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\"This book features the stories and voices of parents, young people, community organizers and educators describing how they are fighting systemic racism in schools by building a new educational justice movement committed to community-based, high quality, humane and empowering education for all young people\"-- Provided by publisher.

Practical components for three-dimensional molecular nanofabrication must be simple to produce, stereopure, rigid, and adaptable. We report a family of DNA tetrahedra, less than 10 nanometers on a side, that can self-assemble in seconds with near-quantitative yield of one diastereomer. They can be connected by programmable DNA linkers. Their triangulated architecture confers structural stability; by compressing a DNA tetrahedron with an atomic force microscope, we have measured the axial compressibility of DNA and observed the buckling of the double helix under high loads.

The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed.

Trust is an essential element in engagement with data sharing and underpins efforts to use data to combat health inequalities. However, research into public trust in data sharing and health care settings may rely on oversimplified notions of what trust entails. How trust relationships manifest in this context has not been widely explored. We aimed to establish the primary reasons for the placement of trust and whether these reasons vary by demographics and domain. We also explored the utility of a composite trust score as a predictor for use of technology in the health sphere. We conducted a cross-sectional survey using Qualtrics to explore the challenges associated with trust and judgments of trustworthiness in the context of the use of technology to collect health-related data. Participants were recruited using a marketing firm, Dynata, in July 2022 and were UK census matched for population representation. A total of 99.33% (1192/1200) of the target UK-based participants aged ≥18 years (n=605, 50.8% female; n=587, 49.2% male) were asked to rate their level of trust in others generally and in specific entities on an ordinal scale (1-5). We constructed Bayesian cumulative logit models and hierarchical models to evaluate whether demographic characteristics predicted reasons for domain-specific or general trust. We created a composite trust score across health data domains (range 1-15) and developed models to determine whether this score predicted the likelihood of having used or using a device to track health or well-being. We report all credible intervals at 95%. General trust responses were bimodally distributed, with the most frequently chosen answers being \"usually not\" and \"usually.\" A cumulative logit model suggested that divorced status predicted choosing \"almost always not\" or \"usually not\" (β estimate=-0.71, 95% CI -1.17 to -0.28). \"They are reliable and keep their promises\" and \"They behave responsibly\" were the most chosen reasons for placing trust. Trust in family, the National Health Service, and technology companies was primarily driven by familiarity, perceived responsibility, and openness and responsible behavior, respectively. A Bayesian hierarchical model suggested that higher general trust was a strong predictor of a higher composite trust score (β estimate=1.93, 95% CI 1.26-2.59). A higher composite trust score also inversely correlated with the likelihood of having used a device to track health or well-being, whereas higher trust in technology companies and the National Health Service predicted a willingness to use such devices. Unlike with prior works evaluating trust and trustworthiness, we demonstrate that trust must be understood as context-specific and relational. Policymakers should note that self-reported global trust may not correlate with specific health- and technology-related behaviors and, consequently, that domain-specific measurements of trust are essential in health policy work.

Mimicry is an essential strategy for exploiting competitors in competitive co-evolutionary relationships. Protection against mimicry may, furthermore, be a driving force in human linguistic diversity: the potential harm caused by failing to detect mimicked group-identity signals may select for high sensitivity to mimicry of honest group members. Here we describe the results of five agent-based models that simulate multi-generational interactions between two groups of individuals: original members of a group with an honest identity signal, and members of an outsider group who mimic that signal, aiming to pass as members of the in-group. The models correspond to the Biblical story of Shibboleth, where a tribe in conflict with another determines tribe affiliation by asking individuals to pronounce the word, ‘Shibboleth.’ In the story, failure to reproduce the word phonetically resulted in death. Here, we run five different versions of a ‘Shibboleth’ model: a first, simple version, which evaluates whether a composite variable of mimicry quality and detection quality is a superior predictor to the model’s outcome than is cost of detection. The models thereafter evaluate variations on the simple model, incorporating group-level behaviours such as altruistic punishment. Our results suggest that group members’ sensitivity to mimicry of the Shibboleth-signal is a better predictor of whether any signal of group identity goes into fixation in the overall population than is the cost of mimicry detection. Thus, the likelihood of being detected as a mimic may be more important than the costs imposed on mimics who are detected. This suggests that theoretical models in biology should place greater emphasis on the likelihood of detection, which does not explicitly entail costs, rather than on the costs to individuals who are detected. From a language learning perspective, the results suggest that admission to group membership through linguistic signals is powered by the ability to imitate and evade detection as an outsider by existing group members.

Mood lability is a concept widely used. However, data on its prevalence and morbid associations are scarce. We sought to establish the occurrence and importance of mood lability in a large community sample of children and adolescents by testing a priori hypotheses. Cross-sectional data were taken from a national mental health survey including 5326 subjects aged 8-19 years in the UK. The outcomes were prevalence and characteristics of mood lability and its associations with psychopathology and overall impairment. Mood lability occurred in more than 5% of the population of children and adolescents, both by parent and self-report. Mood lability was strongly associated with a wide range of psychopathology and was linked to significant impairment even in the absence of psychiatric disorders. Mood lability was particularly strongly associated with co-morbidity between internalizing and externalizing disorders, even when adjusting for the association with individual disorders. The pattern of results did not change after excluding youth with bipolar disorder or with episodes of elated mood. Clinically significant mood lability is relatively common in the community. Our findings indicate that mood lability is not a mere consequence of other psychopathology in that it is associated with significant impairment even in the absence of psychiatric diagnoses. Moreover, the pattern of association of mood lability with co-morbidity suggests that it could be a risk factor shared by both internalizing and externalizing disorders. Our data point to the need for greater awareness of mood lability and its implications for treatment.

The location and trajectory of seizure activity is of great importance, yet our ability to map such activity remains primitive. Recently, the development of multi-electrode arrays for use in humans has provided new levels of temporal and spatial resolution for recording seizures. Here, we show that there is a sharp delineation between areas showing intense, hypersynchronous firing indicative of recruitment to the seizure, and adjacent territories where there is only low-level, unstructured firing. Thus, there is a core territory of recruited neurons and a surrounding 'ictal penumbra'. The defining feature of the 'ictal penumbra' is the contrast between the large amplitude EEG signals and the low-level firing there. Our human recordings bear striking similarities with animal studies of an inhibitory restraint, indicating that they can be readily understood in terms of this mechanism. These findings have important implications for how we localize seizure activity and map its spread. Seizure activity in the brain is characterized by the recruitment of cortical neuronal activity. Schevon and colleagues study seizure activity in human subjects and find that the recruitment of neurons is hypersynchronous and that there is an intrinsic restraint on the propagation of this activity.