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\"This volume presents research findings on the effects of early childhood propgrams and practices in the first decade of life and their implications for policy development and reform. The contributors are leading researchers in the multidisciplinary field of human development and in early childhood learning. Effects and cost-effectiveness of the most influential model, state, and federallly-funded programs, policies, and practices are described. These include Head Start, Early Head Start, the WIC Nutrition program, Nurse Family Partnership, and Perry Preschool as well as school reform strategies. The volume provides a unique multidisciplinary approach for understanding and improving interventions, practices, and policies to optimally foster human captial over the life course\"-- Provided by publisher.

Workplace inhalational hazards remain common worldwide, even though they are ameliorable. Previous American Thoracic Society documents have assessed the contribution of workplace exposures to asthma and chronic obstructive pulmonary disease on a population level, but not to other chronic respiratory diseases. The goal of this document is to report an in-depth literature review and data synthesis of the occupational contribution to the burden of the major nonmalignant respiratory diseases, including airway diseases; interstitial fibrosis; hypersensitivity pneumonitis; other noninfectious granulomatous lung diseases, including sarcoidosis; and selected respiratory infections. Relevant literature was identified for each respiratory condition. The occupational population attributable fraction (PAF) was estimated for those conditions for which there were sufficient population-based studies to allow pooled estimates. For the other conditions, the occupational burden of disease was estimated on the basis of attribution in case series, incidence rate ratios, or attributable fraction within an exposed group. Workplace exposures contribute substantially to the burden of multiple chronic respiratory diseases, including asthma (PAF, 16%); chronic obstructive pulmonary disease (PAF, 14%); chronic bronchitis (PAF, 13%); idiopathic pulmonary fibrosis (PAF, 26%); hypersensitivity pneumonitis (occupational burden, 19%); other granulomatous diseases, including sarcoidosis (occupational burden, 30%); pulmonary alveolar proteinosis (occupational burden, 29%); tuberculosis (occupational burden, 2.3% in silica-exposed workers and 1% in healthcare workers); and community-acquired pneumonia in working-age adults (PAF, 10%). Workplace exposures contribute to the burden of disease across a range of nonmalignant lung conditions in adults (in addition to the 100% burden for the classic occupational pneumoconioses). This burden has important clinical, research, and policy implications. There is a pressing need to improve clinical recognition and public health awareness of the contribution of occupational factors across a range of nonmalignant respiratory diseases.

Artificial intelligence (AI) is being rolled out across the UK National Health Service (NHS) to improve efficiency; yet, its carbon footprint is largely invisible within mandatory Green Plan reporting. This work shows where NHS carbon reporting omits AI-related emissions and proposes feasible accounting and procurement measures that allow trusts to assess whether AI adoption advances or undermines net zero. A review of NHS sustainability guidance, the Department for Environment, Food & Rural Affairs conversion factors, and recent evidence on AI energy use shows that current Scopes 1-3 accounting omits substantial emissions at 3 points. First, a lack of granularity provides averages that can obscure the extreme energy intensity of certain AI workloads. Second, life-cycle emissions from specialized hardware (eg, graphics processing units) are often excluded unless trusts own the equipment, ignoring upstream manufacturing impacts. Third, widespread use of unprocured generative AI tools is unmeasured; extrapolating general practice survey data suggests that ChatGPT queries alone could release ≈ 349t CO₂e per year in primary care. To close these gaps, we propose three potential ways to help reduce these reporting gaps: (1) AI-specific carbon disclosure clauses in vendor contracts, (2) inclusion of cradle-to-grave emission factors for AI hardware in Scope 3 reporting, and (3) lightweight monitoring of external AI traffic (while recognizing potential ethical issues with this). Implementing these measures would give health care leaders a more accurate baseline against which to judge whether AI supports or undermines the NHS net-zero target.

Dopamine-dependent long-term plasticity is believed to be a cellular mechanism underlying reinforcement learning. In response to reward and reward-predicting cues, phasic dopamine activity potentiates the efficacy of corticostriatal synapses on spiny projection neurons (SPNs). Since phasic dopamine activity also encodes other behavioural variables, it is unclear how postsynaptic neurons identify which dopamine event is to induce long-term plasticity. Additionally, it is unknown how phasic dopamine released from arborised axons can potentiate targeted striatal synapses through volume transmission. To examine these questions we manipulated striatal cholinergic interneurons (ChIs) and dopamine neurons independently in two distinct in vivo paradigms. We report that long-term potentiation (LTP) at corticostriatal synapses with SPNs is dependent on the coincidence of pauses in ChIs and phasic dopamine activation, critically accompanied by SPN depolarisation. Thus, the ChI pause defines the time window for phasic dopamine to induce plasticity, while depolarisation of SPNs constrains the synapses eligible for plasticity. It remains unclear how corticostriatal synapses utilize reward prediction error signaling in order to reinforce reward-related behaviors. Here, the authors show that potentiation of corticostriatal synapses requires phasic dopamine activation, pauses in striatal cholinergic interneuron firing, and depolarization of spiny projection neurons.

Linking Willa Cather to \"the modern\" or \"modernism\" still seems an eccentric proposition to some people. Born in 1873, Cather felt tied to the past when she witnessed the emergence of twentieth-century modern culture, and the clean, classical sentences in her fiction contrast starkly with the radically experimental prose of prominent modernists. Nevertheless, her representations of place in the modern world reveal Cather as a writer able to imagine a startling range of different cultures. Divided into two sections, the essays in Cather Studies, Volume 9 examine Willa Cather as an author with an innovative receptivity to modern cultures and a powerful affinity with the visual and musical arts. From the interplay between modern and antimodern in her representations of native culture to the music and visual arts that animated her imagination, the essays are unified by an understanding of Cather as a writer of transition whose fiction meditates on the cultural movement from Victorianism into the twentieth century.

The population prevalence of multimorbidity (the existence of at least 2 or more long-term conditions [LTCs] in an individual) is increasing among young adults, particularly in minority ethnic groups and individuals living in socioeconomically deprived areas. In this study, we applied a data-driven approach to identify clusters of individuals who had an early onset multimorbidity in an ethnically and socioeconomically diverse population. We identified associations between clusters and a range of health outcomes. Using linked primary and secondary care data from the Clinical Practice Research Datalink GOLD (CPRD GOLD), we conducted a cross-sectional study of 837,869 individuals with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) registered with an English general practice between 2010 and 2020. The study population included 777,906 people of White ethnicity (93%), 33,915 people of South Asian ethnicity (4%), and 26,048 people of Black African/Caribbean ethnicity (3%). A total of 204 LTCs were considered. Latent class analysis stratified by ethnicity identified 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity was more common among South Asian (59%, 33,915) and Black (56% 26,048) groups compared to the White population (42%, 777,906). Latent class analysis revealed physical and mental health conditions that were common across all ethnic groups (i.e., hypertension, depression, and painful conditions). However, each ethnic group also presented exclusive LTCs and different sociodemographic profiles: In White groups, the cluster with the highest rates/odds of the outcomes was predominantly male (54%, 44,150) and more socioeconomically deprived than the cluster with the lowest rates/odds of the outcomes. On the other hand, South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. At the end of the study, 4% (34,922) of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black early onset multimorbidity populations (535 and 570, respectively); however, the latter groups died younger and lost more years of life. The 3 ethnic groups each displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. Study limitations include the exclusion of individuals with missing ethnicity information, the age of diagnosis not reflecting the actual age of onset, and the exclusion of people from Mixed, Chinese, and other ethnic groups due to insufficient power to investigate associations between multimorbidity and health-related outcomes in these groups. These findings emphasise the need to identify, prevent, and manage multimorbidity early in the life course. Our work provides additional insights into the excess burden of early onset multimorbidity in those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity and highlights the need to ensure healthcare improvements are equitable.

ATP-hydrolysis-coupled actin polymerization is a fundamental mechanism of cellular force generation 1 – 3 . In turn, force 4 , 5 and actin filament (F-actin) nucleotide state 6 regulate actin dynamics by tuning F-actin’s engagement of actin-binding proteins through mechanisms that are unclear. Here we show that the nucleotide state of actin modulates F-actin structural transitions evoked by bending forces. Cryo-electron microscopy structures of ADP–F-actin and ADP-P i –F-actin with sufficient resolution to visualize bound solvent reveal intersubunit interfaces bridged by water molecules that could mediate filament lattice flexibility. Despite extensive ordered solvent differences in the nucleotide cleft, these structures feature nearly identical lattices and essentially indistinguishable protein backbone conformations that are unlikely to be discriminable by actin-binding proteins. We next introduce a machine-learning-enabled pipeline for reconstructing bent filaments, enabling us to visualize both continuous structural variability and side-chain-level detail. Bent F-actin structures reveal rearrangements at intersubunit interfaces characterized by substantial alterations of helical twist and deformations in individual protomers, transitions that are distinct in ADP–F-actin and ADP-P i –F-actin. This suggests that phosphate rigidifies actin subunits to alter the bending structural landscape of F-actin. As bending forces evoke nucleotide-state dependent conformational transitions of sufficient magnitude to be detected by actin-binding proteins, we propose that actin nucleotide state can serve as a co-regulator of F-actin mechanical regulation. The nucleotide state of actin modulates F-actin structural transitions evoked by bending forces.