Abietane diterpenoids from Caryopteris incana (Thunb.) Miq. And their HIF-2α inhibitory activities in vitro.

Eleven previously undescribed abietane-type diterpenoids, named caryopincanoids A-K (1-11), together with five known compounds, were isolated from the EtOH extract of the aerial parts of Caryopteris incana (Thunb.) Miq. Their structures were elucidated on the basis of comprehensive spectroscopic data, NMR calculations, and ECD calculations. The inhibitory activities of all compounds against HIF-2α gene expression in 786-O cells were tested by luciferase assay. Compounds 7, 9, 15, and 16 showed significant inhibitory effects with IC50 values ranging from 12.73 to 23.80 µM. The preliminary structure-activity relationship of these compounds was also discussed.

Construction of cellulose-based hybrid hydrogel beads containing carbon dots and their high performance in the adsorption and detection of mercury ions in water.

Cellulose-based adsorbents have been extensively developed in heavy metal capture and wastewater treatment. However, most of the reported powder adsorbents suffer from the difficulties in recycling due to their small sizes and limitations in detecting the targets for the lack of sensitive sensor moieties in the structure. Accordingly, carbon dots (CDs) were proposed to be encapsulated in cellulosic hydrogel beads to realize the simultaneous detection and adsorption of Hg (II) in water due to their excellent fluorescence sensing performance. Besides, the molding of cellulose was beneficial to its recycling and further reduced the potential environmental risk generated by secondary pollution caused by adsorbent decomposition. In addition, the detection limit of the hydrogel beads towards Hg (II) reached as low as 8.8 × 10-8 M, which was below the mercury effluent standard declared by WHO, exhibiting excellent practicability in Hg (II) detection and water treatment. The maximum adsorption capacity of CB-50 % for Hg (II) was 290.70 mg/g. Moreover, the adsorbent materials also had preeminent stability that the hydrogel beads could maintain sensitive and selective sensing performance towards Hg (II) after 2 months of storage. Additionally, only 3.3% of the CDs leaked out after 2 weeks of immersion in water, ensuring the accuracy of Hg (II) evaluation. Notably, the adsorbent retained over 80% of its original adsorption capacity after five consecutive regeneration cycles, underscoring its robustness and potential for sustainable environmental applications.

PSAEEGNet: pyramid squeeze attention mechanism-based CNN for single-trial EEG classification in RSVP task.

Introduction: Accurate classification of single-trial electroencephalogram (EEG) is crucial for EEG-based target image recognition in rapid serial visual presentation (RSVP) tasks. P300 is an important component of a single-trial EEG for RSVP tasks. However, single-trial EEG are usually characterized by low signal-to-noise ratio and limited sample sizes. Methods: Given these challenges, it is necessary to optimize existing convolutional neural networks (CNNs) to improve the performance of P300 classification. The proposed CNN model called PSAEEGNet, integrates standard convolutional layers, pyramid squeeze attention (PSA) modules, and deep convolutional layers. This approach arises the extraction of temporal and spatial features of the P300 to a finer granularity level. Results: Compared with several existing single-trial EEG classification methods for RSVP tasks, the proposed model shows significantly improved performance. The mean true positive rate for PSAEEGNet is 0.7949, and the mean area under the receiver operating characteristic curve (AUC) is 0.9341 (p < 0.05). Discussion: These results suggest that the proposed model effectively extracts features from both temporal and spatial dimensions of P300, leading to a more accurate classification of single-trial EEG during RSVP tasks. Therefore, this model has the potential to significantly enhance the performance of target recognition systems based on EEG, contributing to the advancement and practical implementation of target recognition in this field.

A novel dual near-infrared fluorescent probe for bioimaging and visualization of viscosity in acute alcoholic liver injury.

A dual NIR fluorescent probe Cy-ND is developed for viscosity sensing with λex/em = 766/806 nm, making it apt for biological analysis, whose response is validated through DFT and TDDFT computations. Cy-ND successfully detected viscosity changes amidst acute alcohol-induced liver injury and liver ischemia-reperfusion injury.

Construction and validation of "WCH-nomogram" for predicting the prognosis after resection of colorectal liver metastases.

BACKGROUND: The prognostic predictive tool for patients with colorectal liver metastasis (CRLM) is limited and the criteria for administering preoperative neoadjuvant chemotherapy in CRLM patients remain controversial. METHODS: This study enrolled 532 CRLM patients at West China Hospital (WCH) from January 2009 to December 2019. Prognostic factors were identified from the training cohort to construct a WCH-nomogram and evaluating accuracy in the validation cohort. Receiver operating characteristic (ROC) curve analysis was used to compare the prediction accuracy with other existing prediction tools. RESULTS: From the analysis of the training cohort, four independent prognostic risk factors, namely tumor marker score, KRAS mutation, primary lymph node metastasis, and tumor burden score were identified on which a WCH-nomogram was constructed. The C-index of the two cohorts were 0.674 (95% CI: 0.634-0.713) and 0.655 (95% CI: 0.586-0.723), respectively, which was better than the previously reported predication scores (CRS, m-CS and GAME score). ROC curves showed AUCs for predicting 1-, 3-, and 5-year overall survival (OS) of 0.758, 0.709, and 0.717 in the training cohort, and 0.860, 0.669, and 0.692 in the validation cohort, respectively. A cutoff value of 114.5 points was obtained for the WCH-nomogram total score based on the maximum Youden index of the ROC curve of 5-year OS. Risk stratification showed significantly better prognosis in the low-risk group, however, the high-risk group was more likely to benefit from neoadjuvant chemotherapy. CONCLUSIONS: The WCH-nomogram demonstrates superior prognostic stratification compared to prior scoring systems, effectively identifying CRLM patients who may benefit the most from neoadjuvant chemotherapy.

Standardization of ultrasound images across various centers: M2O-DiffGAN bridging the gaps among unpaired multi-domain ultrasound images.

Domain shift problem is commonplace for ultrasound image analysis due to difference imaging setting and diverse medical centers, which lead to poor generalizability of deep learning-based methods. Multi-Source Domain Transformation (MSDT) provides a promising way to tackle the performance degeneration caused by the domain shift, which is more practical and challenging compared to conventional single-source transformation tasks. An effective unsupervised domain combination strategy is highly required to handle multiple domains without annotations. Fidelity and quality of generated images are also important to ensure the accuracy of computer-aided diagnosis. However, existing MSDT approaches underperform in above two areas. In this paper, an efficient domain transformation model named M2O-DiffGAN is introduced to achieve a unified mapping from multiple unlabeled source domains to the target domain. A cycle-consistent "many-to-one" adversarial learning architecture is introduced to model various unlabeled domains jointly. A condition adversarial diffusion process is employed to generate images with high-fidelity, combining an adversarial projector to capture reverse transition probabilities over large step sizes for accelerating sampling. Considering the limited perceptual information of ultrasound images, an ultrasound-specific content loss helps to capture more perceptual features for synthesizing high-quality ultrasound images. Massive comparisons on six clinical datasets covering thyroid, carotid and breast demonstrate the superiority of the M2O-DiffGAN in the performance of bridging the domain gaps and enlarging the generalization of downstream analysis methods compared to state-of-the-art algorithms. It improves the mean MI, Bhattacharyya Coefficient, dice and IoU assessments by 0.390, 0.120, 0.245 and 0.250, presenting promising clinical applications.

Cellulose-based adsorbent using in mercury detection and removal from water via an efficient grafting strategy of fluorometric sensors by click reaction.

Mercury pollution in waters attracts lots of attention due to its serious toxicity and high bioenrichment and many efforts have been devoted in the development of adsorbents for mercury detection and removal. Herein, a cellulose-based adsorbent Cell-TriA-HQ is functionalized with quinoline fluorophore by covalent immobilization through "Click reaction" with high yield. In addition to the admirable adsorptive performance, the prepared adsorbent exhibits excellent selectivity and sensitivity towards Hg (II) in water that the detection limit for Hg (II) is determined to be as low as 1.92 × 10-7 M. The sensitive fluorescence enhancement response is considered to be resulted from the inhibition of photo-induced electron transfer between triazole and quinoline groups and the reinforcement of structural rigidity. The easy manipulation along with excellent performance of adsorption capacity, detective ability and reusability for the multifunctional adsorbent makes it potential in mercury monitoring and removal from aqueous solutions in the field of water treatment.

Assessing Patterns of CGM use and Metrics of Glycemic Control in T1D and T2D Patients in the Veterans Healthcare System: Integrating CGM Device Data with EHR Data.

OBJECTIVE: To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for type 1 and type 2 diabetes patients in the Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. RESEARCH DESIGN AND METHODS: This observational study used Dexcom CGM device data linked with EHR (from 2015-2020) for a large national cohort of diabetes patients. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. RESULTS: The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged three weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 hours over nearly three years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. CONCLUSIONS: The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both type 1 and type 2 patients within the Veterans Affairs Healthcare System and is similar across major race/ethnicity and age groups.

Association between Body Iron Status and Cognitive Task Performance in a Nationally Representative Sample of Older Adults.

Iron is an essential micronutrient that is necessary for proper cognitive function. However, the dose-response relationship between body iron status and cognitive function remains unclear. The objective of this study was to investigate the association between serum ferritin concentrations, an indicator of body iron status, and cognitive function in older adults. Based on the National Health and Nutrition Examination Survey (NHANES) 1999 -2002 in the United States, nationally representative data was collected from 2,567 adults aged 60 years and older who had objectively measured serum ferritin levels and cognitive performance. High ferritin levels were defined as a serum ferritin level >200 ng/mL in women and >300 ng/mL in men. Low ferritin levels were defined as a serum ferritin level <30 ng/mL. The digit symbol substitution test (DSST) was employed to assess cognitive function. Multivariable logistic regression analyses with survey weights were performed after the DSST was dichotomized at the median score. The weighted prevalence of adults with normal, low, and high serum ferritin levels were 73.98%, 9.12%, and 16.91%, respectively. A U-shaped association between serum ferritin concentrations and cognitive task performance was observed. After adjusting for demographic, socioeconomic, lifestyle, and C-reactive protein factors, the odds ratio (95% confidence intervals) for lower cognitive performance was 1.39 (1.11, 1.74) in adults with high ferritin levels and 1.38 (0.86, 2.22) in adults with low ferritin levels, compared with those with normal ferritin levels. The association between serum ferritin levels and lower cognitive performance was stronger in adults aged 60 to 69 years old than those aged 70 years and older. In conclusion, in a nationally representative sample of older adults in the United States, a high serum ferritin level was significantly associated with worse cognitive task performance. Thus, the relationship between low serum ferritin concentrations and cognitive task performance warrants further investigation.

Theoretical Insights into the Effect of Different Numbers of Thiophene Groups on Hydrogen Bond Interaction and Excited-State Intramolecular Proton-Transfer Process for Flavonoid Derivatives.

In this study, we systematically explored the impact of varying the number of thiophene groups on the hydrogen bond interaction and excited-state intramolecular proton-transfer (ESIPT) processes in flavonoid derivatives (STF, DTF, and TTF) using the density functional theory and time-dependent density functional theory methods. Initially, a thorough analysis of the optimized geometric structures revealed that the intramolecular hydrogen bond in the S1 state is enhanced and gradually weakened as the number of thiophene groups increases. To gain a deeper understanding of the hydrogen bond interaction, topological analysis, interaction region indicator scatter plots, and isosurface plots were employed. These images provide further insights that align with the structural analysis. Additionally, we observed a red-shift in the electronic spectra (absorption and fluorescence spectra), which is primarily attributed to the narrowing of the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, as elucidated by the frontier molecular orbitals. Furthermore, a combined analysis between the hole-electron distribution and the transition density matrix heat map shows that electron excitation involves the unidirectional charge-transfer mechanism. In the end, by conducting relaxed potential energy curve scans, we found that an increase in the number of thiophene groups elevates the energy barrier for ESIPT, making it more challenging for the reaction. In summary, our study underscores the vital effect of thiophene-substituted numbers in modulating the ESIPT process, which is able to provide valuable insights for the design and synthesis of desired organic fluorescent probes in the future.

Revealing mechanism of phenol-amine reaction to form humus in compost based on high-resolution liquid chromatography mass spectrometry and spectroscopy.

Humus is the stable form of carbon storage in straw compost. The phenol-amine reaction is a pathway for humus formation in straw compost. In this study, two reaction systems, GP group (pyrogallol and glycine) and GCP group (catechol, pyrogallol, and glycine), were constructed in a simulated composting environment and revealed the molecular binding mechanism of the phenol-amine reaction through spectroscopy and mass spectrometry. The results showed that phenolic self-polymerization was faster than phenol-amine reaction. Therefore, the aromatization degree of GP was 27.14 % higher than that of GCP. The phenol-amine reaction first produced fulvic acid, and then formed humus units rich in active functional group structures (i.e., phenolic hydroxyl and carboxyl groups). These units further captured small molecule compounds to form humic acid eventually. This study would provide theoretical support for exploring the humus formation process and the promotion of straw humification by adding phenol or amino acids to compost.

The effect of liver metastases on clinical efficacy of first-line programmed death-1 inhibitor plus chemotherapy in esophageal squamous cell carcinoma: A post hoc analysis of ASTRUM-007 and meta-analysis.

OBJECTIVE: To explore the efficacy of serplulimab plus chemotherapy in esophageal squamous cell carcinoma (ESCC) patients with liver metastases. METHODS: A post hoc exploratory analysis of ASTRUM-007 study was performed, focusing on the association between the liver metastases status and the clinical outcomes. A systematic literature search of electronic databases was conducted to identify eligible randomized controlled trials for the meta-analysis. Study-level pooled analyses of hazard ratios (HRs) for PFS according to liver metastases were performed. RESULTS: The post hoc analysis of ASTRUM-007 showed that although patients with liver metastases had a worse prognosis comparing with the non-liver metastases patients in both treatment arms (serplulimab plus chemotherapy arm: median PFS, 5.7 vs. 6.6 months, HR 1.57 [95% CI, 1.15-2.13]; median OS, 13.7 vs. 15.3 months, HR 1.48 [95% CI, 1.09-1.98]; placebo plus chemotherapy arm: median PFS, 4.3 vs. 5.5 months, HR 1.58 [95% CI, 1.01-2.39]; median OS, 10.3 vs. 11.2 months, HR 1.32 [95% CI, 0.84-2.00]), OS and PFS benefits derived from serplulimab plus chemotherapy versus placebo plus chemotherapy in this study were observed in both patients with liver metastases (HR of PFS: 0.60; 95% CI, 0.37-0.97; HR of OS: 0.68; 95% CI, 0.43-1.11) and the non-liver metastases patients (HR of PFS: 0.62; 95% CI, 0.49-0.80; HR of OS: 0.69; 95% CI, 0.55-0.87) with similar magnitude. Three randomized controlled trials were included in the meta-analysis. Pooled HRs demonstrated that the addition of anti-PD-1 antibodies significantly improved PFS compared to chemotherapy alone regardless of liver metastases status. CONCLUSIONS: This study reveals that the presence of liver metastases is a poor prognostic factor but does not affect the improvements in both PFS and OS brought by adding PD-1 blockade to chemotherapy in ESCC patients. Predictive biomarkers for survival in these patients warrant further investigation.

Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method.

Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using 'off-the-shelf' products, such as allogeneic CAR natural killer T (AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced AlloCAR-NKT cells with high yield and purity. We generated AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of AlloCAR-NKT cells support their potential for clinical translation.

Fabrication of SERS composite substrates using Ag nanotriangles-modified SiO2 photonic crystal and the application of malachite green detection.

A novel surface-enhanced Raman scattering (SERS) composite substrates on the basis of Ag triangular nanoplates(Ag TNPs)-modified SiO2 photonic crystals (PC) is fabricated and applied to the SERS detection of malachite green (MG). It consists of uniformly arranged Ag TNP@SiO2, a new PC. Notably, Ag TNP are uniformly aligned on the SiO2 surface, forming a three-dimensional high-density hotspot nanostructure. With the tip "hot spots" of Ag TNPs, Bragg diffraction of SiO2 and coupling enhancement between Ag TNPs and SiO2, the SERS enhancement of this composite substrates was multiplied. The effect on the SERS of Ag TNP@SiO2 composite substrate was systematically optimized by tuning Ag TNP size, size of SiO2 microspheres, coverage of Ag TNPs on SiO2 and fabrication method of Ag TNPs and PC. Moreover, the uniform of SERS composite substrates and Raman signal was dramatically increased by the method of vertical deposition. Eventually, the SERS composite substrates were employed in MG detection. Its broad detection range of 1 pM-1 µM and low limit of detection (LOD) of 0.49 pM indicated acceptable sensitivity and repeatability. This work illustrates the promising applicability in food safety analysis based on SERS composite substrates composed by Ag TNP@SiO2 with numerous SERS enhancements and excellent stability.

Exosomes derived from HUVECs alleviate ischemia-reperfusion induced inflammation in neural cells by upregulating KLF14 expression.

Neuroinflammation plays a key role in the progression of secondary brain injury after ischemic stroke, and exosomes have been increasingly recognized to eliminate inflammatory responses through various mechanisms. This study aimed to explore the effect and possible mechanism of human umbilical vein endothelial cells derived exosomes (H-EXOs) on neuroinflammation. We established a transient middle cerebral artery occlusion/reperfusion (tMCAO/R) in male rats and oxygen-glucose-deprivation/reoxygenation (OGD/R) model in cultured neurons to mimic secondary brain injury after ischemic stroke in vivo. H-EXOs were administered at the same time of reperfusion. Results showed that the production of pro-inflammatory cytokines TNF-α, IL-1ß, and IL-6, and the transcription factor Krüppel-like factor 14 (KLF14) were significantly increased both in rat brain tissue and cultured neural cells after ischemic-reperfusion (I/R) injury. H-EXOs treatment significantly improved the cultured cell viability, reduced infarct sizes, mitigated neurobehavioral defects, and alleviated the expression of pro-inflammatory cytokines compared with the control group, indicating that H-EXOs exerted anti-inflammatory effect against I/R injury. Further studies revealed that the anti-inflammatory effect of H-EXOs could be weakened by small-interfering RNA (siKLF4) transfection. KLF14 was a protective factor produced during cerebral ischemia-reperfusion injury. In conclusion, H-EXOs protect neurons from inflammation after I/R injury by enhancing KLF14 expression.

Palladium-Catalyzed Ligand-Controlled Switchable Hetero-(5 + 3)/Enantioselective [2σ+2σ] Cycloadditions of Bicyclobutanes with Vinyl Oxiranes.

For nearly 60 years, significant research efforts have been focused on developing strategies for the cycloaddition of bicyclobutanes (BCBs). However, higher-order cycloaddition and catalytic asymmetric cycloaddition of BCBs have been long-standing formidable challenges. Here, we report Pd-catalyzed ligand-controlled, tunable cycloadditions for the divergent synthesis of bridged bicyclic frameworks. The dppb ligand facilitates the formal (5+3) cycloaddition of BCBs and vinyl oxiranes, yielding valuable eight-membered ethers with bridged bicyclic scaffolds in 100% regioselectivity. The Cy-DPEphos ligand promotes selective hetero-[2σ+2σ] cycloadditions to access pharmacologically important 2-oxabicyclo[3.1.1]heptane (O-BCHeps). Furthermore, the corresponding catalytic asymmetric synthesis of O-BCHeps with 94-99% ee has been achieved using chiral (S)-DTBM-Segphos, representing the first catalytic asymmetric cross-dimerization of two strained rings. The obtained O-BCHeps are promising bioisosteres for ortho-substituted benzenes.

Influence of atomic electronegativity on ESIPT behaviour for the BTDI and its derivatives: Theoretical exploration.

In this work, we theoretically explored the influence of atomic electronegativity on excited-state intramolecular proton transfer (ESIPT) behavior among novel fluorescent probes BTDI and its derivatives (BODI and BSeDI). A thorough examination of the optimized structural parameters and infrared vibrational spectra reveals an enhancement in intramolecular hydrogen bonding within BTDI and its derivatives upon light excitation. This finding is further reinforced by topological analysis and interaction region indicator scatter plots, which underscores the sensitivity of atomic electronegativity to variations in hydrogen bonding strength. With regards to absorption and fluorescence spectra, the decrease in atomic electronegativity leads to a pronounced redshift, primarily attributed to the narrowing of the energy gap. Additionally, an analysis of potential energy curves and the exploration of intrinsic reaction coordinate paths based on transition state structures afford a deeper understanding of the mechanism underlying ESIPT and being modulated through the manipulation of atomic electronegativity. We anticipate that this work on atomic electronegativity regulating ESIPT behavior will serve as a catalyst for novel fluorescent probes in the future, offering fresh perspectives and insights.

Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold.

Out-of-distribution (OOD) detection is crucial for enhancing the reliability of machine learning models when confronted with data that differ from their training distribution. In the image domain, we hypothesize that images inhabit manifolds defined by latent properties such as color, position, and shape. Leveraging this intuition, we propose a novel approach to OOD detection using a diffusion model to discern images that deviate from the in-domain distribution. Our method involves training a diffusion model using in-domain images. At inference time, we lift an image from its original manifold using a masking process, and then apply a diffusion model to map it towards the in-domain manifold. We measure the distance between the original and mapped images, and identify those with a large distance as OOD. Our experiments encompass comprehensive evaluation across various datasets characterized by differences in color, semantics, and resolution. Our method demonstrates strong and consistent performance in detecting OOD images across the tested datasets, highlighting its effectiveness in handling images with diverse characteristics. Additionally, ablation studies confirm the significant contribution of each component in our framework to the overall performance.

Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP).

OBJECTIVE: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS: T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS: Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.