Spatial Index for Uncertain Time Series

A search for patterns in uncertain time series is time-expensive in today\u27s large databases using the currently available methods. To accelerate the search process for uncertain time series data, in this paper, we explore a spatial index structure, which uses uncertain information stored in minimum bounding rectangle and ameliorates the general prune/search process along the path from the root to leaves. To get a better performance, we normalize the uncertain time series using the weighted variance before the prune/hit process. Meanwhile, we add two goodness measures with respect to the variance to improve the robustness. The extensive experiments show that, compared with the primitive probabilistic similarity search algorithm, the prune/hit process of the spatial index can be more efficient and robust using the specific preprocess and variant index operations with just a little loss of accuracy

Fast Online Similarity Search for Uncertain Time Series

To achieve fast retrieval of online data, it is needed for the retrieval algorithm to increase throughput while reducing latency. Based on the traditional online processing algorithm for time series data, we propose a spatial index structure that can be updated and searched quickly in a real-time environment. At the same time, we introduce an adaptive segmentation method to divide the space corresponding to nodes. Unlike traditional retrieval algorithms, for uncertain time series, the distance threshold used for screening will dynamically change due to noise during the search process. Extensive experiments are conducted to compare the accuracy of the query results and the timeliness of the algorithm. The results show that the index structure proposed in this paper has better efficiency while maintaining a similar true positive ratio

Development and Internal Validation of a Novel Nomogram for Predicting Lymph Node Invasion for Prostate Cancer Patients Undergoing Extended Pelvic Lymph Node Dissection

BACKGROUND: Few studies have focused on the performance of Briganti 2012, Briganti 2017 and MSKCC nomograms in the Chinese population in assessing the risk of lymph node invasion(LNI) in prostate cancer(PCa) patients and identifying patients suitable for extended pelvic lymph node dissection(ePLND). We aimed to develop and validate a novel nomogram based on Chinese PCa patients treated with radical prostatectomy(RP) and ePLND for predicting LNI. METHODS: We retrospectively retrieved clinical data of 631 patients with localized PCa receiving RP and ePLND at a Chinese single tertiary referral center. All patients had detailed biopsy information from experienced uropathologist. Multivariate logistic-regression analyses were performed to identify independent factors associated with LNI. The discrimination accuracy and net-benefit of models were quantified using the area under curve(AUC) and Decision curve analysis(DCA).The nonparametric bootstrapping were used to internal validation. RESULTS: A total of 194(30.7%) patients had LNI. The median number of removed lymph nodes was 13(range, 11-18). In univariable analysis, preoperative prostate-specific antigen(PSA), clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa, percentage of positive cores, percentage of positive cores with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy differed significantly. The multivariable model that included preoperative PSA, clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy represented the basis for the novel nomogram. Based on a 12% cutoff, our results showed that 189(30%) patients could have avoided ePLND while only 9(4.8%) had LNI missing ePLND. Our proposed model achieved the highest AUC (proposed model vs Briganti 2012 vs Briganti 2017 vs MSKCC model: 0.83 vs 0.8 vs 0.8 vs 0.8, respectively) and highest net-benefit CONCLUSION: We developed and validated a nomogram predicting the risk of LNI based on Chinese PCa patients, which demonstrated superior performance compared with previous nomograms

Spatial Index for Uncertain Time Series

A search for patterns in uncertain time series is time-expensive in today's large databases using the currently available methods. To accelerate the search process for uncertain time series data, in this paper, we explore a spatial index structure, which uses uncertain information stored in minimum bounding rectangle and ameliorates the general prune/search process along the path from the root to leaves. To get a better performance, we normalize the uncertain time series using the weighted variance before the prune/hit process. Meanwhile, we add two goodness measures with respect to the variance to improve the robustness. The extensive experiments show that, compared with the primitive probabilistic similarity search algorithm, the prune/hit process of the spatial index can be more efficient and robust using the specific preprocess and variant index operations with just a little loss of accuracy

Targeting to Tumor-Harbored Bacteria for Precision Tumor Therapy

The differential tumor environment guides various antitumor drug delivery strategies for efficient cancer treatment. Here, based on the special bacteria-enriched tumor environment, we report a different drug delivery strategy by targeting bacteria inhabiting tumor sites. With a tissue microarray analysis, it was found that bacteria amounts displayed significant differences between tumor and normal tissues. Bacteria-targeted mesoporous silica nanoparticles decorated with bacterial lipoteichoic acid (LTA) antibody (LTA-MSNs) could precisely target bacteria in tumors and deliver antitumor drugs. By the intravenous administration of bacteria-targeted nanoparticles, we showed in mice with colon cancer, lung cancer, and breast cancer that LTA-MSNs exhibited a high tumor-targeting ability. As a proof-of-concept study, tumor microbes as some of the characteristics of a tumor environment could be utilized as potential targets for tumor targeting. This bacteria-guided tumor-targeting strategy might have great potential in differential drug delivery and cancer treatment

Load-induced dynamical transitions at graphene interfaces

The structural superlubricity (SSL), a state of near-zero friction between two contacted solid surfaces, has been attracting rapidly increasing research interest since it was realized in microscale graphite in 2012. An obvious question concerns the implications of SSL for micro- and nanoscale devices such as actuators. The simplest actuators are based on the application of a normal load; here we show that this leads to remarkable dynamical phenomena in microscale graphite mesas. Under an increasing normal load, we observe mechanical instabilities leading to dynamical states, the first where the loaded mesa suddenly ejects a thin flake and the second characterized by peculiar oscillations, during which a flake repeatedly pops out of the mesa and retracts back. The measured ejection speeds are extraordinarily high (maximum of 294 m/s), and correspond to ultrahigh accelerations (maximum of 1.1×1010 m/s2). These observations are rationalized using a simple model, which takes into account SSL of graphite contacts and sample microstructure and considers a competition between the elastic and interfacial energies that defines the dynamical phase diagram of the system. Analyzing the observed flake ejection and oscillations, we conclude that our system exhibits a high speed in SSL, a low friction coefficient of 3.6×10−6, and a high quality factor of 3×107 compared with what has been reported in literature. Our experimental discoveries and theoretical findings suggest a route for development of SSL-based devices such as high-frequency oscillators with ultrahigh quality factors and optomechanical switches, where retractable or oscillating mirrors are requiredISSN:0027-8424ISSN:1091-649

Development and internal validation of a novel nomogram for predicting lymph node invasion for prostate cancer patients undergoing extended pelvic lymph node dissection

BackgroundFew studies have focused on the performance of Briganti 2012, Briganti 2017 and MSKCC nomograms in the Chinese population in assessing the risk of lymph node invasion(LNI) in prostate cancer(PCa) patients and identifying patients suitable for extended pelvic lymph node dissection(ePLND). We aimed to develop and validate a novel nomogram based on Chinese PCa patients treated with radical prostatectomy(RP) and ePLND for predicting LNI.MethodsWe retrospectively retrieved clinical data of 631 patients with localized PCa receiving RP and ePLND at a Chinese single tertiary referral center. All patients had detailed biopsy information from experienced uropathologist. Multivariate logistic-regression analyses were performed to identify independent factors associated with LNI. The discrimination accuracy and net-benefit of models were quantified using the area under curve(AUC) and Decision curve analysis(DCA).The nonparametric bootstrapping were used to internal validation.ResultsA total of 194(30.7%) patients had LNI. The median number of removed lymph nodes was 13(range, 11-18). In univariable analysis, preoperative prostate-specific antigen(PSA), clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa, percentage of positive cores, percentage of positive cores with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy differed significantly. The multivariable model that included preoperative PSA, clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy represented the basis for the novel nomogram. Based on a 12% cutoff, our results showed that 189(30%) patients could have avoided ePLND while only 9(4.8%) had LNI missing ePLND. Our proposed model achieved the highest AUC (proposed model vs Briganti 2012 vs Briganti 2017 vs MSKCC model: 0.83 vs 0.8 vs 0.8 vs 0.8, respectively) and highest net-benefit via DCA in the Chinese cohort compared with previous nomograms. In internal validation of proposed nomogram, all variables had a percent inclusion greater than 50%.ConclusionWe developed and validated a nomogram predicting the risk of LNI based on Chinese PCa patients, which demonstrated superior performance compared with previous nomograms

Normalizing Tumor Microenvironment Based on Photosynthetic Abiotic/Biotic Nanoparticles

Tumor hypoxia has attained the status of a core hallmark of cancer that globally affects the entire tumor phenotype. Reversing tumor hypoxia might offer alternative therapeutic opportunities for current anticancer therapies. In this research, a photosynthetic leaf-inspired abiotic/biotic nano-thylakoid (PLANT) system was designed by fusing the thylakoid membrane with synthetic nanoparticles for efficient O₂ generation <i>in vivo</i>. Under 660 nm laser irradiation, the PLANT system exhibited intracellular O₂ generation and the anaerobic respiration of the multicellular tumor spheroid was suppressed by PLANT as well. <i>In vivo</i>, it was found that PLANT could not only normalize the entire metabolic network but also adjust the abnormal structure and function of the tumor vasculature. It was demonstrated that PLANT could significantly enhance the efficacy of phototherapy or antiangiogenesis therapy. This facile approach for normalizing the tumor microenvironment will find great potential in tumor therapy

Independently Tunable Multipurpose Absorber with Single Layer of Metal-Graphene Metamaterials

This paper reports an independently tunable graphene-based metamaterial absorber (GMA) designed by etching two cascaded resonators with dissimilar sizes in the unit cell. Two perfect absorption peaks were obtained at 6.94 and 10.68 &mu;m with simple single-layer metal-graphene metamaterials; the peaks show absorption values higher than 99%. The mechanism of absorption was analyzed theoretically. The independent tunability of the metamaterial absorber (MA) was realized by varying the Fermi level of graphene under a set of resonators. Furthermore, multi-band and wide-band absorption were observed by the proposed structure upon increasing the number of resonators and resizing them in the unit cell. The obtained results demonstrate the multipurpose performance of this type of absorber and indicate its potential application in diverse applications, such as solar energy harvesting and thermal absorbing