Interfacial Dynamics and Growth Modes of ß2-Microglobulin Dimers.

Protein aggregation is a complex process, strongly dependent on environmental conditions and highly structurally heterogeneous, both at the final level of fibril structure and intermediate level of oligomerization. Since the first step in aggregation is the formation of a dimer, it is important to clarify how certain properties of the latter (e.g., stability or interface geometry) may play a role in self-association. Here, we report a simple model that represents the dimer's interfacial region by two angles and combine it with a simple computational method to investigate how modulations of the interfacial region occurring on the ns-µs time scale change the dimer's growth mode. To illustrate the proposed methodology, we consider 15 different dimer configurations of the ß2m D76N mutant protein equilibrated with long Molecular Dynamics simulations and identify which interfaces lead to limited and unlimited growth modes, having, therefore, different aggregation profiles. We found that despite the highly dynamic nature of the starting configurations, most polymeric growth modes tend to be conserved within the studied time scale. The proposed methodology performs remarkably well taking into consideration the nonspherical morphology of the ß2m dimers, which exhibit unstructured termini detached from the protein's core, and the relatively weak binding affinities of their interfaces, which are stabilized by nonspecific apolar interactions. The proposed methodology is general and can be applied to any protein for which a dimer structure has been experimentally determined or computationally predicted.

IoTMapper: A Metrics Aggregation System Architecture in Support of Smart City Solutions.

Smart cities are, nowadays, an unavoidable and growing reality, supported on software platforms that support city management, through the processing and presentation of a large number of data, obtained from sensors used throughout the cities. Low-power wide area networks (LPWAN) leverage the sensorization process; however, urban landscape, in turn, induces a high probability of change in the propagation conditions of the LPWAN network, thus requiring active monitoring solutions for assessing the city LPWAN network condition. Currently existing solutions usually consider the existence of only one type of LPWAN network to be monitored. In this paper, an architecture for aggregation of metrics from heterogeneous LPWAN networks is presented. The architecture, named IoTMapper, combines purpose build components with existing components from the FIWARE and Apache Kafka ecosystems. Implementation details for the LPWAN networks are abstracted by adapters so that new networks may be easily added. The validation was carried out using real data collected for long-range wide-area network (LoRaWAN) in Lisbon, and a simulated data set extrapolated from the collected data. The results indicate that the presented architecture is a viable solution for metrics aggregation that may be expanded to support multiple networks. However, some of the considered FIWARE components present performance bottlenecks that may hinder the scaling of the architecture while processing new message arrivals.

After a Century of Research into Environmental Mutagens and Carcinogens, Where Do We Stand?

Cancer is one of the longest-known human diseases, yet only in recent times have we begun to perceive that the percentage of neoplasms caused by environmental factors, lifestyle and chemicals, is likely underestimated. The first medical reports associating cancer with pollutants like tars appeared by the early 20th century, but despite initial evidence relating oncogenesis and chromosomal alterations, only after the structure of DNA had been elucidated in the 1950s have genetic disorders been fully perceived as cause. This led to a growing interest in genotoxic and mutagenic pollutants. Even though we are now familiar with a range of environmental carcinogens spanning between aromatic hydrocarbons and asbestos to radionuclides and forms of carbon nanomaterials, establishing causal networks between pollutants and cancer remains cumbersome. In most part, this is due to the complexity of toxicant matrices, unknown modes-of-action of chemicals or their mixtures, the widening array of novel pollutants plus difficulties in subtracting background effects from true aetiology of disease. Recent advances in analytical chemistry, high-throughput toxicology, next-generation sequencing, computational biology and databases that allocate whole normal and cancer genomes, all indicate that we are on the verge of a new age of research into mechanistic 'oncotoxicology', but how can it impact risk assessment and prevention?

KeyRecs: A keystroke dynamics and typing pattern recognition dataset.

Keystroke dynamics can valuably contribute to the development of intelligent authentication systems by enabling a single and continuous authentication process in a passive and non-intrusive manner by continuously verifying a user's identity. This work describes the KeyRecs dataset, which contains fixed-text and free-text samples of user typing behavior and demographic information of the participants age, gender, handedness, and nationality. The keystroke data was obtained from 99 participants of various nationalities who completed password retype and transcription exercises. The recorded samples consist of inter-key latencies computed in a digraph fashion measuring the time between each key press and release during an exercise. KeyRecs can be leveraged to improve the recognition of authorized users and prevent unauthorized access in biometric authentication software.

Predicting stable binding modes from simulated dimers of the D76N mutant of ß 2-microglobulin.

The D76N mutant of the ß 2 m protein is a biologically motivated model system to study protein aggregation. There is strong experimental evidence, supported by molecular simulations, that D76N populates a highly dynamic conformation (which we originally named I 2 ) that exposes aggregation-prone patches as a result of the detachment of the two terminal regions. Here, we use Molecular Dynamics simulations to study the stability of an ensemble of dimers of I 2 generated via protein-protein docking. MM-PBSA calculations indicate that within the ensemble of investigated dimers the major contribution to interface stabilization at physiological pH comes from hydrophobic interactions between apolar residues. Our structural analysis also reveals that the interfacial region associated with the most stable binding modes are particularly rich in residues pertaining to both the N- and C-terminus, as well residues from the BC- and DE-loops. On the other hand, the less stable interfaces are stabilized by intermolecular interactions involving residues from the CD- and EF-loops. By focusing on the most stable binding modes, we used a simple geometric rule to propagate the corresponding dimer interfaces. We found that, in the absence of any kind of structural rearrangement occurring at an early stage of the oligomerization pathway, some interfaces drive a self-limited growth process, while others can be propagated indefinitely allowing the formation of long, polymerized chains. In particular, the interfacial region of the most stable binding mode reported here falls in the class of self-limited growth.

In Silico End-to-End Protein-Ligand Interaction Characterization Pipeline: The Case of SARS-CoV-2.

SARS-CoV-2 triggered a worldwide pandemic disease, COVID-19, for which an effective treatment has not yet been settled. Among the most promising targets to fight this disease is SARS-CoV-2 main protease (Mpro), which has been extensively studied in the last few months. There is an urgency for developing effective computational protocols that can help us tackle these key viral proteins. Hence, we have put together a robust and thorough pipeline of in silico protein-ligand characterization methods to address one of the biggest biological problems currently plaguing our world. These methodologies were used to characterize the interaction of SARS-CoV-2 Mpro with an α-ketoamide inhibitor and include details on how to upload, visualize, and manage the three-dimensional structure of the complex and acquire high-quality figures for scientific publications using PyMOL (Protocol 1); perform homology modeling with MODELLER (Protocol 2); perform protein-ligand docking calculations using HADDOCK (Protocol 3); run a virtual screening protocol of a small compound database of SARS-CoV-2 candidate inhibitors with AutoDock 4 and AutoDock Vina (Protocol 4); and, finally, sample the conformational space at the atomic level between SARS-CoV-2 Mpro and the α-ketoamide inhibitor with Molecular Dynamics simulations using GROMACS (Protocol 5). Guidelines for careful data analysis and interpretation are also provided for each Protocol.

Meningioma of the Pineal Region ­ Differential Radiologic Aspects of Pineal Region Tumors Based on a Clinical Case

Pineal region tumors are uncommon among neoplasm of the central nervous system, with this region being the most heterogeneous in terms of histological types. Meningiomas are rarer still, but can be found at this site, with origins in either the velum interpositum or falcotentorial junction. Neuroimaging exams can distinguish malignant from benign lesions besides helping to define the origin of the lesion as the pineal parenchymal or surrounding structures. We report the case of a woman with a pineal region tumor in which differential diagnoses included meningioma and germinoma, with confirmation of the former based on radiological characteristics and histopathology. In addition, a brief review of differential diagnoses and approaches for cases of lesions in this region is provided.

Os tumores da região da pineal apresentam uma baixa frequência entre as neoplasias do sistema nervoso central, sendo esta região a mais heterogênea em termos de tipos histológicos possíveis. Meningiomas são lesões ainda mais raras, porém possíveis de advirem desta localização, sejam originados do velum interpositum ou da junção falcotentorial. Os exames de neuroimagem permitem distinguir lesões malignas de benignas além de auxiliar na definição entre origem do parênquima pineal ou de estruturas adjacentes. Apresentamos o caso de uma mulher adulta com uma neoplasia da região da pineal cujos diagnósticos diferenciais incluíram meningioma e germinoma, evidenciando-se pelas características radiológicas e resultados histopatológicos tratar-se do primeiro. Além disso, fazemos uma breve revisão a respeito dos diagnósticos diferencias e condutas frente a uma lesão desta região.

[Evaluation of the antimicrobial susceptibility profile of microorganisms isolated from urine in the region of Vale do Sousa and Tâmega]. / Avaliação do perfil de susceptibilidade aos antimicrobianos de microrganismos isolados em urinas na região do Vale do Sousa e Tâmega.

The urinary tract is one of the more common sites of bacterial infections, especially in women. Urinary infection can be defined as an infection of urinary tract structures which occurs, generally, as a consequence of the presence or colonization by urine bacteria. The aim of this study was to determine the etiology of urinary tract infections and their susceptibility to antimicrobial agents in the region of Vale do Sousa and Tâmega. From February 2008 to January 2009, 18653 urine cultures were analyzed. From these cultures 1037 were positive. From this total of positive cultures, 18,3% were from males and 81.7% were from females. In bacteriological positive tests, 23 different strains of microorganisms were found. It was verified that the most frequent microorganism was Escherichia coli, followed by Proteus mirabilis, Klebsiella pneumoniae, Enterococcus faecalis and Pseudomonas aeruginosa. For antimicrobial susceptibility it was verified that Escherichia coli showed low susceptibility to amoxicillin and cotrimoxazole. Proteus mirabilis showed good susceptibility to cefotaxime and low to cotrimoxazole, amoxicillin and ciprofloxacin. For Klebsiella pneumoniae was found only a reasonable susceptibility to gentamicin and Enterococcus faecalis showed amoxicillin susceptibility. Pseudomonas aeruginosa showed low susceptibility to all antibiotics analyzed with the exception of the combination piperacillin/tazobactam. In conclusion, this study shows that Escherichia coli, Proteus mirabilis and Klebsiella pneumoniae are the three main microorganisms that causes urinary infections in the region of Vale do Sousa and Tâmega. Therefore, the antimicrobial empirically used must have a spectrum against enterobacteria, because they are the most likely to be present in urinary tract infections acquired in the community. A periodic analysis of the susceptibility profile should be performed over time for each region in order to help in the beginning of the empirical antimicrobial treatment.