Avaliação de características anatômicas da madeira de Calophyllum brasiliense Cambess. (Clusiaceae), em diferentes condições ambientais, no Estado do Paraná.

Resumo

Dinâmica de crescimento de espécies arbóreas em remanescentes florestais do estado do Paraná, sob diferentes condições ambientais.

Organizado por Patricia Póvoa de Mattos, Celso Garcia Auer, Rejane Stumpf Sberze, Katia Regina Pichelli e Paulo César Botosso

Examining the neural mechanisms of rTMS: a naturalistic pilot study of acute and serial effects in pharmacoresistant depression

IntroductionPrevious studies have demonstrated the effectiveness of therapeutic repetitive transcranial magnetic stimulation (rTMS) to treat pharmacoresistant depression. Nevertheless, these trials have primarily focused on the therapeutic and neurophysiological effects of rTMS following a long-term treatment course. Identifying brain-based biomarkers of early rTMS therapeutic response remains an important unanswered question. In this pilot study, we examined the effects of rTMS on individuals with pharmacoresistant depression using a graph-based method, called Functional Cortical Networks (FCN), and serial electroencephalography (EEG). We hypothesized that changes in brain activity would occur early in treatment course.MethodsA total of 15 patients with pharmacoresistant depression underwent five rTMS sessions (5Hz over the left dorsolateral prefrontal cortex, 120%MT, up to 4,000 pulses/session). Five participants received additional rTMS treatment, up to 40 sessions. Resting EEG activity was measured at baseline and following every five sessions, using 64-channel EEG, for 10 minutes with eyes closed. An FCN model was constructed using time-varying graphs and motif synchronization. The primary outcome was acute changes in weighted-node degree. Secondary outcomes included serial FFT-based power spectral analysis and changes in depressive symptoms measured by the 9-Item Patient Health Questionnaire (PHQ-9) and the 30-item Inventory of Depressive Symptoms-Self Report (IDS-SR).ResultsWe found a significant acute effect over the left posterior area after five sessions, as evidenced by an increase in weighted-node degree of 37,824.59 (95% CI, 468.20 to 75,180.98) and a marginal enhancement in the left frontal region (t (14) = 2.0820, p = 0.056). One-way repeated measures ANOVA indicated a significant decrease in absolute beta power over the left prefrontal cortex (F (7, 28) = 2.37, p = 0.048) following ten rTMS sessions. Furthermore, a significant clinical improvement was observed following five rTMS sessions on both PHQ-9 (t (14) = 2.7093, p = 0.017) and IDS-SR (t (14) = 2.5278, p = 0.024) and progressed along the treatment course.DiscussionOur findings suggest that FCN models and serial EEG may contribute to a deeper understanding of mechanisms underlying rTMS treatment. Additional research is required to investigate the acute and serial effects of rTMS in pharmacoresistant depression and assess whether early EEG changes could serve as predictors of therapeutic rTMS response

A Serum Resistin and Multicytokine Inflammatory Pathway Is Linked With and Helps Predict All-cause Death in Diabetes

Context: Type 2 diabetes (T2D) shows a high mortality rate, partly mediated by atherosclerotic plaque instability. Discovering novel biomarkers may help identify high-risk patients who would benefit from more aggressive and specific managements. We recently described a serum resistin and multicytokine inflammatory pathway (REMAP), including resistin, interleukin (IL)-1 beta, IL-6, IL-8, and TNF-alpha, that is associated with cardiovascular disease.Objective: We investigated whether REMAP is associated with and improves the prediction of mortality in T2D.Methods: A REMAP score was investigated in 3 cohorts comprising 1528 patients with T2D (409 incident deaths) and in 59 patients who underwent carotid endarterectomy (CEA; 24 deaths). Plaques were classified as unstable/stable according to the modified American Heart Association atherosclerosis classification.Results: REMAP was associated with all-cause mortality in each cohort and in all 1528 individuals (fully adjusted hazard ratio [HR] for 1 SD increase=1.34, P<.001). In CEA patients, REMAP was associated with mortality (HR=1.64, P=.04) and a modest change was observed when plaque stability was taken into account (HR=1.58; P=.07). REMAP improved discrimination and reclassification measures of both Estimation of Mortality Risk in Type 2 Diabetic Patients and Risk Equations for Complications of Type 2 Diabetes, well-established prediction models of mortality in T2D (P<.05-<.001).Conclusion: REMAP is independently associated with and improves predict all-cause mortality in T2D; it can therefore be used to identify high-risk individuals to be targeted with more aggressive management. Whether REMAP can also identify patients who are more responsive to IL-6 and IL-1 beta monoclonal antibodies that reduce cardiovascular burden and total mortality is an intriguing possibility to be tested

Urine Proteome Analysis May Allow Noninvasive Differential Diagnosis of Diabetic Nephropathy

AbstractObjective: Chronic renal insufficiency and/or proteinuria in type 2 diabetes may stem from chronic renal diseases (CKD) other than classic diabetic nephropathy (DN) in over one third of cases. We interrogated urine proteomic profiles generated by SELDI-TOF/MS with the aim to isolate a set of biomarkers able to reliably identify biopsy-proven DN and to establish a stringent correlation with the different patterns of renal injury. Research design and methods: Ten mug urine proteins from 190 subjects [20 healthy subjects (HS), 20 normoalbuminuric (NAD) and 18 microalbuminuric (MICRO) diabetic patients, and 132 patients with biopsy-proven nephropathy (65 DN, 10 diabetics with non-diabetic CKD (nd-CKD) and 57 non-diabetic patients with CKD)] were run by CM10 ProteinChip array and analysed by supervised learning methods (CART analysis). Results: The classification model correctly identified 75% NAD, 87.5% MICRO and 87.5% DN when applied to a blinded testing set. Most importantly, it was able to reliably differentiate DN from nd-CKD in both diabetic and non-diabetic patients. Among the best predictors of the classification model, we identified and validated 2 proteins, ubiquitin and ss2-microglobulin. Conclusions: Our data suggest the presence of a specific urine proteomic signature able to reliably identify type 2 diabetic patients with diabetic glomerulosclerosis

GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

Annali storici di Principato Citra, A. 9, n. 1.1 (2011)

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