Nanofibrous ε-Polycaprolactone Matrices Containing Nano-Hydroxyapatite and Humulus lupulus L. Extract: Physicochemical and Biological Characterization for Oral Applications.

Oral bone defects occur as a result of trauma, cancer, infections, periodontal diseases, and caries. Autogenic and allogenic grafts are the gold standard used to treat and regenerate damaged or defective bone segments. However, these materials do not possess the antimicrobial properties necessary to inhibit the invasion of the numerous deleterious pathogens present in the oral microbiota. In the present study, poly(ε-caprolactone) (PCL), nano-hydroxyapatite (nHAp), and a commercial extract of Humulus lupulus L. (hops) were electrospun into polymeric matrices to assess their potential for drug delivery and bone regeneration. The fabricated matrices were analyzed using scanning electron microscopy (SEM), tensile analysis, thermogravimetric analysis (TGA), FTIR assay, and in vitro hydrolytic degradation. The antimicrobial properties were evaluated against the oral pathogens Streptococcus mutans, Porphyromonas gingivalis, and Aggregatibacter actinomycetemcomitans. The cytocompatibility was proved using the MTT assay. SEM analysis established the nanostructured matrices present in the three-dimensional interconnected network. The present research provides new information about the interaction of natural compounds with ceramic and polymeric biomaterials. The hop extract and other natural or synthetic medicinal agents can be effectively loaded into PCL fibers and have the potential to be used in oral applications.

Dynamic topology optimization of 3D-Printed transtibial orthopedic implant using tunable isotropic porous metamaterials.

In this paper, we introduce the design and manufacturing process of a transtibial orthopedic implant. We used medical-grade polyurethane polymer resin to fabricate a 3D porous architected implant with tunable isotropy, employing a high-speed printing method known as Continuous Liquid Interface Production (CLIP). Our objective is to enhance the weight-bearing capabilities of the bone structures in the residual limb, thereby circumventing the traditional reliance on a natural bridge. To achieve a custom-made design, we acquire the topology and morphology of the residual limb as well as the bone structure of the tibia and fibula, utilizing computed tomography (CT) and high-resolution 3D scanning. We employed a dynamic topological optimization method, informed by gait cycle data, to effectively reduce the mass of the implant. This approach, which differs from conventional static methods, enables the quantification of variations in applied forces over time. Using the Euler-Lagrange energy approach, we propose the equations of motion for a homologous multibody model with three degrees of freedom. The versatility of the Solid Isotropic Material with Penalization (SIMP) method facilitates the integration of homogenization methods for microscale porous architectures into the optimized domain. The design of these porous architectures is based on a bias-driven tuning symmetry isotropy of a Triply Periodic Minimal Surface (Schwarz Primitive surface). The internal porosity of the structure significantly reduces weight without compromising the isotropic behavior of the implant.

Sheet-based extrusion bioprinting: a new multi-material paradigm providing mid-extrusion micropatterning control for microvascular applications.

As bioprinting advances into clinical relevance with patient-specific tissue and organ constructs, it must be capable of multi-material fabrication at high resolutions to accurately mimick the complex tissue structures found in the body. One of the most fundamental structures to regenerative medicine is microvasculature. Its continuous hierarchical branching vessel networks bridge surgically manipulatable arteries (∼1-6 mm) to capillary beds (∼10µm). Microvascular perfusion must be established quickly for autologous, allogeneic, or tissue engineered grafts to survive implantation and heal in place. However, traditional syringe-based bioprinting techniques have struggled to produce perfusable constructs with hierarchical branching at the resolution of the arterioles (∼100-10µm) found in microvascular tissues. This study introduces the novel CEVIC bioprinting device (i.e.ContinuouslyExtrudedVariableInternalChanneling), a multi-material technology that breaks the current extrusion-based bioprinting paradigm of pushing cell-laden hydrogels through a nozzle as filaments, instead, in the version explored here, extruding thin, wide cell-laden hydrogel sheets. The CEVIC device adapts the chaotic printing approach to control the width and number of microchannels within the construct as it is extruded (i.e. on-the-fly). Utilizing novel flow valve designs, this strategy can produce continuous gradients varying geometry and materials across the construct and hierarchical branching channels with average widths ranging from 621.5 ± 42.92%µm to 11.67 ± 14.99%µm, respectively, encompassing the resolution range of microvascular vessels. These constructs can also include fugitive/sacrificial ink that vacates to leave demonstrably perfusable channels. In a proof-of-concept experiment, a co-culture of two microvascular cell types, endothelial cells and pericytes, sustained over 90% viability throughout 1 week in microchannels within CEVIC-produced gelatin methacryloyl-sodium alginate hydrogel constructs. These results justify further exploration of generating CEVIC-bioprinted microvasculature, such as pre-culturing and implantation studies.

A Study of PLA Thin Film on SS 316L Coronary Stents Using a Dip Coating Technique.

The dip coating process is one of the recognized techniques used to generate polymeric coatings on stents in an easy and low-cost way. However, there is a lack of information about the influence of the process parameters of this technique on complex geometries such as stents. This paper studies the dip coating process parameters used to provide a uniform coating of PLA with a 4-10 µm thickness. A stainless-steel tube (AISI 316L) was laser-cut, electropolished, and dip-coated in a polylactic acid (PLA) solution whilst changing the process parameters. The samples were characterized to examine the coating's uniformity, thickness, surface roughness, weight, and chemical composition. FTIR and Raman investigations indicated the presence of PLA on the stent's surface, the chemical stability of PLA during the coating process, and the absence of residual chloroform in the coatings. Additionally, the water contact angle was measured to determine the hydrophilicity of the coating. Our results indicate that, when using entry and withdrawal speeds of 500 mm min-1 and a 15 s immersion time, a uniform coating thickness was achieved throughout the tube and in the stent with an average thickness of 7.8 µm.

Microbial and potentially toxic elements risk assessment in high Andean river water based on Monte Carlo simulation, Peru.

The study evaluated microbial and Potentially Toxic Elements-PTEs risks in high Andean river water in Peru using Monte Carlo simulation. A total of 144 water samples were collected from four rivers and evaluated for physicochemical parameters, PTEs and bacterial pathogens. The microbial risk analysis for exposure to pathogens present in the water was based on the probability of occurrence of diseases associated with Escherichia coli, Pseudomonas aeruginosa and enterococci. PTEs risk analysis was performed using a Monte Carlo simulation approach. The results showed that the highest microbial risk due to exposure to water contaminated by E. coli, P. aeruginosa and enterococci was recorded in the Miraflores and Chia rivers. Meanwhile, the analysis of carcinogenic and non-carcinogenic risk by PTEs in adults and children revealed that the Chia river presents a high risk of contamination by PTEs, especially the carcinogenic risk for children. The Monte Carlo simulation indicated a 56.16% and 94.85% probability of exceeding the limit value of 0.0001 for carcinogenic risk in adults and children, respectively. It can be concluded that children consuming the waters of the Chia river are potentially at risk of As toxicity.

Particle Tracking and Micromixing Performance Characterization with a Mobile Device.

Strategies to stir and mix reagents in microfluid devices have evolved concomitantly with advancements in manufacturing techniques and sensing. While there is a large array of reported designs to combine and homogenize liquids, most of the characterization has been focused on setups with two inlets and one outlet. While this configuration is helpful to directly evaluate the effects of features and parameters on the mixing degree, it does not portray the conditions for experiments that involve more than two substances required to be subsequently combined. In this work, we present a mixing characterization methodology based on particle tracking as an alternative to the most common approach to measure homogeneity using the standard deviation of pixel intensities from a grayscale image. The proposed algorithm is implemented on a free and open-source mobile application (MIQUOD) for Android devices, numerically tested on COMSOL Multiphysics, and experimentally tested on a bidimensional split and recombine micromixer and a three-dimensional micromixer with sinusoidal grooves for different Reynolds numbers and geometrical features for samples with fluids seeded with red, blue, and green microparticles. The application uses concentration field data and particle track data to evaluate up to eleven performance metrics. Furthermore, with the insights from the experimental and numerical data, a mixing index for particles (mp) is proposed to characterize mixing performance for scenarios with multiple input reagents.

Smart education system to improve the learning system with CBR based recommendation system using IoT.

Over the last few years, the research fields of intelligent learning systems have been improving the process of learning systems. Smart Tutoring System-(STS) applications have been used in e-learning. The results signify the importance of the learner's engagement in customizing a model. The design outcomes of this IoT-based personalized learning system purely work on the audience's learning requirements, their keyword search, their learning experience levels, proficiency level of subjects, and the type of the course being taught. Students spent an average of 25.67 h accessing textual materials weekly, 27.4 h accessing video assets weekly, and similarly 6.5 h accessing visual learning materials. The research analysis part concludes participants' percentage of learning as per evaluations assessment, which increases whenever the outcome analysis comes with Case-Based Reasoning classifiers-CBR based search model. The findings displayed significant differences before and after learning case by case for every learner as per chosen topic and quiz assessments: 42.57% of the students responded before learning the first question assessments whereas 74.82%, of the students responded, after completion of learning from online resources based on their choice with CBR. Recommendation Model Analysis discussed root means square error-RMSE lies from 10% to 20% for 550 students group size. The RMSE result is 24% for a size of 1600, which is low performance compared to other group sizes. This study focuses on the STS recommendation model for the slow learner group to identify required learning from various online resources.

Mechanical Properties of AISI 316L Lattice Structures via Laser Powder Bed Fusion as a Function of Unit Cell Features.

The growth of additive manufacturing processes has enabled the production of complex and smart structures. These fabrication techniques have led research efforts to focus on the application of cellular materials, which are known for their thermal and mechanical benefits. Herein, we studied the mechanical behavior of stainless-steel (AISI 316L) lattice structures both experimentally and computationally. The lattice architectures were body-centered cubic, hexagonal vertex centroid, and tetrahedron in two cell sizes and at two different rotation angles. A preliminary computational study assessed the deformation behavior of porous cylindrical samples under compression. After the simulation results, selected samples were manufactured via laser powder bed fusion. The results showed the effects of the pore architecture, unit cell size, and orientation on the reduction in the mechanical properties. The relative densities between 23% and 69% showed a decrease in the bulk material stiffness up to 93%. Furthermore, the different rotation angles resulted in a similar porosity level but different stiffnesses. The simulation analysis and experimental results indicate that the variation in the strut position with respect to the force affected the deformation mechanism. The tetrahedron unit cell showed the smallest variation in the elastic modulus and off-axis displacements due to the cell orientation. This study collected computational and experimental data for tuning the mechanical properties of lattice structures by changing the geometry, size, and orientation of the unit cell.

Predictive Modeling of Soft Stretchable Nanocomposites Using Recurrent Neural Networks.

Human skin is characterized by rough, elastic, and uneven features that are difficult to recreate using conventional manufacturing technologies and rigid materials. The use of soft materials is a promising alternative to produce devices that mimic the tactile capabilities of biological tissues. Although previous studies have revealed the potential of fillers to modify the properties of composite materials, there is still a gap in modeling the conductivity and mechanical properties of these types of materials. While traditional Finite Element approximations can be used, these methodologies tend to be highly demanding of time and processing power. Instead of this approach, a data-driven learning-based approximation strategy can be used to generate prediction models via neural networks. This paper explores the fabrication of flexible nanocomposites using polydimethylsiloxane (PDMS) with different single-walled carbon nanotubes (SWCNTs) loadings (0.5, 1, and 1.5 wt.%). Simple Recurrent Neural Networks (SRNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) models were formulated, trained, and tested to obtain the predictive sequence data of out-of-plane quasistatic mechanical tests. Finally, the model learned is applied to a dynamic system using the Kelvin-Voight model and the phenomenon known as the bouncing ball. The best predictive results were achieved using a nonlinear activation function in the SRNN model implementing two units and 4000 epochs. These results suggest the feasibility of a hybrid approach of analogy-based learning and data-driven learning for the design and computational analysis of soft and stretchable nanocomposite materials.

Drug-Eluting, Bioresorbable Cardiovascular Stents─Challenges and Perspectives.

Globally, the leading causes of natural death are attributed to coronary heart disease and type 1 and type 2 diabetes. High blood pressure levels, high cholesterol levels, smoking, and poor eating habits lead to the agglomeration of plaque in the arteries, reducing the blood flow. The implantation of devices used to unclog vessels, known as stents, sometimes results in a lack of irrigation due to the excessive proliferation of endothelial tissue within the blood vessels and is known as restenosis. The use of drug-eluting stents (DESs) to deliver antiproliferative drugs has led to the development of different encapsulation techniques. However, due to the potency of the drugs used in the initial stent designs, a chronic inflammatory reaction of the arterial wall known as thrombosis can cause a myocardial infarction (MI). One of the most promising drugs to reduce this risk is everolimus, which can be encapsulated in lipid systems for controlled release directly into the artery. This review aims to discuss the current status of stent design, fabrication, and functionalization. Variables such as the mechanical properties, metals and their alloys, drug encapsulation and controlled elution, and stent degradation are also addressed. Additionally, this review covers the use of polymeric surface coatings on stents and the recent advances in layer-by-layer coating and drug delivery. The advances in nanoencapsulation techniques such as liposomes and micro- and nanoemulsions and their functionalization in bioresorbable, drug-eluting stents are also highlighted.

Soft Tissue Hybrid Model for Real-Time Simulations.

In this article, a recent formulation for real-time simulation is developed combining the strain energy density of the Spring Mass Model (SMM) with the equivalent representation of the Strain Energy Density Function (SEDF). The resulting Equivalent Energy Spring Model (EESM) is expected to provide information in real-time about the mechanical response of soft tissue when subjected to uniaxial deformations. The proposed model represents a variation of the SMM and can be used to predict the mechanical behavior of biological tissues not only during loading but also during unloading deformation states. To assess the accuracy achieved by the EESM, experimental data was collected from liver porcine samples via uniaxial loading and unloading tensile tests. Validation of the model through numerical predictions achieved a refresh rate of 31 fps (31.49 ms of computation time for each frame), achieving a coefficient of determination R2 from 93.23% to 99.94% when compared to experimental data. The proposed hybrid formulation to characterize soft tissue mechanical behavior is fast enough for real-time simulation and captures the soft material nonlinear virgin and stress-softened effects with high accuracy.

Low-Cost Light-Based GelMA 3D Bioprinting via Retrofitting: Manufacturability Test and Cell Culture Assessment.

Light-based bioprinter manufacturing technology is still prohibitively expensive for organizations that rely on accessing three-dimensional biological constructs for research and tissue engineering endeavors. Currently, most of the bioprinting systems are based on commercial-grade-based systems or modified DIY (do it yourself) extrusion apparatuses. However, to date, few examples of the adoption of low-cost equipment have been found for light-based bioprinters. The requirement of large volumes of bioinks, their associated cost, and the lack of information regarding the parameter selection have undermined the adoption of this technology. This paper showcases the retrofitting and assessing of a low-cost Light-Based 3D printing system for tissue engineering. To evaluate the potential of a proposed design, a manufacturability test for different features, machine parameters, and Gelatin Methacryloyl (GelMA) concentrations for 7.5% and 10% was performed. Furthermore, a case study of a previously seeded hydrogel with C2C12 cells was successfully implemented as a proof of concept. On the manufacturability test, deviational errors were found between 0.7% to 13.3% for layer exposure times of 15 and 20 s. Live/Dead and Actin-Dapi fluorescence assays after 5 days of culture showed promising results in the cell viability, elongation, and alignment of 3D bioprinted structures. The retrofitting of low-cost equipment has the potential to enable researchers to create high-resolution structures and three-dimensional in vitro models.

Characterization of Porous Scaffolds Fabricated by Joining Stacking Based Laser Micro-Spot Welding (JS-LMSW) for Tissue Engineering Applications.

A novel manufacturing approach was used to fabricate metallic scaffolds. A calibration of the laser cutting process was performed using the kerf width compensation in the calculations of the tool trajectory. Welding defects were studied through X-ray microtomography. Penetration depth and width resulted in relative errors of 9.4%, 1.0%, respectively. Microhardness was also measured, and the microstructure was studied in the base material. The microhardness values obtained were 400 HV, 237 HV, and 215 HV for the base material, HAZ, and fusion zone, respectively. No significant difference was found between the microhardness measurement along with different height positions of the scaffold. The scaffolds' dimensions and porosity were measured, their internal architecture was observed with micro-computed tomography. The results indicated that geometries with dimensions under 500 µm with different shapes resulted in relative errors of ~2.7%. The fabricated scaffolds presented an average compressive modulus ~13.15 GPa, which is close to cortical bone properties. The proposed methodology showed a promising future in bone tissue engineering applications.

E-Skin Development and Prototyping via Soft Tooling and Composites with Silicone Rubber and Carbon Nanotubes.

The strategy of embedding conductive materials on polymeric matrices has produced functional and wearable artificial electronic skin prototypes capable of transduction signals, such as pressure, force, humidity, or temperature. However, these prototypes are expensive and cover small areas. This study proposes a more affordable manufacturing strategy for manufacturing conductive layers with 6 × 6 matrix micropatterns of RTV-2 silicone rubber and Single-Walled Carbon Nanotubes (SWCNT). A novel mold with two cavities and two different micropatterns was designed and tested as a proof-of-concept using Low-Force Stereolithography-based additive manufacturing (AM). The effect SWCNT concentrations (3 wt.%, 4 wt.%, and 5 wt.%) on the mechanical properties were characterized by quasi-static axial deformation tests, which allowed them to stretch up to ~160%. The elastomeric soft material's hysteresis energy (Mullin's effect) was fitted using the Ogden-Roxburgh model and the Nelder-Mead algorithm. The assessment showed that the resulting multilayer material exhibits high flexibility and high conductivity (surface resistivity ~7.97 × 104 Ω/sq) and that robust soft tooling can be used for other devices.

LAPKaans: Tool-Motion Tracking and Gripping Force-Sensing Modular Smart Laparoscopic Training System.

Laparoscopic surgery demands highly skilled surgeons. Traditionally, a surgeon's knowledge is acquired by operating under a mentor-trainee method. In recent years, laparoscopic simulators have gained ground as tools in skill acquisition. Despite the wide range of laparoscopic simulators available, few provide objective feedback to the trainee. Those systems with quantitative feedback tend to be high-end solutions with limited availability due to cost. A modular smart trainer was developed, combining tool-tracking and force-using employing commercially available sensors. Additionally, a force training system based on polydimethylsiloxane (PDMS) phantoms for sample stiffness differentiation is presented. This prototype was tested with 39 subjects, between novices (13), intermediates (13), and experts (13), evaluating execution differences among groups in training exercises. The estimated cost is USD $200 (components only), not including laparoscopic instruments. The motion system was tested for noise reduction and position validation with a mean error of 0.94 mm. Grasping force approximation showed a correlation of 0.9975. Furthermore, differences in phantoms stiffness effectively reflected user manipulation. Subject groups showed significant differences in execution time, accumulated distance, and mean and maximum applied grasping force. Accurate information was obtained regarding motion and force. The developed force-sensing tool can easily be transferred to a clinical setting. Further work will consist on a validation of the simulator on a wider range of tasks and a larger sample of volunteers.

Laser Surface Texturing and Electropolishing of CoCr and Ti6Al4V-ELI Alloys for Biomedical Applications.

The interplay between a prosthetic and tissue represents an important factor for the fixation of orthopedic implants. Laser texturing tests and electropolishing were performed on two materials used in the fabrication of medical devices, i.e., CoCr and Ti6Al4V-ELI alloys. The material surface was textured with a diode-pumped solid state (DPSS) laser and its effect on the surface quality and material modification, under different combinations of laser power and marking speed, were investigated. Our results indicate that an increment of energy per unit length causes an incremental trend in surface roughness parameters. Additionally, phase transformation on the surface of both alloys was achieved. Chemical analysis by energy dispersive X-ray spectrometer (EDX) shows the formation of (Co(Cr,Mo)) phase and the M23C6 precipitate on the CoCr surface; while quantitative analysis of the X-ray diffractometer (XRD) results demonstrates the oxidation of the Ti alloy with the formation of Ti2O and Ti6O from the reduction of the α-Ti phase. The behaviors were both related with an increase of the energy per unit length. Control of the final surface roughness was achieved by an electropolishing post-treatment, minimizing the as-treated values. After polishing, a reduction of surface roughness parameters was obtained in a range between 3% and 44%, while no changes in chemical composition or present phases were observed.

Characterization of Soft Tooling Photopolymers and Processes for Micromixing Devices with Variable Cross-Section.

In this paper, we characterized an assortment of photopolymers and stereolithography processes to produce 3D-printed molds and polydimethylsiloxane (PDMS) castings of micromixing devices. Once materials and processes were screened, the validation of the soft tooling approach in microfluidic devices was carried out through a case study. An asymmetric split-and-recombine device with different cross-sections was manufactured and tested under different regime conditions (10 < Re < 70). Mixing performances between 3% and 96% were obtained depending on the flow regime and the pitch-to-depth ratio. The study shows that 3D-printed soft tooling can provide other benefits such as multiple cross-sections and other potential layouts on a single mold.

Evaluación de la dinámica cardíaca durante 16 horas mediante una ley matemática exponencial

Marco teórico. Con base en la teoría de los sistemas dinámicos, fue establecida una ley matemática exponencial que al ser aplicada a los sistemas cardíacos caóticos, permitió cuantificar estados de normalidad y enfermedad, siendo también posible encontrar el número total de dinámicas cardíacas a partir de esta comprensión matemática del fenómeno. En este estudio se evaluó la aplicabilidad clínica y utilidad diagnóstica de la ley exponencial en 300 registros electrocardiográficos continuos y estudios Holter, en 16 horas. Material y métodos. A partir de 300 registros electrocardiográficos continuos y estudios Holter, dentro de los cuales 50 presentaban diagnóstico convencional de normalidad y los restantes 250 algún tipo de patología, se construyeron los mapas de retardo para cada dinámica cardíaca. Seguidamente, se calculó la dimensión fractal y los espacios de ocupación de los atractores. Se realizó la evaluación matemática en 16 y 21 horas, mediante la ley exponencial, y se llevó a cabo la validación estadística. Resultados. Se obtuvo que los valores para la rejilla Kp entre 203 y 346 correspondían a normalidad, mientras que valores entre 35 y 197 correspondían a enfermedad, en 16 horas. El valor encontrado para el coeficiente Kappa fue de 1, la sensibilidad y especificidad fueron de 100%. Conclusiones. Se logró establecer que la metodología matemática permite realizar diagnósticos certeros en 16 horas, comprobándose su aplicabilidad en 300 registros electrocardiográficos.

Background. Based on the theory of dynamic systems, an exponential mathematical law was established that, when applied to chaotic cardiac systems, allowed to quantify states of normality and disease, being also possible to find the total number of cardiac dynamics from This mathematical understanding of the phenomenon, in this study, evaluated the clinical applicability and diagnostic utility of the exponential law in 300 continuous electrocardiographic records and Holter tests, in 16 hours. Methods. With 300 continuous electrocardiographic registers and Holter tests, of which 50 presented conventional diagnosis of normality and the remaining 250 some type of pathology, the delay maps were constructed for each cardiac dynamics. Next, the fractal dimension and the spaces of occupation of the attractors were calculated. It was made the mathematical evaluation in 16 and 21 hours, using the exponential law and the statistical validation was performed. Results. It was obtained that the values for the grid Kp between 203 and 346 corresponded to normality, whereas values between 35 and 197 corresponded to disease, in 16 hours. The value found for the Kappa coefficient was 1; the sensitivity and specificity were 100%. Conclusion. It was possible to establish that the mathematical methodology allows to make accurate diagnoses in 16 hours, being proved its applicability in 300 electrocardiographic registers.

Introdução. Com base na teoria de sistemas dinâmicos, foi criada uma lei matemática exponencial que quando aplicada a sistemas cardíacos caóticos permitidos estados Quantificar de normalidade e doença, também é possível encontrar o número total de dinâmica cardíaca de Essa compreensão matemática do fenômeno, neste estudo, avaliou a aplicabilidade clínica e a utilidade diagnóstica da lei exponencial em 300 registros eletrocardiográficos contínuos e estudos Holter, em 16 horas. Material e métodos. A partir de 300 registros eletrocardiográficos contínuos e estudos Holter, dentre os quais 50 apresentaram diagnóstico normal de normalidade e os demais 250 algum tipo de patologia, os mapas de atraso para cada dinâmica cardíaca foram construídos. Em seguida, calculou-se a dimensão fractal e os espaços de ocupação dos atratores. A avaliação matemática foi realizada às 16 e 21 horas, por meio da lei exponencial, e a validação estatística foi realizada. Resultados. Obteve-se que os valores da malha do Kp entre 203 e 346 correspondiam à normalidade, enquanto os valores entre 35 e 197 correspondiam à doença, em 16 horas. O valor encontrado para o coeficiente Kappa foi de 1, a sensibilidade e especificidade foram de 100%. Conclusões. Estabeleceu-se que a metodologia matemática permite realizar diagnósticos precisos em 16 horas, verificando sua aplicabilidade em 300 registros eletrocardiográficos.

Influence of Controlled Cooling on Crystallinity of Poly (L-Lactic Acid) Scaffolds after Hydrolytic Degradation.

The use of hybrid manufacturing to produce bimodal scaffolds has represented a great advancement in tissue engineering. These scaffolds provide a favorable environment in which cells can adhere and produce new tissue. However, there are several areas of opportunity to manufacture structures that provide enough strength and rigidity, while also improving chemical integrity. As an advancement in the manufacturing process of scaffolds, a cooling system was introduced in a fused deposition modeling (FDM) machine to vary the temperature on the printing bed. Two groups of polylactic acid (PLA) scaffolds were then printed at two different bed temperatures. The rate of degradation was evaluated during eight weeks in Hank's Balanced Salt Solution (HBSS) in a controlled environment (37 °C-120 rpm) to assess crystallinity. Results showed the influence of the cooling system on the degradation rate of printed scaffolds after the immersion period. This phenomenon was attributable to the mechanism associated with alkaline hydrolysis, where a higher degree of crystallinity obtained in one group induced greater rates of mass loss. The overall crystallinity was observed, through differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), and Fourier transformed infrared spectroscopy (FTIR) analysis, to increase with time because of the erosion of some amorphous parts after immersion.