Nitric oxide inhibits ten-eleven translocation DNA demethylases to regulate 5mC and 5hmC across the genome.

DNA methylation at cytosine bases of eukaryotic DNA (5-methylcytosine, 5mC) is a heritable epigenetic mark that can regulate gene expression in health and disease. Enzymes that metabolize 5mC have been well-characterized, yet the discovery of endogenously produced signaling molecules that regulate DNA methyl-modifying machinery have not been described. Herein, we report that the free radical signaling molecule nitric oxide (NO) can directly inhibit the Fe(II)/2-OG-dependent DNA demethylases ten-eleven translocation (TET) and human AlkB homolog 2 (ALKBH2). Physiologic NO concentrations reversibly inhibited TET and ALKBH2 demethylase activity by binding to the mononuclear non-heme iron atom which formed a dinitrosyliron complex (DNIC) preventing cosubstrates (2-OG and O 2 ) from binding. In cancer cells treated with exogenous NO, or cells endogenously synthesizing NO, there was a global increase in 5mC and 5-hydroxymethylcytosine (5hmC) in DNA, the substrates for TET, that could not be attributed to increased DNA methyltransferase activity. 5mC was also elevated in NO-producing cell-line-derived mouse xenograft and patient-derived xenograft tumors. Genome-wide DNA methylome analysis of cells chronically treated with NO (10 days) demonstrated enrichment of 5mC and 5hmC at gene-regulatory loci which correlated to changes in the expression of NO-regulated tumor-associated genes. Regulation of DNA methylation is distinctly different from canonical NO signaling and represents a novel epigenetic role for NO.

Peptidoglycan-Targeted [18F]3,3,3-Trifluoro-d-alanine Tracer for Imaging Bacterial Infection.

Imaging is increasingly used to detect and monitor bacterial infection. Both anatomic (X-rays, computed tomography, ultrasound, and MRI) and nuclear medicine ([111In]-WBC SPECT, [18F]FDG PET) techniques are used in clinical practice but lack specificity for the causative microorganisms themselves. To meet this challenge, many groups have developed imaging methods that target pathogen-specific metabolism, including PET tracers integrated into the bacterial cell wall. We have previously reported the d-amino acid derived PET radiotracers d-methyl-[11C]-methionine, d-[3-11C]-alanine, and d-[3-11C]-alanine-d-alanine, which showed robust bacterial accumulation in vitro and in vivo. Given the clinical importance of radionuclide half-life, in the current study, we developed [18F]3,3,3-trifluoro-d-alanine (d-[18F]-CF3-ala), a fluorine-18 labeled tracer. We tested the hypothesis that d-[18F]-CF3-ala would be incorporated into bacterial peptidoglycan given its structural similarity to d-alanine itself. NMR analysis showed that the fluorine-19 parent amino acid d-[19F]-CF3-ala was stable in human and mouse serum. d-[19F]-CF3-ala was also a poor substrate for d-amino acid oxidase, the enzyme largely responsible for mammalian d-amino acid metabolism and a likely contributor to background signals using d-amino acid derived PET tracers. In addition, d-[19F]-CF3-ala showed robust incorporation into Escherichia coli peptidoglycan, as detected by HPLC/mass spectrometry. Based on these promising results, we developed a radiosynthesis of d-[18F]-CF3-ala via displacement of a bromo-precursor with [18F]fluoride followed by chiral stationary phase HPLC. Unexpectedly, the accumulation of d-[18F]-CF3-ala by bacteria in vitro was highest for Gram-negative pathogens in particular E. coli. In a murine model of acute bacterial infection, d-[18F]-CF3-ala could distinguish live from heat-killed E. coli, with low background signals. These results indicate the viability of [18F]-modified d-amino acids for infection imaging and indicate that improved specificity for bacterial metabolism can improve tracer performance.

Chemiluminescence and electrochemiluminescence of water-soluble iridium(III) complexes containing a tetraethylene-glycol functionalised triazolylpyridine ligand.

BACKGROUND: Iridium(III) complexes, exhibiting high luminescence quantum yields and a wide range of emission colours, are promising alternatives to tris(2,2'-bipyridine)ruthenium(II) for chemiluminescence (CL) and electrochemiluminescence (ECL) detection. This emerging class of reagent, however, is limited by the poor solubility of many iridium(III) complexes in aqueous solution, and lack of understanding of their remarkably variable selectivities towards different analytes. RESULTS: Seven [Ir(C^N)2(pt-TEG)]+ complexes, exhibiting a wide range of reduction potentials and emission energies, were examined with six model analytes. For CL, cerium(IV) was used as the oxidant. The alkylamine analytes generally produced greater CL and ECL with the more readily oxidised Ir(III) complexes (C^N = piq, bt, ppy), predominantly through the 'direct' pathway requiring oxidation of both metal complex and analyte. Aniline derivatives that did not also contain secondary or tertiary alkylamines elicited CL from the less readily oxidised complexes (C^N = df-ppy-CF3, df-ppy) via energy transfer. The most difficult to oxidise complexes (C^N = df(CF3)-ppy-Me, df(CN)-ppy) gave poor responses due to the limited potential window of the solvent and inefficiency of energy transfer to their high energy excited states. Greater CL and/or ECL intensities were generally obtained for each analyte with at least one Ir(III) complex than with [Ru(bpy)3]2+; superior limits of detection for two analytes were demonstrated. SIGNIFICANCE: This exploration of CL/ECL in which the properties of luminophore, analyte and oxidant are all varied provides a new understanding of the influence of the metal-complex potentials and excited state energy on the light-producing and quenching pathways, and consequently, their distinct selectivity towards different analytes. These findings will guide the development of water-soluble Ir(III) complexes as CL and ECL reagents.

Bioorthogonal Radiolabeling of Azide-Modified Bacteria Using [18F]FB-sulfo-DBCO.

Purpose: This study was motivated by the need for better positron emission tomography (PET)-compatible tools to image bacterial infection. Our previous efforts have targeted bacteria-specific metabolism via assimilation of carbon-11 labeled d-amino acids into the bacterial cell wall. Since the chemical determinants of this incorporation are not fully understood, we sought a high-throughput method to label d-amino acid derived structures with fluorine-18. Our strategy employed a chemical biology approach, whereby an azide (-N3) bearing d-amino acid is incorporated into peptidoglycan muropeptides, with subsequent "click" cycloaddition with an 18F-labeled strained cyclooctyne partner. Procedures: A water-soluble, 18F-labeled and dibenzocyclooctyne (DBCO)-derived radiotracer ([18F]FB-sulfo-DBCO) was synthesized. This tracer was incubated with pathogenic bacteria treated with azide-bearing d-amino acids, and incorporated 18F was determined via gamma counting. In vitro uptake in bacteria previously treated with azide-modified d-amino acids was compared to that in cultures treated with amino acid controls. The biodistribution of [18F]FB-sulfo-DBCO was studied in a cohort of healthy mice with implications for future in vivo imaging. Results: The new strain-promoted azide-alkyne cycloaddition (SPAAC) radiotracer [18F]FB-sulfo-DBCO was synthesized with high radiochemical yield and purity via N-succinimidyl 4-[18F]fluorobenzoate ([18F]SFB). Accumulation of [18F]FB-sulfo-DBCO was significantly higher in several bacteria treated with azide-modified d-amino acids than in controls; for example, we observed 7 times greater [18F]FB-sulfo-DBCO ligation in Staphylococcus aureus cultures incubated with 3-azido-d-alanine versus those incubated with d-alanine. Conclusions: The SPAAC radiotracer [18F]FB-sulfo-DBCO was validated in vitro via metabolic labeling of azide-bearing peptidoglycan muropeptides. d-Amino acid-derived PET radiotracers may be more efficiently screened via [18F]FB-sulfo-DBCO modification.

Structural analysis of a U-superfamily conotoxin containing a mini-granulin fold: Insights into key features that distinguish between the ICK and granulin folds.

We are entering an exciting time in structural biology where artificial intelligence can be used to predict protein structures with greater accuracy than ever before. Extending this level of accuracy to the predictions of disulfide-rich peptide structures is likely to be more challenging, at least in the short term, given the tight packing of cysteine residues and the numerous ways that the disulfide bonds can potentially be linked. It has been previously shown in many cases that several disulfide bond connectivities can be accommodated by a single set of NMR-derived structural data without significant violations. Disulfide-rich peptides are prevalent throughout nature, and arguably the most well-known are those present in venoms from organisms such as cone snails. Here, we have determined the first three-dimensional structure and disulfide connectivity of a U-superfamily cone snail venom peptide, TxVIIB. TxVIIB has a VI/VII cysteine framework that is generally associated with an inhibitor cystine knot (ICK) fold; however, AlphaFold predicted that the peptide adopts a mini-granulin fold with a granulin disulfide connectivity. Our experimental studies using NMR spectroscopy and orthogonal protection of cysteine residues indicate that TxVIIB indeed adopts a mini-granulin fold but with the ICK disulfide connectivity. Our findings provide structural insight into the underlying features that govern formation of the mini-granulin fold rather than the ICK fold and will provide fundamental information for prediction algorithms, as the subtle complexity of disulfide isomers may be not adequately addressed by the current prediction algorithms.

Utility of peripheral protein biomarkers for the prediction of incident interstitial features: a multicentre retrospective cohort study.

INTRODUCTION/RATIONALE: Protein biomarkers may help enable the prediction of incident interstitial features on chest CT. METHODS: We identified which protein biomarkers in a cohort of smokers (COPDGene) differed between those with and without objectively measured interstitial features at baseline using a univariate screen (t-test false discovery rate, FDR p<0.001), and which of those were associated with interstitial features longitudinally (multivariable mixed effects model FDR p<0.05). To predict incident interstitial features, we trained four random forest classifiers in a two-thirds random subset of COPDGene: (1) imaging and demographic information, (2) univariate screen biomarkers, (3) multivariable confirmation biomarkers and (4) multivariable confirmation biomarkers available in a separate testing cohort (Pittsburgh Lung Screening Study (PLuSS)). We evaluated classifier performance in the remaining one-third of COPDGene, and, for the final model, also in PLuSS. RESULTS: In COPDGene, 1305 biomarkers were available and 20 differed between those with and without interstitial features at baseline. Of these, 11 were associated with feature progression over a mean of 5.5 years of follow-up, and of these 4 were available in PLuSS, (angiopoietin-2, matrix metalloproteinase 7, macrophage inflammatory protein 1 alpha) over a mean of 8.8 years of follow-up. The area under the curve (AUC) of classifiers using demographics and imaging features in COPDGene and PLuSS were 0.69 and 0.59, respectively. In COPDGene, the AUC of the univariate screen classifier was 0.78 and of the multivariable confirmation classifier was 0.76. The AUC of the final classifier in COPDGene was 0.75 and in PLuSS was 0.76. The outcome for all of the models was the development of incident interstitial features. CONCLUSIONS: Multiple novel and previously identified proteomic biomarkers are associated with interstitial features on chest CT and may enable the prediction of incident interstitial diseases such as idiopathic pulmonary fibrosis.

Suprachoroidal gene transfer with nonviral nanoparticles in large animal eyes.

Suprachoroidal nonviral gene therapy with biodegradable poly(ß-amino ester) nanoparticles (NPs) provides widespread expression in photoreceptors and retinal pigmented epithelial (RPE) cells and therapeutic benefits in rodents. Here, we show in a human-sized minipig eye that suprachoroidal injection of 50 µl of NPs containing 19.2 µg of GFP expression plasmid caused GFP expression in photoreceptors and RPE throughout the entire eye with no toxicity. Two weeks after injection of 50, 100, or 200 µl, there was considerable within-eye and between-eye variability in expression that was reduced 3 months after injection of 200 µl and markedly reduced after three suprachoroidal injections at different locations around the eye. Reduction of bacterial CpG sequences in the expression plasmid resulted in a trend toward higher expression. These data indicate that nonviral suprachoroidal gene therapy with optimized polymer, expression plasmid, and injection approach has potential for treating photoreceptors throughout the entire retina of a human-sized eye.

Unlocking Biradical Character in Diborepins.

Systems that possess open- and closed-shell behavior attract significant attention from researchers due to their inherent redox and charge transport properties. Herein, we report the synthesis of the first diborepin biradicals. They display tunable biradical character based on the steric and electronic profile of the stabilizing ligand and the resulting geometric deviation of the diborepin core from planarity. While there are numerous all-carbon-based biradical systems, boron-based biradical compounds are comparatively rare, particularly ones in which the radical sites are disjointed. Calculations using density functional theory (DFT) and multireference methods demonstrate that the fused diborepin scaffold exhibits high biradical character, up to 95%. Use of a nonsterically demanding diaminocarbene promotes the planarization of the pentacyclic framework, resulting in the synthetic realization of a diborepin containing a dibora-quinoidal core, which possesses a closed-shell ground state and thermally accessible triplet state. The biradicals were structurally authenticated and characterized by both solution and solid-state electron paramagnetic resonance (EPR) spectroscopy. Half-field transitions were observed at low temperatures (about 170 K), confirming the presence of the triplet state. Initial reactivity studies of the biradicals led to the isolation and structural characterization of bis(borepin hydride) and bis(borepin dianion).

Development of CD46 targeted alpha theranostics in prostate cancer using 134Ce/225Ac-Macropa-PEG4-YS5.

Rationale: 225Ac, a long-lived α-emitter with a half-life of 9.92 days, has garnered significant attention as a therapeutic radionuclide when coupled with monoclonal antibodies and other targeting vectors. Nevertheless, its clinical utility has been hampered by potential off-target toxicity, a lack of optimized chelators for 225Ac, and limitations in radiolabeling methods. In a prior study evaluating the effectiveness of CD46-targeted radioimmunotherapy, we found great therapeutic efficacy but also significant toxicity at higher doses. To address these challenges, we have developed a radioimmunoconjugate called 225Ac-Macropa-PEG4-YS5, incorporating a stable PEGylated linker to maximize tumoral uptake and increase tumor-to-background ratios. Our research demonstrates that this conjugate exhibits greater anti-tumor efficacy while minimizing toxicity in prostate cancer 22Rv1 tumors. Methods: We synthesized Macropa.NCS and Macropa-PEG4/8-TFP esters and prepared Macropa-PEG0/4/8-YS5 (with nearly ~1:1 ratio of macropa chelator to antibody YS5) as well as DOTA-YS5 conjugates. These conjugates were then radiolabeled with 225Ac in a 2 M NH4OAc solution at 30 °C, followed by purification using YM30K centrifugal purification. Subsequently, we conducted biodistribution studies and evaluated antitumor activity in nude mice (nu/nu) bearing prostate 22Rv1 xenografts in both single-dose and fractionated dosing studies. Micro-PET imaging studies were performed with 134Ce-Macropa-PEG0/4/8-YS5 in 22Rv1 xenografts for 7 days. Toxicity studies were also performed in healthy athymic nude mice. Results: As expected, we achieved a >95% radiochemical yield when labeling Macropa-PEG0/4/8-YS5 with 225Ac, regardless of the chelator ratios (ranging from 1 to 7.76 per YS5 antibody). The isolated yield exceeded 60% after purification. Such high conversions were not observed with the DOTA-YS5 conjugate, even at a higher ratio of 8.5 chelators per antibody (RCY of 83%, an isolated yield of 40%). Biodistribution analysis at 7 days post-injection revealed higher tumor uptake for the 225Ac-Macropa-PEG4-YS5 (82.82 ± 38.27 %ID/g) compared to other conjugates, namely 225Ac-Macropa-PEG0/8-YS5 (38.2 ± 14.4/36.39 ± 12.4 %ID/g) and 225Ac-DOTA-YS5 (29.35 ± 7.76 %ID/g). The PET Imaging of 134Ce-Macropa-PEG0/4/8-YS5 conjugates resulted in a high tumor uptake, and tumor to background ratios. In terms of antitumor activity, 225Ac-Macropa-PEG4-YS5 exhibited a substantial response, leading to prolonged survival compared to 225Ac-DOTA-YS5, particularly when administered at 4.625 kBq doses, in single or fractionated dose regimens. Chronic toxicity studies observed mild to moderate renal toxicity at 4.625 and 9.25 kBq doses. Conclusions: Our study highlights the promise of 225Ac-Macropa-PEG4-YS5 for targeted alpha particle therapy. The 225Ac-Macropa-PEG4-YS5 conjugate demonstrates improved biodistribution, reduced off-target binding, and enhanced therapeutic efficacy, particularly at lower doses, compared to 225Ac-DOTA-YS5. Incorporating theranostic 134Ce PET imaging further enhances the versatility of macropa-PEG conjugates, offering a more effective and safer approach to cancer treatment. Overall, this methodology has a high potential for broader clinical applications.

Extending the reach of expert amyloidosis care: A feasibility study exploring the staged implementation of a UK amyloidosis network.

There has been an exponential increase in the diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CA). In response, the Midlands Amyloidosis Service was launched with the aim of providing patients with a timely diagnosis, remote expertise from the National Amyloidosis Centre and access to emerging transthyretin (TTR)-directed therapies. This was a descriptive study of a pilot hub-and-spoke model of delivering specialist amyloidosis care. Patients with suspected amyloidosis were referred from the wider Midlands region, and seen in a consultant-led multidisciplinary clinic. The diagnosis of ATTR-CA was established according to either the validated non-biopsy criteria or histological confirmation of ATTR deposits with imaging evidence of amyloid. Study endpoints were the volume of service provision and the time to diagnosis from the receipt of referral. Patients (n=173, age 75±2 years; male 72 %) were referred between 2019 and 2021. Eighty patients (46 %) were found to have cardiac amyloidosis, of whom 68 (85 %) had ATTR-CA. The median time from referral to diagnosis was 43 days. By removing the need for patients to travel to London, an average of 187 patient-miles was saved. Fifteen (9 %) patients with wild-type ATTR-CA received tafamidis under the Early Access to Medicine scheme; 10 (6 %) were enrolled into phase 3 clinical trials of RNA interference or antisense oligonucleotide therapies. Our results suggest that implementing a UK amyloidosis network appears feasible and would enhance equity of access to specialised amyloidosis healthcare for the increasing numbers of older patients found to have ATTR-CA.

Unveiling Three Interconvertible Redox States of Boraphenalene.

Neutral 1-boraphenalene displays the isoelectronic structure of the phenalenyl carbocation and is expected to behave as an attractive organoboron multi-redox system. However, the isolation of new redox states have remained elusive even though the preparation of neutral boron(III)-containing phenalene compounds have been extensively studied. Herein, we have adopted an N-heterocyclic carbene ligand stabilization approach to achieve the first isolation of the stable and ambipolar 1-boraphenalenyl radical 1•. The 1-boraphenalenyl cation 1+ and anion 1- have also been electrochemically observed and chemically isolated, representing new redox forms of boraphenalene for the study of non-Kekulé polynuclear benzenoid molecules. Experimental and theoretical investigations suggest that the interconvertible three-redox-state species undergo reversible electronic structure modifications, which primarily take place on the polycyclic framework of the molecules, exhibiting atypical behavior compared to known donor-stabilized organoboron compounds. Initial reactivity studies, aromaticity evaluations, and photophysical studies show redox-state-dependent trends. While 1+ is luminescent in both the solution and solid states, 1• exhibits boron-centered reactivity and 1- undergoes substitution chemistry on the boraphenalenyl skeleton and serves as a single-electron transfer reductant.

Diagnostic Delay in HPV-Related Oropharyngeal Squamous Cell Carcinoma.

Introduction Human papillomavirus-related (HPV + ) oropharyngeal squamous cell carcinoma (OPSCC) is increasing in incidence and presents diagnostic challenges given its unique clinical presentation. Objective The purpose of the present study is to characterize the impact of the unique clinical presentation of HPV-related OPSCC on delays in diagnosis. Methods Retrospective review of presenting symptoms and clinical characteristics of 284 patients with OPSCC treated from 2002-2014. Delay in diagnosis was defined as the presence of any of the following: multiple non-diagnostic fine needle aspirate (FNA) biopsies; two or more courses of antibiotic therapy; surgery with incorrect preoperative diagnosis; evaluation by an otolaryngologist without further workup; or surgery without definitive postoperative diagnosis. Results p16+ tumors demonstrated a distinct clinical presentation that more commonly involved a neck mass (85.1% versus 57.3% of p16-; p < 0.001) and less frequently included odynophagia (24.6% versus 51.7% of p16-; p < 0.001). Patients who experienced diagnostic delay were more likely to have p16+ tumors (77.7% delayed versus 62.8% not delayed; p = 0.006). p16+ primary tumors were more likely to be undetectable by physical examination of the head and neck including flexible laryngoscopy (19.0% versus 6.7% of p16-; p = 0.007) and more frequently associated with nondiagnostic FNA biopsies of a cervical nodal mass (11.8% versus 3.4% of p16-, p = 0.03). Conclusions Compared with non-HPV related OPSCC, the unique clinical presentation and characteristics of HPV+ OPSCC are associated with an increased incidence of diagnostic delay. Targeted education of appropriate care providers may improve time to diagnosis and treatment.

Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images.

Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We developed a fully-automated deep learning method for FC segmentation. This study included 32,531 images across 227 pullbacks from two registries (TRANSFORM-OCT and UHCMC). Images were semi-automatically labeled using our OCTOPUS with expert editing using established guidelines. We employed preprocessing including guidewire shadow detection, lumen segmentation, pixel-shifting, and Gaussian filtering on raw IVOCT (r,θ) images. Data were augmented in a natural way by changing θ in spiral acquisitions and by changing intensity and noise values. We used a modified SegResNet and comparison networks to segment FCs. We employed transfer learning from our existing much larger, fully-labeled calcification IVOCT dataset to reduce deep-learning training. Postprocessing with a morphological operation enhanced segmentation performance. Overall, our method consistently delivered better FC segmentation results (Dice: 0.837 ± 0.012) than other deep-learning methods. Transfer learning reduced training time by 84% and reduced the need for more training samples. Our method showed a high level of generalizability, evidenced by highly-consistent segmentations across five-fold cross-validation (sensitivity: 85.0 ± 0.3%, Dice: 0.846 ± 0.011) and the held-out test (sensitivity: 84.9%, Dice: 0.816) sets. In addition, we found excellent agreement of FC thickness with ground truth (2.95 ± 20.73 µm), giving clinically insignificant bias. There was excellent reproducibility in pre- and post-stenting pullbacks (average FC angle: 200.9 ± 128.0°/202.0 ± 121.1°). Our fully automated, deep-learning FC segmentation method demonstrated excellent performance, generalizability, and reproducibility on multi-center datasets. It will be useful for multiple research purposes and potentially for planning stent deployments that avoid placing a stent edge over an FC.

AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score.

Background: Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE). Objectives: Create novel, hand-crafted EAT features, "fat-omics", to capture the pathophysiology of EAT and improve MACE prediction. Methods: We segmented EAT using a previously-validated deep learning method with optional manual correction. We extracted 148 radiomic features (morphological, spatial, and intensity) and used Cox elastic-net for feature reduction and prediction of MACE. Results: Traditional fat features gave marginal prediction (EAT-volume/EAT-mean-HU/BMI gave C-index 0.53/0.55/0.57, respectively). Significant improvement was obtained with 15 fat-omics features (C-index=0.69, test set). High-risk features included volume-of-voxels-having-elevated-HU-[-50, -30-HU] and HU-negative-skewness, both of which assess high HU, which as been implicated in fat inflammation. Other high-risk features include kurtosis-of-EAT-thickness, reflecting the heterogeneity of thicknesses, and EAT-volume-in-the-top-25%-of-the-heart, emphasizing adipose near the proximal coronary arteries. Kaplan-Meyer plots of Cox-identified, high- and low-risk patients were well separated with the median of the fat-omics risk, while high-risk group having HR 2.4 times that of the low-risk group (P<0.001). Conclusion: Preliminary findings indicate an opportunity to use more finely tuned, explainable assessments on EAT for improved cardiovascular risk prediction.

Point-of-care HCV RNA testing improves hepatitis C testing rates and allows rapid treatment initiation among people who inject drugs attending a medically supervised injecting facility.

BACKGROUND: To achieve hepatitis C virus (HCV) elimination targets, simplified care engaging people who inject drugs is required. We evaluated whether fingerstick HCV RNA point-of-care testing (PoCT) increased the proportion of clients attending a supervised injecting facility who were tested for hepatitis C. METHODS: Prospective single-arm study with recruitment between 9 November 2020 and 28 January 2021 and follow-up to 31 July 2021. Clients attending the supervised injecting facility were offered HCV RNA testing using the Xpert® HCV Viral Load Fingerstick (Cepheid, Sunnyvale, CA) PoCT. Participants with a positive HCV RNA test were prescribed direct acting antiviral (DAA) therapy. The primary endpoint was the proportion of clients who engaged in HCV RNA PoCT, compared to a historical comparator group when venepuncture-based hepatitis C testing was standard of care. RESULTS: Among 1618 clients who attended the supervised injecting facility during the study period, 228 (14%) engaged in PoCT. This was significantly higher than that observed in the historical comparator group (61/1,775, 3%; p < 0.001). Sixty-five (28%) participants were HCV RNA positive, with 40/65 (62%) receiving their result on the same day as testing. Sixty-one (94%) HCV RNA positive participants were commenced on DAA therapy; 14/61 (23%) started treatment on the same day as diagnosis. There was no difference in the proportion of HCV RNA positive participants commenced on treatment with DAA therapy when compared to the historical comparator group (61/65, 94% vs 22/26, 85%; p = 0.153). However, the median time to treatment initiation was significantly shorter in the PoCT cohort (2 days (IQR 1-20) vs 41 days (IQR 22-76), p < 0.001). Among participants who commenced treatment and had complete follow-up data available, 27/36 (75%) achieved hepatitis C cure. CONCLUSIONS: HCV RNA PoCT led to a significantly higher proportion of clients attending a supervised injecting facility engaging in hepatitis C testing, whilst also reducing the time to treatment initiation.

Reactive transport modelling of tailings hydrogeochemistry under a composite cover.

Quantitative forecasts of acid mine drainage (AMD) production are important for remediation planning. Reactive transport simulations corresponding to a detailed sampling location at a covered legacy tailings impoundment in northern Ontario, Canada, were conducted to quantitatively assess the predominant hydrogeochemical reactions. The simulations span the period from the end of tailings deposition (circa 1970) to early 2020, 12 years after remediation by a five-layer composite cover. The conceptual model of uncovered tailings weathering and subsequent geochemistry of the covered tailings system was implemented in 1D using the multi-component reactive transport code MIN3P. Transient monthly infiltration, post-cover boundary condition changes, and a dynamic temperature regime were incorporated. The shrinking core model, including parallel O2(aq) and Fe3+ oxidation reactions for the waste rock in the cover and the underlying tailings, was implemented to simulate the oxidation of As-bearing pyrite, chalcopyrite, and sphalerite. Primary carbonate and aluminosilicate host minerals promoted acid-neutralization reactions. Precipitation of secondary phases and sorption/desorption of Cu, Zn, and arsenite were incorporated into the model. The overall agreement between key simulated and field-measured post-cover aqueous geochemical parameters suggests that the conceptual model captured the primary hydrogeochemical processes in the covered tailings. A lack of reliable data on initial tailings mineralogy and pre-cover hydrogeochemistry increased simulation uncertainty. Simulated reaction rates indicate that where intact, the cover decreased sulfide oxidation rates by both O2(aq) and Fe3+ and improved pore-water quality over time. Simulation results indicate that elevated concentrations of Zn and As are likely to persist in the tailings regardless of cover performance, whereas concentrations of Cu and Al are the parameters most sensitive to cover effectiveness.

Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.

BACKGROUND: Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen. METHODS: Using four international lung cancer screening studies, we extracted 2060 radiomic features for each of 16 797 nodules (513 malignant) among 6865 participants. After filtering out low-quality radiomic features, 642 radiomic and 9 epidemiological features remained for model development. We used cross-validation and grid search to assess three machine learning (ML) models (eXtreme Gradient Boosted Trees, random forest, least absolute shrinkage and selection operator (LASSO)) for their ability to accurately predict risk of malignancy for pulmonary nodules. We report model performance based on the area under the curve (AUC) and calibration metrics in the held-out test set. RESULTS: The LASSO model yielded the best predictive performance in cross-validation and was fit in the full training set based on optimised hyperparameters. Our radiomics model had a test-set AUC of 0.93 (95% CI 0.90 to 0.96) and outperformed the established Pan-Canadian Early Detection of Lung Cancer model (AUC 0.87, 95% CI 0.85 to 0.89) for nodule assessment. Our model performed well among both solid (AUC 0.93, 95% CI 0.89 to 0.97) and subsolid nodules (AUC 0.91, 95% CI 0.85 to 0.95). CONCLUSIONS: We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.

Deep learning segmentation of endothelial cell images using an active learning paradigm with guided label corrections.

Purpose: To create Guided Correction Software for informed manual editing of automatically generated corneal endothelial cell (EC) segmentations and apply it to an active learning paradigm to analyze a diverse set of post-keratoplasty EC images. Approach: An original U-Net model trained on 130 manually labeled post-Descemet stripping automated endothelial keratoplasty (EK) images was applied to 841 post-Descemet membrane EK images generating "uncorrected" cell border segmentations. Segmentations were then manually edited using the Guided Correction Software to create corrected labels. This dataset was split into 741 training and 100 testing EC images. U-Net and DeepLabV3+ were trained on the EC images and the corresponding uncorrected and corrected labels. Model performance was evaluated in a cell-by-cell analysis. Evaluation metrics included the number of over-segmentations, under-segmentations, correctly identified new cells, and endothelial cell density (ECD). Results: Utilizing corrected segmentations for training U-Net and DeepLabV3+ improved their performance. The average number of over- and under-segmentations per image was reduced from 23 to 11 with the corrected training set. Predicted ECD values generated by networks trained on the corrected labels were not significantly different than the ground truth counterparts (p=0.02, paired t-test). These models also correctly segmented a larger percentage of newly identified cells. The proposed Guided Correction Software and semi-automated approach reduced the time to accurately segment EC images from 15 to 30 to 5 min, an ∼80% decrease compared to manual editing. Conclusions: Guided Correction Software can efficiently label new training data for improved deep learning performance and generalization between EC datasets.