Time series classification is an important research topic in machine learning and data mining communities, since time series data exist in many application domains. Recent studies have shown that ...machine learning algorithms could benefit from good feature representation, explaining why deep learning has achieved breakthrough performance in many tasks. In deep learning, the convolutional neural network (CNN) is one of the most well-known approaches, since it incorporates feature learning and classification task in a unified network architecture. Although CNN has been successfully applied to image and text domains, it is still a challenge to apply CNN to time series data. This paper proposes a tensor scheme along with a novel deep learning architecture called multivariate convolutional neural network (MVCNN) for multivariate time series classification, in which the proposed architecture considers multivariate and lag-feature characteristics. We evaluate our proposed method with the prognostics and health management (PHM) 2015 challenge data, and compare with several algorithms. The experimental results indicate that the proposed method outperforms the other alternatives using the prediction score, which is the evaluation metric used by the PHM Society 2015 data challenge. Besides performance evaluation, we provide detailed analysis about the proposed method.
In the past decades, many optimization methods have been devised and applied to job shop scheduling problem (JSSP) to find the optimal solution. Many methods assumed that the scheduling results were ...applied to static environments, but the whole environments in the real world are always dynamic. Moreover, many unexpected events such as machine breakdowns and material problems may be present to adversely affect the initial job scheduling. This work views JSSP as a sequential decision making problem and proposes to use deep reinforcement learning to cope with this problem. The combination of deep learning and reinforcement learning avoids handcraft features as used in traditional reinforcement learning, and it is expected that the combination will make the whole learning phase more efficient. Our proposed model comprises actor network and critic network, both including convolution layers and fully connected layer. Actor network agent learns how to behave in different situations, while critic network helps agent evaluate the value of statement then return to actor network. This work proposes a parallel training method, combining asynchronous update as well as deep deterministic policy gradient (DDPG), to train the model. The whole network is trained with parallel training on a multi-agent environment and different simple dispatching rules are considered as actions. We evaluate our proposed model on more than ten instances that are present in a famous benchmark problem library - OR library. The evaluation results indicate that our method is comparative in static JSSP benchmark problems, and achieves a good balance between makespan and execution time in dynamic environments. Scheduling score of our method is 91.12% in static JSSP benchmark problems, and 80.78% in dynamic environments.
Go for gold: As‐prepared insulin–Au nanoclusters (NCs) show intense red fluorescence, excellent biocompatibility, and preservation of natural insulin bioactivity in lowering the blood‐glucose level. ...Their versatility in applications is demonstrated by fluorescence imaging, X‐ray computed tomography, and insulin–inhibitor interactions (see picture; IDE=insulin‐degrading enzyme).
Abstract
Context
Dipeptidyl peptidase IV (DPP4) is overexpressed in thyroid cancer and certain malignancies. Furthermore, DPP4 has been identified as a discriminatory marker for thyroid cancer. ...However, it remains unclear whether DPP4 expression plays a prognostic role.
Objective
The aim of this study was to investigate the expression and function of DPP4 in thyroid cancer and the mechanisms involved.
Design
We determined the expression of DPP4 by immunohistochemistry in tissue microarrays of thyroid tumors. In vitro functional studies were performed after genetic and pharmacological inhibition of DPP4. Gene expression and pathway analyses were used to identify downstream targets. The therapeutic potential of DPP4 inhibition was evaluated in a mouse xenograft model.
Results
High DPP4 expression was associated with extrathyroidal extension (P < 0.001), BRAF mutation (P < 0.001), and advanced tumor stage (P = 0.007) in papillary thyroid cancer. Patients in the high–DPP4 expression group were less likely to be classified as having no evidence of disease at final follow-up (P = 0.042). DPP4 silencing or treatment with DPP4 inhibitors significantly suppressed colony formation, cell migration, and invasion. Analysis of differentially expressed genes after DPP4 knockdown suggested that the transforming growth factor-β signaling pathway is involved. In vivo experiments revealed that sitagliptin treatment reduced tumor growth and xenograft transforming growth factor-β receptor I expression.
Conclusions
Increased DPP4 expression is associated with cellular invasion and more aggressive disease in papillary thyroid cancer. Targeting DPP4 may be a therapeutic strategy for DPP4-expressing thyroid cancer.
We studied DPP4 expression in thyroid tumors and found that DPP4 upregulation is associated with more advanced papillary thyroid cancer and may be a prognostic marker and therapeutic target.
Sustained energy starvation leads to activation of AMP-activated protein kinase (AMPK), which coordinates energy status with numerous cellular processes including metabolism, protein synthesis, and ...autophagy. Here, we report that AMPK phosphorylates the histone methyltransferase EZH2 at T311 to disrupt the interaction between EZH2 and SUZ12, another core component of the polycomb repressive complex 2 (PRC2), leading to attenuated PRC2-dependent methylation of histone H3 at Lys27. As such, PRC2 target genes, many of which are known tumor suppressors, were upregulated upon T311-EZH2 phosphorylation, which suppressed tumor cell growth both in cell culture and mouse xenografts. Pathologically, immunohistochemical analyses uncovered a positive correlation between AMPK activity and pT311-EZH2, and higher pT311-EZH2 correlates with better survival in both ovarian and breast cancer patients. Our finding suggests that AMPK agonists might be promising sensitizers for EZH2-targeting cancer therapies.
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•AMPK activation attenuates PRC2-mediated epigenetic silencing•AMPK phosphorylates EZH2 at T311 to disrupt EZH2-SUZ12 interaction•EZH2 T311 phosphorylation inhibits PRC2 oncogenic function•EZH2 T311 phosphorylation correlates with better survival in cancer patients
The metabolic state of the cell can be connected to gene expression and modification of histones through several mechanisms. Wan et al. find that AMPK-mediated phosphorylation of EZH2 at T311 inhibits PRC2 methyltransferase activity to relieve PRC2-dependent epigenetic silencing and subsequently suppresses tumorigenesis.
Imbalanced data is characterized by the severe difference in observation frequency between classes and has received a lot of attention in data mining research. The prediction performances usually ...deteriorate as classifiers learn from imbalanced data, as most classifiers assume the class distribution is balanced or the costs for different types of classification errors are equal. Although several methods have been devised to deal with imbalance problems, it is still difficult to generalize those methods to achieve stable improvement in most cases. In this study, we propose a novel framework called model-based synthetic sampling (MBS) to cope with imbalance problems, in which we integrate modeling and sampling techniques to generate synthetic data. The key idea behind the proposed method is to use regression models to capture the relationship between features and to consider data diversity in the process of data generation. We conduct experiments on 13 datasets and compare the proposed method with 10 methods. The experimental results indicate that the proposed method is not only comparative but also stable. We also provide detailed investigations and visualizations of the proposed method to empirically demonstrate why it could generate good data samples.
Persons with dementia are at high risk for loss of decision-making ability due to increased cognitive decline as the disease progresses. Participation in advance care planning (ACP) discussions in ...the early stages of dementia is crucial for end-of-life (EoL) decision-making to ensure quality of EoL care. A lack of discussions about ACP and EoL care between persons with dementia and family caregivers (FCGs), can lead to decisional conflicts when persons with dementia are in the later stages of the disease. This study explored the effects of a family-centered ACP information intervention among persons with dementia and FCGs. The study was conducted in outpatient clinics in Taiwan. Participants were dyads (n = 40) consisting of persons diagnosed with mild cognitive impairment or mild dementia and their FCGs. A one-group, pretest-posttest, pre-experimental design was employed. The intervention was provided by an ACP-trained senior registered nurse and was guided by ACP manuals and family-centered strategies. Outcome data were collected with four structured questionnaires regarding knowledge of end-stage dementia treatment, knowledge of ACP, attitude towards ACP, and EoL decisional conflict about acceptance or refusal of cardiopulmonary resuscitation, ventilators, and tracheostomy. Paired t tests compared differences between pre-intervention data and 4-weeks' post-intervention data. The intervention resulted in significant improvements among persons with dementia and FCGs for knowledge of end-stage dementia treatment (p = .008 and p < .001, respectively), knowledge of ACP (both p < .001), and significant reductions in decisional conflicts (both p < .001). Scores for positive and negative attitude toward ACP did not change for persons with dementia; however, there was a reduction in negative attitude for FCGs (p = .001). Clinical care for persons with dementia should incorporate ACP interventions that provide knowledge about EoL dementia care using family-centered care strategies that facilitate regular and continuous communication between FCGs, persons with dementia, and medical personnel to reduce decisional conflicts for EoL care.
Aim
Skeletal muscle loss is a common feature of aging, and is associated with unfavorable outcomes. Although several indexes of skeletal muscle mass measurement have been developed, the most optimal ...index for sarcopenia diagnosis among Asian populations has remained unclear. The present study aimed to evaluate the relationship between skeletal muscle mass and physical performance among community‐dwelling people in Taiwan.
Methods
Data of the I‐Lan Longitudinal Aging Study (ILAS) were retrieved for study. Comparisons between demographic profiles, physical performance and skeletal muscle mass (measured by dual‐energy X‐ray absorptiometry) were carried out. Skeletal muscle mass expressed by lean body mass divided by squared height (LBM/ht2), appendicular muscle mass divided by squared height (ASM/ht2) and percent skeletal muscle index (SMI%) were compared between measurements of physical performance.
Results
Overall, the data of 532 participants (mean age 64.6 ± 9.5 years, male 53.0%) were retrieved for analysis. Age was associated with poorer physical performance, and decreased ASM/ht2 and LBM/ht2, but not SMI%. Skeletal muscle mass (SMI%) was less significantly related to slow walking speed than ASM/ht2 in men. In women, all three muscle indexes showed no significant association between slow walking speed. In contrast, low handgrip strength was strongly associated with decreased skeletal muscle mass (measured by ASM/ht2 and LBM/ht2, but not SMI%) in both men and women.
Conclusions
Skeletal muscle mass was significantly associated with handgrip strength along with aging, but the association of skeletal muscle mass and walking speed was less significant. In sarcopenia diagnosis among Asian populations, ASM/ht2 should be the most suitable index for skeletal muscle mass measurements, and physical performance should be measured universally beyond measurements of skeletal muscle mass. Geriatr Gerontol Int 2013; 13: 964–971.
With the advancements in nanotechnology, studies on the synthesis, modification, application, and toxicology evaluation of nanomaterials are gaining increased attention. In particular, the ...applications of nanomaterials in biological systems are attracting considerable interest because of their unique, tunable, and versatile physicochemical properties. Artificially engineered nanomaterials can be well controlled for appropriate usage, and the tuned physicochemical properties directly influence the interactions between nanomaterials and cells. This review summarizes recently synthesized major nanomaterials that have potential biomedical applications. Focus is given on the interactions, including cellular uptake, intracellular trafficking, and toxic response, while changing the physicochemical properties of versatile materials. The importance of physicochemical properties such as the size, shape, and surface modifications of the nanomaterials in their biological effects is also highlighted in detail. The challenges of recent studies and future prospects are presented as well. This review benefits relatively new researchers in this area and gives them a systematic overview of nano-bio interaction, hopefully for further experimental design.
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