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ObjectivesFetal growth restriction (FGR) is commonly associated with placental dysfunction, increasing perinatal morbidity and mortality. Visualizing placental vessels in utero would be advantageous for identifying functional FGR cause and determining proper management strategies. We aimed to utilize high‐sensitivity ultrasound microvessel imaging (HUMI) for quantifying placental vessel density (VD) in pregnancies diagnosed with FGR.MethodsThis pilot case–control study enrolled subjects in the third trimester with a diagnosis of FGR (n = 40) and gestational age‐matched controls with normal fetal growth (n = 20) at a 2:1 ratio, respectively. The Verasonics Vantage ultrasound system was used to perform HUMI on each participant at one timepoint. Scanning involved randomized singular value decomposition‐based clutter filtering to identify the villous tree, followed by step‐by‐step scanning to acquire 3‐dimensional‐like data. Mean VD was calculated from three ultrasound measurements per subject. Additional clinical and pathology data were also collected and compared.ResultsSixteen participants were utilized to establish the scanning protocol and 2 met exclusion criteria at delivery. Thus, VD was successfully measured on 42 pregnancies scanned at 35 weeks 5 days on average. In FGR (n = 24), placental VD was significantly reduced compared to controls (P < .01). VD measures were as good at predicting FGR as systolic/diastolic (S/D) ratios (area under the curve 0.86 versus 0.80). In a smaller cohort, VD in placentas with a diagnosis of inflammatory villitis (n = 10) by histology showed an increase in VD compared to those without inflammation (P = .01). Low VD was correlated with increased S/D ratios (P = .03).ConclusionsHUMI is useful for identifying altered placental vascularization in utero for FGR. VD may be a valuable indicator for placental health and could lead to improved risk stratification methods considering underlying biology.

Abstract Background The urgent need for rapid fentanyl detection at the point-of-care originates from its involvement in a high number of overdose deaths, primarily due to illicit use. Given fentanyl's potency compared to traditional opioids, accurate and sensitive detection is critical. Current lateral flow assays (LFA) cannot detect single-digit concentrations and may yield false negatives due to their lower sensitivity. Herein, we evaluate the clinical performance of a novel LFA (InstaStrip Fentanyl Rapid Test (urine)) with 1 ng/mL cutoff for fentanyl and no cross-reactivity for norfentanyl, offering enhanced sensitivity for effective overdose prevention at the ED. Methods A total of 172 urine samples submitted for UDS analysis were used for comparison studies. Fentanyl concentrations were categorized in 5 groups to cover various concentration categories around the cutoff of the LFA (1 ng/mL). These categories are: drug-free (&lt;0.1 ng/mL, n=68), 0.1-0.5 ng/mL (n=14), 0.5-0.9 ng/mL (n=15), 1-1.5 ng/mL (n=9) and &gt; 1.5 ng/mL (n= 66). Concentrations were determined by in-house LC-MS/MS methods validated according to CLIA standards, with fentanyl concentrations quantitated in the ABSciex software. For LFA testing, 150 μL of urine was added to a reagent tube containing dried rabbit anti-fentanyl antibody conjugated gold nanoparticles. After 20 sec of brief shaking, a test strip was inserted into the test tube. After 5 min, qualitative results were read as follow: both the control and test lines were visible in negative results, whereas only the control lines were visible in positive results. Method comparison study of the LFA was conducted by three operators who were blinded to the LC-MS/MS results. Result comparisons were made between the LFA strip and LC-MS/MS results, as well as among different operators for the same samples. Results Of the 75 urine samples with LC-MS/MS fentanyl concentrations ≥ 1 ng/mL, 74 produced consistently positive results using the InstaStrip Fentanyl Rapid Test. Of the 97 urine samples with LC-MS/MS fentanyl concentrations &lt; 1 ng/mL, 96 produced consistently negative results using the InstaStrip Fentanyl Rapid Test. Using the LC-MS/MS as the gold standard method and 1 ng/mL as a cutoff, the clinical sensitivity of InstaStrip Fentanyl Rapid Test was calculated to be 98.67% (95% confidence interval (CI) 92.79-99.97%), and the clinical specificity was 98.97% (95% CI 94.39-99.97%). Consistent results among three operators were obtained for 100% of the “drug free”, “0.1- 0.5 ng/mL” and &gt; 1.5 ng/mL groups, whereas 93.3 % (14 out of 15) and 88.9% (7 out of 8) were obtained for the “0.5-0.9 ng/mL” and “1-1.5 ng/mL” groups, respectively. The two samples with a singlet discrepant result (1 false positive and 1 false negative) in the triplicate experiments contained fentanyl concentrations of 0.9 and 1.0 ng/mL respectively, which are very close to the cutoff value. Conclusions In this study, the InstaStrip Fentanyl Rapid Test (urine) demonstrated high clinical sensitivity (98.67%), high specificity (98.97%) and high reproducibility showing that it may be useful in screening and identifying patients with fentanyl overdose in minutes in an emergency setting. This would facilitate appropriate patient triaging for optimal clinical care.

Most patients with metastatic prostate cancer eventually develop resistance to primary androgen deprivation therapy. To identify predictive biomarker for Abiraterone acetate/prednisone resistance, we screened alternative splice variants between responders and non-responders from the PROMOTE clinical study and pinned down the most significant variant, CENPK–delta8. Through preclinical patient-derived mouse xenograft (PDX) and 3D organoids obtained from responders and non-responders, as well as in vitro models, aberrant CENPK–delta8 expression was determined to link to drug resistance via enhanced migration and proliferation. The FLNA and FLOT1 were observed to specifically bind to CENK–delta8 rather than wild-type CENPK, underscoring the role of CENPK–delta8 in cytoskeleton organization and cell migration. Our study, leveraging data from the PROMOTE study, TCGA, and TCGA SpliceReq databases, highlights the important function of alternative splice variants in drug response and their potential to be prognostic biomarkers for improving individual therapeutic outcomes in precision medicine.

ObjectivesMetabolic dysfunction‐associated steatotic liver disease (MASLD) is the most prevalent liver disorder in Western countries, with approximately 20%–30% of the MASLD patients progressing to severe stages. There is an urgent need for noninvasive, cost‐effective, widely accessible, and precise biomarkers to evaluate liver steatosis. This study aims to assess and compare the diagnostic performance of a novel reference frequency method‐based ultrasound attenuation coefficient estimation (ACE) in both fundamental (RFM‐ACE‐FI) and harmonic (RFM‐ACE‐HI) imaging for detecting and grading liver steatosis.MethodsAn Institutional Review Board‐approved prospective study was carried out between December 2018 and October 2022. A total number of 130 subjects were enrolled in the study. The correlation between RFM‐ACE‐HI values and magnetic resonance imaging proton density fat fraction (MRI‐PDFF), as well as between RFM‐ACE‐FI values and MRI‐PDFF were calculated. The diagnostic performance of RFM‐ACE‐FI and RFM‐ACE‐HI was evaluated using receiver operating characteristic (ROC) curve analysis, as compared to MRI‐PDFF. The reproducibility of RFM‐ACE‐HI was assessed by interobserver agreement between two sonographers.ResultsA strong correlation was observed between RFM‐ACE‐HI and MRI‐PDFF, with R = 0.88 (95% confidence interval [CI]: 0.83–0.92; P < .001), while the correlation between RFM‐ACE‐FI and MRI‐PDFF was R = 0.65 (95% CI: 0.50–0.76; P < .001). The area under the ROC (AUROC) curve for RFM‐ACE‐HI in staging liver steatosis grades of S ≥ 1 and S ≥ 2 was 0.97 (95% CI: 0.91–0.99; P < .001) and 0.98 (95% CI: 0.93–1.00; P < .001), respectively, and 0.76 (95% CI: 0.65–0.85) and 0.80 (95% CI: 0.70–0.88) for RFM‐ACE‐FI, respectively. Great reproducibility was achieved for RFM‐ACE‐HI, with an interobserver agreement of R = 0.97 (95% CI: 0.94–0.99; P < .001).ConclusionsThe novel RFM‐ACE‐HI method offered high liver steatosis diagnostic accuracy and reproducibility, which has important clinical implications for early disease intervention and treatment evaluation.

Abstract INTRODUCTION Multi‐omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP‐AD) expanded brain multi‐omics profiling to multi‐ethnic donors. RESULTS We generated multi‐omics data and curated and harmonized phenotypic data from BA ( n = 306), LA ( n = 326), or BA and LA ( n = 4) brain donors plus non‐Hispanic White ( n = 252) and other ( n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION The inclusion of traditionally underrepresented groups in multi‐omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD. Highlights Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi‐ethnic populations. Brain multi‐omics data is generated from Black American, Latin American, and non‐Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.

Importance The clinical effects of risankizumab (a monoclonal antibody that selectively targets the p19 subunit of IL-23) for the treatment of ulcerative colitis are unknown. Objective To evaluate the efficacy and safety of risankizumab when administered as an induction and a maintenance therapy for patients with ulcerative colitis. Design, Setting, and Participants Two phase 3 randomized clinical trials were conducted. The induction trial was conducted at 261 clinical centers (in 41 countries) and enrolled 977 patients from November 5, 2020, to August 4, 2022 (final follow-up on May 16, 2023). The maintenance trial was conducted at 238 clinical centers (in 37 countries) and enrolled 754 patients from August 28, 2018, to March 30, 2022 (final follow-up on April 11, 2023). Eligible patients had moderately to severely active ulcerative colitis; a history of intolerance or inadequate response to 1 or more conventional therapies, advanced therapies, or both types of therapies; and no prior exposure to risankizumab. Interventions For the induction trial, patients were randomized 2:1 to receive 1200 mg of risankizumab or placebo administered intravenously at weeks 0, 4, and 8. For the maintenance trial, patients with a clinical response (determined using the adapted Mayo score) after intravenous treatment with risankizumab were randomized 1:1:1 to receive subcutaneous treatment with 180 mg or 360 mg of risankizumab or placebo (no longer receiving risankizumab) every 8 weeks for 52 weeks. Main Outcomes and Measures The primary outcome was clinical remission (stool frequency score ≤1 and not greater than baseline, rectal bleeding score of 0, and endoscopic subscore ≤1 without friability) at week 12 for the induction trial and at week 52 for the maintenance trial. Results Among the 975 patients analyzed in the induction trial (aged 42.1 [SD, 13.8] years; 586/973 [60.1%] were male; and 677 [69.6%] were White), the clinical remission rates at week 12 were 132/650 (20.3%) for 1200 mg of risankizumab and 20/325 (6.2%) for placebo (adjusted between-group difference, 14.0% [95% CI, 10.0%-18.0%], P &amp;lt; .001). Among the 548 patients analyzed in the maintenance trial (aged 40.9 [SD, 14.0] years; 313 [57.1%] were male; and 407 [74.3%] were White), the clinical remission rates at week 52 were 72/179 (40.2%) for 180 mg of risankizumab, 70/186 (37.6%) for 360 mg of risankizumab, and 46/183 (25.1%) for placebo (adjusted between-group difference for 180 mg of risankizumab vs placebo, 16.3% [97.5% CI, 6.1%-26.6%], P &amp;lt; .001; adjusted between-group difference for 360 mg of risankizumab vs placebo, 14.2% [97.5% CI, 4.0%-24.5%], P = .002). No new safety risks were detected in the treatment groups. Conclusion and Relevance Compared with placebo, risankizumab improved clinical remission rates in an induction trial and in a maintenance trial for patients with moderately to severely active ulcerative colitis. Further study is needed to identify benefits beyond the 52-week follow-up. Trial Registration ClinicalTrials.gov Identifiers: NCT03398148 and NCT03398135

PURPOSE The RECIST guidelines provide a standardized approach for evaluating the response of cancer to treatment, allowing for consistent comparison of treatment efficacy across different therapies and patients. However, collecting such information from electronic health records manually can be extremely labor-intensive and time-consuming because of the complexity and volume of clinical notes. The aim of this study is to apply natural language processing (NLP) techniques to automate this process, minimizing manual data collection efforts, and improving the consistency and reliability of the results. METHODS We proposed a complex, hybrid NLP system that automates the process of extracting, linking, and summarizing anticancer therapy and associated RECIST-like responses from narrative clinical text. The system consists of multiple machine learning–/deep learning–based and rule-based modules for diverse NLP tasks such as named entity recognition, assertion classification, relation extraction, and text normalization, to address different challenges associated with anticancer therapy and response information extraction. We then evaluated the system performances on two independent test sets from different institutions to demonstrate its effectiveness and generalizability. RESULTS The system used domain-specific language models, BioBERT and BioClinicalBERT, for high-performance therapy mentions identification and RECIST responses extraction and categorization. The best-performing model achieved a 0.66 score in linking therapy and RECIST response mentions, with end-to-end performance peaking at 0.74 after relation normalization, indicating substantial efficacy with room for improvement. CONCLUSION We developed, implemented, and tested an information extraction system from clinical notes for cancer treatment and efficacy assessment information. We expect this system will support future cancer research, particularly oncologic studies that focus on efficiently assessing the effectiveness and reliability of cancer therapeutics.

11118 Background: Lung cancer survivors experience more physical and mental challenges, heavier symptom burden, and poorer quality of life than survivors of other cancers. Many symptoms persist or worsen for survivors beyond 5 years of cancer diagnosis, referred as long-term lung cancer survivors (LTLCS). Social determinants of health (SDoH) factors negatively impact patient reported outcomes (PROs) among cancer survivors, but their role in outcomes is under reported in lung cancer survivors and unknown in LTLCS. We investigated the impact of SDoH on PROs in a 20-year prospective lung cancer cohort. Methods: Our cohort includes 19,251 lung cancer patients (cases) diagnosed from 1997 through 2016 and followed up to 27 years, of whom 4799 (25%) became LTLCS. SDoH information was obtained by a lung cancer study PRO questionnaire or an institution SDoH questionnaire. Analyzed in this report are 2982 cases and 480 controls who had a low-dose chest CT scan and were ruled out for cancer, all answered at least one PRO questionnaire (first response); and 1366 LTLCS answered 5 years after diagnosis (long-term response). Along with fatigue and dyspnea, 5 SDoH variables, i.e., financial concerns, legal concerns, family and friends support, spiritual well-being, and social activity were scored on a 0 (worst) - 10 (best) scale and dichotomized as 0-5 (deficit/worse/lower) or 6-10 (no deficit/better/higher). We also assessed employment and health-related work experience. A difference of 1.0 unit or more in score was considered clinically meaningful along with a 2-sided test P-value less than 0.05; Chi-square or Fisher’s Exact Test and Kruskal-Wallis test were used accordingly. Results: Compared to controls, cases were younger (mean age: 62 vs. 65 years, P<0.05); more women than men reported worse financial concerns (56% vs. 38%, P<0.01) and lower spiritual well-being (43% vs. 26%, P=0.04) at first response; this sex disparity reduced but remained significant at long-term. Worse dyspnea (4.4-4.8 vs. 5.6) and fatigue (4.7-4.8 vs. 5.8-5.9) were seen in cases with more financial and legal concerns compared to those with fewer concerns (Ps<0.01). Cases with higher family and friends support, spiritual well-being and social activity had less dyspnea (5.7-6.0 vs. 4.2-4.5) and fatigue (5.5-5.9 vs. 3.9-4.4) than those with lower scores (Ps<0.04). Employment and health-related work experience data were provided by 2213 responders: Comparing 1735 cases to 478 controls, a lower proportion of cases was employed (28% vs. 39%), more cases “often felt tired after work” (49% vs. 28%), and more cases had “quite a lot” of difficulty in daily work or could not work at all” (26% vs. 9%, Ps<0.01). Conclusions: We found that in lung cancer survivors, more women than men reported worse financial concerns, and lower SDoH status was correlated with worse dyspnea and fatigue, indicating SDoH-driven interventions are important to improve lung cancer survivors’ PROs.