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Ovarian aging leads to diminished fertility, dysregulated endocrine signaling and increased chronic disease burden. These effects begin to emerge long before follicular exhaustion. Female humans experience a sharp decline in fertility around 35 years of age, which corresponds to declines in oocyte quality. Despite a growing body of work, the field lacks a comprehensive cellular map of the transcriptomic changes in the aging mouse ovary to identify early drivers of ovarian decline. To fill this gap we performed single-cell RNA sequencing on ovarian tissue from young (3-month-old) and reproductively aged (9-month-old) mice. Our analysis revealed a doubling of immune cells in the aged ovary, with lymphocyte proportions increasing the most, which was confirmed by flow cytometry. We also found an age-related downregulation of collagenase pathways in stromal fibroblasts, which corresponds to rises in ovarian fibrosis. Follicular cells displayed stress-response, immunogenic and fibrotic signaling pathway inductions with aging. This report provides critical insights into mechanisms responsible for ovarian aging phenotypes. The data can be explored interactively via a Shiny-based web application.

This paper reports a strategy for combining somatic mutation profiles of human tumors with gene networks to stratify tumors into biologically and clinically relevant subtypes. The method is applied to ovarian, uterine and lung cancers. Many forms of cancer have multiple subtypes with different causes and clinical outcomes. Somatic tumor genome sequences provide a rich new source of data for uncovering these subtypes but have proven difficult to compare, as two tumors rarely share the same mutations. Here we introduce network-based stratification (NBS), a method to integrate somatic tumor genomes with gene networks. This approach allows for stratification of cancer into informative subtypes by clustering together patients with mutations in similar network regions. We demonstrate NBS in ovarian, uterine and lung cancer cohorts from The Cancer Genome Atlas. For each tissue, NBS identifies subtypes that are predictive of clinical outcomes such as patient survival, response to therapy or tumor histology. We identify network regions characteristic of each subtype and show how mutation-derived subtypes can be used to train an mRNA expression signature, which provides similar information in the absence of DNA sequence.

Child maltreatment rates remain unacceptably high and rates are likely to escalate as COVID-related economic problems continue. A comprehensive and evidence-building approach is needed to prevent, detect and intervene where child maltreatment occurs. This review identifies key challenges in definitions, overviews the latest data on prevalence rates, reviews risk and protective factors, and examines common long-term mental health outcomes for children who experience maltreatment. The review takes a systems approach to child maltreatment outcomes through its focus on the overall burden of disease, gene-environment interactions, neurobiological mechanisms and social ecologies linking maltreatment to mental ill-health. Five recommendations relating to the accurate measurement of trends, research on brain structures and processes, improving the reach and impact of teleservices for detecting, preventing and treating child maladjustment, community-based approaches, and building population-focused multidisciplinary alliances and think tanks are presented.

Patient non-attendance remains a major challenge for health services. Few studies have examined how health service providers think about, potentially address, and prioritise non-attendance within the scope of their practice. This study aimed to (1) explore healthcare professionals' perspectives, beliefs, and opinions about the impact of patient non-attendance within a publicly-funded outpatient physiotherapy clinic context; (2) explore perceived barriers and facilitators associated with the implementation of non-attendance mitigation strategies; and (3) identify health service staff generated solutions to address perceived barriers and enhance facilitators. A focus group discussion and semi-structured interviews were conducted between June 2023 to January 2024 with 27 physiotherapy department clinic outpatient staff involved in operationalising clinic referral processing, appointment scheduling, or providing care to patients. Data was analysed using a hybrid inductive/deductive framework analysis approach. Participants indicated that non-attendance had predominantly negative implications for the health service, healthcare provider, and patient. The interconnected issue of non-attendance encompassed multiple areas and were broadly categorised into five inductively identified themes: impact of non-attendance, perceptions of value, material deprivation, service delivery and built environment, and professional role and identity. Non-attendance mitigation strategies generated by participants were deductively mapped to the theoretical domains framework (TDF) to explore behavioural determinants that may influence successful implementation. This included knowledge, reinforcement, goals, optimism, memory, attention and decision-making, environmental resources and context, and emotions. Staff identified multiple strategies for reducing non-attendance; implementing many of these strategies would require additional resourcing. Research determining the effectiveness of such strategies both in the short-term and long-term following implementation into practice remains a priority for future investigation.

Focal oncogene amplification and rearrangements drive tumor growth and evolution in multiple cancer types. We present AmpliconArchitect (AA), a tool to reconstruct the fine structure of focally amplified regions using whole genome sequencing (WGS) and validate it extensively on multiple simulated and real datasets, across a wide range of coverage and copy numbers. Analysis of AA-reconstructed amplicons in a pan-cancer dataset reveals many novel properties of copy number amplifications in cancer. These findings support a model in which focal amplifications arise due to the formation and replication of extrachromosomal DNA. Applying AA to 68 viral-mediated cancer samples, we identify a large fraction of amplicons with specific structural signatures suggestive of hybrid, human-viral extrachromosomal DNA. AA reconstruction, integrated with metaphase fluorescence in situ hybridization (FISH) and PacBio sequencing on the cell-line UPCI:SCC090 confirm the extrachromosomal origin and fine structure of a Forkhead box E1 ( FOXE1 )-containing hybrid amplicon. Focal amplifications are prevalent in many cancer genomes. Here, the authors present AmpliconArchitect (AA), a computational tool for reconstructing their architecture, and reveal an extrachromosomal origin for focal amplifications, including hybrid human-virus elements in HPV-mediated cancers.

To estimate the productivity costs of premature mortality due to cancer in Australia, in aggregate and for the 26 most prevalent cancer sites. A human capital approach was adopted to estimate the long term impacts of Australian cancer deaths in 2003. Using population mortality data, the labour force participation and the present value of lifetime income (PVLI) forgone due to premature mortality was estimated based on individual characteristics at the time of death including age, sex and socioeconomic status. Outcomes were modelled to the year 2030 using economic data from a national microsimulation model. A discount rate of 3% was applied and costs were reported in 2016 Australian dollars. Premature deaths from cancer in 2003 resulted in 88,000 working years lost and a cost of $4.2 billion in the PVLI forgone. Costs were close to three times higher in males than females due to the higher number of premature deaths in men, combined with higher levels of workforce participation and income. Lung, colorectal and brain cancers accounted for the highest proportion of costs, while testicular cancer was the most costly cancer site per death. The productivity costs of premature mortality due to cancer are significant. These results provide an economic measure of the cancer burden which may assist decision makers in allocating scare resources amongst competing priorities.

G protein-coupled receptors (GPCRs) are the most widely targeted gene family for Food and Drug Administration (FDA)-approved drugs. To assess possible roles for GPCRs in cancer, we analyzed The Cancer Genome Atlas (TCGA) data for mRNA expression, mutations, and copy number variation (CNV) in 20 categories and 45 subtypes of solid tumors and quantified differential expression (DE) of GPCRs by comparing tumors against normal tissue from the Gene Tissue Expression Project (GTEx) database. GPCRs are overrepresented among coding genes with elevated expression in solid tumors. This analysis reveals that most tumor types differentially express >50 GPCRs, including many targets for approved drugs, hitherto largely unrecognized as targets of interest in cancer. GPCR mRNA signatures characterize specific tumor types and correlate with expression of cancer-related pathways. Tumor GPCR mRNA signatures have prognostic relevance for survival and correlate with expression of numerous cancer-related genes and pathways. GPCR expression in tumors is largely independent of staging, grading, metastasis, and/or driver mutations. GPCRs expressed in cancer cell lines largely parallel GPCR expression in tumors. Certain GPCRs are frequently mutated and appear to be hotspots, serving as bellwethers of accumulated genomic damage. CNV of GPCRs is common but does not generally correlate with mRNA expression. Our results suggest a previously underappreciated role for GPCRs in cancer, perhaps as functional oncogenes, biomarkers, surface antigens, and pharmacological targets.

Background It is important to determine the relative value of health innovations when allocating limited healthcare resources. Implementation strategies require and consume healthcare resources yet are often excluded from published economic evaluations. This paper reports on the development of a pragmatic implementation costing instrument to assist with the planning, delivery, and evaluation of digital health implementation strategies. Methods A modified e-Delphi process was adopted to develop an implementation costing instrument. Purposive sampling was used to recruit a panel of experts in implementation science, health economic evaluations and/or digital health from the academic, government, clinical or health service sectors. In each round, participants were sent an electronic questionnaire and a prototype of the implementation costing instrument. The prototype in the initial round was informed from a literature review and qualitative interview findings. The prototype was updated iteratively between rounds in response to the panel’s feedback. In subsequent rounds, participants also received the anonymous results of items that did not reach consensus in the previous round. Termination occurred once consensus was reached on integral questions (those pertaining specifically to the instrument design) or when three rounds were completed, to prevent sample fatigue. Consensus was defined as at least 75% of experts in agreement for any item. Results Consensus was reached on the core components and design of the instrument from a panel of twelve experts in implementation science, health economic evaluations and/or digital health. Areas where consensus was not reached included users’ level of implementation science knowledge, specificity of the tool to digital health and accessibility via digital formats. Conclusions Cost-IS is a pragmatic data collection instrument designed to estimate the costs of implementation strategies for digital health solutions. Further piloting of Cost-IS is required to establish its feasibility and generalisability.

Background Global but predictable changes impact the DNA methylome as we age, acting as a type of molecular clock. This clock can be hastened by conditions that decrease lifespan, raising the question of whether it can also be slowed, for example, by conditions that increase lifespan. Mice are particularly appealing organisms for studies of mammalian aging; however, epigenetic clocks have thus far been formulated only in humans. Results We first examined whether mice and humans experience similar patterns of change in the methylome with age. We found moderate conservation of CpG sites for which methylation is altered with age, with both species showing an increase in methylome disorder during aging. Based on this analysis, we formulated an epigenetic-aging model in mice using the liver methylomes of 107 mice from 0.2 to 26.0 months old. To examine whether epigenetic aging signatures are slowed by longevity-promoting interventions, we analyzed 28 additional methylomes from mice subjected to lifespan-extending conditions, including Prop1 df/df dwarfism, calorie restriction or dietary rapamycin. We found that mice treated with these lifespan-extending interventions were significantly younger in epigenetic age than their untreated, wild-type age-matched controls. Conclusions This study shows that lifespan-extending conditions can slow molecular changes associated with an epigenetic clock in mice livers.

Background The importance of accurately costing implementation strategies is increasingly recognised within the field of implementation science. However, there is a lack of methodological guidance for costing implementation, particularly within digital health settings. This study reports on a systematic review of costing analyses conducted alongside implementation of hospital-based computerised decision support systems. Methods PubMed, Embase, Scopus and CINAHL databases were searched between January 2010 and August 2021. Two reviewers independently screened and selected original research studies that were conducted in a hospital setting, examined the implementation of a computerised decision support systems and reported implementation costs. The Expert Recommendations for Implementing Change Framework was used to identify and categorise implementation strategies into clusters. A previously published costing framework was applied to describe the methods used to measure and value implementation costs. The reporting quality of included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards checklist. Results Titles and abstracts of 1836 articles were screened, with nine articles eligible for inclusion in the review. Implementation costs were most frequently reported under the ‘evaluative and iterative strategies’ cluster, followed by ‘provide interactive assistance’. Labour was the largest implementation-related cost in the included papers, irrespective of implementation strategy. Other reported costs included consumables, durable assets and physical space, which was mostly associated with stakeholder training. The methods used to cost implementation were often unclear. There was variation across studies in the overall quality of reporting. Conclusions A relatively small number of papers have described computerised decision support systems implementation costs, and the methods used to measure and value these costs were not well reported. Priorities for future research should include establishing consistent terminology and appropriate methods for estimating and reporting on implementation costs. Trial registration The review protocol is registered with PROSPERO (ID: CRD42021272948).