Functionalized nanostructures with application in regenerative medicine

In the last decade, both regenerative medicine and nanotechnology have been broadly developed leading important advances in biomedical research as well as in clinical practice. The manipulation on the molecular level and the use of several functionalized nanoscaled materials has application in various fields of regenerative medicine including tissue engineering, cell therapy, diagnosis and drug and gene delivery. The themes covered in this review include nanoparticle systems for tracking transplanted stem cells, self-assembling peptides, nanoparticles for gene delivery into stem cells and biomimetic scaffolds useful for 2D and 3D tissue cell cultures, transplantation and clinical application.

Perspectives for the treatment of brucellosis in the 21st century: the Ioannina recommendations

Summary Points Brucellosis remains the commonest anthropozoonosis worldwide, and its treatment remains complex, requiring protracted administration of more than one antibiotic. In November 2006, a consensus meeting aimed at reaching a common specialist statement on the treatment of brucellosis was held in Ioannina, Greece under the auspices of the International Society of Chemotherapy and the Institute of Continuing Medical Education of Ioannina. The author panel suggests that the optimal treatment of uncomplicated brucellosis should be based on a six-week regimen of doxycycline combined either with streptomycin for 2–3 weeks, or rifampicin for six weeks. Gentamicin may be considered an acceptable alternative to streptomycin, while all other regimens/combinations should be considered second-line. The development of a common global therapeutic language for human brucellosis, and future, properly conducted clinical trials would definitely solve controversies regarding the disease.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Efectividad comparativa del seguimiento remoto a personas con marcapasos cardíacos frente al convencional: calidad de vida a los 6 meses.

BACKGROUND The use of remote follow-up (RF) of people with pacemakers (PM) is limited in comparison to the hospital modality (HS), being still poor the scientific evidence that shows their comparative effectiveness. The aim of this study was to compare the quality of life in individuals with different modalities of follow-up. METHODS Controlled, not randomized nor masked clinical trial, with data collection at pre and post-implantation of pacemakers during the 6 months follow-up. All patients over 18 years-old who were implanted a PM during the study period were selected (n = 83), and they were assigned to RF (n = 30) or HF (n = 53) groups according to their personal characteristics and patient's preferences. Baseline characteristics and number of visits to the hospital were analysed, the EuroQol-5D (EQ5D) questionnaire was administered to evaluate the health-related quality of life, and Duke Activity Status Index (DASI) to assess the functional capacity. RESULTS There were no significant differences between both groups in relation to the baseline analysis, EQ5D (RF:0.7299; HF:0.6769) and DASI (RF:21.41; HF:19.99). At 6 months the quality of life was improved in both groups (EQ5D RF:0.8613; HF:0.8175; p = 0,439) still without significant differences between them. DASI score was similar to baseline (20.51 vs 21.80). RF group performed less transmissions/visits per patient (1.57) than hospital group (1.96; relative reduction 31%; p = 0.015). CONCLUSIONS Remote follow-up of people with pacemakers might be considered as an equivalent option to the hospital follow-up in relation to the quality of life and it reduces the number of hospital visits.