More than an RNA matchmaker: Expanding the roles of Hfq into ribosome biogenesis

Ribosome biogenesis is a complex process involving multiple factors. The work described here is primarily centered in the study of ribosomal RNA, highlighting its central role in translation regulation. We have uncovered new regulators involved in rRNA processing, folding and degradation pathways. For the first time, we demonstrate that the widely conserved RNA chaperone Hfq, mostly known as the sRNA-mRNA matchmaker, acts as a ribosomal assembly factor in Escherichia coli, affecting rRNA processing, ribosome levels, translation efficiency and accuracy. This function is suggested to be independent of its activity as sRNA-regulator.(...

Review - Understanding β-lactamase Producing Klebsiella pneumoniae

Klebsiella pneumoniae is a nosocomial pathogen commonly implicated in hospital outbreaks with a propensity for antimicrobial resistance towards mainstay β-lactam antibiotics and multiple other antibiotic classes. The successful proliferation, transmission and infection of the Gram-negative bacterium can be attributed to a myriad of factors including host factors, environmental factors, virulence factors and a large repertoire of antibiotic resistance mechanisms. The poor treatment outcomes and limited treatment options are consequences of the successful pathogenesis and spread of antibiotic resistance in the increasingly common β-lactamase producing K. pneumoniae bacterium. The review briefly explores the biology, successful pathogenesis and antibiotic resistance of K. pneumoniae as well as the detection and characterisation techniques of important strains

The Influence of Dentin Age and the Presence of Cracks in Removal of the Root Filling Material

Introduction: This study evaluated the removal of the filling material during endodontic retreatment considering the presence of cracks and the dentin age. Methods and Materials: A total of 20 freshly extracted single-rooted teeth were categorized into the following two groups according to the age of the patients: Group Young (Y; aged 18-30 years) and Group Old (O; aged ≥60 years). Each tooth specimen was scanned by microcomputed tomography (micro-CT) subsequently after endodontic retreatment with the Reciproc instruments (REC). The images were analyzed for differences in the volume of dentin cracks and the presence of the filling material in the middle and apical thirds of the teeth among the groups, according to the dentin age. Results: The micro-CT images showed that after retreatment, there were more cracks in the old root dentin than those in the young root dentin, although the difference was not statistically significant (P>0.05). The greatest reduction in the filling material was achieved when the old root dentin with cracks was retreated when compared with that of the young root dentin with cracks, but the difference was not statistically significant (P>0.05). Conclusion: The dentinal age and the presence of cracks were not found to be relevant factors for the removal of the filling material.Keywords: Dentin; Microcomputed Tomography; Retreatmen

Purification and Preliminary Crystallographic Analysis of a New Lys49-PLA2 from B. Jararacussu

BjVIII is a new myotoxic Lys49-PLA2 isolated from Bothrops jararacussu venom that exhibits atypical effects on human platelet aggregation. To better understand the mode of action of BjVIII, crystallographic studies were initiated. Two crystal forms were obtained, both containing two molecules in the asymmetric unit (ASU). Synchrotron radiation diffraction data were collected to 2.0 Å resolution and 1.9 Å resolution for crystals belonging to the space group P212121 (a = 48.4 Å, b = 65.3 Å, c = 84.3 Å) and space group P3121 (a = b = 55.7 Å, c = 127.9 Å), respectively. Refinement is currently in progress and the refined structures are expected to shed light on the unusual platelet aggregation activity observed for BjVIII

Associação entre fatores de risco cardiovascular e capacidade funcional de idosos longevos

Modelo do estudo: Estudo transversal. Objetivo: Analisar a associação entre a presença de fatores de risco cardiovascular (FRC) e a capacidade funcional de idosos longevos. Materiais e Método: A amostra foi composta por 91 idosos com idade entre 80 e 90 anos (83,0±2,3 anos), sendo 60 mulheres (82,9±2,1 anos) e 31 homens (83,2±2,6 anos) residentes na cidade de Presidente Prudente/SP. Os FRC analisados foram: Hipertensão Arterial (HA) e excesso de gordura corporal (total e tronco). A presença de Hipertensão foi verificada por meio do questionário auto-referido baseado no Standard Health Questionnaire(SHQ). A avaliação da gordura corporal foi feita pela absorpiometria de dupla energia de raios-X (DEXA) e a capacidade funcional foi avaliada por meio dos testes funcionais (equilíbrio estático, velocidade usual de caminhada e força de membros inferiores). Para tratamento estatístico realizou-se o teste qui-quadrado, o software utilizado foi SPSS (13.0) e o nível de significância estabelecido foi de 5%. Resultados: Os idosos com a presença de HA e excesso de %GC apresentaram menor desempenho no teste de membros inferiores (83,3% menor e 16,7% maior), p=0,011 comparados aqueles com apenas um FCR. As idosas com a presença de HA e excesso de %GTron também apresentaram menor desempenho no mesmo teste (80,6% menor e 19,4% maior), p=0,018 e no teste de velocidade de caminhada (80,6% menor e 19,4% maior), p=0,034. Conclusão: A HA e o excesso de gordura corporal (total e tronco) agregados são FRC, que estão associados à redução da capacidade funcional de idosos longevos.Study design: cross-sectional study. Objective: To assess the association between the presence of cardiovascular risk factor (CRP) and functional capacity of the oldest old. Methods: The sample 9onsisted of 91 elderly aged 80 and 90 years (83.0 ± 2.5 years) with 60 women (82.2 ± 2.1 years) and 31 men (83.2± 2,6 years) residing in the city of Presidente Prudente - SP. The FRC were analyzed: arterial hypertension(AH) and excess body fat (total and trunk). The presence of hypertension was verified by means of selfreported questionnaire based on the Standard Health Questionnaire (SHQ). Assessment of body was made by absorpiometria dual energy X-ray absorptiometry (DXA) and functional capacity was assessed by the functional tests (static balance, normal walking speed and force of the lower limbs). For statistical analysis we carried out the chi-square test, the software used was SPSS (13.0) and the significance level was set at 5%. Results. In males, with hypertension and the presence of excess %BF had lower performance in the lower limbs (83.3% lower and 16.7% higher), p = 0.011 compared to those with only a VCF.The elderly women with hypertension and the presence of excess GTron% also had lower performance on the same test (80.6% lower and 19.4% higher), p = 0.018 and the test of walking speed (80.6% lower and 19.4% higher), p = 0.034. Conclusion: Arterial hypertension and excess body fat (total and trunk)aggregated are FRC, which are associated with reduced functional capacity of the oldest old

Antibodies directed to antigens secreted by murine epithelioid macrophages modulate BCG-induced granulomata

The authors have previously shown that epithelioid cells isolated from mice secrete a factor, called macrophage deactivating factor (MDF), that promptly deactivates superoxide release by activated macrophages and neutrophils. In this paper some biological properties of a polyclonal rat antiserum directed to MDF and other substances secreted by these cells are described. The immunoglobulin fraction of this antiserum reacted, by immunocytochemical methods, with epitopes in the cell membrane of macrophages adherent to coverslips subcutaneously implanted for 14 days; but not for 5 days. It also reacted with antigens within and outside cells in BCG-induced granulomas. This antiserum blocked completely the macrophage deactivating activity of epithelioid cell culture supernatants. Anti-IL-10 monoclonal antibody, did not block MDF activity. The administration of the immunoglobulin fraction from immunized rats to C5 deficient mice bearing BCG-induced granulomatas in the footpad, significantly reduced the size of the lesions. A marked necrosis of inflammatory cells and mononuclear cells phagocyting debris of necrotic cells were observed in these lesions

Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks

Plant phenology studies rely on long-term monitoring of life cycles of plants. High-resolution unmanned aerial vehicles (UAVs) and near-surface technologies have been used for plant monitoring, demanding the creation of methods capable of locating, and identifying plant species through time and space. However, this is a challenging task given the high volume of data, the constant data missing from temporal dataset, the heterogeneity of temporal profiles, the variety of plant visual patterns, and the unclear definition of individuals' boundaries in plant communities. In this letter, we propose a novel method, suitable for phenological monitoring, based on convolutional networks (ConvNets) to perform spatio-temporal vegetation pixel classification on high-resolution images. We conducted a systematic evaluation using high-resolution vegetation image datasets associated with the Brazilian Cerrado biome. Experimental results show that the proposed approach is effective, overcoming other spatio-temporal pixel-classification strategies

Anomaly Detection in Industrial Machinery using IoT Devices and Machine Learning: a Systematic Mapping

Anomaly detection is critical in the smart industry for preventing equipment failure, reducing downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large volumes of data from industrial machinery, providing a rich source of information for Anomaly Detection. However, the volume and complexity of data generated by the Internet of Things ecosystems make it difficult for humans to detect anomalies manually. Machine learning (ML) algorithms can automate anomaly detection in industrial machinery by analyzing generated data. Besides, each technique has specific strengths and weaknesses based on the data nature and its corresponding systems. However, the current systematic mapping studies on Anomaly Detection primarily focus on addressing network and cybersecurity-related problems, with limited attention given to the industrial sector. Additionally, these studies do not cover the challenges involved in using ML for Anomaly Detection in industrial machinery within the context of the IoT ecosystems. This paper presents a systematic mapping study on Anomaly Detection for industrial machinery using IoT devices and ML algorithms to address this gap. The study comprehensively evaluates 84 relevant studies spanning from 2016 to 2023, providing an extensive review of Anomaly Detection research. Our findings identify the most commonly used algorithms, preprocessing techniques, and sensor types. Additionally, this review identifies application areas and points to future challenges and research opportunities

Os compostos isoprénicos da uva e o seu papel no aroma varietal do vinho

Determinados compostos presentes nas uvas são responsáveis pelo chamado aroma varietal dos vinhos. O termo “aroma varietal” não implica que cada casta tenha compostos voláteis específicos. De facto, um dado composto ou precursor aromático é, geralmente, encontrado nos mostos e vinhos de diferentes castas. O perfil aromático de cada casta é o resultado de uma combinação específica de vários compostos. De entre estes, os compostos terpénicos assumem um papel importante no aroma varietal dos vinhos, integrando um grupo químico mais vasto, designado compostos isoprénicos. A casta Moscatel destaca‑se por apresentar uma elevada fração de compostos terpénicos na forma livre (cerca de 50%). Outros compostos relacionados com o aroma varietal dos vinhos são as pirazinas, os norisoprenóides e os tióis.info:eu-repo/semantics/publishedVersio

Predictive Maintenance Model Based on Anomaly Detection in Induction Motors: A Machine Learning Approach Using Real-Time IoT Data

With the support of Internet of Things (IoT) devices, it is possible to acquire data from degradation phenomena and design data-driven models to perform anomaly detection in industrial equipment. This approach not only identifies potential anomalies but can also serve as a first step toward building predictive maintenance policies. In this work, we demonstrate a novel anomaly detection system on induction motors used in pumps, compressors, fans, and other industrial machines. This work evaluates a combination of pre-processing techniques and machine learning (ML) models with a low computational cost. We use a combination of pre-processing techniques such as Fast Fourier Transform (FFT), Wavelet Transform (WT), and binning, which are well-known approaches for extracting features from raw data. We also aim to guarantee an optimal balance between multiple conflicting parameters, such as anomaly detection rate, false positive rate, and inference speed of the solution. To this end, multiobjective optimization and analysis are performed on the evaluated models. Pareto-optimal solutions are presented to select which models have the best results regarding classification metrics and computational effort. Differently from most works in this field that use publicly available datasets to validate their models, we propose an end-to-end solution combining low-cost and readily available IoT sensors. The approach is validated by acquiring a custom dataset from induction motors. Also, we fuse vibration, temperature, and noise data from these sensors as the input to the proposed ML model. Therefore, we aim to propose a methodology general enough to be applied in different industrial contexts in the future