Dynamic Models of the Interaction between Migration and the Differential Growth of Cities

The general area of interest of this paper is the dynamic relationship between regional imbalances, migration, and the differential growth of cities. In particular, the paper considers the feasibility of building dynamic models of the economic and demographic interactions between a set of linked cities, which could be used to explore the effects and repercussions of national settlement policies addressed at the alleviation of imbalances. Inter-regional economic growth models are well known, and, recently several papers have focused on inter-regional demographic models. There has been less research on the dynamics of the interdependent interaction between economic and demographic growth. This paper focuses on this economic-demographic adjustment for a system of linked city regions and considers research results which point to several difficulties in building theoretically well structured dynamic models of differential city growth. Part of the paper considers the inadequacies of current theories of inter-regional population migration and a new approach based on job-search theory is outlined

Bad expression influences time to androgen escape in prostate cancer

<b>OBJECTIVE</b>: To assess the role of selected downstream Bcl-2 family members (Bad, Bax, Bcl-2 and Bcl-xL) in the development of androgen-independent prostate cancer (AIPC), as androgen-deprivation therapy is the treatment of choice in advanced prostate cancer, yet patients generally relapse and progress to an AI state within 18–24 months. <b>PATIENTS, MATERIALS AND METHODS</b>: The patient cohort was established by retrospectively selecting patients with prostate cancer who had an initial response to androgen-deprivation therapy, but subsequently relapsed with AIPC. In all, 58 patients with prostate cancer were included with matched androgen-dependent (AD) and AI prostate tumours available for immunohistochemical analysis; two independent observers using a weighted-histoscore method scored the staining. Changes in Bad, Bax, Bcl-2 and Bcl-xL expression during transition to AIPC were evaluated and then correlated to known clinical variables. <b>RESULTS</b>: High Bad expression in AD tumours was associated with an increased time to biochemical relapse (<i>P</i> = 0.007) and a trend towards improved overall survival (<i>P</i> = 0.053). There were also trends towards a decrease in Bad (<i>P</i> = 0.068) and Bax (<i>P</i> = 0.055) expression with progression to AIPC. There were no significant results for Bcl-2 or Bcl-xL. <b>CONCLUSION</b>: There is evidence to suggest that Bad expression levels at diagnosis influence time to biochemical relapse and overall survival, and that levels of pro-apoptotic proteins Bad and Bax fall during AIPC development. Bad might therefore represent a possible positive prognostic marker and potential therapeutic target for AIPC in the future

Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS).

BackgroundFor men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification.MethodsUrine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to ≥34%. The association of biomarker scores, adjusted for common clinical variables, with short- and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSeven hundred and eighty-two men contributed 2069 urine specimens. After adjusting for PSA, prostate size, and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (OR = 1.3; 95% CI 1.0-1.7, p = 0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker nor marker kinetics was associated with time to reclassification in subsequent biopsies.ConclusionsPCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies

Online Reputation Systems in Web 2.0 Era

Web 2.0 has transformed how reputation systems are designed and used by the Web. Based on a thorough review of the existing online reputation systems and their challenges in use, this paper studied a case of Amazon’s reputation system for the impacts of Web 2.0. Through our case study, several distinguished features of new generation reputation systems are noted including multimedia feedbacks, reviewer centered, folksonomy (use of tag), community contribution, comprehensive reputation, dynamic and interactive system etc.. These new developments promise a path that move towards a trustworthy and reliable online reputation system in the Web 2.0 era

Boolean analysis identifies CD38 as a biomarker of aggressive localized prostate cancer.

The introduction of serum Prostate Specific Antigen (PSA) testing nearly 30 years ago has been associated with a significant shift towards localized disease and decreased deaths due to prostate cancer. Recognition that PSA testing has caused over diagnosis and over treatment of prostate cancer has generated considerable controversy over its value, and has spurred efforts to identify prognostic biomarkers to distinguish patients who need treatment from those that can be observed. Recent studies show that cancer is heterogeneous and forms a hierarchy of tumor cell populations. We developed a method of identifying prostate cancer differentiation states related to androgen signaling using Boolean logic. Using gene expression data, we identified two markers, CD38 and ARG2, that group prostate cancer into three differentiation states. Cancers with CD38-, ARG2- expression patterns, corresponding to an undifferentiated state, had significantly lower 10-year recurrence-free survival compared to the most differentiated group (CD38+ARG2+). We carried out immunohistochemical (IHC) staining for these two markers in a single institution (Stanford; n = 234) and multi-institution (Canary; n = 1326) cohorts. IHC staining for CD38 and ARG2 in the Stanford cohort demonstrated that combined expression of CD38 and ARG2 was prognostic. In the Canary cohort, low CD38 protein expression by IHC was significantly associated with recurrence-free survival (RFS), seminal vesicle invasion (SVI), extra-capsular extension (ECE) in univariable analysis. In multivariable analysis, ARG2 and CD38 IHC staining results were not independently associated with RFS, overall survival, or disease-specific survival after adjusting for other factors including SVI, ECE, Gleason score, pre-operative PSA, and surgical margins

Firmament: Fast, Centralized Cluster Scheduling at Scale

Centralized datacenter schedulers can make high-quality placement decisions when scheduling tasks in a cluster. Today, however, high-quality placements come at the cost of high latency at scale, which degrades response time for interactive tasks and reduces cluster utilization. This paper describes Firmament, a centralized scheduler that scales to over ten thousand machines at sub- second placement latency even though it continuously reschedules all tasks via a min-cost max-flow (MCMF) optimization. Firmament achieves low latency by using multiple MCMF algorithms, by solving the problem incrementally, and via problem-specific optimizations. Experiments with a Google workload trace from a 12,500-machine cluster show that Firmament improves placement latency by 20 x over Quincy [22], a prior centralized scheduler using the same MCMF optimiza- tion. Moreover, even though Firmament is centralized, it matches the placement latency of distributed schedulers for workloads of short tasks. Finally, Firmament exceeds the placement quality of four widely-used central- ized and distributed schedulers on a real-world cluster, and hence improves batch task response time by 6 x.This work was supported by a Google European Doc- toral Fellowship, by NSF award CNS-1413920, and by the Defense Advanced Research Projects Agency (DARPA) and Air Force Research Laboratory (AFRL), under contract FA8750-11-C-0249

Genomic analysis of the kiwifruit pathogen Pseudomonas syringae pv. actnidiae provides insight into the origins of an emergent plant disease

The origins of crop diseases are linked to domestication of plants. Most crops were domesticated centuries – even millennia – ago, thus limiting opportunity to understand the concomitant emergence of disease. Kiwifruit (Actinidia spp.) is an exception: domestication began in the 1930s with outbreaks of canker disease caused by P. syringae pv. actinidiae (Psa) first recorded in the 1980s. Based on SNP analyses of two circularized and 34 draft genomes, we show that Psa is comprised of distinct clades exhibiting negligible within-clade diversity, consistent with disease arising by independent samplings from a source population. Three clades correspond to their geographical source of isolation; a fourth, encompassing the Psa-V lineage responsible for the 2008 outbreak, is now globally distributed. Psa has an overall clonal population structure, however, genomes carry a marked signature of within-pathovar recombination. SNP analysis of Psa-V reveals hundreds of polymorphisms; however, most reside within PPHGI-1-like conjugative elements whose evolution is unlinked to the core genome. Removal of SNPs due to recombination yields an uninformative (star-like) phylogeny consistent with diversification of Psa-V from a single clone within the last ten years. Growth assays provide evidence of cultivar specificity, with rapid systemic movement of Psa-V in Actinidia chinensis. Genomic comparisons show a dynamic genome with evidence of positive selection on type III effectors and other candidate virulence genes. Each clade has highly varied complements of accessory genes encoding effectors and toxins with evidence of gain and loss via multiple genetic routes. Genes with orthologs in vascular pathogens were found exclusively within Psa-V. Our analyses capture a pathogen in the early stages of emergence from a predicted source population associated with wild Actinidia species. In addition to candidate genes as targets for resistance breeding programs, our findings highlight the importance of the source population as a reservoir of new disease

Integrated Expression of Circulating miR375 and miR371 to Identify Teratoma and Active Germ Cell Malignancy Components in Malignant Germ Cell Tumors

Active germ cell malignancies express high levels of specific circulating micro-RNAs (miRNAs), including miR-371a-3p (miR371), which is undetectable in teratoma. Teratoma markers are urgently needed for theselection of patients and treatments because of the risk of malignant transformation and growing teratoma syndrome. To assess the accuracy of plasma miR375 alone or in combination with miR371 in detecting teratoma, 100 germ cell tumor patients, divided into two cohorts, were enrolled in a prospective multi-institutional study. In the discovery cohort, patients with pure teratoma and with no/low risk of harboring teratoma were compared; the validation cohort included patients with confirmed teratoma, active germ cell malignancy, or complete response after chemotherapy. The area under the receiver operating characteristic curve values for miR375, miR371, and miR371-miR375 were, respectively, 0.93 (95% confidence interval [CI]: 0.87-0.99), 0.59 (95% CI: 0.44-0.73), and 0.95 (95% CI: 0.90-0.99) in the discovery cohort and 0.55 (95% CI: 0.36-0.74), 0.74 (95% CI: 0.58-0.91), and 0.77 (95% CI: 0.62-0.93) in the validation cohort. Our study demonstrated that the plasma miR371-miR375 integrated evaluation is highly accurate to detect teratoma. PATIENT SUMMARY: The evaluation of two micro-RNAs (miR375-miR371) in the blood of patients with germ cell tumors is promising to predict teratoma. This test could be particularly relevant to the identification of teratoma in patients with postchemotherapy residual disease.info:eu-repo/semantics/publishedVersio