events. Accordingly, disturbance of PLA2-regulated lipid metabolism is often associated with various diseases. This review updates the current state of understanding of the classification, enzymatic properties, and biological functions of various enzymes belonging to the PLA2 superfamily, focusing particularly on the novel roles of PLA2s in vivo.
Effect of Gosha-Jinki-Gan on Levels of Specific mRNA Transcripts in Mouse Testes after Busulfan Treatment
Authors: Qu Ning , Nagahori Kenta , Kuramasu Miyuki , Ogawa Yuki , Suyama Kaori , Hayashi Shogo , Sakabe Kou , Itoh Masahiro
Published: October 2020

With the increase in survival rates of cancer patients in recent years, infertility caused by anticancer treatments has become a significant concern for cancer survivors. Some studies have suggested that Sertoli cells play a key role in mediating testicular immunology in busulfan-induced aspermatogenesis. We recently demonstrated that Gosha-jinki-gan (TJ107), a traditional Japanese medicine, can completely recover injured spermatogenesis in mice 60 days after busulfan injection. In the present study, we sought to examine the levels of mRNA transcripts encoding markers of 25 Sertoli cell-specific products and 10 markers of germ cell differentiation. Our results demonstrated that only supplementation of TJ107 at day 60 after busulfan injection could significantly recover the increase in five mRNA species (Amh, Clu, Shbg, Testin, and Il1a) and the decrease in four mRNA species (Aqp8, CST9, Wnt5a, and Tjp1) in response to Busulfan (BSF) at day 120, with the increase of all examined spermatogenic markers.
Determination of the Empirical Electrokinetic Equilibrium Condition of Microorganisms in Microfluidic Devices
Authors: Coll De Peña Adriana , Hill Nicole , Lapizco-Encinas Blanca H.
Published: October 2020

The increased concern regarding emerging pathogens and antibiotic resistance has drawn interest in the development of rapid and robust microfluidic techniques to analyze microorganisms. The novel parameter known as the electrokinetic equilibrium condition (EEEC) was presented in recent studies, providing an approach to analyze microparticles in microchannels employing unique electrokinetic (EK) signatures. While the EEEC shows great promise, current estimation approaches can be time-consuming or heavily user-dependent for accurate values. The present contribution aims to analyze existing approaches for estimating this parameter and modify the process into an accurate yet simple technique for estimating the EK behavior of microorganisms in insulator-based microfluidic devices. The technique presented here yields the parameter called the empirical electrokinetic equilibrium condition (eEEEC) which works well as a value for initial approximations of trapping conditions in insulator-based EK (iEK) microfluidic systems. A total of six types of microorganisms were analyzed in this study (three bacteria and three bacteriophages). The proposed approach estimated eEEEC values employing images of trapped microorganisms, yielding high reproducibility (SD 5.0–8.8%). Furthermore, stable trapping voltages (sTVs) were estimated from eEEEC values for distinct channel designs to test that this parameter is system-independent and good agreement was obtained when comparing estimated sTVs vs. experimental values (SD 0.3–19.6%). The encouraging results from this work were used to generate an EK library of data, available on our laboratory website. The data in this library can be used to design tailored iEK microfluidic devices for the analysis of microorganisms.
The Influence of Recreational Substance Use in TMS Research
Authors: Turco Claudia V. , Arsalan Sarah O. , Nelson Aimee J.
Published: October 2020

(1) Background: Transcranial magnetic stimulation (TMS) approaches are widely used to study cortical and corticospinal function. However, responses to TMS are subject to significant intra-and inter-individual variability. Acute and chronic exposure to recreational substances alters the excitability of the sensorimotor system and may contribute to the variability in TMS outcome measures. The increasing prevalence of recreational substance use poses a significant challenge for executing TMS studies, but there is a lack of clarity regarding the influence of these substances on sensorimotor function. (2) Methods: The literature investigating the influence of alcohol, nicotine, caffeine and cannabis on TMS outcome measures of corticospinal, intracortical and interhemispheric excitability was reviewed. (3) Results: Both acute and chronic use of recreational substances modulates TMS measures of excitability. Despite the abundance of research in this field, we identify knowledge gaps that should be addressed in future studies to better understand the influence of these substances on TMS outcomes. (4) Conclusions: This review highlights the need for TMS studies to take into consideration the history of participant substance use and to control for acute substance use prior to testing.
Early Onset Epilepsy Caused by Low-Grade Epilepsy-Associated Tumors and Focal Meningeal Involvement
Authors: De Palma Luca , Pepi Chiara , De Benedictis Alessandro , Pietrafusa Nicola , Mastronuzzi Angela , Cacchione Antonella , Carfì-Pavia Giusy , Rossi-Espagnet Camilla , Diomedi-Camassei Francesca , Rossi Sabrina , Napolitano Antonio , Carai Andrea , Colafati Giovanna Stefania , Longo Daniela , Curatolo Paolo , Vigevano Federico , Marras Carlo Efisio , Specchio Nicola
Published: October 2020

Background: Low-grade epilepsy-associated neuroepithelial tumors (LEATs) are a frequent etiology in pediatric patients with epilepsy undergoing surgery. Objective: To identify differences in clinical and post-surgical follow-up between patients with focal meningeal involvement (MI) and those without MI within our cohort of pediatric patients with LEATs. Methods: We retrospectively reviewed all pediatric patients (<18 y) who underwent epilepsy surgery between 2011 and 2017 at our hospital. Cohort inclusion required histological diagnosis of LEATs and post-surgical follow-up of ≥2 y. We subsequently stratified patients according to presence of neuroradiological MI. Results: We identified 37 patients: five with MI and 32 without. Half of patients (19) were drug sensitive at surgery; similar between groups. The group with MI differed mainly for age of epilepsy-onset (0.6 vs. 7.0 y) but not for epilepsy duration (0.9 vs. 1.5 y). Post-surgery radiological follow-up (median 4.0 y; IQR 2.8–5.0 y) did not indicate disease progression. Seizure outcome was excellent in both groups, with 34 patients overall being both drug- and seizure-free. Conclusions: Our study identified a new subgroup of LEATs with focal MI and excellent post-surgical outcome. Moreover, this highlights the effectiveness of early surgery in pediatric LEATs.
A Three-Stage Teacher, Student Neural Networks and Sequential Feed Forward Selection-Based Feature Selection Approach for the Classification of Autism Spectrum Disorder
Authors: Khan Naseer Ahmed , Waheeb Samer Abdulateef , Riaz Atif , Shang Xuequn
Published: October 2020

Autism disorder, generally known as Autism Spectrum Disorder (ASD) is a brain disorder characterized by lack of communication skills, social aloofness and repetitions in the actions in the patients, which is affecting millions of the people across the globe. Accurate identification of autistic patients is considered a challenging task in the domain of brain disorder science. To address this problem, we have proposed a three-stage feature selection approach for the classification of ASD on the preprocessed Autism Brain Imaging Data Exchange (ABIDE) rs-fMRI Dataset. In the first stage, a large neural network which we call a “Teacher ” was trained on the correlation-based connectivity matrix to learn the latent representation of the input. In the second stage an autoencoder which we call a “Student” autoencoder was given the task to learn those trained “Teacher” embeddings using the connectivity matrix input. Lastly, an SFFS-based algorithm was employed to select the subset of most discriminating features between the autistic and healthy controls. On the combined site data across 17 sites, we achieved the maximum 10-fold accuracy of 82% and for the individual site-wise data, based on 5-fold accuracy, our results outperformed other state of the art methods in 13 out of the total 17 site-wise comparisons.
Arthralgia Induced by BRAF Inhibitor Therapy in Melanoma Patients
Authors: Salzmann Martin , Benesova Karolina , Buder-Bakhaya Kristina , Papamichail Dimitrios , Dimitrakopoulou-Strauss Antonia , Lorenz Hanns-Martin , Enk Alexander H. , Hassel Jessica C.
Published: October 2020

Introduction: BRAF inhibitors (BRAFi), commonly used in BRAF-mutated metastatic melanoma (MM) treatment, frequently cause arthralgia. Although this is one of the most common side effects, it has not been characterized yet. Methods: We retrospectively included all patients treated with BRAFi +/− MEK inhibitors (MEKi) for MM at the National Center for Tumor Diseases (Heidelberg) between 2010 and 2018 and reviewed patient charts for the occurrence and management of arthralgia. The evaluation was supplemented by an analysis of frozen sera. Results: We included 154 patients (63% males); 31% (48/154) of them reported arthralgia with a median onset of 21 days after the start of the therapy. Arthralgia mostly affected small joints (27/36, 75%) and less frequently large joints (19/36, 53%). The most commonly affected joints were in fingers (19/36, 53%), wrists (16/36, 44%), and knees (12/36, 33%). In 67% (24/36) of the patients, arthralgia occurred with a symmetrical polyarthritis, mainly of small joints, resembling the pattern typically observed in patients affected by rheumatoid arthritis (RA), for which a role of the MAPK signaling pathway was previously described. Patients were negative for antinuclear antibodies, anti-citrullinated protein antibodies, and rheumatoid factor; arthritis was visible in 10 of 13 available PET–CT scans. The development of arthralgia was linked to better progression-free survival and overall survival. Conclusion: Arthralgia is a common side effect in patients receiving BRAFi +/− MEKi therapy and often presents a clinical pattern similar to that observed in RA patients. Its occurrence was associated with longer-lasting tumor control.
Dichotomous Impact of Myc on rRNA Gene Activation and Silencing in B Cell Lymphomagenesis
Authors: Joshi Gaurav , Eberhardt Alexander Otto , Lange Lisa , Winkler René , Hoffmann Steve , Kosan Christian , Bierhoff Holger
Published: October 2020

A major transcriptional output of cells is ribosomal RNA (rRNA), synthesized by RNA polymerase I (Pol I) from multicopy rRNA genes (rDNA). Constitutive silencing of an rDNA fraction by promoter CpG methylation contributes to the stabilization of these otherwise highly active loci. In cancers driven by the oncoprotein Myc, excessive Myc directly stimulates rDNA transcription. However, it is not clear when during carcinogenesis this mechanism emerges, and how Myc-driven rDNA activation affects epigenetic silencing. Here, we have used the Eµ-Myc mouse model to investigate rDNA transcription and epigenetic regulation in Myc-driven B cell lymphomagenesis. We have developed a refined cytometric strategy to isolate B cells from the tumor initiation, promotion, and progression phases, and found a substantial increase of both Myc and rRNA gene expression only in established lymphoma. Surprisingly, promoter CpG methylation and the machinery for rDNA silencing were also strongly up-regulated in the tumor progression state. The data indicate a dichotomous role of oncogenic Myc in rDNA regulation, boosting transcription as well as reinforcing repression of silent repeats, which may provide a novel angle on perturbing Myc function in cancer cells.
Radiomic Features and Machine Learning for the Discrimination of Renal Tumor Histological Subtypes: A Pragmatic Study Using Clinical-Routine Computed Tomography
Authors: Uhlig Johannes , Leha Andreas , Delonge Laura M. , Haack Anna-Maria , Shuch Brian , Kim Hyun S. , Bremmer Felix , Trojan Lutz , Lotz Joachim , Uhlig Annemarie
Published: October 2020

This study evaluates the diagnostic performance of radiomic features and machine learning algorithms for renal tumor subtype assessment in venous computed tomography (CT) studies from clinical routine. Patients undergoing surgical resection and histopathological assessment of renal tumors at a tertiary referral center between 2012 and 2019 were included. Preoperative venous-phase CTs from multiple referring imaging centers were segmented, and standardized radiomic features extracted. After preprocessing, class imbalance handling, and feature selection, machine learning algorithms were used to predict renal tumor subtypes using 10-fold cross validation, assessed as multiclass area under the curve (AUC). In total, n = 201 patients were included (73.7% male; mean age 66 ± 11 years), with n = 131 clear cell renal cell carcinomas (ccRCC), n = 29 papillary RCC, n = 11 chromophobe RCC, n = 16 oncocytomas, and n = 14 angiomyolipomas (AML). An extreme gradient boosting algorithm demonstrated the highest accuracy (multiclass area under the curve (AUC) = 0.72). The worst discrimination was evident for oncocytomas vs. AML and oncocytomas vs. chromophobe RCC (AUC = 0.55 and AUC = 0.45, respectively). In sensitivity analyses excluding oncocytomas, a random forest algorithm showed the highest accuracy, with multiclass AUC = 0.78. Radiomic feature analyses from venous-phase CT acquired in clinical practice with subsequent machine learning can discriminate renal tumor subtypes with moderate accuracy. The classification of oncocytomas seems to be the most complex with the lowest accuracy.