bluuebunny/crossref_metadata_2025_split huggingface dataset:
LDCT lung cancer screening in populations at different risk for lung cancer
Authors: Teles Gustavo Borges da Silva , Macedo Ana Carolina Sandoval , Chate Rodrigo Caruso , Valente Viviane Arevalo Tabone , Funari Marcelo Buarque de Gusmao , Szarf Gilberto 
Published: February 2020

IntroductionThe improvement of low-dose CT (LDCT) lung cancer screening selection criteria could help to include more individuals who have lung cancer, or in whom lung cancer will develop, while avoiding significant cost increase. We evaluated baseline results of LDCT lung cancer screening in a population with a heterogeneous risk profile for lung cancer.MethodsLDCT lung cancer screening was implemented alongside a preventive health programme in a private hospital in Brazil. Individuals older than 45 years, smokers and former smokers, regardless of tobacco exposure, were included. Patients were classified according to the National Lung Screening Trial (NLST) eligibility criteria and to PLCOm20126-year lung cancer risk. Patient characteristics, CT positivity rate, detection rate of lung cancer and false-positive rate were assessed.ResultsLDCT scans of 472 patients were evaluated and three lung adenocarcinomas were diagnosed. CT positivity rate (Lung-RADS 3/4) was significantly higher (p=0.019) in the NLST group (10.1% (95% CI, 5.9% to 16.9%)) than in the non-NLST group (3.6% (95% CI, 2.62% to 4.83%)) and in the PLCOm2012high-risk group (14.3% (95% CI, 6.8% to 27.7%)) than in the PLCOm2012low-risk group (3.7% (95% CI, 2.9% to 4.8%)) (p=0.016). Detection rate of lung cancer was also significantly higher (p=0.018) among PLCOm2012high-risk patients (5.7% (95% CI, 2.5% to 12.6%)) than in the PLCOm2012low-risk individuals (0.2% (95% CI, 0.1% to 1.1%)). The false-positive rate for NLST criteria (16.4% (95% CI, 13.2% to 20.1%)) was higher (p<0.001) than for PLCOm2012criteria (7.6 (95% CI, 5.3% to 10.5%)).DiscussionOur study indicates a lower performance when screening low-risk individuals in comparison to screening patients meeting NLST criteria and PLCOm2012high-risk patients. Also, incorporating PLCOm20126-year lung cancer risk ≥0.0151 as an eligibility criterion seems to increase lung cancer screening effectiveness.
Flagging performance of Sysmex XN-10 haematology analyser for malaria detection
Authors: Dumas Cécile , Tirard-Collet Pauline , Mestrallet Fanélie , Girard Sandrine , Jallades Laurent , Picot Stéphane , Bienvenu Anne-Lise 
Published: February 2020

AimThe aim was to assess the flagging performance of Sysmex XN-10 haematology analyser for malaria detection through the parasitic red blood cell (‘pRBC’) alarm.MethodsWe retrospectively studied 584 blood samples performed on the Sysmex XN-10 analyser that were tested for malaria. Sensitivity, specificity, positive and negative predictive values, and prevalence were established for the pRBC alarm.ResultsSensitivity, specificity, and positive and negative predictive values for the pRBC flag were 7.8%, 100%, 100% and 87.7%, respectively. The prevalence of pRBC flag of 0.026% in the overall population was significantly different from the prevalence of 1.027% in the population tested for malaria.ConclusionsConsidering the excellent specificity and the low prevalence of the flag in the overall population, we suggest, in case of the presence of pRBC flag, the implementation of a rapid review of the blood smear looking forPlasmodium, mostly if the patient had fever and had not been tested for malaria.
Integrated characterisation of cancer genes identifies key molecular biomarkers in stomach adenocarcinoma
Authors: Wang Haifeng , Shen Liyijing , Li Yaoqing , Lv Jieqing 
Published: February 2020

AimsGastric cancer is one of the leading causes for cancer mortality. Recent studies have defined the landscape of genomic alterations of gastric cancer and their association with clinical outcomes. However, the pathogenesis of gastric cancer has not been completely characterised.MethodsDriver genes were detected by five computational tools, MutSigCV, OncodriveCLUST, OncodriveFM, dendrix and edriver, using mutation data of stomach adenocarcinoma (STAD) from the cancer genome altas database, followed by an integrative investigation.ResultsTTN, TP53, LRP1B, CSMD3, OBSCN, ARID1A, FAT4, FLG, PCLOandCSMD1were the 10 most frequently mutated genes.PIK3CD, NLRC3, FMNL1, TRAF3IP3andCR1were the top five hub genes of the blue coexpression module positively correlated with pathological tumour stage and lymph node stage (p values <0.05 for all cases). Hierarchical clustering analysis of copy number variations of driver genes revealed three subgroups of STAD patients, and cluster 2 tumours were significantly associated with lower lymph node stage, less number of positive lymph nodes and higher microsatellite instability and better overall survival than cluster 1 and cluster 3 tumours (p values <0.05 for all cases, Wilcoxon rank-sum test or log rank test). High expression in one or more ofDNER, LHCGR, NLRP14, OR4N2, PSG6, TTC29andZNF568genes was associated with increased mortality (p values <0.05 for all cases, log rank test).ConclusionsThe driver genes shed insights into the tumourigenesis of gastric cancer and the genesDNER, LHCGR, NLRP14, OR4N2, PSG6, TTC29andZNF568pave the way for developing prognostic biomarkers for the disease.
Distinct influence of different vascular risk factors on white matter brain lesions in multiple sclerosis
Authors: Geraldes Ruth , Juryńczyk Maciej , dos Passos Giordani , Prichler Alexander , Chung Karen , Hagens Marloes , Ruggieri Serena , Huerga Elena , Sastre-Garriga Jaume , Enzinger Christian , Chard Declan T , Barkhof Frederik , Gasperini Claudio , Rovira Alex , DeLuca Gabriele C , Palace Jacqueline 
Published: February 2020

ObjectiveTo determine if vascular risk factor (VRF), that is, smoking, arterial hypertension (HT), dyslipidaemia and diabetes, have an effect on multiple sclerosis (MS) pathology as measured by MS typical brain lesions, we have compared brain MRIs from patients with MS with and without VRF age-matched and sex-matched.MethodsBrain MRIs from five centres were scored for the presence of Dawson’s fingers (DF) and juxtacortical lesions (JCL). A regression model was built to predict the effect of each individual VRF on DF and JCL, considering age and disease duration.Results92 MS cases without VRF and 106 MS with one or more VRF (80 ever-smokers, 43 hypertensives, 25 dyslipidaemics and 10 diabetics) were included. Ever-smoking associated with a higher burden of DF (Exp(B)=1.29, 95% CI 1.10 to 1.51, p<0.01) and JCL (Exp(B)=1.38, 95% CI 1.21 to 1.57, p<0.01). No other VRF had an impact on DF. Dyslipidaemia associated with increased JCL (Exp(B)=1.30, 95% CI 1.10 to 1.56, p<0.01) but HT did not associate with any of the outcomes.ConclusionsIndividual VRF appear to affect MS-specific lesions differently. An increase in MS lesions was mainly seen in smokers; however, this VRF is most likely to be present from onset of MS, and other VRF effects may be partly mitigated by treatment. Our findings support that treating VRF and cessation of smoking may be important in the management of MS.
Calculated fission-fragment mass yields and average total kinetic energies of heavy and superheavy nuclei
Authors: Albertsson Martin , Carlsson B. Gillis , Døssing Thomas , Möller Peter , Randrup Jørgen , Åberg Sven 
Published: February 2020

AbstractFission-fragment mass and total-kinetic-energy (TKE) distributions following fission of even-even nuclides in the region $$74 \le Z \le 126$$74≤Z≤126 and $$92 \le N \le 230$$92≤N≤230, comprising 896 nuclides have been calculated using the Brownian shape-motion method. The emphasis is the region of superheavy nuclei. To show compatibility with earlier results the calculations are extended to include earlier studied regions. An island of asymmetric fission is obtained in the superheavy region, $$106\le Z\le 114$$106≤Z≤114 and $$162\le N\le 176$$162≤N≤176, where the heavy fragment is found to be close to $$^{208}$$208Pb and the light fragment adjusts accordingly. Most experimentally observed $$\alpha $$α-decay chains of superheavy nuclei with $$Z > 113 $$Z>113 terminate by spontaneous fission in our predicted region of asymmetric fission. In these cases, the pronounced large asymmetry is accompanied by a low TKE value compatible with measurements.
How to extend the chart of nuclides?
Authors: Adamian G. G. , Antonenko N. V. , Diaz-Torres A. , Heinz S. 
Published: February 2020

AbstractIn the past 85 years the number of known nuclides increased by more than a factor of ten, resulting in 4000 presently known isotopes of 118 elements. This considerable progress we owe to the discovery of new reaction types along with the development of powerful accelerators and experimental techniques for separation and identification of reaction products. Model predictions indicate that still about 4000 further nuclides are waiting for their discovery. The vastest unexplored territory is located on the neutron-rich side in the upper half of the chart of nuclides and hides the answers to some of the most fundamental questions of nuclear physics like the limits of nuclear stability, element synthesis in the universe or stellar evolution. The access to these nuclei is presently limited by available beam intensities and/or the lack of appropriate methods for their production and identification. The latter concerns particularly new neutron-rich isotopes of transuranium and superheavy elements. To extend this area, the hope is presently based on multinucleon transfer reactions and on the application of fusion reactions with radioactive ion beams. But how promising are these approaches? Based on a survey of present-day knowledge, we will treat the questions where we currently are on our journey towards new territory on the chart of nuclides, how the chances are to gain new territory in the future and which challenges we will have to face.
Optimizing Deep Learning Inference on Embedded Systems Through Adaptive Model Selection
Authors: Marco Vicent Sanz , Taylor Ben , Wang Zheng , Elkhatib Yehia 
Published: February 2020

Deep neural networks (DNNs) are becoming a key enabling technique for many application domains. However, on-device inference on battery-powered, resource-constrained embedding systems is often infeasible due to prohibitively long inferencing time and resource requirements of many DNNs. Offloading computation into the cloud is often unacceptable due to privacy concerns, high latency, or the lack of connectivity. Although compression algorithms often succeed in reducing inferencing times, they come at the cost of reduced accuracy.
This article presents a new, alternative approach to enable efficient execution of DNNs on embedded devices. Our approach dynamically determines which DNN to use for a given input by considering the desired accuracy and inference time. It employs machine learning to develop a low-cost predictive model to quickly select a pre-trained DNN to use for a given input and the optimization constraint. We achieve this first by offline training a predictive model and then using the learned model to select a DNN model to use for new, unseen inputs. We apply our approach to two representative DNN domains: image classification and machine translation. We evaluate our approach on a Jetson TX2 embedded deep learning platform and consider a range of influential DNN models including convolutional and recurrent neural networks. For image classification, we achieve a 1.8x reduction in inference time with a 7.52% improvement in accuracy over the most capable single DNN model. For machine translation, we achieve a 1.34x reduction in inference time over the most capable single model with little impact on the quality of translation.
Improving Implicit Recommender Systems with Auxiliary Data
Authors: Ding Jingtao , Yu Guanghui , Li Yong , He Xiangnan , Jin Depeng 
Published: February 2020

Most existing recommender systems leverage the primary feedback only, despite the fact that users also generate a large amount of auxiliary feedback. These feedback usually indicate different user preferences when comparing to the primary feedback directly used to optimize the system performance. For example, in E-commerce sites, view data is easily accessible, which provides a valuable yet weaker signal than the primary feedback of purchase. In this work, we improve implicit feedback-based recommender systems (dubbed
Implicit Recommender Systems
) by integrating auxiliary view data into matrix factorization (MF). To exploit different preference levels, we propose both pointwise and pairwise models in terms of how to leverage users’ viewing behaviors. The latter model learns the pairwise ranking relations among purchased, viewed, and non-viewed interactions, being more effective and flexible than the former pointwise MF method. However, such a pairwise formulation poses a computational efficiency problem in learning the model. To address this problem, we design a new learning algorithm based on the
element-wise Alternating Least Squares
(eALS) learner. Notably, our designed algorithm can efficiently learn model parameters from the whole user-item matrix (including all missing data), with a rather low time complexity that is dependent on the observed data only. Extensive experiments on two real-world datasets demonstrate that our method outperforms several state-of-the-art MF methods by 6.43%∼ 6.75%. Our implementation is available at https://github.com/dingjingtao/Auxiliary_enhanced_ALS.
Use of Ex Vivo Patient-Derived Tumor Organotypic Spheroids to Identify Combination Therapies for HER2 Mutant Non–Small Cell Lung Cancer
Authors: Ivanova Elena , Kuraguchi Mari , Xu Man , Portell Andrew J. , Taus Luke , Diala Irmina , Lalani Alshad S. , Choi Jihyun , Chambers Emily S. , Li Shuai , Liu Shengwu , Chen Ting , Barbie Thanh U. , Oxnard Geoffrey R. , Haworth Jacob J. , Wong Kwok-Kin , Dahlberg Suzanne E. , Aref Amir A. , Barbie David A. , Bahcall Magda , Paweletz Cloud P. , Jänne Pasi A. 
Published: February 2020

Abstract

Purpose:
Evaluating drug responses using primary patient-derived cells ex vivo represents a potentially rapid and efficient approach to screening for new treatment approaches. Here, we sought to identify neratinib combinations in HER2 mutant non–small cell lung cancer (NSCLC) patient xenograft-derived organotypic spheroids (XDOTS) using a short-term ex vivo system.

Experimental Design:
We generated two HER2-mutant NSCLC PDX models [DFCI359 (HER2 exon19 755_757LREdelinsRP) and DFCI315 (HER2 exon20 V777_G778insGSP)] and used the PDX tumors to generate XDOTS. Tumor spheroids were grown in a microfluidic device and treated ex vivo with neratinib-based drug combinations. Live/dead quantification was performed by dual-labeling deconvolution fluorescence microscopy. The most efficacious ex vivo combination was subsequently validated in vivo using the DFCI359 and DFCI315 PDXs and a HER2YVMA genetically engineered mouse model.

Results:
Both neratinib and afatinib, but not gefitinib, induced cell death in DFCI359 XDOTS. The combinations of neratinib/trastuzumab and neratinib/temsirolimus enhanced the therapeutic benefit of neratinib alone in DFCI315 and DFCI359. The combination of neratinib and trastuzumab in vivo was more effective compared with single-agent neratinib or trastuzumab and was associated with more robust inhibition of HER2 and downstream signaling.

Conclusions:
The XDOTS platform can be used to evaluate therapies and therapeutic combinations ex vivo using PDX tumors. This approach may accelerate the identification and clinical development of therapies for targets with no or few existing models and/or therapies.
Results of the ADAPT Phase 3 Study of Rocapuldencel-T in Combination with Sunitinib as First-Line Therapy in Patients with Metastatic Renal Cell Carcinoma
Authors: Figlin Robert A. , Tannir Nizar M. , Uzzo Robert G. , Tykodi Scott S. , Chen David Y.T. , Master Viraj , Kapoor Anil , Vaena Daniel , Lowrance William , Bratslavsky Gennady , DeBenedette Mark , Gamble Alicia , Plachco Ana , Norris Marcus S. , Horvatinovich Joe , Tcherepanova Irina Y. , Nicolette Charles A. , Wood Christopher G. 
Published: February 2020

Abstract

Purpose:
Rocapuldencel-T is an autologous immunotherapy prepared from mature monocyte-derived dendritic cells (DC), coelectroporated with amplified tumor RNA plus CD40L RNA. This pivotal phase III trial was initiated to investigate the safety and efficacy of a combination therapy dosing regimen of Rocapuldencel-T plus sunitinib in patients with metastatic renal cell carcinoma (mRCC).

Patients and Methods:
Patients received either Rocapuldencel-T plus standard of care (SOC) or SOC treatment alone. The primary objective compared overall survival (OS) between groups. Secondary objectives included safety assessments, progression-free survival (PFS), and tumor responses based on RECIST 1.1 criteria. Exploratory analyses included immunologic assessments and correlates with OS.

Results:
Between 2013 and 2016, 462 patients were randomized 2:1, 307 to the combination group and 155 to the SOC group. Median OS in the combination group was 27.7 months [95% confidence interval (CI) 23.0–35.9] and 32.4 months (95% CI, 22.5–) in the SOC group HR of 1.10 (95% CI, 0.83–1.40). PFS was 6.0 months and 7.83 months for the combination and SOC groups, respectively [HR = 1.15 (95% CI, 0.92–1.44)]. The ORR was 42.7% (95% CI, 37.1–48.4) for the combination group and 39.4% (95% CI, 31.6–47.5) for the SOC group. Median follow up was 29 months (0.4–47.7 months). On the basis of the lack of clinical efficacy, the ADAPT trial was terminated on February 17, 2017. Immune responses were detected in 70% of patients treated with Rocapuldencel-T, and the magnitude of the immune response positively correlated with OS. In addition, we report the survival-predictive value of measuring IL-12 produced by the DC vaccine and the observation that high baseline numbers of T regulatory cells are associated with improved outcomes in DC-treated patients, but are associated with poor outcomes in patients receiving SOC treatment. No serious adverse events attributed to the study medication have been reported to date.

Conclusions:
Rocapuldencel-T did not improve OS in patients treated with combination therapy, although the induced immune response correlated with OS. Moreover, we identified two potential survival-predictive biomarkers for patients receiving DC based immunotherapy, IL-12 produced by the DC vaccine and higher numbers of T regulatory cells present in the peripheral blood of patients with advanced RCC.
In VivoTracking of Adoptively Transferred Natural Killer Cells in Rhesus Macaques Using 89Zirconium-Oxine Cell Labeling and PET Imaging
Authors: Sato Noriko , Stringaris Kate , Davidson-Moncada Jan K. , Reger Robert , Adler Stephen S. , Dunbar Cynthia , Choyke Peter L. , Childs Richard W. 
Published: February 2020

AbstractPurpose:Trials of adoptive natural killer (NK)-cell immunotherapy for hematologic malignancies have thus far shown only marginal effects, despite the potent in vitro antitumor activity of these cells. Homing of infused cells to tumor microenvironments is critical for efficacy, but has not been well characterized. We established a novel method to track and quantify the distribution of adoptively transferred NK cells using rhesus macaques (RM) as a clinically relevant preclinical model.Experimental Design:RM NK cells were expanded ex vivo for 14–21 days, labeled with 89Zr-oxine complex, and assessed for phenotype, function, and survival. Trafficking of 89Zr-labeled ex vivo–expanded NK cells infused into RMs was monitored and quantitated by serial positron emission tomography (PET)/CT (n = 3, 2.05 ± 0.72 MBq, 23.5 ± 2.0 × 106 NK cells/kg) and compared with that of 89Zr-labeled nonexpanded NK cells, apoptotic NK cells, and hematopoietic stem and progenitor cells (HSPC).Results:NK cells retained sufficient levels of 89Zr for accurate in vivo tracking for 7 days. 89Zr labeling did not alter cellular phenotype, viability, or function. PET/CT showed NK cells initially localized in the lungs, followed by their migration to the liver, spleen, and, at low levels, bone marrow. One day following transfer, only 3.4% of infused NK cells localized to the BM versus 22.1% of HSPCs. No clinical side effects were observed, and dosimetry analysis indicated low organ radioexposures of 6.24 mSv/MBq (spleen) or lower.Conclusions:These data support translation of this technique to humans to track the distribution of adoptively infused cells and to develop novel techniques to improve immune cell homing to tumor microenvironments.
Molecular Mechanisms of Acquired Resistance to MET Tyrosine Kinase Inhibitors in Patients with MET Exon 14–Mutant NSCLC
Authors: Recondo Gonzalo , Bahcall Magda , Spurr Liam F. , Che Jianwei , Ricciuti Biagio , Leonardi Giulia C. , Lo Ying-Chun , Li Yvonne Y. , Lamberti Giuseppe , Nguyen Tom , Milan Marina S.D. , Venkatraman Deepti , Umeton Renato , Paweletz Cloud P. , Albayrak Adem , Cherniack Andrew D. , Price Kristin S. , Fairclough Stephen R. , Nishino Mizuki , Sholl Lynette M. , Oxnard Geoffrey R. , Jänne Pasi A. , Awad Mark M. 
Published: February 2020

AbstractPurpose:Molecular mechanisms of acquired resistance to MET tyrosine kinase inhibitors (TKI) are poorly understood. We aimed to characterize the genomic mechanisms of resistance to type I and type II MET TKIs and their impact on sequential MET TKI therapy outcomes in patients with metastatic MET exon 14–mutant NSCLC.Experimental Design:Genomic alterations occurring at the time of progression on MET TKIs were studied using plasma and tissue next-generation sequencing (NGS).Results:A total of 20 patients had tissue or plasma available for analysis at the time of acquired resistance to a MET TKI. Genomic alterations known or suspected to be mechanisms of resistance were detected in 15 patients (75%). On-target acquired mechanisms of resistance, including single and polyclonal MET kinase domain mutations in codons H1094, G1163, L1195, D1228, Y1230, and high levels of amplification of the MET exon 14–mutant allele, were observed in 7 patients (35%). A number of off-target mechanisms of resistance were detected in 9 patients (45%), including KRAS mutations and amplifications in KRAS, EGFR, HER3, and BRAF; one case displayed both on- and off-target mechanisms of resistance. In 2 patients with on-target resistant mutations, switching between type I and type II MET TKIs resulted in second partial responses.Conclusions:On-target secondary mutations and activation of bypass signaling drive resistance to MET TKIs. A deeper understanding of these molecular mechanisms can support the development of sequential or combinatorial therapeutic strategies to overcome resistance.
Not Yet Another Negative Trial–ReACTing on Recent Glioblastoma Trials
Authors: Wick Wolfgang , Wagener Robin J. 
Published: February 2020

Abstract

The present ReACT trial provides data from a small randomized controlled vaccination trial that in addition to other recent immunotherapy trials in glioblastoma allows sketching a rational, advanced trial design for the development of (immune) therapies in glioblastoma elaborating on but not restricting to biological monitoring and endpoints.
See related article by Reardon et al., p. 1586