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This paper reports the use of nanoparticles (NPs)-modified voltammetric sensors for the rapid determination of glycerol in the presence of ethanol and methanol, which are used in the transesterification reaction of biodiesel production. Two different modified electrodes have been prepared to form the electronic tongue (ET): copper hexacyanoferrate NPs obtained by chemical synthesis and mixed into graphite/epoxy (GEC) electrode, and nickel hydroxide NPs electrodeposited in reduced graphene oxide onto a GEC electrode. The response characteristics of these electrodes were first evaluated by building the respective calibration against glycerol, ethanol, and methanol. The electrodes demonstrated good stability during their analytical characterization, while principal component analysis confirmed the differentiated response against the different alcohols. Finally, the quantification of mixtures of these substances was achieved by a genetic algorithm-artificial neural networks (GA-ANNs) model, showing satisfactory agreement between expected and obtained values.

A 7-year-old farmed white-tailed deer doe was transported to a Levy County, Florida property and began to decline in health, exhibiting weight loss and pelvic limb weakness. The doe prematurely delivered live twin fawns, both of which later died. The doe was treated with corticosteroids, antibiotics, gastric cytoprotectants, and B vitamins but showed no improvement. The doe was euthanized, and a post mortem examination was performed under the University of Florida’s Cervidae Health Research Initiative. We collected lung tissue after the animal was euthanized and performed histological evaluation, using H&E and Ziehl–Neelsen (ZN) staining, and molecular evaluation, using conventional PCR, followed by Sanger sequencing. The microscopic observations of the H&E-stained lung showed multifocal granuloma, while the ZN-stained tissue revealed low numbers of beaded, magenta-staining rod bacteria inside the granuloma formation. Molecular analysis identified the presence of Mycobacterium kansasii. This isolation of a non-tuberculous Mycobacterium in a white-tailed deer emphasizes the importance of specific pathogen identification in cases of tuberculosis-like disease in farmed and free-ranging cervids. We report the first case of M. kansasii infection in a farmed white-tailed deer (Odocoileus virginianus) in Florida. Although M. kansasii cases are sporadic in white-tailed deer, it is important to maintain farm biosecurity and prevent farmed cervids from contacting wildlife to prevent disease transmission.

Aquaculture produces more than 122 million tons of fish globally. Among the several economically important species are the Serrasalmidae, which are valued for their nutritional and sensory characteristics. To meet the growing demand, there is a need for automation and accuracy of processes, at a lower cost. Convolutional neural networks (CNNs) are a viable alternative for automation, reducing human intervention, work time, errors, and production costs. Therefore, the objective of this work is to evaluate the efficacy of convolutional neural networks (CNNs) in counting round fish fingerlings (Serrasalmidae) at different densities using 390 color photographs in an illuminated environment. The photographs were submitted to two convolutional neural networks for object detection: one model was adapted from a pre-trained CNN and the other was an online platform based on AutoML. The metrics used for performance evaluation were precision (P), recall (R), accuracy (A), and F1-Score. In conclusion, convolutional neural networks (CNNs) are effective tools for detecting and counting fish. The pre-trained CNN demonstrated outstanding performance in identifying fish fingerlings, achieving accuracy, precision, and recall rates of 99% or higher, regardless of fish density. On the other hand, the AutoML exhibited reduced accuracy and recall rates as the number of fish increased.

Epilepsy represents a condition in which abnormal neuronal discharges or the hyperexcitability of neurons occur with synchronicity, presenting a significant public health challenge. Prognostic factors, such as etiology, electroencephalogram (EEG) abnormalities, the type and number of seizures before treatment, as well as the initial unsatisfactory effects of medications, are important considerations. Although there are several third-generation antiepileptic drugs currently available, their multiple side effects can negatively affect patient quality of life. The inheritance and etiology of epilepsy are complex, involving multiple underlying genetic and epigenetic mechanisms. Different neurotransmitters play crucial roles in maintaining the normal physiology of different neurons. Dysregulations in neurotransmission, due to abnormal transmitter levels or changes in their receptors, can result in seizures. In this review, we address the roles played by various neurotransmitters and their receptors in the pathophysiology of epilepsy. Furthermore, we extensively explore the neurological mechanisms involved in the development and progression of epilepsy, along with its risk factors. Furthermore, we highlight the new therapeutic targets, along with pharmacological and non-pharmacological strategies currently employed in the treatment of epileptic syndromes, including drug interventions employed in clinical trials related to epilepsy.

This work presents a simulation model developed with the aim to represent and study the thermal behavior of cyclotron liquid targets. Understanding and improving the thermal behavior of the target system is fundamental to improving the target overall performance, especially when using thick target windows, for which a larger amount of heat generated can be limiting. ANSYS CFX and SRIM software were used to develop a simulation model representing the IBA Nirta® Ga-68 liquid target system, to study the use of thick niobium target windows. The model was validated by comparing the results with experimental data obtained for the same liquid target system. In the present study, simulation results and temperature distributions of the main target components were obtained by studying the main parameters of interests, such as the initial temperature and mass flow rate of the coolants, and also distinct target windows with different thicknesses.

This work presents a simple method for determining the energy of the proton beam in biomedical cyclotrons, using no additional experimental set-up and only materials from radioisotope routine productions that are therefore available on-site. The developed method requires neither absolute efficiency calibration nor beam current measurements, thus avoiding two major sources of uncertainty. Two stacks composed of natural titanium thin foils, separated by an energy degrader of niobium, were mounted in a commercial target and irradiated. The resulting activities of 48V were assessed by a HPGe spectrometer.

The ability to treat saltwater to make it suitable for human consumption has long been sought by mankind. More than three-quarters of the earth’s surface is covered with saltwater. Although this water is important for some forms of transportation and fishing, it contains too much salt to sustain human life or agricultural activities. The current work consists of building a low-cost solar still and numerically modeling this device to predict the performance of the solar still without using any experimental measurements. The simulated results were compared with the best experimental values obtained from the water-covering temperatures and desalinated water yield under Brazilian climatic conditions (coordinates: 23°26′31.344″ S and 46°27′27.468″ W). The simulation results were in acceptable agreement with the experimental data. The main results obtained indicate that the solar still has greater efficiency when the volume of water is smaller inside the equipment owing to the lower height of the water and when the global radiation has greater intensity. In addition, numerical modeling allows the analysis of the behavior of the volume fraction over time for water and vapor and indicates better performance in water production after 30 min.

Citrus canker, caused by the bacterium Xanthomonas citri (Xcc), is one of the most devastating diseases for the citrus industry. Xylose is a constituent of the cell wall of plants, and the ability of Xcc to use this carbohydrate may play a role in virulence. Xcc has two genes codifying for xylose isomerase (XI), a bifunctional enzyme that interconverts D-xylose into D-xylulose and D-glucose into D-fructose. The aim of this work was to investigate the functional role of the two putative XI ORFs, XAC1776 (xylA1) and XAC4225 (xylA2), in Xcc pathogenicity. XI-coding genes of Xcc were deleted, and the single mutants (XccΔxylA1 or XccΔxylA2) or the double mutant (XccΔxylA1ΔxylA2) remained viable. The deletion of one or both XI genes (xylA1 and/or xylA2) increased the aggressiveness of the mutants, causing disease symptoms. RT-qPCR analysis of wild strain and xylA deletion mutants grown in vivo and in vitro revealed that the highest expression level of hrpX and xylR was observed in vivo for the double mutant. The results indicate that XI depletion increases the expression of the hrp regulatory genes in Xcc. We concluded that the intracellular accumulation of xylose enhances Xcc virulence.

Drug repurposing is becoming interesting in terms of offering advantages over the traditional drug development, once drug discovery is a costly, time-consuming, and highly risky process. In particular, with the coronavirus disease (COVID-19) declared by World Health Organization as a global pandemic, there has emerged a considerable need to develop therapeutic agents capable of preventing viral outbreaks. Concomitantly, well-known and long-used drugs such as acyclovir (Acv) have been tested against COVID-19. Acv is a guanosine analogue that acts as an antiviral drug, commonly used to treat herpes simplex virus (HSV), genital herpes, and varicella zoster virus (VZV). Acv showed to inhibit viral proteases, multiple viral genes expression, and RNA-Dependent RNA Polymerase, helping to recover COVID-19 patients. However, ACV is a BCS class III/IV drug, with low permeability and/or slight water solubility (concentration-dependent). Given the repurposing eligibility of Acv, in this work, two new salts of this drug are presented (nitrate and sulfate), with the aim of improving its pharmacokinetic properties. The new salts were evaluated by X-ray diffraction, and thermal and spectroscopic analyses. A third salt, a chloride one, was also characterized and used for comparison.

The importance of neuroinflammation in neurology is becoming increasingly apparent. In addition to neuroinflammatory diseases such as multiple sclerosis, the role of neuroinflammation has been identified in many non-inflammatory neurological disorders such as stroke, epilepsy, and cancer. The immune response within the brain involves the presence of CNS resident cells; mainly glial cells, such as microglia, the CNS resident macrophages. We evaluated the peptide Ca-MAP1 bioinspired on the C. albicans immature cytolytic toxin candidalysin to develop a less hemolytic peptide with anti-neuroinflammatory, antibacterial, and cytotoxic activity against tumor cells. In silico and in vitro studies were performed at various concentrations. Ca-MAP1 exhibits low hemolytic activity at lower concentrations and was not cytotoxic to MRC-5 and BV-2 cells. Ca-MAP1 showed activity against Acinetobacter baumannii, Escherichia coli ATCC, E. coli KPC, Klebsiella pneumoniae ATCC, Pseudomonas aeruginosa, and Staphylococcus aureus ATCC. Furthermore, Ca-MAP1 exhibits anti-neuroinflammatory activity in the BV-2 microglia model, with 93.78% inhibition of nitrate production at 18.1 µM. Ca-MAP1 presents cytotoxic activity against tumor cell line NCI-H292 at 36.3 μM, with an IC50 of 38.4 µM. Ca-MAP1 demonstrates results that qualify it to be evaluated in the next steps to promote the control of infections and provide an alternative antitumor therapy.

Nature presents a wide range of biomolecules with pharmacological potential, including venomous animal proteins. Among the protein components from snake venoms, phospholipases (PLA2) are of great importance for the development of new anticancer compounds. Thus, we aimed to evaluate the PLA2 anticancer properties from Bothrops moojeni venom. The crude venom was purified through three chromatographic steps, monitored by enzymatic activity and SDS-PAGE (12%). The purified PLA2 denominated BmPLA2 had its molecular mass and N-terminal sequence identified by mass spectrometry and Edman degradation, respectively. BmPLA2 was assayed against human epithelial colorectal adenocarcinoma cells (Caco-2), human rhabdomyosarcoma cells (RD) and mucoepidermoid carcinoma of the lung (NCI-H292), using human fibroblast cells (MRC-5) and microglia cells (BV-2) as a cytotoxicity control. BmPLA2 presented 13,836 Da and a 24 amino acid-residue homologue with snake PLA2, which showed a 90% similarity with other Bothrops moojeni PLA2. BmPLA2 displayed an IC50 of 0.6 µM against Caco-2, and demonstrated a selectivity index of 1.85 (compared to MRC-5) and 6.33 (compared to BV-2), supporting its selectivity for cancer cells. In conclusion, we describe a new acidic phospholipase, which showed antitumor activity and is a potential candidate in the development of new biotechnological tools.

In June 2019, a horse with neurological disorder was diagnosed with West Nile virus (WNV) in Boa Viagem, a municipality in the state of Ceará, northeast Brazil. A multi-institutional task force coordinated by the Brazilian Ministry of Health was deployed to the area for case investigation. A total of 513 biological samples from 78 humans, 157 domestic animals and 278 free-ranging wild birds, as well as 853 adult mosquitoes of 22 species were tested for WNV by highly specific serological and/or molecular tests. No active circulation of WNV was detected in vertebrates or mosquitoes by molecular methods. Previous exposure to WNV was confirmed by seroconversion in domestic birds and by the detection of specific neutralizing antibodies in 44% (11/25) of equids, 20.9% (14/67) of domestic birds, 4.7% (13/278) of free-ranging wild birds, 2.6% (2/78) of humans, and 1.5% (1/65) of small ruminants. Results indicate that not only equines but also humans and different species of domestic animals and wild birds were locally exposed to WNV. The detection of neutralizing antibodies for WNV in free-ranging individuals of abundant passerine species suggests that birds commonly found in the region may have been involved as amplifying hosts in local transmission cycles of WNV.

Food production to meet human demand has been a challenge to society. Nowadays, one of the main sources of feeding is soybean. Considering agriculture food crops, soybean is sixth by production volume and the fourth by both production area and economic value. The grain can be used directly to human consumption, but it is highly used as a source of protein for animal production that corresponds 75% of the total, or as oil and derived food products. Brazil and the US are the most important players responsible for more than 70% of world production. Therefore, a reliable forecasting is essential for decision-makers to plan adequate policies to this important commodity and to establish the necessary logistical resources. In this sense, this study aims to predict soybean harvest area, yield, and production using Artificial Neural Networks (ANN) and compare with classical methods of Time Series Analysis. To this end, we collected data from a time series (1961–2016) regarding soybean production in Brazil. The results reveal that ANN is the best approach to predict soybean harvest area and production while classical linear function remains more effective to predict soybean yield. Moreover, ANN presents as a reliable model to predict time series and can help the stakeholders to anticipate the world soybean offer.

This paper presents the development of a peak-shaving equipment, composed by a multilevel converter in a cascaded H-bridge topology and battery banks on the DC links. Between specific time periods, when the demand is higher, the equipment injects active power from the batteries into the grid to provide support to the system. During the other times of the day, when the demand is lower, the converter charges its battery banks with the exceeding (and low producing cost) energy from the grid. The charge and discharge control algorithms are implemented in a digital signal processor (DSP). The precise time of the day information is obtained from a real-time-clock from a global positioning system module (GPS), which communicates with the DSP through the serial interface. This paper presents the control algorithms and experimental results obtained in a 24 h continuous operation of the equipment.

The present work describes an experimental system enabling temperature measurement in cyclotron targets’ cooling water during bombardment. The developed system provides sensible and immediate response to variations of irradiation conditions during bombardment and enables quantification of the temperature rise in the cooling water due to beam interaction with the irradiated target and with its collimator. Such a system finds application either as a monitoring safety device to instantaneously detect and register abnormal alterations in target conditions to anticipate thermal-related incidents and as a tool to experimentally validate cyclotron targetry optimization studies and thermal simulations.