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Generalized anxiety disorder is a highly prevalent mental disorder. Previous data indicate that more than 18 million Brazilians suffer from this condition. Traditionally, generalized anxiety disorder has been considered a mild mental health disorder, despite its links to lower life expectancy, cardiovascular disease, and suicide. The aim of this article is to combine elements of systematic and critical reviews to produce a synthesis of the best evidence about generalized anxiety disorder treatment. Systematic reviews, meta-analyses, and randomized controlled trials were included. The descriptor used in the search was "generalized anxiety disorder," which resulted in 4,860 articles and seven other studies, of which 59 were selected. Antidepressants and benzodiazepines were indicated, as was pregabalin, and atypical antipsychotics, such as quetiapine, have been studied. Individual cognitive behavior therapy (third wave) has proven effective. There is extensive literature on many effective treatments for generalized anxiety disorder. The present review summarizes the therapeutic possibilities, emphasizing those available in Brazil. Further studies are needed to compare other available medications, assess psychotherapies and new treatments in greater depth, as well as to assess the ideal duration of therapy. Registration number: PROSPERO CRD42021288323.

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OBJECTIVE: To combine elements of a systematic review and critical review to produce best evidence synthesis for the treatament of GAD. METHOD: There was included systematic reviews, metanalysis, and randomized controlled trials. Descriptor used was "generalized anxiety disorder", resulting in 4860 articles and 7 other studies, of which 59 were selected. RESULTS: Antidepressants and benzodiazepines are indicated, as well as pregabalin. From, atypical antipsychotics quetiapine has been studied. Cognitive behavior therapy (third wave of behavioral and cognitive therapies) as well as individual CBT proven to be effective. CONCLUSION: There is extensive literature on many effective treatments for GAD. The present work summarizes the therapeutic possibilities, emphasizing those available in the Brazil. Further studies are still needed to compare other available medications, to assess psychotherapies in more depth, new treatments and specially to assess the ideal time for maintaining therapy.

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Focal cortical dysplasia (FCD) is a brain malformation that causes medically refractory epilepsy. FCD is classified into three categories based on structural and cellular abnormalities, with FCD type II being the most common and characterized by disrupted organization of the cortex and abnormal neuronal development. In this study, we employed cell-type deconvolution and single-cell signatures to analyze bulk RNA-seq from multiple transcriptomic studies, aiming to characterize the cellular composition of brain lesions in patients with FCD IIa and IIb subtypes. Our deconvolution analyses revealed specific cellular changes in FCD IIb, including neuronal loss and an increase in reactive astrocytes (astrogliosis) when compared to FCD IIa. Astrogliosis in FCD IIb was further supported by a gene signature analysis and histologically confirmed by glial fibrillary acidic protein (GFAP) immunostaining. Overall, our findings demonstrate that FCD II subtypes exhibit differential neuronal and glial compositions, with astrogliosis emerging as a hallmark of FCD IIb. These observations, validated in independent patient cohorts and confirmed using immunohistochemistry, offer novel insights into the involvement of glial cells in FCD type II pathophysiology and may contribute to the development of targeted therapies for this condition.

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BACKGROUND: Despite the criteria already established for the classification of knee osteoarthritis (OA), a radiographic and/or clinical knee OA diagnosis usually occurs in cases of fully manifest or more advanced disease, which can make health promotion, prevention, and functional rehabilitation in more advanced stages of the disease less effective. In addition, radiographic knee OA can generate more financial costs for health services. Therefore, developing and validating screening instruments to assess the probability of development and progression of knee OA would be of great value for both clinical practice and science. OBJECTIVE: To cross-culturally adapt and investigate the measurement properties of the Knee OA Pre-screening Questionnaire Brazilian version. METHODS: A total of 250 individuals of both sexes aged between 35 and 92 years [(mean (standard deviation): 63 (11) years old; 74.1 (15.1) kg; 1.59 (0.09) m; 29.38 (5.44) kg/m2] participated in this study. The cross-cultural adaptation and analyses of the measurement properties of the KOPS Brazilian version included: (1) assessment of conceptual and item equivalence; (2) assessment of semantic equivalence; (3) assessment of operational equivalence; and (4) assessment of measurement equivalence, reliability, and validity. RESULTS: Cronbach's alpha for the internal consistency among the six components of the KOPS Brazilian version was 0.71. The test-retest 72 h apart for each component resulted in a coefficient correlation intraclass ranging from 0.74 to 1.00. The probability of an individual randomly chosen from the population having KL ≥ 1 and KOPS Brazilian version ≥ 21 points was 0.74 (area under the curve of the Receiver Operating Characteristic - AUC of ROC); furthermore, the AUC for KL ≥ 2 and the KOPS Brazilian version ≥ 23 points was 0.77. CONCLUSION: The KOPS Brazilian version is a reliable and valid instrument for early screening of knee OA in individuals aged 35 years and over in the Brazilian context.

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OBJECTIVES: We compared the proteomic signatures of the hippocampal lesion induced in three different animal models of mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE+HS): the systemic pilocarpine model (PILO), the intracerebroventricular kainic acid model (KA), and the perforant pathway stimulation model (PPS). METHODS: We used shotgun proteomics to analyze the proteomes and find enriched biological pathways of the dorsal and ventral dentate gyrus (DG) isolated from the hippocampi of the three animal models. We also compared the proteomes obtained in the animal models to that from the DG of patients with pharmacoresistant MTLE+HS. RESULTS: We found that each animal model presents specific profiles of proteomic changes. The PILO model showed responses predominantly related to neuronal excitatory imbalance. The KA model revealed alterations mainly in synaptic activity. The PPS model displayed abnormalities in metabolism and oxidative stress. We also identified common biological pathways enriched in all three models, such as inflammation and immune response, which were also observed in tissue from patients. However, none of the models could recapitulate the profile of molecular changes observed in tissue from patients. SIGNIFICANCE: Our results indicate that each model has its own set of biological responses leading to epilepsy. Thus, it seems that only using a combination of the three models may one replicate more closely the mechanisms underlying MTLE+HS as seen in patients.

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Abstract Background: Despite the criteria already established for the classification of knee osteoarthritis (OA), a radiographic and/or clinical knee OA diagnosis usually occurs in cases of fully manifest or more advanced disease, which can make health promotion, prevention, and functional rehabilitation in more advanced stages of the disease less effective. In addition, radiographic knee OA can generate more financial costs for health services. Therefore, developing and validating screening instruments to assess the probability of development and progression of knee OA would be of great value for both clinical practice and science. Objective: To cross-culturally adapt and investigate the measurement properties of the Knee OA Pre-screening Questionnaire Brazilian version. Methods: A total of 250 individuals of both sexes aged between 35 and 92 years [(mean (standard deviation): 63 (11) years old; 74.1 (15.1) kg; 1.59 (0.09) m; 29.38 (5.44) kg/m2] participated in this study. The cross-cultural adaptation and analyses of the measurement properties of the KOPS Brazilian version included: (1) assessment of conceptual and item equivalence; (2) assessment of semantic equivalence; (3) assessment of operational equivalence; and (4) assessment of measurement equivalence, reliability, and validity. Results: Cronbach's alpha for the internal consistency among the six components of the KOPS Brazilian version was 0.71. The test-retest 72 h apart for each component resulted in a coefficient correlation intraclass ranging from 0.74 to 1.00. The probability of an individual randomly chosen from the population having KL ≥ 1 and KOPS Brazilian version ≥ 21 points was 0.74 (area under the curve of the Receiver Operating Characteristic - AUC of ROC); furthermore, the AUC for KL ≥ 2 and the KOPS Brazilian version ≥ 23 points was 0.77. Conclusion: The KOPS Brazilian version is a reliable and valid instrument for early screening of knee OA in individuals aged 35 years and over in the Brazilian context.

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Mesial temporal lobe epilepsy (MTLE) is a chronic neurological disorder characterized by the occurrence of seizures, and histopathological abnormalities in the mesial temporal lobe structures, mainly hippocampal sclerosis (HS). We used a multi-omics approach to determine the profile of transcript and protein expression in the dorsal and ventral hippocampal dentate gyrus (DG) and Cornu Ammonis 3 (CA3) in an animal model of MTLE induced by pilocarpine. We performed label-free proteomics and RNAseq from laser-microdissected tissue isolated from pilocarpine-induced Wistar rats. We divided the DG and CA3 into dorsal and ventral areas and analyzed them separately. We performed a data integration analysis and evaluated enriched signaling pathways, as well as the integrated networks generated based on the gene ontology processes. Our results indicate differences in the transcriptomic and proteomic profiles among the DG and the CA3 subfields of the hippocampus. Moreover, our data suggest that epileptogenesis is enhanced in the CA3 region when compared to the DG, with most abnormalities in transcript and protein levels occurring in the CA3. Furthermore, our results show that the epileptogenesis in the pilocarpine model involves predominantly abnormal regulation of excitatory neuronal mechanisms mediated by N-methyl D-aspartate (NMDA) receptors, changes in the serotonin signaling, and neuronal activity controlled by calcium/calmodulin-dependent protein kinase (CaMK) regulation and leucine-rich repeat kinase 2 (LRRK2)/WNT signaling pathways.

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BACKGROUND: Little is known about bacterial transcriptional regulatory networks (TRNs). In Escherichia coli, which is the organism with the largest wet-lab validated TRN, its set of interactions involves only approximately 50% of the repertoire of transcription factors currently known, and ~25% of its genes. Of those, only a small proportion describes the regulation of processes that are clinically relevant, such as drug resistance mechanisms. RESULTS: We designed feed-forward (FF) and bi-fan (BF) motif predictors for E. coli using multi-layer perceptron artificial neural networks (ANNs). The motif predictors were trained using a large dataset of gene expression data; the collection of motifs was extracted from the E. coli TRN. Each network motif was mapped to a vector of correlations which were computed using the gene expression profile of the elements in the motif. Thus, by combining network structural information with transcriptome data, FF and BF predictors were able to classify with a high precision of 83% and 96%, respectively, and with a high recall of 86% and 97%, respectively. These results were found when motifs were represented using different types of correlations together, i.e., Pearson, Spearman, Kendall, and partial correlation. We then applied the best predictors to hypothesize new regulations for 16 operons involved with multidrug resistance (MDR) efflux pumps, which are considered as a major bacterial mechanism to fight antimicrobial agents. As a result, the motif predictors assigned new transcription factors for these MDR proteins, turning them into high-quality candidates to be experimentally tested. CONCLUSION: The motif predictors presented herein can be used to identify novel regulatory interactions by using microarray data. The presentation of an example motif to predictors will make them categorize whether or not the example motif is a BF, or whether or not it is an FF. This approach is useful to find new "pieces" of the TRN, when inspecting the regulation of a small set of operons. Furthermore, it shows that correlations of expression data can be used to discriminate between elements that are arranged in structural motifs and those in random sets of transcripts.

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Gene regulatory networks, or simply gene networks (GNs), have shown to be a promising approach that the bioinformatics community has been developing for studying regulatory mechanisms in biological systems. GNs are built from the genome-wide high-throughput gene expression data that are often available from DNA microarray experiments. Conceptually, GNs are (un)directed graphs, where the nodes correspond to the genes and a link between a pair of genes denotes a regulatory interaction that occurs at transcriptional level. In the present study, we had two objectives: 1) to develop a framework for GN reconstruction based on a Bayesian network model that captures direct interactions between genes through nonparametric regression with B-splines, and 2) to demonstrate the potential of GNs in the analysis of expression data of a real biological system, the yeast pheromone response pathway. Our framework also included a number of search schemes to learn the network. We present an intuitive notion of GN theory as well as the detailed mathematical foundations of the model. A comprehensive analysis of the consistency of the model when tested with biological data was done through the analysis of the GNs inferred for the yeast pheromone pathway. Our results agree fairly well with what was expected based on the literature, and we developed some hypotheses about this system. Using this analysis, we intended to provide a guide on how GNs can be effectively used to study transcriptional regulation. We also discussed the limitations of GNs and the future direction of network analysis for genomic data. The software is available upon request.

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In this work we developed an extension of IsaViz software, a RDF (Resource Description Framework) authoring tool, designed to be a graphical environment to build models of metabolic and regulatory networks. This environment, called Metabolic IsaViz, was linked to a genomic library of types and was modeled on the basis of ontologies. Biochemical pathways included data at sequence level (e.g., the amino acid sequence of enzymes), besides kinetic and thermodynamic parameters for the reactions. Models created with Metabolic IsaViz could be exported to pathways simulators through SBML (Systems Biology Markup Language), which allowed to analyze the pathway dynamics of target chemicals.