Mechanisms of tidal oscillatory salt transport in a partially stratified estuary

Author Posting. © American Meteorological Society, 2015. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 45 (2015): 2773–2789, doi:10.1175/JPO-D-15-0031.1.Tidal oscillatory salt transport, induced by the correlation between tidal variations in salinity and velocity, is an important term for the subtidal salt balance under the commonly used Eulerian method of salt transport decomposition. In this paper, its mechanisms in a partially stratified estuary are investigated with a numerical model of the Hudson estuary. During neap tides, when the estuary is strongly stratified, the tidal oscillatory salt transport is mainly due to the hydraulic response of the halocline to the longitudinal variation of topography. This mechanism does not involve vertical mixing, so it should not be regarded as oscillatory shear dispersion, but instead it should be regarded as advective transport of salt, which results from the vertical distortion of exchange flow obtained in the Eulerian decomposition by vertical fluctuations of the halocline. During spring tides, the estuary is weakly stratified, and vertical mixing plays a significant role in the tidal variation of salinity. In the spring tide regime, the tidal oscillatory salt transport is mainly due to oscillatory shear dispersion. In addition, the transient lateral circulation near large channel curvature causes the transverse tilt of the halocline. This mechanism has little effect on the cross-sectionally integrated tidal oscillatory salt transport, but it results in an apparent left–right cross-channel asymmetry of tidal oscillatory salt transport. With the isohaline framework, tidal oscillatory salt transport can be regarded as a part of the net estuarine salt transport, and the Lagrangian advective mechanism and dispersive mechanism can be distinguished.Tao Wang was supported by the Open Research Fund of State Key Laboratory of Estuarine and Coastal Research (Grant SKLEC-KF201509) and Chinese Scholarship Council. Geyer was supported by by NSF Grant OCE 0926427. Wensheng Jiang was supported by NSFC-Shandong Joint Fund for Marine Science Research Centers (Grant U1406401).2016-05-0

SYK-targeted dendritic cell-mediated cytotoxic T lymphocytes enhance the effect of immunotherapy on retinoblastoma

Purpose: Retinoblastoma (RB) is the most common primary intraocular tumor in children. Chemotherapy is currently the main method of RB treatment. Unfortunately, RB often becomes chemoresistant and turns lethal. Here, we used in vitro cell immunotherapy to explore whether adoptive immunotherapy could be used as a potential treatment for RB. We focused on spleen tyrosine kinase (SYK), which is significantly upregulated in RB cells and serves as a marker for RB cells. Methods: Using lentiviruses, we genetically modified dendritic cells (DCs) to express and present the SYK peptide antigen to cytotoxic T lymphocytes (CTLs) in vitro. We used SYK-negative cell lines (MDA-MB-231, MCF-10A, and hTERT-RPE1) and SYK-positive cell lines (MCF-7 and RB-Y79) to evaluate the specificity and cytotoxicity of DC presented CTLs using FACS, live-cell imaging, and RNA interference. Results: The cytotoxicity of CTLs induced by SYK-overexpressing DCs (SYK-DC–CTLs) was enhanced more than three times in SYK-positive cell lines compared with SYK-negative cell lines. DCs primed with SYK could drive CTL cytotoxicity against SYK-positive cell lines but not against SYK-negative cell lines. Moreover, SYK-silenced RB-Y79 cells successfully evaded the cytotoxic attack from SYK-DC–CTLs. However, SYK-DC–CTLs could target SYK overexpressed hTERT-RPE1 cells, suggesting that SYK is a specific antigen for RB. Furthermore, SYK-DC–CTL exhibited specific cytotoxicity against carboplatin-resistant RB-Y79 cells in vitro. Conclusions: Our data showed that SYK could be a potential immunotherapy target mediated by DCs. We propose SYK as a candidate target for treatment of chemoresistant RB.Fil: Chen, Xuemei. Xi'an Jiaotong University; ChinaFil: Kunda, Patricia Elena. Instituto Universitario de Ciencias Biomédicas de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Lin, Jianwei. Shenzhen University; ChinaFil: Zhou, Meiling. Shenzhen Luohu Peoples Hospital; China. Shenzhen University; ChinaFil: Huang, Jinghan. Shenzhen Luohu Peoples Hospital; ChinaFil: Zhang, Huqin. Xi'an Jiaotong University; ChinaFil: Liu, Tao. Shenzhen University; China. Shenzhen Luohu Peoples Hospital; Chin

Phase 1 dose-escalation, pharmacokinetic, and cerebrospinal fluid distribution study of TAK-285, an investigational inhibitor of EGFR and HER2

Introduction This phase 1 study assessed safety, maximum tolerated dose (MTD), pharmacokinetics, cerebrospinal fluid (CSF) distribution, and preliminary clinical activity of the receptor tyrosine kinase inhibitor TAK-285. Methods Patients with advanced, histologically confirmed solid tumors and Eastern Cooperative Oncology Group performance status ≤2 received daily oral TAK-285; daily dose was escalated within defined cohorts until MTD and recommended phase 2 dose (RP2D) were determined. Eleven patients were enrolled into an RP2D cohort. Blood samples were collected from all cohorts; CSF was collected at pharmacokinetic steady-state from RP2D patients. Tumor responses were assessed every 8 weeks per Response Evaluation Criteria in Solid Tumors. Results Fifty-four patients were enrolled (median age 60; range, 35–76 years). The most common diagnoses were cancers of the colon (28 %), breast (17 %), and pancreas (9 %). Escalation cohorts evaluated doses from 50 mg daily to 500 mg twice daily; the MTD/RP2D was 400 mg twice daily. Dose-limiting toxicities included diarrhea, hypokalemia, and fatigue. Drug absorption was fast (median time of maximum concentration was 2–3 h), and mean half-life was 9 h. Steady-state average unbound CSF concentration (geometric mean 1.54 [range, 0.51–4.27] ng/mL; n = 5) at the RP2D was below the 50 % inhibitory concentration (9.3 ng/mL) for inhibition of tyrosine kinase activity in cells expressing recombinant HER2. Best response was stable disease (12 weeks of nonprogression) in 13 patients. Conclusions TAK-285 was generally well tolerated at the RP2D. Distribution in human CSF was confirmed, but the free concentration of the drug was below that associated with biologically relevant target inhibition

Information-theoretic content selection for automated home video editing

ABSTRACT In automated home video editing, selecting out the most informative contents from the redundant footage is challenging. This paper proposes an information-theoretic approach to content selection by exploring the dependence relations between who (characters) and where (scenes) in the video. First the footage is segmented into basic units about the same characters at the same scene. To compactly represent the dependence relations between scenes and characters, contingency table is used to model their co-occurrence statistics. Suppose the contents about which characters at which scene are dominating by two random variables, an optimal selection criterion is proposed based on joint entropy. To improve the computation efficiency, a pruned N-Best heuristic algorithm is presented to search the most informative video units. Experimental results demonstrated the proposed approach is flexible and effective for automated content selection

Three-Heartbeat Multilead ECG Recognition Method for Arrhythmia Classification

Electrocardiogram (ECG) is the primary basis for the diagnosis of cardiovascular diseases. However, the amount of ECG data of patients makes manual interpretation time-consuming and onerous. Therefore, the intelligent ECG recognition technology is an important means to decrease the shortage of medical resources. This study proposes a novel classification method for arrhythmia that uses for the very first time a three-heartbeat multi-lead (THML) ECG data in which each fragment contains three complete heartbeat processes of multiple ECG leads. The THML ECG data pre-processing method is formulated which makes use of the MIT-BIH arrhythmia database as training samples. Four arrhythmia classification models are constructed based on one-dimensional convolutional neural network (1D-CNN) combined with a priority model integrated voting method to optimize the integrated classification effect. The experiments followed the recommended inter-patient scheme of the Association for the Advancement of Medical Instrumentation (AAMI) recommendations, and the practicability and effectiveness of THML ECG data are proved with ablation experiments. Results show that the average accuracy of the N, V, S, F, and Q classes is 94.82%, 98.10%, 97.28%, 98.70%, and 99.97%, respectively, with the positive predictive value of the N, V, S, and F classes being 97.0%, 90.5%, 71.9%, and 80.4%, respectively. Compared with current studies, the THML ECG data can effectively improve the morphological integrity and time continuity of ECG information and the 1D-CNN model of ECG sequence has a higher accuracy for arrhythmia classification. The proposed method alleviates the problem of insufficient samples, meets the needs of medical ECG interpretation and contributes to the intelligent dynamic research of cardiac disease

A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia

Atrial fibrillation (AF) is the most common cardiovascular disease (CVD); and most existing algorithms are usually designed for the diagnosis (i.e.; feature classification) or prediction of AF. Artificial intelligence (AI) algorithms integrate the diagnosis of AF electrocardiogram (ECG) and predict the possibility that AF will occur in the future. In this paper; we utilized the MIT-BIH AF Database (AFDB); which is composed of data from normal people and patients with AF and onset characteristics; and the AFPDB database (i.e.; PAF Prediction Challenge Database); which consists of data from patients with Paroxysmal AF (PAF; the records contain the ECG preceding an episode of PAF); and subjects who do not have documented AF. We extracted the respective characteristics of the databases and used them in modeling diagnosis and prediction. In the aspect of model construction; we regarded diagnosis and prediction as two classification problems; adopted the traditional support vector machine (SVM) algorithm; and combined them. The improved quantum particle swarm optimization support vector machine (IQPSO-SVM) algorithm was used to speed the training time. During the verification process; the clinical FZU-FPH database created by Fuzhou University and Fujian Provincial Hospital was used for hybrid model testing. The data were obtained from the Holter monitor of the hospital and encrypted. We proposed an algorithm for transforming the PDF ECG waveform images of hospital examination reports into digital data. For the diagnosis model and prediction model trained using the training set of the AFDB and AFPDB databases; the sensitivity; specificity; and accuracy measures were 99.2% and 99.2%; 99.2% and 93.3%; and 91.7% and 92.5% for the test set of the AFDB and AFPDB databases; respectively. Moreover; the sensitivity; specificity; and accuracy were 94.2%; 79.7%; and 87.0%; respectively; when tested using the FZU-FPH database with 138 samples of the ECG composed of two labels. The composite classification and prediction model using a new water-fall ensemble method had a total accuracy of approximately 91% for the test set of the FZU-FPH database with 80 samples with 120 segments of ECG with three labels