Electro-immunosensor for ultra-sensitive determination of cardiac troponin I based on reduced graphene oxide and polytyramine.

This work reports the construction of a novel nanostructured immunosensor for detection of the troponin I biomarker (cTnI). Anti-troponin I antibody was anchored on the modified graphite electrode with reduced graphene oxide and polytyramine for detection of troponin I in serum samples. The performance of the electro-immunosensor was evaluated by differential pulse voltammetry. The immunosensor presented a wide work range, from 4 ng mL-1 to 4 pg mL-1 , whose detection limit (4 pg mL-1 ) is significantly lower than the basal level in human serum, and maintained 100% of response after 30 days of storage. Moreover, the immunosensor showed good selectivity for detection of cTnI in real sample containing interfering substances and specificity of response to cTnI in the serum of healthy and sick patients, and demonstrated the possibility of reuse for two consecutive analyses, in addition to using a simplified and inexpensive platform when compared to other devices, demonstrating them excellent potential for application in diagnosis in the early stages of acute myocardial infarction.

Using Mobile Edge AI to Detect and Map Diseases in Citrus Orchards.

Deep Learning models have presented promising results when applied to Agriculture 4.0. Among other applications, these models can be used in disease detection and fruit counting. Deep Learning models usually have many layers in the architecture and millions of parameters. This aspect hinders the use of Deep Learning on mobile devices as they require a large amount of processing power for inference. In addition, the lack of high-quality Internet connectivity in the field impedes the usage of cloud computing, pushing the processing towards edge devices. This work describes the proposal of an edge AI application to detect and map diseases in citrus orchards. The proposed system has low computational demand, enabling the use of low-footprint models for both detection and classification tasks. We initially compared AI algorithms to detect fruits on trees. Specifically, we analyzed and compared YOLO and Faster R-CNN. Then, we studied lean AI models to perform the classification task. In this context, we tested and compared the performance of MobileNetV2, EfficientNetV2-B0, and NASNet-Mobile. In the detection task, YOLO and Faster R-CNN had similar AI performance metrics, but YOLO was significantly faster. In the image classification task, MobileNetMobileV2 and EfficientNetV2-B0 obtained an accuracy of 100%, while NASNet-Mobile had a 98% performance. As for the timing performance, MobileNetV2 and EfficientNetV2-B0 were the best candidates, while NASNet-Mobile was significantly worse. Furthermore, MobileNetV2 had a 10% better performance than EfficientNetV2-B0. Finally, we provide a method to evaluate the results from these algorithms towards describing the disease spread using statistical parametric models and a genetic algorithm to perform the parameters' regression. With these results, we validated the proposed pipeline, enabling the usage of adequate AI models to develop a mobile edge AI solution.

Pyrolysis Kinetics of Byrsonima crassifolia Stone as Agro-Industrial Waste through Isoconversional Models.

This study is aimed at the analysis of the pyrolysis kinetics of Nanche stone BSC (Byrsonima crassifolia) as an agro-industrial waste using non-isothermal thermogravimetric experiments by determination of triplet kinetics; apparent activation energy, pre-exponential factor, and reaction model, as well as thermodynamic parameters to gather the required fundamental information for the design, construction, and operation of a pilot-scale reactor for the pyrolysis this lignocellulosic residue. Results indicate a biomass of low moisture and ash content and a high volatile matter content (≥70%), making BCS a potential candidate for obtaining various bioenergy products. Average apparent activation energies obtained from different methods (KAS, FWO and SK) were consistent in value (~123.8 kJ/mol). The pre-exponential factor from the Kissinger method ranged from 105 to 1014 min-1 for the highest pyrolytic activity stage, indicating a high-temperature reactive system. The thermodynamic parameters revealed a small difference between EA and ∆H (5.2 kJ/mol), which favors the pyrolysis reaction and indicates the feasibility of the energetic process. According to the analysis of the reaction models (master plot method), the pyrolytic degradation was dominated by a decreasing reaction order as a function of the degree of conversion. Moreover, BCS has a relatively high calorific value (14.9 MJ/kg) and a relatively low average apparent activation energy (122.7 kJ/mol) from the Starink method, which makes this biomass very suitable to be exploited for value-added energy production.

Identification of structures for ion channel kinetic models.

Markov models of ion channel dynamics have evolved as experimental advances have improved our understanding of channel function. Past studies have examined limited sets of various topologies for Markov models of channel dynamics. We present a systematic method for identification of all possible Markov model topologies using experimental data for two types of native voltage-gated ion channel currents: mouse atrial sodium currents and human left ventricular fast transient outward potassium currents. Successful models identified with this approach have certain characteristics in common, suggesting that aspects of the model topology are determined by the experimental data. Incorporating these channel models into cell and tissue simulations to assess model performance within protocols that were not used for training provided validation and further narrowing of the number of acceptable models. The success of this approach suggests a channel model creation pipeline may be feasible where the structure of the model is not specified a priori.

Predicting Patient Response to the Antiarrhythmic Mexiletine Based on Genetic Variation.

RATIONALE: Mutations in the SCN5A gene, encoding the α subunit of the Nav1.5 channel, cause a life-threatening form of cardiac arrhythmia, long QT syndrome type 3 (LQT3). Mexiletine, which is structurally related to the Na+ channel-blocking anesthetic lidocaine, is used to treat LQT3 patients. However, the patient response is variable, depending on the genetic mutation in SCN5A. OBJECTIVE: The goal of this study is to understand the molecular basis of patients' variable responses and build a predictive statistical model that can be used to personalize mexiletine treatment based on patient's genetic variant. METHODS AND RESULTS: We monitored the cardiac Na+ channel voltage-sensing domain (VSD) conformational dynamics simultaneously with other gating properties for the LQT3 variants. To systematically identify the relationship between mexiletine block and channel biophysical properties, we used a system-based statistical modeling approach to connect the multivariate properties to patient phenotype. We found that mexiletine altered the conformation of the Domain III VSD, which is the same VSD that many tested LQT3 mutations affect. Analysis of 15 LQT3 variants showed a strong correlation between the activation of the Domain III-VSD and the strength of the inhibition of the channel by mexiletine. Based on this improved molecular-level understanding, we generated a systems-based model based on a dataset of 32 LQT3 patients, which then successfully predicted the response of 7 out of 8 patients to mexiletine in a blinded, retrospective trial. CONCLUSIONS: Our results imply that the modulated receptor theory of local anesthetic action, which confines local anesthetic binding effects to the channel pore, should be revised to include drug interaction with the Domain III-VSD. Using an algorithm that incorporates this mode of action, we can predict patient-specific responses to mexiletine, improving therapeutic decision making.

Management of an Unusual Blow-In Orbital Roof Fracture Associated an Intracranial Hematoma.

ABSTRACT: Pure orbital wall fractures represent until 25% of the facial fractures and its reconstruction it's considering a challenge for the maxillofacial surgeons. There are many biomaterials used to repair these fractures according to the literature however, the most common are the titanium mesh and autogenous bone graft.The aim of this work is to report a rare case of blow-in roof orbital fracture associated to an intracranial hematoma in the cranium base.

Wearable Edge AI Applications for Ecological Environments.

Ecological environments research helps to assess the impacts on forests and managing forests. The usage of novel software and hardware technologies enforces the solution of tasks related to this problem. In addition, the lack of connectivity for large data throughput raises the demand for edge-computing-based solutions towards this goal. Therefore, in this work, we evaluate the opportunity of using a Wearable edge AI concept in a forest environment. For this matter, we propose a new approach to the hardware/software co-design process. We also address the possibility of creating wearable edge AI, where the wireless personal and body area networks are platforms for building applications using edge AI. Finally, we evaluate a case study to test the possibility of performing an edge AI task in a wearable-based environment. Thus, in this work, we evaluate the system to achieve the desired task, the hardware resource and performance, and the network latency associated with each part of the process. Through this work, we validated both the design pattern review and case study. In the case study, the developed algorithms could classify diseased leaves with a circa 90% accuracy with the proposed technique in the field. This results can be reviewed in the laboratory with more modern models that reached up to 96% global accuracy. The system could also perform the desired tasks with a quality factor of 0.95, considering the usage of three devices. Finally, it detected a disease epicenter with an offset of circa 0.5 m in a 6 m × 6 m × 12 m space. These results enforce the usage of the proposed methods in the targeted environment and the proposed changes in the co-design pattern.

Gating control of the cardiac sodium channel Nav1.5 by its ß3-subunit involves distinct roles for a transmembrane glutamic acid and the extracellular domain.

The auxiliary ß3-subunit is an important functional regulator of the cardiac sodium channel Nav1.5, and some ß3 mutations predispose individuals to cardiac arrhythmias. The ß3-subunit uses its transmembrane α-helix and extracellular domain to bind to Nav1.5. Here, we investigated the role of an unusually located and highly conserved glutamic acid (Glu-176) within the ß3 transmembrane region and its potential for functionally synergizing with the ß3 extracellular domain (ECD). We substituted Glu-176 with lysine (E176K) in the WT ß3-subunit and in a ß3-subunit lacking the ECD. Patch-clamp experiments indicated that the E176K substitution does not affect the previously observed ß3-dependent depolarizing shift of V½ of steady-state inactivation but does attenuate the accelerated recovery from inactivation conferred by the WT ß3-subunit. Removal of the ß3-ECD abrogated both the depolarizing shift of steady-state inactivation and the accelerated recovery, irrespective of the presence or absence of the Glu-176 residue. We found that steady-state inactivation and recovery from inactivation involve movements of the S4 helices within the DIII and DIV voltage sensors in response to membrane potential changes. Voltage-clamp fluorometry revealed that the E176K substitution alters DIII voltage sensor dynamics without affecting DIV. In contrast, removal of the ECD significantly altered the dynamics of both DIII and DIV. These results imply distinct roles for the ß3-Glu-176 residue and the ß3-ECD in regulating the conformational changes of the voltage sensors that determine channel inactivation and recovery from inactivation.

Storm-Drain and Manhole Detection Using the RetinaNet Method.

As key-components of the urban-drainage system, storm-drains and manholes are essential to the hydrological modeling of urban basins. Accurately mapping of these objects can help to improve the storm-drain systems for the prevention and mitigation of urban floods. Novel Deep Learning (DL) methods have been proposed to aid the mapping of these urban features. The main aim of this paper is to evaluate the state-of-the-art object detection method RetinaNet to identify storm-drain and manhole in urban areas in street-level RGB images. The experimental assessment was performed using 297 mobile mapping images captured in 2019 in the streets in six regions in Campo Grande city, located in Mato Grosso do Sul state, Brazil. Two configurations of training, validation, and test images were considered. ResNet-50 and ResNet-101 were adopted in the experimental assessment as the two distinct feature extractor networks (i.e., backbones) for the RetinaNet method. The results were compared with the Faster R-CNN method. The results showed a higher detection accuracy when using RetinaNet with ResNet-50. In conclusion, the assessed DL method is adequate to detect storm-drain and manhole from mobile mapping RGB images, outperforming the Faster R-CNN method. The labeled dataset used in this study is available for future research.

Mapping Utility Poles in Aerial Orthoimages Using ATSS Deep Learning Method.

Mapping utility poles using side-view images acquired with car-mounted cameras is a time-consuming task, mainly in larger areas due to the need for street-by-street surveying. Aerial images cover larger areas and can be feasible alternatives although the detection and mapping of the utility poles in urban environments using top-view images is challenging. Thus, we propose the use of Adaptive Training Sample Selection (ATSS) for detecting utility poles in urban areas since it is a novel method and has not yet investigated in remote sensing applications. Here, we compared ATSS with Faster Region-based Convolutional Neural Networks (Faster R-CNN) and Focal Loss for Dense Object Detection (RetinaNet ), currently used in remote sensing applications, to assess the performance of the proposed methodology. We used 99,473 patches of 256 × 256 pixels with ground sample distance (GSD) of 10 cm. The patches were divided into training, validation and test datasets in approximate proportions of 60%, 20% and 20%, respectively. As the utility pole labels are point coordinates and the object detection methods require a bounding box, we assessed the influence of the bounding box size on the ATSS method by varying the dimensions from 30×30 to 70×70 pixels. For the proposal task, our findings show that ATSS is, on average, 5% more accurate than Faster R-CNN and RetinaNet. For a bounding box size of 40×40, we achieved Average Precision with intersection over union of 50% (AP50) of 0.913 for ATSS, 0.875 for Faster R-CNN and 0.874 for RetinaNet. Regarding the influence of the bounding box size on ATSS, our results indicate that the AP50 is about 6.5% higher for 60×60 compared to 30×30. For AP75, this margin reaches 23.1% in favor of the 60×60 bounding box size. In terms of computational costs, all the methods tested remain at the same level, with an average processing time around of 0.048 s per patch. Our findings show that ATSS outperforms other methodologies and is suitable for developing operation tools that can automatically detect and map utility poles.

Network-based piecewise linear regression for QSAR modelling.

Quantitative Structure-Activity Relationship (QSAR) models are critical in various areas of drug discovery, for example in lead optimisation and virtual screening. Recently, the need for models that are not only predictive but also interpretable has been highlighted. In this paper, a new methodology is proposed to build interpretable QSAR models by combining elements of network analysis and piecewise linear regression. The algorithm presented, modSAR, splits data using a two-step procedure. First, compounds associated with a common target are represented as a network in terms of their structural similarity, revealing modules of similar chemical properties. Second, each module is subdivided into subsets (regions), each of which is modelled by an independent linear equation. Comparative analysis of QSAR models across five data sets of protein inhibitors obtained from ChEMBL is reported and it is shown that modSAR offers similar predictive accuracy to popular algorithms, such as Random Forest and Support Vector Machine. Moreover, we show that models built by modSAR are interpretatable, capable of evaluating the applicability domain of the compounds and serve well tasks such as virtual screening and the development of new drug leads.

Management Platforms and Protocols for Internet of Things: A Survey.

Internet of Things (IoT) management systems require scalability, standardized communication, and context-awareness to achieve the management of connected devices with security and accuracy in real environments. Interoperability and heterogeneity between hardware and application layers are also critical issues. To attend to the network requirements and different functionalities, a dynamic and context-sensitive configuration management system is required. Thus, reference architectures (RAs) represent a basic architecture and the definition of key characteristics for the construction of IoT environments. Therefore, choosing the best technologies of the IoT management platforms and protocols through comparison and evaluation is a hard task, since they are difficult to compare due to their lack of standardization. However, in the literature, there are no management platforms focused on addressing all IoT issues. For this purpose, this paper surveys the available policies and solutions for IoT Network Management and devices. Among the available technologies, an evaluation was performed using features such as heterogeneity, scalability, supported technologies, and security. Based on this evaluation, the most promising technologies were chosen for a detailed performance evaluation study (through simulation and deployment in real environments). In terms of contributions, these protocols and platforms were studied in detail, the main features of each approach are highlighted and discussed, open research issues are identified as well as the lessons learned on the topic.

How to Connect Cardiac Excitation to the Atomic Interactions of Ion Channels.

Many have worked to create cardiac action potential models that explicitly represent atomic-level details of ion channel structure. Such models have the potential to define new therapeutic directions and to show how nanoscale perturbations to channel function predispose patients to deadly cardiac arrhythmia. However, there have been significant experimental and theoretical barriers that have limited model usefulness. Recently, many of these barriers have come down, suggesting that considerable progress toward creating these long-sought models may be possible in the near term.

Role of protein dynamics in ion selectivity and allosteric coupling in the NaK channel.

Flux-dependent inactivation that arises from functional coupling between the inner gate and the selectivity filter is widespread in ion channels. The structural basis of this coupling has only been well characterized in KcsA. Here we present NMR data demonstrating structural and dynamic coupling between the selectivity filter and intracellular constriction point in the bacterial nonselective cation channel, NaK. This transmembrane allosteric communication must be structurally different from KcsA because the NaK selectivity filter does not collapse under low-cation conditions. Comparison of NMR spectra of the nonselective NaK and potassium-selective NaK2K indicates that the number of ion binding sites in the selectivity filter shifts the equilibrium distribution of structural states throughout the channel. This finding was unexpected given the nearly identical crystal structure of NaK and NaK2K outside the immediate vicinity of the selectivity filter. Our results highlight the tight structural and dynamic coupling between the selectivity filter and the channel scaffold, which has significant implications for channel function. NaK offers a distinct model to study the physiologically essential connection between ion conduction and channel gating.

Orbital Emphysema: A Rare Postoperative Complication.

Orbital emphysema can be a rare and severe postoperative complication. Fast and critical diagnosis is essential to avoid permanent visual loss to the patient. Therefore, a case of a male patient victim of a motorcycle accident with a postoperative complication of orbital emphysema has been presented. The immediate diagnosis and treatment of the orbital emphysema revealed to be the main success factors for the resolution of this complication.

Bilateral Coronoid Hyperplasia in a 43-Year-Old Patient Treated With Intraoral Coronoidectomy.

The mandibular coronoid hyperplasia can be classified as a congenital or development change of the temporomandibular joint. This condition occurs due to a no-neoplasic growth of the coronoid process to the infratemporal fossa. Thus, this part of the bone impacts in the posterior face of the zygomatic bone causing limitation of the mouth opening. The aim of this paper is to report a clinical case of a 43-year-old male with mouth-opening limitation 28 years ago. After clinical and computed tomographic examinations, he was diagnosed with bilateral mandibular coronoid hyperplasia. The treatment proposed was a bilateral coronoidectomy by intraoral approach. In a 1-month postoperative period, the patient reported improvement of the painful complaints and mouth opening. After 1 year, the patient recovered the mouth opening improving his quality of life and there were no more complaints.

Dental Infection and Pregnancy: the Lack of Treatment by the Dental Professional Evolving to a Complex Maxillofacial Infection.

Infections of the maxillofacial complex caused by caries disease are common in dental practice. The professionals have to have technical knowledge to treat it at the onset of the condition and avoid the spread to deep anatomical spaces of face and neck, which can implicate in a risk of patients' life.In Brazil, current dental professionals usually denied oral surgical treatments in patients with some clinical conditions, not because of fear to resolve it but for lack of knowledge to treat it. An example of these conditionals is pregnancy. It is well known that during the pregnancy period, the patient can be treated in the correct period of gestation. Early diagnosis is crucial for effective therapy in serious infections. The treatment has to be crucial during pregnancy because of the potentially fatal situation that the disease can create to the pregnant woman and the fetus.The aim of this article is to demonstrate a case of dental caries in a pregnant patient, which was evaluated by other professionals and had the treatment denied, evolving to a serious maxillofacial infection.

A novel NaV1.5 voltage sensor mutation associated with severe atrial and ventricular arrhythmias.

BACKGROUND: Inherited autosomal dominant mutations in cardiac sodium channels (NaV1.5) cause various arrhythmias, such as long QT syndrome and Brugada syndrome. Although dozens of mutations throughout the protein have been reported, there are few reported mutations within a voltage sensor S4 transmembrane segment and few that are homozygous. Here we report analysis of a novel lidocaine-sensitive recessive mutation, p.R1309H, in the NaV1.5 DIII/S4 voltage sensor in a patient with a complex arrhythmia syndrome. METHODS AND RESULTS: We expressed the wild type or mutant NaV1.5 heterologously for analysis with the patch-clamp and voltage clamp fluorometry (VCF) techniques. p.R1309H depolarized the voltage-dependence of activation, hyperpolarized the voltage-dependence of inactivation, and slowed recovery from inactivation, thereby reducing the channel availability at physiologic membrane potentials. Additionally, p.R1309H increased the "late" Na(+) current. The location of the mutation in DIIIS4 prompted testing for a gating pore current. We observed an inward current at hyperpolarizing voltages that likely exacerbates the loss-of-function defects at resting membrane potentials. Lidocaine reduced the gating pore current. CONCLUSIONS: The p.R1309H homozygous NaV1.5 mutation conferred both gain-of-function and loss-of-function effects on NaV1.5 channel activity. Reduction of a mutation-induced gating pore current by lidocaine suggested a therapeutic mechanism.

Kv7.1 ion channels require a lipid to couple voltage sensing to pore opening.

Voltage-gated ion channels generate dynamic ionic currents that are vital to the physiological functions of many tissues. These proteins contain separate voltage-sensing domains, which detect changes in transmembrane voltage, and pore domains, which conduct ions. Coupling of voltage sensing and pore opening is critical to the channel function and has been modeled as a protein-protein interaction between the two domains. Here, we show that coupling in Kv7.1 channels requires the lipid phosphatidylinositol 4,5-bisphosphate (PIP2). We found that voltage-sensing domain activation failed to open the pore in the absence of PIP2. This result is due to loss of coupling because PIP2 was also required for pore opening to affect voltage-sensing domain activation. We identified a critical site for PIP2-dependent coupling at the interface between the voltage-sensing domain and the pore domain. This site is actually a conserved lipid-binding site among different K(+) channels, suggesting that lipids play an important role in coupling in many ion channels.

Histomorphological and Histomorphometric Analyses of Grade IV Commercially Pure Titanium and Grade V Ti-6Al-4V Titanium Alloy Implant Substrates: An In Vivo Study in Dogs.

PURPOSE: To evaluate the bone response to grade IV commercially pure titanium (G4) relative to Ti-6Al-4V (G5). MATERIALS AND METHODS: Implant surface topography was characterized by optical interferometry and scanning electron microscopy (SEM). Thirty-six implants (Signo Vinces, n = 18 per group) were installed in the radius of 18 dogs. The animals were killed at 1, 3, and 6 weeks, resulting in 6 implants per group and time in vivo for bone morphology, bone-to-implant contact (BIC), and bone area fraction occupancy (BAFO) evaluation. RESULTS: SEM depicted a more uniform topography of G4 than G5. Surfaces were statistically homogeneous for Sa, Sq, and Sdr. At 1 week, new bone formation was observed within the healing connective tissue in contact with the implant surface. At 3 weeks, new bone in direct contact with the implant surface was observed at all bone regions. At 6 weeks, the healing chambers filled with woven bone depicted an onset of replacement by lamellar bone. No significant effect of substrate was detected. Time presented an effect on BIC and BAFO (P < 0.001). CONCLUSION: Both titanium substrates were biocompatible and osseoconductive at the bone tissue level.