bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing the Effect of Different Antibiotics in Frozen-Thawed Ram Sperm: Is It Possible to Avoid Their Addition?
Authors: Anel-Lopez Luis , Riesco Marta F. , Montes-Garrido Rafael , Neila-Montero Marta , Boixo Juan C. , Chamorro César , Ortega-Ferrusola Cristina , Carvajal Ana , Altonaga Jose R. , de Paz Paulino , Alvarez Mercedes , Anel Luis
Published: May 2021

It is crucial to perform a deep study about the most extensively used antibiotics in sperm extenders. Most of the protocols and concentrations used in ram are direct extrapolations from other species. It is important to establish species-specific antibiotic treatments to optimize their use and if it is possible to reduce the quantity. Previews studies have assessed some aspects of sperm qualityin vitro, but this study aimed to go further and assess the effect of three different antibiotic treatments, which are the most extensively used, not only in sperm quality or assessing the inhibitory effect on bacterial growth but also assessing these important parameters of productivity such as fertility, prolificacy, fecundity, and sex-ratio during a freeze-thaw process. Gentamicyn (G) treatment showed the worst results, not only concerning sperm quality but also in the reproductive trials exhibiting a toxical effect at the experiment concentration, and being the most powerful inhibiting bacterial growth. For its part, Lincomicyn-spectinomycin (LS) showed similar results inhibiting bacterial growth but it did not show a detrimental effect either in sperm quality or in reproductive parameters. Penicillin-streptomycin (PS) showed good results in the sperm quality and in the reproductivein vivotrials, but it showed a very poor effect inhibiting bacterial growth probably due to some kind of antibiotic resistance. According to our results, there is not a significant positive relationship between the higher bacterial inhibitory activity of LS and PS samples, and the sperm quality respect Control samples (without antibiotics). In the case of G, which exhibited the most effective as antibacterial, we observed a toxic effect on sperm quality that could be translated on productivity parameters. Our results suggest that the bacterial contamination control in frozen-thawed semen may be possible without the use of antibiotics, although the effects of longer periods of cooling storage and different temperatures of storage need to be further investigated for animal semen. At this point, a reflection about a drastic reduction in the use of antibiotic treatments in sperm cryopreservation is mandatory, since freezing conditions could keep sperm doses contamination within the levels recommended by regulatory health agencies.
Heterogeneity of Pulmonary Granulomas in Cattle Experimentally Infected With Mycobacterium bovis
Authors: Palmer Mitchell V. , Thacker Tyler C. , Kanipe Carly , Boggiatto Paola M.
Published: May 2021

Mycobacterium bovis is the cause of tuberculosis in most animals, most notably cattle. The stereotypical lesion of bovine tuberculosis is the granuloma; a distinct morphological lesion where host and pathogen interact and disease outcome (i.e., dissemination, confinement, or resolution) is determined. Accordingly, it is critical to understand host-pathogen interactions at the granuloma level. Host-pathogen interactions within individual granulomas at different stages of disease have not been examined in cattle. We examined bacterial burden and cytokine expression in individual pulmonary granulomas from steers at 30, 90, 180, and 270 days after experimental aerosol infection with M. bovis. Bacterial burdens within individual granulomas examined 30 days after infection were greater and more heterogenous (variable) than those examined 90 to 270 days after infection. Bacterial burdens did not correlate with expression of IFN-γ, TNF-α, TGF-β, granuloma stage, or lung lesion score, although there was a modest positive correlation with IL-10 expression. Granuloma stage did have modest positive and negative correlations with TNF-α and IL-10, respectively. Heterogeneity and mean expression of IFN-γ, IL-10 and TNF-α did not differ significantly over time, however, expression of TGF-β at 90 days was significantly greater than that seen at 30 days after infection.
Między lękiem a fascynacją. Pojęcie powietrza w dziejach
polszczyzny .
Authors: Janowska Aleksandra
Published: May 2021

This paper, which proposes a historical overview, is dedicated to the notion
of  (air) and its lexical equivalent in the Polish language. This notion
has undergone numerous changes over time; it has formed through direct
human experience on the one hand and through the Christian and Slavic
traditions as well as scientifi c knowledge overlapping on the other hand. This
notion has always been important to the human being, it has been commonly
referred to in metaphors and similes.
In the historical analysis, two basic senses of powietrze (air) were taken into
consideration: ‘place’ and ‘substance’. In both cases, there has always been
a clearly ambivalent attitude to the human being, who sees threats on the one
hand and feels that air guarantees life on the other hand.
Keywords: notion – semantic change – history of Polish – historical lexis
Słownictwo dotyczące świata fauny i flory w Symbolice
wiosennej Stefanii Ulanowskiej
Authors: Andrejczyk Małgorzata
Published: May 2021

The object of interest in this sketch is an analysis of the vocabulary indicating
selected elements of the world of fauna and fl ora in Symbolika wiosenna (Spring
symbolism) by Stefania Ulanowska (Kraków 1884). The collected language
material is characterised by wealth and complexity of the subject matter.
The indicated vocabulary has not been characterised yet. This paper employs
elements of the cognitivist description of language. The selection of this method
enables depiction of the relation between linguistic knowledge and encyclopaedic
knowledge. Language becomes an indispensible element of mental processes
of the perception of the world (Tokarski 1995; Miodunka 1980). The analysis
of the excerpted material clearly shows that the discussed spring symbolism
usually invokes, contrary to the prototype, the semantic fi eld related to ‘śmierć’
(death) rather than ‘życie’ (life). The reconstructed image of the folk idea of spring
largely deviates from the ideas established in the consciousness of language
users in general, which is confi rmed by the discussed examples. It presents
unit connotations that are individualised and present in the consciousness of
members of small rural communities of those times.
Keywords: Stefania Ulanowska – vocabulary of fauna and flora
UAV- and Random-Forest-AdaBoost (RFA)-Based Estimation of Rice Plant Traits
Authors: Muharam Farrah Melissa , Nurulhuda Khairudin , Zulkafli Zed , Tarmizi Mohamad Arif , Abdullah Asniyani Nur Haidar , Che Hashim Muhamad Faiz , Mohd Zad Siti Najja , Radhwane Derraz , Ismail Mohd Razi
Published: May 2021

Rapid, accurate and inexpensive methods are required to analyze plant traits throughout all crop growth stages for plant phenotyping. Few studies have comprehensively evaluated plant traits from multispectral cameras onboard UAV platforms. Additionally, machine learning algorithms tend to over- or underfit data and limited attention has been paid to optimizing their performance through an ensemble learning approach. This study aims to (1) comprehensively evaluate twelve rice plant traits estimated from aerial unmanned vehicle (UAV)-based multispectral images and (2) introduce Random Forest AdaBoost (RFA) algorithms as an optimization approach for estimating plant traits. The approach was tested based on a farmer’s field in Terengganu, Malaysia, for the off-season from February to June 2018, involving five rice cultivars and three nitrogen (N) rates. Four bands, thirteen indices and Random Forest-AdaBoost (RFA) regression models were evaluated against the twelve plant traits according to the growth stages. Among the plant traits, plant height, green leaf and storage organ biomass, and foliar nitrogen (N) content were estimated well, with a coefficient of determination (R2) above 0.80. In comparing the bands and indices, red, Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Red-Edge Wide Dynamic Range Vegetation Index (REWDRVI) and Red-Edge Soil Adjusted Vegetation Index (RESAVI) were remarkable in estimating all plant traits at tillering, booting and milking stages with R2 values ranging from 0.80–0.99 and root mean square error (RMSE) values ranging from 0.04–0.22. Milking was found to be the best growth stage to conduct estimations of plant traits. In summary, our findings demonstrate that an ensemble learning approach can improve the accuracy as well as reduce under/overfitting in plant phenotyping algorithms.
Overexpression of OsABCG48 Lowers Cadmium in Rice (Oryza sativa L.)
Authors: Cai Xingzhe , Wang Meng , Jiang Yucong , Wang Changhu , Ow David W.
Published: May 2021

Cadmium pollution threatens food safety and security by causing health issues and reducing farmland availability. Engineering genetic changes in crop plants to lower Cd accumulation can be a cost-effective approach to address this problem. Previously, we reported that a rice line, 2B, which expresses a truncated version of OsO3L2 had reduced Cd accumulation throughout the plant, including in seed. However, downstream events caused by expression of this gene were not known. In this study, RNA-seq was used to identify differentially expressed genes between the wild type and 2B rice with or without Cd treatment, leading to the study of an ABC transporter gene, OsABCG48 (ATP-Binding Cassette transporter G family member 48). Heterologous expression of OsABCG48 conferred tolerance to Cd in Schizosaccharomyces pombe, Arabidopsis and rice. Moreover, overexpressing OsABCG48 in rice lowered root Cd accumulation that was associated with more extensive lateral root development. These data suggest that OsABCG48 might have applications for engineering low-Cd rice.
De Novo Transcriptome Sequencing in Kiwifruit (Actinidia chinensis var. deliciosa (A Chev) Liang et Ferguson) and Development of Tissue-Specific Transcriptomic Resources
Authors: Salazar Juan Alfonso , Vergara-Pulgar Cristian , Jorquera Claudia , Zapata Patricio , Ruiz David , Martínez-Gómez Pedro , Infante Rodrigo , Meneses Claudio
Published: May 2021

Kiwifruit (Actinidia chinensis var. deliciosa (A Chev) Liang et Ferguson) is a sub-tropical vine species from the Actinidiaceae family native to China. This species has an allohexaploid genome (from diploid and autotetraploid parents), contained in 174 chromosomes producing a climacteric and fleshy fruit called kiwifruit. Currently, only a small body of transcriptomic and proteomic data are available for A. chinensis var. deliciosa. In this low molecular knowledge context, the main goal of this study is to construct a tissue-specific de novo transcriptome assembly, generating differential expression analysis among these specific tissues, to obtain new useful transcriptomic information for a better knowledge of vegetative, floral and fruit growth in this species. In this study, we have analyzed different whole transcriptomes from shoot, leaf, flower bud, flower and fruit at four development stages (7, 50, 120 and 160 days after flowering; DAF) in kiwifruit obtained through RNA-seq sequencing. The first version of the developed A. chinensis var. deliciosa de novo transcriptome contained 142,025 contigs (x¯ = 1044 bp, N50 = 1133 bp). Annotation was performed with BLASTX against the TAIR10 protein database, and we found an annotation proportion of 35.6% (50,508), leaving 64.4% (91,517) of the contigs without annotation. These results represent a reference transcriptome for allohexaploid kiwifruit generating a database of A. chinensis var. deliciosa genes related to leaf, flower and fruit development. These results provided highly valuable information identifying over 20,000 exclusive genes including all tissue comparisons, which were associated with the proteins involved in different biological processes and molecular functions.
Diverse Physiological and Physical Responses among Wild, Landrace and Elite Barley Varieties Point to Novel Breeding Opportunities
Authors: Stevens Jim , Jones Matthew Alan , Lawson Tracy
Published: May 2021

Climate change from elevated [CO2] may reduce water availability to crops through changes in precipitation and higher temperatures. However, agriculture already accounts for 70% of human consumption of water. Stomata, pores in the leaf surface, mediate exchange of water and CO2 for the plant. In crops including barley, the speed of stomatal response to changing environmental conditions is as important as maximal responses and can thus affect water use efficiency. Wild barleys and landraces which predate modern elite lines offer the breeder the potential to find unexploited genetic diversity. This study aimed to characterize natural variation in stomatal anatomy and leaf physiology and to link these variations to yield. Wild, landrace and elite barleys were grown in a polytunnel and a controlled environment chamber. Physiological responses to changing environments were measured, along with stomatal anatomy and yield. The elite barley lines did not have the fastest or largest physiological responses to light nor always the highest yields. There was variation in stomatal anatomy, but no link between stomatal size and density. The evidence suggests that high photosynthetic capacity does not translate into yield, and that landraces and wild barleys have unexploited physiological responses that should interest breeders.
Microsatellite-Based Genetic Characterization of the Indigenous Katjang Goat in Peninsular Malaysia
Authors: Ernie Muneerah Mohd Adhan , Md Tamrin Nur Aida , Salisi Mohd Shahrom , Zulkifly Shahrizim , Ghazali Siti Shaidatul Maisarah , Temuli Jackson Jenun , Rosali Mohd Hifzan , Nazari Shariffah , Wan Nik Wan Mohd Kamil , Mamat-Hamidi Kamalludin
Published: May 2021

The Katjang goat is the only indigenous domestic goat breed in Malaysia. Following a national baseline survey from 2001 to 2002, this breed was reported to the FAO as being at risk of extinction. In this study, 36 microsatellite markers were screened, and 25 polymorphic markers were used to analyze the genetic structure of the Katjang goat breed in Peninsular Malaysia. A sample set of data derived from another 10 populations from three published research studies was used as an outgroup for an inter-population genetic study. The analysis showed that the mean value of the observed heterozygosity was 0.29 ± 0.14, and the expected heterozygosity was 0.72 ± 0.14, which indicated low genetic diversity. The inbreeding coefficient, FIS, was high, at 0.46. Significant (p < 0.01) deviations from the Hardy Weinberg equilibrium were noted for all loci. The bottleneck analysis using the Wilcoxon Rank test under the two-phase model of mutation was significant (p < 0.01) for heterozygosity excess, which suggested that the Katjang breed had undergone significant population reduction in the past. Through combined analysis of data from publicly available research, almost the entire population of Katjang goats represent the centroid and are grouped together on a multidimensional scaling plot, except for the Terengganu population. Network analysis revealed that the goat population from Pahang formed the centrality of the network.
Effect of Finishing Diet and Lairage Time on Steers Welfare in Uruguay
Authors: del Campo Gigena Marcia , Soares de Lima Juan Manuel , Brito Gustavo , Manteca Xavier , Hernández Pilar , Montossi Fabio
Published: May 2021

The objective of this experiment was to evaluate the effect of two different pasture-based finishing strategies and lairage time on steers welfare in Uruguayan conditions. Sixty Hereford (H) and Braford (B) steers were assigned to two different diets for finishing purposes: (D1) native pasture plus corn grain (1% of live weight) (H n = 15, B n = 15) and (D2) high-quality pasture (H n = 15, B n = 15). The average daily gain was registered every 14 days, and temperaments were individually assessed one week before slaughter by three individual tests: crush score, flight time and exit speed, building a multicriterial temperament index (TIndex). Animals were slaughtered the same day in two groups (50% from D1 and 50% from D2 in each group) after traveling for 3.5 h and staying 15 (long lairage) and 3 h (short lairage) in the lairage pens, respectively. The behaviors were observed during lairage, and physiological indicators were used to assess stress at the farm after transport, after lairage and at slaughter. Bruises incidence and final pH were registered at the abattoir as a means of assessing the overall animal welfare. Calmer animals had higher average daily gains with no differences either between diets or between breeds. Calmer animals also had a lower stress response during all preslaughter stages, regardless of the time in lairage. Transport did not imply psychological stress (cortisol) for any slaughter group, but physical stress was evident after transport in both groups through NEFA and CPK increases. Bruise incidences did not differ between lairage groups. The short lairage group did not have enough time to cope with the environment before slaughter, with the consequent deleterious effects on the carcass pH. Animals from the long lairage group had a higher metabolic response shown through NEFA values, but they had enough time to rest and recover overnight, reaching final pH values lower than 5.8, considered the upper limit of the normal range. According to this experiment, with pasture-based animals without fasting on the farm and after 3.5 h of transportation, a resting period of 15 h in lairage should be better than a 3-h one.
The Nero Lucano Pig Breed: Recovery and Variability
Authors: Valluzzi Carmelisa , Rando Andrea , Macciotta Nicolò P. P. , Gaspa Giustino , Di Gregorio Paola
Published: May 2021

The Nero Lucano (NL) pig is a black coat colored breed characterized by a remarkable ability to adapt to the difficult territory and climatic conditions of Basilicata region in Southern Italy. In the second half of the twentieth century, technological innovation, agricultural evolution, new breeding methods and the demand for increasingly lean meat brought the breed almost to extinction. Only in 2001, thanks to local institutions such as: the Basilicata Region, the University of Basilicata, the Regional Breeders Association and the Medio Basento mountain community, the NL pig returned to populate the area with the consequent possibility to appreciate again its specific cured meat products. We analyzed the pedigrees recorded by the breeders and the Illumina Porcine SNP60 BeadChip genotypes in order to obtain the genetic structure of the NL pig. Results evidenced that this population is characterized by long mean generation intervals (up to 3.5 yr), low effective population size (down to 7.2) and high mean inbreeding coefficients (FMOL = 0.53, FROH = 0.39). This picture highlights the low level of genetic variability and the critical issues to be faced for the complete recovery of this population.
Cnicin as an Anti-SARS-CoV-2: An Integrated In Silico and In Vitro Approach for the Rapid Identification of Potential COVID-19 Therapeutics
Authors: Alhadrami Hani A. , Sayed Ahmed M. , Hassan Hossam M. , Youssif Khayrya A. , Gaber Yasser , Moatasim Yassmin , Kutkat Omnia , Mostafa Ahmed , Ali Mohamed Ahmed , Rateb Mostafa E. , Abdelmohsen Usama Ramadan , Gamaleldin Noha M.
Published: May 2021

Since the emergence of the SARS-CoV-2 pandemic in 2019, it has remained a significant global threat, especially with the newly evolved variants. Despite the presence of different COVID-19 vaccines, the discovery of proper antiviral therapeutics is an urgent necessity. Nature is considered as a historical trove for drug discovery, especially in global crises. During our efforts to discover potential anti-SARS CoV-2 natural therapeutics, screening our in-house natural products and plant crude extracts library led to the identification of C. benedictus extract as a promising candidate. To find out the main chemical constituents responsible for the extract’s antiviral activity, we utilized recently reported SARS CoV-2 structural information in comprehensive in silico investigations (e.g., ensemble docking and physics-based molecular modeling). As a result, we constructed protein–protein and protein–compound interaction networks that suggest cnicin as the most promising anti-SARS CoV-2 hit that might inhibit viral multi-targets. The subsequent in vitro validation confirmed that cnicin could impede the viral replication of SARS CoV-2 in a dose-dependent manner, with an IC50 value of 1.18 µg/mL. Furthermore, drug-like property calculations strongly recommended cnicin for further in vivo and clinical experiments. The present investigation highlighted natural products as crucial and readily available sources for developing antiviral therapeutics. Additionally, it revealed the key contributions of bioinformatics and computer-aided modeling tools in accelerating the discovery rate of potential therapeutics, particularly in emergency times like the current COVID-19 pandemic.
Predictive Modeling of Changes in TBARS in the Intramuscular Lipid Fraction of Raw Ground Beef Enriched with Plant Extracts
Authors: Kaczmarek Anna , Muzolf-Panek Małgorzata
Published: May 2021

The aim of the study was to develop and compare the predictive models of lipid oxidation in minced raw beef meat enriched with selected plant extracts (allspice, basil, bay leaf, black seed, cardamom, caraway, cloves, garlic, nutmeg, onion, oregano, rosemary and thyme) expressed as value changes of TBARS (thiobarbituric acid reactive substances) in various time/temperature conditions. Meat samples were stored at the temperatures of 4, 8, 12, 16 and 20 °C. The value changes of TBARS in samples stored at 12 °C were used as the external validation dataset. Lipid oxidation increased significantly with storage time and temperature. The rate of this increase varied depending on the addition of the plant extract and was the most pronounced in the control sample. The dependence of lipid oxidation on temperature was adequately modeled by the Arrhenius and log-logistic equation with high average R2 coefficients (≥0.98) calculated for all extracts. Kinetic models and artificial neural networks (ANNs) were used to build the predictive models. The obtained result demonstrates that both kinetic Arrhenius (R2 = 0.972) and log-logistic (R2 = 0.938) models as well as ANN (R2 = 0.935) models can predict changes in TBARS in raw ground beef meat during storage.
Orbit Decomposition Method for Rotordynamic Coefficients Identification of Annular Seals
Authors: Zhang Mingjie , Yang Jiangang , Zhang Wanfu , Gu Qianlei
Published: May 2021

The elliptical orbit whirl model is widely used to identify the frequency-dependent rotordynamic coefficients of annular seals. The existing solution technique of an elliptical orbit whirl model is the transient computational fluid dynamics (CFD) method. Its computational time is very long. For rapid computation, this paper proposes the orbit decomposition method. The elliptical whirl orbit is decomposed into the forward and backward circular whirl orbits. Under small perturbation circumstances, the fluid-induced forces of the elliptical orbit model can be obtained by the linear superposition of the fluid-induced forces arising from the two decomposed circular orbit models. Due to that the fluid-induced forces of circular orbit, the model can be calculated with the steady CFD method, and the transient computations can be replaced with steady ones when calculating the elliptical orbit whirl model. The computational time is significantly reduced. To validate the present method, its rotordynamic results are compared with those of the transient CFD method and experimental data. Comparisons show that the present method can accurately calculate the rotordynamic coefficients. Elliptical orbit parameter analysis reveals that the present method is valid when the whirl amplitude is less than 20% of seal clearance. The effect of ellipticity on rotordynamic coefficients can be ignored.
Multi-Task Learning for Medical Image Inpainting Based on Organ Boundary Awareness
Authors: Tran Minh-Trieu , Kim Soo-Hyung , Yang Hyung-Jeong , Lee Guee-Sang
Published: May 2021

Distorted medical images can significantly hamper medical diagnosis, notably in the analysis of Computer Tomography (CT) images and organ segmentation specifics. Therefore, improving diagnostic imagery accuracy and reconstructing damaged portions are important for medical diagnosis. Recently, these issues have been studied extensively in the field of medical image inpainting. Inpainting techniques are emerging in medical image analysis since local deformations in medical modalities are common because of various factors such as metallic implants, foreign objects or specular reflections during the image captures. The completion of such missing or distorted regions is important for the enhancement of post-processing tasks such as segmentation or classification. In this paper, a novel framework for medical image inpainting is presented by using a multi-task learning model for CT images targeting the learning of the shape and structure of the organs of interest. This novelty has been accomplished through simultaneous training for the prediction of edges and organ boundaries with the image inpainting, while state-of-the-art methods still focus only on the inpainting area without considering the global structure of the target organ. Therefore, our model reproduces medical images with sharp contours and exact organ locations. Consequently, our technique generates more realistic and believable images compared to other approaches. Additionally, in quantitative evaluation, the proposed method achieved the best results in the literature so far, which include a PSNR value of 43.44 dB and SSIM of 0.9818 for the square-shaped regions; a PSNR value of 38.06 dB and SSIM of 0.9746 for the arbitrary-shaped regions. The proposed model generates the sharp and clear images for inpainting by learning the detailed structure of organs. Our method was able to show how promising the method is when applying it in medical image analysis, where the completion of missing or distorted regions is still a challenging task.
Machine Learning Model of Dimensionless Numbers to Predict Flow Patterns and Droplet Characteristics for Two-Phase Digital Flows
Authors: Zhang Jinsong , Zhang Shuai , Zhang Jianhua , Wang Zhiliang
Published: May 2021

In the digital microfluidic experiments, the droplet characteristics and flow patterns are generally identified and predicted by the empirical methods, which are difficult to process a large amount of data mining. In addition, due to the existence of inevitable human invention, the inconsistent judgment standards make the comparison between different experiments cumbersome and almost impossible. In this paper, we tried to use machine learning to build algorithms that could automatically identify, judge, and predict flow patterns and droplet characteristics, so that the empirical judgment was transferred to be an intelligent process. The difference on the usual machine learning algorithms, a generalized variable system was introduced to describe the different geometry configurations of the digital microfluidics. Specifically, Buckingham’s theorem had been adopted to obtain multiple groups of dimensionless numbers as the input variables of machine learning algorithms. Through the verification of the algorithms, the SVM and BPNN algorithms had classified and predicted the different flow patterns and droplet characteristics (the length and frequency) successfully. By comparing with the primitive parameters system, the dimensionless numbers system was superior in the predictive capability. The traditional dimensionless numbers selected for the machine learning algorithms should have physical meanings strongly rather than mathematical meanings. The machine learning algorithms applying the dimensionless numbers had declined the dimensionality of the system and the amount of computation and not lose the information of primitive parameters.
Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data
Authors: Yorks John E. , Selmer Patrick A. , Kupchock Andrew , Nowottnick Edward P. , Christian Kenneth E. , Rusinek Daniel , Dacic Natasha , McGill Matthew J.
Published: May 2021

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.
Measurement of Aerodynamic Characteristics Using Cinder Models through Free Fall Experiment
Authors: Liu Meizhi , Maruyama Takashi , Sasaki Kansuke , Inoue Minoru , Iguchi Masato , Fujita Eisuke
Published: May 2021

Rocks ejected from a volcanic eruption often cause loss of lives and structures. Aerodynamic characteristics are needed for evaluating motions of volcanic rocks for the reduction of damage. Falling motions of volcanic rock were measured by using models imitated the configuration of cinders collected at the site of the experiment, Sakurajima volcano. Two types, one with sharp edges and one without sharp edges, were selected as representative of cinder and a sphere was selected as reference model. The falling motions of the models dropped down from a drone were recorded by video camera and a stand-alone measuring system that included a pressure sensor, acceleration and angular velocity sensors in the models. The motion, posture, velocity and acceleration of the model were obtained in order to measure the three-dimensional falling trajectory. The drag and the deviation angle between relative wind direction and wind force direction were examined. The variation of the drag coefficient and the deviation angle with Reynolds number was clarified.
SeqFu: A Suite of Utilities for the Robust and Reproducible Manipulation of Sequence Files
Authors: Telatin Andrea , Fariselli Piero , Birolo Giovanni
Published: May 2021

Sequence files formats (FASTA and FASTQ) are commonly used in bioinformatics, molecular biology and biochemistry. With the advent of next-generation sequencing (NGS) technologies, the number of FASTQ datasets produced and analyzed has grown exponentially, urging the development of dedicated software to handle, parse, and manipulate such files efficiently. Several bioinformatics packages are available to filter and manipulate FASTA and FASTQ files, yet some essential tasks remain poorly supported, leaving gaps that any workflow analysis of NGS datasets must fill with custom scripts. This can introduce harmful variability and performance bottlenecks in pivotal steps. Here we present a suite of tools, called SeqFu (Sequence Fastx utilities), that provides a broad range of commands to perform both common and specialist operations with ease and is designed to be easily implemented in high-performance analytical pipelines. SeqFu includes high-performance implementation of algorithms to interleave and deinterleave FASTQ files, merge Illumina lanes, and perform various quality controls (identification of degenerate primers, analysis of length statistics, extraction of portions of the datasets). SeqFu dereplicates sequences from multiple files keeping track of their provenance. SeqFu is developed in Nim for high-performance processing, is freely available, and can be installed with the popular package manager Miniconda.
CT/MRI LI-RADS v2018 vs. CEUS LI-RADS v2017—Can Things Be Put Together?
Authors: Caraiani Cosmin , Boca Bianca , Bura Vlad , Sparchez Zeno , Dong Yi , Dietrich Christoph
Published: May 2021

Different LI-RADS core documents were released for CEUS and for CT/MRI. Both documents rely on major and ancillary diagnostic criteria. The present paper offers an exhaustive comparison of the two documents focusing on the similarities, but especially on the differences, complementarity, and added value of imaging techniques in classifying liver nodules in cirrhotic livers. The major diagnostic criteria are defined, and the sensitivity and specificity of each major diagnostic criteria are presented according to the literature. The existing differences between techniques in assessing the major diagnostic features can be then exploited in order to ensure a better classification and a better clinical management of liver nodules in cirrhotic livers. Ancillary features depend on the imaging technique used, and their presence can upgrade or downgrade the LI-RADS score of an observation, but only as far as LI-RADS 4. MRI is the imaging technique that provides the greatest number of ancillary features, whereas CEUS has fewer ancillary features than other imaging techniques. In the final part of the manuscript, some recommendations are made by the authors in order to guidephysicians as to when adding another imaging technique can be helpful in managing liver nodules in cirrhotic livers.
Effect of Long-Term Continuous Light Exposure and Western Diet on Adropin Expression, Lipid Metabolism, and Energy Homeostasis in Rats
Authors: Abulmeaty Mahmoud , Almajwal Ali , Alnumair Khalid , Razak Suhail , Hasan Mai , Fawzy Amal , Farraj Abdullah , Abudawood Manal , Aljuraiban Ghadeer
Published: May 2021

Long-term continuous light exposure (CL) and western diet (WD) effects on Adropin expression, RORα, and Rev-erb-α nuclear receptors and energy homeostasis were studied in rats. Thirty-two male Wistar rats (250–290 g) were enrolled for 3 months in the following groups (n = 8/group): (a) Normal control group (NC), (b) CL group, (c) WD group, and (d) CL + WD group. Then, indirect calorimetry and food intake (FI) were measured. Finally, Adropin, hormone-sensitive lipase (HSL), adipocyte triglyceride lipase (ATGL), and free fatty acids (FFA) were measured. Additionally, the histopathology and gene expression of Enho, RORα, and Rev-erb-α genes were done. The CL alone elevated the Adropin plasma level and gene expression, increased RORα expression, and decreased the Rev-erb-α nuclear receptor expression mainly in the liver and kidney. Besides, CL increased the total energy expenditure (TEE) and decreased the respiratory quotient. WD alone or in combination with the CL reversed gene expression of Enho, RORα, and Rev-erb-α. Combined CL and WD increased the TEE, reduced the food intake, increased the ATGL, and reduced the Adropin level in addition to widespread degenerative changes in the liver, spleen, and renal tissues. The deleterious effects of CL and WD on energy homeostasis may include Adropin with the involvement of the RORα and Rev-erb-α nuclear receptors.
Oncogenic Potential of the Dual-Function Protein MEX3A
Authors: Lederer Marcell , Müller Simon , Glaß Markus , Bley Nadine , Ihling Christian , Sinz Andrea , Hüttelmaier Stefan
Published: May 2021

MEX3A belongs to the MEX3 (Muscle EXcess) protein family consisting of four members (MEX3A-D) in humans. Characteristic for MEX3 proteins is their domain structure with 2 HNRNPK homology (KH) domains mediating RNA binding and a C-terminal really interesting new gene (RING) domain that harbors E3 ligase function. In agreement with their domain composition, MEX3 proteins were reported to modulate both RNA fate and protein ubiquitination. MEX3 paralogs exhibit an oncofetal expression pattern, they are severely downregulated postnatally, and re-expression is observed in various malignancies. Enforced expression of MEX3 proteins in various cancers correlates with poor prognosis, emphasizing their oncogenic potential. The latter is supported by MEX3A’s impact on proliferation, self-renewal as well as migration of tumor cells in vitro and tumor growth in xenograft studies.
Biostimulants Application: A Low Input Cropping Management Tool for Sustainable Farming of Vegetables
Authors: Shahrajabian Mohamad Hesam , Chaski Christina , Polyzos Nikolaos , Petropoulos Spyridon A.
Published: May 2021

Biostimulants, are a diverse class of compounds including substances or microorganism which have positive impacts on plant growth, yield and chemical composition as well as boosting effects to biotic and abiotic stress tolerance. The major plant biostimulants are hydrolysates of plant or animal protein and other compounds that contain nitrogen, humic substances, extracts of seaweeds, biopolymers, compounds of microbial origin, phosphite, and silicon, among others. The mechanisms involved in the protective effects of biostimulants are varied depending on the compound and/or crop and mostly related with improved physiological processes and plant morphology aspects such as the enhanced root formation and elongation, increased nutrient uptake, improvement in seed germination rates and better crop establishment, increased cation exchange, decreased leaching, detoxification of heavy metals, mechanisms involved in stomatal conductance and plant transpiration or the stimulation of plant immune systems against stressors. The aim of this review was to provide an overview of the application of plant biostimulants on different crops within the framework of sustainable crop management, aiming to gather critical information regarding their positive effects on plant growth and yield, as well as on the quality of the final product. Moreover, the main limitations of such practice as well as the future prospects of biostimulants research will be presented.
Mitochondrial Alterations in Fibroblasts of Early Stage Bipolar Disorder Patients
Authors: Marques Ana P. , Resende Rosa , Silva Diana F. , Batista Mariana , Pereira Daniela , Wildenberg Brigite , Morais Sofia , Macedo António , Pais Cláudia , Melo Joana B. , Madeira Nuno , Pereira Cláudia F.
Published: May 2021

This study aims to evaluate whether mitochondrial changes occur in the early stages of bipolar disorder (BD). Using fibroblasts derived from BD patients and matched controls, the levels of proteins involved in mitochondrial biogenesis and dynamics (fission and fusion) were evaluated by Western Blot analysis. Mitochondrial membrane potential (MMP) was studied using the fluorescent probe TMRE. Mitochondrial morphology was analyzed with the probe Mitotracker Green and mitophagy was evaluated by quantifying the co-localization of HSP60 (mitochondria marker) and LC3B (autophagosome marker) by immunofluorescence. Furthermore, the activity of the mitochondrial respiratory chain and the glycolytic capacity of controls and BD patients-derived cells were also studied using the Seahorse technology. BD patient-derived fibroblasts exhibit fragmented mitochondria concomitantly with changes in mitochondrial dynamics and biogenesis in comparison with controls. Moreover, a decrease in the MMP and increased mitophagy was observed in fibroblasts obtained from BD patients when compared with control cells. Impaired energetic metabolism due to inhibition of the mitochondrial electron transport chain (ETC) and subsequent ATP depletion, associated with glycolysis stimulation, was also a feature of BD fibroblasts. Overall, these results support the fact that mitochondrial disturbance is an early event implicated in BD pathophysiology that might trigger neuronal changes and modification of brain circuitry.
Prediction of One Repetition Maximum Using Reference Minimum Velocity Threshold Values in Young and Middle-Aged Resistance-Trained Males
Authors: Fernandes John F. T. , Dingley Amelia F. , Garcia-Ramos Amador , Perez-Castilla Alejandro , Tufano James J. , Twist Craig
Published: May 2021

Background: This study determined the accuracy of different velocity-based methods when predicting one-repetition maximum (1RM) in young and middle-aged resistance-trained males. Methods: Two days after maximal strength testing, 20 young (age 21.0 ± 1.6 years) and 20 middle-aged (age 42.6 ± 6.7 years) resistance-trained males completed three repetitions of bench press, back squat, and bent-over-row at loads corresponding to 20–80% 1RM. Using reference minimum velocity threshold (MVT) values, the 1RM was estimated from the load-velocity relationships through multiple (20, 30, 40, 50, 60, 70, and 80% 1RM), two-point (20 and 80% 1RM), high-load (60 and 80% 1RM) and low-load (20 and 40% 1RM) methods for each group. Results: Despite most prediction methods demonstrating acceptable correlations (r = 0.55 to 0.96), the absolute errors for young and middle-aged groups were generally moderate to high for bench press (absolute errors = 8.2 to 14.2% and 8.6 to 20.4%, respectively) and bent-over-row (absolute error = 14.9 to 19.9% and 8.6 to 18.2%, respectively). For squats, the absolute errors were lower in the young group (5.7 to 13.4%) than the middle-aged group (13.2 to 17.0%) but still unacceptable. Conclusion: These findings suggest that reference MVTs cannot accurately predict the 1RM in these populations. Therefore, practitioners need to directly assess 1RM.
A Brief Review of Catalytic Cathode Materials for Na-CO2 Batteries
Authors: Sui Dong , Chang Meijia , Wang Haiyu , Qian Hang , Yang Yanliang , Li Shan , Zhang Yongsheng , Song Yingze
Published: May 2021

As an emerging energy storage technology, Na-CO2 batteries with high energy density are drawing tremendous attention because of their advantages of combining cost-effective energy conversion and storage with CO2 clean recycle and utilization. Nevertheless, their commercial applications are impeded by unsatisfactory electrochemical performance including large overpotentials, poor rate capability, fast capacity deterioration, and inferior durability, which mainly results from the inefficient electrocatalysts of cathode materials. Therefore, novel structured cathode materials with efficient catalytic activity are highly desired. In this review, the latest advances of catalytic cathode materials for Na-CO2 batteries are summarized, with a special emphasis on the electrocatalysts for CO2 reduction and evolution, the formation and decomposition of discharge product, as well as their catalytic mechanism. Finally, an outlook is also proposed for the future development of Na-CO2 batteries.
An Efficient Catalyst Prepared from Residual Kaolin for the Esterification of Distillate from the Deodorization of Palm Oil
Authors: de Nazaré de Oliveira Alex , Ferreira Irlon Maciel , Jimenez David Esteban Quintero , Neves Fernando Batista , Soares da Silva Linéia , Farias da Costa Ana Alice , Lima Erika Tallyta Leite , de Oliveira Pires Luíza Helena , Ferreira da Costa Carlos Emmerson , Narciso da Rocha Filho Geraldo , Santos do Nascimento Luís Adriano
Published: May 2021

The distillate from the deodorization of palm oil (DDPO) is an agro-industrial residue, approximately 84% of which consists of free fatty acids (FFAs), which can be used for the production of fatty acid ethyl esters (FAEE). A catalyst (10HPMo/AlSiM) obtained from a waste material, Amazon flint kaolin, was applied in the esterification of the DDPO, reaching a conversion index of 94%, capable of maintaining satisfactory activity (>75%) after four consecutive cycles. Flint kaolin is therefore proven to be an efficient option in the search for new heterogeneous low-cost catalysts obtained from industrial by-products, contributing to the reduction of environmental impact and adding value to widely available wastes that would otherwise be discarded directly into the environment. Based on the catalytic results, esterification of DDPO using 10HPMo/AlSiM can be a cheaper alternative for the production of sustainable fuels.
The Role of AMPK Signaling in Brown Adipose Tissue Activation
Authors: van der Vaart Jamie I. , Boon Mariëtte R. , Houtkooper Riekelt H.
Published: May 2021

Obesity is becoming a pandemic, and its prevalence is still increasing. Considering that obesity increases the risk of developing cardiometabolic diseases, research efforts are focusing on new ways to combat obesity. Brown adipose tissue (BAT) has emerged as a possible target to achieve this for its functional role in energy expenditure by means of increasing thermogenesis. An important metabolic sensor and regulator of whole-body energy balance is AMP-activated protein kinase (AMPK), and its role in energy metabolism is evident. This review highlights the mechanisms of BAT activation and investigates how AMPK can be used as a target for BAT activation. We review compounds and other factors that are able to activate AMPK and further discuss the therapeutic use of AMPK in BAT activation. Extensive research shows that AMPK can be activated by a number of different kinases, such as LKB1, CaMKK, but also small molecules, hormones, and metabolic stresses. AMPK is able to activate BAT by inducing adipogenesis, maintaining mitochondrial homeostasis and inducing browning in white adipose tissue. We conclude that, despite encouraging results, many uncertainties should be clarified before AMPK can be posed as a target for anti-obesity treatment via BAT activation.