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Background & aimsDiscerning whether laryngeal symptoms result from gastroesophageal reflux is clinically challenging and a reliable tool to stratify patients is needed. We aimed to develop and validate a model to predict the likelihood of gastroesophageal reflux disease (GERD) among patients with chronic laryngeal symptoms.MethodsThis multicenter international study collected data from adults with chronic laryngeal symptoms who underwent objective testing (upper gastrointestinal endoscopy and/or ambulatory reflux monitoring) between March 2018 and May 2023. The training phase identified a model with optimal receiver operating characteristic curves, and β coefficients informed a weighted model. The validation phase assessed performance characteristics of the weighted model.ResultsA total of 856 adults, 304 in the training cohort and 552 in the validation cohort, were included. In the training phase, the optimal predictive model (area under the curve, 0.68; 95% CI, 0.62-0.74), was the Cough, Overweight/obesity, Globus, Hiatal Hernia, Regurgitation, and male seX (COuGH RefluX) score, with a lower threshold of 2.5 and an upper threshold of 5.0 to predict proven GERD. In the validation phase, the COuGH RefluX score had an area under the curve of 0.67 (95% CI, 0.62-0.71), with 79% sensitivity and 81% specificity for proven GERD.ConclusionsThe externally validated COuGH RefluX score is a clinically practical model to predict the likelihood of proven GERD. The score classifies most patients with chronic laryngeal symptoms as low/high likelihood of proven GERD, with only 38% remaining as indeterminate. Thus, the COuGH RefluX score can guide diagnostic strategies and reduce inappropriate proton pump inhibitor use or testing for patients referred for evaluation of chronic laryngeal symptoms.

ObjectiveFast and accurate deformable image registration (DIR) that include DIR uncertainty estimation are essential for safe and reliable clinical deployment. While recent deep learning models have shown promise in predicting DIR with its uncertainty, challenges persist in proper uncertainty evaluation and hyperparameter optimization for these methods. This work aims to develop and evaluate a model that can perform fast DIR and predict its uncertainty in seconds.ApproachIn this study, we introduce a novel probabilistic multi-resolution image registration model utilizing convolutional neural networks (CNNs) to estimate a multivariate normal distributed dense displacement field (DDF) in a multimodal image registration problem. To assess the quality of the DDF distribution predicted by the model, we propose a new metric based on the Kullback-Leibler divergence. The performance of our approach was evaluated against three other DIR algorithms (VoxelMorph, Monte Carlo Drop-Out, and Monte Carlo B-splines) capable of predicting uncertainty. The evaluation of the models included not only the quality of the deformation but also the reliability of the estimated uncertainty. Our application investigated registration of a treatment planning computed tomography (CT) to follow-up cone beam CT for daily adaptive radiotherapy.Main resultsThe hyperparameter tuning of the models showed that there is a trade-off between the reliability of the estimated uncertainty and the accuracy of the deformation. In the optimal trade-off our model excelled in contour propagation and uncertainty estimation (p < 0.01) compared to existing uncertainty estimation models. We obtained an average dice similarity coefficient of 0.89 and a KL-divergence of 0.15.SignificanceBy addressing challenges in DIR uncertainty estimation and evaluation, our work showed that both the DIR and its uncertainty can be reliably predicted paving the way for safe deployment in clinical environment..

Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P

The composite material-like extracellular matrix (ECM) in the sinoatrial node (SAN) supports the native pacemaking cardiomyocytes (PCMs). To test the roles of SAN ECM in the PCM phenotype and function, we engineered reconstructed-SAN heart tissues (rSANHTs) by recellularizing porcine SAN ECMs with hiPSC-derived PCMs. The hiPSC-PCMs in rSANHTs self-organized into clusters resembling the native SAN and displayed higher expression of pacemaker-specific genes and a faster automaticity compared with PCMs in reconstructed-left ventricular heart tissues (rLVHTs). To test the protective nature of SAN ECMs under strain, rSANHTs and rLVHTs were transplanted onto the murine thoracic diaphragm to undergo constant cyclic strain. All strained-rSANHTs preserved automaticity, whereas 66% of strained-rLVHTs lost their automaticity. In contrast to the strained-rLVHTs, PCMs in strained-rSANHTs maintained high expression of key pacemaker genes (HCN4, TBX3, and TBX18). These findings highlight the promotive and protective roles of the composite SAN ECM and provide valuable insights for pacemaking tissue engineering.

RNA editing, the endogenous modification of nucleic acids, is known to be altered in genes with important neurological function in schizophrenia (SCZ). However, the global profile and molecular functions of disease-associated RNA editing remain unclear. Here, we analyzed RNA editing in postmortem brains of four SCZ cohorts and uncovered a significant and reproducible trend of hypoediting in patients of European descent. We report a set of SCZ-associated editing sites via WGCNA analysis, shared across cohorts. Using massively parallel reporter assays and bioinformatic analyses, we observed that differential 3' untranslated region (3'UTR) editing sites affecting host gene expression were enriched for mitochondrial processes. Furthermore, we characterized the impact of two recoding sites in the mitofusin 1 (MFN1) gene and showed their functional relevance to mitochondrial fusion and cellular apoptosis. Our study reveals a global reduction of editing in SCZ and a compelling link between editing and mitochondrial function in the disease.

RNA editing modifies single nucleotides of RNAs, regulating primary protein structure and protein abundance. In recent years, the diversity of proteins and complexity of gene regulation associated with RNA editing dysregulation has been increasingly appreciated in oncology. Large-scale shifts in editing have been observed in bulk tumors across various cancer types. However, RNA editing in single cells and individual cell types within tumors has not been explored. By profiling editing in single cells from lung adenocarcinoma biopsies, we found that the increased editing trend of bulk lung tumors was unique to cancer cells. Elevated editing levels were observed in cancer cells resistant to targeted therapy, and editing sites associated with drug response were enriched. Consistent with the regulation of antiviral pathways by RNA editing, higher editing levels in cancer cells were associated with reduced antitumor innate immune response, especially levels of natural killer cell infiltration. In addition, the level of RNA editing in cancer cells was positively associated with somatic point mutation burden. This observation motivated the definition of a new metric, RNA editing load, reflecting the amount of RNA mutations created by RNA editing. Importantly, in lung cancer, RNA editing load was a stronger predictor of patient survival than DNA mutations. This study provides the first single cell dissection of editing in cancer and highlights the significance of RNA editing load in cancer prognosis.SignificanceRNA editing analysis in single lung adenocarcinoma cells uncovers RNA mutations that correlate with tumor mutation burden and cancer innate immunity and reveals the amount of RNA mutations that strongly predicts patient survival. See related commentary by Luo and Liang, p. 351.

AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.

IntroductionThere is a paucity of data on immune checkpoint inhibitors (ICIs) plus doublet chemotherapy (C) in patients with advanced lung cancer whose tumor harbors an actionable mutation. We sought to provide insight into the role of this combination in relation to chemotherapy alone in this patient population.MethodsWe conducted a retrospective study at the five University of California National Cancer Institute-designated Comprehensive Cancer Centers. The primary end point was progression-free survival (PFS). Secondary end points included overall survival (OS) and significant adverse events. Adverse events in patients who received a tyrosine kinase inhibitor (TKI) post-ICI were also captured.ResultsA total of 246 patients were identified, 170 treated with C plus ICI and 76 treated with C alone. Driver alterations included EGFR (54.9%), KRAS (32.9%), ALK (5.3%), HER2/ERBB2 (2.9%), ROS1 (1.2%), MET (1.2%), RET (0.8%), and BRAF non-V600 (0.8%). The overall PFS and OS hazard ratios were not significant at 1.12 (95% confidence interval 0.83-1.51; p = 0.472) and 0.86 (95% confidence interval: 0.60-1.24, p = 0.429), respectively. No significant differences in PFS or OS were observed in the mutational subgroups. Grade 3 or greater adverse events were lower in the C plus ICI group. The multivariate analysis for PFS and OS revealed a performance status (Eastern Cooperative Oncology Group) score of 2, and previous TKI treatment was associated with poorer outcomes with C plus ICI.ConclusionsOur study suggests that patients with oncogenic-driven NSCLC, primarily those with EGFR-driven tumors, treated with a TKI should not subsequently receive C plus ICI. Analysis from prospective clinical trials will provide additional information on the role of ICIs in this group of patients.

BackgroundTo evaluate acute and late genitourinary and gastrointestinal toxicities and patient reported urinary and sexual function following accelerated, hypofractionated external beam radiotherapy to the prostate, seminal vesicles and pelvic lymph nodes and high dose rate (HDR) brachytherapy or stereotactic body radiation therapy (SBRT) prostate boost.MethodsPatients at a single institution with NCCN intermediate- and high-risk localized prostate cancer with logistical barriers to completing five weeks of whole pelvic radiotherapy (WPRT) were retrospectively reviewed for toxicity following accelerated, hypofractionated WPRT (41.25 Gy in 15 fractions of 2.75 Gy). Patients also received prostate boost radiotherapy with either HDR brachytherapy (1 fraction of 15 Gy) or SBRT (19 Gy in 2 fractions of 9.5 Gy). The duration of androgen deprivation therapy was at the discretion of the treating radiation oncologist. Toxicity was evaluated by NCI CTCAE v 5.0.ResultsBetween 2015 and 2017, 22 patients with a median age of 71 years completed accelerated, hypofractionated WPRT. Median follow-up from the end of radiotherapy was 32 months (range 2-57). 5%, 73%, and 23% of patients had clinical T1, T2, and T3 disease, respectively. 86% of tumors were Gleason grade 7 and 14% were Gleason grade 9. 68% and 32% of patients had NCCN intermediate- and high-risk disease, respectively. 91% and 9% of patients received HDR brachytherapy and SBRT prostate boost following WPRT, respectively. Crude rates of grade 2 or higher GI and GU toxicities were 23% and 23%, respectively. 3 patients (14%) had late or persistent grade 2 toxicities of urinary frequency and 1 patient (5%) had late or persistent GI toxicity of diarrhea. No patient experienced grade 3 or higher toxicity at any time. No difference in patient-reported urinary or sexual function was noted at 12 months.ConclusionsAccelerated, hypofractionated whole pelvis radiotherapy was associated with acceptable GU and GI toxicities and should be further validated for those at risk for harboring occult nodal disease.

Purpose: Teachers are occupational voice users with significant vocal demand. This study examined if a vocal hygiene program could mitigate the effects of occupational vocal demand in primary school teachers across 1 month. Method: Sixty female teachers participated, with 30 in an experimental group receiving vocal hygiene education plus daily home practice for 1 month and 30 in a control group with no intervention. Their vocal changes across the month were quantified with (a) acoustic measures on fundamental frequency (f[subscript o]), vocal intensity, jitter and shimmer, harmonics-to-noise ratio, and smoothed cepstral peak prominence and (b) Voice Handicap Index (VHI-10) and Vocal Fatigue Index (VFI) scores. Results: Analysis of covariance showed significantly larger changes (significant decreases) in conversational f[subscript o] and in jitter for the experimental group relative to the control group. Post hoc pairwise comparisons following repeated-measures analysis of variance showed significant decreases in conversational f[subscript o] and in jitter across the month for the experimental group. No significant differences in VHI-10 and VFI scores were found between the groups. Conclusions: Vocal demand-related changes in acoustic measures could be partially mitigated with the vocal hygiene program. Future studies with a more refined intervention program and more long-term follow-up are recommended to better understand the long-term benefits of vocal hygiene programs on primary school teachers.

Undergraduate research (UGR), one of several high-impact practices (HIPs) in education, can positively impact student retention and graduation rates. However, not all students take advantage of UGR opportunities, with fewer students from underrepresented minority groups, those with first-generation status, and students eligible for a Pell grant or federally subsidized loan. We obtained retention and graduation data from our Office of Institutional Research and Planning for all UGR participants for academic years 2009-2010 to 2016-2017. We specifically focused on data for UGR participants from underrepresented demographics that historically have lower retention and graduation rates than those of the overall student body. We created Sankey-like ribbon diagrams to analyze the characteristics of UGR participants, whether they participated in UGR for 1 year or longer, their class standings when they started UGR, retention rates for 1st- and 2nd-year students for the year following their UGR participation, and graduation rates for all participants. Our data show that irrespective of demographics, students who participated in UGR were significantly more likely to persist in college and graduate within 6 years compared to students who did not. Persistence and success in college may depend on students' socioeconomic status, sense of belonging, and other factors. Assessing the impact of a single HIP, such as UGR, on retention and graduation rates, can, therefore, be complicated. However, our study indicates that UGR participation can significantly improve persistence and success for students traditionally considered "at-risk," irrespective of their socioeconomic status, family background, or class standing. This information can be important for campus leaders and other stakeholders interested in facilitating student success and reducing the equity gap by incorporating UGR in more students' college experiences. We describe our analytical methods and discusses our findings. We also demonstrate the effectiveness of Sankey-like diagrams for visualizing and analyzing large programmatic data sets, and as a tool for communicating program impacts to a general audience.

SignificanceFollicular thyroid carcinoma carries a substantially poor prognosis due to its unique biological behavior and less favorable outcomes. In particular, fine-needle aspiration (FNA) biopsies, which play a key role in screening thyroid nodules, cannot differentiate benign from malignant follicular neoplasm.AimWe report on the use of hyperspectral Raman microscopy in combination with chemometric analysis for identifying and classifying single cells obtained from clinical samples of human follicular thyroid neoplasms.ApproachWe used a method intended to simulate the FNA procedure to obtain single cells from thyroid nodules. A total of 392 hyperspectral Raman images of single cells from follicular thyroid neoplasms were collected.ResultsMalignant cells were identified based on their intrinsic Raman spectral signatures with an overall diagnostic accuracy of up to 83.7%.ConclusionsOur findings indicate that hyperspectral Raman microscopy can potentially be developed into an ancillary test for analyzing single cells from thyroid FNA biopsies to better stratify "indeterminate" nodules and other cytologically challenging cases.