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A new species belonging to the genus Vehilius Godman, 1900, Vehilius jabre Medeiros, Souza & Kerpel sp. nov., endemic to the Caatinga biome, northeastern Brazil, is here described based on data from adult and immature stages. Information about the biology, hostplant, distribution, and adult and larval behavior of the new species is provided. The new species is morphologically similar to Vehilius warreni (Weeks, 1901), but can be distinguished by a set of characters on wings and male and female genitalia. Adults and genitalia for both sexes of V. jabre sp. nov. and V. warreni are illustrated and compared.

The sanitary quality of seed is essential in agriculture. This is because pathogenic fungi compromise seed physiological quality and prevent the formation of plants in the field, which causes losses to farmers. Multispectral images technologies coupled with machine learning algorithms can optimize the identification of healthy peanut seeds, greatly improving the sanitary quality. The objective was to verify whether multispectral images technologies and artificial intelligence tools are effective for discriminating pathogenic fungi in tropical peanut seeds. For this purpose, dry peanut seeds infected by fungi ( A. flavus , A. niger , Penicillium sp., and Rhizopus sp.) were used to acquire images at different wavelengths (365 to 970 nm). Multispectral markers of peanut seed health quality were found. The incubation period of 216 h was the one that most contributed to discriminating healthy seeds from those containing fungi through multispectral images. Texture (Percent Run), color (CIELab L *) and reflectance (490 nm) were highly effective in discriminating the sanitary quality of peanut seeds. Machine learning algorithms (LDA, MLP, RF, and SVM) demonstrated high accuracy in autonomous detection of seed health status (90 to 100%). Thus, multispectral images coupled with machine learning algorithms are effective for screening peanut seeds with superior sanitary quality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Sudki, Fonseca de Oliveira, de Medeiros, Mastrangelo, Arthur, Amaral da Silva and Mastrangelo.)

Background: F abry disease (FD) is an X-linked lysosomal storage disorder with accumulation of globotriosylceramide, causing neurologic involvement mainly as acroparesthesias and cerebrovascular disease. Aseptic meningitis has been reported in 11 patients with FD, but no prior study has correlated alpha-galactosidase (GLA) specific variants with meningitis. We present in this manuscript a family in which a novel GLA pathogenic variant was associated with aseptic meningitis in 2 of 5 family members., Methods: This study began with identifying the proband, then screening family members for FD symptoms and evaluating symptomatic individuals for genetic and biochemical status. All patients underwent magnetic resonance imaging, and those with headache underwent cerebrospinal fluid (CSF) analysis., Results: Five patients (3 females) from a single family were included in this study. Mean age at diagnosis was 20.6 years. Two patients (40%) had aseptic meningitis; one of them also had cerebrovascular events. C-reactive protein and erythrocyte sedimentation rate were elevated during aseptic meningitis episodes. Both patients responded to intravenous methylprednisolone with resolution of fever, headache, and vomiting. One of them recurred and needed chronic immunosuppression with azathioprine., Conclusion: We described aseptic meningitis in a family with a novel GLA variant. Meningitis might be a common phenomenon in FD and not a particularity of this variant. Understanding the mechanisms underlying meningitis and its association with cerebrovascular events may lead to a new paradigm of treatment for stroke in these patients. Further prospective studies with CSF collection in patients with FD and recurrent headache could help to elucidate this question., (© 2022. Fondazione Società Italiana di Neurologia.)

In recent years, technological innovations have allowed significant advances in the diagnosis of seed quality. Seeds with superior physiological quality are those with the highest level of physiological maturity and the integration of rapid and precise methods to separate them contributes to better performance in the field. Autofluorescence-spectral imaging is an innovative technique based on fluorescence signals from fluorophores present in seed tissues, which have biological implications for seed quality. Thus, through this technique, it would be possible to classify seeds in different maturation stages. To test this, we produced plants of a commercial cultivar (MG/BR 46 "Conquista") and collected the seeds at five reproductive (R) stages: R7.1 (beginning of maturity), R7.2 (mass maturity), R7.3 (seed disconnected from the mother plant), R8 (harvest point), and R9 (final maturity). Autofluorescence signals were extracted from images captured at different excitation/emission combinations. In parallel, we investigated physical parameters, germination, vigor and the dynamics of pigments in seeds from different maturation stages. To verify the accuracy in predicting the seed maturation stages based on autofluorescence-spectral imaging, we created machine learning models based on three algorithms: (i) random forest, (ii) neural network, and (iii) support vector machine. Here, we reported the unprecedented use of the autofluorescence-spectral technique to classify the maturation stages of soybean seeds, especially using the excitation/emission combination of chlorophyll a (660/700 nm) and b (405/600 nm). Taken together, the machine learning algorithms showed high performance segmenting the different stages of seed maturation. In summary, our results demonstrated that the maturation stages of soybean seeds have their autofluorescence-spectral identity in the wavelengths of chlorophylls, which allows the use of this technique as a marker of seed maturity and superior physiological quality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Batista, Mastrangelo, de Medeiros, Petronilio, Fonseca de Oliveira, dos Santos, Crusciol and Amaral da Silva.)

In the agricultural industry, advances in optical imaging technologies based on rapid and non-destructive approaches have contributed to increase food production for the growing population. The present study employed autofluorescence-spectral imaging and machine learning algorithms to develop distinct models for classification of soybean seeds differing in physiological quality after artificial aging. Autofluorescence signals from the 365/400 nm excitation-emission combination (that exhibited a perfect correlation with the total phenols in the embryo) were efficiently able to segregate treatments. Furthermore, it was also possible to demonstrate a strong correlation between autofluorescence-spectral data and several quality indicators, such as early germination and seed tolerance to stressful conditions. The machine learning models developed based on artificial neural network, support vector machine or linear discriminant analysis showed high performance (0.99 accuracy) for classifying seeds with different quality levels. Taken together, our study shows that the physiological potential of soybean seeds is reduced accompanied by changes in the concentration and, probably in the structure of autofluorescent compounds. In addition, altering the autofluorescent properties in seeds impact the photosynthesis apparatus in seedlings. From the practical point of view, autofluorescence-based imaging can be used to check modifications in the optical properties of soybean seed tissues and to consistently discriminate high-and low-vigor seeds., (© 2021. The Author(s).)

Spectroscopy and machine learning (ML) algorithms have provided significant advances to the modern food industry. Instruments focusing on near-infrared spectroscopy allow obtaining information about seed and grain chemical composition, which can be related to changes caused by field pesticides. We investigated the potential of FT-NIR spectroscopy combined with Linear Discriminant Analysis (LDA) to discriminate chickpea seeds produced using different desiccant herbicides at harvest anticipation. Five herbicides applied at three moments of the plant reproductive stage were utilized. The NIR spectra obtained from individual seeds were used to build ML models based on LDA algorithm. The models developed to identify the herbicide and the plant phenological stage at which it was applied reached 94% in the independent validation set. Thus, the LDA models developed using near-infrared spectral data provided to be efficient, quick, non-destructive, and accurate to identify differences between seeds due to pre-harvest herbicides application., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The South American genus Panca Evans, 1955 and its respective species are revised. Previous to this study, the genus included solely its type species, Lerodea subpunctuli Hayward, 1934, until Panca moseri Dolibaina, Carneiro O. Mielke, 2017 was described recently. However, as a result of a broader morphological study including closely related genera, we here propose that Panca assembles 12 species, most of which inhabit open environments such as the Cerrado biome and the natural grasslands of the Atlantic Forest biome. Eight species formerly included among other genera of Moncina are here combined with Panca: Panca satyr (Evans, 1955) comb. nov., Panca tobiasi (Mielke, 1992) comb. nov., Panca trogon (Evans, 1955) comb. nov., Panca steinhauseri (Dolibaina A. Warren, 2015) comb. nov., Panca acroleuca (Plötz, 1884) comb. nov., and Panca mirnae (O. Mielke, Dolibaina, Carneiro A. Warren, 2015) comb. nov. (all formerly in Artines Godman, 1901), Panca paulo (Bell, 1932) comb. nov. (formerly in Eutocus Godman, 1901), and Panca mictra (Evans, 1955) comb. nov. (formerly in Vidius Evans, 1955). Additionally, two new species are described from Brazil: Panca puri Medeiros, O. Mielke Casagrande sp. nov. (from Pará, Pernambuco, Minas Gerais, Rio de Janeiro and Paraná) and Panca xavante Medeiros, O. Mielke Dolibaina sp. nov. (from Mato Grosso, Goiás, Distrito Federal and Minas Gerais). A neotype for Apaustus acroleuca Plötz, 1884 is designated. Illustrations of the male and female genitalia and distribution maps are presented for all the species of Panca and an identification key is provided for both sexes.

New computer vision solutions combined with artificial intelligence algorithms can help recognize patterns in biological images, reducing subjectivity and optimizing the analysis process. The aim of this study was to propose an approach based on interactive and traditional machine learning methods to classify soybean seeds and seedlings according to their appearance and physiological potential. In addition, we correlated the appearance of seeds to their physiological performance. Images of soybean seeds and seedlings were used to develop models using low-cost approaches and free-access software. The models developed showed high performance, with overall accuracy reaching 0.94 for seeds and seedling classification. The high precision of the models that were developed based on interactive and traditional machine learning demonstrated that the method can easily be used to classify soybean seeds according to their appearance, as well as to classify soybean seedling vigor quickly and non-subjectively. The appearance of soybean seeds is strongly correlated with their physiological performance.

Conventional methods for detecting seed-borne fungi are laborious and time-consuming, requiring specialized analysts for characterization of pathogenic fungi on seed. Multispectral imaging (MSI) combined with machine vision was used as an alternative method to detect Drechslera avenae (Eidam) Sharif [ Helminthosporium avenae (Eidam)] in black oat seeds ( Avena strigosa Schreb). The seeds were inoculated with Drechslera avenae ( D. avenae ) and then incubated for 24, 72 and 120 h. Multispectral images of non-infested and infested seeds were acquired at 19 wavelengths within the spectral range of 365 to 970 nm. A classification model based on linear discriminant analysis (LDA) was created using reflectance, color, and texture features of the seed images. The model developed showed high performance of MSI in detecting D. avenae in black oat seeds, particularly using color and texture features from seeds incubated for 120 h, with an accuracy of 0.86 in independent validation. The high precision of the classifier showed that the method using images captured in the Ultraviolet A region (365 nm) could be easily used to classify black oat seeds according to their health status, and results can be achieved more rapidly and effectively compared to conventional methods.

Two new species of Alychna Grishin, 2019, Alychna chulumani Medeiros, Dolibaina O. Mielke sp. nov. from Bolivia (La Paz, Chulumani) and Alychna argenteus Medeiros, Dolibaina Casagrande sp. nov. from Peru (Huánuco, Carpish) are described. Illustrations of the wing pattern, forewing stigma and male genitalia of the two species are provided.

New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality.

The genus Tarmia Lindsey, 1925, long considered a junior synonym of Phanes Godman, 1901, is here revised and its status is revalidated based on morphological evidence. Two Andean species are included in Tarmia: the type species, T. monastica Lindsey, 1925 comb. rev., and a new species herein described, Tarmia greeneyi A. Warren, Medeiros, Dolibaina O. Mielke sp. nov., from Ecuador, Peru and Bolivia. The male's symmetrical valvae and aedeagus with a twisted median portion, and the very wide ductus bursae of the female genitalia support Tarmia as valid genus apart of Phanes. Illustrations of the main diagnostic characters of both sexes and a distribution map are provided for the species of Tarmia.

The genus Artines Godman, 1901 and its respective species are revised. The results shows that Artines consists of 15 species distributed from Mexico to Bolivia, Paraguay, southern Brazil and northern Argentina. Nine new species are described: Artines panama Medeiros Carneiro sp. nov. from Panama, Artines solange Medeiros O. Mielke sp. nov. from Brazil (Maranhão), Artines delfos Medeiros Casagrande sp. nov. from Brazil (Amazonas), Artines litoralis Medeiros Dolibaina sp. nov. from Brazil (from Paraíba to Espírito Santo), Artines liege Medeiros, O. Mielke Casagrande sp. nov. from Brazil (central region of Brazil, from Pará to Paraná), Argentina (Misiones) and Paraguay (Alto Paraná), Artines bamba Medeiros O. Mielke sp. nov. from Brazil (Acre and Amazonas) and Peru (San Martin and Madre de Díos), Artines angelica Medeiros sp. nov. from Brazil (Acre, Pará, Maranhão and Mato Grosso), Peru (Madre de Díos) and Bolivia (La Paz), Artines cofus Medeiros Dolibaina sp. nov. from Brazil (Acre and Rondônia) and Peru (Madre de Díos and San Martin) and Artines donia Medeiros Carneiro sp. nov. from Brazil (Rondônia and Goiás). A neotype for Thracides aepitus Geyer, 1832 and a lectotype for Artines atizies Godman, 1901 are designated. Genitalia of both sexes are illustrated and distribution maps for all species are provided. The females of Artines aepitus (Geyer, 1832), Artines focus Evans, 1955 and Artines aquilina (Plötz, 1882) are illustrated for the first time. An identification key is provided for males.

Purpose: To evaluate the effects and mechanisms of andiroba-based emulsion (ABE) topical treatment on full-thickness cutaneous wounds in rats., Methods: The wounds were harvested on days 3, 7, 15, and 20 post-surgery. Wound contraction rate, quantitative immunohistochemistry [macrophages, myofibroblasts, capillaries, collagens (col) I and III, transforming growth factor β3β (TGFβ3)], and tensile strength were assessed., Results: Treated wounds were smaller, contracted earlier and had increased angiogenesis, fewer CD68+ and M2 macrophages on days 7 and 15, but higher on day 20. Myofibroblasts appeared on days 3 to 7 in untreated wounds and on days 7 to 15 in treated wounds. TGFβ3 levels were higher in the treated wounds, less dense collagen fibers, lower col I/III ratios and a higher tensile strength., Conclusion: These results demonstrate the important anti-inflammatory role of treatment and the associated modulation of macrophages, myofibroblasts, and TGFβ3 levels. Collagen fibers in the treated wounds were more organized and less dense, similar to unwounded skin, which likely contributed to the higher tensile strength.

Toxoplasmosis is caused by Toxoplasma gondii, which is the main causative agent of abortion in small ruminants. Goats are among the animals that are most susceptible to this protozoon, and the disease that it causes leads to significant economic losses and has implications for public health, since presence of the parasite in products of goat origin is one of the main sources of human infection. Because of the significant economic impact, there is an urgent need to study the prevalence of T. gondii infection among goats in Sertão do Cabugi, which is the largest goat-producing region in Rio Grande do Norte. In the present study, the ELISA assay was used to test 244 serum samples from nine farms, located in four different municipalities in the Sertão do Cabugi region, which is an important goat-rearing region. The results showed that the prevalence of anti-T. gondii antibodies was 47.1% and that there was a significant association between positivity and the variables of age (≥ 34 months), location (Lajes, Angicos and Afonso Bezerra) and farm (all the farms). The avidity test was applied to all the 115 ELISA-positive samples to distinguish between acute and chronic infection. One hundred and three samples (89.6%) displayed high-avidity antibodies, thus indicating that most of the animals presented chronic infection, with a consequent great impact on the development of the goat production system and a risk to human health.

Serum samples of 930 sheep were tested by ELISA to assess the prevalence of anti-Toxoplasma gondii antibodies and to identify risk factors associated with the presence of toxoplasmosis in two regions of Rio Grande do Norte (Northeast Brazil), with different climatic conditions. The overall estimated prevalence was 22.1%, with 26.3% and 17.8% positive sheep in Leste Potiguar and Central Potiguar regions, respectively. Among the positive sheep, 18.1% had low-avidity IgG antibodies, suggesting the occurrence of recent toxoplasmosis. The risk factors for toxoplasmosis in sheep were: presence of cats (odds ratio (OR) = 1.55; confidence interval (CI) 95% = 1.11-2.16), age of the animals, with adults presenting a greater chance of infection (OR = 2.44; CI 95% = 1.58-3.75), and the use of running water (OR = 1.61; CI 95% = 1.25-2.09), characterizing the existence of transmission by sporulated oocysts of T. gondii in the environment., (© M.M.C. Andrade et al., published by EDP Sciences, 2013.)

Objectives: To estimate the proportion of individuals seronegative for measles antibody among blood donors from a blood bank in the city of Rio de Janeiro, Brazil, and to describe their social and demographic characteristics, with the goal of exploring the potential use of plasma banks to supplement serological surveillance with relevant data in order to support the program of measles elimination in the city of Rio de Janeiro and elsewhere., Methods: Plasma samples from 1 101 consecutive blood donations made in November 2000 at HEMORIO, the largest blood bank in the state of Rio de Janeiro, were tested for measles immunoglobulin G, using a commercial enzyme immunoassay and a plaque reduction neutralization test. We calculated the proportion (and 95% confidence interval (CI)) of samples seronegative for measles antibody for the total sample of blood donors and also for subgroups categorized by age, sex, neighborhood of residence, education, and occupation. We used the chi-square test to assess the statistical significance of differences in proportions and linear trends in proportions., Results: Of the total group of blood donors, 6.9% of them (95% CI: 5.4%-8.4%) were seronegative for measles. Women had a higher proportion (10.1%; 95% CI: 6.8%-13.4%) of seronegative results than did men (5.6%; 95% CI: 4.0%-7.2%). In terms of age, 86.8% of seronegative individuals were born between 1971 and 1982. Seronegativity was inversely proportional to age (chi-square = 58.0; P < 0.0001). With regard to occupation, students had the highest proportion of seronegative individuals (17.8%). In terms of education, most of the susceptible persons were in the categories of "incomplete university degree" or "incomplete high school." For the various areas of residence the proportions ranged from 2.1% to 11.4%., Conclusions: Blood bank plasma may constitute a useful and convenient source of complementary data for serological surveillance in adults of measles and other infections for which immunization and surveillance activities are implemented. This approach could be beneficial to other areas in Brazil and other countries where plasma from blood donors is available for surveillance. The use of residual sera from patients and plasma from blood donors represents a tradeoff between representativeness and timeliness as well as economy of resources.