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

The Utility and Compatibility of Simple Migration Models

This paper examines the contribution that three simple migration models can make towards a fuller understanding of the migration process. The models employed are a Kinematic model, a Markov Chain model and a Modified Markov model. Their capacities to reflect trends inherent in migration matrices from England and Wales, Italy, Germany, and France are examined in three ways. Firstly, the variations between the projections of each model are compared with the maximum projected changes after ten and fifty years. Secondly, the sensitivity of the models to changes in system parameters is explored in order to test the utility of the models as monitoring tools. Thirdly, the generality of the models is tested by making changes in the geographic specification of the German regional system. An associate exercise employs a more complex model incorporating positive feedback effects in order to compare the likely redistributive effects of policy input

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

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

Adversarial Policies Beat Superhuman Go AIs

We attack the state-of-the-art Go-playing AI system KataGo by training adversarial policies against it, achieving a >97% win rate against KataGo running at superhuman settings. Our adversaries do not win by playing Go well. Instead, they trick KataGo into making serious blunders. Our attack transfers zero-shot to other superhuman Go-playing AIs, and is comprehensible to the extent that human experts can implement it without algorithmic assistance to consistently beat superhuman AIs. The core vulnerability uncovered by our attack persists even in KataGo agents adversarially trained to defend against our attack. Our results demonstrate that even superhuman AI systems may harbor surprising failure modes. Example games are available https://goattack.far.ai/.Comment: Accepted to ICML 2023, see paper for changelo

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

A diagnosis of prostate cancer and pursuit of active surveillance is not followed by weight loss: potential for a teachable moment

BACKGROUND: Obesity is a risk factor for incident prostate cancer (PC) as well as risk of disease progression and mortality. We hypothesized that men diagnosed with lower-risk PC and who elected active surveillance (AS) for their cancer management would likely initiate lifestyle changes that lead to weight loss. METHODS: Patients were enrolled in the Prostate Active Surveillance Study (PASS), a multicenter prospective biomarker discovery and validation study of men who have chosen AS for their PC. Data from 442 men diagnosed with PC within 1 year of study entry who completed a standard of care 12-month follow-up visit were analyzed. We examined the change in weight and body mass index (BMI) over the first year of study participation. RESULTS: After 1 year on AS, 7.5% (33/442) of patients had lost 5% or more of their on-study weight. The proportion of men who lost 5% or more weight was similar across categories of baseline BMI: normal/underweight (8%), overweight (6%) and obese (10%, χ2 test P=0.44). The results were similar for patients enrolled in the study 1 year or 6 months after diagnosis. By contrast, after 1 year, 7.7% (34/442) of patients had gained >5% of their weight. CONCLUSIONS: Only 7.5% of men with low-risk PC enrolled in AS lost a modest (⩾5%) amount of weight after diagnosis. Given that obesity is related to PC progression and mortality, targeted lifestyle interventions may be effective at this 'teachable moment', as men begin AS for low-risk PC

Large oncosomes contain distinct protein cargo and represent a separate functional class of tumor-derived extracellular vesicles

Large oncosomes (LO) are atypically large (1-10 mu m diameter) cancer-derived extracellular vesicles (EVs), originating from the shedding of membrane blebs and associated with advanced disease. We report that 25% of the proteins, identified by a quantitative proteomics analysis, are differentially represented in large and nano-sized EVs from prostate cancer cells. Proteins enriched in large EVs included enzymes involved in glucose, glutamine and amino acid metabolism, all metabolic processes relevant to cancer. Glutamine metabolism was altered in cancer cells exposed to large EVs, an effect that was not observed upon treatment with exosomes. Large EVs exhibited discrete buoyant densities in iodixanol (OptiPrep (TM)) gradients. Fluorescent microscopy of large EVs revealed an appearance consistent with LO morphology, indicating that these structures can be categorized as LO. Among the proteins enriched in LO, cytokeratin 18 (CK18) was one of the most abundant (within the top 5th percentile) and was used to develop an assay to detect LO in the circulation and tissues of mice and patients with prostate cancer. These observations indicate that LO represent a discrete EV type that may play a distinct role in tumor progression and that may be a source of cancer-specific markers.1182Ysciescopu

Integrated analysis of the prostate cancer small-nucleolar transcriptome reveals <i>SNORA55</i> as a driver of prostate cancer progression

Metastasis is the primary cause of death in prostate cancer (PCa) patients. Small nucleolar RNAs (snoRNAs) have long been considered "housekeeping" genes with no relevance for cancer biology. Emerging evidence has challenged this assumption, suggesting that snoRNA expression is frequently modulated during cancer progression. Despite this, no study has systematically addressed the prognostic and functional significance of snoRNAs in PCa. We performed RNA Sequencing on paired metastatic/non-metastatic PCa xenografts derived from clinical specimens. The clinical significance of differentially expressed snoRNAs was further investigated in two independent primary PCa cohorts (131 and 43 patients, respectively). The snoRNA demonstrating the strongest association with clinical outcome was quantified in PCa patient-derived serum samples and its functional relevance was investigated in PCa cells via gene expression profiling, pathway analysis and gene silencing. Our comparison revealed 21 differentially expressed snoRNAs in the metastatic vs. non-metastatic xenografts. Of those, 12 were represented in clinical databases and were further analyzed. SNORA55 emerged as a predictor of shorter relapse-free survival (results confirmed in two independent databases). SNORA55 was reproducibly detectable in serum samples from PCa patients. SNORA55 silencing in PCa cell lines significantly inhibited cell proliferation and migration. Pathway analysis revealed that SNORA55 expression is significantly associated with growth factor signaling and pro-inflammatory cytokine expression in PCa. Our results demonstrate that SNORA55 up-regulation predicts PCa progression and that silencing this non-coding gene affects PCa cell proliferation and metastatic potential, thus positioning it as both a novel biomarker and therapeutic target