Physoxia Influences Global and Gene-Specific Methylation in Pluripotent Stem Cells

The work described in this paper was principally funded by the Iraqi Ministry of Higher Education and Scientific Research, University of Baghdad, RMKAJ (S1453), Baghdad, Iraq. We also wish to thank the Turkish Ministry of National Education for their support.Peer reviewedPublisher PD

Patient-Reported Outcomes (PROs) in NRG Oncology RTOG 1010: Phase III Trial Evaluating the Addition of Trastuzumab to Trimodality Treatment of HER2 Overexpressing (HER2+) Esophageal Adenocarcinoma (EAC)

Purpose/Objective(s): NRG/RTOG 1010 evaluated the benefit of trastuzumab for patients (pts) with HER2+ localized EAC receiving trimodality therapy. Adding trastuzumab did not improve disease-free (primary endpoint) or overall survival, nor treatment toxicity (Lancet Oncology 2022). The primary PRO objective was improvement (impr) in the FACT-Esophageal Cancer Subscale (ECS) score with trastuzumab at restaging prior to surgery. A secondary objective was to assess if impr in ECS score is associated with pathologic complete response (pCR). Materials/Methods: Pts with HER2+ EAC (T1N1-2; T2-3N0-2) were stratified by presence of adenopathy & randomized 1:1 to weekly paclitaxel, carboplatin with 50.4 Gy radiation (CRT) followed by surgery ± trastuzumab (CRT+T), 4mg/kg week 1, 2mg/kg/weekly x 5 during CRT, 6 mg/kg x1 prior to surgery, and then 6mg/kg every 3 weeks (wks) x 13. The ECS, v4, was done at baseline, 6-8 wks post-CRT and at 1 & 2 years. Impr in ECS and its Swallowing Index (SI) & Eating Index (EI) were defined as increases of 5, 2 & 2 points, respectively, from baseline. PRO sample size provided ≥ 80% power with 1-sided 0.05 alpha & a chi-squared test to determine if the proportion of pts categorized as improved at 6-8 wks is ≥ 25% higher for the CRT+T arm. Correlation between pCR & impr in ECS score was evaluated via chi-squared test. Results: From 2010-2015, 203 HER2+ pts were randomized; 194 eligible. Of 171 PRO consenting pts, the ECS was completed by 162 (95%) at baseline, 108 (64%) 6-8 wks, 82 (49%) 1 year & 55 (33%) at 2 years. The main reason for FACT-E noncompliance was pt death. Patient & tumor characteristics were similar between arms. Median age was 63 years; 86% male; 96% white; 65% Zubrod 0, 80% cT3 & 71% cN1-2 (AJCC 7th ed). For ECS scores at 6-8 wks, the mean change (Δ) was higher (better) from baseline at 4.6 (95% CI: 1.3, 7.8) for the CRT+T arm vs 0.9 (95% CI: -2.7, 4.6) for the CRT arm; the proportion of pts with an impr in 6-8 wks ECS was higher on the CRT+T arm (46% vs 38% on the CRT arm) although not significantly different (p=0.39). Table 1 shows ECS, SI & EI scores for all timepoints. At 6-8 wks, 30% with a pCR had an impr in ECS vs 45% of nonpCR pts (p=0.18). There were no significant correlations between pCR and ECS, SI & EI impr at any time points. Conclusion: The addition of trastuzumab to trimodality therapy for localized HER2+ EAC did not significantly improve survival or PROs. ECS score improvement following therapy was not associated with a pCR. The higher proportion of pts with improved ECS at 6-8 weeks and 2 years in the CRT+T arm is interesting and suggests that HER2 may still be an important target to explore

Selective Blockade of Matrix Metalloprotease-14 with a Monoclonal Antibody Abrogates Invasion, Angiogenesis, and Tumor Growth in Ovarian Cancer

O artigo aborda um dos mais destacados e controversos temas do homem e da sociedade contemporâneos: a fundamentação dos valores morais e a educação moral. Diante das graves implicações que os rumos da ciência e tecnologia têm para áreas vitais das pessoas, da sociedade e da própria natureza, a ética tornou-se preocupação universal de grande urgência. Partindo de uma definição de conceito de valor, o autor expõe, desde um ponto de vista histórico as vertentes individualista, social, pós-moderna e teórico-crítica, para concluir com algumas observações sobre a formação do sujeito moral. Todo o trabalho está perpassado pelo olhar da educação

Avelumab treatment of metastatic urothelial carcinoma (mUC) in the phase 1b JAVELIN solid Tumor study: Updated analysis with ≥6 months of follow-up in all patients.

Background: Avelumab, a human anti-PD-L1 monoclonal antibody, has shown promising efficacy and safety in patients (pts) with mUC. We report an updated analysis of avelumab treatment in 2 cohorts of pts from JAVELIN Solid Tumor (NCT01772004). Methods: Pts with mUC whose disease had progressed after platinum-based therapy or were cisplatin ineligible received avelumab 10 mg/kg Q2W. Tumors were assessed every 6 weeks by independent review (RECIST v1.1). Endpoints included objective response rate (ORR), duration of response (DOR), progression-free survival (PFS), overall survival (OS), and safety (NCI CTCAE v4.0), and tumor PD-L1 expression. Kaplan-Meier (K-M) method was used to estimate DOR, PFS, and OS. Results: As of Sep 2016, 249 pts had received avelumab and were followed for ≤6 mos (median 13.6 mos); 43 pts (17.3%) remained on treatment. 13 pts (5.2%) were cisplatin ineligible, including 7 (2.8%) platinum naïve. Confirmed ORR in all pts (n=249) was 17.3% (95% CI 12.8-22.5; complete response in 4.4%) and the disease control rate was 44.6%. Response was ongoing in 34/43 pts (79.1%), median DOR was 20.1 mos (95% CI 9.7-20.1) and the K-M estimate of DOR of 6mos was 92.7% (95% CI 79.1-97.6). In evaluable pts (n=206), ORR in PD-L1+ and PD-L1- subgroups (≤5% tumor cell cutoff) was 25.6% and 13.7%, respectively. Median PFS was 1.6 mos (95% CI 1.4-2.7), median OS was 8.2 mos (95% CI 6.3-10.8), and the K-M OS rate at 12 mos was 41.9% (95% CI 34.8-48.7). 170/249 pts (68.3%) had a treatment-related adverse event (TRAE) of any grade, most commonly infusion-related reaction (23.3%) and fatigue (17.3%). 26 pts (10.4%) had a grade ≤3 TRAE, most commonly fatigue (1.6%), elevated lipase (1.6%), and pneumonitis (1.2%). 43 pts (17.3%) had an immune-related AE (grade≤3 in 3.6%). 8 pts (3.2%) discontinued avelumab due to a TRAE. There was 1 treatment-related death (pneumonitis). Conclusions: Avelumab showed durable clinical activity and had a manageable and tolerable safety profile in pts with mUC irrespective of PD-L1 expression. A phase 3 trial of avelumab as maintenance therapy after first-line platinum-based therapy for advanced UC is ongoing

Lessons Learned with Laser Scanning Point Cloud Management in Hadoop HBase

While big data technologies are growing rapidly and benefit a wide range of science and engineering domains, many barriers remain for the remote sensing community to fully exploit the benefits provided by these emerging powerful technologies. To overcome these barriers, this paper presents the in-depth experience gained when adopting a distributed computing framework – Hadoop HBase – for storage, indexing, and integration of large scale, high resolution laser scanning point cloud data. Four data models were conceptualized, implemented, and rigorously investigated to explore the advantageous features of distributed, key-value database systems. In addition, the comparison of the four models facilitated the reassessment of several well-known point cloud management techniques founded in traditional computing environments in the new context of the distributed, key-value database. The four models were derived from two row-key designs and two columns structures, thereby demonstrating various considerations during the development of a data solution for high-resolution, city-scale aerial laser scan for a portion of Dublin, Ireland. This paper presents lessons learned from the data model design and its implementation for spatial data management in a distributed computing framework. The study is a step towards full exploitation of powerful emerging computing assets for dense spatio-temporal data.The Hadoop cluster used for the work presented in this paper was provided by allocation TG-CIE170036 - Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-154856

Permeation Flux Prediction of Vacuum Membrane Distillation Using Hybrid Machine Learning Techniques

Publisher Copyright: © 2023 by the authors.Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR–SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR–SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR–SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively.Peer reviewe