Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Bioactive Compounds of Opuntia ficus-indica (L.) Mill. Seeds from Spanish Cultivars

Opuntia ficus-indica (L.) Mill. is the Cactaceae plant with the greatest economic relevance in the world. It can be used for medicinal purposes, animal nutrition, production of biofuels and phytoremediation of soils. Due to its high content of bioactive compounds, the prickly pear has antioxidant, antimicrobial and anticancer properties. The aim of this study was to determine the polyphenolic, fatty acid and amino acid profile and characterize the antioxidant capacity of seeds of seven Spanish prickly pear cultivars. A total of 21 metabolites, mainly phenolic acids and flavonols, were identified using ultraperformance liquid chromatography photodiode detector quadrupole/time-of-flight mass spectrometry (UPLC-PDA-Q/TOF-MS). Significant differences were found in the phenolic concentrations of the investigated varieties. The highest amount of phenolic compounds (266.67 mg/kg dry matter) were found in the “Nopal espinoso” variety, while the “Fresa” variety was characterized by the lowest content (34.07 mg/kg DM) of these compounds. In vitro antioxidant capacity was positively correlated with the amount of polyphenols. The amino acid composition of protein contained in prickly pear seeds was influenced by the variety. Glutamic acid was the predominant amino acid followed by arginine, aspartic acid and leucine, independent of prickly pear variety. Overall, 13 different fatty acids were identified and assessed in prickly pear seeds. The dominant fatty acid was linoleic acid, with content varying between 57.72% “Nopal ovalado” and 63.11% “Nopal espinoso”.
A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across time, subjects, frequency, or other domains. Identifying the modular structure in multilayer brain networks represents a gateway toward a deeper understanding of neural processes underlying cognition. Electroencephalographic (EEG) signals, thanks to their high temporal resolution, can give rise to multilayer networks able to follow the dynamics of brain activity. Despite this potential, the community organization has not yet been thoroughly investigated in brain networks estimated from EEG. Furthermore, at the state of the art, there is still no agreement about which algorithm is the most suitable to detect communities in multilayer brain networks, and a way to test and compare them all under a variety of conditions is lacking. In this work, we perform a comprehensive analysis of three algorithms at the state of the art for multilayer community detection (namely, genLouvain, DynMoga, and FacetNet) as compared with an approach based on the application of a single-layer clustering algorithm to each slice of the multilayer network. We test their ability to identify both steady and dynamic modular structures. We statistically evaluate their performances by means of ad hoc benchmark graphs characterized by properties covering a broad range of conditions in terms of graph density, number of clusters, noise level, and number of layers. The results of this simulation study aim to provide guidelines about the choice of the more appropriate algorithm according to the different properties of the brain network under examination. Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. The test on real data provided results in agreement with the conclusions of the simulation study and confirmed the feasibility of multilayer analysis of EEG-based brain networks in both steady and dynamic conditions.
Extensive Chemometric Investigations of Distinctive Patterns and Levels of Biogenic Amines in Fermented Foods: Human Health Implications

Although biogenic amines (BAs) present in fermented foods exert important health-promoting and physiological function support roles, their excessive ingestion can give rise to deleterious toxicological effects. Therefore, here we have screened the BA contents and supporting food quality indices of a series of fermented food products using a multianalyte-chemometrics strategy. A liquid chromatographic triple quadrupole mass spectrometric (LC-MS/MS) technique was utilized for the simultaneous multicomponent analysis of 8 different BAs, and titratable acidity, pH, total lipid content, and thiobarbituric acid-reactive substances (TBARS) values were also determined. Rigorous univariate and multivariate (MV) chemometric data analysis strategies were employed to evaluate results acquired. Almost all foods analyzed had individual and total BA contents that were within recommended limits. The chemometrics methods applied were useful for recognizing characteristic patterns of BA analytes and food quality measures between some fermented food classes, and for assessing their inter-relationships and potential metabolic sources. MV analysis of constant sum-normalized BA profile data demonstrated characteristic signatures for cheese (cadaverine only), fermented cod liver oil (2-phenylethylamine, tyramine, and tryptamine), and wine/vinegar products (putrescine, spermidine, and spermine). In conclusion, this LC-MS/MS-linked chemometrics approach was valuable for (1) contrasting and distinguishing BA catabolite signatures between differing fermented foods, and (2) exploring and evaluating the health benefits and/or possible adverse public health risks of such products.
Optical Fiber Sensors by Direct Laser Processing: A Review

The consolidation of laser micro/nano processing technologies has led to a continuous increase in the complexity of optical fiber sensors. This new avenue offers novel possibilities for advanced sensing in a wide set of application sectors and, especially in the industrial and medical fields. In this review, the most important transducing structures carried out by laser processing in optical fiber are shown. The work covers different types of fiber Bragg gratings with an emphasis in the direct-write technique and their most interesting inscription configurations. Along with gratings, cladding waveguide structures in optical fibers have reached notable importance in the development of new optical fiber transducers. That is why a detailed study is made of the different laser inscription configurations that can be adopted, as well as their current applications. Microcavities manufactured in optical fibers can be used as both optical transducer and hybrid structure to reach advanced soft-matter optical sensing approaches based on optofluidic concepts. These in-fiber cavities manufactured by femtosecond laser irradiation followed by chemical etching are promising tools for biophotonic devices. Finally, the enhanced Rayleigh backscattering fibers by femtosecond laser dots inscription are also discussed, as a consequence of the new sensing possibilities they enable.
Sparse Blind Deconvolution with Nonconvex Optimization for Ultrasonic NDT Application

In the field of ultrasonic nondestructive testing (NDT), robust and accurate detection of defects is a challenging task because of the attenuation and noising of the ultrasonic wave from the structure. For determining the reflection characteristics representing the position and amplitude of ultrasonic detection signals, sparse blind deconvolution methods have been implemented to separate overlapping echoes when the ultrasonic transducer impulse response is unknown. This letter introduces the ℓ1/ℓ2 ratio regularization function to model the deconvolution as a nonconvex optimization problem. The initialization influences the accuracy of estimation and, for this purpose, the alternating direction method of multipliers (ADMM) combined with blind gain calibration is used to find the initial approximation to the real solution, given multiple observations in a joint sparsity case. The proximal alternating linearized minimization (PALM) algorithm is embedded in the iterate solution, in which the majorize-minimize (MM) approach accelerates convergence. Compared with conventional blind deconvolution algorithms, the proposed methods demonstrate the robustness and capability of separating overlapping echoes in the context of synthetic experiments.
Neural stem cell pools in the vertebrate adult brain: Homeostasis from cell‐autonomous decisions or community rules?

Adult stem cell populations must coordinate their own maintenance with the generation of differentiated cell types to sustain organ physiology, in a spatially controlled manner and over long periods. Quantitative analyses of clonal dynamics have revealed that, in epithelia, homeostasis is achieved at the population rather than at the single stem cell level, suggesting that feedback mechanisms coordinate stem cell maintenance and progeny generation. In the central nervous system, however, little is known of the possible community processes underlying neural stem cell maintenance. Recent work, in part based on intravital imaging made possible in the adult zebrafish, conclusively highlights that homeostasis in neural stem cell pools may rely on population asymmetry and long‐term spatiotemporal coordination of neural stem cell states and fates. These results suggest that neural stem cell assemblies in the vertebrate brain behave as self‐organized systems, such that the stem cells themselves generate their own intrinsic niche.
A nickel nanoparticle/carbon quantum dot hybrid as an efficient electrocatalyst for hydrogen evolution under alkaline conditions

The exploration of an efficient electrocatalyst for hydrogen evolution reaction (HER) from water is a key to relieve the energy crisis, which is a great challenge. Herein, a nickel nanoparticle/carbon quantum dot (Ni/CQD) hybrid is synthesized and evaluated as an electrocatalyst for HER under a strongly alkaline medium (1 M KOH solution). The obtained Ni/CQD hybrid shows good catalytic ability for HER with an onset potential comparable to that of Pt wire and a low Tafel slope of 98 mV dec−1, which may be attributed to the Ni–O–C interface between Ni NPs and CQDs. The Ni/CQDs also exhibit high stability after 1000 CV cycles with negligible current loss (around 1 mA cm−2). Moreover, the catalytic ability of Ni/CQDs can be further improved under visible light illumination, suggested by a lower Tafel slope of 77 mV dec−1.
Striped Non-Uniform Corrosion Behavior of Non-Equiatomic FeMnCoCr High-Entropy Alloy Prepared by Laser Melting Deposition in 0.1 M H2SO4 Solution

The corrosion behavior of the Fe50Mn30Co10Cr10 high-entropy alloy (HEA) manufactured via laser melting deposition (LMD) was investigated using open circuit potential, potentiodynamic polarization, and electrochemical impedance spectroscopy measurements. The microstructure and morphology of LMD samples before and after the electrochemical tests were compared using X-ray diffraction, optical microscopy, scanning electron microscopy, and electron backscatter diffraction techniques. After the corrosion tests, a striped morphology was observed on the surface of the LMD HEA, which is mainly caused by the interval distribution of high-density and low-density grain-boundary regions. The corrosion performances varied with different planes of the LMD HEA sample, which is mainly controlled by the grain size at each plane. Local corrosion in this HEA is concentrated at the melt pool boundary, which may be due to the abundant metallurgical defects and stress concentration at this location.
The comparison of the survival rates of intensive and palliative care units.

Introduction Palliative care is a multidisciplinary therapy formed by physical, social, psychological, cultural and spiritual support of patients and families. The aim of the present study is to compare the survival rates of the intensive care unit (ICU) and palliative care unit (PCU). Materials and Methods A retrospective observational cohort study was performed using the database of an intensive care unit. Patients with terminal illness admitted to the intensive care unit or palliative care unit were included in the study. Demographic data, comorbidities, time of admission, discharge and death were recorded. The survival estimation was completed using Kaplan Meier survival analysis. Result A total of 112 patients were included in the study. Patients were divided into two groups where 60 patients (53.6%) were in Group ICU and 52 (46.4%) were in Group PCU. The Kaplan-Meier estimation of survival curves showed that the overall median time was 29 days. This result demonstrated that 50% of the patients was survived longer than 29 days, in which it was 12 days and 38 days for Group ICU and Group PCU, respectively (𝜒2= 3.475, p= 0.062). The cost of either intensive care unit or palliative care unit did not show any difference (p= 0.902). Conclusions The present study showed that long-term survival rates are similar in intensive care unit and palliative care unit.
Telemedicine in neurology: current evidence

ABSTRACT Background: Telemedicine was first introduced in Neurology as a tool to facilitate access to acute stroke treatment. More recently, evidence has emerged of the use of telemedicine in several other areas of Neurology. With the advent of the COVID-19 pandemic and the need for social isolation, Brazilian authorities have expanded the regulation of the use of telemedicine, thus allowing the treatment of many patients with neurological diseases to be conducted with less risk of SARS-CoV-2 contamination. Objective: This study aimed to critically review the current evidence of the use, efficacy, safety, and usefulness of telemedicine in Neurology. Methods: A review of PubMed indexed articles was carried out by searching for the terms “telemedicine AND”: “headache”, “multiple sclerosis”, “vestibular disorders”, “cerebrovascular diseases”, “epilepsy”, “neuromuscular diseases”, “dementia”, and “movement disorders”. The more relevant studies in each of these areas were critically analyzed. Results: Several articles were found and analyzed in each of these areas of Neurology. The main described contributions of telemedicine in the diagnosis and treatment of such neurological conditions were presented, indicating a great potential of use of this type of assistance in all these fields. Conclusion: Current evidence supports that teleneurology can be a tool to increase care for patients suffering from neurological diseases.
Phase Behavior and Polymorphism of Saturated and Unsaturated Phytosterol Esters

This study investigated how the physicochemical characteristics of phytosterol esters are influenced by the chain length and degree of unsaturation of the fatty acid ester moiety. Saturated and unsaturated phytosterol esters (PEs) were synthesized by the esterification of different types of fatty acids (stearic, palmitic, lauric, oleic, and linoleic acid) to β-sitosterol. The non-isothermal crystallization and melting behavior of the pure PEs were analyzed. It was proven by X-ray diffraction that saturated β-sitosteryl esters and β-sitosteryl oleate formed a bilayer crystal structure. The lamellar spacings of the bilayer structure decreased with decreasing fatty acid chain length and with an increasing degree in unsaturation. The degree of unsaturation of the fatty acid chain of the β-sitosteryl esters also influenced the type of subcell packing of the fatty acid moieties in the bilayer structure, whether or not a metastable or stable liquid crystalline phase was formed during cooling. Furthermore, it was found that the melting temperature and enthalpy of the β-sitosteryl esters increased with an increasing fatty acid chain length while they decreased with an increasing degree of unsaturation. The microscopic analyses demonstrated that β-sitosteryl oleate formed much smaller spherulites than their saturated β-sitosteryl analogues.
Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer

Prior highly-tuned image parsing models are usually studied in a certain domain with a specific set of semantic labels and can hardly be adapted into other scenarios (e.g.sharing discrepant label granularity) without extensive re-training. Learning a single universal parsing model by unifying label annotations from different domains or at various levels of granularity is a crucial but rarely addressed topic. This poses many fundamental learning challenges, e.g.discovering underlying semantic structures among different label granularity or mining label correlation across relevant tasks. To address these challenges, we propose a graph reasoning and transfer learning framework, named “Graphonomy,” which incorporates human knowledge and label taxonomy into the intermediate graph representation learning beyond local convolutions. In particular, Graphonomy learns the global and structured semantic coherency in multiple domains via semantic-aware graph reasoning and transfer, enforcing the mutual benefits of the parsing across domains (e.g.different datasets or co-related tasks). The Graphonomy includes two iterated modules: Intra-Graph Reasoning and Inter-Graph Transfer modules. The former extracts the semantic graph in each domain to improve the feature representation learning by propagating information with the graph; the latter exploits the dependencies among the graphs from different domains for bidirectional knowledge transfer. We apply Graphonomy to two relevant but different image understanding research topics: human parsing and panoptic segmentation, and show Graphonomy can handle both of them well via a standard pipeline against current state-of-the-art approaches. Moreover, some extra benefit of our framework is demonstrated, e.g., generating the human parsing at various levels of granularity by unifying annotations across different datasets.
The Potential of a Digital Twin in Surgery

Digital twins are virtual replicas of physical entities that go beyond a still image and encompass the dynamic functionality of the real-life object. They are widely used in industries such as construction and aviation. Their advent is said to mark the fourth industrial revolution for the innovation of new products and services. The concept is increasingly entering the healthcare industry with the aim of creating molecular and phenotypic copies of human beings that can allow for trialling of different therapies to elucidate the most efficacious treatment for the real-life patient. Although the literature is increasingly discussing the potential for medical specialities such as cardiology and oncology, there are few articles discussing their potential in surgical practice.
Metabolic impact of persistent organic pollutants on gut microbiota

ABSTRACT Emerging evidence supports that exposure to persistent organic pollutants (POPs) can impact the interaction between the gut microbiota and host. Recent efforts have characterized the relationship between gut microbiota and environment pollutants suggesting additional research is needed to understand potential new avenues for toxicity. Here, we systematically examined the direct effects of POPs including 2,3,7,8-tetrachlorodibenzofuran (TCDF), 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), and polychlorinated biphenyls (PCB-123 and PCB-156) on the microbiota using metatranscriptomics and NMR- and mass spectrometry-based metabolomics combined with flow cytometry and growth rate measurements (OD600). This study demonstrated that (1) POPs directly and rapidly affect isolated cecal bacterial global metabolism that is associated with significant decreases in microbial metabolic activity; (2) significant changes in cecal bacterial gene expression related to tricarboxylic acid (TCA) cycle as well as carbon metabolism, carbon fixation, pyruvate metabolism, and protein export were observed following most POP exposure; (3) six individual bacterial species show variation in lipid metabolism in response to POP exposure; and (4) PCB-153 (non-coplanar)has a greater impact on bacteria than PCB-126 (coplanar) at the metabolic and transcriptional levels. These data provide new insights into the direct role of POPs on gut microbiota and begins to establish possible microbial toxicity endpoints which may help to inform risk assessment.
New Adopters of Telemedicine During the Coronavirus-19 Pandemic in Respondents to an Online Community Survey: The Case for Access to Remote Management Tools for Individuals with Chronic Obstructive Pulmonary Disease.

Objectives To investigate telemedicine adoption, emergency room avoidance, and related characteristics of patients with chronic obstructive pulmonary disease (COPD) with and without exacerbations since the COVID-19 pandemic began. Methods We conducted the second of a series of online surveys via SurveyMonkey.com of people with COPD between May 1, 2020 and May 31, 2020. Frequency, percent, and Fisher's exact test (two-sided) were calculated using SPSS version 26. Results More than half of respondents (157, 64%), indicated that they started using telemedicine in 2020. Forty-seven percent of respondents had at least one exacerbation since January 1, 2020. Respondents who had at least one exacerbation in 2020 were more likely to start using telemedicine in 2020 than respondents who did not report any exacerbation in 2020 (75.7% versus 54.3%, p < 0.001). Respondents reporting a 2020 exacerbation indicated significantly higher avoidance of emergency healthcare since the pandemic began (27.8%) as compared to those who did not have an exacerbation in 2020 (10.1%), p < 0.001. Conclusions In response to social distancing and other COVID-19 precautions, people with COPD are avoiding traditional, in-person health care environments and turning to telemedicine to prevent and manage exacerbations. Further investigation is needed to identify best practices in and barriers to telemedicine in this population.
Sources of insoluble inclusions in stratospheric sulfate particles

Abstract– Properties of aerosol collected in the stratosphere from altitudes of 20–45 km are reviewed. Removal of the soluble material from predominantly sulfate particles collected at 20 km revealed the presence of insoluble individual particles, or small groups of them, typically 40–50 nm in diameter. The size distribution of components of chain aggregates found above 35 km was almost identical, suggesting that rupture of the chains by condensing sulfuric acid, as they fell into the sulfate layer from above, was the source of the inclusions. Particles collected above 35 km on thin films of metal all showed the presence of a partially volatile liquid. On a copper surface, the liquid was stabilized, and of greater extent than the solid component. Three observations suggest that the upper stratospheric particles and their associated liquid were partly or wholly organic and derived from cometary dust too small to be heated on entering the atmosphere. These are: (1) the presence of a liquid that reacts with copper and the similarity to the behavior of particles collected on copper during a manned space flight, (2) their morphological similarity to published photographs of particles collected in the mesosphere from rockets, (3) the consistency with recent spacecraft observations of the size distribution of components sub‐10 μm aggregates in cometary dust and the presence within them of carbon compounds.