Imaging Features and Complications of Facial Cosmetic Procedures.

Facial aesthetic procedures have become increasingly popular and complex, making knowledge of facial anatomy crucial for achieving desired outcomes without complications. Some of the most common procedures include blepharoplasty, bichectomy, face-lifts, facial implants, thread lifting, and fillers. Blepharoplasty and bichectomy are surgical procedures that respectively aim to restore youthful contours to the periorbita and create a slimmer lower face by removing Bichat fat from the maxillofacial region. Facial implants are used for aesthetic augmentation of the skeletal structure and restoration of facial contour by using biomaterials or autogenous bone grafts. Face-lift surgeries involve incisions and removal of excess skin, and thread lifts involve less invasive procedures performed by inserting threads beneath the skin, with the aim to lift the skin and thus reduce wrinkles and sagging. Fillers improve wrinkles and loss of facial volume, with biologic types made from animal, human, or bacterial sources (such as hyaluronic acid), while synthetic fillers include substances such as paraffin, silicone, calcium hydroxyapatite, polymethylmethacrylate microspheres, polyacrylamide hydrogel, hydroxyethyl-ethyl methacrylate, and poly-l-lactic acid. Synthetic fillers can be classified as rapidly resorbable (<12 months), slowly resorbable (<24 months), or permanent. Imaging modalities such as US, CT, and MRI can help identify and analyze each type of facial aesthetic procedure or filler, as well as their possible complications such as foreign-body granuloma, noninflammatory nodule, late intermittent persistent edema, filler migration, infection, or complications after removal of the buccal fat pad. ©RSNA, 2023 Quiz questions for this article are available through the Online Learning Center The online slide presentation from the RSNA Annual Meeting is available for this article.

Boundary-aware glomerulus segmentation: Toward one-to-many stain generalization.

The growing availability of scanned whole-slide images (WSIs) has allowed nephropathology to open new possibilities for medical decision-making over high-resolution images. Diagnosis of renal WSIs includes locating and identifying specific structures in the tissue. Considering the glomerulus as one of the first structures analyzed by pathologists, we propose here a novel convolutional neural network for glomerulus segmentation. Our end-to-end network, named DS-FNet, combines the strengths of semantic segmentation and semantic boundary detection networks via an attention-aware mechanism. Although we trained the proposed network on periodic acid-Schiff (PAS)-stained WSIs, we found that our network was capable to segment glomeruli on WSIs stained with different techniques, such as periodic acid-methenamine silver (PAMS), hematoxylin-eosin (HE), and Masson trichrome (TRI). To assess the performance of the proposed method, we used three public data sets: HuBMAP (available in a Kaggle competition), a subset of the NEPTUNE data set, and a novel challenging data set, called WSI_Fiocruz. We compared the DS-FNet with six other deep learning networks: original U-Net, our attention version of U-Net called AU-Net, U-Net++, U-Net3Plus, ResU-Net, and DeepLabV3+. Results showed that DS-FNet achieved equivalent or superior results on all data sets: On the HuBMAP data set, it reached a dice score (DSC) of 95.05%, very close to the first place (95.15%); on the NEPTUNE and WSI_Fiocruz data sets, DS-FNet obtained the highest average DSC, whether on PAS-stained images or images stained with other techniques. To the best we know, this is the first work to show consistently high performance in a one-to-many-stain glomerulus segmentation following a thorough protocol on data sets from different medical labs.

Neurological imaging findings in hospitalized COVID-19 patients: a retrospective observational study in two Brazilian reference centers / Achados de neuroimagem em pacientes hospitalizados por COVID-19: um estudo retrospectivo e observacional em dois serviços brasileiros de referência

ABSTRACT Background: A variety of neurological manifestations have been attributed to COVID-19. Objective: To investigate the occurrence of neurological symptoms and neuroimaging findings in patients hospitalized in two Brazilian reference centers. Methods: We performed a retrospective cohort study of patients who had laboratory-confirmed COVID-19 presenting in two hospitals in Brazil between March 4 and July 7, 2020, who underwent brain imaging. Results: We recorded 1,359 patients with laboratory-confirmed COVID-19. Brain imaging was performed in 250 (18.4%) patients with neurological symptoms, and nine of them (3.6%) had acute or subacute ischemic stroke neuroimaging findings. Six of the nine patients initially presented with respiratory symptoms while the other three patients presented to the emergency room with acute stroke signs. Conclusions: We described the neuroimaging findings of patients infected with COVID-19 who presented with neurological symptoms in two major hospitals in Brazil. We reinforce the importance of being aware of cerebrovascular complications, both in severe hospitalized patients and in patients who present to the emergency room with acute neurological symptoms, even in the elderly.

RESUMO Introdução: Diversas manifestações neurológicas têm sido atribuídas à COVID-19. Objetivo: Investigar a ocorrência de sintomas neurológicos e achados de neuroimagem em pacientes internados em dois centros de referência brasileiros. Métodos: Estudo retrospectivo que avaliou pacientes internados em dois hospitais no Brasil entre 4 de março e 7 de julho de 2020, com confirmação laboratorial de infecção pelo COVID-19 e que foram submetidos a tomografia computadorizada ou ressonância magnética do crânio em razão de sintomas neurológicos. Resultados: Obtivemos 1.359 pacientes com confirmação laboratorial de infecção pelo COVID-19. Deles, 250 (18,4%) apresentaram sintomas neurológicos e foram submetidos a exames de imagem do crânio e nove (3,6%) demonstraram achados de neuroimagem compatíveis com acidente vascular cerebral (AVC) isquêmico agudo ou subagudo. Em seis dos nove pacientes, observaram-se inicialmente tosse e dispneia graves, enquanto outros três chegaram ao pronto-socorro com sinais de AVC agudo. Conclusões: Foram descritos os achados de neuroimagem em pacientes infectados com COVID-19 em dois grandes centros de referência brasileiros. Reforçamos a importância de estar atento aos quadros neurológicos, especialmente de AVC, tanto em pacientes graves hospitalizados quanto em pacientes que chegam ao pronto-socorro com sintomas neurológicos agudos, mesmo em idosos.

Neurological imaging findings in hospitalized COVID-19 patients: a retrospective observational study in two Brazilian reference centers.

BACKGROUND: A variety of neurological manifestations have been attributed to COVID-19. OBJECTIVE: To investigate the occurrence of neurological symptoms and neuroimaging findings in patients hospitalized in two Brazilian reference centers. METHODS: We performed a retrospective cohort study of patients who had laboratory-confirmed COVID-19 presenting in two hospitals in Brazil between March 4 and July 7, 2020, who underwent brain imaging. RESULTS: We recorded 1,359 patients with laboratory-confirmed COVID-19. Brain imaging was performed in 250 (18.4%) patients with neurological symptoms, and nine of them (3.6%) had acute or subacute ischemic stroke neuroimaging findings. Six of the nine patients initially presented with respiratory symptoms while the other three patients presented to the emergency room with acute stroke signs. CONCLUSIONS: We described the neuroimaging findings of patients infected with COVID-19 who presented with neurological symptoms in two major hospitals in Brazil. We reinforce the importance of being aware of cerebrovascular complications, both in severe hospitalized patients and in patients who present to the emergency room with acute neurological symptoms, even in the elderly.

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration capability, leading to protein loss and metabolic waste retention. An example of lesion is the glomerular hypercellularity, which is characterized by an increase in the number of cell nuclei in different areas of the glomeruli. Glomerular hypercellularity is a frequent lesion present in different kidney diseases. Automatic detection of glomerular hypercellularity would accelerate the screening of scanned histological slides for the lesion, enhancing clinical diagnosis. Having this in mind, we propose a new approach for classification of hypercellularity in human kidney images. Our proposed method introduces a novel architecture of a convolutional neural network (CNN) along with a support vector machine, achieving near perfect average results on FIOCRUZ data set in a binary classification (lesion or normal). Additionally, classification of hypercellularity sub-lesions was also evaluated, considering mesangial, endocapilar and both lesions, reaching an average accuracy of 82%. Either in binary task or in the multi-classification one, our proposed method outperformed Xception, ResNet50 and InceptionV3 networks, as well as a traditional handcrafted-based method. To the best of our knowledge, this is the first study on deep learning over a data set of glomerular hypercellularity images of human kidney.

Pharmacophore modeling, docking and molecular dynamics to identify Leishmania major farnesyl pyrophosphate synthase inhibitors.

Leishmaniasis is caused by protozoa of the genus Leishmania spp. and is considered the second most important protozoa in the world due to the number of cases and mortality. Despite its importance in terms of public health, the treatment of patients is limited and has mostly low levels of efficacy and safety. Farnesyl pyrophosphate synthase (FPPS) acts in the early stages of isoprenoid synthesis, and is important for maintaining the integrity of the lipid bilayer of the parasite that causes the disease. The aim of this work was to identify one potential inhibitor of the FPPS of Leishmania major through virtual screening by pharmacophore modeling and docking. A total of 85,000 compounds from a natural products database (ZINC15) was submitted for virtual hierarchical screening, and the top ranked molecule in both methods was analyzed by intermolecular interaction profile and 20 ns molecular dynamics simulations. These results showed a promising compound from natural products that mimic the major interactions present in the substrate/inhibitor.

Identification of new promising Plasmodium falciparum superoxide dismutase allosteric inhibitors through hierarchical pharmacophore-based virtual screening and molecular dynamics.

Malaria is the world's most widespread protozoan infection, being responsible for more than 445,000 annual deaths. Among the malaria parasites, Plasmodium falciparum is the most prevalent and lethal. In this context, the search for new antimalarial drugs is urgently needed. P. falciparum superoxide dismutase (PfSOD) is an important enzyme involved in the defense mechanism against oxidative stress. The goal of this study was to identify through hierarchical screening on pharmacophore models and molecular dynamics (MD), promising allosteric PfSOD inhibitors that do not show structural requirements for human inhibition. MD simulations of 1000 ps were performed on PfSOD using GROMACS 5.1.2. For this, the AMBER99SB-ILDN force field was adapted to describe the metal-containing system. The simulations indicated stability in the developed system. Therefore, a covariance matrix was generated, in which it was possible to identify residues with correlated and anticorrelated movements with the active site. These results were associated with the results found in the predictor of allosteric sites, AlloSitePro, which affirmed the ability of these residues to delimit an allosteric site. Then, after successive filtering of the Sigma-Aldrich® compounds database for HsSOD1 and PfSOD pharmacophores, 152 compounds were selected, also obeying Lipinski's rule of 5. Further filtering of those compounds based on molecular docking results, toxicity essays, availability, and price filtering led to the selection of a best compound, which was then submitted to MD simulations of 20,000 ps on the allosteric site. The study concludes that the ZINC00626080 compound could be assayed against SODs. Graphical Abstract Plasmodium falciparum superoxide dismutase.

Comparison of complex networks and tree-based methods of phylogenetic analysis and proposal of a bootstrap method.

Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits. In order to perform a close comparison to these methods, we selected Basidiomycota fungi as the taxonomic group and used a high-quality, manually curated and characterized database of chitin synthase sequences. This enzymatic protein plays a key role in the synthesis of one of the exclusive features of the fungal cell wall: the presence of chitin. The communities (modules) detected by the complex network method corresponded exactly to the groups retrieved by the phylogenetic inference methods. Additionally, we propose a bootstrap method for the complex network approach. The statistical results we have obtained with this method were also close to those obtained using traditional bootstrap methods.

PathoSpotter-K: A computational tool for the automatic identification of glomerular lesions in histological images of kidneys.

PathoSpotter is a computational system designed to assist pathologists in teaching about and researching kidney diseases. PathoSpotter-K is the version that was developed to detect nephrological lesions in digital images of kidneys. Here, we present the results obtained using the first version of PathoSpotter-K, which uses classical image processing and pattern recognition methods to detect proliferative glomerular lesions with an accuracy of 88.3 ± 3.6%. Such performance is only achieved by similar systems if they use images of cell in contexts that are much less complex than the glomerular structure. The results indicate that the approach can be applied to the development of systems designed to train pathology students and to assist pathologists in determining large-scale clinicopathological correlations in morphological research.

Prediction of CD8+ Epitopes in Leishmania braziliensis Proteins Using EPIBOT: In Silico Search and In Vivo Validation.

BACKGROUND: Leishmaniasis is caused by intracellular Leishmania parasites that induce a T-cell mediated response associated with recognition of CD4+ and CD8+ T cell Line 1Lineepitopes. Identification of CD8+ antigenic determinants is crucial for vaccine and therapy development. Herein, we developed an open-source software dedicated to search and compile data obtained from currently available on line prediction algorithms. METHODOLOGY/PRINCIPAL FINDINGS: We developed a two-phase algorithm and implemented in an open source software called EPIBOT, that consolidates the results obtained with single prediction algorithms, generating a final output in which epitopes are ranked. EPIBOT was initially trained using a set of 831 known epitopes from 397 proteins from IEDB. We then screened 63 Leishmania braziliensis vaccine candidates with the EPIBOT trained tool to search for CD8+ T cell epitopes. A proof-of-concept experiment was conducted with the top eight CD8+ epitopes, elected by EPIBOT. To do this, the elected peptides were synthesized and validated for their in vivo cytotoxicity. Among the tested epitopes, three were able to induce lysis of pulsed-target cells. CONCLUSION: Our results show that EPIBOT can successfully search across existing prediction tools, generating a compiled list of candidate CD8+ epitopes. This software is fast and a simple search engine that can be customized to search over different MHC alleles or HLA haplotypes.

Structure-based drug design studies of UDP-N-acetylglucosamine pyrophosphosrylase, a key enzyme for the control of witches' broom disease.

BACKGROUND: The witches' broom disease is a plague caused by Moniliophthora perniciosa in the Theobroma cacao, which has been reducing the cocoa production since 1989. This issue motivated a genome project that has showing several new molecular targets, which can be developed inhibitors in order to control the plague. Among the molecular targets obtained, the UDP-N-acetylglucosamine pyrophosphorylase (UNAcP) is a key enzyme to construct the fungal cell wall. The inhibition of this enzyme results in the fungal cell death. RESULTS: The results show that the molecular recognition of the enzyme with the substrates occurs mainly by hydrogen bonds between ligands and Arg116, Arg383, Gly381, and Lys408 amino acids; and few hydrophobic interactions with Tyr382 and Lys123 residues. CONCLUSIONS: Among the compounds analyzed, the NAG5 showed the best binding energy (-95.2 kcal/mol). The next steps for the control of witches' broom plague involve the synthesis and biological evaluation of these compounds, which are in progress.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks.

BACKGROUND: Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. METHODS: The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. RESULTS: Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). CONCLUSIONS: An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

Comparative modeling of DNA and RNA polymerases from Moniliophthora perniciosa mitochondrial plasmid.

BACKGROUND: The filamentous fungus Moniliophthora perniciosa (Stahel) Aime & Phillips-Mora is a hemibiotrophic Basidiomycota that causes witches' broom disease of cocoa (Theobroma cacao L.). This disease has resulted in a severe decrease in Brazilian cocoa production, which changed the position of Brazil in the market from the second largest cocoa exporter to a cocoa importer. Fungal mitochondrial plasmids are usually invertrons encoding DNA and RNA polymerases. Plasmid insertions into host mitochondrial genomes are probably associated with modifications in host generation time, which can be involved in fungal aging. This association suggests activity of polymerases, and these can be used as new targets for drugs against mitochondrial activity of fungi, more specifically against witches' broom disease. Sequencing and modeling: DNA and RNA polymerases of M. perniciosa mitochondrial plasmid were completely sequenced and their models were carried out by Comparative Homology approach. The sequences of DNA and RNA polymerase showed 25% of identity to 1XHX and 1ARO (pdb code) using BLASTp, which were used as templates. The models were constructed using Swiss PDB-Viewer and refined with a set of Molecular Mechanics (MM) and Molecular Dynamics (MD) in water carried out with AMBER 8.0, both working under the ff99 force fields, respectively. Ramachandran plots were generated by Procheck 3.0 and exhibited models with 97% and 98% for DNA and RNA polymerases, respectively. MD simulations in water showed models with thermodynamic stability after 2000 ps and 300 K of simulation. CONCLUSION: This work contributes to the development of new alternatives for controlling the fungal agent of witches' broom disease.

Transferências fiscais intergovernamentais no Brasil: uma avaliação das transferências federais, com ênfase no Sistema Único de Saúde / Texto para Discussão (TD) 1451: Transferências fiscais intergovernamentais no Brasil: uma avaliação das transferências federais, com ênfase no Sistema Único de Saúde

Avalia as transferências fiscais intergovernamentais brasileiras de modo a identificar quais tipos seriam mais adequados na eficiência e à equidade no acesso aos serviços públicos. Propõe, em particular, específicos tipos e formas de transferências para a consecução dos programas de saúde.