A Physiologically-Based Pharmacokinetic Model for the Antibiotic Ertapenem

Ertapenem is an antibiotic commonly used to treat a broad spectrum of infections, which is part of a broader class of antibiotics called carbapenem. Unlike other carbapenems, ertapenem has a longer half-life and thus only has to be administered once a day. A physiologically-based pharmacokinetic (PBPK) model was developed to investigate the uptake, distribution, and elimination of ertapenem following a single one gram dose. PBPK modeling incorporates known physiological parameters such as body weight, organ volumes, and blood ow rates in particular tissues. Furthermore, ertapenem is highly bound in human blood plasma; therefore, nonlinear binding is incorporated in the model since only the free portion of the drug can saturate tissues and, hence, is the only portion of the drug considered to be medicinally effective. Parameters in the model were estimated using a least squares inverse problem formulation with published data for blood concentrations of ertapenem for normal height, normal weight males. Finally, an uncertainty analysis of the parameter estimation and model predictions is presented

Evolution Of A Higher Intracellular Oxidizing Environment In Caenorhabditis Elegans Under Relaxed Selection

We explored the relationship between relaxed selection, oxidative stress, and spontaneous mutation in a set of mutation-accumulation (MA) lines of the nematode Caenorhabditis elegans and in their common ancestor. We measured steady-state levels of free radicals and oxidatively damaged guanosine nucleosides in the somatic tissues of five MA lines for which nuclear genome base substitution and GC-TA transversion frequencies are known. The two markers of oxidative stress are highly correlated and are elevated in the MA lines relative to the ancestor; point estimates of the per-generation rate of mutational decay (DM) of these measures of oxidative stress are similar to those reported for fitness-related traits. Conversely, there is no significant relationship between either marker of oxidative stress and the per-generation frequencies of base substitution or GC-TA transversion. Although these results provide no direct evidence for a causative relationship between oxidative damage and base substitution mutations, to the extent that oxidative damage may be weakly mutagenic in the germline, the case for condition-dependent mutation is advanced

Bilateral Carotid Artery Dissection After a Fall: A Case of Horner Syndrome Revealed on Examination

Introduction: Carotid artery dissections are uncommon but critical vascular injuries. They involve a tear to the intima, the innermost layer of the arterial wall, leading to formation of a false lumen. This false lumen can disrupt blood flow, weaken the wall, and lead to thrombus or rupture of the artery. Carotid artery dissections can occur spontaneously or in the setting of trauma. Traumatic carotid artery dissections (TCAD) are rare and occasionally present with third-order Horner syndrome,characterized by ipsilateral ptosis, miosis, and anhidrosis. The presence of subtle physical exam signs like Horner syndrome reinforces the importance of maintaining a high index of suspicion and obtaining vascular imaging in trauma-related cases. While there have been case reports of bilateral TCAD, these have been rarely reported in the literature. Case Report: We present a case involving a 53-year-old female with no significant past medical history who presented to the emergency department after tripping and falling down a flight of stairs. Over three weeks, the patient had persistent tinnitus and right neck pain and, on the exam, was found to have right-sided miosis and ptosis. These exam findings led us to obtain a computed tomography (CT) angiogram of her neck, which revealed bilateral internal carotid artery dissections.The patient was taken for cerebral angiography, which confirmed the diagnosis. A stent was placed in the right internal carotid artery, and the patient was started on aspirin and clopidogrel. The patient was discharged without deficits three days later. Conclusion: Traumatic internal carotid artery dissection can occasionally result in Horner syndrome and requires CT angiography of the neck and potentially a diagnostic cerebral angiogram to diagnose. This case adds to the limited literature on bilateral TCAD, particularly with a delayed and asymmetric presentation. Horner syndrome in the setting of trauma, while subtle, can suggest a carotid artery dissection. Awareness of such rare presentations is key to early diagnosis andtreatment. Clinicians must maintain a high index of suspicion for underlying vascular injury in patients presenting with lesser mechanisms of injury

Coronary Artery Stenosis and High-Risk Plaque Assessed With an Unsupervised Fully Automated Deep Learning Technique

BackgroundCoronary computed tomography angiography (CCTA) has emerged as a reliable noninvasive modality to assess coronary artery stenosis and high-risk plaque (HRP). However, CCTA assessment of stenosis and HRP is time-consuming and requires specialized training, limiting its clinical translation.ObjectivesThe aim of this study is to develop and validate a fully automated deep learning system capable of characterizing stenosis severity and HRP on CCTA.MethodsA deep learning system was trained to assess stenosis and HRP on CCTA scans from 570 patients in multiple centers. Stenosis severity was categorized as >0%, 1 to 49%, ≥50%, and ≥70%. HRP was defined as low attenuation plaque (≤30 HU), positive remodeling (≥10% diameter), and spotty calcification (<3 mm). The model was then tested on 769 patients (3,012 vessels) for stenosis severity and 45 patients (325 vessels) for HRP.ResultsOur deep learning system achieved 93.5% per-vessel agreement within 1 Coronary Artery Disease-Reporting and Data System (CAD-RADS) category for stenosis. Diagnostic performance for per-vessel stenosis was very good for sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve with: >0% stenosis: 90.6%, 88.8%, 83.4%, 93.9%, 89.7%, respectively; ≥50% stenosis: 87.1%, 92.3%, 60.9%, 98.1%, 89.7%, respectively. Similarly, the per-vessel HRP feature achieved very good diagnostic performance with an area under the curve of 0.80, 0.79, and 0.77 for low attenuation plaque, spotty calcification, and positive remodeling, respectively.ConclusionsA fully automated unsupervised deep learning system can rapidly evaluate stenosis severity and characterize HRP with very good diagnostic performance on CCTA

Evaluation of an Artificial Intelligence Coronary Artery Calcium Scoring Model from Computed Tomography

OBJECTIVES: Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC. METHODS: Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1–10, 11–100, 101–400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers). RESULTS: Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman’s r = 0.90, 95% confidence interval [CI] 0.89–0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98–0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland–Altman analysis demonstrated little difference (1.69, 95% limits of agreement: −41.22, 44.60) and there was almost excellent agreement (Cohen’s κ = 0.90, 95% CI 0.88–0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan. CONCLUSIONS: This artificial intelligence–based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation. KEY POINTS: • Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)–based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09028-3

Evolution of a Higher Intracellular Oxidizing Environment in Caenorhabditis elegans under Relaxed Selection

We explored the relationship between relaxed selection, oxidative stress, and spontaneous mutation in a set of mutation-accumulation (MA) lines of the nematode Caenorhabditis elegans and in their common ancestor. We measured steady-state levels of free radicals and oxidatively damaged guanosine nucleosides in the somatic tissues of five MA lines for which nuclear genome base substitution and GC-TA transversion frequencies are known. The two markers of oxidative stress are highly correlated and are elevated in the MA lines relative to the ancestor; point estimates of the per-generation rate of mutational decay (DM) of these measures of oxidative stress are similar to those reported for fitness-related traits. Conversely, there is no significant relationship between either marker of oxidative stress and the per-generation frequencies of base substitution or GC-TA transversion. Although these results provide no direct evidence for a causative relationship between oxidative damage and base substitution mutations, to the extent that oxidative damage may be weakly mutagenic in the germline, the case for condition-dependent mutation is advanced

Sex-specific risk of cardiovascular disease and cognitive decline: pregnancy and menopause

Understanding the biology of sex differences is integral to personalized medicine. Cardiovascular disease and cognitive decline are two related conditions, with distinct sex differences in morbidity and clinical manifestations, response to treatments, and mortality. Although mortality from all-cause cardiovascular diseases has declined in women over the past five years, due in part to increased educational campaigns regarding the recognition of symptoms and application of treatment guidelines, the mortality in women still exceeds that of men. The physiological basis for these differences requires further research, with particular attention to two physiological conditions which are unique to women and associated with hormonal changes: pregnancy and menopause. Both conditions have the potential to impact life-long cardiovascular risk, including cerebrovascular function and cognition in women. This review draws on epidemiological, translational, clinical, and basic science studies to assess the impact of hypertensive pregnancy disorders on cardiovascular disease and cognitive function later in life, and examines the effects of post-menopausal hormone treatments on cardiovascular risk and cognition in midlife women. We suggest that hypertensive pregnancy disorders and menopause activate vascular components, i.e., vascular endothelium and blood elements, including platelets and leukocytes, to release cell-membrane derived microvesicles that are potential mediators of changes in cerebral blood flow, and may ultimately affect cognition in women as they age. Research into specific sex differences for these disease processes with attention to an individual’s sex chromosomal complement and hormonal status is important and timely

Drug problems among homeless individuals in Toronto, Canada: prevalence, drugs of choice, and relation to health status

<p>Abstract</p> <p>Background</p> <p>Drug use is believed to be an important factor contributing to the poor health and increased mortality risk that has been widely observed among homeless individuals. The objective of this study was to determine the prevalence and characteristics of drug use among a representative sample of homeless individuals and to examine the association between drug problems and physical and mental health status.</p> <p>Methods</p> <p>Recruitment of 603 single men, 304 single women, and 284 adults with dependent children occurred at homeless shelters and meal programs in Toronto, Canada. Information was collected on demographic characteristics and patterns of drug use. The Addiction Severity Index was used to assess whether participants suffered from drug problems. Associations of drug problems with physical and mental health status (measured by the SF-12 scale) were examined using regression analyses.</p> <p>Results</p> <p>Forty percent of the study sample had drug problems in the last 30 days. These individuals were more likely to be single men and less educated than those without drug problems. They were also more likely to have become homeless at a younger age (mean 24.8 vs. 30.9 years) and for a longer duration (mean 4.8 vs. 2.9 years). Marijuana and cocaine were the most frequently used drugs in the past two years (40% and 27%, respectively). Drug problems within the last 30 days were associated with significantly poorer mental health status (-4.9 points, 95% CI -6.5 to -3.2) but not with poorer physical health status (-0.03 points, 95% CI -1.3 to 1.3)).</p> <p>Conclusions</p> <p>Drug use is common among homeless individuals in Toronto. Current drug problems are associated with poorer mental health status but not with poorer physical health status.</p

Beyond Increasing Sample Sizes: Optimizing Effect Sizes in Neuroimaging Research on Individual Differences

Linking neurobiology to relatively stable individual differences in cognition, emotion, motivation, and behavior can require large sample sizes to yield replicable results. Given the nature of between-person research, sample sizes at least in the hundreds are likely to be necessary in most neuroimaging studies of individual differences, regardless of whether they are investigating the whole brain or more focal hypotheses. However, the appropriate sample size depends on the expected effect size. Therefore, we propose four strategies to increase effect sizes in neuroimaging research, which may help to enable the detection of replicable between-person effects in samples in the hundreds rather than the thousands: (1) theoretical matching between neuroimaging tasks and behavioral constructs of interest; (2) increasing the reliability of both neural and psychological measurement; (3) individualization of measures for each participant; and (4) using multivariate approaches with cross-validation instead of univariate approaches. We discuss challenges associated with these methods and highlight strategies for improvements that will help the field to move toward a more robust and accessible neuroscience of individual differences