Disease resistance gene count increases with rainfall in Silphium integrifolium.

Intracellular plant defense against pathogens is mediated by a class of disease resistance genes known as NB-LRRs or NLRs (R genes). Many of the diseases these genes protect against are more prevalent in regions of higher rainfall, which provide better growth conditions for the pathogens. As such, we expect a higher selective pressure for the maintenance and proliferation of R genes in plants adapted to wetter conditions. In this study, we enriched libraries for R genes using RenSeq from baits primarily developed from the common sunflower (Helianthus annuus) reference genome. We sequenced the R gene libraries of Silphium integrifolium Michx, a perennial relative of sunflower, from 12 prairie remnants across a rainfall gradient in the Central Plains of the United States, with both Illumina short-read (n = 99) and PacBio long-read (n = 10) approaches. We found a positive relationship between the mean effective annual precipitation of a plant's source prairie remnant and the number of R genes in its genome, consistent with intensity of plant pathogen coevolution increasing with precipitation. We show that RenSeq can be applied to the study of ecological hypotheses in non-model relatives of model organisms.

Unconventional insulator-to-metal phase transition in Mn3Si2Te6.

The nodal-line semiconductor Mn3Si2Te6 is generating enormous excitment due to the recent discovery of a field-driven insulator-to-metal transition and associated colossal magnetoresistance as well as evidence for a new type of quantum state involving chiral orbital currents. Strikingly, these qualities persist even in the absence of traditional Jahn-Teller distortions and double-exchange mechanisms, raising questions about exactly how and why magnetoresistance occurs along with conjecture as to the likely signatures of loop currents. Here, we measured the infrared response of Mn3Si2Te6 across the magnetic ordering and field-induced insulator-to-metal transitions in order to explore colossal magnetoresistance in the absence of Jahn-Teller and double-exchange interactions. Rather than a traditional metal with screened phonons, the field-driven insulator-to-metal transition leads to a weakly metallic state with localized carriers. Our spectral data are fit by a percolation model, providing evidence for electronic inhomogeneity and phase separation. Modeling also reveals a frequency-dependent threshold field for carriers contributing to colossal magnetoresistance which we discuss in terms of polaron formation, chiral orbital currents, and short-range spin fluctuations. These findings enhance the understanding of insulator-to-metal transitions in new settings and open the door to the design of unconventional colossal magnetoresistant materials.

A Common Longitudinal Intensive Care Unit data Format (CLIF) to enable multi-institutional federated critical illness research.

Background: Critical illness, or acute organ failure requiring life support, threatens over five million American lives annually. Electronic health record (EHR) data are a source of granular information that could generate crucial insights into the nature and optimal treatment of critical illness. However, data management, security, and standardization are barriers to large-scale critical illness EHR studies. Methods: A consortium of critical care physicians and data scientists from eight US healthcare systems developed the Common Longitudinal Intensive Care Unit (ICU) data Format (CLIF), an open-source database format that harmonizes a minimum set of ICU Data Elements for use in critical illness research. We created a pipeline to process adult ICU EHR data at each site. After development and iteration, we conducted two proof-of-concept studies with a federated research architecture: 1) an external validation of an in-hospital mortality prediction model for critically ill patients and 2) an assessment of 72-hour temperature trajectories and their association with mechanical ventilation and in-hospital mortality using group-based trajectory models. Results: We converted longitudinal data from 94,356 critically ill patients treated in 2020-2021 (mean age 60.6 years [standard deviation 17.2], 30% Black, 7% Hispanic, 45% female) across 8 health systems and 33 hospitals into the CLIF format, The in-hospital mortality prediction model performed well in the health system where it was derived (0.81 AUC, 0.06 Brier score). Performance across CLIF consortium sites varied (AUCs: 0.74-0.83, Brier scores: 0.06-0.01), and demonstrated some degradation in predictive capability. Temperature trajectories were similar across health systems. Hypothermic and hyperthermic-slow-resolver patients consistently had the highest mortality. Conclusions: CLIF facilitates efficient, rigorous, and reproducible critical care research. Our federated case studies showcase CLIF's potential for disease sub-phenotyping and clinical decision-support evaluation. Future applications include pragmatic EHR-based trials, target trial emulations, foundational multi-modal AI models of critical illness, and real-time critical care quality dashboards.

Standardized Management of Sickle Cell Disease Patients and the Effects on Care Utilization and Costs.

An individualized management program for patients with sickle cell disease (SCD) was created to reduce health care utilization and cost. The program was implemented to standardize the management of patients with SCD. SCD encounters from January 2010 to December 2020 were reviewed for analysis. Preintervention utilization of inpatient, emergency room, and outpatient settings was compared to postintervention. There were 7114 encounters analyzed. Outpatient encounters increased from 36.5% to 70.9%; inpatient encounters decreased from 38.6% to 20.3%; and emergency department visits decreased from 20.3% to 8.8%. The number of high inpatient utilizers decreased 8.4% and the number of individuals who received any emergency care decreased 11.9%. When comparing average charges per time period, the median charge per encounter decreased by $1838 postintervention compared to preintervention. This newly implemented SCD program demonstrated success through shifting the care of the SCD patient to the outpatient setting rather than the emergency department or inpatient hospitalizations.

Germline genome editing of human IVF embryos should not be subject to overly stringent restrictions.

This paper critiques the restrictive criteria for germline genome editing recently proposed by Chin, Nguma, and Ahmad in this journal. While praising the authors for resisting fervent calls for an outright ban on clinical applications of the technology, this paper argues that their approach is nevertheless unduly restrictive, and may thus hinder technological progress. This response advocates for weighing potential benefits against risks without succumbing to excessive caution, proposing that ethical oversight combined with genetic scrutiny at the embryo stage post-editing can enable responsible use of the technology, ultimately reducing the burden of genetic diseases and enhancing human health, akin to how IVF transformed reproductive medicine despite strong initial opposition.

Merck Animal Health Veterinary Team study reveals factors associated with well-being, burnout, and mental health among nonveterinarian practice team members.

OBJECTIVE: To assess the levels of burnout, well-being, and mental health of nonveterinarian employees of veterinary practices and, for context, compare them to veterinarians and the general population by use of validated instruments. METHODS: An online survey of 2,271 nonveterinary practice employees drawn from members of the North American Veterinary Technicians Association, members of the Veterinary Hospital Managers Association, referrals from veterinarian respondents to a companion survey, and a large hospital group that owns several hundred US veterinary practices. The study was fielded from September 11 to October 9, 2023. RESULTS: A majority of practice team members were satisfied with their work in veterinary medicine. However, serious psychological distress was twice as prevalent among team members as among veterinarians and well-being was lower than that of veterinarians. Burnout was similar to veterinarians. Personality played a role: team members on average were more likely to score higher in neuroticism than veterinarians and the general population, and neuroticism was a predictor of low well-being, poor mental health, and burnout. There was also evidence of substantial financial stress among team members. CONCLUSIONS: Serious psychological distress was common among practice team members. Financial stress may play a role. Burnout and low levels of well-being were also common. CLINICAL RELEVANCE: This study provided a useful profile of the psychological conditions that many practice employees may be experiencing.

AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial.

Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many cancers are missed. Supplemental screening using magnetic resonance imaging (MRI) can reduce the number of missed cancers. However, as qualified MRI staff are lacking, the equipment is expensive to purchase and cost-effectiveness for screening may not be convincing, the utilization of MRI is currently limited. An effective method for triaging individuals to supplemental MRI screening is therefore needed. We conducted a randomized clinical trial, ScreenTrustMRI, using a recently developed artificial intelligence (AI) tool to score each mammogram. We offered trial participation to individuals with a negative screening mammogram and a high AI score (top 6.9%). Upon agreeing to participate, individuals were assigned randomly to one of two groups: those receiving supplemental MRI and those not receiving MRI. The primary endpoint of ScreenTrustMRI is advanced breast cancer defined as either interval cancer, invasive component larger than 15 mm or lymph node positive cancer, based on a 27-month follow-up time from the initial screening. Secondary endpoints, prespecified in the study protocol to be reported before the primary outcome, include cancer detected by supplemental MRI, which is the focus of the current paper. Compared with traditional breast density measures used in a previous clinical trial, the current AI method was nearly four times more efficient in terms of cancers detected per 1,000 MRI examinations (64 versus 16.5). Most additional cancers detected were invasive and several were multifocal, suggesting that their detection was timely. Altogether, our results show that using an AI-based score to select a small proportion (6.9%) of individuals for supplemental MRI after negative mammography detects many missed cancers, making the cost per cancer detected comparable with screening mammography. ClinicalTrials.gov registration: NCT04832594 .

Harnessing Immunomodulatory Polymers for Treatment of Autoimmunity, Allergy, and Transplant Rejection.

Autoimmunity, allergy, and transplant rejection are a collection of chronic diseases that are currently incurable, drastically decrease patient quality of life, and consume considerable health care resources. Underlying each of these diseases is a dysregulated immune system that results in the mounting of an inflammatory response against self or an innocuous antigen. As a consequence, afflicted patients are required to adhere to lifelong regimens of multiple immunomodulatory drugs to control disease and reclaim agency. Unfortunately, current immunomodulatory drugs are associated with a myriad of side effects and adverse events, such as increased risk of cancer and increased risk of serious infection, which negatively impacts patient adherence rates and quality of life. The field of immunoengineering is a new discipline that aims to harness endogenous biological pathways to thwart disease and minimize side effects using novel biomaterial-based strategies. We highlight and discuss polymeric micro/nanoparticles with inherent immunomodulatory properties that are currently under investigation in biomaterial-based therapies for treatment of autoimmunity, allergy, and transplant rejection.

Increased heart rate fragmentation in those with Williams-Beuren syndrome suggests nonautonomic mechanistic contributors to sudden death risk.

Williams-Beuren syndrome (WBS) is a rare genetic condition caused by a chromosomal microdeletion at 7q11.23. It is a multisystem disorder characterized by distinct facies, intellectual disability, and supravalvar aortic stenosis (SVAS). Those with WBS are at increased risk of sudden death, but mechanisms underlying this remain poorly understood. We recently demonstrated autonomic abnormalities in those with WBS that are associated with increased susceptibility to arrhythmia and sudden cardiac death (SCD). A recently introduced method for heart rate variability (HRV) analysis called "heart rate fragmentation" (HRF) correlates with adverse cardiovascular events (CVEs) and death in studies where heart rate variability (HRV) failed to identify high-risk subjects. Some argue that HRF quantifies nonautonomic cardiovascular modulators. We, therefore, sought to apply HRF analysis to a WBS cohort to determine 1) if those with WBS show differences in HRF compared with healthy controls and 2) if HRF helps characterize HRV abnormalities in those with WBS. Similar to studies of those with coronary artery disease (CAD) and atherosclerosis, we found significantly higher HRF (4 out of 7 metrics) in those with WBS compared with healthy controls. Multivariable analyses showed a weak-to-moderate association between HRF and HRV, suggesting that HRF may reflect HRV characteristics not fully captured by traditional HRV metrics (autonomic markers). We also introduce a new metric inspired by HRF methodology, significant acute rate drop (SARD), which may detect vagal activity more directly. HRF and SARD may improve on traditional HRV measures to identify those at greatest risk for SCD both in those with WBS and in other populations.NEW & NOTEWORTHY This work is the first to apply heart rate fragmentation analyses to individuals with Williams syndrome and posits that the heart rate fragmentation parameter W3 may enable detection and investigation of phenomena underlying the proarrhythmic short-long-short RR interval sequences paradigm known to precede ventricular fibrillation and ventricular tachycardia. It also forwards a novel method for quantifying sinus arrhythmia and sinus pauses that likely correlate with parasympathetic activity.

Impact of genome build on RNA-seq interpretation and diagnostics.

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium. Across six routinely collected biospecimens, 61% of quantified genes were not influenced by genome build. However, we identified 1,492 genes with build-dependent quantification, 3,377 genes with build-exclusive expression, and 9,077 genes with annotation-specific expression across six routinely collected biospecimens, including 566 clinically relevant and 512 known OMIM genes. Further, we demonstrate that between builds for a given gene, a larger difference in quantification is well correlated with a larger change in expression outlier calling. Combined, we provide a database of genes impacted by build choice and recommend that transcriptomics-guided analyses and diagnoses are cross referenced with these data for robustness.

Toward Alleviating Clinician Documentation Burden: A Scoping Review of Burden Reduction Efforts.

BACKGROUND: Studies have shown that documentation burden experienced by clinicians may lead to less direct patient care, increased errors, and job dissatisfaction. Implementing effective strategies within health care systems to mitigate documentation burden can result in improved clinician satisfaction and more time spent with patients. However, there is a gap in the literature regarding evidence-based interventions to reduce documentation burden. OBJECTIVES: The objective of this review was to identify and comprehensively summarize the state of the science related to documentation burden reduction efforts. METHODS: Following Joanna Briggs Institute Manual for Evidence Synthesis and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, we conducted a comprehensive search of multiple databases, including PubMed, Medline, Embase, CINAHL Complete, Scopus, and Web of Science. Additionally, we searched gray literature and used Google Scholar to ensure a thorough review. Two reviewers independently screened titles and abstracts, followed by full-text review, with a third reviewer resolving any discrepancies. Data extraction was performed and a table of evidence was created. RESULTS: A total of 34 articles were included in the review, published between 2016 and 2022, with a majority focusing on the United States. The efforts described can be categorized into medical scribes, workflow improvements, educational interventions, user-driven approaches, technology-based solutions, combination approaches, and other strategies. The outcomes of these efforts often resulted in improvements in documentation time, workflow efficiency, provider satisfaction, and patient interactions. CONCLUSION: This scoping review provides a comprehensive summary of health system documentation burden reduction efforts. The positive outcomes reported in the literature emphasize the potential effectiveness of these efforts. However, more research is needed to identify universally applicable best practices, and considerations should be given to the transfer of burden among members of the health care team, quality of education, clinician involvement, and evaluation methods.

Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures.

Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8 weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.

Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder.

PURPOSE: The function of FAM177A1 and its relationship to human disease is largely unknown. Recent studies have demonstrated FAM177A1 to be a critical immune-associated gene. One previous case study has linked FAM177A1 to a neurodevelopmental disorder in 4 siblings. METHODS: We identified 5 individuals from 3 unrelated families with biallelic variants in FAM177A1. The physiological function of FAM177A1 was studied in a zebrafish model organism and human cell lines with loss-of-function variants similar to the affected cohort. RESULTS: These individuals share a characteristic phenotype defined by macrocephaly, global developmental delay, intellectual disability, seizures, behavioral abnormalities, hypotonia, and gait disturbance. We show that FAM177A1 localizes to the Golgi complex in mammalian and zebrafish cells. Intersection of the RNA sequencing and metabolomic data sets from FAM177A1-deficient human fibroblasts and whole zebrafish larvae demonstrated dysregulation of pathways associated with apoptosis, inflammation, and negative regulation of cell proliferation. CONCLUSION: Our data shed light on the emerging function of FAM177A1 and defines FAM177A1-related neurodevelopmental disorder as a new clinical entity.

Synthesis and Regioselective Functionalization of Tetrafluorobenzo-[α]-Fused BOPYPY Dyes.

The synthesis of a new bis-BF2 tetrafluorobenzo-[α]-fused BOPYPY dye from 4,5,6,7-tetrafluoroisoindole and 2-hydrazinopyrazine is reported. The regioselectivity of nucleophilic substitution reactions at the periphery of the tetrafluorinated BOPYPY and its α-bromo derivative were investigated using N-, O-, S-, and C-based nucleophiles. Among the aromatic fluorine atoms, the F2 atom is consistently regioselectively substituted, except when the α-position contains a thiophenol group; in this case, F4 is substituted instead due to stabilizing π-π-stacking between the two aromatic groups. The α-bromo BOPYPY derivative also reacts under Stille cross-coupling reaction conditions to produce the corresponding α-substituted product. The spectroscopic properties of these new fluorinated BOPYPYs were investigated and compared with nonfluorinated analogs.

Pressure-Temperature-Magnetic Field Phase Diagram of Multiferroic (NH4)2FeCl5·H2O.

We combined synchrotron-based infrared absorbance and Raman scattering spectroscopies with diamond anvil cell techniques and a symmetry analysis to explore the properties of multiferroic (NH4)2FeCl5·H2O under extreme pressure-temperature conditions. Compression-induced splitting of the Fe-Cl stretching, Cl-Fe-Cl and Cl-Fe-O bending, and NH4+ librational modes defines two structural phase transitions, and a group-subgroup analysis reveals space group sequences that vary depending upon proximity to the unexpectedly wide order-disorder transition. We bring these findings together with prior high-field work to develop the pressure-temperature-magnetic field phase diagram uncovering competing polar, chiral, and magnetic phases in this system.

Redox-induced controllable engineering of MnO2-MnxCo3-xO4 interface to boost catalytic oxidation of ethane.

Multicomponent oxides are intriguing materials in heterogeneous catalysis, and the interface between various components often plays an essential role in oxidations. However, the underlying principles of how the hetero-interface affects the catalytic process remain largely unexplored. Here we report a unique structure design of MnCoOx catalysts by chemical reduction, specifically for ethane oxidation. Part of the Mn ions incorporates with Co oxides to form spinel MnxCo3-xO4, while the rests stay as MnO2 domains to create the MnO2-MnxCo3-xO4 interface. MnCoOx with Mn/Co ratio of 0.5 exhibits an excellent activity and stability up to 1000 h under humid conditions. The synergistic effects between MnO2 and MnxCo3-xO4 are elucidated, in which the C2H6 tends to be adsorbed on the interfacial Co sites and subsequently break the C-H bonds on the reactive lattice O of MnO2 layer. Findings from this study provide valuable insights for the rational design of efficient catalysts for alkane combustion.

Work-life balance is essential to reducing burnout, improving well-being.

OBJECTIVE: To assess levels of burnout, well-being, and mental health of veterinarians and compare them to those of nonveterinarians by use of validated instruments, and to identify the predictive values of techniques individuals can use to help reduce burnout and/or improve well-being and mental health. SAMPLE: An online survey of 4,636 veterinarians from a random sample of 40,000 US veterinarians provided by the AVMA. METHODS: The study was fielded from September 11 to October 9, 2023. RESULTS: Burnout and well-being of veterinarians were generally consistent with that of employed US adults. Serious psychological distress was more common among veterinarians than in the general population. Veterinarians on average were more likely to score higher in neuroticism than nonveterinarians, and neuroticism was a predictor of low well-being, poor mental health, and burnout. Work-life balance, an effective coping mechanism for stress, and working in a positive clinic culture were among the significant factors that predicted good well-being and mental health and reduced burnout. CLINICAL RELEVANCE: The higher percentage than the norm of veterinarians with serious psychological distress was a concern. Focusing on maintaining a good work-life balance and adopting a reliable coping mechanism can potentially help reduce distress. Veterinary medicine is an inherently stressful profession. The purpose of this study was to identify key factors that contribute to burnout, well-being, and mental health and to determine what behaviors and management techniques help reduce stress and burnout and contribute to well-being and mental health, thus improving job satisfaction and personal fulfillment.

Is political anxiety different than general anxiety?

Recently, there has been growing interest in the concept of political anxiety. One important question that remains unanswered is whether political anxiety is just a symptom of general anxiety-that those reporting anxiety tied to politics are the same individuals who would already score highly on measures of general anxiety. Using survey data collected in 2023 (N = 436), we find that measures of political and generalized anxiety do not appear to be tapping into a single underlying construct. In addition, the systematic correlates of these measures identified by previous literature are not equivalent predictors of the different types of anxiety. Politics seems to be a source of apprehensiveness and worry that affects individuals who are not necessarily suffering from general anxiety.

Fluoroscopy-guided high-intensity focused ultrasound neurotomy of the lumbar zygapophyseal joints: a prospective, open-label study.

OBJECTIVE: The objective of this study is to investigate safety and effectiveness of a fluoroscopy-guided high-intensity focused ultrasound (HIFU) system for thermal ablation of the lumbar medial branch nerves. METHODS: This dual center prospective cohort study enrolled 30 participants with lumbar zygapophyseal joint syndrome. Each participant previously had a positive response to either a single diagnostic analgesic block or radiofrequency ablation (RFA). The primary effectiveness outcome was individual responder rate, defined as a reduction of two points or more on the pain intensity numerical rating scale without an increase in opioid intake, or a reduction in opioid intake without an increase in pain at 6 months after the intervention. The primary safety outcome was procedure-related or device-related adverse events (AEs). Secondary outcome variables included MRI evidence of tissue ablation, Oswestry Disability Index, 12-Item Short Form Health Survey, Brief Pain Inventory, and Patient Global Impression of Change. RESULTS: The individual responder rate was 89.7% at 2 days, 89.7% at 7 days, 72.4% at 14 days, 82.1% at 30 days, 59.3% at 90 days and 82.6% at 180 days. The average Numeric Rating Scale for pain severity decreased from 7.1 at baseline to 3.0 (N=29) after 2 days, 3.0 (N=29) after 7 days, 3.1 (N=29) after 14 days, 3.2 (N=28) after 30 days, 4.3 (N=27) after 90 days, and 3.3 (N=23) after 180 days. All participants tolerated the procedure well with no significant side effects or complications. CONCLUSIONS: Fluoroscopy-guided HIFU neurotomy achieved clinical responses comparable with RFA, and there were no significant device-related or procedure-related AEs. TRIAL REGISTRATION NUMBER: NCT04129034.

Use of an AI Score Combining Cancer Signs, Masking, and Risk to Select Patients for Supplemental Breast Cancer Screening.

Background Mammographic density measurements are used to identify patients who should undergo supplemental imaging for breast cancer detection, but artificial intelligence (AI) image analysis may be more effective. Purpose To assess whether AISmartDensity-an AI-based score integrating cancer signs, masking, and risk-surpasses measurements of mammographic density in identifying patients for supplemental breast imaging after a negative screening mammogram. Materials and Methods This retrospective study included randomly selected individuals who underwent screening mammography at Karolinska University Hospital between January 2008 and December 2015. The models in AISmartDensity were trained and validated using nonoverlapping data. The ability of AISmartDensity to identify future cancer in patients with a negative screening mammogram was evaluated and compared with that of mammographic density models. Sensitivity and positive predictive value (PPV) were calculated for the top 8% of scores, mimicking the proportion of patients in the Breast Imaging Reporting and Data System "extremely dense" category. Model performance was evaluated using area under the receiver operating characteristic curve (AUC) and was compared using the DeLong test. Results The study population included 65 325 examinations (median patient age, 53 years [IQR, 47-62 years])-64 870 examinations in healthy patients and 455 examinations in patients with breast cancer diagnosed within 3 years of a negative screening mammogram. The AUC for detecting subsequent cancers was 0.72 and 0.61 (P < .001) for AISmartDensity and the best-performing density model (age-adjusted dense area), respectively. For examinations with scores in the top 8%, AISmartDensity identified 152 of 455 (33%) future cancers with a PPV of 2.91%, whereas the best-performing density model (age-adjusted dense area) identified 57 of 455 (13%) future cancers with a PPV of 1.09% (P < .001). AISmartDensity identified 32% (41 of 130) and 34% (111 of 325) of interval and next-round screen-detected cancers, whereas the best-performing density model (dense area) identified 16% (21 of 130) and 9% (30 of 325), respectively. Conclusion AISmartDensity, integrating cancer signs, masking, and risk, outperformed traditional density models in identifying patients for supplemental imaging after a negative screening mammogram. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kim and Chang in this issue.