Protein-based nanodevices for therapeutic applications

Tese de Doutoramento em Biologia Molecular e Ambiental (área de especialização em Biologia Celular e Saúde).

Patterned CNT-PDMS nanocomposites for flexible pressure sensors

This paper reports the fabrication process and characterization of a flexible pressure sensor based on polydimethylsiloxane (PDMS) and multi-walled carbon nanotubes (CNT-PDMS). The proposed approach relies on patterned CNT-PDMS nanocomposite strain gauges fabricated with SU-8 microstructures (with the micropatterns) in a low‑cost and simple fabrication process. This nanocomposite polymer is mounted over a PDMS membrane, which, in turn, lies on top of a PDMS diaphragm like structure. This configuration enables the PDMS membrane to bend when pressure is applied, thereby affecting the nanocomposite strain gauges, effectively changing their electrical resistance. Carbon nanotubes have several advantages such as excellent mechanical properties, high electrical conductivity and thermal stability. Furthermore, the measurement range of the proposed sensor can be adapted according to the application by varying the CNTs content and geometry of microstructure. In addition, the sensor’s biocompatibility, low cost and simple fabrication makes it very appealing for biomechanical strain sensing. The sensor’s sensitivity was about 0.073%ΔR/mmHg.

Flexible gastrointestinal motility pressure sensors based on aluminum thin-film strain-gauge arrays

This paper reports on an innovative approach to measuring intraluminal pressure in the upper gastrointestinal (GI) tract, especially monitoring GI motility and peristaltic movements. The proposed approach relies on thin-film aluminum strain gauges deposited on top of a Kapton membrane, which in turn lies on top of an SU-8 diaphragm-like structure. This structure enables the Kapton membrane to bend when pressure is applied, thereby affecting the strain gauges and effectively changing their electrical resistance. The sensor, with an area of 3.4 mm2, is fabricated using photolithography and standard microfabrication techniques (wet etching). It features a linear response (R2 = 0.9987) and an overall sensitivity of 2.6 mV mmHg−1. Additionally, its topology allows a high integration capability. The strain gauges’ responses to pressure were studied and the fabrication process optimized to achieve high sensitivity, linearity, and reproducibility. The sequential acquisition of the different signals is carried out by a microcontroller, with a 10-bit ADC and a sample rate of 250 Hz. The pressure signals are then presented in a user-friendly interface, developed using the Integrated Development Environment software, QtCreator IDE, for better visualization by physicians.

An epidemiological study determining blood pressure in a Portuguese cohort: the Guimaraes/Vizela study

Surveying the evolution of blood pressure (BP) levels and hypertension (HTN) prevalence is important. A stringent strategy was utilized in a population cohort study. The BP was measured at two visits at least 3 months apart, and the results were analyzed using the following two methods: the Surveillance method (three BP measurements were performed in one visit, and the results were compared with those published previously for the identical method) and the Clinical method (three measurements per visit for two visits, and the concordant results in both visits were used to determine the BP classification). A total of 2542 subjects completed the evaluation. Using the Clinical method, an average systolic/diastolic BP value of 129.8/76.8?mm?Hg was obtained, and the prevalence of HTN was 31.6%. Of the hypertensive patients, 74.3% were aware of his/her condition; 69.1% were treated and 40.8% of those treated had adequate BP control. A total of 24.7% of subjects changed his/her BP classification between visits, and 13.7% misreported HTN. Using the Surveillance method, we determined that the average global SBP has been maintained, with HTN prevalence increasing in this region, drifting from reported trends nationally and worldwide. There has been improvement in the proportion of treated and controlled subjects; however, the Surveillance method overestimated the HTN prevalence and underestimated the proportion of treated and controlled subjects. The BP levels were higher than observed worldwide in high-cardiovascular (CV) risk countries as well as higher than the minimum risk exposure level for developing CV disease.

The positive effect on ketamine as a priming adjuvant in antidepressant treatment.

Ketamine is an anesthetic with antidepressant properties. The rapid and lasting effect of ketamine observed in preclinical and clinical research makes it a promising therapeutic to improve current major depression (MD) treatment. Our work intended to evaluate whether the combined use of classic antidepressants (imipramine or fluoxetine) and ketamine would improve the antidepressant response. Using an animal model of depressive-like behavior, we show that the addition of ketamine to antidepressants anticipates the behavioral response and accelerates the neuroplastic events when compared with the use of antidepressants alone. In conclusion, our results suggest the need for a reappraisal of the current pharmacological treatment of MD.

Avaliação da toxicidade das águas do rio Cubatão (Norte) - Joinville, SC, com base em ensaios ecotoxicológicos com Daphnia magna

Dissertação de mestrado em Ecologia

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.