A partner-matching framework for social activity communities

A lot of daily activities require more than one person to participate and collaborate with each other; however, for many people, it is not easy to find good partners to engage in activities with one another. With the rapid growth of social network applications, more and more people get used to creating connections with people on the social network. Therefore, designing social network framework for partner-matching is significant in helping people to easily find good partners. In this paper, we proposed a framework which can match partners for an active community. In order to improve the matching performance, all users are divided into groups based on a specific classification tree that is built for a specific activity. The optimization goal of the partner-matching is to maintain as many stable partnerships as possible in the community. To achieve the goal, various factors are considered to design matching functions. The simulation results show that the proposed framework can help most people find stable partners quickly

A Model for Residential Building Energy Consumption Characteristics and Energy Demand: A Case in Chongqing

AbstractThis study adopts a bottom-up typical method to establish the microscopic model to simulate the urban residential building energy consumption. The model is composed of a three-hierarchy structure: a) the classification according to the climate; b) according to the energy use; c) according to the energy intensity. Based on the model, energy consumption of urban residential building in Chongqing is calculated as an example. The calculation results of the model and the actual energy consumption are compared and validated. The residential building energy consumption model can be used to analyze the energy consumption in the past years using the existing data, as well as the development trend of the related factors so that the appropriate energy saving measures can be selected properly

The Mechanism and Pathways of Dopamine and Dopamine Agonists in Prolactinomas

Dopamine agonists such as bromocriptine and cabergoline are the predominant treatment drugs for prolactinoma by inhibiting prolactin secretion and shrinking tumor size. However, the pathways of either dopamine or its agonists that lead to the death of cells are incompletely understood and some are even conflicting conclusions. The main aim of this paper is to review the different pathways of dopamine and its agonists in prolactinomas to help to gain a better understanding of their functions and drug resistance mechanisms

Multi-view radiomics and deep learning modeling for prostate cancer detection based on multi-parametric MRI

IntroductionThis study aims to develop an imaging model based on multi-parametric MR images for distinguishing between prostate cancer (PCa) and prostate hyperplasia.MethodsA total of 236 subjects were enrolled and divided into training and test sets for model construction. Firstly, a multi-view radiomics modeling strategy was designed in which different combinations of radiomics feature categories (original, LoG, and wavelet) were compared to obtain the optimal input feature sets. Minimum-redundancy maximum-relevance (mRMR) selection and least absolute shrinkage selection operator (LASSO) were used for feature reduction, and the next logistic regression method was used for model construction. Then, a Swin Transformer architecture was designed and trained using transfer learning techniques to construct the deep learning models (DL). Finally, the constructed multi-view radiomics and DL models were combined and compared for model selection and nomogram construction. The prediction accuracy, consistency, and clinical benefit were comprehensively evaluated in the model comparison.ResultsThe optimal input feature set was found when LoG and wavelet features were combined, while 22 and 17 radiomic features in this set were selected to construct the ADC and T2 multi-view radiomic models, respectively. ADC and T2 DL models were built by transferring learning from a large number of natural images to a relatively small sample of prostate images. All individual and combined models showed good predictive accuracy, consistency, and clinical benefit. Compared with using only an ADC-based model, adding a T2-based model to the combined model would reduce the model’s predictive performance. The ADCCombinedScore model showed the best predictive performance among all and was transformed into a nomogram for better use in clinics.DiscussionThe constructed models in our study can be used as a predictor in differentiating PCa and BPH, thus helping clinicians make better clinical treatment decisions and reducing unnecessary prostate biopsies

The change in blood glucose levels in tuberculosis patients before and during anti-tuberculosis treatment in China.

OBJECTIVE: We aimed to observe (i) changes in fasting blood glucose (FBG) in tuberculosis (TB) patients before and during anti-TB treatment, (ii) whether FBG levels were stable or unstable and (iii) baseline characteristics associated with an unstable FBG. METHOD: TB patients consecutively attended six clinics or hospitals. FBG measurements were made at months 0, 2 and 6. Data analysis was performed using the chi-square test and multivariate logistic regression. RESULTS: Of 232 patients without diabetes mellitus (DM) whose initial FBG < 6.1 mmol/L, over 90% maintained FBG < 6.1 mmol/L during treatment and no patient developed DM. Of 17 patients without DM and initial FBG between 6.1 and 6.9 mmol/L, over half had FBG < 6.1 mmol/L during treatment and no patient had DM at the end of treatment. Eight DM patients with already known DM had their FBG controlled at < 7.0 mmol/L during treatment. There were 13 DM patients newly diagnosed with FBG ≥ 7.0 mmol/L, and 69% continued to have FBG ≥ 7.0 mmol/L. After adjustment for confounding, the odds for an unstable FBG were higher for HIV-positive status, already having DM, smoking and coming to hospitals rather than clinics. CONCLUSION: TB patients who do not have DM based on FBG measurements do not develop DM during anti-TB treatment. Those newly diagnosed with DM on screening in general maintain their DM status with high FBG and need to be better managed

Social Cognitive Role of Schizophrenia Candidate Gene GABRB2

10.1371/journal.pone.0062322PLoS ONE84

Development of a PNA Probe for Fluorescence In Situ Hybridization Detection of Prorocentrum donghaiense

Prorocentrum donghaiense is a common but dominant harmful algal bloom (HAB) species, which is widely distributed along the China Sea coast. Development of methods for rapid and precise identification and quantification is prerequisite for early-stage warning and monitoring of blooms due to P. donghaiense. In this study, sequences representing the partial large subunit rDNA (D1–D2), small subunit rDNA and internal transcribed spacer region (ITS-1, 5.8S rDNA and ITS-2) of P. donghaiense were firstly obtained, and then seven candidate DNA probes were designed for performing fluorescence in situ hybridization (FISH) tests on P. donghaiense. Based on the fluorescent intensity of P. donghaiense cells labeled by the DNA probes, the probe DP0443A displayed the best hybridization performance. Therefore, a PNA probe (PP0443A) analogous to DP0443A was used in the further study. The cells labeled with the PNA probe displayed more intensive green fluorescence than that labeled with its DNA analog. The PNA probe was used to hybridize with thirteen microalgae belonging to five families, i.e., Dinophyceae, Prymnesiophyceae, Raphidophyceae, Chlorophyceae and Bacillariophyceae, and showed no visible cross-reaction. Finally, FISH with the probes PP0443A and DP0443A and light microscopy (LM) analysis aiming at enumerating P. donghaiense cells were performed on the field samples. Statistical comparisons of the cell densities (cells/L) of P. donghaiense in the natural samples determined by FISH and LM were performed using one-way ANOVA and Duncan's multiple comparisons of the means. The P. donghaiense cell densities determined by LM and the PNA probe are remarkably higher than (p<0.05) that determined by the DNA probe, while no significant difference is observed between LM and the PNA probe. All results suggest that the PNA probe is more sensitive that its DNA analog, and therefore is promising for the monitoring of harmful algal blooms of P. donghaiense in the future

Effects of the neurogranin variant rs12807809 on thalamocortical morphology in schizophrenia

10.1371/journal.pone.0085603PLoS ONE812-POLN