Management of Traumatic Pseudoaneurysm of the Supraclinoid Internal Carotid Artery using Coil Embolization: A Case Report

Traumatic aneurysm of the internal carotid artery (ICA) occurs rarely, with an approximate incidence of 0.15% and 0.40% of total intracranial aneurysms. An interesting case of delayed presentation of pseudoaneurysm of the left ICA in a 61-year-old patient is reported here, who came to us for evaluation of blindness, proptosis, and ophthalmoparesis. This potentially life-threatening condition was successfully managed using coil embolization after complete evaluation and investigations

Identification of Lubricating Oil-Degrading Microorganisms in Oil Polluted Soils from Five Auto- mechanic Workshops in Accra, Ghana

Trichothecium, Trichoderma, Aspergillus niger, Fusarium, and Penicillium spp. from oil contaminated soil from 5 Mechanic Shops in Accra, Ghana showed zones of clearance of oil on Minimum Salt Enrichment Medium (MSEM) Agar seeded with 1000ppm Engen™ Lubricating Oil (ELO), so were counted as presumptive lubricating oil-utilizing moulds. Significant increases (P ? 0.05) in viable counts, fungal dry weights and optical densities; significant decreases (P ? 0.05) in pH’s of pure cultures of the moulds in MSEM+1.0%(v/v) ELO medium at 30°C for 0 - 25 day’s; positive correlations between viable counts and fungal dry weights, viable counts and optical densities, and fungal dry weights and optical densities; and negative correlations between pH and viable counts, and pH and optical densities, confirmed the moulds as lubricating oil consuming fungi with potential for use in bioremediation of oil polluted soils. Aspergillus niger exhibited the highest bioremediation capacity and Trichothecium the least. Keywords: Lubricating Oil, Pollution, Fungi, Bioremediatio

Radiomic Texture Feature Descriptor to Distinguish Recurrent Brain Tumor From Radiation Necrosis Using Multimodal MRI

Despite multimodal aggressive treatment with chemo-radiation-therapy, and surgical resection, Glioblastoma Multiforme (GBM) may recur which is known as recurrent brain tumor (rBT), There are several instances where benign and malignant pathologies might appear very similar on radiographic imaging. One such illustration is radiation necrosis (RN) (a moderately benign impact of radiation treatment) which are visually almost indistinguishable from rBT on structural magnetic resonance imaging (MRI). There is hence a need for identification of reliable non-invasive quantitative measurements on routinely acquired brain MRI scans: pre-contrast T1-weighted (T1), post-contrast T1-weighted (T1Gd), T2-weighted (T2), and T2 Fluid Attenuated Inversion Recovery (FLAIR) that can accurately distinguish rBT from RN. In this work, sophisticated radiomic texture features are used to distinguish rBT from RN on multimodal MRI for disease characterization. First, stochastic multiresolution radiomic descriptor that captures voxel-level textural and structural heterogeneity as well as intensity and histogram features are extracted. Subsequently, these features are used in a machine learning setting to characterize the rBT from RN from four sequences of the MRI with 155 imaging slices for 30 GBM cases (12 RN, 18 rBT). To reduce the bias in accuracy estimation our model is implemented using Leave-one-out crossvalidation (LOOCV) and stratified 5-fold cross-validation with a Random Forest classifier. Our model offers mean accuracy of 0.967 ± 0.180 for LOOCV and 0.933 ± 0.082 for stratified 5-fold cross-validation using multiresolution texture features for discrimination of rBT from RN in this study. Our findings suggest that sophisticated texture feature may offer better discrimination between rBT and RN in MRI compared to other works in the literature

Combined analysis of the salivary microbiome and host defence peptides predicts dental disease

Understanding the triad of host response, microbiome and disease status is potentially informative for disease prediction, prevention, early intervention and treatment. Using longitudinal assessment of saliva and disease status, we demonstrated that partial least squares modelling of microbial, immunological and clinical measures, grouped children according to future dental disease status. Saliva was collected and dental health assessed in 33 children aged 4 years, and again 1-year later. The composition of the salivary microbiome was assessed and host defence peptides in saliva were quantified. Principal component analysis of the salivary microbiome indicated that children clustered by age and not disease status. Similarly, changes in salivary host defence peptides occurred with age and not in response to, or preceding dental caries. Partial least squares modelling of microbial, immunological and clinical baseline measures clustered children according to future dental disease status. These data demonstrate that isolated evaluation of the salivary microbiome or host response failed to predict dental disease. In contrast, combined assessment of both host response together with the microbiome revealed clusters of health and disease. This type of approach is potentially relevant to myriad diseases that are modified by host–microbiome interactions

EQ-5D-5L versus 3L: the impact on cost-effectiveness

Objectives To model the relationship between EQ-5D-3L and EQ-5D-5L and examine how differences impact on cost-effectiveness in case studies. Methods We used two datasets that included both EQ-5D-3L and EQ-5D-3L from the same respondents. The EuroQoL dataset (n=3551) included patients with different diseases and a healthy cohort. The National Databank (NDB) dataset included patients with rheumatoid disease (n=5205). We estimated a system of ordinal regressions in each dataset using copula models, to link responses to the 3L instrument to 5L and its tariff, and vice versa. Results were applied to nine cost-effectiveness studies. Results Best-fitting models differed between EuroQoL and NDB datasets in terms of the explanatory variables, copulas and coefficients. In both cases the coefficients of the covariates and latent factor between -3L and -5L were significantly different, indicating that the two instruments are not a uniform realignment of the response levels for most dimensions. In the case studies, moving from 3L to 5L caused a decrease of up to 87% in incremental QALYs gained from effective technologies in almost all cases. ICERs increased, often substantially. Conversely, one technology with a significant mortality gain saw increased incremental QALYs. Conclusion 5L shifts mean utility scores up the utility scale towards full health and compresses them into a smaller range, compared to -3L. Improvements in quality of life are valued less using 5L than with 3L. 3L and 5L can produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences

Opioid Use Disorder Prediction Using Machine Learning of fMRI Data

According to the Centers for Disease Control and Prevention (CDC) more than 932,000 people in the US have died since 1999 from a drug overdose. Just about 75% of drug overdose deaths in 2020 involved Opioid, which suggests that the US is in an Opioid overdose epidemic. Identifying individuals likely to develop Opioid use disorder (OUD) can help public health in planning effective prevention, intervention, drug overdose and recovery policies. Further, a better understanding of prediction of overdose leading to the neurobiology of OUD may lead to new therapeutics. In recent years, very limited work has been done using statistical analysis of functional magnetic resonance imaging (fMRI) methods to analyze the neurobiology of Opioid addictions in humans. In this work, for the first time in the literature, we propose a machine learning (ML) framework to predict OUD users utilizing clinical fMRI-BOLD (Blood oxygen level dependent) signal from OUD users and healthy controls (HC). We first obtain the features and validate these with those extracted from selected brain subcortical areas identified in our previous statistical analysis of the fMRI-BOLD signal discriminating OUD subjects from that of the HC. The selected features from three representative brain areas such as default mode network (DMN), salience network (SN), and executive control network (ECN) for both OUD participants and HC subjects are then processed for OUD and HC subjects’ prediction. Our leave one out cross validated results with sixty-nine OUD and HC cases show 88.40% prediction accuracies. These results suggest that the proposed techniques may be utilized to gain a greater understanding of the neurobiology of OUD leading to novel therapeutic development

Cost-effectiveness of alternative changes to a national blood collection service.

OBJECTIVES: To evaluate the cost-effectiveness of changing opening times, introducing a donor health report and reducing the minimum inter-donation interval for donors attending static centres. BACKGROUND: Evidence is required about the effect of changes to the blood collection service on costs and the frequency of donation. METHODS/MATERIALS: This study estimated the effect of changes to the blood collection service in England on the annual number of whole-blood donations by current donors. We used donors' responses to a stated preference survey, donor registry data on donation frequency and deferral rates from the INTERVAL trial. Costs measured were those anticipated to differ between strategies. We reported the cost per additional unit of blood collected for each strategy versus current practice. Strategies with a cost per additional unit of whole blood less than £30 (an estimate of the current cost of collection) were judged likely to be cost-effective. RESULTS: In static donor centres, extending opening times to evenings and weekends provided an additional unit of whole blood at a cost of £23 and £29, respectively. Introducing a health report cost £130 per additional unit of blood collected. Although the strategy of reducing the minimum inter-donation interval had the lowest cost per additional unit of blood collected (£10), this increased the rate of deferrals due to low haemoglobin (Hb). CONCLUSION: The introduction of a donor health report is unlikely to provide a sufficient increase in donation frequency to justify the additional costs. A more cost-effective change is to extend opening hours for blood collection at static centres

Leveraging PET to image folate receptor α therapy of an antibody-drug conjugate

Background: The folate receptor α (FRα)-targeting antibody-drug conjugate (ADC), IMGN853, shows great antitumor activity against FRα-expressing tumors in vivo, but patient selection and consequently therapy outcome are based on immunohistochemistry. The aim of this study is to develop an antibody-derived immuno-PET imaging agent strategy for targeting FRα in ovarian cancer as a predictor of treatment success. Methods: We developed [89Zr]Zr-DFO-M9346A, a humanized antibody-based radiotracer targeting tumorassociated FRα in the preclinical setting. [89Zr]Zr-DFO-M9346A’s binding ability was tested in an in vitro uptake assay using cell lines with varying FRα expression levels. The diagnostic potential of [89Zr]Zr-M9346A was evaluated in KB and OV90 subcutaneous xenografts. Following intravenous injection of [89Zr]Zr-DFO-M9346A (~90 μCi, 50 μg), PET imaging and biodistribution studies were performed. We determined the blood half-life of [89Zr]Zr-DFO-M9346A and compared it to the therapeutic, radioiodinated ADC [131I]-IMGN853. Finally, in vivo studies using IMG853 as a therapeutic, paired with [89Zr]Zr-DFO-M9346A as a companion diagnostic were performed using OV90 xenografts. Results: DFO-M9346A was labeled with Zr-89 at 37 °C within 60 min and isolated in labeling yields of 85.7 ± 5.7%, radiochemical purities of 98.0 ± 0.7%, and specific activities of 3.08 ± 0.43 mCi/mg. We observed high specificity for binding FRα positive cells in vitro. For PET and biodistribution studies, [89Zr]Zr-M9346A displayed remarkable in vivo performance in terms of excellent tumor uptake for KB and OV xenografts (45.8 ± 29.0 %IA/g and 26.1 ± 7.2 %IA/g), with low non-target tissue uptake in other organs such as kidneys (4.5 ± 1.2 %IA/g and 4.3 ± 0.7 %IA/g). A direct comparison of the blood half life of [89Zr]Zr-M9346A and [131I]-IMGN853 corroborated the equivalency of the radiopharmaceutical and the ADC, paving the way for a companion PET imaging study. Conclusions: We developed a new folate receptor-targeted 89Zr-labeled PET imaging agent with excellent pharmacokinetics in vivo. Good tumor uptake in subcutaneous KB and OV90 xenografts were obtained, and ADC therapy studies were performed with the precision predictor