Socio-economic conditions influence the implementation of proposed solutions for transforming food systems. Here we systematically screen over 1,700 articles and select 349 for detailed review, investigating the role of socio-economic drivers in sustainable food systems transformations across different world contexts. We identify seven sustainable food systems transformations, including sustainable land resources and soil health, precision agricultural practices, diet change and novel food transition, good nutrition and health, food loss and waste reduction, healthy freshwater and marine ecosystems, and climate change mitigation and biodiversity conservation. We propose socio-economic pathways comprising specific socio-economic drivers needed for achieving them and provide actor-specific recommendations to support sustainable food systems transformations.

Insulin resistance (IR), a primary precursor to type 2 diabetes, is characterized by impaired insulin action in tissues1. However, diagnostic methods remain expensive and inaccessible, which hinders early intervention2,3. Here we present the WEAR-ME study, a large, remotely conducted study of IR (n = 1,165 participants; median body mass index (BMI) = 28 kg m-2, medianage = 45 years, medianhaemoglobin A1c (HbA1c) = 5.4%) that uses time-series data from wearable devices and routine blood biomarkers to train deep neural networks against a ground-truth measure of IR (homeostatic model assessment of IR; HOMA-IR). Using a HOMA-IR cut-off of 2.9, our multimodal model achieved robust performance (area under the receiver operating characteristic curve (AUROC) = 0.80, sensitivity = 76%, specificity = 84%) with data from wearable devices, together with demographic and routine blood biomarker data. To enhance the use of time-series data from wearables, we fine-tuned a wearable foundation model (WFM) pretrained on 40 million hours of sensor data. In an independent validation cohort (n = 72), a model integrating WFM-derived representations with demographic data surpassed a demographics-only baseline (AUROC = 0.75 versus 0.66). Moreover, adding WFM-derived representations to a model with demographics, fasting glucose and a lipid panel substantially improved performance, compared with an identical model without data from wearables (AUROC = 0.88 versus 0.76). We integrate IR prediction into a large language model to contextualize the results and facilitate personalized recommendations. This work establishes a scalable, accessible framework for the early detection of metabolic risk, which could enable timely lifestyle interventions to prevent progression to type 2 diabetes.

Bacteriophages (phages) play a critical role in controlling bacterial populations, both in nature and as potential therapeutic agents. Their ability to replicate, compete against each other, and eradicate target cell populations is usually understood through a number of ‘life history parameters’, traditionally measured by population-level assays, which implicitly average the parameter’s value across a large number of infection events. Recent experiments suggest that bacteriophage life history parameters are subject to considerable stochasticity, raising the question of whether experimental and modelling efforts that do not account for this variability may overlook important factors in phage’s behaviour, competitive fitness or therapeutic viability. Here, using agent-based simulations, we investigate the importance of stochasticity in lysis time and burst size of lytic bacteriophages in two common laboratory competition experiments: serial passage of well-mixed populations and plaque expansion across a bacterial lawn. We find that a phage’s analytic growth rate in isolation can be a poor predictor of its fitness advantage in simulated competition experiments. Specifically, when lysis times are tightly distributed, we identify a novel effect we name “population resonance”, through which a bacteriophage can display a significant fitness advantage over a competitor with a much greater growth rate in isolation. Our simulations also show that both serial passage and plaque expansion reward variability in lysis time more than expected, by increasing the phage resilience when resources are scarce.

To develop a palatine approach to the canine maxillary nerve and compare its feasibility and the spread of dye and contrast medium with that of the infraorbital technique. Ten canine cadaveric heads were used in this study. The maxillary nerve was approached bilaterally by inserting hypodermic needles into either the infraorbital or the palatine foramen on each side. Dye/contrast injections (1:1 solution) were followed by CT and anatomical dissections, performed to isolate the maxillary nerves and measure their stained portions. Procedural failure was defined as a nerve stain <6 mm in length. Descriptive statistics, analysis of proportions and comparison of either means or medians were used for data analysis. The stained portion of the maxillary nerve was shorter for the palatine technique (0 (0 to 10) mm) than the infraorbital technique (35 (17 to 52) mm) (P = .015). Procedural failure rate was higher for the palatine technique (80%) compared to the infraorbital technique (20%; P = .025). For both techniques, imaging showed contrast spread along the nerve pathway in 70% of injections. Contrast medium contamination of nasal turbinates and nasal passages did not differ between approaches and was observed in 50% of palatine and 30% of infraorbital injections (P = .057). The novel palatine approach produced a higher procedural failure rate than the infraorbital technique and cannot be recommended as a suitable alternative to existing methods for canine maxillary nerve block.

BackgroundInformed choice is of the highest importance in health care. However, confusion and challenges remain toward how it is conceptualized and measured.PurposeThis umbrella review aimed to establish how informed choice is operationalized in health care and the characteristics and performance of the most commonly used measurement instruments.Data SourcesFour electronic databases (Ovid MEDLINE, Ovid EMBASE, APA PsycINFO, and Cochrane Library) were searched up to January 29, 2024. Reference lists of included studies were hand searched for further relevant publications.Study SelectionAfter the titles and abstracts of 10,434 articles were screened by one reviewer and 10% were screened by a second reviewer for consistency, 2 reviewers independently screened 60 full-text articles for inclusion. Key eligibility criteria included systematic reviews in adult health care settings where the aim included an evaluation of measures of informed choice. Sixteen articles were included.Data ExtractionData were independently extracted by 2 reviewers using a standardized template. Data Synthesis. Data were synthesized using the summarization technique with systematic reviews as the main unit of analysis and additional subanalysis of primary measurement instruments identified.LimitationsHeterogeneous definitions complicate search strategies, and eligibility criteria may limit external validity. The ROBIS appraisal identified many reviews as high risk of bias, limiting the conclusions drawn. Due to heterogeneity, meta-analysis was not possible, and conclusions were limited to narrative reviews.ConclusionsThere remains no consensus on how informed choice should be conceptualized and measured within health care. This review attempts to bridge these gaps by presenting available concepts and instruments for clinicians, researchers, and policy makers. Future recommendations include achieving consistent definitions of informed choice and related concepts, followed by the use of standardized, validated, multidimensional instruments informed by theory in diverse populations.HighlightsInformed choice is of key importance and increasingly emphasized across health care.Despite this importance, confusion and challenges remain regarding how informed choice is conceptualized and measured in health care.Consistent definitions and the use of standardized, validated, multidimensional instruments, informed by theory and patients themselves, in diverse populations should be the first steps to improve this.These recommendations apply to all in health care, including health professionals, researchers, and policy makers.

Online product reviews are a pervasive form of public feedback, yet research on their perceived helpfulness has focused almost exclusively on overall sentiment. Drawing on feedback literature, we propose that review structure—the sequencing of positive and negative content across the evaluative message—shapes helpfulness above and beyond aggregate valence. We conducted an exploratory study by analyzing 195,675 Amazon reviews using growth curve modeling to capture each review’s opening tone and valence trajectory. Results show that the most effective structures depend on product ratings. For highly rated products, reviews that grow increasingly positive are most helpful, while those that turn negative are least. For average-rated products, progressively negative trajectories enhance helpfulness, whereas reviews that start negative and grow positive are least effective. For low-rated products, reviews are judged most helpful when they open constructively before introducing criticism. These findings advance theories of online reviews and feedback by showing that how evaluative information is organized matters as much as what is said.

Diffuse alveolar damage (DAD) and the related clinical syndrome-acute respiratory distress syndrome (ARDS)-result in non-cardiogenic pulmonary edema (NCPE) through acute endothelial and/or alveolar epithelial injury. ARDS endotypes that have been suggested for human medicine may be applicable to veterinary contexts, and the molecular signatures of those endotypes require classification. Both the primary injury and the subsequent amplification by secondary inflammatory processes contribute to the molecular signature; raising awareness of these primary and secondary input processes increases the resolution of data analysis. Furthermore, species-specific differences in inflammatory pathways should be considered when interpreting data or applying new precision immunomodulatory therapeutics. We review other causes of NCPE in dogs and cats and explore the challenges in diagnosing pathologic pulmonary edema with histology. We explore the subsequent immune and cell-death processes that amplify the primary insult to the lung interstitium, ultimately leading to ARDS or DAD, along with the comparative immunology. For cases of acute lung damage-which result in non-cardiogenic edema that lack the classical histologic features of DAD-the histologic changes in dogs and cats can be subtle and nonspecific. Combining these subtle findings with a multidisciplinary approach to reviewing case evidence can yield greater diagnostic accuracy. Therefore, we summarize the histologic features that support a diagnosis of pathologic pulmonary edema and differentiate this condition from peracute agonal pulmonary edema or artefact.

While induced pluripotent stem cells (iPSCs) have gained popularity in studying neurodegenerative diseases, the heterogeneity of stem cells used across studies impacts cross-study comparison. The iPSC Neurodegenerative Disease Initiative (iNDI) selected the KOLF2.1J cell line and prioritized its use as a reference standard for studying the effects of pathogenic variants on cell biology due to its stability and neutral neurodegenerative disease genetic risk. This cell line, and its derivatives expressing over 100 variants related to Alzheimer’s disease, Parkinson’s disease, and other neurological diseases, are available for academic and industry access. Current genomic data analyses are limited by the use of a human reference genome that does not capture the complete genetic background of a given iPSC line. While in the future this issue may be partially mitigated by the creation of a comprehensive human pangenome, previous work has shown that generating custom genomes is of value both to characterize the variation present and to serve as a more appropriate genomic reference. Here, we generated and characterized a custom complete genome assembly from KOLF2.1J. Mapping of sequencing reads to a personalized diploid assembly results in more comprehensive mapping compared to traditional linear references (i.e GRCh38). In addition, we provide a comprehensive custom gene annotation along with isoform expression and differential methylation analyses across multiple cell types. The assembly and all additional data is browsable and publicly available. This resource will enable more accurate investigation of the KOLF2.1J cell line and any genomics data generated compared to using traditional generalized references, while also serving as a foundational approach for establishing custom reference assemblies for other high-value iPSC lines.

This study investigated whether earlier menopause is associated with reduced later-life cognitive performance and brain structure in a population-based cohort. It is among a few studies examining both cognition and neuroimaging within the same postmenopausal sample, and the first to test whether gray matter volume mediates the relationship between menopause timing and cognitive performance within the same sample. We analyzed data from the Cambridge Centre of Neuroscience and Aging, including 747 postmenopausal women who underwent cognitive testing. A subset was additionally tested with a fluid intelligence test and structural brain scans. Multiple linear regression models evaluated the association between menopause age, cognitive performance, and gray matter volume, controlling for chronological age, education, depressive symptoms, and physical activity. Earlier menopause was associated with lower cognitive performance ( t717 =2.2, P =0.028) and fluid intelligence ( t153 =1.59, P =0.026). Structural imaging analyses (n=182) revealed that earlier menopause was associated with decreased total gray matter volume ( t182 =0.152, P =0.024). Exploratory mediation analysis showed that total gray matter volume partially mediated the relationship between age at menopause and cognitive performance ( P =0.006). In this population-based cohort, earlier menopause was associated with both lower cognitive performance and reduced gray matter volume, suggesting a potential mechanism linking earlier menopause to cognitive decline. However, the cross-sectional nature of this study prevents causal conclusions, and longitudinal research is needed to establish causal links and explore potential targeted interventions.