PATTERN: Pain Assessment for paTients who can't TEll using Restricted Boltzmann machiNe.

BackgroundAccurately assessing pain for those who cannot make self-report of pain, such as minimally responsive or severely brain-injured patients, is challenging. In this paper, we attempted to address this challenge by answering the following questions: (1) if the pain has dependency structures in electronic signals and if so, (2) how to apply this pattern in predicting the state of pain. To this end, we have been investigating and comparing the performance of several machine learning techniques.MethodsWe first adopted different strategies, in which the collected original n-dimensional numerical data were converted into binary data. Pain states are represented in binary format and bound with above binary features to construct (n + 1) -dimensional data. We then modeled the joint distribution over all variables in this data using the Restricted Boltzmann Machine (RBM).ResultsSeventy-eight pain data items were collected. Four individuals with the number of recorded labels larger than 1000 were used in the experiment. Number of avaliable data items for the four patients varied from 22 to 28. Discriminant RBM achieved better accuracy in all four experiments.ConclusionThe experimental results show that RBM models the distribution of our binary pain data well. We showed that discriminant RBM can be used in a classification task, and the initial result is advantageous over other classifiers such as support vector machine (SVM) using PCA representation and the LDA discriminant method

First-principles method of propagation of tightly bound excitons: exciton band structure of LiF and verification with inelastic x-ray scattering

We propose a simple first-principles method to describe propagation of tightly bound excitons. By viewing the exciton as a composite object (an effective Frenkel exciton in Wannier orbitals), we define an exciton kinetic kernel to encapsulate the exciton propagation and decay for all binding energy. Applied to prototypical LiF, our approach produces three exciton bands, which we verified quantitatively via inelastic x-ray scattering. The proposed real-space picture is computationally inexpensive and thus enables study of the full exciton dynamics, even in the presence of surfaces and impurity scattering. It also provides intuitive understanding to facilitate practical exciton engineering in semiconductors, strongly correlated oxides, and their nanostructures.Comment: 5 pages, 4 figures. Accepted by PR

Anxiety predicts internet addiction, which predicts depression among male college students: A cross-lagged comparison by sex

ObjectivesInternet addiction has become an increasingly serious public health issue, putting young people at particular risk of psychological harm. This study aimed to analyze the interactions between college students’ depression, anxiety, and Internet addiction and explore how these interactions differ between men and women.MethodsA 6-month follow-up study was conducted on 234 college students using the Self-Rating Depression Scale, Self-rating Anxiety Scale, and Revised Chen Internet Addiction Scale.ResultsDepression, anxiety, and Internet addiction were positively correlated (p < 0.01). Anxiety can predict Internet addiction and that Internet addiction can predict depression. Moreover, anxiety had a significant predictive effect on Internet addiction among men.ConclusionAnxiety predicts Internet addiction, and Internet addiction predicts depression among male college students. These findings may better inform future Internet addiction intervention strategies. Particularly, interventions may better address Internet addiction by focusing on the role of anxiety, especially among men

Cold atmospheric plasma for selectively ablating metastatic breast cancer cells

Traditional breast cancer treatments such as surgery and radiotherapy contain many inherent limitations with regards to incomplete and nonselective tumor ablation. Cold atomospheric plasma (CAP) is an ionized gas where the ion temperature is close to room temperature. It contains electrons, charged particles, radicals, various excited molecules, UV photons and transient electric fields. These various compositional elements have the potential to either enhance and promote cellular activity, or disrupt and destroy them. In particular, based on this unique composition, CAP could offer a minimally-invasive surgical approach allowing for specific cancer cell or tumor tissue removal without influencing healthy cells. Thus, the objective of this research is to investigate a novel CAP-based therapy for selectively bone metastatic breast cancer treatment. For this purpose, human metastatic breast cancer (BrCa) cells and bone marrow derived human mesenchymal stem cells (MSCs) were separately treated with CAP, and behavioral changes were evaluated after 1, 3, and 5 days of culture. With different treatment times, different BrCa and MSC cell responses were observed. Our results showed that BrCa cells were more sensitive to these CAP treatments than MSCs under plasma dose conditions tested. It demonstrated that CAP can selectively ablate metastatic BrCa cells in vitro without damaging healthy MSCs at the metastatic bone site. In addition, our study showed that CAP treatment can significantly inhibit the migration and invasion of BrCa cells. The results suggest the great potential of CAP for breast cancer therapy

The effect of tuning cold plasma composition on glioblastoma cell viability

Previous research in cold atmospheric plasma (CAP) and cancer cell interaction has repeatedly proven that the cold plasma induced cell death. It is postulated that the reactive oxygen species (ROS) and reactive nitrogen species (RNS) play a major role in the CAP cancer therapy. In this paper, we seek to determine a mechanism of CAP therapy on glioblastoma cells (U87) through an understanding of the composition of the plasma, including treatment time, voltage, flow-rate and plasma-gas composition. In order to determine the threshold of plasma treatment on U87, normal human astrocytes (E6/E7) were used as the comparison cell line. Our data showed that the 30 sec plasma treatment caused 3-fold cell death in the U87 cells compared to the E6/E7 cells. All the other compositions of cold plasma were performed based on this result: plasma treatment time was maintained at 30 s per well while other plasma characteristics such as voltage, flow rate of source gas, and composition of source gas were changed one at a time to vary the intensity of the reactive species composition in the plasma jet, which may finally have various effect on cells reflected by cell viability. We defined a term “plasma dosage” to summarize the relationship of all the characteristics and cell viability