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Item Open Access Adjuvant autologous melanoma vaccine for macroscopic stage III disease: survival, biomarkers, and improved response to CTLA-4 blockade(Hindawi Limited, 2016) Lotem, M.; Merims, S.; Frank, S.; Hamburger, T.; Nissan, A.; Kadouri, L.; Cohen, J.; Straussman, R.; Eisenberg, G.; Frankenburg, S.; Carmon, E.; Alaiyan, B.; Shneibaum, S.; Ayyildiz, Z. O.; Isbilen, M.; Senses, K. M.; Ron, I.; Steinberg, H.; Smith, Y.; Shiloni, E.; Gure, A. O.; Peretz, T.Background. There is not yet an agreed adjuvant treatment for melanoma patients with American Joint Committee on Cancer stages III B and C. We report administration of an autologous melanoma vaccine to prevent disease recurrence. Patients and Methods. 126 patients received eight doses of irradiated autologous melanoma cells conjugated to dinitrophenyl and mixed with BCG. Delayed type hypersensitivity (DTH) response to unmodified melanoma cells was determined on the vaccine days 5 and 8. Gene expression analysis was performed on 35 tumors from patients with good or poor survival. Results. Median overall survival was 88 months with a 5-year survival of 54%. Patients attaining a strong DTH response had a significantly better (p = 0.0001) 5-year overall survival of 75% compared with 44% in patients without a strong response. Gene expression array linked a 50-gene signature to prognosis, including a cluster of four cancer testis antigens: CTAG2 (NY-ESO-2), MAGEA1, SSX1, and SSX4. Thirty-five patients, who received an autologous vaccine, followed by ipilimumab for progressive disease, had a significantly improved 3-year survival of 46% compared with 19% in nonvaccinated patients treated with ipilimumab alone (p = 0.007). Conclusion. Improved survival in patients attaining a strong DTH and increased response rate with subsequent ipilimumab suggests that the autologous vaccine confers protective immunity.Item Open Access BRAPH: A graph theory software for the analysis of brain connectivity(Public Library of Science, 2017) Mijalkov, M.; Kakaei, E.; Pereira, J. B.; Westman, E.; Volpe, G.The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. © 2017 Mijalkov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Item Open Access Colon cancer associated transcript-1 (CCAT1) expression in adenocarcinoma of the stomach(Ivyspring International Publisher, 2015) Mizrahi, I.; Mazeh, H.; Grinbaum, R.; Beglaibter, N.; Wilschanski, M.; Pavlov, V.; Adileh, M.; Stojadinovic, A.; Avital, I.; Gure, A. O.; Halle, D.; Nissan, A.Background: Long non-coding RNAs (lncRNAs) have been shown to have functional roles in cancer biology and are dys-regulated in many tumors. Colon Cancer Associated Transcript -1 (CCAT1) is a lncRNA, previously shown to be significantly up-regulated in colon cancer. The aim of this study is to determine expression levels of CCAT1 in gastric carcinoma (GC). Methods: Tissue samples were obtained from patients undergoing resection for gastric carcinoma (n=19). For each patient, tumor tissue and normal appearing gastric mucosa were taken. Normal gastric tissues obtained from morbidly obese patients, undergoing laparoscopic sleeve gastrectomy served as normal controls (n=19). A human gastric carcinoma cell line (AGS) served as positive control. RNA was extracted from all tissue samples and CCAT1 expression was analyzed using quantitative real time-PCR (qRT-PCR). Results: Low expression of CCAT1 was identified in normal gastric mucosa samples obtained from morbidly obese patients [mean Relative Quantity (RQ) = 1.95±0.4]. AGS human gastric carcinoma cell line showed an elevated level of CCAT1 expression (RQ=8.02). Expression levels of CCAT1 were approximately 10.8 fold higher in GC samples than in samples taken from the negative control group (RQ=21.1±5 vs. RQ=1.95±0.4, respectively, p<0.001). Interestingly, CCAT1 expression was significantly overexpressed in adjacent normal tissues when compared to the negative control group (RQ = 15.25±2 vs. RQ=1.95±0.4, respectively, p<0.001). Tissues obtained from recurrent GC cases showed the highest expression levels (RQ = 88.8±31; p<0.001). Expression levels increased with tumor stage (T4- 36.4±15, T3- 16.1±6, T2- 4.7±1), however this did not reach statistical significance (p=0.2). There was no difference in CCAT1 expression between intestinal and diffuse type GC (RQ=22.4±7 vs. 22.4±16, respectively, p=0.9). Within the normal gastric tissue samples, no significant difference in CCAT1 expression was observed in helicobacter pylori negative and positive patients (RQ= 2.4±0.9 vs. 0.93±0.2, respectively, p=0.13). Conclusion: CCAT1 is up-regulated in gastric cancer, and may serve as a potential bio-marker for early detection and surveillance.Item Open Access Data mining experiments on the Angiotensin II-Antagonist in Paroxysmal Atrial Fibrillation (ANTIPAF-AFNET 2) trial: ‘exposing the invisible’(Oxford University Press, 2016) Okutucu, S.; Katircioglu-Öztürk, D.; Oto, E.; Güvenir, H. A.; Karaagaoglu, E.; Oto, A.; Meinertz, T.; Goette, A.Aims: The aims of this study include (i) pursuing data-mining experiments on the Angiotensin II-Antagonist in Paroxysmal Atrial Fibrillation (ANTIPAF-AFNET 2) trial dataset containing atrial fibrillation (AF) burden scores of patients with many clinical parameters and (ii) revealing possible correlations between the estimated risk factors of AF and other clinical findings or measurements provided in the dataset. Methods: Ranking Instances by Maximizing the Area under a Receiver Operating Characteristics (ROC) Curve (RIMARC) is used to determine the predictive weights (Pw) of baseline variables on the primary endpoint. Chi-square automatic interaction detector algorithm is performed for comparing the results of RIMARC. The primary endpoint of the ANTIPAF-AFNET 2 trial was the percentage of days with documented episodes of paroxysmal AF or with suspected persistent AF. Results: By means of the RIMARC analysis algorithm, baseline SF-12 mental component score (Pw = 0.3597), age (Pw = 0.2865), blood urea nitrogen (BUN) (Pw = 0.2719), systolic blood pressure (Pw = 0.2240), and creatinine level (Pw = 0.1570) of the patients were found to be predictors of AF burden. Atrial fibrillation burden increases as baseline SF-12 mental component score gets lower; systolic blood pressure, BUN and creatinine levels become higher; and the patient gets older. The AF burden increased significantly at age >76. Conclusions: With the ANTIPAF-AFNET 2 dataset, the present data-mining analyses suggest that a baseline SF-12 mental component score, age, systolic blood pressure, BUN, and creatinine level of the patients are predictors of AF burden. Additional studies are necessary to understand the distinct kidney-specific pathophysiological pathways that contribute to AF burden. Published on behalf of the European Society of Cardiology.Item Open Access Ischemic stroke phenotype in patients with nonsustained atrial fibrillation(Lippincott Williams and Wilkins, 2015) Arsava, E. M.; Bas, D. F.; Atalar, Ergin; Has, A. C.; Oguz, K. K.; Topcuoglu, M. A.Background and Purpose: The widespread use of ambulatory cardiac monitoring has not only increased the detection of high-risk arrhythmias like persistent and paroxysmal atrial fibrillation (AF), but also made it possible to identify other aberrations such as short-lasting (<30 seconds) irregular runs of supraventricular tachycardia. Ischemic stroke phenotype might be helpful in understanding whether these nonsustained episodes play a similar role in stroke pathophysiology like their persistent and paroxysmal counterparts. Methods: In a consecutive series of patients with ischemic stroke, we retrospectively determined clinical and imaging features associated with nonsustained AF (n=126), defined as <30-second-lasting supraventricular tachyarrhythmias with irregular RR interval on 24-hour Holter monitoring, and compared them to patients with persistent/paroxysmal AF (n=239) and no AF (n=246). Results: Patients with persistent/paroxysmal AF significantly differed from patients with nonsustained AF by a higher prevalence of female sex (odds ratio [95% confidence interval], 1.8 [1.1-2.9]), coronary artery disease (1.9 [1.1-3.0]), and embolic imaging features (2.7 [1.1-6.5]), and lower frequency of smoking (0.4 [0.2-0.8]) and hyperlipidemia (0.5 [0.3-0.8]). In contrast, patients with no AF were younger (0.5 [0.4-0.6] per decade) and more likely to be male (1.7 [1.0-2.8]) in comparison with nonsustained AF population. The prevalence of nonsustained AF was similar among cryptogenic and noncryptogenic stroke patients (32% versus 29%). Voxel-wise comparison of lesion probability maps revealed no significant difference between cryptogenic stroke patients with and without nonsustained AF. Conclusions: Clinical features of patients with nonsustained AF exhibited an intermediary phenotype in between patients with persistent/paroxysmal AF and no AF. Furthermore, imaging features did not entirely resemble patterns observed in patients with longer durations of AF.