Entrepreneurship and Urban Success: Toward a Policy Consensus

Like all politics, all entrepreneurship is local. Individuals launch firms and, if successful, expand their enterprises to other locations. But new firms must start somewhere, even if their businesses are conducted largely or exclusively on the Internet. Likewise, policymakers at local and state levels increasingly recognize that entrepreneurship is the key to building and sustaining their economies\u27 growth. Although this is a seemingly obvious proposition, it represents something of a departure from past thinking about how local, state, or regional economies grow. Historically, state and local policymakers have put their energies into trying to attract existing firms from somewhere else, either to relocate to a particular area or to build new facilities there. Such smokestack chasing - or, in this cleaner era, simply firm chasing - often has degenerated into what is essentially a zero-sum game for the national economy. When one city or state offers tax breaks or other financial inducements to encourage firms to locate new plants or headquarters, and succeeds, some other city or state loses out in the process. Local, state, and regional economic development centered on entrepreneurship, however, is a fundamentally different phenomenon. The formation and growth of new firms, especially those built around new products or ways of doing things, wherever this occurs, is clearly a positive sum game, not just for the locality, but for the nation as a whole. This essay provides a guide to policymakers and citizens to what is known about the effects of various local and state policies aimed at fostering entrepreneurially driven growth. There is also much we do not know; thus, the essay identifies subjects that require further research

Longitudinal Screening Detects Cognitive Stability and Behavioral Deterioration in ALS Patients

Objective. To evaluate longitudinal cognitive/behavioral change over 12 months in participants enrolled in the ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS). Methods. We analyzed data from 294 ALS participants, 134 of whom were studied serially. Change over time was evaluated controlling for age, sex, symptom duration, education, race, and ethnicity. Using multiple regression, we evaluated associations among decline in ALS Functional Rating Scale-Revised (ALSFRS-R) scores, forced vital capacity (FVC), and cognitive/behavioral changes. Change in cognitive/behavioral subgroups was assessed using one-way analyses of covariance. Results. Participants with follow-up data had fewer baseline behavior problems compared to patients without follow-up data. We found significant worsening of behavior (ALS Cognitive Behavioral Screen (ALS CBS) behavioral scale, p \u3c 0.001; Frontal Behavioral Inventory-ALS (FBI-ALS) disinhibition subscale, p = 0.044). Item analysis suggested change in frustration tolerance, insight, mental rigidity, and interests (p \u3c 0.05). Changes in ALSFRS-R correlated with the ALS CBS. Worsening disinhibition (FBI-ALS) did not correlate with ALSFRS-R, FVC, or disease duration. Conclusion. We did not detect cognitive change. Behavioral change was detected, and increased disinhibition was found among patients with abnormal baseline behavioral scores. Disinhibition changes did not correlate with disease duration or progression. Baseline behavioral problems were associated with advanced, rapidly progressive disease and study attrition

Corrigendum to "Longitudinal Screening Detects Cognitive Stability and Behavioral Deterioration in ALS Patients".

[This corrects the article DOI: 10.1155/2018/5969137.]

Longitudinal Screening Detects Cognitive Stability and Behavioral Deterioration in ALS Patients.

ObjectiveTo evaluate longitudinal cognitive/behavioral change over 12 months in participants enrolled in the ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS).MethodsWe analyzed data from 294 ALS participants, 134 of whom were studied serially. Change over time was evaluated controlling for age, sex, symptom duration, education, race, and ethnicity. Using multiple regression, we evaluated associations among decline in ALS Functional Rating Scale-Revised (ALSFRS-R) scores, forced vital capacity (FVC), and cognitive/behavioral changes. Change in cognitive/behavioral subgroups was assessed using one-way analyses of covariance.ResultsParticipants with follow-up data had fewer baseline behavior problems compared to patients without follow-up data. We found significant worsening of behavior (ALS Cognitive Behavioral Screen (ALS CBS) behavioral scale, p < 0.001; Frontal Behavioral Inventory-ALS (FBI-ALS) disinhibition subscale, p = 0.044). Item analysis suggested change in frustration tolerance, insight, mental rigidity, and interests (p < 0.05). Changes in ALSFRS-R correlated with the ALS CBS. Worsening disinhibition (FBI-ALS) did not correlate with ALSFRS-R, FVC, or disease duration.ConclusionWe did not detect cognitive change. Behavioral change was detected, and increased disinhibition was found among patients with abnormal baseline behavioral scores. Disinhibition changes did not correlate with disease duration or progression. Baseline behavioral problems were associated with advanced, rapidly progressive disease and study attrition

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Evidence of positive selection associated with placental loss in tiger sharks

Background: All vertebrates initially feed their offspring using yolk reserves. In some live-bearing species these yolk reserves may be supplemented with extra nutrition via a placenta. Sharks belonging to the Carcharhinidae family are all live-bearing, and with the exception of the tiger shark (Galeocerdo cuvier), develop placental connections after exhausting yolk reserves. Phylogenetic relationships suggest the lack of placenta in tiger sharks is due to secondary loss. This represents a dramatic shift in reproductive strategy, and is likely to have left a molecular footprint of positive selection within the genome. Results: We sequenced the transcriptome of the tiger shark and eight other live-bearing shark species. From this data we constructed a time-calibrated phylogenetic tree estimating the tiger shark lineage diverged from the placental carcharhinids approximately 94 million years ago. Along the tiger shark lineage, we identified five genes exhibiting a signature of positive selection. Four of these genes have functions likely associated with brain development (YWHAE and ARL6IP5) and sexual reproduction (VAMP4 and TCTEX1D2). Conclusions: Our results indicate the loss of placenta in tiger sharks may be associated with subsequent adaptive changes in brain development and sperm production