Fast Markov Clustering Algorithm Based on Belief Dynamics.

Graph clustering is one of the most significant, challenging, and valuable topic in the analysis of real complex networks. To detect the cluster configuration accurately and efficiently, we propose a new Markov clustering algorithm based on the limit state of the belief dynamics model. First, we present a new belief dynamics model, which focuses beliefs of multicontent and randomly broadcasting information. A strict proof is provided for the convergence of nodes' normalized beliefs in complex networks. Second, we introduce a new Markov clustering algorithm (denoted as BMCL) by employing a belief dynamics model, which guarantees the ideal cluster configuration. Following the trajectory of the belief convergence, each node is mapped into the corresponding cluster repeatedly. The proposed BMCL algorithm is highly efficient: the convergence speed of the proposed algorithm researches O(TN) in sparse networks. Last, we implement several experiments to evaluate the performance of the proposed methods.

Comprehensive assessment of cellular senescence in the tumor microenvironment.

Cellular senescence (CS), a state of permanent growth arrest, is intertwined with tumorigenesis. Due to the absence of specific markers, characterizing senescence levels and senescence-related phenotypes across cancer types remain unexplored. Here, we defined computational metrics of senescence levels as CS scores to delineate CS landscape across 33 cancer types and 29 normal tissues and explored CS-associated phenotypes by integrating multiplatform data from ~20 000 patients and ~212 000 single-cell profiles. CS scores showed cancer type-specific associations with genomic and immune characteristics and significantly predicted immunotherapy responses and patient prognosis in multiple cancers. Single-cell CS quantification revealed intra-tumor heterogeneity and activated immune microenvironment in senescent prostate cancer. Using machine learning algorithms, we identified three CS genes as potential prognostic predictors in prostate cancer and verified them by immunohistochemical assays in 72 patients. Our study provides a comprehensive framework for evaluating senescence levels and clinical relevance, gaining insights into CS roles in cancer- and senescence-related biomarker discovery.

Developing a Sustainable Long-Term Ageing Health Care System Using the DANP-mV Model: Empirical Case of Taiwan.

Most of the baby boomers born after the Second World War (WWII) have passed the age of 65, meaning they have gradually lost their social functions and positions, and are facing the need for care. In Taiwan, the lack of a long-term care mechanism is having a certain degree of impact on society as a whole, and thus, it is important to have a mechanism to take care of the elderly. In order to make this system sustainable, sufficient funds and continuous improvement are important factors. In the past, in order to avoid the illegal transfer of benefits, the social welfare mechanism avoided the use of for-profit organizations. However, as the economic environment declines, the role of for-profit organizations should be considered. This study defines the long-term ageing health care system using five major dimensions and 20 criteria. The DANP-mV model was used to analyze Taiwan's current system and identify problems, and then to develop a continuous improvement strategy from the perspective of the source of the problem in order to improve long-term ageing health care.

[Assessment of hypoglycemic status among hospitalized elderly patients with type 2 diabetes].

OBJECTIVE: To investigate the hypoglycemic characteristics of hospitalized elderly patients with type 2 diabetes mellitus (T2DM). METHODS: From January, 2014 to December, 2015, the data of 58 565 blood measurements using a standard blood glucose monitoring system (BGMS) were collected from 1187 cases of patients with type 2 diabetes during hospitalization in the Department of Endocrinology, Guangdong General Hospital (Guangzhou, China). Stratified analyses were conducted by dividing the patients into 3 age groups, namely <45 years group (128 cases), 45-64 years group (594 cases), and ≥65 years group (465 cases). The incidence and time distribution of hypoglycemia in these patients were compared among the 3 age groups. RESULTS: The risk of hypoglycemia increased with age. Compared with those below 45 years of age, the patients beyond or equal to 65 years had a significantly increased hypoglycemic density (0.95% vs 0.40%, P<0.001), a higher proportion of patients with hypoglycemia (28.17% vs 10.94%, P<0.001), and greater patient-days with hypoglycemia (4.48% vs 1.76%, P<0.001). In the elderly patients, hypoglycemia occurred most frequently before dawn, at which time the hypoglycemic density was 2.66% in patients ≥65 years of age, significantly higher than that in patients below 45 years (1.09%, P<0.05) and between 45 and 64 years (1.90%, P<0.05); the proportion of patients with hypoglycemia was also significantly higher in the elderly patients (14.57%) than in those below 45 years (3.77%, P<0.02) and between 45 and 64 years (9.42%, P<0.02). The proportion of patients with recurrent hypoglycemia (≥2 times) was significantly higher in patients ≥65 years (13.33%) than in younger patients (2.34% in <45 years group and 9.43% in 45-64 years group, P<0.05). CONCLUSION: The hypoglycemic risk in hospitalized elderly patients with T2DM is significantly higher than that in younger patients, especially before dawn and in terms of recurrent hypoglycemia. Clinicians should develop differential blood glucose monitoring and management strategies for these elderly patients to improve the clinical safety.

A straightforward strategy toward large BN-embedded π-systems: synthesis, structure, and optoelectronic properties of extended BN heterosuperbenzenes.

A straightforward strategy has been used to construct large BN-embedded π-systems simply from azaacenes. BN heterosuperbenzene derivatives, the largest BN heteroaromatics to date, have been synthesized in three steps. The molecules exhibit curved π-surfaces, showing two different conformations which are self-organized into a sandwich structure and further packed into a π-stacking column. The assembled microribbons exhibit good charge transport properties and photoconductivity, representing an important step toward the optoelectronic applications of BN-embedded aromatics.

[Uncertainty analysis of water environmental capacity in the nonpoint source polluted river].

Based on the one-dimension model for river water environmental capacity (WEC) and the statistical analysis of the measured hydrological and water quality variables, a uncertainty analysis method for the WEC in nonpoint source polluted river was developed, which included the sensitivity analysis for input parameters of the model and the probability distributions analysis for the WEC using Monte Carlo simulation approach. The method, which described the uncertainty derived from the adopted information of the river system and the randomicity from the occurrence of nonpoint source pollution, could provide different WEC combined with reliabilities for different hydrological seasons. As a case study, the total nitrogen (TN) WEC in the Changle River located in southeast China was calculated using the method. Results indicated that the TN WEC with 90% of reliability were 487.9, 949.8 and 1392.8 kg x d(-1) in dry season, average season and flood season, respectively, and the dilution effect of river water flow accounted for the main content of WEC. In order to satisfy water quality target of the river, about 1258.3-3591.2 kg x d(-1) of current TN quantity that entered into the river should be reduced in watershed, and the largest reducing quantity of TN was occurred during flood season. The uncertainty method, which reflected hydrology and water quality variations in the nonpoint source polluted river, provided a more reliable and efficient method for the WEC calculation.