Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing.

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

Reduced-form and complex ACTM modelling for air quality policy development: A model inter-comparison.

Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM2.5, primary PM2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties.

Quantifying the impact of ozone on crops in Sub-Saharan Africa demonstrates regional and local hotspots of production loss.

Tropospheric ozone can have a detrimental effect on vegetation, including reducing the quantity of crop yield. This study uses modelled ozone flux values (POD3IAM; phytotoxic ozone dose above 3 nmol m-2 s-1, parameterised for integrated assessment modelling) for 2015, together with species-specific flux-effect relationships, spatial data on production and growing season dates to quantify the impact of ozone on the production of common wheat (Triticum aestivum) and common beans (Phaseolus vulgaris) across Sub-Saharan Africa (SSA). A case study for South Africa was also done using detailed data per province. Results suggest that ozone pollution could decrease wheat yield by between 2 and 13%, with a total annual loss of 453,000 t across SSA. The impact on bean production depended on the season; however, estimated yield losses were up to 21% in some areas of SSA, with an annual loss of ~300,000 t for each of the two main growing seasons. Production losses tended to be greater in countries with the highest production, for example, Ethiopia (wheat) and Tanzania (beans). This study provides an indication of the location of areas at high risk of crop losses due to ozone. Results emphasise that efforts to reduce ozone precursors could contribute to reducing the yield gap in SSA. More stringent air pollution abatement policies are required to reduce crop losses to ozone in the future.

Life Course Air Pollution Exposure and Cognitive Decline: Modelled Historical Air Pollution Data and the Lothian Birth Cohort 1936.

BACKGROUND: Air pollution has been consistently linked with dementia and cognitive decline. However, it is unclear whether risk is accumulated through long-term exposure or whether there are sensitive/critical periods. A key barrier to clarifying this relationship is the dearth of historical air pollution data. OBJECTIVE: To demonstrate the feasibility of modelling historical air pollution data and using them in epidemiologicalmodels. METHODS: Using the EMEP4UK atmospheric chemistry transport model, we modelled historical fine particulate matter (PM2.5) concentrations for the years 1935, 1950, 1970, 1980, and 1990 and combined these with contemporary modelled data from 2001 to estimate life course exposure in 572 participants in the Lothian Birth Cohort 1936 with lifetime residential history recorded. Linear regression and latent growth models were constructed using cognitive ability (IQ) measured by the Moray House Test at the ages of 11, 70, 76, and 79 years to explore the effects of historical air pollution exposure. Covariates included sex, IQ at age 11 years, social class, and smoking. RESULTS: Higher air pollution modelled for 1935 (when participants would have been in utero) was associated with worse change in IQ from age 11-70 years (ß = -0.006, SE = 0.002, p = 0.03) but not cognitive trajectories from age 70-79 years (p > 0.05). There was no support for other critical/sensitive periods of exposure or an accumulation of risk (all p > 0.05). CONCLUSION: The life course paradigm is essential in understanding cognitive decline and this is the first study to examine life course air pollution exposure in relation to cognitive health.

Immunohistochemical Detection of Synuclein Pathology in Skin in Idiopathic Rapid Eye Movement Sleep Behavior Disorder and Parkinsonism.

BACKGROUND: Recent studies reported abnormal alpha-synuclein deposition in biopsy-accessible sites of the peripheral nervous system in Parkinson's disease (PD). This has considerable implications for clinical diagnosis. Moreover, if deposition occurs early, it may enable tissue diagnosis of prodromal PD. OBJECTIVE: The aim of this study was to develop and test an automated bright-field immunohistochemical assay of cutaneous pathological alpha-synuclein deposition in patients with idiopathic rapid eye movement sleep behavior disorder, PD, and atypical parkinsonism and in control subjects. METHODS: For assay development, postmortem skin biopsies were taken from 28 patients with autopsy-confirmed Lewy body disease and 23 control subjects. Biopsies were stained for pathological alpha-synuclein in automated stainers using a novel dual-immunohistochemical assay for serine 129-phosphorylated alpha-synuclein and pan-neuronal marker protein gene product 9.5. After validation, single 3-mm punch skin biopsies were taken from the cervical 8 paravertebral area from 79 subjects (28 idiopathic rapid eye movement sleep behavior disorder, 20 PD, 10 atypical parkinsonism, and 21 control subjects). Raters blinded to clinical diagnosis assessed the biopsies. RESULTS: The immunohistochemistry assay differentiated alpha-synuclein pathology from nonpathological-appearing alpha-synuclein using combined phosphatase and protease treatments. Among autopsy samples, 26 of 28 Lewy body samples and none of the 23 controls were positive. Among living subjects, punch biopsies were positive in 23 (82%) subjects with idiopathic rapid eye movement sleep behavior disorder, 14 (70%) subjects with PD, 2 (20%) subjects with atypical parkinsonism, and none (0%) of the control subjects. After a 3-year follow-up, eight idiopathic rapid eye movement sleep behavior disorder subjects phenoconverted to defined neurodegenerative syndromes, in accordance with baseline biopsy results. CONCLUSION: Even with a single 3-mm punch biopsy, there is considerable promise for using pathological alpha-synuclein deposition in skin to diagnose both clinical and prodromal PD. © 2020 International Parkinson and Movement Disorder Society.

Cell-free DNA alterations in the AR enhancer and locus predict resistance to AR-directed therapy in patients with metastatic prostate cancer.

PURPOSE: Cell-free DNA (cfDNA) and circulating tumor cell (CTC) based liquid biopsies have emerged as potential tools to predict responses to androgen receptor (AR)-directed therapy in metastatic prostate cancer. However, due to complex mechanisms and incomplete understanding of genomic events involved in metastatic prostate cancer resistance, current assays (e.g. CTC AR-V7) demonstrate low sensitivity and remain underutilized. The recent discovery of AR enhancer amplification in >80% of metastatic patients and its association with disease resistance presents an opportunity to improve upon current assays. We hypothesized that tracking AR/enhancer genomic alterations in plasma cfDNA would detect resistance with high sensitivity and specificity. METHODS: We developed a targeted sequencing and analysis method as part of a new assay called Enhancer and neighboring loci of Androgen Receptor Sequencing (EnhanceAR-Seq). We applied EnhanceAR-Seq to plasma collected from 40 patients with metastatic prostate cancer treated with AR-directed therapy to monitor AR/enhancer genomic alterations and correlate these events with therapy resistance, progression-free survival (PFS) and overall survival (OS). RESULTS: EnhanceAR-Seq identified genomic alterations in the AR/enhancer locus in 45% of cases, including a 40% rate of AR enhancer amplification. Patients with AR/enhancer alterations had significantly worse PFS and OS than those without (6-month PFS: 30% vs. 71%, P=0.0002; 6-month OS: 59% vs. 100%, P=0.0015). AR/enhancer alterations in plasma cfDNA detected 18 of 23 resistant cases (78%) and outperformed the CTC AR-V7 assay which was also run on a subset of patients. CONCLUSION: cfDNA-based AR locus alterations, including of the enhancer, are strongly associated with resistance to AR-directed therapy and significantly worse survival. cfDNA analysis using EnhanceAR-Seq may enable more precise risk stratification and personalized therapeutic approaches for metastatic prostate cancer.

The Efficacy of Lenvatinib Plus Everolimus in Patients with Metastatic Renal Cell Carcinoma Exhibiting Primary Resistance to Front-Line Targeted Therapy or Immunotherapy.

BACKGROUND: Patients with primary refractory metastatic renal cell carcinoma (mRCC) have a dismal prognosis and poor response to subsequent treatments. While there are several approved second-line therapies, it remains critical to choose the most effective treatment regimen. PATIENTS AND METHODS: We identified 7 patients with clear cell mRCC who had primary resistance to vascular endothelial growth factor (VEGF)-targeted tyrosine kinase inhibitors (TKIs) or immune checkpoint inhibitor (ICI) combination therapy. The patients were treated with lenvatinib (a multitargeted TKI) plus everolimus (a mammalian target of rapamycin inhibitor). Among these 7 patients, 2 had prior TKI therapy, 3 had prior ICI therapy, and 2 had prior TKI and ICI therapy. We collected the patients' clinical characteristics, molecular profiles, treatment durations, and toxicity outcomes. RESULTS: The median time to progression on prior therapies was 1.5 months. Lenvatinib plus everolimus was used either as a second-line (n = 4) or third-line (n = 3) therapy. As best responses, 3 patients had partial responses and 3 achieved stable disease. Patients were followed for ≥17 months; progression-free survival ranged from 3 to 15 months, and overall survival ranged from 4 to 17 months. CONCLUSION: These 7 cases provide real-world data for the use of lenvatinib plus everolimus in patients with mRCC with primary resistance to first-line VEGF-targeted TKIs or ICI combination therapy.

n-Ethyl Pentylone-Related Deaths in Alabama.

n-Ethyl pentylone (NEP) is a chemical substance derived from cathinone. Synthetic cathinones are an evolving group of drugs with stimulating, mind-altering effects sometimes referred to as novel or new psychoactive substances (NPS). There is scarce information in the medical literature regarding forensic cases in which NEP is detected in toxicological testing. We present four fatalities involving NEP from Alabama in 2017. Deaths were attributed to NEP toxicity in two cases (peripheral blood concentrations of 0.121 and 0.953 mg/L) and injuries caused by gunshot wounds in two cases (peripheral blood concentrations of 0.045 and 0.031 mg/L). One case involving NEP described an individual who exhibited classic CNS-stimulant induced erratic behavior before being found dead. These cases enhance the forensic literature regarding specific NPS like NEP and provide contextual reference for professionals considering the significance of NEP in toxicological interpretation.

The influence of residential and workday population mobility on exposure to air pollution in the UK.

Traditional approaches of quantifying population-level exposure to air pollution assume that concentrations of air pollutants at the residential address of the study population are representative for overall exposure. This introduces potential bias in the quantification of human health effects. Our study combines new UK Census data comprising information on workday population densities, with high spatio-temporal resolution air pollution concentration fields from the WRF-EMEP4UK atmospheric chemistry transport model, to derive more realistic estimates of population exposure to NO2, PM2.5 and O3. We explicitly allocated workday exposures for weekdays between 8:00 am and 6:00 pm. Our analyses covered all of the UK at 1 km spatial resolution. Taking workday location into account had the most pronounced impact on potential exposure to NO2, with an estimated 0.3 µg m-3 (equivalent to 2%) increase in population-weighted annual exposure to NO2 across the whole UK population. Population-weighted exposure to PM2.5 and O3 increased and decreased by 0.3%, respectively, reflecting the different atmospheric processes contributing to the spatio-temporal distributions of these pollutants. We also illustrate how our modelling approach can be utilised to quantify individual-level exposure variations due to modelled time-activity patterns for a number of virtual individuals living and working in different locations in three example cities. Changes in annual-mean estimates of NO2 exposure for these individuals were considerably higher than for the total UK population average when including their workday location. Conducting model-based evaluations as described here may contribute to improving representativeness in studies that use small, portable, automatic sensors to estimate personal exposure to air pollution.

Improving predictive asthma algorithms with modelled environment data for Scotland: an observational cohort study protocol.

INTRODUCTION: Asthma has a considerable, but potentially, avoidable burden on many populations globally. Scotland has some of the poorest health outcomes from asthma. Although ambient pollution, weather changes and sociodemographic factors have been associated with asthma attacks, it remains unclear whether modelled environment data and geospatial information can improve population-based asthma predictive algorithms. We aim to create the afferent loop of a national learning health system for asthma in Scotland. We will investigate the associations between ambient pollution, meteorological, geospatial and sociodemographic factors and asthma attacks. METHODS AND ANALYSIS: We will develop and implement a secured data governance and linkage framework to incorporate primary care health data, modelled environment data, geospatial population and sociodemographic data. Data from 75 recruited primary care practices (n=500 000 patients) in Scotland will be used. Modelled environment data on key air pollutants at a horizontal resolution of 5 km×5 km at hourly time steps will be generated using the EMEP4UK atmospheric chemistry transport modelling system for the datazones of the primary care practices' populations. Scottish population census and education databases will be incorporated into the linkage framework for analysis. We will then undertake a longitudinal retrospective observational analysis. Asthma outcomes include asthma hospitalisations and oral steroid prescriptions. Using a nested case-control study design, associations between all covariates will be measured using conditional logistic regression to account for the matched design and to identify suitable predictors and potential candidate algorithms for an asthma learning health system in Scotland.Findings from this study will contribute to the development of predictive algorithms for asthma outcomes and be used to form the basis for our learning health system prototype. ETHICS AND DISSEMINATION: The study received National Health Service Research Ethics Committee approval (16/SS/0130) and also obtained permissions via the Public Benefit and Privacy Panel for Health and Social Care in Scotland to access, collate and use the following data sets: population and housing census for Scotland; Scottish education data via the Scottish Exchange of Data and primary care data from general practice Data Custodians. Analytic code will be made available in the open source GitHub website. The results of this study will be published in international peer reviewed journals.

Quantification of Loperamide by Gas Chromatography Mass Spectrometry.

Due to reported pharmacological activity similar to classical opioids at supratherapeutic concentrations, abuse of the anti-diarrheal medication loperamide (Imodium AD™) has become a target in the opioid epidemic. While this phenomenon is not new, published quantitative analytical methods use liquid chromatography tandem mass spectrometry. Described here is an 11 min method for quantification of loperamide in postmortem whole blood by gas chromatography mass spectrometry. Validation studies performed followed SWGTOX guidelines and included: accuracy, specificity, limit of detection (LOD), regression model analysis, stability, and matrix recovery enhancement and/or suppression. The accuracy study consisted of inter-day, intra-day, reproducibility and dilution integrity experiments. Inter-day and intra-day accuracy, precision and coefficient of variation (CV) were measured; normalized results were 1.05 ± 0.09 with 8.87% CV (n = 36) and 1.03 ± 0.09 with 8.53% CV (n = 27), respectively. Reproducibility was evaluated through standard addition with an observed CV of 10.84% (n = 10). Dilution integrity (2× and 4×) resulted in 0.94 ± 0.13 with a CV of 13.9% (n = 5). No interference was observed through analyses of the internal standard (loperamide-d6), endogenous compounds (10 blank matrices) or 60 commonly encountered analytes. The LOD/decision point was 100 ng/mL (CV 8.40%). A linear calibration model was established from 100 to 1,000 ng/mL. Stability was examined; observed analyte-to-internal standard response resulted in 6.59% CV. Recovery was determined for loperamide and loperamide-d6 (31% and 36%, respectively). Neither matrix suppression nor enhancement was observed with loperamide at 750 ng/mL and loperamide-d6 at 300 ng/mL (-6.5% and -4.2%); however, some suppression was exhibited at lower concentrations (-39.8%). The designed method was determined to be sufficient for the analysis of loperamide-related death cases in Alabama (n = 8) and offers postmortem toxicology laboratories an alternative approach that is both highly selective and specific.

Tandem DART™ MS Methods for Methadone Analysis in Unprocessed Urine.

Current methods of methadone analysis in untreated urine are traditionally limited to enzyme immunoassays (EIA) while confirmation techniques require specimen processing (i.e., sample clean-up) before analyzing by gas or liquid chromatography coupled with mass spectrometry (GC-MS or LC-MS-MS). EIA and traditional confirmation techniques can be costly and, at times inefficient. As an alternative approach, we present Direct Analysis in Real Time (DART™) coupled with both time-of-flight and triple quadrupole linear ion trap (Q-TRAP™) mass spectrometers for screening and confirming methadone in untreated urine specimens. These approaches require neither expensive kits nor sample clean-up for analysis. More importantly, the total combined analysis time for both screening and confirmation methods was <5 min per sample; in contrast to the 3-5 day process required by traditional EIA, GC-MS and LC-MS-MS techniques. To examine the fundamental protocol and its applicability for routine drug screening, studies were performed that included limits of detection, precision, selectivity and specificity, sample recovery and stability and method robustness. The methods described in this report were determined to be highly specific and selective; allowing for detection of methadone at 250 ng/mL, consistent with cutoffs for current EIA techniques (300 ng/mL). The results reported here demonstrate the DART™ MS platform provides rapid and selective methadone analysis and the potential for providing savings of both time and resources compared with current analysis procedures.

Impact of molecular weight and degree of conjugation on the thermodynamics of DNA complexation and stability of polyethylenimine-graft-poly(ethylene glycol) copolymers.

Poly(ethylene glycol) (PEG) is often conjugated to polyethylenimine (PEI) to provide colloidal stability to PEI-DNA polyplexes and shield charge leading to toxicity. Here, a library of nine cationic copolymers was synthesized by grafting three molecular weights (750, 2000, 5000Da) of PEG to linear PEI at three conjugation ratios. Using isothermal titration calorimetry, we have quantified the thermodynamics of the associations between the copolymers and DNA and determined the extent to which binding is hindered as a function of PEG molecular weight and conjugation ratio. Low conjugation ratios of 750Da PEG to PEI resulted in little decrease in DNA affinity, but a significant decrease-up to two orders of magnitude-was found for the other copolymers. We identified limitations in determination of affinity using indirect assays (electrophoretic mobility shift and ethidium bromide exclusion) commonly used in the field. Dynamic light scattering of the DNA complexes at physiological ionic strength showed that PEI modifications that did not reduce DNA affinity also did not confer significant colloidal stability, a finding that was supported by calorimetric data on the aggregation process. These results quantify the DNA interaction thermodynamics of PEGylated polycations for the first time and indicate that there is an optimum PEG chain length and degree of substitution in the design of agents that have desirable properties for effective in vivo gene delivery.

Platypnea-orthodeoxia: an unusual case of hypoxemia.

A 52 year old female presented for two weeks of acute onset dyspnea on exertion. She was found to be hypoxic with a room air saturation of 88%. Baseline echocardiogram was normal with the exception of aortic root dilation. Right and left heart catheterizations were performed. The coronary arteries were normal in original and without disease. The right heart catheterization demonstrated normal pulmonary pressures and "no evidence of intra-cardiac shunt". Repeat echocardiogram was performed with agitated saline contrast and revealed a small amount of right to left shunting across the intra-atrial septum with cough while supine and significant right to left shunting while upright; these findings were consistent with the presence of a patent foramen ovale (PFO) and platypnea-orthodeoxia syndrome. The patient underwent percutaneous closure of her PFO with an Amplatzer device, and exhibited rapid resolution of her symptoms and hypoxia. She is off oxygen and has returned to work as a nurse practitioner. The case highlights the importance of clinical vigilance and consideration of this syndrome in the differential diagnosis of unexplained hypoxia. Our patient had a dramatic and positive outcome: complete alleviation of dyspnea and oxygen dependence after PFO closure.

Conversion to atorvastatin in patients intolerant or refractory to simvastatin therapy: the CAPISH study.

OBJECTIVE: To examine the safety and efficacy of switching from simvastatin to atorvastatin in patients who had either an inadequate lipid-lowering response with, or an adverse reaction to, simvastatin. PATIENTS AND METHODS: The Conversion to Atorvastatin in Patients Intolerant or Refractory to Simvastatin Therapy (CAPISH) study was designed in 2 parts: a retrospective cohort study of patients (group A), identified from a large pharmacy database, who converted from simvastatin to atorvastatin at a single academic military medical center (between April 1998 and March 2002) and a prospective cohort study of patients (group B) monitored in a lipid clinic at the same institution (between April 2002 and March 2003). Group A was identified by 2 or more simvastatin prescription fills and at least 1 atorvastatin prescription fill. Group B was identified by a physician-perceived need to switch from simvastatin to atorvastatin. Clinical, pharmaceutical, and laboratory records of both cohorts were reviewed. RESULTS: Approximately 1 in 4 simvastatin-treated patients discontinued therapy during a 4-year period. The most common reason for switching to atorvastatin was inadequate low-density lipoprotein (LDL) cholesterol control, although asymptomatic creatine kinase (CK) elevation and myalgias were also common. In most cases of myositis and in nearly all cases of rhabdomyolysis, patients were taking 80 mg of simvastatin. Achievement of National Cholesterol Education Program LDL cholesterol goals increased from 25% to 63% in group A and from 13% to 78% in group B, both P<.001. Significant reductions in CK also were seen in both groups. Adherence to atorvastatin was greater than 80% in both groups after 28.1+/-13.2 months (group A, 841 patients) and 8.1+/-3.8 months (group B, 104 patients). Among patients not taking atorvastatin at follow-up, 58% were no longer taking statins. CONCLUSION: Atorvastatin was well tolerated in patients who previously were taking simvastatin. Serum lipid panels were improved substantially and CK levels were decreased without compromise to patient safety.