In depth characterization of midbrain organoids derived from wild type iPSC lines.

The ability to model human neurological tissues in vitro has been a major hurdle to effective drug development for neurological disorders. iPSC-derived brain organoids have emerged as a compelling solution to this problem as they have the potential to relevantly model the protein expression pattern and physiology of specific brain regions. Although many protocols now exist for the production of brain organoids, few attempts have been made to do an in-depth kinetic evaluation of expression of mature regiospecific markers of brain organoids. To address this, we differentiated midbrain-specific brain organoids from iPSC-lines derived from three apparently healthy individuals using a matrix-free, bioreactor method. We monitored the expression of midbrain-specific neuronal markers from 7 to 90-days using immunofluorescence and immunohistology. The organoids were further characterized using electron microscopy and RNA-seq. In addition to serving as a potential benchmark for the future evaluation of other differentiation protocols, the markers observed in this study can be useful as control parameters to identify and evaluate the disease phenotypes in midbrain organoid derived from patient iPSC-lines with genetic neurological disorders.

Generation and characterization of NGLY1 patient-derived midbrain organoids.

NGLY1 deficiency is an ultra-rare, autosomal recessive genetic disease caused by mutations in the NGLY1 gene encoding N-glycanase one that removes N-linked glycan. Patients with pathogenic mutations in NGLY1 have complex clinical symptoms including global developmental delay, motor disorder and liver dysfunction. To better understand the disease pathogenesis and the neurological symptoms of the NGLY1 deficiency we generated and characterized midbrain organoids using patient-derived iPSCs from two patients with distinct disease-causing mutations-one homozygous for p. Q208X, the other compound heterozygous for p. L318P and p. R390P and CRISPR generated NGLY1 knockout iPSCs. We demonstrate that NGLY1 deficient midbrain organoids show altered neuronal development compared to one wild type (WT) organoid. Both neuronal (TUJ1) and astrocytic glial fibrillary acid protein markers were reduced in NGLY1 patient-derived midbrain organoids along with neurotransmitter GABA. Interestingly, staining for dopaminergic neuronal marker, tyrosine hydroxylase, revealed a significant reduction in patient iPSC derived organoids. These results provide a relevant NGLY1 disease model to investigate disease mechanisms and evaluate therapeutics for treatments of NGLY1 deficiency.

High-Content Drug Discovery Targeting Molecular Bladder Cancer Subtypes.

Molecular subtypes of muscle-invasive bladder cancer (MIBC) display differential survival and drug sensitivities in clinical trials. To date, they have not been used as a paradigm for phenotypic drug discovery. This study aimed to discover novel subtype-stratified therapy approaches based on high-content screening (HCS) drug discovery. Transcriptome expression data of CCLE and BLA-40 cell lines were used for molecular subtype assignment in basal, luminal, and mesenchymal-like cell lines. Two independent HCSs, using focused compound libraries, were conducted to identify subtype-specific drug leads. We correlated lead drug sensitivity data with functional genomics, regulon analysis, and in-vitro drug response-based enrichment analysis. The basal MIBC subtype displayed sensitivity to HDAC and CHK inhibitors, while the luminal subtype was sensitive to MDM2 inhibitors. The mesenchymal-like cell lines were exclusively sensitive to the ITGAV inhibitor SB273005. The role of integrins within this mesenchymal-like MIBC subtype was confirmed via its regulon activity and gene essentiality based on CRISPR-Cas9 knock-out data. Patients with high ITGAV expression showed a significant decrease in the median overall survival. Phenotypic high-content drug screens based on bladder cancer cell lines provide rationales for novel stratified therapeutic approaches as a framework for further prospective validation in clinical trials.

Design, Synthesis, and Biological Evaluation of the First Inhibitors of Oncogenic CHD1L.

Chromodomain helicase DNA-binding protein 1 like (CHD1L) is an oncogene implicated in tumor progression, multidrug resistance, and metastasis in many types of cancer. In this article, we described the optimization of the first lead CHD1L inhibitors (CHD1Li) through drug design and medicinal chemistry. More than 30 CHD1Li were synthesized and evaluated using a variety of colorectal cancer (CRC) tumor organoid models and functional assays. The results led to the prioritization of six lead CHD1Li analogues with improved potency, antitumor activity, and drug-like properties including metabolic stability and in vivo pharmacokinetics. Furthermore, lead CHD1Li 6.11 proved to be an orally bioavailable antitumor agent, significantly reducing the tumor volume of CRC xenografts generated from isolated quasi mesenchymal cells (M-phenotype), which possess enhanced tumorigenic properties. In conclusion, we reported the optimization of first-in-class inhibitors of oncogenic CHD1L as a novel therapeutic strategy with potential for the treatment of cancer.

The distributional outcomes of rights-based management in fisheries.

Fisheries managers have increasingly adopted rights-based management (i.e., "catch shares" or "individual transferable quotas" [ITQs]) to address economic and biological management challenges under prior governance regimes. Despite their ability to resolve some of the symptoms of the tragedy of the commons and improve economic efficiency, catch shares remain controversial for their potentially disruptive social effects. One criticism is that the benefits of rights-based reforms are unequally distributed across vessels and between fishery participants (e.g., crew and hired captains) and that stakeholders that do not receive an allocation of harvest rights may see their remuneration decrease. Yet, empirically assessing these claims is difficult in almost all ITQs due to poor availability of longitudinal cost, earnings, and employment data. This paper evaluates these claims using vessel-level data to characterize impacts of a long-established ITQ program for Alaskan crab fisheries on the level and distribution of payments to claimant groups. We find that the share of vessel proceeds accruing to captains, crew, and vessel owners declined under the catch-share regime to make room for new payments to quota owners. Average daily payments to captains, crew, and vessel owners declined, albeit slightly, yet retained their pre-ITQ premia relative to compensation in other sectors. However, inequality in payments to workers and vessel owners declined after ITQs, as did the interseasonal volatility in compensation to workers, a measure of financial risk. Finally, we find that consolidation-induced increases in leasing costs have had little effect on workers' remuneration, but have reduced returns to vessel ownership.

Recommendation as generalization: Using big data to evaluate cognitive models.

The explosion of data generated during human interactions online presents an opportunity for psychologists to evaluate cognitive models outside the confines of the laboratory. Moreover, the size of these online data sets can allow researchers to construct far richer models than would be feasible with smaller in-lab behavioral data. In the current article, we illustrate this potential by evaluating 3 popular psychological models of generalization on 2 web-scale online data sets typically used to build automated recommendation systems. We show that each psychological model can be efficiently implemented at scale and in certain cases can capture trends in human judgments that standard recommendation systems from machine learning miss. We use these results to illustrate the opportunity Internet-scale data sets offer to psychologists and to underscore the importance of using insights from cognitive modeling to supplement the standard predictive-analytic approach taken by many existing machine learning approaches. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Covalent inhibition of NSD1 histone methyltransferase.

The nuclear receptor-binding SET domain (NSD) family of histone methyltransferases is associated with various malignancies, including aggressive acute leukemia with NUP98-NSD1 translocation. While NSD proteins represent attractive drug targets, their catalytic SET domains exist in autoinhibited conformation, presenting notable challenges for inhibitor development. Here, we employed a fragment-based screening strategy followed by chemical optimization, which resulted in the development of the first-in-class irreversible small-molecule inhibitors of the nuclear receptor-binding SET domain protein 1 (NSD1) SET domain. The crystal structure of NSD1 in complex with covalently bound ligand reveals a conformational change in the autoinhibitory loop of the SET domain and formation of a channel-like pocket suitable for targeting with small molecules. Our covalent lead-compound BT5-demonstrates on-target activity in NUP98-NSD1 leukemia cells, including inhibition of histone H3 lysine 36 dimethylation and downregulation of target genes, and impaired colony formation in an NUP98-NSD1 patient sample. This study will facilitate the development of the next generation of potent and selective inhibitors of the NSD histone methyltransferases.

First-in-Class Inhibitors of Oncogenic CHD1L with Preclinical Activity against Colorectal Cancer.

Since the discovery of CHD1L in 2008, it has emerged as an oncogene implicated in the pathology and poor prognosis of a variety of cancers, including gastrointestinal cancers. However, a mechanistic understanding of CHD1L as a driver of colorectal cancer has been limited. Until now, there have been no reported inhibitors of CHD1L, also limiting its development as a molecular target. We sought to characterize the clinicopathologic link between CHD1L and colorectal cancer, determine the mechanism(s) by which CHD1L drives malignant colorectal cancer, and discover the first inhibitors with potential for novel treatments for colorectal cancer. The clinicopathologic characteristics associated with CHD1L expression were evaluated using microarray data from 585 patients with colorectal cancer. Further analysis of microarray data indicated that CHD1L may function through the Wnt/TCF pathway. Thus, we conducted knockdown and overexpression studies with CHD1L to determine its role in Wnt/TCF-driven epithelial-to-mesenchymal transition (EMT). We performed high-throughput screening (HTS) to identify the first CHD1L inhibitors. The mechanism of action, antitumor efficacy, and drug-like properties of lead CHD1L inhibitors were determined using biochemical assays, cell models, tumor organoids, patient-derived tumor organoids, and in vivo pharmacokinetics and pharmacodynamics. Lead CHD1L inhibitors display potent in vitro antitumor activity by reversing TCF-driven EMT. The best lead CHD1L inhibitor possesses drug-like properties in pharmacokinetic/pharmacodynamic mouse models. This work validates CHD1L as a druggable target and establishes a novel therapeutic strategy for the treatment of colorectal cancer.

Fishing to live or living to fish: Job satisfaction and identity of west coast fishermen.

Fishing is a dangerous and financially risky way to make a living, but it attracts many participants that prefer it to higher paying and safer jobs. Based on a survey of over 1400 U.S. West Coast fishing vessel owners we use factor analysis and structural equation modeling to quantify distinct latent variables representing job satisfaction related to non-monetary versus monetary aspects of fishing and measures of identity and social capital associated with being a fisher. We show that these latent variables have distinct effects on (stated) fishery participation behavior and that higher non-monetary job satisfaction, social capital, and identity, are associated with a willingness to forgo higher income to be a fisher. Understanding how these factors affect and are affected by participation in fisheries could be important to increase benefits from fisheries and to ensure sustainability of management regimes that rely on indirect controls on effort to limit catch.

Drug Design Targeting T-Cell Factor-Driven Epithelial-Mesenchymal Transition as a Therapeutic Strategy for Colorectal Cancer.

Metastasis is the cause of 90% of mortality in cancer patients. For metastatic colorectal cancer (mCRC), the standard-of-care drug therapies only palliate the symptoms but are ineffective, evidenced by a low survival rate of ∼11%. T-cell factor (TCF) transcription is a major driving force in CRC, and we have characterized it to be a master regulator of epithelial-mesenchymal transition (EMT). EMT transforms relatively benign epithelial tumor cells into quasi-mesenchymal or mesenchymal cells that possess cancer stem cell properties, promoting multidrug resistance and metastasis. We have identified topoisomerase IIα (TOP2A) as a DNA-binding factor required for TCF-transcription. Herein, we describe the design, synthesis, biological evaluation, and in vitro and in vivo pharmacokinetic analysis of TOP2A ATP-competitive inhibitors that prevent TCF-transcription and modulate or reverse EMT in mCRC. Unlike TOP2A poisons, ATP-competitive inhibitors do not damage DNA, potentially limiting adverse effects. This work demonstrates a new therapeutic strategy targeting TOP2A for the treatment of mCRC and potentially other types of cancers.

Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations.

Decades of psychological research have been aimed at modeling how people learn features and categories. The empirical validation of these theories is often based on artificial stimuli with simple representations. Recently, deep neural networks have reached or surpassed human accuracy on tasks such as identifying objects in natural images. These networks learn representations of real-world stimuli that can potentially be leveraged to capture psychological representations. We find that state-of-the-art object classification networks provide surprisingly accurate predictions of human similarity judgments for natural images, but they fail to capture some of the structure represented by people. We show that a simple transformation that corrects these discrepancies can be obtained through convex optimization. We use the resulting representations to predict the difficulty of learning novel categories of natural images. Our results extend the scope of psychological experiments and computational modeling by enabling tractable use of large natural stimulus sets.

Status-quo management of marine recreational fisheries undermines angler welfare.

Recreational fisheries can have a significant impact on fish populations and can suffer from the same symptoms of open access as commercial fisheries. However, recreational fisheries receive little attention compared with their commercial counterparts. Regulations designed to allocate scarce fish, such as seasonal closures and bag limits, can result in significant losses of value to anglers. We provide an estimate of these foregone benefits by estimating the potential gains to implementing management reforms of the headboat portion of the recreational red snapper fishery in the US Gulf of Mexico. This fishery has suffered from a regulatory spiral of shortened seasons and lowered bag limits in spite of rebuilding stocks. We gather primary survey data of headboat anglers that elicit trip behavior and their planned number and seasonal distribution of trips under status-quo and alternative management approaches. We use these data to estimate a model of anglers' seasonal trip demand as a function of the ability to retain red snapper, bag limits, and fees. We find that a hypothetical rights-based policy, whereby vessels with secure rights to a portion of annual catch could offer their customers year-round fishing in exchange for lower per-angler retention and increased fees, could raise the average angler's welfare by $139/y. When placed in the global context of recreational fishing, these estimates suggest that status-quo management may deprive anglers of billions of dollars of lost economic value per year.

Bond-orientational order and Frank's constant in two-dimensional colloidal hard spheres.

Recently, the full phase behaviour of 2D colloidal hard spheres was experimentally established, and found to involve a first order liquid to hexatic transition and a continuous hexatic to crystal transition (Thorneywork et al 2017 Phys. Rev. Lett. 118 158001). Here, we expand upon this work by considering the behaviour of the bond-orientational correlation time and Frank's constant in the region of these phase transitions. We also consider the excess entropy, as calculated from the radial distribution functions, for a wide range of area fractions covering the liquid, hexatic and crystal phases. In all cases, the behaviour of these quantities further corroborates the previously reported melting scenario of 2D colloidal hard spheres.

Ecosystem-based management and the wealth of ecosystems.

We merge inclusive wealth theory with ecosystem-based management (EBM) to address two challenges in the science of sustainable management of ecosystems. First, we generalize natural capital theory to approximate realized shadow prices for multiple interacting natural capital stocks (species) making up an ecosystem. These prices enable ecosystem components to be better included in wealth-based sustainability measures. We show that ecosystems are best envisioned as portfolios of assets, where the portfolio's performance depends on the performance of the underlying assets influenced by their interactions. Second, changes in ecosystem wealth provide an attractive headline index for EBM, regardless of whether ecosystem wealth is ultimately included in a broader wealth index. We apply our approach to the Baltic Sea ecosystem, focusing on the interacting community of three commercially important fish species: cod, herring, and sprat. Our results incorporate supporting services embodied in the shadow price of a species through its trophic interactions. Prey fish have greater shadow prices than expected based on market value, and predatory fish have lower shadow prices than expected based on market value. These results are because correctly measured shadow prices reflect interdependence and limits to substitution. We project that ecosystem wealth in the Baltic Sea fishery ecosystem generally increases conditional on the EBM-inspired multispecies maximum sustainable yield management beginning in 2017, whereas continuing the current single-species management generally results in declining wealth.

Biological origins of color categorization.

The biological basis of the commonality in color lexicons across languages has been hotly debated for decades. Prior evidence that infants categorize color could provide support for the hypothesis that color categorization systems are not purely constructed by communication and culture. Here, we investigate the relationship between infants' categorization of color and the commonality across color lexicons, and the potential biological origin of infant color categories. We systematically mapped infants' categorical recognition memory for hue onto a stimulus array used previously to document the color lexicons of 110 nonindustrialized languages. Following familiarization to a given hue, infants' response to a novel hue indicated that their recognition memory parses the hue continuum into red, yellow, green, blue, and purple categories. Infants' categorical distinctions aligned with common distinctions in color lexicons and are organized around hues that are commonly central to lexical categories across languages. The boundaries between infants' categorical distinctions also aligned, relative to the adaptation point, with the cardinal axes that describe the early stages of color representation in retinogeniculate pathways, indicating that infant color categorization may be partly organized by biological mechanisms of color vision. The findings suggest that color categorization in language and thought is partially biologically constrained and have implications for broader debate on how biology, culture, and communication interact in human cognition.

Two-Dimensional Melting of Colloidal Hard Spheres.

We study the melting of quasi-two-dimensional colloidal hard spheres by considering a tilted monolayer of particles in sedimentation-diffusion equilibrium. In particular, we measure the equation of state from the density profiles and use time-dependent and height-resolved correlation functions to identify the liquid, hexatic, and crystal phases. We find that the liquid-hexatic transition is first order and that the hexatic-crystal transition is continuous. Furthermore, we directly measure the width of the liquid-hexatic coexistence gap from the fluctuations of the corresponding interface, and thereby experimentally establish the full phase behavior of hard disks.

Testing the feasibility of a hypothetical whaling-conservation permit market in Norway.

A cap-and-trade system for managing whale harvests represents a potentially useful approach to resolve the current gridlock in international whale management. The establishment of whale permit markets, open to both whalers and conservationists, could reveal the strength of conservation demand, about which little is known. This lack of knowledge makes it difficult to predict the outcome of a hypothetical whale permit market. We developed a bioeconomic model to evaluate the influence of economic uncertainty about demand for whale conservation or harvest. We used simulations over a wide range of parameterizations of whaling and conservation demands to examine the potential ecological consequences of the establishment of a whale permit market in Norwegian waters under bounded (but substantial) economic uncertainty. Uncertainty variables were slope of whaling and conservation demand, participation level of conservationists and their willingness to pay for whale conservation, and functional forms of demand, including linear, quadratic, and log-linear forms. A whale-conservation market had the potential to yield a wide range of conservation and harvest outcomes, the most likely outcomes were those in which conservationists bought all whale permits.

Focal colors across languages are representative members of color categories.

Focal colors, or best examples of color terms, have traditionally been viewed as either the underlying source of cross-language color-naming universals or derived from category boundaries that vary widely across languages. Existing data partially support and partially challenge each of these views. Here, we advance a position that synthesizes aspects of these two traditionally opposed positions and accounts for existing data. We do so by linking this debate to more general principles. We show that best examples of named color categories across 112 languages are well-predicted from category extensions by a statistical model of how representative a sample is of a distribution, independently shown to account for patterns of human inference. This model accounts for both universal tendencies and variation in focal colors across languages. We conclude that categorization in the contested semantic domain of color may be governed by principles that apply more broadly in cognition and that these principles clarify the interplay of universal and language-specific forces in color naming.

Exploring Human Cognition Using Large Image Databases.

Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories.