Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-wide characterization and identification of Trihelix transcription factors and expression profiling in response to abiotic stresses in Chinese Willow (Salix matsudana Koidz)

Trihelix transcription factors (TTF) are a class of light-responsive proteins with a typical triple-helix structure (helix-loop-helix-loop-helix). Members of this gene family play an important role in plant growth and development, especially in various abiotic stress responses. Salix matsudana Koidz is an allotetraploid ornamental forest tree that is widely planted for its excellent resistance to stress, but no studies on its Trihelix gene family have been reported. In this study, the Trihelix gene family was analyzed at the genome-wide level in S. matsudana. A total of 78 S. matsudana Trihelix transcription factors (SmTTFs) were identified, distributed on 29 chromosomes, and classified into four subfamilies (GT-1, GT-2, SH4, SIP1) based on their structural features. The gene structures and conserved functional domains of these Trihelix genes are similar in the same subfamily and differ between subfamilies. The presence of multiple stress-responsive cis-elements on the promoter of the S. matsudana Trihelix gene suggests that the S. matsudana Trihelix gene may respond to abiotic stresses. Expression pattern analysis revealed that Trihelix genes have different functions during flooding stress, salt stress, drought stress and low temperature stress in S. matsudana. Given that SmTTF30, as a differentially expressed gene, has a faster response to flooding stress, we selected SmTTF30 for functional studies. Overexpression of SmTTF30 in Arabidopsis thaliana (Arabidopsis) enhances its tolerance to flooding stress. Under flooding stress, the leaf cell activity and peroxidase activity (POD) of the overexpression strain were significantly higher than the leaf cell activity and POD of the wild type, and the malondialdehyde (MDA) content was significantly lower than the MDA content of the wild type. Thus, these results suggest that SmTTF30 enhances plant flooding tolerance and plays a positive regulatory role in plant flooding tolerance.
Preclinical PET Imaging of Tumor Cell Death following Therapy Using Gallium-68-Labeled C2Am

Simple Summary There is an unmet clinical need for imaging agents capable of detecting the presence, extent, and distribution of tumor cell death following treatment. We describe here a gallium-68-labeled derivative of the C2A domain of Synaptotagmin-I (68Ga-C2Am), which binds to the phosphatidylserine exposed by dying cells, for imaging tumor cell death in vivo using positron emission tomography (PET). Since PET is a highly sensitive tomographic imaging technique that is widely used in clinical oncology and gallium-68 has emerged as a cost-effective radiotracer that can be eluted on site from a benchtop generator, 68Ga-C2Am could find clinical application for the rapid assessment of tumor responses to treatment. Abstract There is an unmet clinical need for imaging agents capable of detecting early evidence of tumor cell death, since the timing, extent, and distribution of cell death in tumors following treatment can give an indication of treatment outcome. We describe here 68Ga-labeled C2Am, which is a phosphatidylserine-binding protein, for imaging tumor cell death in vivo using positron emission tomography (PET). A one-pot synthesis of 68Ga-C2Am (20 min, 25 °C, >95% radiochemical purity) has been developed, using a NODAGA-maleimide chelator. The binding of 68Ga-C2Am to apoptotic and necrotic tumor cells was assessed in vitro using human breast and colorectal cancer cell lines, and in vivo, using dynamic PET measurements in mice implanted subcutaneously with the colorectal tumor cells and treated with a TRAIL-R2 agonist. 68Ga-C2Am showed predominantly renal clearance and low retention in the liver, spleen, small intestine, and bone and generated a tumor-to-muscle (T/m) ratio of 2.3 ± 0.4, at 2 h post probe administration and at 24 h following treatment. 68Ga-C2Am has the potential to be used in the clinic as a PET tracer for assessing early treatment response in tumors.
Genomic Characterization and Wetland Occurrence of a Novel Campylobacter Isolate from Canada Geese

Populations of resident, non-migratory Canada geese are rapidly increasing. Canada geese are known to transmit viral and bacterial diseases, posing a possible threat to human health. The most prevalent pathogens vectored by geese are Campylobacter species, yet the current understanding of the identity and virulence of these pathogens is limited. In our previous study, we observed a high prevalence of Campylobacter spp. in the Banklick Creek wetland—a constructed treatment wetland (CTW) located in northern KY (USA) used to understand sources of fecal contamination originating from humans and waterfowl frequenting the area. To identify the types of Campylobacter spp. found contaminating the CTW, we performed genetic analyses of Campylobacter 16s ribosomal RNA amplified from CTW water samples and collected fecal material from birds frequenting those areas. Our results showed a high occurrence of a Campylobacter canadensis-like clade from the sampling sites. Whole-genome sequence analyses of an isolate from Canada goose fecal material, called MG1, were used to confirm the identity of the CTW isolates. Further, we examined the phylogenomic position, virulence gene content, and antimicrobial resistance gene profile of MG1. Lastly, we developed an MG1-specific real-time PCR assay and confirmed the presence of MG1 in Canada goose fecal samples surrounding the CTW. Our findings reveal that the Canada goose-vectored Campylobacter sp. MG1 is a novel isolate compared to C. canadensis that possesses possible zoonotic potential, which may be of human health concern.
Widespread synchrony in phosphorus concentrations in northern lakes linked to winter temperature and summer precipitation

In recent years, unexplained declines in lake total phosphorus (TP) concentrations have been observed at northern latitudes (> 42°N latitude) where most of the world's lakes are found. We compiled data from 389 lakes in Fennoscandia and eastern North America to investigate the effects of climate on lake TP concentrations. Synchrony in year‐to‐year variability is an indicator of climatic influences on lake TP, because other major influences on nutrients (e.g., land use change) are not likely to affect all lakes in the same year. We identified significant synchrony in lake TP both within and among different geographic regions. Using a bootstrapped random forest analysis, we identified winter temperature as the most important factor controlling annual TP, followed by summer precipitation. In Fennoscandia, TP was negatively correlated with the winter East Atlantic Pattern, which is associated with regionally warmer winters. Our results suggest that, in the absence of other overriding factors, lake TP and productivity may decline with continued winter warming in northern lakes.
Upper limit on flux of cosmic-ray monopoles obtained with a three-loop superconductive detector

A three-loop superconductive monopole detector has been continuously operated for over 150 days. Its sensing area is 476 cm/sup 2/ (71 cm/sup 2/ loop area and 405 cm/sup 2/ near-miss area) for double coincidence events. The data, which contain no candidate events, set an upper limit of 3.7 x 10/sup -11/ cm/sup -2/ sec/sup -1/ sr/sup -1/ (90% C.L.) for monopoles of any mass and at any velocity passing through the Earth's surface.
Machine learning prediction of progressive subclinical myocardial dysfunction in moderate aortic stenosis

Background Moderate severity aortic stenosis (AS) is poorly understood, is associated with subclinical myocardial dysfunction, and can lead to adverse outcome rates that are comparable to severe AS. Factors associated with progressive myocardial dysfunction in moderate AS are not well described. Artificial neural networks (ANNs) can identify patterns, inform clinical risk, and identify features of importance in clinical datasets. Methods We conducted ANN analyses on longitudinal echocardiographic data collected from 66 individuals with moderate AS who underwent serial echocardiography at our institution. Image phenotyping involved left ventricular global longitudinal strain (GLS) and valve stenosis severity (including energetics) analysis. ANNs were constructed using two multilayer perceptron models. The first model was developed to predict change in GLS from baseline echocardiography alone and the second to predict change in GLS using data from baseline and serial echocardiography. ANNs used a single hidden layer architecture and a 70%:30% training/testing split. Results Over a median follow-up interval of 1.3 years, change in GLS (≤ or >median change) could be predicted with accuracy rates of 95% in training and 93% in testing using ANN with inputs from baseline echocardiogram data alone (AUC: 0.997). The four most important predictive baseline features (reported as normalized % importance relative to most important feature) were peak gradient (100%), energy loss (93%), GLS (80%), and DI < 0.25 (50%). When a further model was run including inputs from both baseline and serial echocardiography (AUC 0.844), the top four features of importance were change in dimensionless index between index and follow-up studies (100%), baseline peak gradient (79%), baseline energy loss (72%), and baseline GLS (63%). Conclusions Artificial neural networks can predict progressive subclinical myocardial dysfunction with high accuracy in moderate AS and identify features of importance. Key features associated with classifying progression in subclinical myocardial dysfunction included peak gradient, dimensionless index, GLS, and hydraulic load (energy loss), suggesting that these features should be closely evaluated and monitored in AS. GRAPHICAL ABSTRACT
Asymptotic and Qualitative Performance of Non-Parametric Density Estimators: A Comparative Study

Motivated by finance applications, we assessed the performance of several univariate density estimation methods, focusing on their ability to deal with heavy-tailed target densities. Four approaches, a fixed bandwidth kernel estimator, an adaptive bandwidth kernel estimator, the Hermite series (SNP) estimator of Gallant and Nychka, and the logspline estimator of Kooperberg and Stone, are compared. We conclude that the logspline and adaptive kernel methods provide superior performance, and the convergence rate of the SNP estimator is remarkably slow compared with the other methods. The Hellinger convergence rate of the SNP estimator is derived as a function of tail heaviness. These findings are confirmed in Monte Carlo experiments. Qualitative assessment reveals the possibility that side lobes in the tails of the fixed kernel and SNP estimates are artefacts of the fitting method. Copyright The Author(s). Journal compilation Royal Economic Society 2008
Expression of cannabinoid (CB1 and CB2) and cannabinoid-related receptors (TRPV1, GPR55, and PPARα) in the synovial membrane of the horse metacarpophalangeal joint

Background The metacarpophalangeal joint undergoes enormous loading during locomotion and can therefore often become inflamed, potentially resulting in osteoarthritis (OA). There are studies indicating that the endocannabinoid system (ECS) modulates synovium homeostasis, and could be a promising target for OA therapy. Some cannabinoid receptors, which modulate proliferative and secretory responses in joint inflammation, have been functionally identified in human and animal synovial cells. Objective To characterize the cellular distribution of the cannabinoid receptors 1 (CB1R) and 2 (CB2R), and the cannabinoid-related receptors transient receptor potential vanilloid type 1 (TRPV1), G protein-related receptor 55 (GPR55) and peroxisome proliferator-activated receptor alpha (PPARα) in the synovial membrane of the metacarpophalangeal joint of the horse. Animals The dorsal synovial membranes of 14 equine metacarpophalangeal joints were collected post-mortem from an abattoir. Materials and methods The dorsal synovial membranes of 14 equine metacarpophalangeal joints were collected post-mortem from an abattoir. The expression of the CB1R, CB2R, TRPV1, GPR55, and PPARα in synovial tissues was studied using qualitative and quantitative immunofluorescence, and quantitative real-time reverse transcriptase PCR (qRT-PCR). Macrophage-like (MLS) and fibroblast-like (FLS) synoviocytes were identified by means of antibodies directed against IBA1 and vimentin, respectively. Results Both the mRNA and protein expression of the CB2R, TRPV1, GPR55, and PPARα were found in the synoviocytes and blood vessels of the metacarpophalangeal joints. The synoviocytes expressed the mRNA and protein of the CB1R in some of the horses investigated, but not in all. Conclusions and clinical importance Given the expression of the CB1R, CB2R, TRPV1, GPR55, and PPARα in the synovial elements of the metacarpophalangeal joint, these findings encouraged the development of new studies supporting the use of molecules acting on these receptors to reduce the inflammation during joint inflammation in the horse.
Differential Gene Expression Analysis of Neopyropia yezoensis (Bangiales, Rhodophyta) Mutant with High-growth and Development of SSR Marker Using RNA-seq

Neopyropia yezoensis is a type of red macroalgae that is becoming economically important owing to increasing demand. A high-growth-rate mutant, NyEMS, was recently developed using ethyl methanesulfonate to meet this demand. However, the high-growth-rate mechanisms of NyEMS have not yet been identified because of the poor understanding of N. yezoensis biomolecules. In this study, NyEMS was subjected to comparative transcriptome analysis using RNA-seq. As a result, total of 7,933 differentially expressed unigenes were identified. From the transcriptome analysis, it was demonstrated that increased proteasome expression and repressed 1- aminocyclopropane-l-carboxylate (ACC) production could be responsible for the enhanced growth rate of the mutant. Additionally, genes involved in vitamin B6 biosynthesis were up-regulated, while those related to phycobilisomes were downregulated in the mutant, which could be responsible for its characteristic features. Moreover, 1,281 SNPs and 12,963 cSSRs were identified from assembled data. To determine possible biomarkers, primer pairs were designed from the identified cDNAderived simple sequence repeats. This study expands our understanding of the genetic mechanisms of N. yezoensis for future research and will be helpful in the development of N. yezoensis biomarkers.
Relativistic shocks and particle acceleration

L'hydrodynamique des ondes de choc relativistes est etudiee et les resultats sont utilises pour calculer l'indice spectral des particules accelerees par le processus de Fermi dans ces chocs. Les distributions des particules accelerees sont calculees pour la propagation des ondes de choc dans un plasma proton-electron et positon-electron. Deux spectres de puissance differents sont consideres pour les ondes diffusantes et les resultats montrent que l'indice spectral des particules depend du spectre de puissance de l'onde
Time to Effective Ventilation in Neonatal Manikins with a Supraglottic Airway vs. a Facemask: A Randomized Controlled Trial

(1) Background: Timely and effective positive pressure ventilation (PPV) is the most important component of neonatal resuscitation. Emerging data supports the use of supraglottic airways such as the laryngeal mask airway (LMA) as a first-line interface for PPV during neonatal resuscitation. LMA use reduces the need for intubation compared to facemask use in systematic reviews, but there is no difference in the incidence of death or moderate-to-severe hypoxic ischemic encephalopathy (HIE). Time to effective ventilation during simulation with manikin models by providers with limited neonatal airway experience may add to the current evidence that compares the LMA to the neonatal facemask as the first-line ventilation interface during neonatal resuscitation. ; (2) Methods: Thirty-two pre-clinical medical students were recruited and randomized to learning and performing ventilation with either the LMA or neonatal facemask on a neonatal manikin. Tidal volume was measured by breath-by-breath analysis to assess adequacy and consistency of PPV in 10 consecutive breaths. Perceived confidence was measured by pre- and post-intervention surveys that utilized a Likert scale from 1 to 5. ; (3) Results: Median time to achieve effective ventilation was shorter with a neonatal facemask compared to the LMA (43 (30, 112) seconds vs. 82 (61, 264) seconds, p < 0.01). Participants reported higher perceived confidence post-intervention with use of a facemask when compared to use of the LMA (5 (4, 5) vs. 4 (4, 4), p = 0.03). ; (4) Conclusions: Pre-clinical medical students demonstrated a shorter time to effective ventilation and reported higher confidence scores after learning and demonstrating PPV using the facemask when compared to LMA in a neonatal manikin. Further studies are warranted to evaluate the use of supraglottic airways in providers with limited experience with airway management of neonates, as well as in ways to better promote proficiency and confidence in the use of the LMA.
Prediction Machine Learning Models on Propensity Convicts to Criminal Recidivism

Increasing internal state security requires an understanding of the factors that influence the commission of repetitive crimes (recidivism) since the crime is not caused by public danger but by the criminal person. Against the background of informatization of the information activities of law enforcement agencies, there is no doubt about the expediency of using artificial intelligence algorithms and blockchain technology to predict and prevent crimes. The prediction machine-learning models for identifying significant factors (individual characteristics of convicts), which affect the propensity to commit criminal recidivism, were applied in this article. For predicting the probability of propensity for criminal recidivism of customers of Ukrainian penitentiary institutions, a Decision Tree model was built to suggest the probability of repeated criminal offenses by convicts. It was established that the number of convictions to the actual punishment and suspended convictions is the main factors that determine the propensity of customers of penitentiary institutions to commit criminal recidivism in the future. Decision Tree models for the classification of convicts prone or not prone to recidivism were built. They can be used to predict new cases for decision-making support in criminal justice. In our further research, the possibility of using the technology of distributed registers/blockchain in predictive criminology will be analyzed.
Conversion of waste polyolefins to polyethylene wax via pyrolysis

ABSTRACT Waste polyolefins can be converted into value-added products like oils and chemical waxes by a process called pyrolysis. In the present study, conversion of waste polyethylene to polyethylene (PE) wax was carried out via pyrolysis using a ZSM 5 (zeolite based) and Luperox as catalysts. The effect of pyrolysis residence time, catalyst type, loading on the yield, and properties of the PE wax were investigated. Further, a comparison of the properties of PE wax obtained via pyrolysis and the market sample of PE wax was made to optimize the reaction conditions of pyrolysis. It was observed that with an increase in the catalyst loading and residence time, not just the yield of PE wax reduced but it also led to the degradation in the properties of PE wax. The waxes produced via pyrolysis at residence time of 90 min for waste low-density polyethylene and 150 min for waste high-density polyethylene exhibited properties comparable to that of the market sample of PE wax. The PE wax thus obtained has application in textile coatings, plastic processing, and printing inks.
Cluster Synchronization of a Nonlinear Network With Fixed and Switching Topologies

This article mainly addresses the synchronization problem of leaderless and leader–follower clusters in directed topologically coupled nonlinear systems. The relationship between nodes within each cluster is cooperative, and nodes belonging to different clusters may compete with each other. For each case of leaderless and leader-following, we consider both fixed and switching topologies. The vector field at each node satisfies the one-sided Lipschitz condition. For situations where there is no leader and leader to follow, we do not need to use the in-degree balanced condition that is often required in most existing literature. Under the leaderless framework, the cluster synchronization (CS) problem is transformed into a stability problem through variable transformation. Under the leader-following framework, by equipping each cluster with a virtual leader, we design a new class of leader-following protocols that can be used to achieve CS of coupled nonlinear systems. Finally, two numerical examples are provided to illustrate the validity of the obtained results.
Experimental validation of field cooling simulations for linear superconducting magnetic bearings

For practical stability of a superconducting magnetic bearing the refrigeration process must occur with the superconductor in the presence of the magnetic field (a field cooling (FC) process). This paper presents an experimental validation of a method for simulating this system in the FC case. Measured and simulated results for a vertical force between a high temperature superconductor and a permanent magnet rail are compared. The main purpose of this work is to consolidate a simulation tool that can help in future projects on superconducting magnetic bearings for MagLev vehicles.
Experiments on shock wave reflection transition and hysteresis in low-noise wind tunnel

Experiments on the transition between steady regular and Mach reflections of shock waves have been performed in a low-noise wind tunnel. Owing to a very low level of free-stream disturbances inherent in this facility, the hysteresis phenomenon has been observed in close agreement with theoretical predictions and results of the previous numerical simulations. When increasing the incident shock wave angle, regular reflection persists in most of the dual solution domain. Thus, the detachment criterion can be considered as a true one for the transition from regular to Mach reflection, and an earlier transition observed in many wind tunnel experiments is certainly caused by free-stream disturbances, which were present in those facilities.