Phenylenevinylene Systems: The Oligomer Approach

Among conducting polymers, poly-p-phenylenevinylenes (PPVs) have attained a special place in polymer electronics. The optoelectronic properties initially exposed by PPVs in organic light-emitting diodes (OLEDs) turned these organic electronic conjugated systems from the solo academic interest into a technologically very promising area. The easiness of the tuning of their optoelectronic properties through synthetic modifications make PPVs an outstanding and suitable compound for technological applications and fundamental science development. Unfortunately, the synthesis and structural optoelectronic characterization of novel PPVs is a long and difficult task that sometimes yields unclear results. However, phenylenevinylene oligomers (oPV) can be synthesized and characterized in a very straightforward manner, and their performance in novel applications can be directly related to their structural analogue polymer, methodology designated as the oligomer approach. Herein, we describe the oligomer approach using the Mizoroki-Heck reaction as a synthetic route for oPVs and PPVs, and the importance of an extensive characterization for novel applications, such as photocatalysis and matrix-assisted laser desorption/ionization (MALDI) matrices, where these electronic conjugated systems have very promising applications

Towards Automated Semantic Segmentation in Mammography Images

Mammography images are widely used to detect non-palpable breast lesions or nodules, preventing cancer and providing the opportunity to plan interventions when necessary. The identification of some structures of interest is essential to make a diagnosis and evaluate image adequacy. Thus, computer-aided detection systems can be helpful in assisting medical interpretation by automatically segmenting these landmark structures. In this paper, we propose a deep learning-based framework for the segmentation of the nipple, the pectoral muscle, the fibroglandular tissue, and the fatty tissue on standard-view mammography images. We introduce a large private segmentation dataset and extensive experiments considering different deep-learning model architectures. Our experiments demonstrate accurate segmentation performance on variate and challenging cases, showing that this framework can be integrated into clinical practice.Comment: 6 page

Development of a software tool for the estimation of the autonomic nervous system performance by heart rate variability, QT segment variability and QT dispersion

La evaluación del estado del sistema nervioso autónomo (SNA) se puede realizar mediante la medición de la variabilidad de la frecuencia cardiaca, la variabilidad del segmento QT y la dispersión del segmento QT. En este trabajo se presenta la implementación de estas estimaciones mediante algoritmos basados en la transformadaWavelet y la estimación espectral de Yule-Walker. Registros electrocardiográfcos de 20 minutos de duración fueron evaluados, con 15 minutos tomados de forma continua. Parámetros de la fuctuación cardiaca fueron tomados de una población de 92 pacientes, quienes presentaron el primer accidente cerebrovascular y llevaron a cabo un protocolo de inclusión estricto para evaluar su variabilidad en la frecuencia cardiaca. Las pruebas estadísticas se realizaron para determinar la repetibilidad de las mediciones.The evaluation of the Autonomic Nervous System (ANS) status can be performed by the measurement of the cardiac frequency variability, the variability of the QT segment and the dispersion of the QT segment. This paper presents the implementation of these estimations by means of Wavelet Transform-based algorithms and the Yule-Walker’s spectral estimation. Electrocardiographic records 20 minutes long were evaluated, having 15 minutes taken in a continuous way. Parameters of cardiac fuctuation were taken out from a population of 92 patients, who presented frst stroke and carried out with a strict inclusion protocol to evaluate their cardiac frequency variability. Statistical tests were performed to determine the repeatability of the measurements.&nbsp

Development of a software tool for the estimation of the autonomic nervous system performance by heart rate variability, QT segment variability and QT dispersion

La evaluación del estado del sistema nervioso autónomo (SNA) se puede realizar mediante la medición de la variabilidad de la frecuencia cardiaca, la variabilidad del segmento QT y la dispersión del segmento QT. En este trabajo se presenta la implementación de estas estimaciones mediante algoritmos basados en la transformadaWavelet y la estimación espectral de Yule-Walker. Registros electrocardiográfcos de 20 minutos de duración fueron evaluados, con 15 minutos tomados de forma continua. Parámetros de la fuctuación cardiaca fueron tomados de una población de 92 pacientes, quienes presentaron el primer accidente cerebrovascular y llevaron a cabo un protocolo de inclusión estricto para evaluar su variabilidad en la frecuencia cardiaca. Las pruebas estadísticas se realizaron para determinar la repetibilidad de las mediciones.The evaluation of the Autonomic Nervous System (ANS) status can be performed by the measurement of the cardiac frequency variability, the variability of the QT segment and the dispersion of the QT segment. This paper presents the implementation of these estimations by means of Wavelet Transform-based algorithms and the Yule-Walker’s spectral estimation. Electrocardiographic records 20 minutes long were evaluated, having 15 minutes taken in a continuous way. Parameters of cardiac fuctuation were taken out from a population of 92 patients, who presented frst stroke and carried out with a strict inclusion protocol to evaluate their cardiac frequency variability. Statistical tests were performed to determine the repeatability of the measurements.&nbsp

Scaffold proteins LACK and TRACK as potential drug targets in kinetoplastid parasites: Development of inhibitors

Parasitic diseases cause similar to 500,000 deaths annually and remain a major challenge for therapeutic development. Using a rational design based approach, we developed peptide inhibitors with anti-parasitic activity that were derived from the sequences of parasite scaffold proteins LACK (Leishmania's receptor for activated C-kinase) and TRACK (Trypanosoma receptor for activated C-kinase). We hypothesized that sequences in LACK and TRACK that are conserved in the parasites, but not in the mammalian ortholog, RACK (Receptor for activated C-kinase), may be interaction sites for signaling proteins that are critical for the parasites' viability. One of these peptides exhibited leishmanicidal and trypanocidal activity in culture. Moreover, in infected mice, this peptide was also effective in reducing parasitemia and increasing survival without toxic effects. The identified peptide is a promising new anti-parasitic drug lead, as its unique features may limit toxicity and drug-resistance, thus overcoming central limitations of most anti-parasitic drugs. (C) 2016 The Authors. Published by Elsevier Ltd on behalf of Australian Society for Parasitology.National Institutes of HealthStanford Univ, Sch Med, Dept Chem & Syst Biol, Stanford, CA 94305 USAUniv Sao Paulo, Inst Quim, Dept Bioquim, BR-05508 Sao Paulo, SP, BrazilMcGill Univ, Res Inst, Natl Reference Ctr Parasitol, Montreal, PQ, CanadaUniv Autonoma Yucatan, Ctr Invest Reg Dr Hideyo Noguchi, Parasitol Lab, Merida, Yucatan, MexicoStanford Univ, Biomat & Adv Drug Delivery Lab, Stanford, CA 94305 USAUniv Estadual Campinas, Inst Chem, Campinas, SP, BrazilUniv Fed Sao Paulo, Dept Ciencias Biol, Campus Diadema, Sao Paulo, BrazilMcGill Univ, Inst Parasitol, Quebec City, PQ, CanadaMcGill Univ, Ctr Host Parasite Interact, Quebec City, PQ, CanadaUniv Fed Sao Paulo, Dept Ciencias Biol, Campus Diadema, Sao Paulo, BrazilNIH: TW008781-01C-IDEANIH: AI078505Web of Scienc

Cross-Sectional Analysis of Late HAART Initiation in Latin America and the Caribbean: Late Testers and Late Presenters

Background: Starting HAART in a very advanced stage of disease is assumed to be the most prevalent form of initiation in HIV-infected subjects in developing countries. Data from Latin America and the Caribbean is still lacking. Our main objective was to determine the frequency, risk factors and trends in time for being late HAART initiator (LHI) in this region. Methodology: Cross-sectional analysis from 9817 HIV-infected treatment-naive patients initiating HAART at 6 sites (Argentina, Chile, Haiti, Honduras, Peru and Mexico) from October 1999 to July 2010. LHI had CD4$^+$ count $\leq$200cells/mm$^3$ prior to HAART. Late testers (LT) were those LHI who initiated HAART within 6 months of HIV diagnosis. Late presenters (LP) initiated after 6 months of diagnosis. Prevalence, risk factors and trends over time were analyzed. Principal Findings: Among subjects starting HAART (n = 9817) who had baseline CD4$^+$ available (n = 8515), 76% were LHI: Argentina (56%[95%CI:52–59]), Chile (80%[95%CI:77–82]), Haiti (76%[95%CI:74–77]), Honduras (91%[95%CI:87–94]), Mexico (79%[95%CI:75–83]), Peru (86%[95%CI:84–88]). The proportion of LHI statistically changed over time (except in Honduras) ($p\leq0.02$; Honduras p = 0.7), with a tendency towards lower rates in recent years. Males had increased risk of LHI in Chile, Haiti, Peru, and in the combined site analyses (CSA). Older patients were more likely LHI in Argentina and Peru (OR 1.21 per +10-year of age, 95%CI:1.02–1.45; OR 1.20, 95%CI:1.02–1.43; respectively), but not in CSA (OR 1.07, 95%CI:0.94–1.21). Higher education was associated with decreased risk for LHI in Chile (OR 0.92 per +1-year of education, 95%CI:0.87–0.98) (similar trends in Mexico, Peru, and CSA). LHI with date of HIV-diagnosis available, 55% were LT and 45% LP. Conclusion: LHI was highly prevalent in CCASAnet sites, mostly due to LT; the main risk factors associated were being male and older age. Earlier HIV-diagnosis and earlier treatment initiation are needed to maximize benefits from HAART in the region

Peces de la estrella fluvial inírida: ríos Guaviare, Inírida, Atabapo y Orinoco (Orinoquía colombiana)

Data derived from the literature supplemented with new collections made in the Inírida Fluvial Star (15th to 27th February 2008) reveal a species richness of 470 fishes species grouped in 224 genera, 40 families, and 10 orders. Its represents the higher species richness in the Orinoco River Basin. Orders with the largest numbers of species in the Star were Characiformes (237 species), Siluriformes (136 species), Perciformes (60 species), and Gymnotiformes (19 species), with the remaining 6 orders having from 1 to 7 species. At the family level, the Characidae has the greatest number of species (141 species), followed by the Cichlidae (55 species), Loricariidae (39 species), Pimelodidae (23 species), and Anostomidae (21 species); the remaining 35 families have 1 to 18 species. Present data indicate that 4 species are new records for the Orinoco River Basin and 19 are new for Colombia. The species richness by river was: 280 for the Inírida, 238 for Atabapo, 224 for Guaviare, and 82 for the Orinoco. In the Inírida Fluvial Star 335 species have commercial value as ornamentals, and 132 are harvested for food

Sympathetic nervous activation, mitochondrial dysfunction and outcome in acutely decompensated cirrhosis: the metabolomic prognostic models (CLIF-C MET)

Background and aims Current prognostic scores of patients with acutely decompensated cirrhosis (AD), particularly those with acute-on-chronic liver failure (ACLF), underestimate the risk of mortality. This is probably because systemic inflammation (SI), the major driver of AD/ACLF, is not reflected in the scores. SI induces metabolic changes, which impair delivery of the necessary energy for the immune reaction. This investigation aimed to identify metabolites associated with short-term (28-day) death and to design metabolomic prognostic models. Methods Two prospective multicentre large cohorts from Europe for investigating ACLF and development of ACLF, CANONIC (discovery, n=831) and PREDICT (validation, n=851), were explored by untargeted serum metabolomics to identify and validate metabolites which could allow improved prognostic modelling. Results Three prognostic metabolites strongly associated with death were selected to build the models. 4-Hydroxy-3-methoxyphenylglycol sulfate is a norepinephrine derivative, which may be derived from the brainstem response to SI. Additionally, galacturonic acid and hexanoylcarnitine are associated with mitochondrial dysfunction. Model 1 included only these three prognostic metabolites and age. Model 2 was built around 4-hydroxy-3-methoxyphenylglycol sulfate, hexanoylcarnitine, bilirubin, international normalised ratio (INR) and age. In the discovery cohort, both models were more accurate in predicting death within 7, 14 and 28 days after admission compared with MELDNa score (C-index: 0.9267, 0.9002 and 0.8424, and 0.9369, 0.9206 and 0.8529, with model 1 and model 2, respectively). Similar results were found in the validation cohort (C-index: 0.940, 0.834 and 0.791, and 0.947, 0.857 and 0.810, with model 1 and model 2, respectively). Also, in ACLF, model 1 and model 2 outperformed MELDNa 7, 14 and 28 days after admission for prediction of mortality. Conclusions Models including metabolites (CLIF-C MET) reflecting SI, mitochondrial dysfunction and sympathetic system activation are better predictors of short-term mortality than scores based only on organ dysfunction (eg, MELDNa), especially in patients with ACLF

Sympathetic nervous activation, mitochondrial dysfunction and outcome in acutely decompensated cirrhosis: the metabolomic prognostic models (CLIF-C MET)

Background and aims: Current prognostic scores of patients with acutely decompensated cirrhosis (AD), particularly those with acute-on-chronic liver failure (ACLF), underestimate the risk of mortality. This is probably because systemic inflammation (SI), the major driver of AD/ACLF, is not reflected in the scores. SI induces metabolic changes, which impair delivery of the necessary energy for the immune reaction. This investigation aimed to identify metabolites associated with short-term (28-day) death and to design metabolomic prognostic models. Methods: Two prospective multicentre large cohorts from Europe for investigating ACLF and development of ACLF, CANONIC (discovery, n=831) and PREDICT (validation, n=851), were explored by untargeted serum metabolomics to identify and validate metabolites which could allow improved prognostic modelling. Results: Three prognostic metabolites strongly associated with death were selected to build the models. 4-Hydroxy-3-methoxyphenylglycol sulfate is a norepinephrine derivative, which may be derived from the brainstem response to SI. Additionally, galacturonic acid and hexanoylcarnitine are associated with mitochondrial dysfunction. Model 1 included only these three prognostic metabolites and age. Model 2 was built around 4-hydroxy-3-methoxyphenylglycol sulfate, hexanoylcarnitine, bilirubin, international normalised ratio (INR) and age. In the discovery cohort, both models were more accurate in predicting death within 7, 14 and 28 days after admission compared with MELDNa score (C-index: 0.9267, 0.9002 and 0.8424, and 0.9369, 0.9206 and 0.8529, with model 1 and model 2, respectively). Similar results were found in the validation cohort (C-index: 0.940, 0.834 and 0.791, and 0.947, 0.857 and 0.810, with model 1 and model 2, respectively). Also, in ACLF, model 1 and model 2 outperformed MELDNa 7, 14 and 28 days after admission for prediction of mortality. Conclusions: Models including metabolites (CLIF-C MET) reflecting SI, mitochondrial dysfunction and sympathetic system activation are better predictors of short-term mortality than scores based only on organ dysfunction (eg, MELDNa), especially in patients with ACLF