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Although individual genomic structural variants (SVs) are known to influence gene expression and trait variation, the extent and scale of SV impact across a species remain unknown. In the present study, we constructed a reference library of 334,461 SVs from genome assemblies of 16 representative morphotypes of neopolyploid Brassica napus accessions and detected 258,865 SVs in 2,105 resequenced genomes. Coupling with 5 tissue population transcriptomes, we uncovered 285,976 SV-expression quantitative trait loci (eQTLs) that associate with altered expression of 73,580 genes. We developed a pipeline for the high-throughput joint analyses of SV-genome-wide association studies (SV-GWASs) and transcriptome-wide association studies of phenomic data, eQTLs and eQTL-GWAS colocalization, and identified 726 SV-gene expression-trait variation associations, some of which were verified by transgenics. The pervasive SV impact on how SV reshapes trait variation was demonstrated with the glucosinolate biosynthesis and transport pathway. The study highlighting the impact of genome-wide and species-scale SVs provides a powerful methodological strategy and valuable resources for studying evolution, gene discovery and breeding.

Alcohol use disorder (AUD) is frequently comorbid with anxiety disorders, yet whether alcohol abuse precedes or follows the expression of anxiety remains unclear. Rodents offer control over the first drink, an advantage when testing the causal link between anxiety and AUD. Here, we utilized a risk-avoidance task to determine anxiety-like behaviors before and after alcohol exposure. We found that alcohols anxiolytic efficacy varied among inbred mice and mice with high risk-avoidance showed heightened alcohol relief. While dopamine D1 receptors in the striatum are required for alcohols relief, their levels alone were not correlated with relief. Rather, the ratio between striatal D1 and D2 receptors was a determinant factor for risk-avoidance and alcohol relief. We show that increasing striatal D1 to D2 receptor ratio was sufficient to promote risk-avoidance and enhance alcohol relief, even at initial exposure. Mice with high D1 to D2 receptor ratio were more prone to continue drinking despite adverse effects, a hallmark of AUD. These findings suggest that an anxiety phenotype may be a predisposing factor for AUD.

The dog, Canis lupus familiaris, is an important model for studying human diseases. Unlike many model organisms, the dog genome has a comparatively poor functional annotation, which hampers gene discovery for development, morphology, disease, and behavior. To fill this gap, we established a comprehensive tissue biobank for both the dog and wolf samples. The biobank consists of 5485 samples representing 132 tissues from 13 dogs, 12 dog embryos, and 24 wolves. In a subset of 100 tissues from nine dogs and 12 embryos, we characterized gene expression activity for each promoter, including alternative and novel, i.e., previously not annotated, promoter regions, using the 5 targeting RNA sequencing technology STRT2-seq. We identified over 100,000 promoter region candidates in the recent canine genome assembly, CanFam4, including over 45,000 highly reproducible sites with gene expression and respective tissue enrichment levels. We provide a promoter and gene expression atlas with interactive, open data resources, including a data coordination center and genome browser track hubs. We demonstrated the applicability of Dog Genome Annotation (DoGA) data and resources using multiple examples spanning canine embryonic development, morphology and behavior, and diseases across species.

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

AIMS: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes. However, most HF patients are not hospitalized, and manual review of big electronic health record (EHR) data is not practical. The US Department of Veterans Affairs (VA) has the largest integrated healthcare system in the nation, and an estimated 1.5 million patients have ICD codes for HF (HF ICD-code universe) in their VA EHR. The objective of our study was to develop artificial intelligence (AI) models to phenotype HF in these patients. METHODS AND RESULTS: The model development cohort (n = 20 000: training, 16 000; validation 2000; testing, 2000) included 10 000 patients with HF and 10 000 without HF who were matched by age, sex, race, inpatient/outpatient status, hospital, and encounter date (within 60 days). HF status was ascertained by manual chart reviews in VAs External Peer Review Program for HF (EPRP-HF) and non-HF status was ascertained by the absence of ICD codes for HF in VA EHR. Two clinicians annotated 1000 random snippets with HF-related keywords and labelled 436 as HF, which was then used to train and test a natural language processing (NLP) model to classify HF (positive predictive value or PPV, 0.81; sensitivity, 0.77). A machine learning (ML) model using linear support vector machine architecture was trained and tested to classify HF using EPRP-HF as cases (PPV, 0.86; sensitivity, 0.86). From the HF ICD-code universe, we randomly selected 200 patients (gold standard cohort) and two clinicians manually adjudicated HF (gold standard HF) in 145 of those patients by chart reviews. We calculated NLP, ML, and NLP + ML scores and used weighted F scores to derive their optimal threshold values for HF classification, which resulted in PPVs of 0.83, 0.77, and 0.85 and sensitivities of 0.86, 0.88, and 0.83, respectively. HF patients classified by the NLP + ML model were characteristically and prognostically similar to those with gold standard HF. All three models performed better than ICD code approaches: one principal hospital discharge diagnosis code for HF (PPV, 0.97; sensitivity, 0.21) or two primary outpatient encounter diagnosis codes for HF (PPV, 0.88; sensitivity, 0.54). CONCLUSIONS: These findings suggest that NLP and ML models are efficient AI tools to phenotype HF in big EHR data to create contemporary HF registries for clinical studies of effectiveness, quality improvement, and hypothesis generation.

Mycobacterium tuberculosis (Mtb) releases the unusual terpene nucleoside 1-tuberculosinyladenosine (1-TbAd) to block lysosomal function and promote survival in human macrophages. Using conventional approaches, we found that genes Rv3377c and Rv3378c, but not Rv3376, were necessary for 1-TbAd biosynthesis. Here, we introduce linear models for mass spectrometry (limms) software as a next-generation lipidomics tool to study the essential functions of lipid biosynthetic enzymes on a whole-cell basis. Using limms, whole-cell lipid profiles deepened the phenotypic landscape of comparative mass spectrometry experiments and identified a large family of approximately 100 terpene nucleoside metabolites downstream of Rv3378c. We validated the identity of previously unknown adenine-, adenosine-, and lipid-modified tuberculosinol-containing molecules using synthetic chemistry and collisional mass spectrometry, including comprehensive profiling of bacterial lipids that fragment to adenine. We tracked terpene nucleoside genotypes and lipid phenotypes among Mycobacterium tuberculosis complex (MTC) species that did or did not evolve to productively infect either human or nonhuman mammals. Although 1-TbAd biosynthesis genes were thought to be restricted to the MTC, we identified the locus in unexpected species outside the MTC. Sequence analysis of the locus showed nucleotide usage characteristic of plasmids from plant-associated bacteria, clarifying the origin and timing of horizontal gene transfer to a pre-MTC progenitor. The data demonstrated correlation between high level terpene nucleoside biosynthesis and mycobacterial competence for human infection, and 2 mechanisms of 1-TbAd biosynthesis loss. Overall, the selective gain and evolutionary retention of tuberculosinyl metabolites in modern species that cause human TB suggest a role in human TB disease, and the newly discovered molecules represent candidate disease-specific biomarkers.

INTRODUCTION: In trials of amyloid-lowering drugs for Alzheimers disease (AD), differential eligibility may contribute to under-inclusion of racial and ethnic underrepresented groups. We examined plasma amyloid beta 42/40 and positron emission tomography (PET) amyloid eligibility for the ongoing AHEAD Study preclinical AD program (NCT04468659). METHODS: Univariate logistic regression models were used to examine group differences in plasma and PET amyloid screening eligibility. RESULTS: Of 4905 participants screened at time of analysis, 1724 were plasma eligible to continue in screening: 13.3% Hispanic Black, 24.7% Hispanic White, 20.8% non-Hispanic (NH) Asian, 24.7% NH Black, and 38.9% NH White. Plasma eligibility differed across groups in models controlling for covariates (odds ratio from 1.9 to 4.0 compared to the NH White reference group, P

Two of every three persons living with dementia reside in low- and middle-income countries (LMICs). The projected increase in global dementia rates is expected to affect LMICs disproportionately. However, the majority of global dementia care costs occur in high-income countries (HICs), with dementia research predominantly focusing on HICs. This imbalance necessitates LMIC-focused research to ensure that characterization of dementia accurately reflects the involvement and specificities of diverse populations. Development of effective preventive, diagnostic, and therapeutic approaches for dementia in LMICs requires targeted, personalized, and harmonized efforts. Our article represents timely discussions at the 2022 Symposium on Dementia and Brain Aging in LMICs that identified the foremost opportunities to advance dementia research, differential diagnosis, use of neuropsychometric tools, awareness, and treatment options. We highlight key topics discussed at the meeting and provide future recommendations to foster a more equitable landscape for dementia prevention, diagnosis, care, policy, and management in LMICs. HIGHLIGHTS: Two-thirds of persons with dementia live in LMICs, yet research and costs are skewed toward HICs. LMICs expect dementia prevalence to more than double, accompanied by socioeconomic disparities. The 2022 Symposium on Dementia in LMICs addressed advances in research, diagnosis, prevention, and policy. The Nairobi Declaration urges global action to enhance dementia outcomes in LMICs.

Objective. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.Approach. We introduced PyHFO, which enables time-efficient high-frequency oscillation (HFO) detection algorithms like short-term energy and Montreal Neurological Institute and Hospital detectors. It incorporates DL models for artifact and HFO with spike classification, designed to operate efficiently on standard computer hardware.Main results. The validation of PyHFO was conducted on three separate datasets: the first comprised solely of grid/strip electrodes, the second a combination of grid/strip and depth electrodes, and the third derived from rodent studies, which sampled the neocortex and hippocampus using depth electrodes. PyHFO demonstrated an ability to handle datasets efficiently, with optimization techniques enabling it to achieve speeds up to 50 times faster than traditional HFO detection applications. Users have the flexibility to employ our pre-trained DL model or use their EEG data for custom model training.Significance. PyHFO successfully bridges the computational challenge faced in applying DL techniques to EEG data analysis in epilepsy studies, presenting a feasible solution for both clinical and research settings. By offering a user-friendly and computationally efficient platform, PyHFO paves the way for broader adoption of advanced EEG data analysis tools in clinical practice and fosters potential for large-scale research collaborations.

Tissue engineering can provide in vitro models for drug testing, disease modeling, and perhaps someday, tissue/organ replacements. For building 3D heart tissue, the alignment of cardiac cells or cardiomyocytes (CMs) is important in generating a synchronously contracting tissue. To that end, researchers have generated several fabrication methods for building heart tissue, but direct comparisons of pros and cons using the same cell source is lacking. Here, we derived cardiomyocytes (CMs) from human induced pluripotent stem cells (hiPSCs) and compare the assembly of these cells using three fabrication methods: cardiospheres, muscle rings, and muscle strips. All three protocols successfully generated compacted tissue comprised of hiPSC-derived CMs stable for at least 2 weeks. The percentage of aligned cells was greatest in the muscle strip (55%) and the muscle ring (50%) compared with the relatively unaligned cardiospheres (35%). The iPSC-derived CMs within the muscle strip also exhibited the greatest elongation, with elongation factor at 2.0 compared with 1.5 for the muscle ring and 1.2 for the cardiospheres. This is the first direct comparison of various fabrication techniques using the same cell source.

BackgroundUnderstanding the characteristics of multiparametric MRI (mpMRI) in patients from different racial/ethnic backgrounds is important for reducing the observed gaps in clinical outcomes.PurposeTo investigate the diagnostic performance of mpMRI and quantitative MRI parameters of prostate cancer (PCa) in African American (AA) and matched White (W) men.Study typeRetrospective.SubjectsOne hundred twenty-nine patients (43 AA, 86 W) with histologically proven PCa who underwent mpMRI before radical prostatectomy.Field strength/sequence3.0 T, T2-weighted turbo spin echo imaging, a single-shot spin-echo EPI sequence diffusion-weighted imaging, and a gradient echo sequence dynamic contrast-enhanced MRI with an ultrafast 3D spoiled gradient-echo sequence.AssessmentThe diagnostic performance of mpMRI in AA and W men was assessed using detection rates (DRs) and positive predictive values (PPVs) in zones defined by the PI-RADS v2.1 prostate sector map. Quantitative MRI parameters, including Ktrans and ve of clinically significant (cs) PCa (Gleason score ≥ 7) tumors were compared between AA and W sub-cohorts after matching age, prostate-specific antigen (PSA), and prostate volume.Statistical testsWeighted Pearson's chi-square and Mann-Whitney U tests with a statistically significant level of 0.05 were used to examine differences in DR and PPV and to compare parameters between AA and matched W men, respectively.ResultsA total number of 264 PCa lesions were identified in the study cohort. The PPVs in the peripheral zone (PZ) and posterior prostate of mpMRI for csPCa lesions were significantly higher in AA men than in matched W men (87.8% vs. 68.1% in PZ, and 89.3% vs. 69.6% in posterior prostate). The Ktrans of index csPCa lesions in AA men was significantly higher than in W men (0.25 ± 0.12 vs. 0.20 ± 0.08 min-1; P

UNLABELLED: A comprehensive microbial surveillance was conducted at NASAs Mars 2020 spacecraft assembly facility (SAF), where whole-genome sequencing (WGS) of 110 bacterial strains was performed. One isolate, designated 179-BFC-A-HST, exhibited less than 80% average nucleotide identity (ANI) to known species, suggesting a novel organism. This strain demonstrated high-level resistance [minimum inhibitory concentration (MIC) >256 mg/L] to third-generation cephalosporins, including ceftazidime, cefpodoxime, combination ceftazidime/avibactam, and the fourth-generation cephalosporin cefepime. The results of a comparative genomic analysis revealed that 179-BFC-A-HST is most closely related to Virgibacillus halophilus 5B73CT, sharing an ANI of 78.7% and a digital DNA-DNA hybridization (dDDH) value of 23.5%, while their 16S rRNA gene sequences shared 97.7% nucleotide identity. Based on these results and the recent recognition that the genus Virgibacillus is polyphyletic, strain 179-BFC-A-HST is proposed as a novel species of a novel genus, Tigheibacillus jepli gen. nov., sp. nov (type strain 179-BFC-A-HST = DSM 115946T = NRRL B-65666T), and its closest neighbor, V. halophilus, is proposed to be reassigned to this genus as Tigheibacillus halophilus comb. nov. (type strain 5B73CT = DSM 21623T = JCM 21758T = KCTC 13935T). It was also necessary to reclassify its second closest neighbor Virgibacillus soli, as a member of a novel genus Paracerasibacillus, reflecting its phylogenetic position relative to the genus Cerasibacillus, for which we propose Paracerasibacillus soli comb. nov. (type strain CC-YMP-6T = DSM 22952T = CCM 7714T). Within Amphibacillaceae (n = 64), P. soli exhibited 11 antibiotic resistance genes (ARG), while T. jepli encoded for 3, lacking any known β-lactamases, suggesting resistance from variant penicillin-binding proteins, disrupting cephalosporin efficacy. P. soli was highly resistant to azithromycin (MIC >64 mg/L) yet susceptible to cephalosporins and penicillins. IMPORTANCE: The significance of this research extends to understanding microbial survival and adaptation in oligotrophic environments, such as those found in SAF. Whole-genome sequencing of several strains isolated from Mars 2020 mission assembly cleanroom facilities, including the discovery of the novel species Tigheibacillus jepli, highlights the resilience and antimicrobial resistance (AMR) in clinically relevant antibiotic classes of microbes in nutrient-scarce settings. The study also redefines the taxonomic classifications within the Amphibacillaceae family, aligning genetic identities with phylogenetic data. Investigating ARG and virulence factors (VF) across these strains illuminates the microbial capability for resistance under resource-limited conditions while emphasizing the role of human-associated VF in microbial survival, informing sterilization practices and microbial management in similar oligotrophic settings beyond spacecraft assembly cleanrooms such as pharmaceutical and medical industry cleanrooms.

Background: Hepatocellular carcinoma (HCC) is the most common type of liver cancer, with 10-40% of cases involving portal vein tumor thrombosis (PVTT), leading to poor outcomes and a short survival. The effectiveness of PVTT treatment in patients with HCC is still controversial. Methods: This prospective dual-center study cohort comprised 60 patients with HCC and PVTT who underwent PVR-EPRFA-ST using a novel intravascular radiofrequency system followed by vascular stent placement across the PVTT stenosed segment under fluoroscopy guidance. Results: PVR-EPRFA-ST was technically and clinically successful in 54/60 (90%) and 37/54 (68.5%) patients, respectively. The mean tumor size, PVTT length, post-ablation luminal diameter, and median duration of the recanalized PV patency were 8.6 ± 3.4 cm, 4.1 ± 2.1 cm, 10.3 ± 1.8 mm, and 13.4 months. Higher technical and clinical success rates were associated with a longer survival (177 ± 17.3 days, HR: 0.3, 95%CI 0.12-0.71, p = 0.04; and 233 ± 18.3 days, HR: 0.14, 0.07-0.27, p < 0.001). A shorter survival was associated with Child-Pugh C (HR: 2.7, p = 0.04), multiple tumors (HR: 1.81, p = 0.03), and PVTT length (HR: 1.16, p = 0.04). Conclusions: PVR-EPRFA-ST was feasible and effective for the treatment of selected patients with PVTT, especially in patients with Child-Pugh A/B, single tumors, or a shorter PVTT length.

Multi-parametric MRI (mpMRI) is widely used for prostate cancer (PCa) diagnosis. Deep learning models show good performance in detecting PCa on mpMRI, but domain-specific PCa-related anatomical information is sometimes overlooked and not fully explored even by state-of-the-art deep learning models, causing potential suboptimal performances in PCa detection. Symmetric-related anatomical information is commonly used when distinguishing PCa lesions from other visually similar but benign prostate tissue. In addition, different combinations of mpMRI findings are used for evaluating the aggressiveness of PCa for abnormal findings allocated in different prostate zones. In this study, we investigate these domain-specific anatomical properties in PCa diagnosis and how we can adopt them into the deep learning framework to improve the models detection performance. We propose an anatomical-aware PCa detection Network (AtPCa-Net) for PCa detection on mpMRI. Experiments show that the AtPCa-Net can better utilize the anatomical-related information, and the proposed anatomical-aware designs help improve the overall model performance on both PCa detection and patient-level classification.

IntroductionUrology residency prepares trainees for independent practice. The optimal operative chief resident year experience to prepare for practice is undefined. We analyzed the temporal arc of cases residents complete during their residency compared to their chief year in a multi-institutional cohort.MethodsAccreditation Council for Graduate Medical Education case logs of graduating residents from 2010 to 2022 from participating urology residency programs were aggregated. Resident data for 5 categorized index procedures were recorded: (1) general urology, (2) endourology, (3) reconstructive urology, (4) urologic oncology, and (5) pediatric urology. Interactions were tested between the trends for total case exposure in residency training relative to the chief resident year.ResultsFrom a sample of 479 resident graduates, a total of 1,287,433 total cases were logged, including 375,703 during the chief year (29%). Urologic oncology cases had the highest median percentage completed during chief year (56%) followed by reconstructive urology (27%), general urology (24%), endourology (17%), and pediatric urology (2%). Across the study period, all categories of cases had a downward trend in median percentage completed during chief year except for urologic oncology. However, only trends in general urology (slope of -0.68, P = .013) and endourology (slope of -1.71, P ≤ .001) were significant.ConclusionsOver 50% of cases completed by chief residents are urologic oncology procedures. Current declining trends indicate that residents are being exposed to proportionally fewer general urology and endourology cases during their chief year prior to entering independent practice.

BackgroundMultiparametric MRI (mpMRI) has shown a substantial impact on prostate cancer (PCa) diagnosis. However, the understanding of the spatial correlation between mpMRI performance and PCa location is still limited.PurposeTo investigate the association between mpMRI performance and tumor spatial location within the prostate using a prostate sector map, described by Prostate Imaging Reporting and Data System (PI-RADS) v2.1.Study typeRetrospective.SubjectsOne thousand one hundred forty-three men who underwent mpMRI before radical prostatectomy between 2010 and 2022.Field strength/sequence3.0 T. T2-weighted turbo spin-echo, a single-shot spin-echo EPI sequence for diffusion-weighted imaging, and a gradient echo sequence for dynamic contrast-enhanced MRI sequences.AssessmentIntegrated relative cancer prevalence (rCP), detection rate (DR), and positive predictive value (PPV) maps corresponding to the prostate sector map for PCa lesions were created. The relationship between tumor location and its detection/missing by radiologists on mpMRI compared to WMHP as a reference standard was investigated.Statistical testsA weighted chi-square test was performed to examine the statistical differences for rCP, DR, and PPV of the aggregated sectors within the zone, anterior/posterior, left/right prostate, and different levels of the prostate with a statistically significant level of 0.05.ResultsA total of 1665 PCa lesions were identified in 1143 patients, and from those 1060 lesions were clinically significant (cs)PCa tumors (any Gleason score [GS] ≥7). Our sector-based analysis utilizing weighted chi-square tests suggested that the left posterior part of PZ had a high likelihood of missing csPCa lesions at a DR of 67.0%. Aggregated sector analysis indicated that the anterior or apex locations in PZ had the significantly lowest csPCa detection at 67.3% and 71.5%, respectively.Data conclusionSpatial characteristics of the per-lesion-based mpMRI performance for diagnosis of PCa were studied. Our results demonstrated that there is a spatial correlation between mpMRI performance and locations of PCa on the prostate.Evidence level4 TECHNICAL EFFICACY: Stage 2.

Opinion statementPSMA-PET has been a practice-changing imaging biomarker for the management of men with PCa. Research suggests improved accuracy over conventional imaging and other PET radiotracers in many contexts. With multiple approved PSMA-targeting radiotracers, PSMA PET will become even more available in clinical practice. Its increased use requires an understanding of the prospective data available and caution when extrapolating from prior trial data that utilized other imaging modalities. Future trials leveraging PSMA PET for treatment optimization and management decision-making will ultimately drive its clinical utility.

284 Background: Multiparametric MRI (mpMRI) and PSMA-PET are complementary imaging modalities used in the pre-surgical evaluation of patients with prostate cancer (PCa). The aim of this study was to evaluate the imaging and pathology parameters associated with PSMA-PET and mpMRI disagreement with each other and with gold standard histopathology. Methods: Patients undergoing radical prostatectomy (RP) with pre-surgical PSMA-PET and mpMRI were screened for inclusion in this retrospective analysis. Patients had the imaging scans done 3, n=153). mpMRI and PSMA PET identified 138 and 170 lesions, respectively. Sensitivity for ISUP>3 lesions was 79% and 87% for mpMRI and PSMA-PET, respectively. 115/153 (76%) ISUP> 3 lesions were correctly identified, and 14/153 (9%) were missed by both imaging modalities, respectively. 5/153 (3%) were correctly identified by mpMRI and missed by PSMA-PET, 17/153 (11%) were correctly identified by PSMA-PET and missed by mpMRI. Lesion’s ISUP grade group and size on pathology were significantly lower in mpMRI- compared to mpMRI+ and in PET- compared to PET+ lesions. SUVmax and SUVmean were significantly higher in PET+/MRI+ than PET+/MRI- lesions. Lesion’s ISUP grade group and size were significantly correlated to PSMA-PET and mpMRI agreement, whereas PSMA-PET metrics were not. Logistic regression model showed that lesions with lower ISUP, smaller size, and lack of aggressive prostate cancer features on pathology (cribriform pattern and intraductal carcinoma) have higher likelihood of being missed by PET and mpMRI and of PET/MRI disagreement. Conclusions: Higher SUVmax, SUVmean, and tumor volume on PSMA-PET were associated with a TP finding on PSMA-PET, higher ISUP grade group and size on pathology were associated with a TP finding on both PSMA-PET and mpMRI, and with agreement between PSMA-PET and mpMRI.

Background and study aims The Bethesda ERCP Skill Assessment Tool (BESAT) is a video-based assessment tool of technical endoscopic retrograde cholangiopancreatography (ERCP) skill with previously established validity evidence. We aimed to assess the discriminative validity of the BESAT in differentiating ERCP skill levels. Methods Twelve experienced ERCP practitioners from tertiary academic centers were asked to blindly rate 43 ERCP videos using the BESAT. ERCP videos consisted of native biliary cannulation and sphincterotomy and were recorded from 10 unique endoscopists of various ERCP experience (from advanced endoscopy fellow to > 10 years of ERCP experience). Inter-rater reliability, discriminative validity, and internal structure validity were subsequently assessed. Results The BESAT was found to reliably differentiate between endoscopists of varying levels of ERCP experience with experienced ERCPists scoring higher than novice ERCPists in 11 of 13 (85%) instrument items. Inter-rater reliability for BESAT items ranged from good to excellent (intraclass correlation range: 0.86 to 0.93). Internal structure validity was assessed with item-total correlations ranging from 0.53 to 0.83. Conclusions Study findings demonstrate that the BESAT, a video-based ERCP skill assessment tool, has high inter-rater reliability and has discriminative validity in differentiating novice from expert ERCP skill. Further investigations are needed to determine the role of video-based assessment in improving trainee learning curves and patient outcomes.

BackgroundMany cognitively unimpaired older adults are interested in learning their Alzheimer's disease (AD) biomarker status, but little is known about motivations to undergo biomarker testing and result disclosure in the setting of preclinical AD trials.ObjectivesExamine whether motivations to undergo AD biomarker testing and disclosure differ for individuals who have elevated amyloid compared to those with not elevated amyloid, and whether disclosure of amyloid results impacts participants' motivations.Design, setting, participantsWe conducted post-hoc analyses using data from the EARLY study, a preclinical AD trial of the beta-secretase inhibitor atabecestat. As part of the screening process of the trial, participants underwent biomarker testing and disclosure. We analyzed data from n=2241 participants.MeasurementsWe analyzed data from the Views and Perceptions of Amyloid Imaging (VPAI), a 9-item questionnaire assessing how strongly participants agreed with motivating factors for undergoing amyloid testing. The VPAI was administered at the first screening visit and again after amyloid disclosure.ResultsPrior to amyloid disclosure, a greater proportion of participants in the elevated amyloid group responded at the two highest levels of endorsement for the items, "to confirm the feeling that I might already be developing symptoms of AD dementia" (p

BACKGROUND: Advances in plasma biomarkers to detect Alzheimers disease (AD) biology allows researchers to improve the efficiency of participant recruitment into preclinical trials. Recently, protein levels of plasma amyloid-beta and tau proteins have been shown to be predictive of elevated amyloid in brain. Online registries, such as the Alzheimers Prevention Trials (APT) Webstudy, include and follow participants using remote assessments to facilitate efficient screening and enrollment of large numbers of individuals who may be at higher risk for AD. OBJECTIVES: The AlzMatch Pilot Study investigated the feasibility of recruiting individuals from an online registry for blood sample collection at community-based phlebotomy centers and plasma biomarker quantification to assess an individuals eligibility for AD preclinical trials. DESIGN: Pilot feasibility study with co-primary outcomes. SETTING: This pilot feasibility study included participants from the APT Webstudy, the remote assessment arm of the Trial-ready cohort for Preclinical and Prodromal AD (TRC-PAD) Platform. Novel design included collection of electronic consent, use of community laboratories for plasma collection, mass spectrometry-based biomarker assay, and telephone communication of plasma biomarker screening eligibility. PARTICIPANTS: Participants invited to the AlzMatch pilot feasibility study were active in the APT Webstudy, 50 years of age or older, resided within 50 miles of both a Quest Diagnostics Patient Services Center (a national diagnostic laboratory with convenient locations for sample collection and processing) and one of six TRC-PAD vanguard clinical trial sites, had no self-reported dementia diagnosis, were able to communicate in English and engaged with the APT Webstudy within the prior 6 months. MEASUREMENTS: Primary feasibility outcomes were completion of electronic consent (e-consent) for invited participants and collection of usable blood samples. Additional feasibility outcomes included invitation response rate, plasma biomarker eligibility status (based on amyloid beta-42/40 [Aβ42/40] concentration ratio), ApoE proteotype, and trial inclusion criterion), and completion of telephone contact to learn eligibility to screen for a study. RESULTS: 300 APT Webstudy participants were invited to consent to the AlzMatch study. The AlzMatch e-consent rate was 39% (n=117) (95% CI of 33.5%-44.5%) overall, which was higher than the expected rate of 25%. Similar consent rates were observed across participants based on self-defined sex (41% Female (n=75), 37% Male (n=42)) and race and ethnicity (37% from underrepresented groups (URG) (n=36), 40% not from URG (n=79)). Among those that consented (n=117), plasma was successfully collected from 74% (n=87) (95% CI of 66%-82%), with similar rates across sex (76% Female (n=57), 71% Male (n=30)) and race and ethnicity (75% URG (n=27) and 75% not from URG (n=59)). 60% (n=51) of participants with plasma biomarker results were eligible to screen for future preclinical AD trials. CONCLUSION: Electronic consent of participants through an online registry, blood sample collection at community-based centers, plasma biomarker quantification and reporting, and biomarker assessments for study eligibility were all feasible with similar engagement rates across demographic groups. Although this pilot was a small and selective sample, participants engaged and consented at higher than expected rates. We conclude that collecting blood at community laboratories for biomarker analyses may improve accessibility beyond research, and may facilitate broader access for clinical use of AD plasma biomarkers. Based on our results, an expanded version of the AlzMatch study is underway, which involves expanding invitations to additional APT Webstudy participants and clinical trial sites.

INTRODUCTION: Metrics of a participants socioeconomic status (SES) are not routinely collected or standardized in clinical trials. This omission limits the ability to evaluate the generalizability of trial results and restricts clinicians from confidently interpreting the efficacy of new treatments across important sub-populations. METHODS: We adapted an SES measure of social disparity; the Hollingshead Two Factor Index of Social Position, which combines education and occupation into a single metric. We modernized the 1965 occupations to reflect the 2017 careers tabulated by the US Bureau of Labor Statistics. We currently use this adapted measure in Alzheimers Clinical Trials Consortium studies. RESULTS: We present the revised table of occupations. We found that the collection of SES data using the modified Hollingshead was feasible in a multi-site clinical trial and scores were distributed across all SES strata. DISCUSSION: The modified Hollingshead provides a standardized method for collecting SES information, enabling data aggregation, monitoring, and reporting.

BACKGROUND: Converging evidence suggests that markers of Alzheimers disease (AD) pathology in cognitively unimpaired older individuals are associated with high risk of cognitive decline and progression to functional impairment. The Anti-Amyloid Treatment in Asymptomatic Alzheimers disease (A4) and Longitudinal Evaluation of Amyloid and Neurodegeneration Risk (LEARN) Studies enrolled a large cohort of cognitively normal older individuals across a range of baseline amyloid PET levels. Recent advances in AD blood-based biomarkers further enable the comparison of baseline markers in the prediction of longitudinal clinical outcomes. OBJECTIVES: We sought to evaluate whether biomarker indicators of higher levels of AD pathology at baseline predicted greater cognitive and functional decline, and to compare the relative predictive power of amyloid PET imaging, tau PET imaging, and a plasma P-tau217 assay. DESIGN: All participants underwent baseline amyloid PET scan, plasma P-tau217; longitudinal cognitive testing with the Primary Alzheimer Cognitive Composite (PACC) every 6 months; and annual functional assessments with the clinical dementia rating (CDR), cognitive functional index (CFI), and activities of daily living (ADL) scales. Baseline tau PET scans were obtained in a subset of participants. Participants with elevated amyloid (Aβ+) on screening PET who met inclusion/exclusion criteria were randomized to receive placebo or solanezumab in a double-blind phase of the A4 Study over 240+ weeks. Participants who did not have elevated amyloid (Aβ-) but were otherwise eligible for the A4 Study were referred to the companion observational LEARN Study with the same outcome assessments over 240+ weeks. SETTING: The A4 and LEARN Studies were conducted at 67 clinical trial sites in the United States, Canada, Japan and Australia. PARTICIPANTS: Older participants (ages 65-85) who were cognitively unimpaired at baseline (CDR-GS=0, MMSE 25-30 with educational adjustment, and Logical Memory scores within the normal range LMIIa 6-18) were eligible to continue in screening. Aβ+ participants were randomized to either placebo (n=583) or solanezumab (n=564) in the A4 Study. A subset of Aβ+ underwent tau PET imaging in A4 (n=350). Aβ- were enrolled into the LEARN Study (n=553). MEASUREMENTS: Baseline 18-F Florbetapir amyloid PET, 18-F Flortaucipir tau PET in a subset and plasma P-tau217 with an electrochemiluminescence (ECL) immunoassay were evaluated as predictors of cognitive (PACC), and functional (CDR, CFI and ADL) change. Models were evaluated to explore the impact of baseline tertiles of amyloid PET and tertiles of plasma P-tau217 on cognitive and functional outcomes in the A4 Study compared to LEARN. Multivariable models were used to evaluate the unique and common variance explained in longitudinal outcomes based on baseline predictors, including effects for age, gender, education, race/ethnic group, APOEε4 carrier status, baseline PACC performance and treatment assignment in A4 participants (solanezumab vs placebo). RESULTS: Higher baseline amyloid PET CL and P-tau217 levels were associated with faster rates of PACC decline, and increased likelihood of progression to functional impairment (CDR 0.5 or higher on two consecutive measurements), both across LEARN Aβ- and A4 Aβ+ (solanezumab and placebo arms). In analyses considering all baseline predictor variables, P-tau217 was the strongest predictor of PACC decline. Among participants in the highest tertiles of amyloid PET or P-tau217, >50% progressed to CDR 0.5 or greater. In the tau PET substudy, neocortical tau was the strongest predictor of PACC decline, but plasma P-tau217 contributed additional independent predictive variance in commonality variance models. CONCLUSIONS: In a large cohort of cognitively unimpaired individuals enrolled in a Phase 3 clinical trial and companion observational study, these findings confirm that higher baseline levels of amyloid and tau markers are associated with increased rates of cognitive decline and progression to functional impairment. Interestingly, plasma P-tau217 was the best predictor of decline in the overall sample, superior to baseline amyloid PET. Neocortical tau was the strongest predictor of cognitive decline in the subgroup with tau PET, suggesting that tau deposition is most closely linked to clinical decline. These findings indicate that biomarkers of AD pathology are useful to predict decline in an older asymptomatic population and may prove valuable in the selection of individuals for disease-modifying treatments.

BACKGROUND: Participant discontinuation from study treatment in a clinical trial can leave a trial underpowered, produce bias in statistical analysis, and limit interpretability of study results. Retaining participants in clinical trials for the full study duration is therefore as important as participant recruitment. OBJECTIVE: This analysis aims to identify associations of pre-randomization characteristics of participants with premature discontinuation during the blinded phase of the Anti-Amyloid treatment in Asymptomatic AD (A4) Study. DESIGN: All A4 trial randomized participants were classified as having prematurely discontinued study during the blinded period of the study for any reason (dropouts) or completed the blinded phase of the study on treatment (completers). SETTING: The trial was conducted across 67 study sites in the United States, Canada, Japan and Australia through the global COVID-19 pandemic. PARTICIPANTS: The sample consisted of all 1169 A4 trial randomized participants. MEASUREMENTS: Pre-randomization demographic, clinical, amyloid PET and genetic predictors of study discontinuation were evaluated using a univariate generalized linear mixed model (GLMM), with discontinuation status as the binary outcome, each predictor as a fixed effect, and site as a random effect to account for differences among study sites in the trial. Characteristics significant at p

Environmental DNA (eDNA) methods complement traditional aquatic monitoring surveys and are especially advantageous for rare and listed species to detect spatial and temporal distribution patterns. However, improvements in ease of use and portability could increase the utility of eDNA methods, leading to more widespread application, including expanding its role in management decision-making processes. We describe the development of an eDNA detection assay for delta smelt (Hypomesus transpacificus), an endangered fish in the San Francisco Estuary, using SHERLOCK (Specific High-Sensitivity Enzymatic Reporter Unlocking). SHERLOCK is a clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostic tool with the ability to detect species-specific genetic variants, making it ideal for genetic-based taxonomic identification of any organism. Because of its high sensitivity and specificity, SHERLOCK is adaptable to eDNA detection in water samples. Here, we describe adaptation of a delta smelt SHERLOCK assay for use with estuarine water eDNA samples. This version of the assay exhibits increased sensitivity compared to the original delta smelt SHERLOCK protocol (new limit of detection approximately three copies per reaction compared to ~300 in original assay) and successfully detected delta smelt eDNA in both experimental and natural contexts. Overall, our results demonstrate that SHERLOCK eDNA detection offers managers an alternative, isothermal methodology, and highlights some challenges for detection of rare, endangered species at low abundance.

PURPOSE: To evaluate the efficacy of combination therapy using transarterial chemoembolization with microwave ablation (MWA) therapy vs. MWA monotherapy for hepatocellular carcinomas (HCCs) >3 cm in size. METHODS: This two-arm retrospective observational study included patients with HCCs >3 cm who underwent either combination therapy (29 patients) or MWA monotherapy (35 patients) between 2014 and 2020. The treatment outcomes related to primary treatment efficacy, local tumor progression (LTP), tumor control rate, and overall survival were compared between each cohort. RESULTS: The technical success and primary efficacy were 96.56% and 100.00% in the combination therapy cohort, and 91.42% and 100.00% in the MWA cohort, respectively, over a mean follow-up period of 27.6 months. The 1- and 3-year rates of LTP-free survival were 78.57% and 69.56% in the combination therapy cohort, vs. 72.45% and 35.44% in the MWA cohort, respectively (P = 0.001). The overall progression-free survival was longer in the combination therapy cohort compared with the MWA cohort (median: 56.0 vs. 13.0 months; P = 0.017). With the incorporation of additional locoregional therapy, the overall survival rates were not significantly different, with 1- and 3-year overall survival rates of 100.00% and 88.71% in the combination therapy cohort and rates of 90.15% and 82.76% in the MWA cohort, respectively (P = 0.235). CONCLUSION: The combination therapy provided significantly longer upfront LTP-free survival in HCCs >3 cm when compared with the MWA treatment alone, albeit with similar local tumor control and overall survival rates when accounting for additional locoregional therapies.

ObjectiveTo characterize ictal EEG change in the centromedian (CM) and anterior nucleus (AN) of the thalamus, using stereoelectroencephalography (SEEG) recordings.MethodsForty habitual seizures were analyzed in nine patients with pediatric-onset neocortical drug-resistant epilepsy who underwent SEEG (age 2-25 y) with thalamic coverage. Both visual and quantitative analysis was used to evaluate ictal EEG signal in the cortex and thalamus. The amplitude and cortico-thalamic latencies of broadband frequencies at ictal onset were measured.ResultsVisual analysis demonstrated consistent detection of ictal EEG changes in both the CM nucleus and AN nucleus with latency to thalamic ictal EEG changes of less than 400 ms in 95% of seizures, with low-voltage fast activity being the most common ictal pattern. Quantitative broadband amplitude analysis showed consistent power changes across the frequency bands, corresponding to ictal EEG onset, while while ictal EEG latency was variable from -18.0 seconds to 13.2 seconds. There was no significant difference between detection of CM and AN ictal activity on visual or amplitude analysis. Four patients with subsequent thalamic responsive neurostimulation (RNS) demonstrated ictal EEG changes consistent with SEEG findings.ConclusionsIctal EEG changes were consistently seen at the CM and AN of the thalamus during neocortical seizures.SignificanceIt may be feasible to use a closed-loop system in the thalamus to detect and modulate seizure activity for neocortical epilepsy.

Abstract: Identifying the anisotropies in a cosmologically sourced stochastic gravitational wave background (SGWB) would be of significance in shedding light on the nature of primordial inhomogeneities.For example, if SGWB carries isocurvature fluctuations, it would provide evidence for a multi-field inflationary origin of these inhomogeneities.However, this is challenging in practice due to finite detector sensitivity and also the presence of the astrophysical foregrounds that can compete with the cosmological signal.In this work, we explore the prospects for measuring cosmological SGWB anisotropies in the presence of an astrophysical counterpart and detector noise.To illustrate the main idea, we perform a Fisher analysis using a well-motivated cosmological SGWB template corresponding to a first order phase transition,and an astrophysical SGWB template corresponding to extra-galactic binary mergers, and compute the uncertainty with which various parameters characterizing the isotropic and anisotropic components can be extracted.We also discuss some subtleties and caveats involving shot noise in the astrophysical foreground.Overall, we show that upcoming experiments, e.g., LISA, Taiji, Einstein Telescope, Cosmic Explorer, and BBO, can all be effective in discovering plausible anisotropic cosmological SGWBs.

Purpose/objective(s)Radiographic MRI response following prostate radiotherapy, particularly stereotactic body radiotherapy (SBRT), remains poorly understood. Our objective was to describe radiographic changes to the prostate gland and prostate tumor following SBRT of men treated on a prospective, randomized trial.Materials/methodsMIRAGE (NCT04384770) is a single center, randomized phase III trial of patients receiving either CT or MRI guided SBRT for localized prostate cancer. Patients underwent pre-treatment and annual post-treatment MRIs, in addition to routine PSA surveillance. Outcomes reported include percent gland shrinkage, percent PSA response at one year, and presence of residual tumor based on radiographic interpretation. Patient characteristics were compared via two-sample t-test or Fischer's exact test. Both univariate and multivariable logistical analysis were employed to identify potential clinical predictors of residual tumor on 1-year follow up MRI.ResultsThis study cohort included 94 eligible patients with baseline characteristics in Table 1. Residual lesions were seen in 13 patients (14%), 5/27 (18.5%) treated without ADT and 8/67 (12%) with ADT. PSA ablation was deep, with a 79% median decrease without ADT and 98% median decrease with ADT. Patients receiving ADT showed more gland shrinkage (17% vs. 34% shrinkage, p = 0.0001), while radiographic non-responders and responders experienced similar gland shrinkage (median 21% vs 29% shrinkage, p > 0.05). No significant clinical predictors of residual tumor were identified on univariate and multivariate analysis. No patient had any clinical or biochemical evidence of failure.ConclusionA total of 14% of patients were found to have residual tumor detected on MRI one year after SBRT. These data highlight the protracted nature of radiographic tumor response to radiation therapy, even with ablative radiation techniques. The analysis is limited by the lack of biopsy data to quantify whether visualized residual tumor harbor active cancer.

OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery. METHODS: We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for spike association and time-frequency plot characteristics. A deep learning (DL)-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method. RESULTS: The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors had the highest spike association rate. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification. CONCLUSIONS: HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs. SIGNIFICANCE: Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

Motivated by the analysis of the performance of the simplex method, we study the behavior of families of pivot rules of linear programs. We introduce normalized-weight pivot rules which are fundamental for the following reasons: First, they are memory-less, in the sense that the pivots are governed by local information encoded by an arborescence. Second, many of the most used pivot rules belong to that class, and we show this subclass is critical for understanding the complexity of all pivot rules. Finally, normalized-weight pivot rules can be parametrized in a natural continuous manner. The latter leads to the existence of two polytopes, the pivot rule polytopes and the neighbotopes, that capture the behavior of normalized-weight pivot rules on polytopes and linear programs. We explain their face structure in terms of multi-arborescences and compute upper bounds on the number of coherent arborescences, that is, vertices of our polytopes. We introduce a normalized-weight pivot rule, called the max-slope pivot rule, which generalizes the shadow-vertex pivot rule. The corresponding pivot rule polytopes and neighbotopes refine the monotone path polytopes of Billera and Sturmfels. Our constructions are important beyond optimization and provide new perspectives on classical geometric combinatorics. Special cases of our polytopes yield permutahedra, associahedra, and multiplihedra. For the greatest-improvement pivot rules we draw connections to sweep polytopes and polymatroids.

Caffeine has significant effects on neurovascular activity and behavior throughout the sleep-wake cycle. We used a minimally invasive microchip/video system to continuously record effects of caffeine in the drinking water of freely behaving mice. Chronic caffeine shifted both rest and active phases by up to 2 h relative to the light-dark cycle in a dose-dependent fashion. There was a particular delay in the onset of rapid eye movement (REM) sleep as compared with non-REM sleep during the rest phase. Chronic caffeine increased wakefulness during the active phase and consolidated sleep during the rest phase; overall, there was no net change in the amount of time spent in the wake, sleep, or REM sleep states during caffeine administration. Despite these effects on wakefulness and sleep, chronic caffeine decreased mean cerebral blood volume (CBV) during the active phase and increased mean CBV during the rest phase. Chronic caffeine also increased heart rate variability in both the sleep and wake states. These results provide new insight into the effects of caffeine on the biology of the sleep-wake cycle. Increased blood flow during sleep caused by chronic caffeine may have implications for its potential neuroprotective effects through vascular mechanisms of brain waste clearance.

Written instructions improve patient comprehension of discharge instructions but are often provided only in English even for patients with a non-English language preference (NELP). We implemented standardized written discharge instructions in English, Spanish, and Chinese for hospital medicine patients at an urban academic medical center. Using an interrupted time series analysis, we assessed the impact on medication-related postdischarge questions for patients with English, Spanish, or Chinese language preferences. Of 4013 patients, ∼15% had NELP. Preintervention, Chinese-preferring patients had a 5.6 percentage point higher probability of questions (adjusted odds ratio [aOR] = 1.55, 95% confidence interval [CI]: 1.08, 2.21) compared to English-preferring patients; Spanish-preferring and English-preferring patients had similar rates of questions. Postintervention, English-preferring and Spanish-preferring patients had no significant change; Chinese-preferring patients had a significant 10.9 percentage point decrease in the probability of questions (aOR = 0.38, 95% CI: 0.21, 0.69) thereby closing the disparity. Language-concordant written discharge instructions may reduce disparities in medication-related postdischarge questions for patients with NELP.

Purpose To investigate Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) approximations of target lesion tumor burden by comparing categorical treatment response according to conventional RECIST versus actual tumor volume measurements of RECIST target lesions. Materials and Methods This is a retrospective cohort study of individuals with metastatic renal cell carcinoma enrolled in a clinical trial (from 2003 to 2017) and includes individuals who underwent baseline and at least one follow-up chest, abdominal, and pelvic CT study and with at least one target lesion. Target lesion volume was assessed by (a) Vmodel, a spherical model of conventional RECIST 1.1, which was extrapolated from RECIST diameter, and (b) Vactual, manually contoured volume. Volumetric responses were determined by the sum of target lesion volumes (Vmodel-sum TL and Vactual-sum TL, respectively). Categorical volumetric thresholds were extrapolated from RECIST. McNemar tests were used to compare categorical volume responses. Results Target lesions were assessed at baseline (638 participants), week 9 (593 participants), and week 17 (508 participants). Vmodel-sum TL classified more participants as having progressive disease (PD), compared with Vactual-sum TL at week 9 (52 vs 31 participants) and week 17 (57 vs 39 participants), with significant overall response discordance (P < .001). At week 9, 25 (48%) of 52 participants labeled with PD by Vmodel-sum TL were classified as having stable disease by Vactual-sum TL. Conclusion A model of RECIST 1.1 based on a single diameter measurement more frequently classified PD compared with response assessment by actual measured tumor volume. Keywords: Urinary, Kidney, Metastases, Oncology, Tumor Response, Volume Analysis, Outcomes Analysis ClinicalTrials.gov registration no. NCT01865747 © RSNA, 2023 Supplemental material is available for this article.

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

INTRODUCTION: Despite growing awareness of neurodevelopmental impairments in children with congenital heart disease (CHD), there is a lack of large, longitudinal, population-based cohorts. Little is known about the contemporary neurodevelopmental profile and the emergence of specific impairments in children with CHD entering school. The performance of standardised screening tools to predict neurodevelopmental outcomes at school age in this high-risk population remains poorly understood. The NITric oxide during cardiopulmonary bypass to improve Recovery in Infants with Congenital heart defects (NITRIC) trial randomised 1371 children

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Childrens Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

BackgroundCOVID-19 forced healthcare systems to make unprecedented changes in clinical care processes. The authors hypothesized that the COVID-19 pandemic adversely impacted timely access to care, perioperative processes, and clinical outcomes for pediatric patients undergoing primary appendectomy.MethodsA retrospective, international, multicenter study was conducted using matched cohorts within participating centers of the international PEdiatric Anesthesia COVID-19 Collaborative (PEACOC). Patients younger than 18 yr old were matched using age, American Society of Anesthesiologists Physical Status, and sex. The primary outcome was the difference in hospital length of stay of patients undergoing primary appendectomy during a 2-month period early in the COVID-19 pandemic (April to May 2020) compared with prepandemic (April to May 2019). Secondary outcomes included time to appendectomy and the incidence of complicated appendicitis.ResultsA total of 3,351 cases from 28 institutions were available with 1,684 cases in the prepandemic cohort matched to 1,618 in the pandemic cohort. Hospital length of stay was statistically significantly different between the two groups: 29 h (interquartile range: 18 to 79) in the pandemic cohort versus 28 h (interquartile range: 18 to 67) in the prepandemic cohort (adjusted coefficient, 1 [95% CI, 0.39 to 1.61]; P < 0.001), but this difference was small. Eight centers demonstrated a statistically significantly longer hospital length of stay in the pandemic period than in the prepandemic period, while 13 were shorter and 7 did not observe a statistically significant difference. During the pandemic period, there was a greater occurrence of complicated appendicitis, prepandemic 313 (18.6%) versus pandemic 389 (24.1%), an absolute difference of 5.5% (adjusted odds ratio, 1.32 [95% CI, 1.1 to 1.59]; P = 0.003). Preoperative SARS-CoV-2 testing was associated with significantly longer time-to-appendectomy, 720 min (interquartile range: 430 to 1,112) with testing versus 414 min (interquartile range: 231 to 770) without testing, adjusted coefficient, 306 min (95% CI, 241 to 371; P < 0.001), and longer hospital length of stay, 31 h (interquartile range: 20 to 83) with testing versus 24 h (interquartile range: 14 to 68) without testing, adjusted coefficient, 7.0 (95% CI, 2.7 to 11.3; P = 0.002).ConclusionsFor children undergoing appendectomy, the COVID-19 pandemic did not significantly impact hospital length of stay.Editor’s perspective

The balance between neural stem cell proliferation and neuronal differentiation is paramount for the appropriate development of the nervous system. Sonic hedgehog (Shh) is known to sequentially promote cell proliferation and specification of neuronal phenotypes, but the signaling mechanisms responsible for the developmental switch from mitogenic to neurogenic have remained unclear. Here, we show that Shh enhances Ca2+ activity at the neural cell primary cilium of developing Xenopus laevis embryos through Ca2+ influx via transient receptor potential cation channel subfamily C member 3 (TRPC3) and release from intracellular stores in a developmental stage-dependent manner. This ciliary Ca2+ activity in turn antagonizes canonical, proliferative Shh signaling in neural stem cells by down-regulating Sox2 expression and up-regulating expression of neurogenic genes, enabling neuronal differentiation. These discoveries indicate that the Shh-Ca2+-dependent switch in neural cell ciliary signaling triggers the switch in Shh action from canonical-mitogenic to neurogenic. The molecular mechanisms identified in this neurogenic signaling axis are potential targets for the treatment of brain tumors and neurodevelopmental disorders.

Background and objectivesSleep and physical activity have gained traction as modifiable risk factors for Alzheimer's disease. Sleep duration is linked to amyloid-β clearance while physical activity is associated with brain volume maintenance. We investigate how sleep duration and physical activity are associated with cognition by testing if the associations between sleep duration or physical activity to cognition are explained by amyloid-β burden and brain volume, respectively. Additionally, we explore the mediating role of tau deposition in sleep duration-cognition and physical activity-cognition relationships.MethodsThis cross-sectional study obtained data from participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study, a randomized clinical trial. In trial screening, cognitively unimpaired participants (age 65-85 years) underwent amyloid PET and brain MRI; APOE genotype and lifestyle questionnaire data were obtained. Cognitive performance was assessed using the Preclinical Alzheimer Cognitive Composite (PACC). Self-reported nightly sleep duration and weekly physical activity were the primary predictors. Regional Aβ and tau pathologies and volumes were the proposed variables influencing relationships between sleep duration or physical activity and cognition.ResultsAβ data were obtained from 4322 participants (1208 with MRI, 59% female, 29% amyloid positive). Sleep duration was associated with a Aβ composite score (β = -0.005, CI: (-0.01, -0.001)) and Aβ burden in the anterior cingulate (ACC) (β = -0.012, CI: (-0.017, -0.006)) and medial orbitofrontal cortices (MOC) (β = -0.009, CI: (-0.014, -0.005)). Composite (β = -1.54, 95% CI:(-1.93, -1.15)), ACC (β = -1.22, CI:(-1.54, -0.90)) and MOC (β = -1.44, CI:(-1.86, -1.02)) Aβ deposition was associated with PACC. Sleep duration-PACC association was explained by Aβ burden in path analyses. Physical activity was associated with hippocampal (β = 10.57, CI: (1.06, 20.08)), parahippocampal (β = 9.3, CI: (1.69, 16.91)), entorhinal (β = 14.68, CI: (1.75, 27.61), and fusiform gyral (β = 38.38, CI: (5.57, 71.18)) volumes, which were positively associated with PACC (p

In 2021, the World Health Organization reclassified glioblastoma, the most common form of adult brain cancer, into isocitrate dehydrogenase (IDH)-wild-type glioblastomas and grade IV IDH mutant (G4 IDHm) astrocytomas. For both tumor types, intratumoral heterogeneity is a key contributor to therapeutic failure. To better define this heterogeneity, genome-wide chromatin accessibility and transcription profiles of clinical samples of glioblastomas and G4 IDHm astrocytomas were analyzed at single-cell resolution. These profiles afforded resolution of intratumoral genetic heterogeneity, including delineation of cell-to-cell variations in distinct cell states, focal gene amplifications, as well as extrachromosomal circular DNAs. Despite differences in IDH mutation status and significant intratumoral heterogeneity, the profiled tumor cells shared a common chromatin structure defined by open regions enriched for nuclear factor 1 transcription factors (NFIA and NFIB). Silencing of NFIA or NFIB suppressed in vitro and in vivo growths of patient-derived glioblastomas and G4 IDHm astrocytoma models. These findings suggest that despite distinct genotypes and cell states, glioblastoma/G4 astrocytoma cells share dependency on core transcriptional programs, yielding an attractive platform for addressing therapeutic challenges associated with intratumoral heterogeneity.

To translate artificial intelligence (AI) algorithms into clinical practice requires generalizability of models to real-world data. One of the main obstacles to generalizability is data shift, a data distribution mismatch between model training and real environments. Explainable AI techniques offer tools to detect and mitigate the data shift problem and develop reliable AI for clinical practice. Most medical AI is trained with datasets gathered from limited environments, such as restricted disease populations and center-dependent acquisition conditions. The data shift that commonly exists in the limited training set often causes a significant performance decrease in the deployment environment. To develop a medical application, it is important to detect potential data shift and its impact on clinical translation. During AI training stages, from premodel analysis to in-model and post hoc explanations, explainability can play a key role in detecting model susceptibility to data shift, which is otherwise hidden because the test data have the same biased distribution as the training data. Performance-based model assessments cannot effectively distinguish the model overfitting to training data bias without enriched test sets from external environments. In the absence of such external data, explainability techniques can aid in translating AI to clinical practice as a tool to detect and mitigate potential failures due to data shift. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

The poor generalizability of clinical research data due to the enrollment of highly educated, non-Latinx White participants hampers the development of therapies for Alzheimers disease (AD). Black and Latinx older adults have a greater risk for dementia, yet it is unclear how health-care disparities and sociocultural factors influence potential AD therapies and prognosis. Low enrollment of under-represented populations may be attributable to several factors including greater exclusion due to higher rates of comorbidities, lower access to AD clinics, and the legacy of unethical treatment in medical research. This perspective outlines solutions tested in the Brain Health Registry (BHR) and the Alzheimers Disease Neuroimaging Initiative (ADNI), including culturally-informed digital research methods, community-engaged research strategies, leadership from under-represented communities, and the reduction of exclusion criteria based on comorbidities. Our successes demonstrate that it is possible to increase the inclusion and engagement of under-represented populations into US-based clinical studies, thereby increasing the generalizability of their results.

RATIONALE AND OBJECTIVES: Early prostate cancer detection and staging from MRI is extremely challenging for both radiologists and deep learning algorithms, but the potential to learn from large and diverse datasets remains a promising avenue to increase their performance within and across institutions. To enable this for prototype-stage algorithms, where the majority of existing research remains, we introduce a flexible federated learning framework for cross-site training, validation, and evaluation of custom deep learning prostate cancer detection algorithms. MATERIALS AND METHODS: We introduce an abstraction of prostate cancer groundtruth that represents diverse annotation and histopathology data. We maximize use of this groundtruth if and when they are available using UCNet, a custom 3D UNet that enables simultaneous supervision of pixel-wise, region-wise, and gland-wise classification. We leverage these modules to perform cross-site federated training using 1400+ heterogeneous multi-parameteric prostate MRI exams from two University hospitals. RESULTS: We observe a positive result, with significant improvements in cross-site generalization performance with negligible intra-site performance degradation for both lesion segmentation and per-lesion binary classification of clinically-significant prostate cancer. Cross-site lesion segmentation performance intersection-over-union (IoU) improved by 100%, while cross-site lesion classification performance overall accuracy improved by 9.5-14.8%, depending on the optimal checkpoint selected by each site. CONCLUSION: Federated learning can improve the generalization performance of prostate cancer detection models across institutions while protecting patient health information and institution-specific code and data. However, even more data and participating institutions are likely required to improve the absolute performance of prostate cancer classification models. To enable adoption of federated learning with limited re-engineering of federated components, we open-source our FLtools system at https://federated.ucsf.edu, including examples that can be easily adapted to other medical imaging deep learning projects.

INTRODUCTION: The Alzheimers disease (AD) continuum begins with a long asymptomatic or preclinical stage, during which amyloid beta (Aβ) is accumulating for more than a decade prior to widespread cortical tauopathy, neurodegeneration, and manifestation of clinical symptoms. The AHEAD 3-45 Study (BAN2401-G000-303) is testing whether intervention with lecanemab (BAN2401), a humanized immunoglobulin 1 (IgG1) monoclonal antibody that preferentially targets soluble aggregated Aβ, initiated during this asymptomatic stage can slow biomarker changes and/or cognitive decline. The AHEAD 3-45 Study is conducted as a Public-Private Partnership of the Alzheimers Clinical Trial Consortium (ACTC), funded by the National Institute on Aging, National Institutes of Health (NIH), and Eisai Inc. METHODS: The AHEAD 3-45 Study was launched on July 14, 2020, and consists of two sister trials (A3 and A45) in cognitively unimpaired (CU) individuals ages 55 to 80 with specific dosing regimens tailored to baseline brain amyloid levels on screening positron emission tomography (PET) scans: intermediate amyloid (≈20 to 40 Centiloids) for A3 and elevated amyloid (>40 Centiloids) for A45. Both trials are being conducted under a single protocol, with a shared screening process and common schedule of assessments. A3 is a Phase 2 trial with PET-imaging end points, whereas A45 is a Phase 3 trial with a cognitive composite primary end point. The treatment period is 4 years. The study utilizes innovative approaches to enriching the sample with individuals who have elevated brain amyloid. These include recruiting from the Trial-Ready Cohort for Preclinical and Prodromal Alzheimers disease (TRC-PAD), the Australian Dementia Network (ADNeT) Registry, and the Japanese Trial Ready Cohort (J-TRC), as well as incorporation of plasma screening with the C2N mass spectrometry platform to quantitate the Aβ 42/40 ratio (Aβ 42/40), which has been shown previously to reliably identify cognitively normal participants not likely to have elevated brain amyloid levels. A blood sample collected at a brief first visit is utilized to screen out individuals who are less likely to have elevated brain amyloid, and to determine the participants eligibility to proceed to PET imaging. Eligibility to randomize into the A3 Trial or A45 Trial is based on the screening PET imaging results. RESULT: The focus of this article is on the innovative design of the study. DISCUSSION: The AHEAD 3-45 Study will test whether with lecanemab (BAN2401) can slow the accumulation of tau and prevent the cognitive decline associated with AD during its preclinical stage. It is specifically targeting both the preclinical and the early preclinical (intermediate amyloid) stages of AD and is the first secondary prevention trial to employ plasma-based biomarkers to accelerate the screening process and potentially substantially reduce the number of screening PET scans.

BackgroundTalimogene laherparepvec (T-VEC), a first-in-class oncolytic viral immunotherapy, enhances tumor-specific immune activation. T-VEC combined with atezolizumab, which blocks inhibitor T-cell checkpoints, could provide greater benefit than either agent alone. Safety/efficacy of the combination was explored in patients with triple negative breast cancer (TNBC) or colorectal cancer (CRC) with liver metastases.MethodsIn this phase Ib, multicenter, open-label, parallel cohort study of adults with TNBC or CRC with liver metastases, T-VEC (106 then 108 PFU/ml; ≤4 ml) was administered into hepatic lesions via image-guided injection every 21 (±3) days. Atezolizumab 1200 mg was given on day 1 and every 21 (±3) days thereafter. Treatment continued until patients experienced dose-limiting toxicity (DLT), had complete response, progressive disease, needed alternative anticancer treatment, or withdrew due to an adverse event (AE). The primary endpoint was DLT incidence, and secondary endpoints included efficacy and AEs.ResultsBetween 19 March 2018 and 6 November 2020, 11 patients with TNBC were enrolled (safety analysis set: n = 10); between 19 March 2018 and 16 October 2019, 25 patients with CRC were enrolled (safety analysis set: n = 24). For the 5 patients in the TNBC DLT analysis set, no patient had DLT; for the 18 patients in the CRC DLT analysis set, 3 (17%) had DLT, all serious AEs. AEs were reported by 9 (90%) TNBC and 23 (96%) CRC patients, the majority with grade ≥3 [TNBC, 7 (70%); CRC, 13 (54%)], and 1 was fatal [CRC, 1 (4%)]. Evidence of efficacy was limited. Overall response rate was 10% (95% confidence interval 0.3-44.5) for TNBC; one (10%) patient had a partial response. For CRC, no patients had a response; 14 (58%) were unassessable.ConclusionsThe safety profile reflected known risks with T-VEC including risks of intrahepatic injection; no unexpected safety findings from addition of atezolizumab to T-VEC were observed. Limited evidence of antitumor activity was observed.

ObjectiveSubspecialty consultation in the emergency department (ED) is a vital, albeit time consuming, part of modern medicine. Traditional consultation requires manual paging to initiate communication. Although consult orders through the electronic health record (EHR) may help, they do not facilitate 2-way communication. However, the impact of combining these systems within the EHR is unknown. We estimated the effect of implementing an integrated paging system on ED workflow efficiency and user attitudes.MethodsWe integrated a messaging system into order entry at our tertiary care academic ED, such that placing a consult order simultaneously paged the consultant. We measured ED workflow efficiency metrics (length of stay [LOS], consult initiation time) and MD/nurse practitioner (NP)/physician assistant (PA) attitudes (perceived mis-pages, efficiency, and workflow preference) 3 months before and 6 months after the implementation.ResultsSix months after implementation, there was 25% use of the new workflow. During the pre-implementation phase, the median time to consult initiation and ED LOS were 150 and 621 minutes, respectively. Implementation of the order was associated with a 15-minute reduction in median time to consult initiation (P