Sovereign: User-Controlled Smart Homes

Smart homes made up of Internet of Things (IoT) devices have seen wide deployment in recent years, with most, if not all, of them controlled by remote servers in the cloud. Such designs raise security and privacy concerns for end users. We believe that the current situation has largely resulted from lacking a systematic home IoT framework to support localized end user control. To let end users take back the control of smart homes, we propose Sovereign, an IoT system framework that allows users to securely control home IoT systems without depending on a cloud backend. Unlike existing solutions, Sovereign networks home IoT devices and applications using named data with application-level semantics; the names are then used to construct security mechanisms. Users define security policies and these policies are then executed by the localized security modules. We implement Sovereign as a pub/sub based development platform together with a prototype local IoT controller. Our preliminary evaluation shows that Sovereign provides an easy-to-use systematic solution to secure smart homes under user control without imposing noticeable overhead

The prognostic index PRIMA-PI combined with Ki67 as a better predictor of progression of disease within 24 months in follicular lymphoma

BackgroundProgression of disease within 24 months (POD24) is a risk factor for poor survival in follicular lymphoma (FL), and there is currently no optimal prognostic model to accurately predict patients with early disease progression. How to combine traditional prognostic models with new indicators to establish a new prediction system, to predict the early progression of FL patients more accurately is a future research direction.MethodsThis study retrospectively analyzed patients with newly diagnosed FL patients in Shanxi Provincial Cancer Hospital from January 2015 to December 2020. Data from patients undergoing immunohistochemical detection (IHC) were analyzed using χ2 test and multivariate Logistic regression. Also, we built a nomogram model based on the results of LASSO regression analysis of POD24, which was validated in both the training set and validation set, and additional external validation was performed using a dataset (n = 74) from another center, Tianjin Cancer Hospital.ResultsThe multivariate Logistic regression results suggest that high-risk PRIMA-PI group, Ki-67 high expression represent risk factors for POD24 (P<0.05). Next, PRIMA-PI and Ki67 were combined to build a new model, namely, PRIMA-PIC to reclassify high and low-risk groups. The result showed that the new clinical prediction model constructed by PRIMA-PI with ki67 has a high sensitivity to the prediction of POD24. Compared to PRIMA-PI, PRIMA-PIC also has better discrimination in predicting patient’s progression-free survival (PFS) and overall survival (OS). In addition, we built nomogram models based on the results of LASSO regression (histological grading, NK cell percentage, PRIMA-PIC risk group) in the training set, which were validated using internal validation set and external validation set, we found that C-index and calibration curve showed good performance.ConclusionAs such, the new predictive model-based nomogram established by PRIMA-PI and Ki67 could well predict the risk of POD24 in FL patients, which boasts clinical practical value

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research

Trends in Notifiable Infectious Diseases in China: Implications for Surveillance and Population Health Policy

This study aimed to analyse trends in notifiable infectious diseases in China, in their historical context. Both English and Chinese literature was searched and diseases were categorised according to the type of disease or transmission route. Temporal trends of morbidity and mortality rates were calculated for eight major infectious diseases types. Strong government commitment to public health responses and improvements in quality of life has led to the eradication or containment of a wide range of infectious diseases in China. The overall infectious diseases burden experienced a dramatic drop during 1975–1995, but since then, it reverted and maintained a gradual upward trend to date. Most notifiable diseases are contained at a low endemic level; however, local small-scale outbreaks remain common. Tuberculosis, as a bacterial infection, has re-emerged since the 1990s and has become prevalent in the country. Sexually transmitted infections are in a rapid, exponential growth phase, spreading from core groups to the general population. Together human immunodeficiency virus (HIV), they account for 39% of all death cases due to infectious diseases in China in 2008. Zoonotic infections, such as severe acute respiratory syndrome (SARS), rabies and influenza, pose constant threats to Chinese residents and remain the most deadly disease type among the infected individuals. Therefore, second-generation surveillance of behavioural risks or vectors associated with pathogen transmission should be scaled up. It is necessary to implement public health interventions that target HIV and relevant coinfections, address transmission associated with highly mobile populations, and reduce the risk of cross-species transmission of zoonotic pathogens

The TOP-SCOPE Survey of Planck Galactic Cold Clumps : Survey Overview and Results of an Exemplar Source, PGCC G26.53+0.17

The low dust temperatures (<14 K) of Planck Galactic cold clumps (PGCCs) make them ideal targets to probe the initial conditions and very early phase of star formation. "TOP-SCOPE" is a joint survey program targeting similar to 2000 PGCCs in J = 1-0 transitions of CO isotopologues and similar to 1000 PGCCs in 850 mu m continuum emission. The objective of the "TOP-SCOPE" survey and the joint surveys (SMT 10 m, KVN 21 m, and NRO 45 m) is to statistically study the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments. The observations, data analysis, and example science cases for these surveys are introduced with an exemplar source, PGCC G26.53+0.17 (G26), which is a filamentary infrared dark cloud (IRDC). The total mass, length, and mean line mass (M/L) of the G26 filament are similar to 6200 M-circle dot, similar to 12 pc, and similar to 500 M-circle dot pc(-1), respectively. Ten massive clumps, including eight starless ones, are found along the filament. The most massive clump as a whole may still be in global collapse, while its denser part seems to be undergoing expansion owing to outflow feedback. The fragmentation in the G26 filament from cloud scale to clump scale is in agreement with gravitational fragmentation of an isothermal, nonmagnetized, and turbulent supported cylinder. A bimodal behavior in dust emissivity spectral index (beta) distribution is found in G26, suggesting grain growth along the filament. The G26 filament may be formed owing to large-scale compression flows evidenced by the temperature and velocity gradients across its natal cloud.Peer reviewe

Plasma mRNA expression levels of BRCA1 and TS as potential predictive biomarkers for chemotherapy in gastric cancer

OBJECTIVE: Personalized chemotherapy based on predictive biomarkers can maximize efficacy. However, tumor tissue obtained at the time of initial diagnosis will not reflect genetic alterations observed at the time of disease progression. We have examined whether plasma mRNA levels can be a surrogate for tumor levels in predicting chemosensitivity. METHODS: In 150 gastric cancer patients, mRNA levels of BRCA1 and TS were assessed in plasma and paired tumor tissue. The Mann-Whitney U-test was used to compare mRNA expression levels between tumor samples exhibiting in vitro sensitivity or resistance to docetaxel and pemetrexed. All statistical tests were two-sided. RESULTS: There were significant correlations between plasma and tumor mRNA levels of BRCA1 (rho = 0.696, P < 0.001) and TS (rho = 0.620, P < 0.001). BRCA1 levels in plasma (docetaxel-sensitive: 1.25; docetaxel-resistant: 0.50, P < 0.001) and tumor (docetaxel-sensitive: 8.81; docetaxel-resistant: 4.88, P < 0.001) were positively associated with docetaxel sensitivity. TS levels in plasma (pemetrexed-sensitive: 0.90; pemetrexed-resistant: 1.82, P < 0.001) and tumor (pemetrexed-sensitive: 6.56; pemetrexed-resistant: 16.69, P < 0.001) were negatively associated with pemetrexed sensitivity. CONCLUSIONS: Plasma mRNA expression levels mirror those in the tumor and may have a promising role as potential predictive biomarkers for chemotherapy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-014-0355-2) contains supplementary material, which is available to authorized users