Structure shapes the representation of a novel category.

Concepts contain rich structures that support flexible semantic cognition. These structures can be characterized by patterns of feature covariation: Certain features tend to cluster in the same items (e.g., feathers, wings, can fly). Existing computational models demonstrate how this kind of structure can be leveraged to slowly learn the distinctions between categories, on developmental timescales. However, it is not clear whether and how we leverage feature structure to quickly learn a novel category. We thus investigated how the internal structure of a new category is first extracted from experience, with the prediction that feature-based structure would have a rapid and broad influence on the learned category representation. Across three experiments, novel categories were designed with patterns of feature associations determined by carefully constructed graph structures, with Modular graphs-exhibiting strong clusters of feature covariation-compared against Random and Lattice graphs. In Experiment 1, a feature inference task using verbal stimuli revealed that Modular structure broadly facilitated category learning. Experiment 2 replicated this effect in visual categories. In Experiment 3, a statistical learning paradigm revealed that this Modular benefit relates to high-level structure rather than pairwise feature associations and persists even when category structure is incidental to the task. A neural network model was readily able to account for these effects, suggesting that correlational feature structure may be encoded within rapidly learned, distributed category representations. These findings constrain theories of category representation and link theories of category learning with structure learning more broadly. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Compassionate Off-Ramps: The Availability of Terminal Master's Degrees in US Medical Schools.

Medical students who underperform or find they are not a "good fit" for medicine have limited options. A terminal master's degree represents an exit alternative that recognizes students' completed coursework and acknowledges their commitment to the medical sciences. Although medical educators have called for the creation of such programs, termed "compassionate off-ramps," the prevalence of degree offerings in US programs is unknown. In the fall of 2020, a survey was sent to Student Affairs Deans at 141 LCME-accredited MD programs; 73 institutions responded (52%). Terminal master's degrees were offered by 19% of respondent institutions (n = 13). While 85% of those without a terminal master's (n = 48) endorsed degree benefits, only 36% (n = 21) had plans to create the degree. This study demonstrates that few US medical schools offer a terminal master's degree, leaving students who exit medicine with high levels of debt without an avenue for a degree to support employment or future academic pursuits. The authors identify implications for students, particularly those who are at a higher risk of failing Step 1, such as students who are underrepresented in medicine, socioeconomically disadvantaged, or who have a disability and are unaccommodated. Potential barriers to terminal master's program creation are identified and mitigating strategies are recommended.

Constructing complex social categories under uncertainty.

Conceptual combination is the act of building complex concepts from simpler ones. Although research has examined how inferences about compound objects (e.g., fuzzy chair) are produced from their constituent concepts, little is known about the combinatorial processes that produce inferences about compound social categories (e.g., Irish musician). Using a computational approach, we investigated the relationship between ratings of 25 nationality-occupation combinations and ratings of their constituent concepts along the attribute dimensions of warmth and competence. We found that people incorporate uncertainty into their perceptions of compound social categories. Further, people are more likely to use a linear combination strategy when they are more certain about the attributes of the constituents and less familiar with the combination. Conversely, when social combinations are more familiar, their judged attributes deviate further from the predictions of a combinatorial model and are shared across participants, suggesting that stereotype-based knowledge plays a central role in the representation of complex social groups. Twenty-five non-human animal combinations (e.g., circus snake) serve as a comparison and were rated on size and ferocity. We found evidence that familiarity has different effects on the strategies used to combine person concepts and animal concepts, pointing to the possible existence of both common and distinct mechanisms for constructing social and non-social categories.

Impact of SARS-CoV-2 on Host Factors Involved in Mental Disorders.

COVID-19, caused by SARS-CoV-2, is a systemic illness due to its multiorgan effects in patients. The disease has a detrimental impact on respiratory and cardiovascular systems. One early symptom of infection is anosmia or lack of smell; this implicates the involvement of the olfactory bulb in COVID-19 disease and provides a route into the central nervous system. However, little is known about how SARS-CoV-2 affects neurological or psychological symptoms. SARS-CoV-2 exploits host receptors that converge on pathways that impact psychological symptoms. This systemic review discusses the ways involved by coronavirus infection and their impact on mental health disorders. We begin by briefly introducing the history of coronaviruses, followed by an overview of the essential proteins to viral entry. Then, we discuss the downstream effects of viral entry on host proteins. Finally, we review the literature on host factors that are known to play critical roles in neuropsychiatric symptoms and mental diseases and discuss how COVID-19 could impact mental health globally. Our review details the host factors and pathways involved in the cellular mechanisms, such as systemic inflammation, that play a significant role in the development of neuropsychological symptoms stemming from COVID-19 infection.

Feature Uncertainty Predicts Behavioral and Neural Responses to Combined Concepts.

The cognitive and neural structure of conceptual knowledge affects how concepts combine in language and thought. Examining the principles by which individual concepts (e.g., diamond, baseball) combine into more complex phrases (e.g., "baseball diamond") can illuminate not only how the brain combines concepts but also the key ingredients of conceptual structure. Here we specifically tested the role of feature uncertainty in the modulation of conceptual brightness evoked by adjective-noun combinations (e.g., "dark diamond") in male and female human subjects. We collected explicit ratings of conceptual brightness for 45 noun concepts and their "dark" and "light" combinations, resulting in a measure reflecting the degree of conceptual brightness modulation in each noun concept. Feature uncertainty was captured in an entropy measure, as well as in a predictive Bayesian model of feature modulation. We found that feature uncertainty (i.e., entropy) and the Bayesian model were both strong predictors of these behavioral effects. Using fMRI, we observed the neural responses evoked by the concepts and combinations in a priori ROIs. Feature uncertainty predicted univariate responses in left inferior frontal gyrus, and multivariate responses in left anterior temporal lobe were predicted by degree of conceptual brightness modulation. These findings suggest that feature uncertainty is a key ingredient of conceptual structure, and inform cognitive neuroscience theories of conceptual combination by highlighting the role of left inferior frontal gyrus and left anterior temporal lobe in the process of flexible feature modulation during comprehension of complex language.SIGNIFICANCE STATEMENT The meaning of a word depends on the words surrounding it. The challenge of understanding how flexible meaning emerges in language can be simplified by studying adjective-noun phrases. We tested whether the uncertainty of a feature (i.e., brightness) in a given noun concept (e.g., diamond) influences how the adjective and noun concepts combine. We analyzed feature uncertainty using two probabilistic measures, and found that feature uncertainty predicted people's explicit interpretations of adjective-noun phrases (e.g., "dark diamond"). Using fMRI, we found that combined concepts evoked responses in left inferior frontal gyrus and left anterior temporal lobe that related to our measures of feature modulation and uncertainty. These findings reveal the cognitive and neural processes supporting conceptual combination and complex language use.

Semantic Search as Pattern Completion across a Concept.

What role does the hippocampus play in semantic memory? In a recent paper, Cutler et al. use a vector space model of semantics to characterize semantic search deficits in hippocampal amnesia. We relate their findings to properties of the hippocampal neural code and to controversies regarding hippocampal contributions to cognition.

Implementing a concept network model.

The same concept can mean different things or be instantiated in different forms, depending on context, suggesting a degree of flexibility within the conceptual system. We propose that a feature-based network model can be used to capture and predict this flexibility. We modeled individual concepts (e.g., BANANA, BOTTLE) as graph-theoretical networks, in which properties (e.g., YELLOW, SWEET) were represented as nodes and their associations as edges. In this framework, networks capture within-concept statistics that reflect how properties relate to one another across instances of a concept. We extracted formal measures of these networks that capture different aspects of network structure, and explored whether a concept's network structure relates to its flexibility of use. To do so, we compared network measures to a text-based measure of semantic diversity, as well as to empirical data from a figurative-language task and an alternative-uses task. We found that network-based measures were predictive of the text-based and empirical measures of flexible concept use, highlighting the ability of this approach to formally capture relevant characteristics of conceptual structure. Conceptual flexibility is a fundamental attribute of the cognitive and semantic systems, and in this proof of concept we reveal that variations in concept representation and use can be formally understood in terms of the informational content and topology of concept networks.

Downregulation of CD3ζ in NK Cells from Systemic Lupus Erythematosus Patients Confers a Proinflammatory Phenotype.

Cytotoxic function and cytokine profile of NK cells are compromised in patients with systemic lupus erythematosus (SLE). CD3ζ, an important molecule for NK cell activation, is downregulated in SLE T cells and contributes to their altered function. However, little is known about the role of CD3ζ in SLE NK cells. We studied CD3ζ levels and its contribution to cytotoxic, degranulation, and cytokine production capacity of NK cells from patients with SLE. Furthermore, we studied the human NK cell line, NKL, in which manipulation of CD3ζ levels was achieved using small interfering RNA and NK cells from Rag2 mice deficient in CD3ζ. We found reduced CD3ζ expression in NK cells from SLE patients independent of disease activity. Downregulation of CD3ζ expression in NK cells is mediated, at least in part, by Caspase 3, the activity of which is higher in NK cells from patients with SLE compared with NK cells from healthy donors. CD3ζ levels correlated inversely with natural cytotoxicity and the percentage of cells capable of producing the proinflammatory cytokines IFN-γ and TNF. In contrast, CD3ζ levels showed a direct correlation with levels of Ab-dependent cellular cytotoxicity. Experiments performed in CD3ζ-silenced NKL and CD3ζ-deficient NK cells from Rag2 mice confirmed the dependence of NK cell function on CD3ζ levels. Our results demonstrate a differential role for CD3ζ in natural cytotoxicity and Ab-dependent cellular cytotoxicity. We conclude that downregulated CD3ζ confers a proinflammatory phenotype to SLE NK cells and contributes to their altered function in patients with SLE.

Finding features, figuratively.

Object concepts refer to unique clusters of properties that can be selectively activated or inhibited depending on what information is currently relevant. This conceptual "stretching" enables limitless new meanings to be generated, and figurative language provides a useful framework in which to study this conceptual flexibility. Here we probe the cognitive and neural mechanisms underlying the comprehension of novel metaphors as a means of understanding the conceptual flexibility inherent to language processing more generally. We show that novel metaphor comprehension involves the activation or inhibition of conceptual properties that are either relevant or irrelevant to the metaphor, and that left inferior frontal gyrus is recruited in this process, supporting a role for this region in the fine-tuning of conceptual meaning. Our results are consistent with a flexible, compositional account of conceptual structure in which semantic control mechanisms operate over conceptual properties during figurative language comprehension in order to create context-dependent meaning.

Immunotherapy with single agent nivolumab for advanced leiomyosarcoma of the uterus: Results of a phase 2 study.

BACKGROUND: Immunotherapy has changed the therapeutic landscape in oncology. Advanced uterine leiomyosarcoma (ULMS) remains an incurable disease in most cases, and despite new drug approvals, improvements in overall survival have been modest at best. The goal of this study was to evaluate programmed-death 1 (PD-1) inhibition with nivolumab in this patient population. METHODS: This single-center phase 2 trial completed enrollment between May and October 2015. Patients received 3 mg/kg of intravenous nivolumab on day 1 of each 2-week cycle until disease progression or unacceptable toxicity. The primary endpoint was objective response rate. We assessed PD-1, PD-ligand 1 (PD-L1), and PD-L2 expression in archival tumor samples and variations in immune-phenotyping of circulating immune cells during treatment. RESULTS: Twelve patients were enrolled in the first stage of the 2-stage design. A median of 5 (range, 2-6) 2-week cycles of nivolumab were administered. Of the 12 patients, none responded to treatment. The overall median progression-free survival was 1.8 months (95% confidence interval, 0.8-unknown). The study did not open the second stage due to lack of benefit as defined by the statistical plan. Archival samples were available for 83% of patients. PD-1 (>3% of cells), PD-L1, and PD-L2 (>5% and >10% of tumor cells, respectively) expression were observed in 20%, 20%, and 90% of samples, respectively. No significant differences were observed between pre- and posttreatment cell phenotypes. CONCLUSION: Single-agent nivolumab did not demonstrate a benefit in this cohort of previously treated advanced ULMS patients. Further biomarker-driven approaches and studies evaluating combined immune checkpoint-modulators should be considered. Cancer 2017;123:3285-90. © 2017 American Cancer Society.

Computational methods to design cyclic peptides.

Cyclic peptides (CPs) are promising modulators of protein-protein interactions (PPIs), but their application remains challenging. It is currently difficult to predict the structures and bioavailability of CPs. The ability to design CPs using computer modeling would greatly facilitate the development of CPs as potent PPI modulators for fundamental studies and as potential therapeutics. Herein, we describe computational methods to generate CP libraries for virtual screening, as well as current efforts to accurately predict the conformations adopted by CPs. These advances are making it possible to envision robust computational design of active CPs. However, unique properties of CPs pose significant challenges associated with sampling CP conformational space and accurately describing CP energetics. These major obstacles to structure prediction likely must be solved before robust design of active CPs can be reliably achieved.

A meta-analysis of fMRI decoding: Quantifying influences on human visual population codes.

Information in the human visual system is encoded in the activity of distributed populations of neurons, which in turn is reflected in functional magnetic resonance imaging (fMRI) data. Over the last fifteen years, activity patterns underlying a variety of perceptual features and objects have been decoded from the brains of participants in fMRI scans. Through a novel multi-study meta-analysis, we have analyzed and modeled relations between decoding strength in the visual ventral stream, and stimulus and methodological variables that differ across studies. We report findings that suggest: (i) several organizational principles of the ventral stream, including a gradient of pattern granulation and an increasing abstraction of neural representations as one proceeds anteriorly; (ii) how methodological choices affect decoding strength. The data also show that studies with stronger decoding performance tend to be reported in higher-impact journals, by authors with a higher h-index. As well as revealing principles of regional processing, our results and approach can help investigators select from the thousands of design and analysis options in an empirical manner, to optimize future studies of fMRI decoding.

Competition between Mutually Exclusive Object States in Event Comprehension.

Successful language comprehension requires one to correctly match symbols in an utterance to referents in the world, but the rampant ambiguity present in that mapping poses a challenge. Sometimes the ambiguity lies in which of two (or more) types of things in the world are under discussion (i.e., lexical ambiguity); however, even a word with a single sense can have an ambiguous referent. This ambiguity occurs when an object can exist in multiple states. Here, we consider two cases in which the presence of multiple object states may render a single-sense word ambiguous. In the first case, one must disambiguate between two states of a single object token in a short discourse. In the second case, the discourse establishes two different tokens of the object category. Both cases involve multiple object states: These states are mutually exclusive in the first case, whereas in the second case, these states can logically exist at the same time. We use fMRI to contrast same-token and different-token discourses, using responses in left posterior ventrolateral prefrontal cortex (pVLPFC) as an indicator of conflict. Because the left pVLPFC is sensitive to competition between multiple, incompatible representations, we predicted that state ambiguity should engender conflict only when those states are mutually exclusive. Indeed, we find evidence of conflict in same-token, but not different-token, discourses. Our data support a theory of left pVLPFC function in which general conflict resolution mechanisms are engaged to select between multiple incompatible representations that arise in many kinds of ambiguity present in language.

A cortical network for the encoding of object change.

Understanding events often requires recognizing unique stimuli as alternative, mutually exclusive states of the same persisting object. Using fMRI, we examined the neural mechanisms underlying the representation of object states and object-state changes. We found that subjective ratings of visual dissimilarity between a depicted object and an unseen alternative state of that object predicted the corresponding multivoxel pattern dissimilarity in early visual cortex during an imagery task, while late visual cortex patterns tracked dissimilarity among distinct objects. Early visual cortex pattern dissimilarity for object states in turn predicted the level of activation in an area of left posterior ventrolateral prefrontal cortex (pVLPFC) most responsive to conflict in a separate Stroop color-word interference task, and an area of left ventral posterior parietal cortex (vPPC) implicated in the relational binding of semantic features. We suggest that when visualizing object states, representational content instantiated across early and late visual cortex is modulated by processes in left pVLPFC and left vPPC that support selection and binding, and ultimately event comprehension.

Efficacy and safety of regorafenib in patients with metastatic and/or unresectable GI stromal tumor after failure of imatinib and sunitinib: a multicenter phase II trial.

PURPOSE: Metastatic GI stromal tumor (GIST) is a life-threatening disease with no therapy of proven efficacy after failure of imatinib and sunitinib. Regorafenib is a structurally unique inhibitor of multiple cancer-associated kinases, including KIT and platelet-derived growth factor receptor (PDGFR), with broad-spectrum anticancer activity in preclinical and early-phase trials. Because KIT and PDGFR-α remain drivers of GIST after resistance to imatinib and sunitinib, we performed a multicenter single-stage phase II trial of regorafenib in patients with advanced GIST after failure of at least imatinib and sunitinib. PATIENTS AND METHODS: Patients received regorafenib orally, 160 mg daily, on days 1 to 21 of a 28-day cycle. Disease assessment was performed every two cycles per RECIST 1.1. Primary end point was clinical benefit rate (CBR), defined as objective responses (ie, complete or partial response [PR] as well as stable disease [SD] ≥ 16 weeks). Serial tumor biopsies were obtained from consenting patients whenever possible. RESULTS: From February to December 2010, 34 patients were enrolled at four US centers. As of July 28, 2011, 33 patients had received at least two cycles of regorafenib (range, two to 17 cycles). CBR was 79% (95% CI, 61% to 91%). Four patients achieved PR, and 22 exhibited SD ≥ 16 weeks. Median progression-free survival was 10.0 months. The most common grade 3 toxicities were hypertension and hand-foot-skin reaction. CONCLUSION: Regorafenib has significant activity in patients with advanced GIST after failure of both imatinib and sunitinib. A phase III trial of regorafenib versus placebo is ongoing to define more fully the safety and efficacy of regorafenib in this setting.

The base component of 3'-azido-2',3'-dideoxynucleosides influences resistance mutations selected in HIV-1 reverse transcriptase.

We recently reported that HIV-1 resistant to 3'-azido-3'-deoxythymidine (AZT) is not cross-resistant to 3'-azido-2',3'-dideoxypurines. This finding suggested that the nucleoside base is a major determinant of HIV-1 resistance to nucleoside analogs. To further explore this hypothesis, we conducted in vitro selection experiments by serial passage of HIV-1(LAI) in MT-2 cells in increasing concentrations of 3'-azido-2',3'-dideoxyguanosine (3'-azido-ddG), 3'-azido-2',3'-dideoxycytidine (3'-azido-ddC), or 3'-azido-2',3'-dideoxyadenosine (3'-azido-ddA). 3'-Azido-ddG selected for virus that was 5.3-fold resistant to 3'-azido-ddG compared to wild-type HIV-1(LAI) passaged in the absence of drug. Population sequencing of the entire reverse transcriptase (RT) gene identified L74V, F77L, and L214F mutations in the polymerase domain and K476N and V518I mutations in the RNase H domain. However, when introduced into HIV-1 by site-directed mutagenesis, these 5 mutations only conferred ∼2.0-fold resistance. Single-genome sequencing analyses of the selected virus revealed a complex population of mutants that all contained L74V and L214F linked to other mutations, including ones not identified during population sequencing. Recombinant HIV-1 clones containing RT derived from single sequences exhibited 3.2- to 4.0-fold 3'-azido-ddG resistance. In contrast to 3'-azido-ddG, 3'-azido-ddC selected for the V75I mutation in HIV-1 RT that conferred 5.9-fold resistance, compared to the wild-type virus. Interestingly, we were unable to select HIV-1 that was resistant to 3'-azido-ddA, even at concentrations of 3'-azido-ddA that yielded high intracellular levels of 3'-azido-ddA-5'-triphosphate. Taken together, these findings show that the nucleoside base is a major determinant of HIV-1 resistance mechanisms that can be exploited in the design of novel nucleoside RT inhibitors.

Synthesis, antiviral activity, cytotoxicity and cellular pharmacology of l-3'-azido-2',3'-dideoxypurine nucleosides.

Microwave-assisted optimized transglycosylation reactions were used to prepare eleven modified l-3'-azido-2',3'-dideoxypurine nucleosides. These l-nucleoside analogs were evaluated against HIV and hepatitis B virus. The l-3'-azido-2',3'-dideoxypurines nucleosides were metabolized to nucleoside 5'-triphosphates in primary human lymphocytes, but exhibited weak or no antiviral activity against HIV-1. The nucleosides were also inactive against HBV in HepG2 cells. Pre-steady state kinetic experiments demonstrated that the l-3'-azido-2',3'-dideoxypurine triphosphates could be incorporated by purified HIV-1 reverse transcriptase, although their catalytic efficiency (k(pol)/K(d)) of incorporation was low. Interestingly, a phosphoramidate prodrug of l-3'-azido-2',3'-dideoxyadenosine exhibited anti-HIV-1 activity without significant toxicity.

Synthesis and evaluation of 3'-azido-2',3'-dideoxypurine nucleosides as inhibitors of human immunodeficiency virus.

Based on the promising drug resistance profile and potent anti-HIV activity of beta-d-3'-azido-2',3'-dideoxyguanosine, a series of purine modified nucleosides were synthesized by a chemical transglycosylation reaction and evaluated for their antiviral activity, cytotoxicity, and intracellular metabolism. Among the synthesized compounds, several show potent and selective anti-HIV activity in primary lymphocytes.