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In recent years, great efforts have been made to analyse biological systems to understand the long-run behaviours. As a well-established formalism for modelling real-life biological systems, Boolean networks (BNs) allow their representation and analysis using formal reasoning and tools. Most biological systems are robust - they can withstand the loss of links and cope with external environmental perturbations. Hence, the BNs used to model such systems are necessarily large and dense, and yet modular. However, existing analysis methods only work well on networks of moderate size. Thus, there is a great need for efficient methods that can handle large-scale BNs and for doing so it is inevitable to exploit both the structural and dynamic properties of the networks. In this paper, we propose a method towards the optimal decomposition of BNs to balance the relation between the structure and dynamics of a network. We show that our method can greatly improve the existing decomposition-based attractor detection by analysing a number of large real-life biological networks.

Although patients benefit from surgical transurethral resection of bladder cancers, some niduses are missed or incompletely resected, and small malignant lesions may recur. Intravesical chemotherapy and immunotherapy are universally accepted as adjuvant treatments after surgery to avoid recurrence and progression. However, these treatments still have limitations, including an insufficient retention period, inefficient permeability of chemotherapeutic agents, and dilution of the agents by urine. Nanostructure-based smart therapeutic platforms can be tailored to be responsive to internal or external stimuli to ameliorate this situation. This unparalleled capability empowers the precise aggregation of stimulus-responsive nanocarriers in the target regions, namely, the tumors, and subsequent release of the anticancer materials. This review summarizes the current nanostructure-based therapeutic platforms, especially stimulus-responsive nanocarriers, and highlights their benefits and limitations in bladder cancer therapy. Novel innovations in nanotechnology have undoubtedly arrived at a new height and have become useful for practical applications. Nanotechnology will positively promote the development of anticancer agents not only for bladder cancer but also for other solid tumors.

s To help optimize the spacecraft design and reduce the risk of spacecraft mission failure, a new approach to assess the survivability of spacecraft in orbit is presented here, including the following three steps: 1) Sensitivity Analysis of spacecraft. A new sensitivity analysis method, a ray method based on virtual outer wall, is presented here. Using rays to simulate the debris cloud can effectively address the component shadowing issues. 2) Component Vulnerability analysis of spacecraft. A function “Component functional reduction degree – Component physical damage degree” is provided here to clearly describe the component functional reduction. 3) System-level Survivability Assessment of spacecraft. A new method based on expert knowledge reasoning, instead of traditional artificial failure tree method, is presented here to greatly improve the efficiency and accuracy of calculation.

In this study, the lateral resistances of mass timber shear walls were investigated for seismic design. The lateral resistances were predicted by kinematic models with mechanical properties of connectors, and compared with experimental data. Four out of 7 shear wall specimens consisted of a single Ply-lam panel and withdrawal-type connectors. Three out of 7 shear wall specimens consisted of two panels made by dividing a single panel in half. The divided panels were connected by 2 or 4 connectors like a single panel before being divided. The applied vertical load was 0, 24, or 120 kN, and the number of connectors for connecting the Ply-lam wall-to-floor was 2 or 4. As a result, the tested data were 6.3 to 52.7% higher than the predicted value by kinematic models, and it means that the lateral resistance can be designed by the behavior of the connector, and the prediction will be safe. The effects of wall-to-wall connectors, wall-to-floor connectors and vertical loads on the shear wall were analyzed with the experimental data.

Translation of community-based functional training for older adults to reduce frailty is still lacking. We evaluated the effectiveness and implementation of a community-delivered group-based functional power training (FPT) program for frail older adults within their neighborhoods. A two-arm, multicenter assessor-blind stratified randomized controlled trial was conducted at four local senior activity centers in Singapore. Sixty-one community-dwelling older adults with low handgrip strength were randomized to intervention (IG) or control (CG) group. The IG underwent the FPT program (power and balance exercises using simple equipment) delivered by a community service provider. The 12-week program comprised 2 × 60 min sessions/week. CG continued usual activities at the centers. Functional performance, muscle strength, and frailty status were assessed at baseline and 3 months. Program implementation was evaluated using RE-AIM framework. The program was halted due to Coronavirus Disease 2019-related suspension of senior center activities. Results are reported from four centers, which completed the program. IG showed significantly greater improvement in the Short Physical Performance Battery test as compared to CG (p = 0.047). No effects were found for timed up and go test performance, muscle strength, and frailty status. The community program exhibited good reach, effectiveness, adoption, and implementation. Our study demonstrated that FPT was associated with greater improvement in physical function in pre-frail/frail participants as compared to exercise activities offered at local senior activity centers. It is a feasible intervention that can be successfully implemented for frail older adults in their neighborhoods. Trial registration ClinicalTrials.gov, NCT04438876. Registered 19 June 2020–retrospectively registered.

Ultrasonography (US) contrast imaging using US contrast agents has been widely applied for the diagnosis and differential diagnosis of tumors. Commercial US contrast agents have limited applications because of their large size and shorter imaging time. At the same time, the desired therapeutic purpose cannot be achieved by applying only conventional US contrast agents. The development of nanoscale US agents with US imaging and therapeutic functions has attracted increasing attention. In this study, we successfully developed DOX-loaded poly-1,6-hexanedithiol-sodium bicarbonate nanoparticles (DOX@HADT-SS-NaHCO3 NPs) with pH-responsive NaHCO3 and GSH-responsive disulfide linkages. DOX@HADT-SS-NaHCO3 NPs underwent acid-triggered decomposition of NaHCO3 to generate CO2 bubbles and a reduction of disulfide linkages to further promote the release of CO2 and DOX. The potential of DOX@HADT-SS-NaHCO3 NPs for contrast-enhanced US imaging and therapy of prostate cancer was thoroughly evaluated using in vitro agarose gel phantoms and a C4-2 tumor-bearing nude mice model. These polymeric NPs displayed significantly enhanced US contrast at acidic pH and antitumor efficacy. Therefore, the NaHCO3 and DOX-encapsulated polymeric NPs hold tremendous potential for effective US imaging and therapy of prostate cancer.

Objectives To 1) report prevalence of ‘osteosarcopenia’ (OS) and osteosarcopenic obesity (OSO) entities using evidence-based diagnostic techniques and definitions, 2) examine if OSO offers additional predictive value of functional decline over its components, and 3) identify associated factors in a multi-racial Southeast Asian population. Methods We performed a cross-sectional study of a representative sample of 542 community-dwelling adults (21–90 years old), and assessed anthropometry, cognition, functional performance, and self-report sociodemographic, health and lifestyle questionnaires. Low muscle mass, and the Asian Working Group for Sarcopenia (AWGS) 2019 criteria, were used to assess sarcopenia. Obesity was defined using percentage body fat and fat mass index. Osteopenia/osteoporosis was determined using lumbar spinal bone mineral density. Associated factors were examined using logistic regression, and OSO’s value investigated using linear regressions with functional performance. Results OS and OSO prevalence were 1.8% and 0% (21–59 years), 12.9% and 2.8% (≥ 60 years), 17.3% and 4.1% (≥ 65 years), and 25.5% and 7.0% (≥75 years), respectively. OSO entity as defined was not a significant predictor (P > 0.05) and did not improve explanations for functional decline over sarcopenia or sarcopenic obesity. Age, sex, race and body mass index (BMI) were associated with OS, while age, sex, race and alcoholism were associated with OSO. Conclusions Our results do not support OSO as a distinct entity in relation to functional decline. Aside from biological age, sex, and race, amenable lifestyle factors such as BMI and alcohol intake are important variables that can influence the co-existence of osteopenia/osteoporosis, sarcopenia and obesity.

Objective With the development of interventional therapy and precise radiotherapy, such as 3‐D conformal intensity‐modulated radiation therapy and stereotactic body radiotherapy (SBRT), transarterial chemoembolization (TACE) combined with radiotherapy has become an important method of comprehensive treatment for advanced liver cancer. However, few studies focus on the treatment of massive hepatocellular carcinoma (HCC) with SBRT. In this study, we investigated the effects and prognostic factors of whole‐body gamma‐knife SBRT combined with TACE in the treatment of massive HCC. Methods A retrospective analysis was carried out in 81 patients with massive, who received super gamma‐knife (type SGS‐I) SBRT after TACE treatment between 2 January 2011 and 30 June 2016. The curative effects were evaluated using the Modified Response Evaluation Criteria in Solid Tumors criteria. The alpha‐fetoprotein and alanine aminotransferase levels were measured before and after treatment. Patients were followed up for overall survival and 1‐, 3‐, and 5‐year survival rates. Adverse reactions were evaluated using the Radiation Therapy Oncology Group and the European Organization for Research and Treatment of Cancer criteria. Results A total of 81 patients were evaluated, including 29 patients with complete response, 48 patients with partial response, two patients with stable disease, and two patients with progressive disease; the total response rate was 95.06%. The 1‐year local control rate was 71.60%. The overall survival rates at 1, 3, and 5 years were 81.48%, 40.74%, and 16.67%, respectively. The median survival time was 15.0 months (95% CI 10.1–19.8 months). Progression‐free time was 11.0 months (95% CI 9.5–14.4 months). The alpha‐fetoprotein level after treatment was (85.53 ± 21.36) μg/L and was significantly lower than that before treatment (635.62 ± 125.83 μg/L; t = 8.189, P = 0.002). The alanine aminotransferase levels were 70.34 ± 16.60 and (54.95 ± 12.02) U/L before and after treatment, respectively, and were not significantly different (t = 1.348, P = 0.624). Multivariate analysis showed that a portal vein tumor thrombus (χ2 = 4.727, P = 0.016) and the Child–Pugh grade of liver function (χ2 = 4.893, P = 0.013) were adverse prognostic factors of overall survival. The 1‐year local control rates and the median survival times were 72.03% and 71.17%, and 16 and14 months, respectively, for the clinical target volumes ≥120 cm3 and

Background While there have been studies in Singapore on the prevalence and economic burden of osteoporotic hip fracture, there is a severe lack of reference data on bone mineral density and prevalence of osteoporosis. The purpose of this study is to establish the reference values for BMD and compare prevalence of osteoporotic conditions using other available reference values so as to better understand the status of bone health in Singaporean adults. Methods We carried out a population-based cross-sectional study using dual-energy x-ray absorptiometry (Hologic Discovery Wi) to measure the bone mineral density of Singaporean adults aged ≥21 years. A total of 542 participants were recruited from the large north-eastern residential town of Yishun. We computed T- scores (denoted by TSG) for each individual in the study. Similar diagnoses were also done based on T-scores provided by the densitometer (TDXA), NHANES database (TNHANES), and China (TCHN), and the differences in prevalence compared. We then compared the concordance between TSG and TDXA in the classification of osteoporosis. Osteoporosis was defined according to criteria by the World Health Organization (WHO). Results Peak lumbar spine BMD was 1.093 ± 0.168 g/cm2 in women, and 1.041 ± 0.098 g/cm2 for men. Peak whole-body BMD was 1.193 ± 0.93 g/cm2 in women at, and 1.224 ± 0.112 g/cm2 for men. Prevalence of osteoporosis based on lumbar spine was 9.3% in postmenopausal women, and 0.7% in men after 50 years of age. The percentage difference in prevalence range from 60.5–163.6%, when using reference values from TDXA, TNHANES, and TCHN. Comparing diagnosis using TDXA and TSG cut-off values, 28 versus 15 women were diagnosed as osteoporotic respectively. The kappa statistics was 0.81 for women and 0.85 for men. Conclusion: Our study shows that T-scores provided by DXA manufacturer over-diagnosed osteoporosis in Singaporeans, and the prevalence of osteoporotic conditions is not accurately represented. This over-diagnosis may result in unnecessary treatment in some individuals.

Temporal networks are networks that edges evolve over time, hence link prediction in temporal networks aims at inferring new edges based on a sequence of network snapshots. In this paper, we propose a graph wavelet neural network (TT-GWNN) framework using topological and temporal features for link prediction in temporal networks. To capture topological and temporal features, we develope a second-order weighted random walk sampling algorithm. It combines network snapshots with both first-order and second-order weights into one weighted graph. Moreover, it incorporates a damping factor to assign greater weights to more recent snapshots. Next, we adopt graph wavelet neural networks to embed the vertices and use gated recurrent units for predicting new links. Extensive experiments demonstrate that TT-GWNN can effectively predict links on temporal networks.

The space debris environment is one of the major threats against payloads. Space debris orbital distribution is of great importance for space debris environment modeling. Due to perturbation factors, the Right Ascension of Ascending Node (RAAN) of space objects changes consistently, causing regular rotation of the orbit plane around Earth’s axis. Based on the investigation of the RAAN perturbation rate of concerned objects, this paper proposes a RAAN discretization method in order to present the space debris longitude-dependent distribution. Combined with two line element (TLE) data provided by the US Space Surveillance Network, the estimated value from RAAN discretization method is compared with the real case. The results suggest that using only the initial orbital data at the beginning of the time interval of interest, the RAAN discretization method is able to provide reliable longitude distribution of concerned targets in the next following period. Furthermore, spacecraft cumulative flux against space debris is calculated in this paper. The results suggest that the relevance between spacecraft RAAN setup and flux output is much smaller for LEO targets than MEO targets, which corresponds with the theory analysis. Since the nonspherical perturbation is the major factor for RAAN variation, the RAAN perturbation rate has little connection with the size of orbital objects. In other words, the RAAN discretization method introduced in this paper also applies to space debris of different size range, proposing a possible suggestion for the improvement of space debris environment engineering models.

ObjectivesRegular moderate-to-vigorous intensity recreational physical activity (PA) improves physical and cognitive functions. However, the age-associated relationships between non-recreational PA and functional ability remain less explored. We examined the associations between housework and functional health among younger and older Singaporean community-dwelling adults.DesignCross-sectional study.Setting and participantsYounger (Outcome measuresPhysical function was assessed using Short Physical Performance Battery (SPPB), repeated-chair-sit-to-stand and gait speed. Cognitive and sensorimotor functions were assessed using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Physiological Profile Assessment (PPA), respectively.MethodsLight housework (LH) and heavy housework (HH), recreational, and occupational and transport-related PAs were assessed using PA questionnaires. Participants were dichotomised into low-volume and high-volume LH and HH groups. Results were adjusted for level of recreational and other non-recreational PAs.ResultsAmong older but not younger adults, RBANS scores were 8% and 5% higher in high HH and LH groups compared with low HH and LH groups, respectively (p=0.012 and p=0.016). Specifically, HH was associated with 14% higher attention score (p=0.014), and LH was associated with 12% and 8% higher immediate and delayed memory scores, respectively (pConclusionsAmong older adults, housework is associated with higher cognitive function, specifically in attention and memory. Associations of housework with physical function and sensorimotor performance were intensity dependent. Housework PA is positively associated with functional health among community-dwelling older adults, independent of recreation and other non-recreational PAs. Further longitudinal and intervention studies are needed to establish causality.

Many countries have undertaken market-oriented reforms of the power sector over the past four decades. However, the literature has not investigated whether the reforms have contributed to economic growth. This study assesses the potential macroeconomic impacts of following the market-based principle in operating and expanding the power system, an important ingredient of the power sector reform launched in China in 2015. The study uses a hybrid modeling approach by coupling a top-down computable general equilibrium model with a bottom-up energy sector TIMES model. The study finds that electricity prices in China would be 20 percent lower than the country is likely to experience in 2020 if the country follows the market principle to expand and operate the power system. The price reduction would spill over throughout the economy, resulting in an increase in the gross domestic product of more than one percent (or more than a billion US dollars) in 2020. It would also have positive impacts on most economic indicators, including household income and international trade. The findings quantitatively highlight the importance of implementing the 2015 power sector reforms in China and further expanding the initiatives in the future.

Platelets are essential components in the tumor microenvironment. For decades, clinical data have demonstrated that cancer patients have a high risk of thrombosis that is associated with adverse prognosis and decreased survival, indicating the involvement of platelets in cancer progression. Increasing evidence confirms that cancer cells are able to induce production and activation of platelets. Once activated, platelets serve as allies of cancer cells in tumor growth and metastasis. They can protect circulating tumor cells (CTCs) against the immune system and detachment-induced apoptosis while facilitating angiogenesis and tumor cell adhesion and invasion. Therefore, antiplatelet agents and platelet-based therapies should be developed for cancer treatment. Here, we discuss the mechanisms underlying the bidirectional cancer-platelet crosstalk and platelet-based therapeutic approaches.

Summary Direct cell reprogramming, also called transdifferentiation, has great potential for tissue engineering and regenerative medicine. Boolean networks, a popular modelling framework for gene regulatory networks, make it possible to identify intervention targets for direct cell reprogramming with computational methods. In this work, we present our software, CABEAN, for the control of asynchronous Boolean networks. CABEAN identifies efficacious nodes, whose perturbations can drive the dynamics of a network from a source attractor (the initial cell type) to a target attractor (the desired cell type). CABEAN provides several control methods integrating practical constraints. Thus, it has the ability to provide a rich set of control sets, such that biologists can select suitable ones for validation based on specific experimental settings. Availability and implementation The executable binary and the user guide of the software are publicly available at https://satoss.uni.lu/software/CABEAN/.

The neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), as markers of systematic inflammation response, have been reported to be indicators in metastatic castration-resistant prostate cancer (mCRPC), whereas their prognostic values remain conflict. This study was to assess the prognostic value of NLR and PLR in mCRPC patients and to assess the response of abiraterone or enzalutamide through using NLR and PLR. Databases searching was conducted in the PubMed, EMBASE, Google Scholar, and the Cochrane Library for relevant published literature up to October 2019. Data extraction and quality evaluation were performed on the eligible studies. STATA 14.0 software was used to pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) for overall survival (OS) and progression-free survival (PFS). A total of 3144 mCRPC patients were enrolled from 15 cohort studies in this meta-analysis. The pooled results demonstrated that elevated NLR had a significant association with inferior OS in mCRPC patients treated with abiraterone (HR = 1.63, 95% CI: 1.43–1.85, P

Objective Currently, concurrent chemoradiotherapy has become the standard treatment for locally advanced non‐small cell lung cancer, but it is often difficult for elderly patients to tolerate. In this study, we evaluated the curative effect, acute radiation reaction, and clinical application of stereotactic radiotherapy with whole‐body gamma‐knife combined with pemetrexed treatment in elderly patients with locally advanced lung adenocarcinoma. Methods A total of 37 elderly patients with lung adenocarcinoma from Hubei Provincial Armed Police Corps Hospital from 2 January 2013 to 30 December 2015, who were treated with stereotactic radiotherapy with super‐gamma‐knife, were included in the study. The radiotherapy plan was made according to the patient's physical condition, tumor location and size, and therapeutic purpose. A dose of 3.5–5 Gy was administered by 50–70% isodose curve, with a total dose range of peripheral irradiation 35–45 Gy. In the same period, pemetrexed was administered at 500 mg/m2, the first day of chemotherapy (d1), intravenous drip, with 21 days as one cycle, and the number of cycles was more than two. Results The median follow‐up duration was 18 months, and the 1‐, 2‐, and 3‐year follow‐up rates were 86.49% (32/37), 59.46% (33/37), and 21.62% (8/37), respectively. There were no missing cases. After 2–3 months of treatment, computed tomography showed that 13 patients (35.14%) had complete remission, 22 patients (59.46%) had partial remission, one patient (2.70%) achieved a stable status, and one patient (2.70%) still had progression, and the total response rate was 94.59%. The 1‐year local control rate was 67.57%. The 1‐, 2‐, and 3‐year overall survival rates were 86.49%, 45.45%, and 25.00%, respectively. The median overall survival time was 17.0 months (95% CI 14.5–21.3 months); the progression‐free survival time was 12.0 months (95% CI 11.6–12.8 months). Multivariate analysis showed that lymph node stage N ≥2 and radiotherapy biological effective dose 2 acute or late lung and esophagus toxicity was observed. Conclusions In elderly patients with lung adenocarcinoma, stereotactic body radiotherapy with super‐gamma‐knife combined with pemetrexed treatment is safe and definitive, with mild adverse effects.

Background Recently, sclerostin, a bone-derived protein, has been shown to play a key role in atherosclerosis progression. However, few studies have investigated the influence of sclerostin on cardiovascular disease prognosis. We investigated the relationship between serum sclerostin levels and adverse outcomes in elderly patients with stable coronary artery disease (SCAD) who were undergoing percutaneous coronary intervention (PCI). Methods We enrolled 310 elderly SCAD patients who underwent PCI in this study and followed them 3 years. According to the median serum sclerostin levels, subjects were stratified into a low sclerostin (low scl) group (n = 144) and a high sclerostin (high scl) group (n = 166). Time-to-event analyses were performed with the Kaplan–Meier method. Associations between sclerostin levels and main adverse cardiovascular and cerebrovascular events (MACCEs) and mortality were evaluated by Cox multivariate regression analysis. The prognostic power of predictive models was verified by the concordance index and receiver operating characteristic curve analysis. Results The high scl group had a significantly higher MACCE-free rate and better survival than the low scl group. Serum sclerostin was an independent predictor and could improve the prognostic power for adverse outcomes. In addition, serum sclerostin levels were significantly associated with bone turnover markers, a lower presence of multivessel disease and a lower CCS angina class. Conclusions Serum sclerostin is a prognostic parameter for predicting and intervening in the adverse outcomes of elderly SCAD patients undergoing PCI, which may be explained by its potential role in the bone–vascular axis.

Current cancer therapies have encountered adverse response due to poor therapeutic efficiency, severe side effects and acquired resistance to multiple drugs. Thus, there are urgent needs for finding new cancer-targeted pharmacological strategies. In this review, we summarized the current understanding with THZ1, a covalent inhibitor of cyclin-dependent kinase 7 (CDK7), which demonstrated promising anti-tumor activity against different cancer types. By introducing the anti-tumor behaviors and the potential targets for different cancers, this review aims to provide more effective approaches to CDK7 inhibitor-based therapeutic agents and deeper insight into the diverse tumor proliferation mechanisms. Keywords: THZ1, Cyclin-dependent kinase 7, Cancer therapy, Transcription, Super-enhancer

Objective: To develop and validate a non-invasive MRI-based radiomics signature for distinguishing between indolent and aggressive prostate cancer (PCa) prior to therapy. Methods: In all, 139 qualified and pathology-confirmed PCa patients were divided into a training set (n = 93) and a validation set (n = 46). A total of 1576 radiomics features were extracted from the T2WI (n = 788) and diffusion-weighted imaging (n = 788) for each patient. The Select K Best and the least absolute shrinkage and selection operator regression algorithm were used to construct a radiomics signature in the training set. The predictive performance of the radiomics signature was assessed in the training set and then validated in the validation set by receiver operating characteristic curve analysis. We computed the calibration curve and the decision curve to evaluate the calibration and clinical usefulness of the signature. Results: Nine radiomics features were identified to form the radiomics signature. The radiomics score (Rad-score) was significantly different between indolent and aggressive PCa (p < 0.001). The radiomics signature exhibited favorable discrimination between the indolent and aggressive PCa groups in the training set (AUC: 0.853, 95% CI: 0.766 to 0.941) and validation set (AUC: 0.901, 95% CI: 0.793 to 1.000). The decision curve analysis showed that a greater net benefit would be obtained when the threshold probability ranged from 20 to 90%. Conclusion: The multiparametric MRI-based radiomics signature can potentially serve as a non-invasive tool for distinguishing between indolent and aggressive PCa prior to therapy. Advances in knowledge: The multiparametric MRI-based radiomics signature has the potential to non-invasively distinguish between the indolent and aggressive PCa, which might aid clinicians in making personalized therapeutic decisions.

The Sinkhorn divergence has become a very popular metric to compare probability distributions in optimal transport. However, most works resort to the Sinkhorn divergence in Euclidean space, which greatly blocks their applications in complex data with nonlinear structure. It is therefore of theoretical demand to empower the Sinkhorn divergence with the capability of capturing nonlinear structures. We propose a theoretical and computational framework to bridge this gap. In this paper, we extend the Sinkhorn divergence in Euclidean space to the reproducing kernel Hilbert space, which we term "Hilbert Sinkhorn divergence" (HSD). In particular, we can use kernel matrices to derive a closed form expression of the HSD that is proved to be a tractable convex optimization problem. We also prove several attractive statistical properties of the proposed HSD, i.e., strong consistency, asymptotic behavior and sample complexity. Empirically, our method yields state-of-the-art performances on image classification and topological data analysis.

Election verifiability aims to ensure that the outcome produced by electronic voting systems correctly reflects the intentions of eligible voters, even in the presence of an adversary that may corrupt various parts of the voting infrastructure. Protecting such systems from manipulation is challenging because of their distributed nature involving voters, election authorities, voting servers and voting platforms. An adversary corrupting any of these can make changes that, individually, would go unnoticed, yet in the end will affect the outcome of the election. It is, therefore, important to rigorously evaluate whether the measures prescribed by election verifiability achieve their goals. We propose a formal framework that allows such an evaluation in a systematic and automated way. We demonstrate its application to the verification of various scenarios in Helios and Belenios, two prominent internet voting systems, for which we capture features and corruption models previously outside the scope of formal verification. Relying on the Tamarin protocol prover for automation, we derive new security proofs and attacks on deployed versions of these protocols, illustrating trade-offs between usability and security.

BackgroundProstate cancer (PCa) is the second most common cancer among males in the world and the majority of patients will eventually progress to the metastatic phase. How to choose an effective way for the treatment of metastatic PCa, especially in the later stage of the disease is still confusing. Herein we reported the case of a patient diagnosed with metastatic PCa and conducted a literature review on this issue.Case PresentationA 57-year-old man with metastatic PCa had been managed by Dr. J.P. since April 2012 when the patient was admitted to the Third Affiliated Hospital of Sun Yat-sen University by aggravating frequent urination and dysuria. The prostate-specific antigen (PSA) concentration was 140 ng/ml, and the diagnosis of PCa was confirmed by prostate biopsy, with Gleason score 4 + 5 = 9. Chest CT and bone scan indicated multiple metastases in the lungs and bones. Triptorelin, bicalutamide, zoledronic acid, and docetaxel were then administered, six cycles later, the metastatic tumors in the lungs disappeared and those in the bones lessened significantly, along with a remarkable reduction in PSA level (< 2 ng/ml). Intermittent androgen deprivation was subsequently conducted until August 2018, when the serum PSA level was found to be 250 ng/ml, again docetaxel 75 mg/m2 was administered immediately but the patient was intolerant this time. Instead, abiraterone was administered until March 2019 because of intolerable gastrointestinal side-effects and increasing PSA level. In October 2019, the patient came to our center, a modified approach of docetaxel (day 1 40 mg/m2 + day 8 35 mg/m2) was administered. Luckily, the PSA level decreased rapidly, the bone pain was greatly relieved, and no obvious side effects occurred. However, four cycles later, docetaxel failed to work anymore, the metastatic tumor in the liver progressed. We proposed several regimens as alternatives, but they were soon denied due to the high prices or unavailability or uncertain effect of the drugs. In addition, the patient’s condition deteriorated speedily and can no longer bear any aggressive treatment. Finally, the patient died of multiple organ failure in August 2020.ConclusionThe experiences of this case provide valuable evidence and reference for the treatment choices of metastatic PCa, in some circumstances modified and advanced regimens may produce unexpected effects.

Network embedding has shown its effectiveness in many tasks, such as link prediction, node classification, and community detection. Most attributed network embedding methods consider topological features and attribute features to obtain a node embedding but ignore its implicit information behavior features, including information inquiry, interaction, and sharing. These can potentially lead to ineffective performance for downstream applications. In this article, we propose a novel network embedding framework, named information behavior extraction (IBE), that incorporates nodes’ topological features, attribute features, and information behavior features within a joint embedding framework. To design IBE, we use an existing embedding method (e.g., SDNE, CANE, or CENE) to extract a node’s topological features and attribute features into a basic vector. Then, we propose a topic-sensitive network embedding (TNE) model to extract a node’s information behavior features and eventually generate information behavior feature vectors. In our TNE model, we design an importance score rating algorithm (ISR), which considers both effects of the topic-based community of a node and its interaction with adjacent nodes to capture the node’s information behavior features. Eventually, we concatenate a node’s information behavior feature vector with its basic vector to get its ultimate joint embedding vector. Extensive experiments demonstrate that our method achieves significant and consistent improvements compared to several state-of-the-art embedding methods on link prediction.

Background The Short Physical Performance Battery (SPPB) is an established test of physical performance. We provide reference values for SPPB and determine SPPB performance and cut-offs in assessing sarcopenia for Asian community-dwelling older adults. Methods Five hundred thirty-eight (57.8% women) community-dwelling adults aged 21–90 years were recruited. SPPB and its subtest scores and timings (8 ft. gait speed (GS), five-times repeated chair sit-to-stand (STS) and balance) were determined. Appendicular lean mass divided by height-squared, muscle strength (handgrip) and physical performance (6 m GS, STS and SPPB) were assessed to define sarcopenia for various Asian criteria. Area under the ROC curve (AUC) was used to assess performance of SPPB and subtests in discriminating sarcopenia in adults aged ≥60 years. Optimal SPPB and GS subtest cut-offs for each sarcopenia criterion were determined by maximizing sensitivity and specificity. Results The mean SPPB score was 11.6(SD 1.1) in men and 11.5(SD1.2) in women. Majority of participants(≥50%) aged 21–80 years achieved the maximum SPPB score. SPPB total and subtest scores generally decreased with age (all p Conclusions Population-specific normative SPPB values are important for use in diagnostic criteria and to interpret results of studies evaluating and establishing appropriate treatment goals. Performance on the SPPB should be reported in terms of the total sum score and registered time to complete the repeated-chair STS and 8-ft walk tests. The performance of GS subtest was comparable to SPPB and could be a useful, simple and accessible screening tool for discriminating severe sarcopenia in community-dwelling older adults.

Background Cancer cells prefer utilizing aerobic glycolysis in order to exacerbate tumor mass and maintain un-regulated proliferative rates. As a key glycolytic activator, phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3) has been implicated in multiple tumor type progression. However, the specific function and clinical significance of PFKFB3 in renal cell carcinoma (RCC) are yet not clarified. This investigation assessed PFKFB3 roles in RCC. Methods PFKFB3 expression levels were analyzed in clear cell renal cell carcinoma (ccRCC) tissues, together with its relationship with clinical characteristics of ccRCC. Real-time PCR and Western blot assays were employed for determining PFKFB3 expression in different RCC cell lines. Furthermore, we determined the glycolytic activity by glucose uptake, lactate secretion assay and ECAR analysis. CCK-8 assay, clone formation, flow cytometry and EdU assessments were performed for monitoring tumor proliferative capacity and cell-cycle distribution. Furthermore, a murine xenograft model was employed for investigating the effect of PFKFB3 on tumor growth in vivo. Results PFKFB3 was significantly up-regulated in RCC specimens and cell lines in comparison to normal control. Overexpression of PFKFB3 was directly correlated to later TNM stages, thus becoming a robust prognostic biomarker for ccRCC cases. Furthermore, PFKFB3 knockdown suppressed cell glycolysis, proliferative rate and cell-cycle G1/S conversion in RCC cells. Importantly, in vivo experiments confirmed that PFKFB3 knockdown delayed tumor growth derived from the ACHN cell line. Conclusions Such results suggest that PFKFB3 is a key molecular player in RCC progression via mediating glycolysis / proliferation and provides a potential therapeutic target against RCC.

Generative adversarial networks (GANs) have made unprecedented performance in image synthesis and play a key role in various downstream applications of computer vision. However, GAN models trained on sensitive data also pose a distinct threat to privacy. In this poster, we present a novel over-representation based membership inference attack. Unlike prior attacks against GANs which focus on the overall metrics, such as the attack accuracy, our attack aims to make inference from the high-precision perspective, which allows the adversary to concentrate on inferring a sample as a member confidently. Initial experimental results demonstrate that the adversary can achieve a high precision attack even if the overall attack accuracy is about 50% for a well-trained GAN model. Our work will raise awareness of the importance of precision when GAN owners evaluate the privacy risks of their models.

Background: Regular moderate-to-vigorous intensity recreational physical activity (PA) protects against ill health. The relationship between non-recreational PA with ageing health is less explored, especially in high income countries. We examined the associations between housework and functional health among younger and older Singaporean community-dwelling adults. Methods: Younger (

This paper proposes a framework for a layout evaluation of urban public sports facilities. First, the buffer analysis method is used to measure the service level of public sports facilities. The study findings indicate that the overall service level of public sports facilities presents the spatial characteristics of a central agglomeration, and the value of the service level diffuses outward from high to low. There is evident spatial heterogeneity in the layout of public sports facilities in Hangzhou. Second, the Gini coefficient, Lorenz curve, and location entropy are employed to measure the equity of the distribution among spatial units and the intradistrict disparity. The results show a mismatch between the spatial distribution of the facilities and the distribution of the permanent population. The patterns of distribution of the location entropy classes of Hangzhou can be divided into three types: balanced, alternating, and divergent districts. The method in this paper is effective in measuring spatial equity and visualizing it. it has a certain degree of systemicity, universality and operability. At the same time, this method can compare the diachronic characteristics of the same city and the synchronic characteristics of different cities, which has universal application value.

Background Sarcopenia and obesity are reportedly associated with risk of cognitive decline, and sarcopenic obesity (SO) heightens the risk, but the evidence is sparse and inconclusive. This study aimed to examine the association between SO and cognitive impairment. Methods A total of 542 community-dwelling adults aged between 21 and 90 years were recruited. All participants were assessed for body composition (dual X-ray absorptiometry), handgrip strength (HGS), gait speed (GS), and cognitive function (Repeatable Battery for the Assessment of Neuropsychological Status). Sarcopenia was defined by the presence of low appendicular lean mass index (ALMI) and low HGS or low GS according to the 2019 Asian Working Group for Sarcopenia criteria, and obesity was defined based on the upper two quintiles of fat mass index (FMI). Results Sarcopenia alone or in combination with obesity were not significantly associated with cognitive impairment after controlling for confounding variables. Obesity on its own was significantly associated with greater odds of impaired attention (OR: 2.05, 95%CI 1.12–3.82). Low ALMI was not associated, but low HGS, slow GS, and high FMI were individually associated with cognitive impairment: low HGS and immediate memory (OR: 1.91, 95% CI 1.04–3.49); low GS and immediate memory (OR: 2.17, 95% CI 1.26–3.72); high FMI and attention (OR: 2.06, 95% CI 1.22–3.51). Co-occurring high FMI with either low HGS or slow GS exacerbated the observed odds of global and domain-specific (attention, visuospatial) cognitive impairment. Conclusions Lean mass is not relevant, whereas muscle strength and physical performance or adiposity are relevant in defining sarcopenia or sarcopenic obesity in terms of their cognitive impacts.

Background The main aim of this study was to the determine relationship between Body Mass Index (BMI) and percentage body fat (BF%) in Singaporean adults, derive a prediction model to estimate BF%, and to report population BF%. The secondary aim was to determine the prevalence of overweight and obesity based on BF% threshold and the new risk categories for obesity in Singaporean population. Methods This was a population-based study of 542 community-dwelling Singaporeans (21–90 years old, 43.1% men). Anthropometry and body composition were assessed. Relationship between BMI and BF% were analysed using multiple regression models. Prevalence of overweight and obesity were estimated using WHO and Singapore Ministry of Health (MOH) Clinical Practice Guidelines for BMI classification, and BF% cut-off points of 25 and 35% for men and women respectively. Results We derived a prediction model to estimate BF% based on BMI, age and sex. The current cohort of Singaporeans when compared to Caucasians in the US and Europe as well as a Singapore cohort from 20 years age have higher BF% when matched for BMI, age, and sex. The overall population-adjusted prevalence of obesity according to WHO International classification (BMI ≥30 kg/m2) was 12.9% (14.9% men; 11.0% women); and 26.6% (30.7% men; 22.8% women) according to the MOH classification (BMI ≥27.5 kg/m2). However, using the BF% cut-off (> 25% for men and > 35% for women) resulted in very high prevalence of obesity of 82.0% (80.2% men; 83.8% women). Conclusion There is a large discrepancy between BF% and BMI measured obesity in Singaporean adults. The results confirmed that Singaporean adults have higher BF% at lower BMI compared to US and Europe white counterparts; and that BF% in our population has increased over two decades.

Over the last century, we observe a steady and exponential growth of scientific publications globally. The overwhelming amount of available literature makes a holistic analysis of the research within a field and between fields based on manual inspection impossible. Automatic techniques to support the process of literature review are required to find the epistemic and social patterns that are embedded in scientific publications. In computer sciences, new tools have been developed to deal with large volumes of data. In particular, deep learning techniques open the possibility of automated end-to-end models to project observations to a new, low-dimensional space where the most relevant information of each observation is highlighted. Using deep learning to build new representations of scientific publications is a growing but still emerging field of research. The aim of this paper is to discuss the potential and limits of deep learning for gathering insights about scientific research articles. We focus on document-level embeddings based on the semantic and relational aspects of articles, using Natural Language Processing (NLP) and Graph Neural Networks (GNNs). We explore the different outcomes generated by those techniques. Our results show that using NLP we can encode a semantic space of articles, while GNN we enable us to build a relational space where the social practices of a research community are also encoded.

BACKGROUND Skeleton is a preferred site for prostate cancer metastasis, and once metastases occur, the disease becomes incurable. Increasing evidence indicated the prognostic value of skeletal related parameters, but remains controversy. OBJECTIVE To perform a systematic review of the existing literature on assessing the prognostic value of alkaline phosphatase (ALP), bone-specific alkaline phosphatase (BSAP), urinary N-telopeptide (uNTx), bone scan index (BSI) and Brief Pain Inventory Short Form (BPI-SF) score in castration-resistant prostate cancer (CRPC) patients with skeleton metastasis. EVIDENCE ACQUISITION PubMed, Web of Science, Cochrane Library, Medline, OVID, and Embase between 2010 and 2019 were reviewed. Key terms included randomized trials, prostate cancer, alkaline phosphatase, bone-specific alkaline phosphatase, urinary N-telopeptide, bone scan index and Brief Pain Inventory Short Form. Data were collected, checked, and analyzed from December 2019 to March 2020. Hazard ratios (HRs), overall survival (OS) were extracted to estimate the relationship between the parameters above and OS in patients with metastatic prostate cancer (mPCa). EVIDENCE SYNTHESIS Totally 1055 studies were identified in initial screening, including 1032 from database searching and 23 from other sources. After removing the duplicates, 164 records were further excluded according to tittle and abstract. Remaining 36 potential articles were screened carefully and finally 15 eligible studies syntheses, which were published between 2010 and 2019, comprised data for a total of 11,378 patients, whose mean age ranged from 66 to 72 years old. The sample size ranged from 82 to 1901 patients. And the median follow-up time ranged from 24-55 months. Based on 15 randomized controlled trials published between 2010 and 2019, including 11378 patients. The higher ALP levels (HR=1.60, 95% CI: 1.38-1.87 P

Recent research regards the electroencephalogram (EEG) as a promising method to study real-time brain dynamic changes in patients with Parkinson's disease (PD), but a deeper understanding is needed to discern coincident pathophysiology, patterns of changes, and diagnosis. This review summarized recent research on EEG characterization related to the cognitive and motor functions in PD patients and discussed its potential to be used as diagnostic biomarkers. Thirty papers out of 220 published from 2010 to 2020 were reviewed. Movement abnormalities and cognitive decline are related to changes in EEG spectrum and event-related potentials (ERPs) during typical oddball paradigms and/or combined motor tasks. Abnormalities in β and δ frequency bands are, respectively the main manifestation of dyskinesia and cognitive decline in PD. The review showed that PD patients have noteworthy changes in specific EEG characterizations, however, the underlying mechanism of the interrelation between gait and cognitive is still unclear. Understanding the specific nature of the relationship is essential for development of novel invasive clinical diagnostic and therapeutic methods.

Objectives The “timed up and go” (TUG) test is a simple and widely used test of overall functional mobility. There is a paucity of TUG normative data among Asian individuals who differ in habitual gait speed and fall risk from Western population. The objectives of this study were to determine TUG reference values and optimum cutoffs predicting prevalent and incident disability for community-dwelling adults. Design One cross-sectional (Study 1–Yishun Study) and one longitudinal (Study 2–Singapore Longitudinal Aging Study) study in Singapore. Setting and Participants Study 1 comprised 538 nondisabled, community-dwelling adults aged between 21 and 90 years. Study 2 comprised 1356 community-dwelling older adults aged ≥55 years followed for 3 years. Methods Study 1 collected TUG reference values and assessed physiological fall risk (PFR) using the Physiological Profile Assessment (PPA). Study 2 assessed association of TUG with disability with the Barthel Index and the Lawton scale at baseline and follow-up. Results From Study 1, mean TUG time for individuals aged 60 to 74 years was 9.80 seconds, shorter than values reported for Westerners of 12.30 seconds. It was significantly associated with high PFR [odds ratio (OR) 1.14, 95% confidence interval (CI) 1.03–1.27], 74.0% agreement, Cohen's kappa = 0.314 (95% CI 0.238–0.390); area under the curve = 0.85 (95% CI 0.80–0.90). A TUG cutoff of 10.2 seconds discriminated high PFR from low PFR with 84.4% sensitivity and 72.6% specificity. In Study 2, the threshold for observing significantly increased risk of disability was ≥9.45 seconds for prevalent disability (OR 2.98, 95% CI 1.41–6.78), functional decline (OR 2.68, 95% CI 1.33–5.80), and incidental disability (OR 2.25, 95% CI 1.08–4.97). Conclusions and Implications TUG reference values and cutoff predicting disability for community-dwelling older adults in Singapore are consistent with Asian data and lower than for Western individuals. TUG could be used to guide development and evaluation of risk screening of adverse health outcomes across the life span in Singapore.

Purpose: Accumulative studies suggest the Glasgow prognostic score (GPS) and modified Glasgow prognostic score (mGPS) to be potential biomarkers; however, their prognostic value remains debatable. Our meta-analysis focused on assessing the accurate prognostic value of GPS and mGPS in patients with renal cell carcinoma (RCC) in addition to their effectiveness. Methods: To investigate the relationship between mGPS/GPS and prognostic value in patients with RCC, we performed a comprehensive retrieval of relevant articles from databases such as PubMed, Embase, Web of Science, and Medline up to February 1, 2020. STATA 15.0 software was used to obtain pooled hazard ratios (HRs) and their 95% confidence intervals for survival outcome, including overall survival (OS), recurrence-free survival (RFS), progression-free survival (PFS), and cancer-specific survival (CSS). A formal meta-analysis of these outcomes was performed. Results: In total, 2,691 patients with RCC were enrolled from 15 cohort studies. Higher GPS/mGPS (GPS/mGPS of 2) indicated poorer OS, CSS, PFS, and RFS in patients with RCC. Similarly, medium GPS/mGPS (GPS/mGPS of 1) also had a significant association with poorer OS, CSS, PFS, and RFS but superior than higher GPS/mGPS in these patients. Conclusion: GPS and mGPS are effective biomarkers for predicting prognosis in patients with RCC, and higher GPS and mGPS are closely related to inferior survival outcomes. More randomized controlled trials are needed to investigate the promising value of GPS/mGPS in the future.

Background. Previous studies showed that recanalization and angiogenesis within the infarct region are of vital importance to the survival of myocardial cells during the treatment of acute myocardial infarction (AMI).Methods. In this study, EdU cell proliferation assay, Transwell assay, scratch wound assay, and tube formation assay were used. Twelve bioinformatics analysis packages were used to predict the target genes of miR-101. Target genes were verified by luciferase reporter generation and assay, fluorescent quantitative PCR, and western blotting. Animal model and treatments were detected by M-mode echocardiography and immunofluorescent staining of CD31, Ki67, andα-SMA.Results. AgomiR-101 significantly enhanced HUVEC proliferation, migration, and tube formation. A double-luciferase reporter assay revealed that the hsa-miR-101 mimic attenuated the activity of the EIF4E3′-UTR-wt type plasmid by 36%. The expression levels of HIF-1αand VEGF-A in the scrambled RNA group were significantly lower than those in the EIF4E3 siRNA and agomiR-101 groups. The left ventricular ejection fraction of the AMI+Adv-miR-101 group was significantly higher than that of the AMI+Adv-null and Sham+Adv-null groups. The proliferation of vessel cells in the peripheral infarcted myocardium was higher in the AMI+Adv-miR-101 group than that in the AMI+Adv-null and Sham+Adv-null groups.Conclusion. MiR-101 can promote angiogenesis in the region surrounding the myocardial infarction.

The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information. Thus, discussions on OSNs may become a reflection of reality. This paper aims to figure out how Twitter users in the Greater Region (GR) and related countries react differently over time through conducting a data-driven exploratory study of COVID-19 information using machine learning and representation learning methods. We find that tweet volume and COVID-19 cases in GR and related countries are correlated, but this correlation only exists in a particular period of the pandemic. Moreover, we plot the changing of topics in each country and region from 22 January 2020 to 5 June 2020, figuring out the main differences between GR and related countries.

BackgroundRisk and crisis communication plays an essential role in public health emergency responses. The COVID-19 pandemic has triggered spontaneous and intensive media attention, which has affected people’s adoption of personal preventive measures and their mental health.ObjectiveThe aim of this study was to investigate the associations between exposure to COVID-19–specific information and mental health (depression and sleep quality) and self-reported compliance with personal preventive measures (face mask wearing and hand sanitizing). We also tested whether these associations were moderated by thoughtful consideration of the veracity of the information to which people were exposed.MethodsA cross-sectional, closed web-based survey was conducted among a sample of 3035 factory workers at the beginning of work resumption following the COVID-19 outbreak in Shenzhen, China. A stratified two-stage cluster sampling design was used for recruitment. Multivariate linear and logistic regression models were used for the analyses.ResultsThe prevalence of probable moderate-to-severe depression was 170/3035 (5.6%), while that of good or excellent sleep quality was 2110/3035 (69.5%). The prevalence of self-reported consistent face mask wearing in public places was 2903/3035 (95.7%), while that of sanitizing hands every time after returning from public spaces or touching public installations was 2151/3035 (70.9%). Of the 3035 respondents, 1013 to 1638 (33.3% to 54.0%) reported >1 hour of daily exposure to COVID-19–specific information through web-based media and television. After controlling for significant background variables, higher information exposure via television and via newspapers and magazines was associated with better sleep quality and higher compliance with hand sanitizing. Higher exposure via unofficial web-based media was associated with higher compliance with hand sanitizing but was also associated with higher depressive symptoms. In contrast, higher exposure through face-to-face communication was associated with higher depressive symptoms, worse sleep quality, and lower compliance with hand sanitizing. Exposure to information about positive outcomes for patients with COVID-19, development of vaccines and effective treatments, and heroic stories about frontline health care workers were associated with both better mental health and higher compliance with preventive measures. Higher overall information exposure was associated with higher depressive symptoms among participants who were less likely to carefully consider the veracity of the information to which they were exposed; it was also associated with better sleep quality among people who reported more thoughtful consideration of information veracity.ConclusionsThis study provides empirical evidence of how the amount, sources, and contents of information to which people were exposed influenced their mental health and compliance with personal preventive measures at the initial phase of work resumption in China. Thoughtful consideration of information quality was found to play an important moderating role. Our findings may inform strategic risk communication by government and public health authorities during the COVID-19 pandemic.

Background Frailty is a common geriatric syndrome, characterized by reduced physiologic reserve and increased vulnerability to stressors, due to cumulative decline in multiple physiological systems. We studied the feasibility of a community-delivered Baduanjin (BDJ) training program among pre-frail/frail community-dwelling older people. We examined (1) safety (adverse events) and physical and psychological effects; and (2) feasibility of recruitment, retention, adherence; recruitment efforts, and any program challenges, so as to inform future studies. Methods Our study was a single arm pre-post study in a community setting. Sixteen-week group BDJ training (2×/week in the first 4 weeks and 3×/week thereafter) was co-designed and implemented by community-based providers in Singapore. Recruitment, attendance, and adverse events were recorded throughout the training. A participants’ survey was also administered after the training program. Effects of the intervention on physical and functional outcomes (hand grip strength, knee extension strength, Time Up and Go (TUG), Physiological Profile Assessment (PPA), 30-s Sit-to-Stand test, 6-m fast gait speed test), frailty outcomes (frailty score and status), and other outcomes (Maastricht Questionnaire (MQ), Fall Efficacy Scale (FES), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), and EQ-5D-5L) were examined before and after the program. Results Of 31 older adults screened to be frail, 15 met inclusion criteria and 3 refused participation, resulting in 12 older adults (9 women) enrolled into the program. During the program, one participant was hospitalized (unrelated to BDJ training) and the other 11 (aged 77 ± 6 years; 2 frail, 9 prefrail at baseline) completed the program with average overall attendance of 89%. Most (89%) of the 44 training sessions had attendance > 80%. The program received positive feedback with no training-related adverse events. Participants either reversed (n = 2) or maintained (n = 9) their frailty statuses. There post-training outcomes in hand grip strength, knee extension strength, TUG, MQ, FES, MoCA, GDS, and EQ-5D-5L index score appeared to be better. The reduction of frailty and PPA fall risk scores was of moderate-to-large effect size. Conclusions Community-delivered BDJ training program was safe and feasible for prefrail/frail older adults with the potential to improve physical and cognitive function, reduce fall risk, improve psychological well-being, and reverse frailty status.

©American Psychological Association, 2020. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at: https://doi.apa.org/doi/10.1037/bul0000220 To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from 2 separate large samples (total N 15,000) were then randomly assigned to complete 1 version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: Materials from different teams rendered statistically significant effects in opposite directions for 4 of 5 hypotheses, with the narrowest range in estimates being d = 0.37 to 0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for 2 hypotheses and a lack of support for 3 hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, whereas considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.

A multi-graph is modeled as a bag of graphs, whose mutual relationships can be used to enhance the accuracy of multi-graph classification. However, to the best of our knowledge, research on utilizing those mutual relationships has not been reported. In this paper, we propose a novel super-graph model $SG=(MG,AG)$ , where MG denotes a multi-graph and AG represents a graph (named abstract-graph), that describes the mutual relationships among the graphs contained in MG. The super-graph classification problem is challenging to solve because of the very complex structure of the super-graph model. Furthermore, it is hard to directly select distinguished subgraphs, i.e., subgraph features, from super-graphs. A subgraph g of graph G is a graph that is isomorphic with one of the substructures of G. Moreover, the practical applications require the super-graph classification algorithm to have high precision. In this paper, we propose a concept and algorithm for selecting composite subgraph features, based on which a framework is proposed to solve the super-graph classification problem. Subgraph features denote subgraphs that can be used to distinguish super-graphs with different class labels. We first design a two-step approach to select k composite subgraph features from the subgraphs of super-graphs’ abstract-graphs and multi-graphs. Then, based on composite features and the subgraph feature representation of a super-graph, each super-graph SG is transformed into a 0-1 vector with k dimensions. If there exists a substructure in SG that is isomorphic with its i th composite feature, the i th component of the target vector is set to 1 (1 ≤ i ≤ k). Otherwise, it is set to 0. Based on the derived k-dimensional vectors, one of the existing classification algorithms is used to construct a prediction model to predict the class labels of the unseen super-graphs, such as naive Bayes or support vector machine (SVM). Specifically, we adapt the extreme learning machine (ELM) algorithm to further improve the accuracy of super-graph classification. In this paper, we propose a super-graph model and study the problem of super-graph classification. We first derive the concept of composite subgraph features that are selected by our proposed two-step method. Based on the mined composite subgraph features, we propose a super-graph classification framework (SGC) to solve the super-graph classification problem. Moreover, ELM can be used to further improve the classification accuracy. Extensive experiments on real-world image datasets show that our algorithm based on ELM is more accurate than the baseline algorithms.

With the popularity of mobile devices and various sensors, the local geographical activities of human beings can be easily accessed than ever. Yet due to the privacy concern, it is difficult to acquire the social connections among people possessed by services providers, which can benefit applications such as identifying terrorists and recommender systems. In this paper, we propose the location-aware acquaintance inference (LAI) problem, which aims at finding the acquaintances for any given query individual based on solely people’s local geographical activities, such as geo-tagged posts in Instagram and meeting events in Meetup, within a targeted geo-spatial area. We propose to leverage the concept of active learning to tackle the LAI problem. We develop a novel semi-supervised model, active learning-enhanced random walk (ARW), which imposes the idea of active learning into the technique of random walk with restart (RWR) in an activity graph. Specifically, we devise a series of candidate selection strategies to select unlabeled individuals for labeling and perform the different graph refinement mechanisms that reflect the labeling feedback to guide the RWR random surfer. Experiments conducted on Instagram and Meetup datasets exhibit the promising performance, compared with a set of state-of-the-art methods. With a series of empirical settings, ARW is demonstrated to derive satisfying results of acquaintance inference in different real scenarios.

Background Global disparities in prostate cancer (PCa) incidence highlight the urgent need to identify genomic abnormalities in prostate tumors in different ethnic populations including Asian men. Objective To systematically explore the genomic complexity and define disease-driven genetic alterations in PCa. Design, setting, and participants The study sequenced whole-genome and transcriptome of tumor-benign paired tissues from 65 treatment-naive Chinese PCa patients. Subsequent targeted deep sequencing of 293 PCa-relevant genes was performed in another cohort of 145 prostate tumors. Outcome measurements and statistical analysis The genomic alteration landscape in PCa was analyzed using an integrated computational pipeline. Relationships with PCa progression and survival were analyzed using nonparametric test, log-rank, and multivariable Cox regression analyses. Results and limitations We demonstrated an association of high frequency of CHD1 deletion with a low rate of TMPRSS2-ERG fusion and relatively high percentage of mutations in androgen receptor upstream activator genes in Chinese patients. We identified five putative clustered deleted tumor suppressor genes and provided experimental and clinical evidence that PCDH9, deleted/loss in approximately 23% of tumors, functions as a novel tumor suppressor gene with prognostic potential in PCa. Furthermore, axon guidance pathway genes were frequently deregulated, including gain/amplification of PLXNA1 gene in approximately 17% of tumors. Functional and clinical data analyses showed that increased expression of PLXNA1 promoted prostate tumor growth and independently predicted prostate tumor biochemical recurrence, metastasis, and poor survival in multi-institutional cohorts of patients with PCa. A limitation of this study is that other genetic alterations were not experimentally investigated. Conclusions There are shared and salient genetic characteristics of PCa in Chinese and Caucasian men. Novel genetic alterations in PCDH9 and PLXNA1 were associated with disease progression. Patient summary We reported the first large-scale and comprehensive genomic data of prostate cancer from Asian population. Identification of these genetic alterations may help advance prostate cancer diagnosis, prognosis, and treatment.

A multi-graph is represented by a bag of graphs. Semi-supervised multi-graph classification is a partly supervised learning problem, which has a wide range of applications, such as bio-pharmaceutical activity tests, scientific publication categorization and online product recommendation. However, to the best of our knowledge, few research works have be reported. In this paper, we propose a semi-supervised multi-graph classification algorithm to handle the semi-supervised multi-graph classification problem. Our algorithm consists of three main steps, including the optimal subgraph feature selection, the subgraph feature representation of multi-graph and the semi-supervised classifier building. We first propose an evaluation criterion of the optimal subgraph features, which not only considers unlabeled multi-graphs but also considers the constraints between the multi-graph level and the graph level. Then, the optimal subgraph feature selection problem is equivalently converted into the problem of mining m most informative subgraph features. Based on those derived m subgraph features, every multi-graph is represented by an m -dimensional vector, where the i th dimension equals to 1 if at least one graph involved in the multi-graph contains the i th subgraph feature. At last, based on these vectors, semi-supervised extreme learning machine(semi-supervised ELM) is adopted to build the prediction model for predicting the labels of unseen multi-graphs. Extensive experiments on real-world and synthetic graph datasets show that the proposed algorithm is effective and efficient.

Background Primary malignant lymphoma of the prostate (PMLP) is prone to occur in the elderly, and it has no significant correlation with lactate dehydrogenase (LDH) and prostate specific antigen (PSA). Clinical symptoms and imaging data of PMLP remain unspecific, and its prognosis is poor. A previous result showed that collapsin response mediator protein 4 (CRMP4) promotor methylation can be used as a predictor for lymph node metastases in prostate biopsies. However, the relationship between CRMP4 promotor methylation and PMLP has not been studied. Methods We investigated the clinicopathological features of PMLP and the significance of CRMP4 methylation in PMLP. The clinical data and diagnosis information of 10 patients with PMLP were retrospectively analyzed. The CRMP4 promotor methylation level in paraffin-embedded tissues of the 10 patients with PMLP were determined and then compared to limited prostate cancer (LPCa) and its negative lymph node tissue [LPCa-LN (−) (10 cases)] and also to metastatic prostate adenocarcinoma (mPCa) and its positive lymph node tissue [mPCa-LN (+) (10 cases)]. Methylation of the CRMP4 promotor in each group was analyzed statistically. A receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of CRMP4 methylation in PMLP. Results The average methylation value of CRMP4 in 10 PMLP patients, 20 cases of prostate adenocarcinoma tissue, 10 cases LPCa-LN (−) and 10 cases mPCa-LN (+) were 42.3, 30.6, 6.7 and 20.3%, respectively. A Kruskal–Wallis test showed that the difference of CRMP4 methylation was significant (X2 = 38.0, P 40.9% could diagnose PMLP. This method had 90% sensitivity and 95% specificity under conditions of CRMP4 methylation > 40.9%. The area under the curve (AUC) was 0.957. Conclusions Methylation of the CRMP4 gene was significantly increased in PMLP, and it is expected to become a new predictor for PMLP.

Bi doped n-type SnSe thin films were prepared by chemical vapor deposition (CVD) and their structure and thermoelectric properties were studied. The x-ray diffraction patterns, x-ray photoelectron spectroscopy, and microscopic images show that the prepared SnSe thin films were composed of pure SnSe crystals. The Seebeck coefficients of the Bi-doped SnSe were greatly improved compared to that of undoped SnSe thin films. Specifically, Sn0.99Bi0.01Se thin film exhibited a Seebeck coefficient of –905.8 μV⋅K−1 at 600 K, much higher than 285.5 μV⋅K−1 of undoped SnSe thin film. Further first-principles calculations reveal that the enhancement of the thermoelectric properties can be explained mainly by the Fermi level lifting and the carrier pockets increasing near the Fermi level due to Bi doping in the SnSe samples. Our results suggest the potentials of the Bi-doped SnSe thin films in thermoelectric applications.