Efficacy of ravulizumab in patients with generalized myasthenia gravis by time from diagnosis: A post hoc subgroup analysis of the CHAMPION MG study.

INTRODUCTION/AIMS: The CHAMPION MG study demonstrated that ravulizumab significantly improved Myasthenia Gravis-Activities of Daily Living (MG-ADL) and Quantitative Myasthenia Gravis (QMG) total scores versus placebo in adults with acetylcholine receptor antibody-positive generalized myasthenia gravis (AChR+ gMG). This post hoc analysis aimed to assess these outcomes by time from MG diagnosis. METHODS: Changes from baseline to week 26 in MG-ADL and QMG total scores were analyzed by time from MG diagnosis to study entry (≤2 vs. >2 years). Within each subgroup, least-squares (LS) mean changes for ravulizumab and placebo were compared using mixed models for repeated measures. RESULTS: In ravulizumab-treated patients, differences in LS mean (standard error of the mean) changes from baseline to week 26 were not statistically significant in the ≤2-years subgroup versus the >2-years subgroup for MG-ADL (-4.3 [0.70] vs. -2.9 [0.37]; p = .0511) or QMG (-4.3 [0.94] vs. -2.5 [0.50]; p = .0822) scores. No clear trends were observed in the placebo group. LS mean changes from baseline were significantly greater for ravulizumab versus placebo in both the ≤2 and >2 years from diagnosis subgroups for MG-ADL and QMG scores (all p < .05). The difference in treatment effect between the ≤2-years and >2-years subgroups was not statistically significant. No clinically meaningful between-subgroup differences in treatment-emergent adverse events were observed in ravulizumab-treated patients. DISCUSSION: Ravulizumab treatment improved clinical outcomes for patients with AChR+ gMG regardless of time from diagnosis. A numerical trend was observed favoring greater treatment effect with earlier versus later treatment after diagnosis. Further studies are required for confirmation.

Impact of Baseline Anxiety on Well-being in People with Post-COVID-19 Condition: A Secondary Analysis.

BACKGROUND: Post-COVID-19 condition (PCC) is associated with a host of psychopathological conditions including prominent anxiety symptoms. However, it is not known what effect anxious symptoms have on measures of well-being in individuals living with PCC. This study aims to evaluate anxiety's association with measures of well-being in people with PCC. METHODS: This is a post hoc analysis utilizing data from a placebo-controlled, randomized, double-blind clinical trial assessing the effect of vortioxetine on cognitive impairment in individuals with PCC (NCT05047952). Baseline data with respect to anxiety and well-being were collected using the Generalized Anxiety Disorder Scale, 7-Item (GAD-7), and the World Health Organization (WHO) Well-Being Index, 5-Item (WHO-5), respectively. A generalized linear model (GLM) analysis on baseline GAD-7 and WHO-5 scores was conducted with age, sex, employment status, education level, previous major depressive disorder (MDD) diagnosis, and confirmed COVID-19 cases as covariates. RESULTS: Data was analyzed in a sample of 144 participants (N = 144). After controlling for the aforementioned covariates, the results found that GAD-7 and WHO-5 scores had a significant negative correlation (ß = -0.053, p = <0.001), signifying that increased anxiety had adverse effects on the overall well-being of individuals with PCC. CONCLUSION: Herein, we observed a clinically meaningful level of anxiety in individuals with PCC. We also identified a robust correlation between anxiety in PCC and measures of general well-being. Our results require replication, providing the impetus for recommending screening and targeting anxious symptoms as a tactic to improve general well-being and outcomes in individuals with PCC.

New Approach Methodologies (NAMs) for ad hoc human health risk assessment of food and non-food products - Proceedings of a workshop.

RIVM convened a workshop on the use of New Approach Methodologies (NAMs) for the ad hoc human health risk assessment of food and non-food products. Central to the workshop were two case studies of marketed products with a potential health concern: the botanical Tabernanthe iboga which is used to facilitate mental or spiritual insight or to (illegally) treat drug addiction and is associated with cardiotoxicity, and dermal creams containing female sex hormones, intended for use by perimenopausal women to reduce menopause symptoms without medical supervision. The workshop participants recognized that data from NAM approaches added valuable information for the ad hoc risk assessment of these products, although the available approaches were inadequate to derive health-based guidance values. Recommendations were provided on how to further enhance and implement NAM approaches in regulatory risk assessment, specifying both scientific and technical aspects as well as stakeholder engagement aspects.

R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut.

Transformer-based models have gained popularity in the field of natural language processing (NLP) and are extensively utilized in computer vision tasks and multi-modal models such as GPT4. This paper presents a novel method to enhance the explainability of transformer-based image classification models. Our method aims to improve trust in classification results and empower users to gain a deeper understanding of the model for downstream tasks by providing visualizations of class-specific maps. We introduce two modules: the "Relationship Weighted Out" and the "Cut" modules. The "Relationship Weighted Out" module focuses on extracting class-specific information from intermediate layers, enabling us to highlight relevant features. Additionally, the "Cut" module performs fine-grained feature decomposition, taking into account factors such as position, texture, and color. By integrating these modules, we generate dense class-specific visual explainability maps. We validate our method with extensive qualitative and quantitative experiments on the ImageNet dataset. Furthermore, we conduct a large number of experiments on the LRN dataset, which is specifically designed for automatic driving danger alerts, to evaluate the explainability of our method in scenarios with complex backgrounds. The results demonstrate a significant improvement over previous methods. Moreover, we conduct ablation experiments to validate the effectiveness of each module. Through these experiments, we are able to confirm the respective contributions of each module, thus solidifying the overall effectiveness of our proposed approach.

Delay-Oriented Roadside Unit Deployment for Highway Intersections in Vehicular Ad Hoc Networks.

Optimizing the deployment of roadside units (RSUs) holds great potential for enhancing the delay performance of vehicular ad hoc networks. However, there has been limited focus on devising RSU deployment strategies tailored specifically for highway intersections. In this study, we introduce a novel probabilistic model to characterize events occurring around highway intersections. By leveraging this model, we analytically determine the expected event reporting delays for both highway segments and intersections. Subsequently, we propose an RSU deployment scheme specifically designed for highway intersections, aimed at minimizing the expected event reporting delay. To implement this scheme, we introduce an innovative algorithm named cooperative walking. Through illustrative examples, we demonstrate that our proposed RSU deployment strategy for highway intersections outperforms the commonly employed uniform RSU deployment scheme and the previously proposed balloon method in terms of delay performance.

Integrated Sensing and Secure Communication with XL-MIMO.

This paper studies extremely large-scale multiple-input multiple-output (XL-MIMO)-empowered integrated sensing and secure communication systems, where both the radar targets and the communication user are located within the near-field region of the transmitter. The radar targets, being untrusted entities, have the potential to intercept the confidential messages intended for the communication user. In this context, we investigate the near-field beam-focusing design, aiming to maximize the achievable secrecy rate for the communication user while satisfying the transmit beampattern gain requirements for the radar targets. We address the corresponding globally optimal non-convex optimization problem by employing a semidefinite relaxation-based two-stage procedure. Additionally, we provide a sub-optimal solution to reduce complexity. Numerical results demonstrate that beam focusing enables the attainment of a positive secrecy rate, even when the radar targets and communication user align along the same angle direction.

Ad Hoc Mesh Network Localization Using Ultra-Wideband for Mobile Robotics.

This article explores the implementation of high-accuracy GPS-denied ad hoc localization. Little research exists on ad hoc ultra-wideband-enabled localization systems with mobile and stationary nodes. This work aims to demonstrate the localization of bicycle-modeled robots in a non-static environment through a mesh network of mobile, stationary robots, and ultra-wideband sensors. The non-static environment adds a layer of complexity when actors can enter and exit the node's field of view. The method starts with an initial localization step where each unmanned ground vehicle (UGV) uses the surrounding, available anchors to derive an initial local or, if possible, global position estimate. The initial localization uses a simplified implementation of the iterative multi-iteration ad hoc localization system (AHLos). This estimate was refined using an unscented Kalman filter (UKF) following a constant turn rate and velocity magnitude model (CTRV). The UKF then fuses the robot's odometry and the range measurements from the Decawave ultra-wideband receivers stationed on the network nodes. Through this position estimation stage, the robot broadcasts its estimated position to its neighbors to help the others further improve their localization estimates and localize themselves. This wave-like cycle of nodes helping to localize each other allows the network to act as a mobile ad hoc localization network.

Internet of Vehicles (IoV)-Based Task Scheduling Approach Using Fuzzy Logic Technique in Fog Computing Enables Vehicular Ad Hoc Network (VANET).

The intelligent transportation system (ITS) relies heavily on the vehicular ad hoc network (VANET) and the internet of vehicles (IoVs), which combine cloud and fog to improve task processing capabilities. As a cloud extension, the fog processes' infrastructure is close to VANET, fostering an environment favorable to smart cars with IT equipment and effective task management oversight. Vehicle processing power, bandwidth, time, and high-speed mobility are all limited in VANET. It is critical to satisfy the vehicles' requirements for minimal latency and fast reaction times while offloading duties to the fog layer. We proposed a fuzzy logic-based task scheduling system in VANET to minimize latency and improve the enhanced response time when offloading tasks in the IoV. The proposed method effectively transfers workloads to the fog computing layer while considering the constrained resources of car nodes. After choosing a suitable processing unit, the algorithm sends the job and its associated resources to the fog layer. The dataset is related to crisp values for fog computing for system utilization, latency, and task deadline time for over 5000 values. The task execution, latency, deadline of task, storage, CPU, and bandwidth utilizations are used for fuzzy set values. We proved the effectiveness of our proposed task scheduling framework via simulation tests, outperforming current algorithms in terms of task ratio by 13%, decreasing average turnaround time by 9%, minimizing makespan time by 15%, and effectively overcoming average latency time within the network parameters. The proposed technique shows better results and responses than previous techniques by scheduling the tasks toward fog layers with less response time and minimizing the overall time from task submission to completion.

Routing Selection Algorithm for Mobile Ad Hoc Networks Based on Neighbor Node Density.

In the process of data transmission in mobile ad hoc networks, it is essential to establish optimal routes from source nodes to destination nodes. However, as network density increases, this process is often accompanied by a significant rise in network overhead. To address this issue, the ND-AODV (neighborhood density AODV) protocol has been introduced, which reduces the probability of transmitting control information in high-density node environments to mitigate network overhead. Nevertheless, this may come at the cost of reduced routing accuracy, potentially leading to unnecessary resource wastage in certain scenarios. Furthermore, ND-AODV does not comprehensively consider the location of the receiving nodes, which limits its ability to reduce network overhead effectively. To overcome these limitations, this paper introduces a novel routing approach, known as CND-AODV (common neighborhood density AODV). In comparison to ND-AODV, CND-AODV offers a more comprehensive solution to the challenges posed by high-density network environments. It intelligently processes control information based on the special positioning of the receiving nodes, thereby significantly reducing unnecessary network overhead. Through simulation experiments comparing performance metrics such as throughput, packet delivery rate, and latency, the results clearly indicate that CND-AODV substantially decreases network overhead, enhancing network performance. Compared to ND-AODV, this innovative routing approach exhibits significant advantages. It provides a more efficient and reliable solution for ad hoc networks in high-density environments.

A Novel Framed Slotted Aloha Medium Access Control Protocol Based on Capture Effect in Vehicular Ad Hoc Networks.

The capture effect is a frequently observed phenomenon in vehicular ad hoc networks (VANETs) communication. When conflicts arise during time slot access, failure to access does not necessarily occur; instead, successful access may still be achieved. The capture effect can enhance the likelihood of multiple access and improve communication efficiency. The security of VANETs communication is undoubtedly the primary concern. One crucial approach to enhance security involves the design of an efficient and reliable medium access control (MAC) protocol. Taking into account both aspects, we propose a novel framed slotted Aloha (FSA) MAC protocol model. Firstly, we derive the closed-form expression for the capture probability in the Rician fading channel in this paper. Subsequently, we analyze how the number of vehicles and time slots influence the success probability of vehicle access channels as well as examine the impact of the capture effect on this success probability. Then, under constraints regarding vehicle access channel success probability, we derive optimal values for slot numbers, access times, and transmission power while proposing a comprehensive implementation method to ensure high access channel success probabilities. We verify both theoretical derivations and proposed methods through simulation experiments.

Feasibility Analysis of ECG-Based pH Estimation for Asphyxia Detection in Neonates.

Birth asphyxia is a potential cause of death that is also associated with acute and chronic morbidities. The traditional and immediate approach for monitoring birth asphyxia (i.e., arterial blood gas analysis) is highly invasive and intermittent. Additionally, alternative noninvasive approaches such as pulse oximeters can be problematic, due to the possibility of false and erroneous measurements. Therefore, further research is needed to explore alternative noninvasive and accurate monitoring methods for asphyxiated neonates. This study aims to investigate the prominent ECG features based on pH estimation that could potentially be used to explore the noninvasive, accurate, and continuous monitoring of asphyxiated neonates. The dataset used contained 274 segments of ECG and pH values recorded simultaneously. After preprocessing the data, principal component analysis and the Pan-Tompkins algorithm were used for each segment to determine the most significant ECG cycle and to compute the ECG features. Descriptive statistics were performed to describe the main properties of the processed dataset. A Kruskal-Wallis nonparametric test was then used to analyze differences between the asphyxiated and non-asphyxiated groups. Finally, a Dunn-Sidák post hoc test was used for individual comparison among the mean ranks of all groups. The findings of this study showed that ECG features (T/QRS, T Amplitude, Tslope, Tslope/T, Tslope/|T|, HR, QT, and QTc) based on pH estimation differed significantly (p < 0.05) in asphyxiated neonates. All these key ECG features were also found to be significantly different between the two groups.

Dual-Slope Path Loss Model for Integrating Vehicular Sensing Applications in Urban and Suburban Environments.

The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions.

Predictivism and avoidance of ad hoc-ness: An empirical study.

Predictivism is the thesis that evidence successfully predicted by a scientific theory counts more (or ought to count more) in the confirmation of that theory than already known evidence would. One rationale that has been proposed for predictivism is that predictive success guards against ad hoc hypotheses. Despite the intuitive attraction of predictivism, there is historical evidence that speaks against it. As valuable as the historical evidence may be, however, it is largely indirect evidence for the epistemic attitudes of individual - albeit prominent - scientists. This paper presents the results of an empirical study of scientists' attitudes toward predictivism and ad hoc-ness (n = 492), which will put the debate on a more robust empirical footing. The paper also draws attention to a tension between the ad hoc-ness avoidance rationale of predictivism and the ways philosophers have spelled out the notion of ad hoc-ness.

Controlling for false discoveries subsequently to large scale one-way ANOVA testing in proteomics: Practical considerations.

In discovery proteomics, as well as many other "omic" approaches, the possibility to test for the differential abundance of hundreds (or of thousands) of features simultaneously is appealing, despite requiring specific statistical safeguards, among which controlling for the false discovery rate (FDR) has become standard. Moreover, when more than two biological conditions or group treatments are considered, it has become customary to rely on the one-way analysis of variance (ANOVA) framework, where a first global differential abundance landscape provided by an omnibus test can be subsequently refined using various post-hoc tests (PHTs). However, the interactions between the FDR control procedures and the PHTs are complex, because both correspond to different types of multiple test corrections (MTCs). This article surveys various ways to orchestrate them in a data processing workflow and discusses their pros and cons.

Haplotype based testing for a better understanding of the selective architecture.

BACKGROUND: The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies. RESULTS: Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits. CONCLUSIONS: Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios.

Workplace-based primary prevention intervention reduces incidence of hypertension: a post hoc analysis of cluster randomized controlled study.

BACKGROUND: A workplace-based primary prevention intervention be an effective approach to reducing the incidence of hypertension (HTN). However, few studies to date have addressed the effect among the Chinese working population. We assessed the effect of a workplace-based multicomponent prevention interventions program for cardiovascular disease on reducing the occurrence of HTN through encouraging employees to adopt a healthy lifestyle. METHODS: In this post hoc analysis of cluster randomized controlled study, 60 workplaces across 20 urban regions in China were randomized to either the intervention group (n = 40) or control group (n = 20). All employees in each workplace were asked to complete a baseline survey after randomization for obtaining sociodemographic information, health status, lifestyle, etc. Employees in the intervention group were given a 2-year workplace-based primary prevention intervention program for improving their cardiovascular health, including (1) cardiovascular health education, (2) a reasonable diet, (3) tobacco cessation, (4) physical environment promotion, (5) physical activity, (6) stress management, and (7) health screening. The primary outcome was the incidence of HTN, and the secondary outcomes were improvements of blood pressure (BP) levels and lifestyle factors from baseline to 24 months. A mix effect model was used to assess the intervention effect at the end of the intervention in the two groups. RESULTS: Overall, 24,396 participants (18,170 in the intervention group and 6,226 in the control group) were included (mean [standard deviation] age, 39.3 [9.1] years; 14,727 men [60.4%]). After 24 months of the intervention, the incidence of HTN was 8.0% in the intervention groups and 9.6% in the control groups [relative risk (RR) = 0.66, 95% CI, 0.58 ~ 0.76, P < 0.001]. The intervention effect was significant on systolic BP (SBP) level (ß = - 0.7 mm Hg, 95% CI, - 1.06 ~ - 0.35; P < 0.001) and on diastolic BP (DBP) level (ß = - 1.0 mm Hg, 95% CI, - 1.31 ~ - 0.76; P < 0.001). Moreover, greater improvements were reported in the rates of regular exercise [odd ratio (OR) = 1.39, 95% CI, 1.28 ~ 1.50; P < 0.001], excessive intake of fatty food (OR = 0.54, 95% CI, 0.50 ~ 0.59; P < 0.001), and restrictive use of salt (OR = 1.22, 95% CI, 1.09 ~ 1.36; P = 0.001) in intervention groups. People with a deteriorating lifestyle had higher rates of developing HTN than those with the same or improved lifestyle. Subgroup analysis showed that the intervention effect of BP on employees with educational attainment of high school above (SBP: ß = - 1.38/ - 0.76 mm Hg, P < 0.05; DBP: ß = - 2.26/ - 0.75 mm Hg, P < 0.001), manual labor workers and administrative worker (SBP: ß = - 1.04/ - 1.66 mm Hg, P < 0.05; DBP: ß = - 1.85/ - 0.40 mm Hg, P < 0.05), and employees from a workplace with an affiliated hospital (SBP: ß = - 2.63 mm Hg, P < 0.001; DBP: ß = - 1.93 mm Hg, P < 0.001) were significantly in the intervention group. CONCLUSIONS: This post hoc analysis found that workplace-based primary prevention interventions program for cardiovascular disease were effective in promoting healthy lifestyle and reducing the incidence of HTN among employees. TRIAL REGISTRATION: Chinese Clinical Trial Registry No. ChiCTR-ECS-14004641.

Cardiac resynchronization therapy in patients with a prior history of atrial fibrillation: Insights from four major clinical trials.

AIMS: To investigate the association of cardiac resynchronization therapy (CRT) on outcomes among participants with and without a history of atrial fibrillation (AF). METHODS: Individual-patient-data from four randomized trials investigating CRT-Defibrillators (COMPANION, MADIT-CRT, REVERSE) or CRT-Pacemakers (COMPANION, MIRACLE) were analyzed. Outcomes were time to a composite of heart failure hospitalization or all-cause mortality or to all-cause mortality alone. The association of CRT on outcomes for patients with and without a history of AF was assessed using a Bayesian-Weibull survival regression model adjusting for baseline characteristics. RESULTS: Of 3964 patients included, 586 (14.8%) had a history of AF; 2245 (66%) were randomized to CRT. Overall, CRT reduced the risk of the primary composite endpoint (hazard ratio [HR]: 0.69, 95% credible interval [CI]: 0.56-0.81). The effect was similar (posterior probability of no interaction = 0.26) in patients with (HR: 0.78, 95% CI: 0.55-1.10) and without a history of AF (HR: 0.67, 95% CI: 0.55-0.80). In these four trials, CRT did not reduce mortality overall (HR: 0.82, 95% CI: 0.66-1.01) without evidence of interaction (posterior probability of no interaction = 0.14) for patients with (HR: 1.09, 95% CI: 0.70-1.74) or without a history of AF (HR: 0.70, 95% CI: 0.60-0.97). CONCLUSION: The association of CRT on the composite endpoint or mortality was not statistically different for patients with or without a history of AF, but this could reflect inadequate power. Our results call for trials to confirm the benefit of CRT recipients with a history of AF.

Closed testing with Globaltest, with application in metabolomics.

The Globaltest is a powerful test for the global null hypothesis that there is no association between a group of features and a response of interest, which is popular in pathway testing in metabolomics. Evaluating multiple feature sets, however, requires multiple testing correction. In this paper, we propose a multiple testing method, based on closed testing, specifically designed for the Globaltest. The proposed method controls the familywise error rate simultaneously over all possible feature sets, and therefore allows post hoc inference, that is, the researcher may choose feature sets of interest after seeing the data without jeopardizing error control. To circumvent the exponential computation time of closed testing, we derive a novel shortcut that allows exact closed testing to be performed on the scale of metabolomics data. An R package ctgt is available on comprehensive R archive network for the implementation of the shortcut procedure, with applications on several real metabolomics data examples.

Active Uptake of Oxycodone at Both the Blood-Cerebrospinal Fluid Barrier and The Blood-Brain Barrier without Sex Differences: A Rat Microdialysis Study.

BACKGROUND: Oxycodone active uptake across the blood-brain barrier (BBB) is associated with the putative proton-coupled organic cation (H+/OC) antiporter system. Yet, the activity of this system at the blood-cerebrospinal fluid barrier (BCSFB) is not fully understood. Additionally, sex differences in systemic pharmacokinetics and pharmacodynamics of oxycodone has been reported, but whether the previous observations involve sex differences in the function of the H+/OC antiporter system remain unknown. The objective of this study was, therefore, to investigate the extent of oxycodone transport across the BBB and the BCSFB in female and male Sprague-Dawley rats using microdialysis. METHODS: Microdialysis probes were implanted in the blood and two of the following brain locations: striatum and lateral ventricle or cisterna magna. Oxycodone was administered as an intravenous infusion, and dialysate, blood and brain were collected. Unbound partition coefficients (Kp,uu) were calculated to understand the extent of oxycodone transport across the blood-brain barriers. Non-compartmental analysis was conducted using Phoenix 64 WinNonlin. GraphPad Prism version 9.0.0 was used to perform t-tests, one-way and two-way analysis of variance followed by Tukey's or Sídák's multiple comparison tests. Differences were considered significant at p < 0.05. RESULTS: The extent of transport at the BBB measured in striatum was 4.44 ± 1.02 (Kp,uu,STR), in the lateral ventricle 3.41 ± 0.74 (Kp,uu,LV) and in cisterna magna 2.68 ± 1.01 (Kp,uu,CM). These Kp,uu values indicate that the extent of oxycodone transport is significantly lower at the BCSFB compared with that at the BBB, but still confirm the presence of active uptake at both blood-brain interfaces. No significant sex differences were observed in neither the extent of oxycodone delivery to the brain, nor in the systemic pharmacokinetics of oxycodone. CONCLUSIONS: The findings clearly show that active uptake is present at both the BCSFB and the BBB. Despite some underestimation of the extent of oxycodone delivery to the brain, CSF may be an acceptable surrogate of brain ISF for oxycodone, and potentially also other drugs actively transported into the brain via the H+/OC antiporter system.

Effect of Microplastic Types on the In Vivo Bioavailability of Polychlorinated Biphenyls.

As MPs are released into the soil, various equilibrium statuses are expected. MPs could play roles as a "source," a "cleaner," or a "sink" of HOCs. Three types of MPs (LDPE, PLA, and PS) were selected to study their effect on polychlorinated biphenyl (PCBs) relative bioavailability (RBA) measured by a mouse model. As a "source" of HOCs, exposure to MP-sorbed PCBs resulted in their accumulation in adipose tissue with PCB RBA as 101 ± 6.73% for LDPE, 76.2 ± 19.2% for PLA, and 9.22 ± 2.02% for PS. The addition of 10% MPs in PCB-contaminated soil led to a significant (p < 0.05) reduction in PCB RBA (52.2 ± 16.7%, 49.3 ± 4.85%, and 47.1 ± 5.99% for LDPE, PLA, and PS) compared to control (75.0 ± 4.26%), implying MPs acted as "cleaner" by adsorbing PCBs from the digestive system and reducing PCB accumulation. MPs acted as a "sink" for PCBs in contaminated soil after aging, but the sink effect varied among MP types with more pronounced effect for LDPE than PLA and PS. Therefore, the role played by MPs in bioavailability of HOCs closely depended on the MP types as well as the equilibrium status among MPs, soil, and HOCs.