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Nighttime oxidation of monoterpenes (MT) via the nitrate radical (NO3) and ozone (O3) contributes to the formation of secondary organic aerosol (SOA). This study uses observations in Atlanta, Georgia from 2011 to 2022 to quantify trends in nighttime production of NO3 (PNO3) and O3 concentrations and compare to model outputs from the EPA's Air QUAlity TimE Series Project (EQUATES). We present urban‐suburban gradients in nighttime NO3 and O3 concentrations and quantify their fractional importance (F) for MT oxidation. Both observations and EQUATES show a decline in PNO3, with modeled PNO3 declining faster than observations. Despite decreasing PNO3, we find that NO3 continues to dominate nocturnal boundary layer (NBL) MT oxidation (FNO3 = 60%) in 2017, 2021, and 2022, which is consistent with EQUATES (FNO3 = 80%) from 2013 to 2019. This contrasts an anticipated decline in FNO3 based on prior observations in the nighttime residual layer, where O3 is the dominant oxidant. Using two case studies of heatwaves in summer 2022, we show that extreme heat events can increase NO3 concentrations and FNO3, leading to short MT lifetimes (<1 hr) and high gas‐phase organic nitrate production. Regardless of the presence of heatwaves, our findings suggest sustained organic nitrate aerosol formation in the urban SE US under declining NOx emissions, and highlight the need for improved representation of extreme heat events in chemistry‐transport models and additional observations along urban to rural gradients. Plain Language Summary: Monoterpenes are important precursors of secondary organic aerosol (SOA), which influence air quality and climate. At night, they react with the nitrate radical (NO3) and ozone (O3). Trends in these two oxidants and their role on air quality in the southeastern United Sates (SE US) is partially dictated by changes in nitrogen oxide (NOx = NO + NO2) emissions which have declined in recent years. We find that NO3 dominates present‐day monoterpene loss in the summer, and may continue to do so even as NOx concentrations decrease in the future. We show that heatwaves in the SE US further elevate both O3 and NO3 concentrations at night, with a larger relative importance for NO3. We compare observations to a regional air quality model, and find the model overpredicts both oxidant concentrations. This overprediction may impact model‐based studies of future nighttime chemistry. Key Points: Nitrate radical (NO3) continues to control nocturnal boundary layer monoterpene oxidation in the urban SE USRegional model overpredicts oxidant concentrations and fractional NO3 contribution to monoterpene lossExtreme heat events increase nighttime NO3 concentrations, monoterpene oxidation rates, and gas‐phase organic nitrate production [ABSTRACT FROM AUTHOR]

Isoprene emitted by vegetation is an important precursor of secondary organic aerosol (SOA), but the mechanism and yields are uncertain. Aerosol is prevailingly aqueous under the humid conditions typical of isoprene-emitting regions. Here we develop an aqueous-phase mechanism for isoprene SOA formation coupled to a detailed gas-phase isoprene oxidation scheme. The mechanism is based on aerosol reactive uptake coefficients (γ) for water-soluble isoprene oxidation products, including sensitivity to aerosol acidity and nucleophile concentrations. We apply this mechanism to simulation of aircraft (SEAC4RS) and ground-based (SOAS) observations over the southeast US in summer 2013 using the GEOS-Chem chemical transport model. Emissions of nitrogen oxides (NOx ≡ NO+NO2/ over the southeast US are such that the peroxy radicals produced from isoprene oxidation (ISOPO2) react significantly with both NO (high-NOx pathway) and HO2 (low-NOx pathway), leading to different suites of isoprene SOA precursors. We find a mean SOA mass yield of 3.3% from isoprene oxidation, consistent with the observed relationship of total fine organic aerosol (OA) and formaldehyde (a product of isoprene oxidation). Isoprene SOA production is mainly contributed by two immediate gasphase precursors, isoprene epoxydiols (IEPOX, 58% of isoprene SOA) from the low-NOx pathway and glyoxal (28 %) from both low- and high-NOx pathways. This speciation is consistent with observations of IEPOX SOA from SOAS and SEAC4RS. Observations show a strong relationship between IEPOX SOA and sulfate aerosol that we explain as due to the effect of sulfate on aerosol acidity and volume. Isoprene SOA concentrations increase as NOx emissions decrease (favoring the low-NOx pathway for isoprene oxidation), but decrease more strongly as SO2 emissions decrease (due to the effect of sulfate on aerosol acidity and volume). The US Environmental Protection Agency (EPA) projects 2013-2025 decreases in anthropogenic emissions of 34% for NOx (leading to a 7% increase in isoprene SOA) and 48% for SO2 (35% decrease in isoprene SOA). Reducing SO2 emissions decreases sulfate and isoprene SOA by a similar magnitude, representing a factor of 2 co-benefit for PM2.5 from SO2 emission controls. [ABSTRACT FROM AUTHOR]

Isoprene emitted by vegetation is an important precursor of secondary organic aerosol (SOA), but the mechanism and yields are uncertain. Aerosol is prevailingly aqueous under the humid conditions typical of isoprene-emitting regions. Here we develop an aqueous-phase mechanism for isoprene SOA formation coupled to a detailed gasphase isoprene oxidation scheme. The mechanism is based on aerosol reactive uptake probabilities (γ) for water-soluble isoprene oxidation products, including sensitivity to aerosol acidity and nucleophile concentrations. We apply this mechanism to simulation of aircraft (SEAC4RS) and ground-based (SOAS) observations over the Southeast US in summer 2013 using the GEOS-Chem chemical transport model. Emissions of nitrogen oxides (NOx = NO+NO2) over the Southeast US are such that the peroxy radicals produced from isoprene oxidation (ISOPO2) react significantly with both NO (high-NOx pathway) and HO2 (low-NOx pathway), leading to different suites of isoprene SOA precursors. We find a mean SOA mass yield of 3.3% from isoprene oxidation, consistent with the observed relationship of OA and formaldehyde (a product of isoprene oxidation). The yield is mainly contributed by two immediate gas-phase precursors, isoprene epoxydiols (IEPOX, 58% of isoprene SOA) from the low-NOx pathway and glyoxal (28 %) from both low- and high-NOx pathways. This speciation is consistent with observations of IEPOX SOA from SOAS and SEAC4RS. Observations show a strong relationship between IEPOX SOA and sulfate aerosol that we explain as due to the indirect effect of sulfate on aerosol acidity and volume, rather than a direct mechanistic role for sulfate. Isoprene SOA concentrations increase as NOx emissions decrease (favoring the low-NOx pathway for isoprene oxidation), but decrease as SO2 emissions decrease (due to the effect of sulfate on aerosol acidity and volume). The US EPA projects 2013-2025 decreases in anthropogenic emissions of 34% for NOx (leading to 7% increase in isoprene SOA) and 48% for SO2 (35% decrease in isoprene SOA). The combined projected decreases in NOx and SO2 emissions reduce isoprene SOA yields from 3.3 to 2.3 %. Reducing SO2 emissions decreases sulfate and isoprene SOA by a similar magnitude, representing a factor of 2 co-benefit for PM2.5 from SO2 emission controls. [ABSTRACT FROM AUTHOR]

Community Multiscale Air Quality (CMAQ) model simulations utilizing the volatility basis set (VBS) treatment for organic aerosols (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of organic aerosol (OA) in southern California. CMAQ-VBS (OA lumped by volatility, semivolatile POA) underpredicted total organic carbon (OC) at CSN (-25.5% Normalized Median Bias (NMdnB)) and IMPROVE (-63.9% NMdnB) locations and total OC was underpredicted to a greater degree compared to the CMAQ-AE6 (9.9 and -55.7% NMdnB, respectively; semi-explicit OA treatment, SOA lumped by parent hydrocarbon, nonvolatile POA). However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA indicated that CMAQ-VBS better represented the diurnal profile and the primary/secondary split of OA. CMAQ-VBS secondary organic aerosol (SOA) underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate of SOA) concentration by a factor of 5.2 (4.7 µg m-3 measured vs. 0.9 µg m-3 modeled), a considerable improvement to CMAQ-AE6 SOA predictions, which were approximately 24× lower than the average AMS OOA concentration. We use two new methods, based on species ratios and on a simplified SOA parameterization from the observations, to apportion the SOA underprediction for CMAQ-VBS to too slow photochemical oxidation (estimated as 1.5× lower than observed at Pasadena using - log (NOx: NOy)), low intrinsic SOA formation efficiency (low by 1.6 to 2× for Pasadena), and too low emissions or too high dispersion for the Pasadena site (estimated to be 1.6 to 2.3× too low/high). The first and third factors will be similar for CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7×. For CMAQ-VBS, 90% of the anthropogenic SOA mass formed was attributed to aged secondary semivolatile vapors (70% originating from volatile organic compounds (VOCs) and 20% from intermediate volatility compounds (IVOCs)). From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48%, and consistent with a substantial fraction of cooking OA in the observations), compared to 18% from gasoline vehicle emissions, 13% from biomass burning (in the form of residential wood combustion), and 8% from diesel vehicle emissions. All "other" inventoried emission sources (e.g. industrial/point sources) comprised the final 13%. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 (1.16 µg m-3 modeled vs. 2.05 µg m-3 observed) compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but did well to capture the AMS diurnal profile of HOA and CIOA, with the exception of the midday peak. We estimated that using the National Emission Inventory (NEI) POA emissions without scaling to represent SVOCs underestimates SVOCs by ~1.7×. [ABSTRACT FROM AUTHOR]

Background and Purpose We aimed to characterize the pharmacology and electrophysiology of N-[3-(1 H-benzimidazol-2-yl)-4-chloro-phenyl]pyridine-3-carboxamide ( AZSMO-23), an activator of the human ether-a-go-go-related gene ( hERG)-encoded K+ channel ( Kv11.1). Experimental Approach Automated electrophysiology was used to study the pharmacology of AZSMO-23 on wild-type ( WT), Y652 A, F656 T or G628 C/ S631 C hERG, and on other cardiac ion channels. Its mechanism of action was characterized with conventional electrophysiology. Key Results AZSMO-23 activated WT hERG pre-pulse and tail current with EC50 values of 28.6 and 11.2 μM respectively. At 100 μM, pre-pulse current at +40 mV was increased by 952 ± 41% and tail current at −30 mV by 238 ± 13% compared with vehicle values. The primary mechanism for this effect was a 74.5 mV depolarizing shift in the voltage dependence of inactivation, without any shift in the voltage dependence of activation. Structure-activity relationships for this effect were remarkably subtle, with close analogues of AZSMO-23 acting as hERG inhibitors. AZSMO-23 blocked the mutant channel, hERG Y652 A, but against another mutant channel, hERG F656 T, its activator activity was enhanced. It inhibited activity of the G628 C/ S631 C non-inactivating hERG mutant channel. AZSMO-23 was not hERG selective, as it blocked hKv4.3- hKChIP2.2, hCav3.2 and hKv1.5 and activated hCav1.2/β2/α2δ channels. Conclusion and Implications The activity of AZSMO-23 and those of its close analogues suggest these compounds may be of value to elucidate the mechanism of type 2 hERG activators to better understand the pharmacology of this area from both a safety perspective and in relation to treatment of congenital long QT syndrome. [ABSTRACT FROM AUTHOR]

Background: Serum PSA and digital rectal examination remain the key diagnostic tools for detecting prostate cancer. However, due to the limited specificity of serum PSA, the applicability of this marker continues to be controversial. Recent use of image-guided biopsy along with pathological assessment and the use of biomarkers has dramatically improved the diagnosis of clinically significant cancer. Despite the two modalities working together for diagnosis biomarker research often fails to correlate findings with imaging., Methods and Results: We looked at 21 prostate cancer biomarkers correlating our results with mpMRI data to investigate the hypothesis that biomarkers along with mpMRI data make a powerful tool to detect clinically significant prostate cancer. Biomarkers were selected based on the existing literature. Using a tissue microarray comprised of samples from the PICTURE study, with biopsies at 5 mm intervals and mpMRI data we analysed which biomarkers could differentiate benign and malignant tissue. Biomarker data were also correlated with pathological grading, mpMRI, serum PSA, age and family history. AGR2, CD10 and EGR protein expression was significantly different in both matched malignant and benign tissues. AMACR, ANPEP, GDF15, MSMB, PSMA, PTEN, TBL1XR1, TP63, VPS13A and VPS28 showed significantly different expression between Gleason grades in malignant tissue. The majority of the biomarkers tested did not correlate with mpMRI data. However, CD10, KHDRBS3, PCLAF, PSMA, SIK2 and GDF15 were differentially expressed with prostate cancer progression. AMACR and PTEN were identified in both pathological and image data evaluation., Conclusions: There is a high demand to develop biomarkers that would help the diagnosis and prognosis of prostate cancer. Tissue biomarkers are of particular interest since immunohistochemistry remains a cheap, reliable method that is widely available in pathology departments. These results demonstrate that testing biomarkers in a cohort consistent with the current diagnostic pathway is crucial to identifying biomarker with potential clinical utility., Competing Interests: Competing interests: The authors declare no competing interests. Ethics: Ethics committee approval for the PICTURE study was granted by London City Road and Hampstead National Research Ethics Committee (11/LO/1657) and all procedures were in accordance with the Helsinki Declaration. Informed consent was obtained from all individual participants included in the study., (© 2024. The Author(s).)

Purpose: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer., Methods: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning. We do this quantitatively on simulated data by comparing the Pearson's correlation coefficient, mean-squared error, bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed-rank test., Results: In simulations, ssVERDICT outperforms the baseline methods (nonlinear least squares and supervised deep learning) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and mean-squared error. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods., Conclusion: ssVERDICT significantly outperforms state-of-the-art methods for VERDICT model fitting and shows, for the first time, fitting of a detailed multicompartment biophysical diffusion MRI model with machine learning without the requirement of explicit training labels., (© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Nighttime oxidation of monoterpenes (MT) via the nitrate radical (NO 3 ) and ozone (O 3 ) contributes to the formation of secondary organic aerosol (SOA). This study uses observations in Atlanta, Georgia from 2011-2022 to quantify trends in nighttime production of NO 3 (PNO 3 ) and O 3 concentrations and compare to model outputs from the EPA's Air QUAlity TimE Series Project (EQUATES). We present urban-suburban gradients in nighttime NO 3 and O 3 concentrations and quantify their fractional importance (F) for MT oxidation. Both observations and EQUATES show a decline in PNO 3 , with modeled PNO 3 declining faster than observations. Despite decreasing PNO 3 , we find that NO 3 continues to dominate nocturnal boundary layer (NBL) MT oxidation (F NO3 = 60%) in 2017, 2021, and 2022, which is consistent with EQUATES (F NO3 = 80%) from 2013-2019. This contrasts an anticipated decline in F NO3 based on prior observations in the nighttime residual layer, where O 3 is the dominant oxidant. Using two case studies of heatwaves in summer 2022, we show that extreme heat events can increase NO 3 concentrations and F NO3 , leading to short MT lifetimes (<1 h) and high gas-phase organic nitrate production. Regardless of the presence of heatwaves, our findings suggest sustained organic nitrate aerosol formation in the urban SE US under declining NO x emissions, and highlight the need for improved representation of extreme heat events in chemistry-transport models and additional observations along urban to rural gradients.

Although postpartum dyads frequently present to the emergency department, treatment of the lactating parent and breastfeeding child is often driven by medical misconceptions. Incorrect advice about continuation or cessation of breastfeeding for medical reasons can lead to maternal and infant harm. In lactation, demand begets supply; missing a feed can be detrimental to short- and long-term breastfeeding outcomes. The purpose of this Clinical Nurses Forum article is to argue the importance of appropriate care of the breastfeeding dyad in the emergency department setting and to interpret current evidence-based information on lactation for the emergency staff nurse. High-quality care for the breastfeeding dyad requires knowledge of lactation physiology, contraindications for breastfeeding, and safe medications and diagnostic procedures. The well-informed emergency nurse must advocate for evidence-based care of the breastfeeding dyad within the emergency department., (Copyright © 2024 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.)

Purpose: This study aimed to assess the image quality of apparent diffusion coefficient (ADC) maps derived from conventional diffusion-weighted MRI and fractional intracellular volume maps (FIC) from VERDICT MRI (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) in patients from the INNOVATE trial. The inter-reader agreement was also assessed., Methods: Two readers analysed both ADC and FIC maps from 57 patients enrolled in the INNOVATE prospective trial. Image quality was assessed using the Prostate Imaging Quality (PI-QUAL) score and a subjective image quality Likert score (Likert-IQ). The image quality of FIC and ADC were compared using a Wilcoxon Signed Ranks test. The inter-reader agreement was assessed with Cohen's kappa., Results: There was no statistically significant difference between the PI-QUAL score for FIC datasets compared to ADC datasets for either reader (p = 0.240 and p = 0.614). Using the Likert-IQ score, FIC image quality was higher compared to ADC (p = 0.021) as assessed by reader-1 but not for reader-2 (p = 0.663). The inter-reader agreement was 'fair' for PI-QUAL scoring of datasets with FIC maps at 0.27 (95% confidence interval; 0.08-0.46) and ADC datasets at 0.39 (95% confidence interval 0.22-0.57). For Likert scoring, the inter-reader agreement was also 'fair' for FIC maps at 0.38 (95% confidence interval; 0.10-0.65) and substantial for ADC maps at 0.62 (95% confidence interval; 0.39-0.86)., Conclusion: Image quality was comparable for FIC and ADC. The inter-reader agreement was similar when using PIQUAL for both FIC and ADC datasets but higher for ADC maps compared to FIC maps using the image quality Likert score., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2023. Published by Elsevier B.V. All rights reserved.)

Aberrant glycosylation is a universal feature of cancer cells, and cancer-associated glycans have been detected in virtually every cancer type. A common change in tumour cell glycosylation is an increase in α2,6 sialylation of N-glycans, a modification driven by the sialyltransferase ST6GAL1. ST6GAL1 is overexpressed in numerous cancer types, and sialylated glycans are fundamental for tumour growth, metastasis, immune evasion, and drug resistance, but the role of ST6GAL1 in prostate cancer is poorly understood. Here, we analyse matched cancer and normal tissue samples from 200 patients and verify that ST6GAL1 is upregulated in prostate cancer tissue. Using MALDI imaging mass spectrometry (MALDI-IMS), we identify larger branched α2,6 sialylated N-glycans that show specificity to prostate tumour tissue. We also monitored ST6GAL1 in plasma samples from >400 patients and reveal ST6GAL1 levels are significantly increased in the blood of men with prostate cancer. Using both in vitro and in vivo studies, we demonstrate that ST6GAL1 promotes prostate tumour growth and invasion. Our findings show ST6GAL1 introduces α2,6 sialylated N-glycans on prostate cancer cells and raise the possibility that prostate cancer cells can secrete active ST6GAL1 enzyme capable of remodelling glycans on the surface of other cells. Furthermore, we find α2,6 sialylated N-glycans expressed by prostate cancer cells can be targeted using the sialyltransferase inhibitor P-3F AX -Neu5Ac. Our study identifies an important role for ST6GAL1 and α2,6 sialylated N-glycans in prostate cancer progression and highlights the opportunity to inhibit abnormal sialylation for the development of new prostate cancer therapeutics. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland., (© 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.)

Objectives: To assess of the clinical performance of Proclarix ® (a novel Conformité Européenne [CE]-marked biomarker test aiding in the identification of clinically significant prostate cancer [csPCa]) alone or in combination with multiparametric magnetic resonance imaging (mpMRI) to predict csPCa (International Society of Urological Pathology Grade Group ≥2)., Patients and Methods: The study included blood samples from 721 men undergoing mpMRI followed by biopsy at University College London, London, and Vall d'Hebron University Hospital, Barcelona. Samples were tested blindly. The Proclarix-MRI model combining prostate volume, Proclarix and mpMRI results was trained using the UCL cohort (n = 159) and validated in the Vall d'Hebron cohort (n = 562). Its diagnostic performance was established in correlation to biopsy outcome and compared to available clinical parameters and risk calculators., Results: Clinical performance of the Proclarix-MRI model in the validation cohort did not significantly differ from the training cohort and resulted in a sensitivity for csPCa of 90%, 90% negative predictive value and 66% positive predictive value. The Proclarix-MRI score's specificity (68%) was significantly (P < 0.001) better than the MRI-European Randomized study of Screening for Prostate Cancer risk score (51%), Proclarix (27%) or mpMRI (28%) alone. In addition, Proclarix by itself was found to be useful in the MRI Prostate Imaging-Reporting and Data System (PI-RADS) score 3 subgroup by outperforming prostate-specific antigen density in terms of specificity (25% vs 13%, P = 0.004) at 100% sensitivity., Conclusion: When combined with mpMRI and prostate volume, Proclarix reliably predicted csPCa and ruled out men with no or indolent cancer. A large reduction of two thirds of unneeded biopsies was achieved. Proclarix can further be used with high confidence to reliably detect csPCa in men with an indeterminate PI-RADS score 3 mpMRI. Despite these encouraging results, further validation is needed., (© 2023 BJU International.)

Prostate cancer is the most common cancer in men and it is estimated that over 350,000 men worldwide die of prostate cancer every year. There remains an unmet clinical need to improve how clinically significant prostate cancer is diagnosed and develop new treatments for advanced disease. Aberrant glycosylation is a hallmark of cancer implicated in tumour growth, metastasis, and immune evasion. One of the key drivers of aberrant glycosylation is the dysregulated expression of glycosylation enzymes within the cancer cell. Here, we demonstrate using multiple independent clinical cohorts that the glycosyltransferase enzyme GALNT7 is upregulated in prostate cancer tissue. We show GALNT7 can identify men with prostate cancer, using urine and blood samples, with improved diagnostic accuracy than serum PSA alone. We also show that GALNT7 levels remain high in progression to castrate-resistant disease, and using in vitro and in vivo models, reveal that GALNT7 promotes prostate tumour growth. Mechanistically, GALNT7 can modify O-glycosylation in prostate cancer cells and correlates with cell cycle and immune signalling pathways. Our study provides a new biomarker to aid the diagnosis of clinically significant disease and cements GALNT7-mediated O-glycosylation as an important driver of prostate cancer progression., (© 2023. The Author(s).)

This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction f ic discriminated between Gleason 3 + 3 and 3 + 4 (p = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 (p = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition (p > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R 2  = 0.79-0.98; CV = 1-7%; ICC = 92-98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3., (© 2023. The Author(s).)

Background In men suspected of having prostate cancer (PCa), up to 50% of men with positive multiparametric MRI (mpMRI) findings (Prostate Imaging Reporting and Data System [PI-RADS] or Likert score of 3 or higher) have no clinically significant (Gleason score ≤3+3, benign) biopsy findings. Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumor (VERDICT) MRI analysis could improve the stratification of positive mpMRI findings. Purpose To evaluate VERDICT MRI, mpMRI-derived apparent diffusion coefficient (ADC), and prostate-specific antigen density (PSAD) as determinants of clinically significant PCa (csPCa). Materials and Methods Between April 2016 and December 2019, men suspected of having PCa were prospectively recruited from two centers and underwent VERDICT MRI and mpMRI at one center before undergoing targeted biopsy. Biopsied lesion ADC, lesion-derived fractional intracellular volume (FIC), and PSAD were compared between men with csPCa and those without csPCa, using nonparametric tests subdivided by Likert scores. Area under the receiver operating characteristic curve (AUC) was calculated to test diagnostic performance. Results Among 303 biopsy-naive men, 165 study participants (mean age, 65 years ± 7 [SD]) underwent targeted biopsy; of these, 73 had csPCa. Median lesion FIC was higher in men with csPCa (FIC, 0.53) than in those without csPCa (FIC, 0.18) for Likert 3 ( P = .002) and Likert 4 (0.60 vs 0.28, P < .001) lesions. Median lesion ADC was lower for Likert 4 lesions with csPCa (0.86 × 10 -3 mm 2 /sec) compared with lesions without csPCa (1.12 × 10 -3 mm 2 /sec, P = .03), but there was no evidence of a difference for Likert 3 lesions (0.97 × 10 -3 mm 2 /sec vs 1.20 × 10 -3 mm 2 /sec, P = .09). PSAD also showed no difference for Likert 3 (0.17 ng/mL 2 vs 0.12 ng/mL 2 , P = .07) or Likert 4 (0.14 ng/mL 2 vs 0.12 ng/mL 2 , P = .47) lesions. The diagnostic performance of FIC (AUC, 0.96; 95% CI: 0.93, 1.00) was higher ( P = .02) than that of ADC (AUC, 0.85; 95% CI: 0.79, 0.91) and PSAD (AUC, 0.74; 95% CI: 0.66, 0.82) for the presence of csPCa in biopsied lesions. Conclusion Lesion fractional intracellular volume enabled better classification of clinically significant prostate cancer than did apparent diffusion coefficient and prostate-specific antigen density. Clinical trial registration no. NCT02689271 © RSNA, 2022 Online supplemental material is available for this article.

False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer—true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)—false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular−extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.

Risk assessment represents one of the requirements for all activities involving human tissues within the premises. Although a variety of procedures are available to prepare risk assessments in general, there are no published examples of risks associated with the use of human samples in research. To cover this gap and to give an overview of the evaluation performed in our institution, we summarized the potential risks for the use of human samples in research identified in the projects under the remit of the UCL/UCLH Biobank. The procedures of acquisition, transportation, storage, use, and disposal of human samples, and security of the premises were analyzed. From our experience, there are governance-related risks associated with the process of consenting the patients, with the donor confidentiality, with mislabeling of samples and with the ethical approval associated with the project, and they generally do not compromise the integrity of the samples. On the other hand, samples' integrity is more at risk during collection, storage, transport, and use of the sample. Adequate training and having appropriate standard procedures in place and available for all staff seem to be the most effective control measures to prevent any issue. In addition, appropriate equipment maintenance, contingency plans, and strict regulation and monitoring of the facility security should always be in place. In summary, an appropriate evaluation of the risks associated with the use of human samples in research is one of the requirements for the use of human samples in research and it is fundamental for the protection of staff, students, the institution itself, and the patients. Supporting biobanking, implementing a culture of biosafety in the life sciences, and raising awareness in the scientific and regulatory communities are key ways to anticipate future problems associated with biological and governance risks.

Recent developments in sequencing the cancer genome have provided the first in-depth mapping of structural variants (SV) across 38 tumour types. Sixteen signatures of structural variants have been proposed which broadly characterise the variation seen across cancer types. One signature shows increased duplications and deletions at fragile sites, with little association with the typical DNA repair defects. We discuss how, for many of these fragile sites, the clinical impacts are yet to be explored. One example is NAALADL2, one of the most frequently altered fragile sites in the cancer genome. The copy-number variations (CNVs) which occur at fragile sites, such as NAALADL2, may span many genes without typical DNA repair defects and could have a large impact on cell signalling.

The emergence of new bacterial pathogens is a continuing challenge for agriculture and food safety. Salmonella Typhimurium is a major cause of foodborne illness worldwide, with pigs a major zoonotic reservoir. Two phylogenetically distinct variants, U288 and ST34, emerged in UK pigs around the same time but present different risk to food safety. Here we show using genomic epidemiology that ST34 accounts for over half of all S. Typhimurium infections in people while U288 less than 2%. That the U288 clade evolved in the recent past by acquiring AMR genes, indels in the virulence plasmid pU288-1, and accumulation of loss-of-function polymorphisms in coding sequences. U288 replicates more slowly and is more sensitive to desiccation than ST34 isolates and exhibited distinct pathogenicity in the murine model of colitis and in pigs. U288 infection was more disseminated in the lymph nodes while ST34 were recovered in greater numbers in the intestinal contents. These data are consistent with the evolution of S. Typhimurium U288 adaptation to pigs that may determine their reduced zoonotic potential.

Objectives : To assess the clinical outcomes of mpMRI before biopsy and evaluate the space remaining for novel biomarkers. Methods: The INNOVATE study was set up to evaluate the validity of novel fluidic biomarkers in men with suspected prostate cancer who undergo pre-biopsy mpMRI. We report the characteristics of this clinical cohort, the distribution of clinical serum biomarkers, PSA and PSA density (PSAD), and compare the mpMRI Likert scoring system to the Prostate Imaging-Reporting and Data System v2.1 (PI-RADS) in men undergoing biopsy. Results : 340 men underwent mpMRI to evaluate suspected prostate cancer. 193/340 (57%) men had subsequent MRI-targeted prostate biopsy. Clinically significant prostate cancer (csigPCa), i.e., overall Gleason ≥ 3 + 4 of any length OR maximum cancer core length (MCCL) ≥4 mm of any grade including any 3 + 3, was found in 96/195 (49%) of biopsied patients. Median PSA (and PSAD) was 4.7 (0.20), 8.0 (0.17), and 9.7 (0.31) ng/mL (ng/mL/mL) in mpMRI scored Likert 3,4,5 respectively for men with csigPCa on biopsy. The space for novel biomarkers was shown to be within the group of men with mpMRI scored Likert3 (178/340) and 4 (70/350), in whom an additional of 40% (70/178) men with mpMRI-scored Likert3, and 37% (26/70) Likert4 could have been spared biopsy. PSAD is already considered clinically in this cohort to risk stratify patients for biopsy, despite this 67% (55/82) of men with mpMRI-scored Likert3, and 55% (36/65) Likert4, who underwent prostate biopsy had a PSAD below a clinical threshold of 0.15 (or 0.12 for men aged <50 years). Different thresholds of PSA and PSAD were assessed in mpMRI-scored Likert4 to predict csigPCa on biopsy, to achieve false negative levels of ≤5% the proportion of patients whom who test as above the threshold were unsuitably high at 86 and 92% of patients for PSAD and PSA respectively. When PSA was re tested in a sub cohort of men repeated PSAD showed its poor reproducibility with 43% (41/95) of patients being reclassified. After PI-RADS rescoring of the biopsied lesions, 66% (54/82) of the Likert3 lesions received a different PI-RADS score. Conclusions : The addition of simple biochemical and radiological markers (Likert and PSAD) facilitate the streamlining of the mpMRI-diagnostic pathway for suspected prostate cancer but there remains scope for improvement, in the introduction of novel biomarkers for risk assessment in Likert3 and 4 patients, future application of novel biomarkers tested in a Likert cohort would also require re-optimization around Likert3/PI-RADS2, as well as reproducibility testing.

Gleason score 7 prostate cancer with a higher proportion of pattern 4 (G4) has been linked to genomic heterogeneity and poorer patient outcome. The current assessment of G4 proportion uses estimation by a pathologist, with a higher proportion of G4 more likely to trigger additional imaging and treatment over active surveillance. This estimation method has been shown to have inter-observer variability. Fifteen patients with Prostate Grade Group (GG) 2 (Gleason 3 + 4) and fifteen patients with GG3 (Gleason 4 + 3) disease were selected from the PROMIS study with 192 haematoxylin and eosin-stained slides scanned. Two experienced uropathologists assessed the maximum cancer core length (MCCL) and G4 proportion using the current standard method (visual estimation) followed by detailed digital manual annotation of each G4 area and measurement of MCCL (planimetric estimation) using freely available software by the same two experts. We aimed to compare visual estimation of G4 and MCCL to a pathologist-driven digital measurement. We show that the visual and digital MCCL measurement differs up to 2 mm in 76.6% (23/30) with a high degree of agreement between the two measurements; Visual gave a median MCCL of 10 ± 2.70 mm (IQR 4, range 5-15 mm) compared to digital of 9.88 ± 3.09 mm (IQR 3.82, range 5.01-15.7 mm) (p = 0.64) The visual method for assessing G4 proportion over-estimates in all patients, compared to digital measurements [median 11.2% (IQR 38.75, range 4.7-17.9%) vs 30.4% (IQR 18.37, range 12.9-50.76%)]. The discordance was higher as the amount of G4 increased (Bias 18.71, CI 33.87-48.75, r 0.7, p < 0.0001). Further work on assessing actual G4 burden calibrated to clinical outcomes might lead to the use of differing G4 thresholds of significance if the visual estimation is used or by incorporating semi-automated methods for G4 burden measurement.