A junctionless SONOS nonvolatile memory device constructed with in situ-doped polycrystalline silicon nanowires

In this paper, a silicon-oxide-nitride-silicon nonvolatile memory constructed on an n+-poly-Si nanowire [NW] structure featuring a junctionless [JL] configuration is presented. The JL structure is fulfilled by employing only one in situ heavily phosphorous-doped poly-Si layer to simultaneously serve as source/drain regions and NW channels, thus greatly simplifying the manufacturing process and alleviating the requirement of precise control of the doping profile. Owing to the higher carrier concentration in the channel, the developed JL NW device exhibits significantly enhanced programming speed and larger memory window than its counterpart with conventional undoped-NW-channel. Moreover, it also displays acceptable erase and data retention properties. Hence, the desirable memory characteristics along with the much simplified fabrication process make the JL NW memory structure a promising candidate for future system-on-panel and three-dimensional ultrahigh density memory applications

Statistical identification of gene association by CID in application of constructing ER regulatory network

<p>Abstract</p> <p>Background</p> <p>A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating <it>in silico </it>inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A).</p> <p>Results</p> <p>The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's <it>t</it>-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays.</p> <p>Conclusion</p> <p>CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers.</p> <p>Availability</p> <p>the implementation of CID in R codes can be freely downloaded from <url>http://homepage.ntu.edu.tw/~lyliu/BC/</url>.</p

Effect of music interventions on anxiety during labor: a systematic review and meta-analysis of randomized controlled trials

Background Anxiety is commonly experienced during the delivery process and has shown to have adverse effects on maternal and infant health outcomes. Music interventions tend to reduce the effects of anxiety in diverse populations, are low cost, are easily accessible, and have high acceptability. The aim of this review and meta-analysis was to assess the effectiveness of music interventions in reducing anxiety levels among women during labor. Methods Seven databases from inception to the end of December, 2018, without any language or time restriction including Embase, PubMed, the Cochrane Library, the Cumulative Index to Nursing and Allied Health, PsycINFO, Airiti Library, and PerioPath: Index to Taiwan Periodical Literature were searched using key terms related to pregnancy, anxiety, and music. Randomized controlled trials that assessed the effect of music during labor and measured anxiety levels as an outcome were included. Meta-analyses were conducted to assess anxiety reduction following a music intervention compared to that after placebo treatment. Results A total of 14 studies that investigated a total of 1,310 participants were included in this review. The meta-analyses indicated that those in the intervention group had a significant decrease in anxiety scores (standardized mean difference = −2.40, 95% confidence interval (CI) [−3.29 to −1.52], p < 0.001; I2 = 97.66%), heart rate (HR) (difference in means = −3.04 beats/min, 95% CI [−4.79 to −1.29] beats/min, p = 0.001; I2 = 0.00%), systolic blood pressure (SBP) (difference in means = −3.71 mmHg, 95% CI [−7.07 to −0.35] mmHg, p = 0.031; I2 = 58.47%), and diastolic blood pressure (DBP) (difference in means = −3.54 mmHg, 95% CI [−5.27 to −1.81] mmHg, p < 0.001; I2 = 0.00%) as compared to the women in the control group. Conclusions Music interventions may decrease anxiety scores and physiological indexes related to anxiety (HR, SBP, and DBP). Music interventions may be a good non-pharmacological approach for decreasing anxiety levels during labor

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1

A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a robust computerized respiratory sound analysis algorithm has not yet been validated in practical applications. In this study, we developed a lung sound database (HF_Lung_V1) comprising 9,765 audio files of lung sounds (duration of 15 s each), 34,095 inhalation labels, 18,349 exhalation labels, 13,883 continuous adventitious sound (CAS) labels (comprising 8,457 wheeze labels, 686 stridor labels, and 4,740 rhonchi labels), and 15,606 discontinuous adventitious sound labels (all crackles). We conducted benchmark tests for long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (BiLSTM), bidirectional GRU (BiGRU), convolutional neural network (CNN)-LSTM, CNN-GRU, CNN-BiLSTM, and CNN-BiGRU models for breath phase detection and adventitious sound detection. We also conducted a performance comparison between the LSTM-based and GRU-based models, between unidirectional and bidirectional models, and between models with and without a CNN. The results revealed that these models exhibited adequate performance in lung sound analysis. The GRU-based models outperformed, in terms of F1 scores and areas under the receiver operating characteristic curves, the LSTM-based models in most of the defined tasks. Furthermore, all bidirectional models outperformed their unidirectional counterparts. Finally, the addition of a CNN improved the accuracy of lung sound analysis, especially in the CAS detection tasks.Comment: 48 pages, 8 figures. To be submitte

Efficacy of concurrent radiotherapy in patients with locally advanced rectal cancer and synchronous metastasis receiving systemic therapy

BackgroundNeoadjuvant chemoradiotherapy followed by total mesorectal excision is the standard treatment for patients with nonmetastatic locally advanced rectal cancer (LARC). However, for patients with LARC and synchronous metastasis, the optimal treatment strategy and sequence remain inconclusive. In the present study, we evaluated the efficacy and safety of concurrent radiotherapy in patients with de novo metastatic rectal cancer who received chemotherapy and targeted therapy.MethodsWe retrospectively reviewed the data of 63 patients with LARC and synchronous metastasis who received intensive therapy at the study hospital between April 2015 and November 2018. The included patients were divided into two groups: RT-CT, those who received systemic chemotherapy with targeted therapy and concurrent radiotherapy (for primary rectal cancer), and CT, those who received only systemic chemotherapy with targeted therapy.ResultsTreatment response was better in the RT-CT group than in the CT group. The rate of primary tumor resection (PTR) was higher in the RT-CT group than in the CT group (71.4% and 42.9%, respectively; P = .0286). The RT-CT group exhibited considerably longer local recurrence-free survival (P = .0453) and progression-free survival (PFS; from 13.3 to 22.5 months) than did the CT group (P = .0091); however, the groups did not differ in terms of overall survival (OS; P = .49). Adverse events were almost similar between the groups, except frequent diarrhea, the prevalence of which was higher in the RT-CT group than in the CT group (59.5% and 23.8%, respectively; P = .0075).ConclusionsIn the era of biologics, radiotherapy may increase the resectability of primary rectal tumors, reducing the risk of locoregional failure and prolonging PFS. Concurrent pelvic radiotherapy may not substantially improve OS, which is indicated by metastasis. Hence, the resection of the distant metastases may be essential for improving long-term OS. To further determine the efficacy of concurrent radiotherapy, additional prospective, randomized studies must combine preoperative pelvic radiotherapy with PTR and metastectomy to treat patients with stage IV LARC

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population.

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction  = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

The Determinants of Liver Fibrosis in Patients with Nonalcoholic Fatty Liver Disease and Type 2 Diabetes Mellitus

Liver fibrosis is a key pathophysiology process in chronic liver disease. It is still unclear whether the impact of liver fibrosis is not fully realized in type 2 diabetes mellitus (T2D) patients with nonalcoholic fatty liver disease (NAFLD), and the factors affecting nonalcoholic steatohepatitis (NASH) or liver stiffness also remain unclear. The aim of this study was to evaluate the determinants of liver fibrosis and in T2D patients with NAFLD. Liver fibrosis and steatosis were measured using transient elastography (FibroScan). Of 226 T2D patients with NAFLD, 50 with liver fibrosis had higher body mass index, serum uric acid, triglyceride and glycated hemoglobin levels and lower high density lipoprotein levels than 176 without liver fibrosis. Multivariate analysis revealed that aging, obesity, sulfonylurea usage and high levels of AST increased the risk of liver fibrosis in T2D patients with NAFLD. Our findings provide useful information to clinical physicians for earlier detection of liver fibrosis in T2D patients with NAFLD and to prevent liver fibrosis through controlling these risk factors

Optimal Allocation of Virtual Machines in Cloud Computing

Virtualization is one of the core technologies used in cloud computing to provide services on demand for end users over the Internet. Most current research allocates virtual machines to physical machines based on CPU utilization. However, for many applications that require communication between services running on different servers, communication costs influence the overall performance. Therefore, this study focuses on the optimal allocation of virtual machines across multiple geographically dispersed data centers, with the objective of minimizing communication costs. The original problem can be constructed as a quadratic assignment problem that is a classical NP-hard combinatorial optimization problem. This study adopts an efficient deterministic optimization approach to reformulate the original problem as a mixed-integer linear program that may be solved to obtain a globally optimal solution. Since the required bandwidth matrix and communication cost matrix are symmetric, the mathematical model of virtual machine placement can be simplified. Several numerical examples drawn from the literature are solved to demonstrate the computational efficiency of the proposed method for determining the optimal virtual machine allocation in cloud computing