Fine time scaling of purifying selection on human nonsynonymous mtDNA mutations based on the worldwide population tree and mother-child pairs

A high-resolution mtDNA phylogenetic tree allowed us to look backward in time to investigate purifying selection. Purifying selection was very strong in the last 2,500 years, continuously eliminating pathogenic mutations back until the end of the Younger Dryas (∼11,000 years ago), when a large population expansion likely relaxed selection pressure. This was preceded by a phase of stable selection until another relaxation occurred in the out-of-Africa migration. Demography and selection are closely related: expansions led to relaxation of selection and higher pathogenicity mutations significantly decreased the growth of descendants. The only detectible positive selection was the recurrence of highly pathogenic nonsynonymous mutations (m.3394T>C-m.3397A>G-m.3398T>C) at interior branches of the tree, preventing the formation of a dinucleotide STR (TATATA) in the MT-ND1 gene. At the most recent time scale in 124 mother-children transmissions, purifying selection was detectable through the loss of mtDNA variants with high predicted pathogenicity. A few haplogroup-defining sites were also heteroplasmic, agreeing with a significant propensity in 349 positions in the phylogenetic tree to revert back to the ancestral variant. This nonrandom mutation property explains the observation of heteroplasmic mutations at some haplogroup-defining sites in sequencing datasets, which may not indicate poor quality as has been claimed.

Multifunctional Ti–Me (Me=Al, Cu) thin film systems for biomedical sensing devices

Ti-Me binary intermetallic thin films based on a titanium matrix doped with increasing amounts of Me (Me = Al, Cu) were prepared by magnetron sputtering (under similar conditions), aiming their application in biomedical sensing devices. The differences observed on the composition and on the micro(structural) features of the films, attributed to changes in the discharge characteristics, were correlated with the electrical properties of the intermetallic systems (Ti-Al and Ti-Cu). For the same Me exposed areas placed on the Ti target (ranging from 0.25 cm2 to 20 cm2) the Cu content increased from 3.5 at.% to 71.7 at.% in the Ti-Cu system and the Al content, in Ti-Al films, ranged from 11 to 45 at.%. The structural characterization evidenced the formation of metastable Ti-Me intermetallic phases for Al/Ti atomic ratios above 0.20 and for Cu/Ti ratios above 0.25. For lower Me concentrations, the effect of the α-Ti(Me) structure domains the overall structure. With the increase amount of the Me into Ti structure a clear trend for amorphization was observed. For both systems it was observed a significant decrease of the electrical resistivity with increasing Me/Ti atomic ratios (higher than 0.5 for Al/Ti atomic ratio and higher than 1.3 for Cu/Ti atomic ratio). Although similar trends were observed in the resistivity evolution for both systems, the Ti-Cu films presented lower resistivity values in comparison to Ti-Al system.

Exploração de dados para soluções de retalho em business intelligence

Dissertação de mestrado integrado em Engenharia de Gestão e Sistemas de Informação

Historical analysis of the Brazilian cervical cancer screening program from 2006 to 2013: a time for reflection

BACKGROUND: The Cervical Cancer Database of the Brazilian National Health Service (SISCOLO) contains information regarding all cervical cytological tests and, if properly explored, can be used as a tool for monitoring and managing the cervical cancer screening program. The aim of this study was to perform a historical analysis of the cervical cancer screening program in Brazil from 2006 to 2013. MATERIAL AND METHODS: The data necessary to calculate quality indicators were obtained from the SISCOLO, a Brazilian health system tool. Joinpoint analysis was used to calculate the annual percentage change. RESULTS: We observed important trends showing decreased rates of low-grade squamous intraepithelial lesions (LSIL) and high-grade squamous intraepithelial lesions (HSIL) and an increased rate of rejected exams from 2009 to 2013. The index of positivity was maintained at levels below those indicated by international standards; very low frequencies of unsatisfactory cases were observed over the study period, which partially contradicts the low rate of positive cases. The number of positive cytological diagnoses was below that expected, considering that developed countries with low frequencies of cervical cancer detect more lesions annually. CONCLUSIONS: The evolution of indicators from 2006 to 2013 suggests that actions must be taken to improve the effectiveness of cervical cancer control in Brazil.

Real-time monitoring of progression towards renal failure in primary care patients

First published online: December 16, 2014.

Investigations on relational control of time perception

Tese de Doutoramento em Psicologia Básica

Da pós-neotelevisão: a reconfiguração do prime-time nos canais generalistas portugueses

"Colecção: Comunicação e sociedade - 12"

Blow-up and finite time extinction for p(x, t)-curl systems arising in electromagnetism

"Available online 22 March 2016"

First- and second-time parents’ couple relationship: from pregnancy to second year postpartum

First- and second-time parents’ couple relationships were studied from early pregnancy to the second year postpartum. The Relationship Questionnaire (RQ) was administered to Portuguese couples (N = 82), first- or second-time parents, at the first, second and third pregnancy trimester, childbirth, 3 and 18 months postpartum. Adverse changes in positive and negative partner relationship dimensions were reported from early pregnancy to the second year postpartum by all participants; in the same way by mothers and fathers and by first- and second-time parents. Second-time parents reported a worse couple relationship (lower RQ-positive scores) than first-time parents, but only during pregnancy. Results from the present study suggest a decline in partner relationship quality during the transition to parenthood both in mothers and fathers, as well as in first- and second-time parents.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

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%.

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.

Consequences of the Prolonged Waiting Time for Patients Candidates for Heart Surgery

OBJECTIVE - To assess mortality and the psychological repercussions of the prolonged waiting time for candidates for heart surgery. METHODS - From July 1999 to May 2000, using a standardized questionnaire, we carried out standardized interviews and semi-structured psychological interviews with 484 patients with coronary heart disease, 121 patients with valvular heart diseases, and 100 patients with congenital heart diseases. RESULTS - The coefficients of mortality (deaths per 100 patients/year) were as follows: patients with coronary heart disease, 5.6; patients with valvular heart diseases, 12.8; and patients with congenital heart diseases, 3.1 (p<0.0001). The survival curve was lower in patients with valvular heart diseases than in patients with coronary heart disease and congenital heart diseases (p<0.001). The accumulated probability of not undergoing surgery was higher in patients with valvular heart diseases than in the other patients (p<0.001), and, among the patients with valvular heart diseases, this probability was higher in females than in males (p<0.01). Several patients experienced intense anxiety and attributed their adaptive problems in the scope of love, professional, and social lives, to not undergoing surgery. CONCLUSION - Mortality was high, and even higher among the patients with valvular heart diseases, with negative psychological and social repercussions.