CSD: a multi-user similarity metric for community recommendation in online social networks

Communities are basic components in networks. As a promising social application, community recommendation selects a few items (e.g., movies and books) to recommend to a group of users. It usually achieves higher recommendation precision if the users share more interests; whereas, in plenty of communities (e.g., families, work groups), the users often share few. With billions of communities in online social networks, quickly selecting the communities where the members are similar in interests is a prerequisite for community recommendation. To this end, we propose an easy-to-compute metric, Community Similarity Degree (CSD), to estimate the degree of interest similarity among multiple users in a community. Based on 3460 emulated Facebook communities, we conduct extensive empirical studies to reveal the characteristics of CSD and validate the effectiveness of CSD. In particular, we demonstrate that selecting communities with larger CSD can achieve higher recommendation precision. In addition, we verify the computation efficiency of CSD: it costs less than 1 hour to calculate CSD for over 1 million of communities. Finally, we draw insights about feasible extensions to the definition of CSD, and point out the practical uses of CSD in a variety of applications other than community recommendation.This work has been funded by China Scholarship Council. It has also been partially funded by the Ministerio de Economia y Competitividad of SPAIN through the project BigDatAAM (FIS2013-47532-C3-3-P), H2020-DS-2014-1 through the TYPES Project under Grant Agreement number 653449, State Key Laboratory of Geo-Information Engineering (No. SKLGIE2014-M-2-2). and the Program of National Natural Science Foundation of China (No. 41404025)

Semi-supervised Optimal Transport with Self-paced Ensemble for Cross-hospital Sepsis Early Detection

The utilization of computer technology to solve problems in medical scenarios has attracted considerable attention in recent years, which still has great potential and space for exploration. Among them, machine learning has been widely used in the prediction, diagnosis and even treatment of Sepsis. However, state-of-the-art methods require large amounts of labeled medical data for supervised learning. In real-world applications, the lack of labeled data will cause enormous obstacles if one hospital wants to deploy a new Sepsis detection system. Different from the supervised learning setting, we need to use known information (e.g., from another hospital with rich labeled data) to help build a model with acceptable performance, i.e., transfer learning. In this paper, we propose a semi-supervised optimal transport with self-paced ensemble framework for Sepsis early detection, called SPSSOT, to transfer knowledge from the other that has rich labeled data. In SPSSOT, we first extract the same clinical indicators from the source domain (e.g., hospital with rich labeled data) and the target domain (e.g., hospital with little labeled data), then we combine the semi-supervised domain adaptation based on optimal transport theory with self-paced under-sampling to avoid a negative transfer possibly caused by covariate shift and class imbalance. On the whole, SPSSOT is an end-to-end transfer learning method for Sepsis early detection which can automatically select suitable samples from two domains respectively according to the number of iterations and align feature space of two domains. Extensive experiments on two open clinical datasets demonstrate that comparing with other methods, our proposed SPSSOT, can significantly improve the AUC values with only 1% labeled data in the target domain in two transfer learning scenarios, MIMIC $rightarrow$ Challenge and Challenge $rightarrow$ MIMIC.Comment: 14 pages, 9 figure

The signature of pyroptosis-related gene prognostic and immune microenvironment in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) has a low incidence but a poor prognosis. And ACC has complex clinical manifestations and limited treatment. Pyroptosis has a dual character and has both positive and negative effects on cancer. However, the role of pyroptosis-related genes (PRGs) in ACC and the impact on ACC progression remains unelucidated. This study performed systematic bioinformatics analysis and basic experimental validation to enable the establishment of prognostic models and demonstrate levels of immune infiltration. Pearson’s correlation analysis was used to assess the association of PRGs with tumor immune infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoints. There 4 PRGs were upregulated, and 25 PRGs were downregulated in ACC. At the same time, we analyzed and reviewed the genetic mutation variation landscape of PRGs. Functional enrichment analysis was also performed to clarify the function of PRGs. Pyroptosis, the inflammatory response, the Toll-like receptor signaling pathway, and the NOD-like receptor signaling pathway are the functions and pathways mainly involved and exerted effects by these 33 PRGs. The results of the prognosis analysis revealed high expression of CASP3, CASP9, GSDMB, GSDMD, NLRC4, PRKACA, and SCAF11 caused a poor survival rate for ACC patients. The above seven PRGs were screened by the optimal λ value of LASSO Cox analysis, and the five selected genes (CASP3, CASP9, GSDMB, GSDMD, NLRC4) were involved in constructing a prognostic PRGs model which enables the overall survival in ACC patients can be predicted with moderate to high accuracy. Prognostic PRGs, especially CASP9, which is the independent factor of ACC prognosis, may be closely correlated with immune-cell infiltration, tumor mutation burden, microsatellite instability, and immune checkpoints. Quantitative Real-Time PCR (qRT-PCR), Western blot and immunohistochemical were performed to validate the mRNA expression levels of CASP9 in adjacent normal tissues and ACC tissues. According to the result of immune checkpoints analysis, NLRC4 and GSDMB may be identified as potential therapeutic targets. In conclusion, we established a prognostic model of PRG characteristics in ACC and analyzed the relationship between PRGs and immune infiltration. Through our study, it may be helpful to find the mechanism of pyroptosis in ACC

European Society of Endodontology position statement: Management of deep caries and the exposed pulp

This position statement on the management of deep caries and the exposed pulp represents the consensus of an expert committee, convened by the European Society of Endodontology (ESE). Preserving the pulp in a healthy state with sustained vitality, preventing apical periodontitis and developing minimally invasive biologically based therapies are key themes within contemporary clinical endodontics. The aim of this statement was to summarize current best evidence on the diagnosis and classification of deep caries and caries‐induced pulpal disease, as well as indicating appropriate clinical management strategies for avoiding and treating pulp exposure in permanent teeth with deep or extremely deep caries. In presenting these findings, areas of controversy, low‐quality evidence and uncertainties are highlighted, prior to recommendations for each area of interest. A recently published review article provides more detailed information and was the basis for this position statement (Bjørndal et al. 2019, International Endodontic Journal, doi:10.1111/iej.13128). The intention of this position statement is to provide the practitioner with relevant clinical guidance in this rapidly developing area. An update will be provided within 5 years as further evidence emerges

GP-selector:a generic participant selection framework for mobile crowdsourcing systems

Participant selection is a common and crucial function for mobile crowdsourcing (MCS) systems or platforms. This paper introduces a generic framework, named GP-Selector, to handle the participant selection from MCS task creation time to runtime. Compared to existing approaches, ours has the following two unique features. 1) In the task creation time, it assists task creators with diverse levels of programming skills to define basic requirements of participant selection. 2) In the runtime, it adopts a two-phase selection process to select participants who not only meet the basic requirements but also are willing to accept the task. Specifically, we utilize the state-of-the-art techniques including ontology modeling, end-user programming and multi-classifier fusion to implement GP-Selector. We evaluate GP-Selector extensively in three aspects: the end-user task creation, the expressiveness of the core ontology model, and the willingness-based selection algorithm. The evaluation results demonstrate the usability and effectiveness

Real-time and generic queue time estimation based on mobile crowdsensing

People often have to queue for a busy service in many places around a city, and knowing the queue time can be helpful for making better activity plans to avoid long queues. Traditional solutions to the queue time monitoring are based on pre-deployed infrastructures, such as cameras and infrared sensors, which are costly and fail to deliver the queue time information to scattered citizens. This paper presents CrowdQTE, a mobile crowdsensing system, which utilizes the sensor-enhanced mobile devices and crowd human intelligence to monitor and provide real-time queue time information for various queuing scenarios. When people are waiting in a line, we utilize the accelerometer sensor data and ambient contexts to automatically detect the queueing behavior and calculate the queue time. When people are not waiting in a line, it estimates the queue time based on the information reported manually by participants. We evaluate the performance of the system with a two-week and 12-person deployment using commercially-available smartphones. The results demonstrate that CrowdQTE is effective in estimating queuing status

Fine-Grained Multitask Allocation for Participatory Sensing With a Shared Budget

For participatory sensing, task allocation is a crucial research problem that embodies a tradeoff between sensing quality and cost. An organizer usually publishes and manages multiple tasks utilizing one shared budget. Allocating multiple tasks to participants, with the objective of maximizing the overall data quality under the shared budget constraint, is an emerging and important research problem. We propose a fine-grained multitask allocation framework (MTPS), which assigns a subset of tasks to each participant in each cycle. Specifically, considering the user burden of switching among varying sensing tasks, MTPS operates on an attention-compensated incentive model where, in addition to the incentive paid for each specific sensing task, an extra compensation is paid to each participant if s/he is assigned with more than one task type. Additionally, based on the prediction of the participants' mobility pattern, MTPS adopts an iterative greedy process to achieve a near-optimal allocation solution. Extensive evaluation based on real-world mobility data shows that our approach outperforms the baseline methods, and theoretical analysis proves that it has a good approximation bound

Exosome Released From Schwann Cells May Be Involved in Microenergy Acoustic Pulse–Associated Cavernous Nerve Regeneration

BackgroundNeurogenic erectile dysfunction (ED) is often refractory to treatment because of insufficient functional nerve recovery after injury or insult. Noninvasive mechano-biological intervention, such as microenergy acoustic pulse (MAP), low-intensity pulsed ultrasound, and low-intensity extracorporeal shockwave treatment, is an optimal approach to stimulate nerve regeneration.AimTo establish a new model in vitro to simulate nerve injury in neurogenic ED and to explore the mechanisms of MAP in vitro.MethodsSprague-Dawley rats were used to isolate Schwann cells (SCs), major pelvic ganglion (MPG), and cavernous nerve with MPG (CN/MPG). SCs were then treated with MAP (0.033 mJ/mm2, 1 Hz, 100 pulses), and SC exosomes were isolated. The MPG and CN/MPG were treated with MAP (0.033 mJ/mm2, 1 Hz) at different dosages (25, 50, 100, 200, or 300 pulses) or exosomes derived from MAP-treated SCs in vitro.OutcomesNeurite growth from the MPG fragments and CN was photographed and measured. Expression of neurotropic factors (brain-derived neurotrophic factor, nerve growth factor, and neurotrophin-3) was checked.ResultsNeurite outgrowth from MPG and CN/MPG was enhanced by MAP in a dosage response manner, peaking at 100 pulses. MAP promoted SC proliferation, neurotropic factor (brain-derived neurotrophic factor, nerve growth factor, and neurotrophin-3) expression, and exosome secretion. SC-derived exosomes significantly enhanced neurite outgrowth from MPG in vitro.Clinical implicationsMAP may have utility in the treatment of neurogenic ED by SC-derived exosomes.Strength & limitationsWe confirmed that MAP enhances penile nerve regeneration through exsomes. Limitations of this study include that our study did not explore the exact mechanisms of how MAP increases SC exosome secretion nor whether MAP modulates the content of exosomes.ConclusionThis study revealed that neurite outgrowth from MPG was enhanced by MAP and by SC-derived exosomes which were isolated after MAP treatment. Our findings indicate that one mechanism by which MAP induces nerve regeneration is by stimulation of SCs to secrete exosomes. Peng D, Reed-Maldonado AB, Zhou F, et al. Exosome Released From Schwann Cells May Be Involved in Microenergy Acoustic Pulse-Associated Cavernous Nerve Regeneration. J Sex Med 2020;17:1618-1628

Peripheral blood mitochondrial DNA copy number is associated with prostate cancer risk and tumor burden.

Alterations of mitochondrial DNA (mtDNA) have been associated with the risk of a number of human cancers; however, the relationship between mtDNA copy number in peripheral blood leukocytes (PBLs) and the risk of prostate cancer (PCa) has not been investigated. In a case-control study of 196 PCa patients and 196 age-paired healthy controls in a Chinese Han population, the association between mtDNA copy number in PBLs and PCa risk was evaluated. The relative mtDNA copy number was measured using quantitative real-time PCR; samples from three cases and two controls could not be assayed, leaving 193 cases and 194 controls for analysis. PCa patients had significantly higher mtDNA copy numbers than controls (medians 0.91 and 0.82, respectively; P<0.001). Dichotomized at the median value of mtDNA copy number in the controls, high mtDNA copy number was significantly associated with an increased risk of PCa (adjusted odds ratio= 1.85, 95% confidence interval: 1.21-2.83). A significant dose-response relationship was observed between mtDNA copy number and risk of PCa in quartile analysis (Ptrend = 0.011). Clinicopathological analysis showed that high mtDNA copy numbers in PCa patients were significantly associated with high Gleason score and advanced tumor stage, but not serum prostate-specific antigen level (P = 0.002, 0.012 and 0.544, respectively). These findings of the present study indicate that increased mtDNA copy number in PBLs is significantly associated with an increased risk of PCa and may be a reflection of tumor burden

Data from: Peripheral blood mitochondrial DNA copy number is associated with prostate cancer risk and tumor burden

Alterations of mitochondrial DNA (mtDNA) have been associated with the risk of a number of human cancers; however, the relationship between mtDNA copy number in peripheral blood leukocytes (PBLs) and the risk of prostate cancer (PCa) has not been investigated. In a case-control study of 196 PCa patients and 196 age-paired healthy controls in a Chinese Han population, the association between mtDNA copy number in PBLs and PCa risk was evaluated. The relative mtDNA copy number was measured using quantitative real-time PCR; samples from three cases and two controls could not be assayed, leaving 193 cases and 194 controls for analysis. PCa patients had significantly higher mtDNA copy numbers than controls (medians 0.91 and 0.82, respectively; P<0.001). Dichotomized at the median value of mtDNA copy number in the controls, high mtDNA copy number was significantly associated with an increased risk of PCa (adjusted odds ratio = 1.85, 95% confidence interval: 1.21–2.83). A significant dose-response relationship was observed between mtDNA copy number and risk of PCa in quartile analysis (Ptrend = 0.011). Clinicopathological analysis showed that high mtDNA copy numbers in PCa patients were significantly associated with high Gleason score and advanced tumor stage, but not serum prostate-specific antigen level (P = 0.002, 0.012 and 0.544, respectively). These findings of the present study indicate that increased mtDNA copy number in PBLs is significantly associated with an increased risk of PCa and may be a reflection of tumor burden