Stromal vascular fraction cell sheets angiogenic potential for tissue engineering and regenerative medicine applications

One of the biggest concerns in the Tissue Engineering field is the correct vascularization of engineered constructs. Strategies involving the use of endothelial cells are promising but adequate cell sourcing and neo-vessels stability are enduring challenges. In this work, we propose the hypoxic pre-conditioning of the stromal vascular fraction (SVF) of human adipose tissue to obtain highly angiogenic cell sheets (CS). For that, SVF was isolated after enzymatic dissociation of adipose tissue and cultured until CS formation in normoxic (pO2=21%) and hypoxic (pO2=5%) conditions for 5 and 8 days, in basal medium. Immunocytochemistry against CD31 and CD146 revealed the presence of highly branched capillary-like structures, which were far more complex for hypoxia. ELISA quantification showed increased VEGF and TIMP-1 secretion in hypoxia for 8 days of culture. In a Matrigel assay, the formation of capillary-like structures by endothelial cells was more prominent when cultured in conditioned medium recovered from the cultures in hypoxia. The same conditioned medium increased the migration of adipose stromal cells in a scratch assay, when compared with the medium from normoxia. Histological analysis after implantation of 8 days normoxic- and hypoxic-conditioned SVF CS in a hindlimb ischemia murine model showed improved formation of neo-blood vessels. Furthermore, Laser Doppler results demonstrated that the blood perfusion of the injured limb after 30 days was enhanced for the hypoxic CS group. Overall, these results suggest that SVF CS created under hypoxia can be used as functional vascularization units for tissue engineering and regenerative medicine.

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Bioactive ceramics for tissue engineering and regenerative medicine derived from marine sponges

Publicado em "Journal of tissue engineering and regenerative medicine". Vol. 8, suppl. s1 (2014)

Parents' physical victimization in childhood and current risk of child maltreatment: the mediator role of psychosomatic symptoms

Objective: To test the potential mediation effect of psychosomatic symptoms on the relationship between parents' history of childhood physical victimization and current risk for child physical maltreatment. Methods: Data from the Portuguese National Representative Study of Psychosocial Context of Child Abuse and Neglect were used. Nine-hundred and twenty-four parents completed the Childhood History Questionnaire, the Psychosomatic Scale of the Brief Symptom Inventory, and the Child Abuse Potential Inventory. Results: Mediation analysis revealed that the total effect of the childhood physical victimization on child maltreatment risk was significant. The results showed that the direct effect from the parents' history of childhood physical victimization to their current maltreatment risk was still significant once parents' psychosomatic symptoms were added to the model, indicating that the increase in psychosomatic symptomatology mediated in part the increase of parents' current child maltreatment risk. Discussion: The mediation analysis showed parents' psychosomatic symptomatology as a causal pathway through which parents' childhood history of physical victimization exerts its effect on increased of child maltreatment risk. Somatization-related alterations in stress and emotional regulation are discussed as potential theoretical explanation of our findings. A cumulative risk perspective is also discussed in order to elucidate about the mechanisms that contribute for the intergenerational continuity of child physical maltreatment.

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%.