Citations

Abstract Background 5- Fluorouracil (5-FU) is one of the most common chemotherapeutic agents used in treating solid tumors, and the 5-FU-induced cardiotoxicity is the second cause of cardiotoxicity induced by chemotherapeutic drugs. Propolis (Pro) has vigorous anti-inflammatory activity. Its cardio-protective characteristic against doxorubicin-induced cardiotoxicity was previously proven. The current study aimed to appraise the effect of Pro on 5-FU-induced cardiotoxicity in rats. Methods Twenty-four male Wistar rats were divided into four groups: Control, 5-FU, 5-FU + Pro 250 mg/kg, and 5-FU + Colchicine (CLC) 5 mg/kg. Different hematological, serological, biochemical, histopathological, and molecular assays were performed to assess the study aim. Moreover, rat myocardium (H9C2(2 − 1)) and human skin fibroblast (HNFF-P18) cell lines were also used to assess this protective effect in-vitro. Results 5-FU resulted in significant cardiotoxicity represented by an increase in malondialdehyde (MDA) levels, cyclooxygenase-2 (COX-2), and tumor necrosis factor-α (TNF-α) expression, cardiac enzyme levels, and histopathological degenerations. 5-FU treatment also decreased bodyweight, total anti-oxidant capacity (TAC), catalase (CAT) levels, blood cell counts, and hemoglobin (Hb) levels. In addition, 5-FU disrupted ECG parameters, including increased elevation in the ST-segment and increased QRS complex and QTc duration. Treating with Pro reduced oxidative stress, cardiac enzymes, histopathological degenerations, and COX-2 expression in cardiac tissue alleviated ECG disturbances and increased the number of blood cells and TAC levels. Moreover, 5-FU-induced bodyweight loss was ameliorated after treatment with Pro. Conclusion Our results demonstrated that treatment with Pro significantly improved cardiotoxicity induced by 5-FU in rats.

AbstractBackground and objectivePleuroscopy with pleural biopsy has a high sensitivity for malignant pleural effusion (MPE). Because MPEs tend to recur, concurrent diagnosis and treatment of MPE during pleuroscopy is desired. However, proceeding directly to treatment at the time of pleuroscopy requires confidence in the on‐site diagnosis. The study's primary objective was to create a predictive model to estimate the probability of MPE during pleuroscopy.MethodsA prospective observational multicentre cohort study of consecutive patients undergoing pleuroscopy was conducted. We used a logistic regression model to evaluate the probability of MPE with relation to visual assessment, rapid on‐site evaluation (ROSE) of touch preparation and presence of pleural nodules/masses on computed tomography (CT). To assess the model's prediction accuracy, a bootstrapped training/testing approach was utilized to estimate the cross‐validated area under the receiver operating characteristic curve.ResultsOf the 201 patients included in the study, 103 had MPE. Logistic regression showed that higher level of malignancy on visual assessment is associated with higher odds of MPE (OR = 34.68, 95% CI = 9.17–131.14,p < 0.001). The logistic regression also showed that higher level of malignancy on ROSE of touch preparation is associated with higher odds of MPE (OR = 11.63, 95% CI = 3.85–35.16,p < 0.001). Presence of pleural nodules/masses on CT is associated with higher odds of MPE (OR = 6.61, 95% CI = 1.97–22.1,p = 0.002). A multivariable logistic regression model of final pathologic status with relation to visual assessment, ROSE of touch preparation and presence of pleural nodules/masses on CT had a cross‐validated AUC of 0.94 (95% CI = 0.91–0.97).ConclusionA prediction model using visual assessment, ROSE of touch preparation and CT scan findings demonstrated excellent predictive accuracy for MPE. Further validation studies are needed to confirm our findings.

The major pulmonary complication of rheumatoid arthritis (RA) is interstitial lung disease (ILD), which causes significant morbidity and mortality and influences the natural course of disease. Recent advances in the management of arthritis have improved patient outcomes. However, exceptionally high medical needs still remain for effective therapies for the patients with ILD in RA. Better understanding of the shared and distinct pathophysiology of fibrotic diseases led to the development of novel antifibrotic agents such as nintedanib and pirfenidone. The further stratification analysis of the phase III INBUILD trial demonstrated beneficial effects of nintedanib in RA-ILD with a progressive phenotype by reducing the rate of decline in forced vital capacity (FVC) over 52 weeks by 60%. Pirfenidone is another antifibrotic agent currently under phase II clinical study (TRAIL1) aiming to evaluate its effects for RA-ILD. This review provides an overview of state-of-the-art pathogenesis and the current therapeutic options for RA-ILD, with a focus on antifibrotic strategies.

The antigen specificity of Anti‐Neuronal Nuclear Antibody‐type 3 (ANNA3)‐IgG is unknown. We identified Dachshund‐homolog 1 (DACH1) as the ANNA3 autoantigen and confirmed it by antigen‐specific assays, immunohistochemical colocalization and immune absorption experiments. Patients' median age was 63.5 years (range, 49–88); 67% were female. Neurological manifestations (information available for 30 patients) included one or more of neuropathy, 12; cognitive difficulties, 11; ataxia, 8; dysautonomia, 7. Evidence of a neoplasm was present in 27 of 30 (90%), most of neuroendocrine lineage. DACH1‐IgG is rare and represents a novel proposed biomarker of neurological autoimmunity and cancer. ANN NEUROL 2022;91:670–675

AbstractPurposeTo evaluate the relative biological effectiveness (RBE)‐weighted dose to the heart and to estimate RBE uncertainties when assuming a constant RBE of 1.1, for breast cancer patients receiving intensity‐modulated proton therapy (IMPT). Further, to study the impact of RBE uncertainties on the risk of an acute coronary event (ACE).Material and methodsWe analyzed 20 patients who received IMPT to either the left breast (n = 10) or left chest wall (n = 10) and regional lymph nodes. The Monte Carlo simulation engine, MCsquare, was used to simulate the dose‐averaged linear energy transfer (LETd) map. The RBE‐weighted dose to the heart and its substructures was calculated using three different RBE models. The risk of ACE was estimated per its linear relationship with mean heart dose (MHD) as established by Darby et al.ResultsThe median MHD increased from 1.33 GyRBE assuming an RBE of 1.1 to 1.64, 1.87, and 1.99 GyRBE when using the RBE‐weighted dose models. The median values (and ranges) of the excess absolute risk of ACE were 0.4% (0.1%–0.8%) when assuming an RBE of 1.1, and 0.6% (0.2%–1.0%), 0.6% (0.2%–1.1%), and 0.7% (0.2%–1.1%) with the RBE‐weighted models. For our patient cohort, the maximum excess absolute risk of ACE increased by 0.3% with the RBE‐weighted doses compared to the constant RBE of 1.1, reaching an excess absolute ACE risk of 1.1%. The interpatient LETd variation was small for the relevant high‐dose regions of the heart.ConclusionAll three RBE models predicted a higher biological dose compared to the clinical standard dose assuming a constant RBE of 1.1. An underestimation of the biological dose results in underestimation of the ACE risk. Analyzing the voxel‐by‐voxel biological dose and the LET map alongside clinical outcomes is warranted in the development of a more accurate normal‐tissue complication probability model.

Abstract Prostate cancer remains the second leading cause of cancer death among American men. Radiotherapy is a potentially curative treatment for localized prostate cancer, and failure to control localized disease contributes to the majority of prostate cancer deaths. Neuroendocrine differentiation (NED) in prostate cancer, a process by which prostate adenocarcinoma cells transdifferentiate into neuroendocrine-like (NE-like) cells, is an emerging mechanism of resistance to cancer therapies and contributes to disease progression. NED also occurs in response to treatment to promote the development of treatment-induced neuroendocrine prostate cancer (NEPC), a highly aggressive and terminal stage disease. We previously demonstrated that by mimicking clinical radiotherapy protocol, fractionated ionizing radiation (FIR) induces prostate cancer cells to undergo NED in vitro and in vivo. Here, we performed transcriptomic analysis and confirmed that FIR-induced NE-like cells share some features of clinical NEPC, suggesting that FIR-induced NED represents a clinically relevant model. Furthermore, we demonstrated that protein arginine methyltransferase 5 (PRMT5), a master epigenetic regulator of the DNA damage response and a putative oncogene in prostate cancer, along with its cofactors pICln and MEP50, mediate FIR-induced NED. Knockdown of PRMT5, pICln, or MEP50 during FIR-induced NED and sensitized prostate cancer cells to radiation. Significantly, PRMT5 knockdown in prostate cancer xenograft tumors in mice during FIR prevented NED, enhanced tumor killing, significantly reduced and delayed tumor recurrence, and prolonged overall survival. Collectively, our results demonstrate that PRMT5 promotes FIR-induced NED and suggests that targeting PRMT5 may be a novel and effective radiosensitization approach for prostate cancer radiotherapy.

AbstractBackgroundThe incidence of colorectal cancer (CRC) among individuals aged younger than 50 years has been increasing. As screening guidelines lower the recommended age of screening initiation, concerns including the burden on screening capacity and costs have been recognized, suggesting that an individualized approach may be warranted. We developed risk prediction models for early-onset CRC that incorporate an environmental risk score (ERS), including 16 lifestyle and environmental factors, and a polygenic risk score (PRS) of 141 variants.MethodsRelying on risk score weights for ERS and PRS derived from studies of CRC at all ages, we evaluated risks for early-onset CRC in 3486 cases and 3890 controls aged younger than 50 years. Relative and absolute risks for early-onset CRC were assessed according to values of the ERS and PRS. The discriminatory performance of these scores was estimated using the covariate-adjusted area under the receiver operating characteristic curve.ResultsIncreasing values of ERS and PRS were associated with increasing relative risks for early-onset CRC (odds ratio per SD of ERS = 1.14, 95% confidence interval [CI] = 1.08 to 1.20; odds ratio per SD of PRS = 1.59, 95% CI = 1.51 to 1.68), both contributing to case-control discrimination (area under the curve = 0.631, 95% CI = 0.615 to 0.647). Based on absolute risks, we can expect 26 excess cases per 10 000 men and 21 per 10 000 women among those scoring at the 90th percentile for both risk scores.ConclusionsPersonal risk scores have the potential to identify individuals at differential relative and absolute risk for early-onset CRC. Improved discrimination may aid in targeted CRC screening of younger, high-risk individuals, potentially improving outcomes.

PurposeTo improve the estimation of coil sensitivity functions from limited auto‐calibration signals (ACS) in SENSE‐based reconstruction for brain imaging.MethodsWe propose to use deep learning to estimate coil sensitivity functions by leveraging information from previous scans obtained using the same RF receiver system. Specifically, deep convolutional neural networks were designed to learn an end‐to‐end mapping from the initial sensitivity to the high‐resolution counterpart. Sensitivity alignment was further proposed to reduce the geometric variation caused by different subject positions and imaging FOVs. Cross‐validation with a small set of datasets was performed to validate the learned neural network. Iterative SENSE reconstruction was adopted to evaluate the utility of the sensitivity functions from the proposed and conventional methods.ResultsThe proposed method produced improved sensitivity estimates and SENSE reconstructions compared to the conventional methods in terms of aliasing and noise suppression with very limited ACS data. Cross‐validation with a small set of data demonstrated the feasibility of learning coil sensitivity functions for brain imaging. The network learned on the spoiled GRE data can be applied to predict sensitivity functions for spin‐echo and MPRAGE datasets.ConclusionA deep learning‐based method has been proposed for improving the estimation of coil sensitivity functions. Experimental results have demonstrated the feasibility and potential of the proposed method for improving SENSE‐based reconstructions especially when the ACS data are limited.

Progress in development of prognostic and therapeutic options for the rare cholestatic liver diseases, primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC), is hampered by limited knowledge of their pathogeneses. In particular, the potential role of hepatotoxic and/or metabolism‐altering environmental chemicals in the pathogenesis of these diseases remains relatively unstudied. Moreover, the extent to which metabolic pathways are altered due to ongoing cholestasis and subsequent liver damage or possibly influenced by hepatotoxic chemicals is poorly understood. In this study, we applied a comprehensive exposomics‐metabolomics approach to uncover potential pathogenic contributors to PSC and PBC. We used untargeted high‐resolution mass spectrometry to characterize a wide range of exogenous chemicals and endogenous metabolites in plasma and tested them for association with disease. Exposome‐wide association studies (EWAS) identified environmental chemicals, including pesticides, additives and persistent pollutants, that were associated with PSC and/or PBC, suggesting potential roles for these compounds in disease pathogenesis. Metabolome‐wide association studies (MWAS) found disease‐associated alterations to amino acid, eicosanoid, lipid, co‐factor, nucleotide, mitochondrial and microbial metabolic pathways, many of which were shared between PSC and PBC. Notably, this analysis implicates a potential role of the 5‐lipoxygenase pathway in the pathogenesis of these diseases. Finally, EWAS × MWAS network analysis uncovered linkages between environmental agents and disrupted metabolic pathways that provide insight into potential mechanisms for PSC and PBC. Conclusion: This study establishes combined exposomics‐metabolomics as a generalizable approach to identify potentially pathogenic environmental agents and enumerate metabolic alterations that may impact PSC and PBC, providing a foundation for diagnostic and therapeutic strategies.