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ABSTRACT: The advent of immunological therapies has revolutionized the treatment of solid and haematological cancers over the last decade. Licensed therapies which activate the immune system to target cancer cells can be broadly divided into two classes. The first class are antibodies that inhibit immune checkpoint signalling, known as immune checkpoint inhibitors (ICIs). The second class are cell‐based immune therapies including chimeric antigen receptor T lymphocyte (CAR‐T) cell therapies, natural killer (NK) cell therapies, and tumour infiltrating lymphocyte (TIL) therapies. The clinical efficacy of all these treatments generally outweighs the risks, but there is a high rate of immune‐related adverse events (irAEs), which are often unpredictable in timing with clinical sequalae ranging from mild (e.g. rash) to severe or even fatal (e.g. myocarditis, cytokine release syndrome) and reversible to permanent (e.g. endocrinopathies).The mechanisms underpinning irAE pathology vary across different irAE complications and syndromes, reflecting the broad clinical phenotypes observed and the variability of different individual immune responses, and are poorly understood overall. Immune‐related cardiovascular toxicities have emerged, and our understanding has evolved from focussing initially on rare but fatal ICI‐related myocarditis with cardiogenic shock to more common complications including less severe ICI‐related myocarditis, pericarditis, arrhythmias, including conduction system disease and heart block, non‐inflammatory heart failure, takotsubo syndrome and coronary artery disease. In this scientific statement on the cardiovascular toxicities of immune therapies for cancer, we summarize the pathophysiology, epidemiology, diagnosis, and management of ICI, CAR‐T, NK, and TIL therapies. We also highlight gaps in the literature and where future research should focus.

BackgroundCancer patients are at risk of pulmonary embolism (PE). Catheter-based therapies (CBT) are novel reperfusion options for PE though data in patients with cancer is lacking.Study design and methodsPatients with intermediate- or high-risk PE were identified using the National Readmission Database (NRD) from 2017 to 2020. Primary outcome were in-hospital death and 90-day readmission. Secondary outcomes were in-hospital bleeding, 90-day readmission for venous thromboembolism (VTE)-related or right heart failure-related reasons and bleeding. Propensity scores were estimated using logistic regression and inverse-probability treatment weighting (IPTW) was utilized to compare outcomes between CBT and no CBT as well as CBT versus systemic thrombolysis.ResultsA total of 7785 patients were included (2511 with high-risk PE) of whom 1045 (13.4%) were managed with CBT. After IPTW, CBT was associated with lower rates of index hospitalization death (OR 0.89, 95% CI 0.83-0.96) and 90-day readmission (HR 0.75, 95% CI 0.69-0.81) but higher rates of in-hospital bleeding (OR 1.11, 95% CI 1.03-1.20) which was predominantly post-procedural bleeding. CBT was associated with lower risk of major bleeding (20.8% vs 24.8%; OR 0.80, 95% CI 0.68-0.94) compared with systemic thrombolysis.InterpretationAmong patients with cancer with intermediate or high-risk PE, CBT was associated with lower in-hospital death and 90-day readmission. CBT was also associated with decreased risk of index hospitalization major bleeding compared with systemic thrombolysis. Prospective, randomized trials with inclusion of patients with cancer are needed to confirm these findings.

BackgroundThe optimal timing of noncardiac surgery (NCS) following transcatheter aortic valve replacement (TAVR) for aortic stenosis has not been elucidated by current national guidelines.ObjectivesThe aim of this study was to evaluate the effect of the time interval between TAVR and NCS (Δt) on the perioperative risk of major adverse events (MAEs).MethodsAll adult admissions for isolated TAVR for aortic stenosis were identified in the 2016 to 2020 Nationwide Readmissions Database. Patients who received NCS on subsequent admission were included for analysis and grouped by Δt as follows: ≤30, 31 to 60, 61 to 90, and >90 days. Multivariable regression models were constructed to examine the association of Δt with ensuing outcomes.ResultsOf 3,098 patients (median age = 79 years, 41.6% female), 19.1% underwent NCS at ≤30 days, 22.9% at 31 to 60 days, 16.7% at 61 to 90 days, and 41.3% at >90 days. After adjustment, the odds of MAEs were similar for operations performed at ≤30 days (adjusted OR [AOR]: 1.05; 95% confidence interval [CI]: 0.74-1.50), 31 to 60 days (AOR: 0.97; 95% CI: 0.71-1.31), and 61 to 90 days (AOR: 0.95; 95% CI: 0.67-1.34), with those at >90 days as reference. When examining the average marginal effect of the interval to surgery, risk-adjusted MAE rates were statistically similar across Δt groups for elective status and NCS risk category combinations.ConclusionsNCS within 30, 31 to 60, or 61 to 90 days after TAVR was not associated with increased odds of MAEs compared with operations after 90 days irrespective of NCS risk category or elective status. Our findings suggest that the interval between NCS and TAVR may not be an accurate predictor of MAE risk in this population.

Objective: We reviewed our institutional experience of radical prostatectomy with and without preoperative multiparametric magnetic resonance imaging (mpMRI) to assess the impact of preoperative prostate mpMRI on surgical outcomes of radical prostatectomy. Methods: We identified patients at our institution who underwent radical prostatectomy for prostate cancer (PCa) between January 2012 and December 2017 (n = 1044). Using propensity scoring analysis, patients who underwent preoperative mpMRI (n = 285) were matched 1:1 to patients who did not receive preoperative mpMRI (n = 285). Multivariable regression analysis was performed to identify factors predictive of operative time, estimated blood loss (EBL), lymph node yield, rates of complications within 30 days, and positive surgical margin (PSM). Results: There were no significant differences in operative time, EBL, PSM, lymph node yield, or complication rates between the two cohorts. Multivariable analysis demonstrated that preoperative mpMRI was not predictive of the measured perioperative outcomes. Significant comorbidity (Charlson Comorbidity Index ≥3) was the sole predictor of perioperative complications (P = 0.015). Increasing biopsy Gleason score predicted increased lymph node yield (P < 0.001). The probability of PSM was associated with increasing preoperative prostate-specific antigen (odds ratio 1.036, P = 0.009). Body mass index was a predictor of operative time (P = 0.016) and EBL (P = 0.001). Conclusions: Although preoperative mpMRI has an important role in the diagnosis and staging of PCa, it does not impact perioperative radical prostatectomy outcomes. Our findings do not support the routine use of preoperative mpMRI for surgical planning in patients already diagnosed with clinically localized PCa., Author(s): Christopher K. Bozorgmehr [1]; Johnny Wang [1]; James T. Gross [1]; Nicholas A. Pickersgill (corresponding author) [1,2]; Joel M. Vetter [1]; Joseph E. Ippolito [3]; Eric H. Kim [4,5] [...]

With the widespread adoption of intranasal radiofrequency (RF) devices, our objective was to report national adverse events (AEs) associated with their use. The Food and Drug Administration's Manufacturer and User Facility Device Experience was queried. A total of 24 device-related AEs were reported, 11 (45.8%) for Celon® (Olympus), 3 (12.5%) for Vivaer® (Aerin), 2 (8.3%) for Neuromark® (Neurent), and 8 (33.3%) for Rhinaer® (Aerin). Seven (63.6%) of the Celon®-related complications were related to tissue necrosis (largely user error-related), but 1 (9.1%) episode of pediatric ocular palsy was also reported. Vivaer® complications included synechiae formation, a mucosal perforation, and a case of empty nose syndrome. Of the posterior nasal nerve ablating devices, 9 of 10 AEs were epistaxes, of which 7 (77.8%) required operative intervention. Surgeons should exercise vigilance and tissue-appropriate device settings when utilizing RF devices. Epistaxis and tissue necrosis may occur, as well as more rare, but devastating, complications.

Introduction: Timely diagnosis of patients affected by an emerging infectious disease plays a crucial role in treating patients and avoiding disease spread. In prior research, we developed an approach by using machine learning (ML) algorithms to predict serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection based on clinical features of patients visiting an emergency department (ED) during the early coronavirus 2019 (COVID-19) pandemic. In this study, we aimed to externally validate this approach within a distinct ED population.Methods: To create our training/validation cohort (model development) we collected data retrospectively from suspected COVID-19 patients at a US ED from February 23–May 12, 2020. Another dataset was collected as an external validation (testing) cohort from an ED in another country from May 12–June 15, 2021. Clinical features including patient demographics and triage information were used to train and test the models. The primary outcome was the confirmed diagnosis of COVID-19, defined as a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. We employed three different ML algorithms, including gradient boosting, random forest, and extra trees classifiers, to construct the predictive model. The predictive performances were evaluated with the area under the receiver operating characteristic curve (AUC) in the testing cohort.Results: In total, 580 and 946 ED patients were included in the training and testing cohorts, respectively. Of them, 98 (16.9%) and 180 (19.0%) were diagnosed with COVID-19. All the constructed ML models showed acceptable discrimination, as indicated by the AUC. Among them, random forest (0.785, 95% confidence interval [CI] 0.747–0.822) performed better than gradient boosting (0.774, 95% CI 0.739–0.811) and extra trees classifier (0.72, 95% CI 0.677–0.762). There was no significant difference between the constructed models.Conclusion: Our study validates the use of ML for predicting COVID-19 in the ED and demonstrates its potential for predicting emerging infectious diseases based on models built by clinical features with temporal and spatial heterogeneity. This approach holds promise for scenarios where effective diagnostic tools for an emerging infectious disease may be lacking in the future.

Pulmonary embolism (PE) is a common complication among patients with cancer and is a significant contributor to morbidity and mortality. Catheter-based therapies (CBT), including catheter-directed thrombolysis (CDT) and mechanical thrombectomy, have been developed and are used in patients with intermediate or high-risk PE. However, there is a paucity of data on outcomes in patients with cancer as most clinical studies exclude this group of patients.To characterize outcomes of patients with cancer admitted with intermediate or high-risk PE treated with CBT compared with no CBT.Patients with an admission diagnosis of intermediate or high-risk PE and a history of cancer from October 2015 to December 2018 were identified using the National Inpatient Sample. Outcomes of interest were in-hospital death or cardiac arrest (CA) and major bleeding. Inverse probability treatment weighting (IPTW) was utilized to compare outcomes between patients treated with and without CBT. Variables that remained unbalanced after IPTW were adjusted using multivariable logistic regression.A total of 2084 unweighted admissions (10,420 weighted) for intermediate or high-risk PE and cancer were included, of which 136 (6.5%) were treated with CBT. After IPTW, CBT was associated with lower death or CA (aOR 0.54, 95% CI 0.46-0.64) but higher major bleeding (aOR 1.41, 95% CI 1.21-1.65). After stratifying by PE risk type, patients treated with CBT had lower risk of death or CA in both intermediate (aOR 0.52, 95% CI 0.36-0.75) and high-risk PE (aOR 0.48, 95% CI 0.33-0.53). However, patients with CBT were associated with increased risk of major bleeding in intermediate-risk PE (aOR 2.12, 95% CI 1.67-2.69) but not in those with high-risk PE (aOR 0.84, 95% CI 0.66-1.07).Among patients with cancer hospitalized with intermediate or high-risk PE, treatment with CBT was associated with lower risk of in-hospital death or CA but higher risk of bleeding. Prospective studies and inclusion of patients with cancer in randomized trials are warranted to confirm our findings.

Objective We reviewed our institutional experience of radical prostatectomy with and without preoperative multiparametric magnetic resonance imaging (mpMRI) to assess the impact of preoperative prostate mpMRI on surgical outcomes of radical prostatectomy. Methods We identified patients at our institution who underwent radical prostatectomy for prostate cancer (PCa) between January 2012 and December 2017 (n = 1044). Using propensity scoring analysis, patients who underwent preoperative mpMRI (n = 285) were matched 1:1 to patients who did not receive preoperative mpMRI (n = 285). Multivariable regression analysis was performed to identify factors predictive of operative time, estimated blood loss (EBL), lymph node yield, rates of complications within 30 days, and positive surgical margin (PSM). Results There were no significant differences in operative time, EBL, PSM, lymph node yield, or complication rates between the two cohorts. Multivariable analysis demonstrated that preoperative mpMRI was not predictive of the measured perioperative outcomes. Significant comorbidity (Charlson Comorbidity Index ≥3) was the sole predictor of perioperative complications (P = 0.015). Increasing biopsy Gleason score predicted increased lymph node yield (P < 0.001). The probability of PSM was associated with increasing preoperative prostate-specific antigen (odds ratio 1.036, P = 0.009). Body mass index was a predictor of operative time (P = 0.016) and EBL (P = 0.001). Conclusions Although preoperative mpMRI has an important role in the diagnosis and staging of PCa, it does not impact perioperative radical prostatectomy outcomes. Our findings do not support the routine use of preoperative mpMRI for surgical planning in patients already diagnosed with clinically localized PCa.

Abstract Background In recent years, covalent modifications on RNA nucleotides have emerged as pivotal moieties influencing the structure, function, and regulatory processes of RNA Polymerase II transcripts such as mRNAs and lncRNAs. However, our understanding of their biological roles and whether these roles are conserved across eukaryotes remains limited. Results In this study, we leveraged standard polyadenylation-enriched RNA-sequencing data to identify and characterize RNA modifications that introduce base-pairing errors into cDNA reads. Our investigation incorporated data from three Poaceae (Zea mays, Sorghum bicolor, and Setaria italica), as well as publicly available data from a range of stress and genetic contexts in Sorghum and Arabidopsis thaliana. We uncovered a strong enrichment of RNA covalent modifications (RCMs) deposited on a conserved core set of nuclear mRNAs involved in photosynthesis and translation across these species. However, the cohort of modified transcripts changed based on environmental context and developmental program, a pattern that was also conserved across flowering plants. We determined that RCMs can partly explain accession-level differences in drought tolerance in Sorghum, with stress-associated genes receiving a higher level of RCMs in a drought tolerant accession. To address function, we determined that RCMs are significantly enriched near exon junctions within coding regions, suggesting an association with splicing. Intriguingly, we found that these base-pair disrupting RCMs are associated with stable mRNAs, are highly correlated with protein abundance, and thus likely associated with facilitating translation. Conclusions Our data point to a conserved role for RCMs in mRNA stability and translation across the flowering plant lineage.

Abstract Background CINNAMYL ALCOHOL DEHYDROGENASE (CAD) catalyzes the NADPH-dependent reduction of cinnamaldehydes into cinnamyl alcohols and is a key enzyme found at the final step of the monolignol pathway. Cinnamyl alcohols and their conjugates are subsequently polymerized in the secondary cell wall to form lignin. CAD genes are typically encoded by multi-gene families and thus traditionally organized into general classifications of functional relevance. Results In silico analysis of the hexaploid Triticum aestivum genome revealed 47 high confidence TaCAD copies, of which three were determined to be the most significant isoforms (class I) considered bone fide CADs. Class I CADs were expressed throughout development both in RNAseq data sets as well as via qRT-PCR analysis. Of the 37 class II TaCADs identified, two groups were observed to be significantly co-expressed with class I TaCADs in developing tissue and under chitin elicitation in RNAseq data sets. These co-expressed class II TaCADs were also found to be phylogenetically unrelated to a separate clade of class II TaCADs previously reported to be an influential resistance factor to pathogenic fungal infection. Lastly, two groups were phylogenetically identified as class III TaCADs, which possess distinct conserved gene structures. However, the lack of data supporting their catalytic activity for cinnamaldehydes and their bereft transcriptional presence in lignifying tissues challenges their designation and function as CADs. Conclusions Taken together, our comprehensive transcriptomic analyses suggest that TaCAD genes contribute to overlapping but nonredundant functions during T. aestivum growth and development across a wide variety of agroecosystems and provide tolerance to various stressors.