Unsupervised word embeddings capture latent knowledge from materials science literature.

The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the materials research community has come from structured property databases1,2, which encompass only a small fraction of the knowledge present in the research literature. Beyond property values, publications contain valuable knowledge regarding the connections and relationships between data items as interpreted by the authors. To improve the identification and use of this knowledge, several studies have focused on the retrieval of information from scientific literature using supervised natural language processing3-10, which requires large hand-labelled datasets for training. Here we show that materials science knowledge present in the published literature can be efficiently encoded as information-dense word embeddings11-13 (vector representations of words) without human labelling or supervision. Without any explicit insertion of chemical knowledge, these embeddings capture complex materials science concepts such as the underlying structure of the periodic table and structure-property relationships in materials. Furthermore, we demonstrate that an unsupervised method can recommend materials for functional applications several years before their discovery. This suggests that latent knowledge regarding future discoveries is to a large extent embedded in past publications. Our findings highlight the possibility of extracting knowledge and relationships from the massive body of scientific literature in a collective manner, and point towards a generalized approach to the mining of scientific literature

Structured information extraction from complex scientific text with fine-tuned large language models

Intelligently extracting and linking complex scientific information from unstructured text is a challenging endeavor particularly for those inexperienced with natural language processing. Here, we present a simple sequence-to-sequence approach to joint named entity recognition and relation extraction for complex hierarchical information in scientific text. The approach leverages a pre-trained large language model (LLM), GPT-3, that is fine-tuned on approximately 500 pairs of prompts (inputs) and completions (outputs). Information is extracted either from single sentences or across sentences in abstracts/passages, and the output can be returned as simple English sentences or a more structured format, such as a list of JSON objects. We demonstrate that LLMs trained in this way are capable of accurately extracting useful records of complex scientific knowledge for three representative tasks in materials chemistry: linking dopants with their host materials, cataloging metal-organic frameworks, and general chemistry/phase/morphology/application information extraction. This approach represents a simple, accessible, and highly-flexible route to obtaining large databases of structured knowledge extracted from unstructured text. An online demo is available at http://www.matscholar.com/info-extraction

Should We Trust our Judgments about the Proficiency of Motivational Interviewing Counselors?A Glimpse at the Impact of Low Inter-rater Reliability

Standardized rating systems are often used to evaluate the proficiency of Motivational Interviewing (MI) counselors. The published inter-rater reliability (degree of coder agreement)  in many studies using these instruments has varied a great deal; some studies report MI proficiency scores that have only fair inter-rater reliability, and others report scores with excellent reliability. How much can we to trust the scores with fair versus excellent reliability? Using a Monte Carlo statistical simulation, we compared the impact of fair (0.50) versus excellent (0.90) reliability on the error rates of falsely judging a given counselor as MI proficient or not proficient. We found that improving the inter-rater reliability of any given score from 0.5 to 0.9 would cause a marked reduction in proficiency judgment errors, a reduction that in some MI evaluation situations would be critical. We discuss some practical tradeoffs inherent in various MI evaluation situations, and offer suggestions for applying findings from formal MI research to problems faced by real-world MI evaluators, to help them minimize the MI proficiency judgment errors bearing the greatest cost

Investigating Rurality as a Risk Factor for State and Trait Hopelessness in Hospitalized Patients with Ischemic Heart Disease

Background Rurality and hopelessness are each associated with increased mortality in adults with ischemic heart disease (IHD), yet there is no known research examining rurality as a risk factor for hopelessness in patients with IHD. This study evaluated rurality as a risk factor for state and trait hopelessness in adults hospitalized with IHD in samples drawn from the Great Lakes and Great Plains regions of the United States. Methods and Results A descriptive cross‐sectional design was used. Data were collected from 628 patients hospitalized for IHD in the Great Lakes (n=516) and Great Plains (n=112). Rural–Urban Commuting Area codes were used to stratify study participants by level of rurality. Levels of state hopelessness (measured by the State‐Trait Hopelessness Scale) were higher in rural patients (58.8% versus 48.8%; odds ratio [OR], 1.50; 95% CI, 1.03–2.18), a difference that remained statistically significant after adjusting for demographics, depression severity (measured by the Patient Health Questionnaire–8), and physical functioning (measured by the Duke Activity Status Index; OR, 1.59; 95% CI, 1.06–2.40; P=0.026). There was evidence of an interaction between marital status and rurality on state hopelessness after accounting for covariates (P=0.02). Nonmarried individuals had an increased prevalence of state hopelessness (nonmarried 72.0% versus married 52.0%) in rural areas (P=0.03). Conclusions Rural patients with IHD, particularly those who are nonmarried, may be at higher risk for state hopelessness compared with patients with IHD living in urban settings. Understanding rurality differences is important in identifying subgroups most at risk for hopelessness

How Women Living With HIV React and Respond to Learning About Canadian Law That Criminalises HIV Non-disclosure: ‘How Do You Prove That You Told?’

The Women, ART and the Criminalization of HIV Study is a qualitative, arts-based research study focusing on the impact of the HIV non-disclosure law on women living with HIV in Canada. The federal law requires people living with HIV to disclose their HIV-positive status to sexual partners before engaging in sexual activities that pose what the Supreme Court of Canada called a ‘realistic possibility of transmission’. Drawing on findings from seven education and discussion sessions with 48 women living with HIV regarding HIV non-disclosure laws in Canada, this paper highlights the ways in which women living with HIV respond to learning about the criminalisation of HIV non-disclosure. The most common emergent themes included: the way the law reproduces social and legal injustices; gendered experiences of intimate injustice; and the relationship between disclosure and violence against women living with HIV. These discussions illuminate the troubling consequences inherent in a law that is antithetical to the science of HIV transmission risk, and that fails to acknowledge the multiple barriers to HIV disclosure that women living with HIV experience. Women’s experiences also highlight the various ways the law contributes to their experiences of sexism, racism and other forms of marginalisation in society

Meisosomes, folded membrane microdomains between the apical extracellular matrix and epidermis

Apical extracellular matrices (aECMs) form a physical barrier to the environment. In Caenorhabditis elegans, the epidermal aECM, the cuticle, is composed mainly of different types of collagen, associated in circumferential ridges separated by furrows. Here, we show that in mutants lacking furrows, the normal intimate connection between the epidermis and the cuticle is lost, specifically at the lateral epidermis, where, in contrast to the dorsal and ventral epidermis, there are no hemidesmosomes. At the ultrastructural level, there is a profound alteration of structures that we term 'meisosomes,' in reference to eisosomes in yeast. We show that meisosomes are composed of stacked parallel folds of the epidermal plasma membrane, alternately filled with cuticle. We propose that just as hemidesmosomes connect the dorsal and ventral epidermis, above the muscles, to the cuticle, meisosomes connect the lateral epidermis to it. Moreover, furrow mutants present marked modifications of the biomechanical properties of their skin and exhibit a constitutive damage response in the epidermis. As meisosomes co-localise to macrodomains enriched in phosphatidylinositol (4,5) bisphosphate, they could conceivably act, like eisosomes, as signalling platforms, to relay tensile information from the aECM to the underlying epidermis, as part of an integrated stress response to damage

Dopamine Genetic Risk Score Predicts Depressive Symptoms in Healthy Adults and Adults with Depression

Background: Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression. Methods: Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3). Results: In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = −0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = −0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = −0.86, p = 0.15). Conclusions: Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

An Open, Large-Scale, Collaborative Effort to Estimate the Reproducibility of Psychological Science

Reproducibility is a defining feature of science. However, because of strong incentives for innovation and weak incentives for confirmation, direct replication is rarely practiced or published. The Reproducibility Project is an open, large-scale, collaborative effort to systematically examine the rate and predictors of reproducibility in psychological science. So far, 72 volunteer researchers from 41 institutions have organized to openly and transparently replicate studies published in three prominent psychological journals in 2008. Multiple methods will be used to evaluate the findings, calculate an empirical rate of replication, and investigate factors that predict reproducibility. Whatever the result, a better understanding of reproducibility will ultimately improve confidence in scientific methodology and findings