How to be an effective ally.

Inclusivity in biomedical research provides many positive attributes, including increased productivity, higher creativity, and improved wellness for all. While marginalized individuals work tirelessly to achieve equity and inclusion, this task should not be left solely to those most affected by exclusionary tactics. These individuals and the organizations with whom they are affiliated would benefit from the support of an ally. An ally is defined as a person or organization that actively supports the rights of a marginalized group without being a member of it. Allies have a unique opportunity to play a pivotal role in promoting fairness, equity, and inclusion, and thus serve as positive change agents within an organizational setting. We summarize here the importance of being an effective and dynamic ally and offer guidance on how to achieve that goal.

BiU-net: A dual-branch structure based on two-stage fusion strategy for biomedical image segmentation.

BACKGROUND AND OBJECTIVE: Computer-based biomedical image segmentation plays a crucial role in planning of assisted diagnostics and therapy. However, due to the variable size and irregular shape of the segmentation target, it is still a challenge to construct an effective medical image segmentation structure. Recently, hybrid architectures based on convolutional neural networks (CNNs) and transformers were proposed. However, most current backbones directly replace one or all convolutional layers with transformer blocks, regardless of the semantic gap between features. Thus, how to sufficiently and effectively eliminate the semantic gap as well as combine the global and local information is a critical challenge. METHODS: To address the challenge, we propose a novel structure, called BiU-Net, which integrates CNNs and transformers with a two-stage fusion strategy. In the first fusion stage, called Single-Scale Fusion (SSF) stage, the encoding layers of the CNNs and transformers are coupled, with both having the same feature map size. The SSF stage aims to reconstruct local features based on CNNs and long-range information based on transformers in each encoding block. In the second stage, Multi-Scale Fusion (MSF), BiU-Net interacts with multi-scale features from various encoding layers to eliminate the semantic gap between deep and shallow layers. Furthermore, a Context-Aware Block (CAB) is embedded in the bottleneck to reinforce multi-scale features in the decoder. RESULTS: Experiments on four public datasets were conducted. On the BUSI dataset, our BiU-Net achieved 85.50 % on Dice coefficient (Dice), 76.73 % on intersection over union (IoU), and 97.23 % on accuracy (ACC). Compared to the state-of-the-art method, BiU-Net improves Dice by 1.17 %. For the Monuseg dataset, the proposed method attained the highest scores, reaching 80.27 % and 67.22 % for Dice and IoU. The BiU-Net achieves 95.33 % and 81.22 % Dice on the PH2 and DRIVE datasets. CONCLUSIONS: The results of our experiments showed that BiU-Net transcends existing state-of-the-art methods on four publicly available biomedical datasets. Due to the powerful multi-scale feature extraction ability, our proposed BiU-Net is a versatile medical image segmentation framework for various types of medical images. The source code is released on (https://github.com/ZYLandy/BiU-Net).

Enabling nurses' engagement in the design of healthcare technology - Core competencies and requirements: A qualitative study.

Background: Due to the globally increasing demand for care, innovation is important to maintain quality, safety, effectiveness, patient sensitivity, and outcome orientation. Health care technologies could be a solution to innovate, maintain, or improve the quality of care and simultaneously decrease nurses' workload. Currently, nurses are rarely involved in the design of health care technologies, mostly due to time constraints with clinical nursing responsibilities and limited exposure to technology and design disciplines. To ensure that health care technologies fit into nurses' core and routine practice, nurses should be actively involved in the design process. Objective: The aim of the present study was to explore the main requirements for nurses' active participation in the design of health care technologies. Design: An exploratory descriptive qualitative design was used which helps to both understand and describe a phenomenon. Participants: Twelve nurses from three academic hospitals in the Netherlands participated in this study. Method: Data were collected from semistructured interviews with hospital nurses experienced in design programs and thematically analysed. Results: Four themes were identified concerning the main requirements for nurses to participate in the design of health care technologies: (1) nurses' motivations to participate, (2) the process of technology development, (3) required competence to participate (such as assertiveness, creative thinking, problem solving skills), and (4) facilitating and organizing nurses' participation. Conclusion: Nurses experience their involvement in the design process as essential, distinctive, and meaningful but experience few possibilities to combine this work with their current workload, flows, routines, and requirements. To participate in the design of health care technologies nurses need motivation and specific competencies. Organizations should facilitate time for nurses to acquire the required competencies and to be intentionally involved in technology design and development activities.

Scalable and Ultra-Sensitive Nanofibers Coaxial Yarn-Woven Triboelectric Nanogenerator Textile Sensors for Real-Time Gait Analysis.

Yarn-woven triboelectric nanogenerators (TENGs) have greatly advanced wearable sensor technology, but their limited sensitivity and stability hinder broad adoption. To address these limitations, Poly(VDF-TrFE) and P(olyadiohexylenediamine (PA66)-based nanofibers coaxial yarns (NCYs) combining coaxial conjugated electrospinning and online conductive adhesive coating are developed. The integration of these NCYs led to enhanced TENGs (NCY-TENGs), notable for their flexibility, stretchability, and improved sensitivity, which is ideal for capturing body motion signals. One significant application of this technology is the fabrication of smart insoles from NCY-TENG plain-woven fabrics. These insoles are highly sensitive and possess antibacterial, breathable, and washable properties, making them ideal for real-time gait monitoring in patients with diabetic foot conditions. The NCY-TENGs and their derivatives show immense potential for a variety of wearable electronic devices, representing a considerable advancement in the field of wearable sensors.

Olive leaf extract-derived chitosan-metal nanocomposite: Green synthesis and dual antimicrobial-anticancer action.

In this study, we developed a novel nanocomposite by synthesizing zinc (ZnNPs), copper (CuNPs), and silver (AgNPs) nanoparticles using olive leaf extract and incorporating them into a chitosan polymer. This approach combines the biocompatibility of chitosan with the antimicrobial and anticancer properties of metal nanoparticles, enhanced by the phytochemical richness of olive leaf extract. The significance of our research lies in its potential to offer a biodegradable and stable alternative to conventional antibiotics and cancer treatments, particularly in combating multidrug-resistant bacteria and various cancer types. Comprehensive characterization through Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Analysis (TGA), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray (EDX), and Transmission Electron Microscopy (TEM) confirmed the successful synthesis of the nanocomposites, with an average size of ~22.6 nm. Phytochemical analysis highlighted the antioxidant-rich composition of both the olive leaf extract and the nanoparticles themselves. Functionally, the synthesized nanoparticles exhibited potent antimicrobial activity against multidrug-resistant bacterial strains, outperforming traditional antibiotics by inhibiting key resistance genes (ermC, tetX3-q, blaZ, and Ery-msrA). In anticancer assessments, the nanoparticles showed selective cytotoxicity towards cancer cells in a concentration-dependent manner, with CuNPs and AgNPs showing particularly strong anticancer effects, while demonstrating minimal toxicity towards normal cells. ZnNPs were noted for their low cytotoxicity, highlighting the safety profile of these nanoparticles. Further, the nanoparticles induced apoptosis in cancer cells, as evidenced by the modulation of oncogenes (P21, P53, and BCL2), suggesting their therapeutic potential. The findings of our study underscore the versatile applications of these biogenic nanoparticles in developing safer and more effective antimicrobial and anticancer therapies.

A versatile ratiometric fluorescence nanoprobe for the determination of clonazepam in patients' plasma samples.

Despite the necessity of the study of therapeutic drug monitoring of clonazepam (CLZ), there are only a few fast detection methods available for determining CLZ in biological media. This study aims to develop a cost-effective and ratiometric probe for the quantification of CLZ in plasma samples. Fluorescent polydopamine nanoparticles were produced through a self-polymerization process at a pH of 8.5. Rhodamine B molecules were employed as a fluorescent reference material, emitting stable fluorescence in the visible range. The fabricated probe exhibited a specific detection capability for CLZ. The fluorescence emission of the probe was enhanced in two concentration ranges: from 50 ng/mL to 1.0 µg/mL and from 1.0 to 15.0 µg/mL with a lower limit of quantification of 50 ng/mL, indicating the sensitivity of the probe for detecting CLZ plasma levels. The accuracy of the probe is favorable which could be recommended for CLZ monitoring in the biological media. Furthermore, this probe is highly specific towards CLZ in the presence of various interfering agents which is mainly caused by its ratiometric nature. The developed platform showed high reliability in quantifying CLZ concentrations in patients' plasma samples. Hence, the fabricated probe could be recommended as a reliable method for the routine detection of CLZ in clinical settings.

Ceria nanoparticles: biomedical applications and toxicity. / 二氧化铈纳米颗粒：生物医学应用和毒性.

Ceria nanoparticles (CeO2 NPs) have become popular materials in biomedical and industrial fields due to their potential applications in anti-oxidation, cancer therapy, photocatalytic degradation of pollutants, sensors, etc. Many methods, including gas phase, solid phase, liquid phase, and the newly proposed green synthesis method, have been reported for the synthesis of CeO2 NPs. Due to the wide application of CeO2 NPs, concerns about their adverse impacts on human health have been raised. This review covers recent studies on the biomedical applications of CeO2 NPs, including their use in the treatment of various diseases (e.|g., Alzheimer's disease, ischemic stroke, retinal damage, chronic inflammation, and cancer). CeO2 NP toxicity is discussed in terms of the different systems of the human body (e.|g., cytotoxicity, genotoxicity, respiratory toxicity, neurotoxicity, and hepatotoxicity). This comprehensive review covers both fundamental discoveries and exploratory progress in CeO2 NP research that may lead to practical developments in the future.

Compressed Sensing for Biomedical Photoacoustic Imaging: A Review.

Photoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging. Abnormal biological tissues (such as tumors and inflammation) generate different levels of thermal expansion after absorbing optical energy, producing distinct acoustic signals from normal tissues. This technique can detect small tissue lesions in biological tissues and has demonstrated significant potential for applications in tumor research, melanoma detection, and cardiovascular disease diagnosis. During the process of collecting photoacoustic signals in a PAI system, various factors can influence the signals, such as absorption, scattering, and attenuation in biological tissues. A single ultrasound transducer cannot provide sufficient information to reconstruct high-precision photoacoustic images. To obtain more accurate and clear image reconstruction results, PAI systems typically use a large number of ultrasound transducers to collect multi-channel signals from different angles and positions, thereby acquiring more information about the photoacoustic signals. Therefore, to reconstruct high-quality photoacoustic images, PAI systems require a significant number of measurement signals, which can result in substantial hardware and time costs. Compressed sensing is an algorithm that breaks through the Nyquist sampling theorem and can reconstruct the original signal with a small number of measurement signals. PAI based on compressed sensing has made breakthroughs over the past decade, enabling the reconstruction of low artifacts and high-quality images with a small number of photoacoustic measurement signals, improving time efficiency, and reducing hardware costs. This article provides a detailed introduction to PAI based on compressed sensing, such as the physical transmission model-based compressed sensing method, two-stage reconstruction-based compressed sensing method, and single-pixel camera-based compressed sensing method. Challenges and future perspectives of compressed sensing-based PAI are also discussed.

Smart diabetic foot ulcer scoring system.

Current assessment methods for diabetic foot ulcers (DFUs) lack objectivity and consistency, posing a significant risk to diabetes patients, including the potential for amputations, highlighting the urgent need for improved diagnostic tools and care standards in the field. To address this issue, the objective of this study was to develop and evaluate the Smart Diabetic Foot Ulcer Scoring System, ScoreDFUNet, which incorporates artificial intelligence (AI) and image analysis techniques, aiming to enhance the precision and consistency of diabetic foot ulcer assessment. ScoreDFUNet demonstrates precise categorization of DFU images into "ulcer," "infection," "normal," and "gangrene" areas, achieving a noteworthy accuracy rate of 95.34% on the test set, with elevated levels of precision, recall, and F1 scores. Comparative evaluations with dermatologists affirm that our algorithm consistently surpasses the performance of junior and mid-level dermatologists, closely matching the assessments of senior dermatologists, and rigorous analyses including Bland-Altman plots and significance testing validate the robustness and reliability of our algorithm. This innovative AI system presents a valuable tool for healthcare professionals and can significantly improve the care standards in the field of diabetic foot ulcer assessment.

Svetlana a supervised segmentation classifier for Napari.

We present Svetlana (SuperVised sEgmenTation cLAssifier for NapAri), an open-source Napari plugin dedicated to the manual or automatic classification of segmentation results. A few recent software tools have made it possible to automatically segment complex 2D and 3D objects such as cells in biology with unrivaled performance. However, the subsequent analysis of the results is oftentimes inaccessible to non-specialists. The Svetlana plugin aims at going one step further, by allowing end-users to label the segmented objects and to pick, train and run arbitrary neural network classifiers. The resulting network can then be used for the quantitative analysis of biophysical phenoma. We showcase its performance through challenging problems in 2D and 3D and provide a comprehensive discussion on its strengths and limits.

Antibacterial, Anti-Biofilm, and Anti-Inflammatory Properties of Gelatin-Chitosan-Moringa-Biopolymer-Based Wound Dressings towards Staphylococcus aureus and Escherichia coli.

In contemporary times, the sustained aspiration of bioengineering and biomedical applications is the progressive advancement of materials characterized by biocompatibility and biodegradability. The investigation of the potential applications of polymers as natural and non-hazardous materials has placed significant emphasis on their physicochemical properties. Thus, this study was designed to investigate the potential of gelatin-chitosan-moringa leaf extract (G-CH-M) as a novel biomaterial for biomedical applications. The wound-dressing G-CH-M biopolymer was synthesized and characterized. The blood haemolysis, anti-inflammatory, antioxidant, and antibacterial activities of the biopolymer were investigated against Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacterial isolates. Our results showed that S. aureus swarming motility was drastically affected. However, the biopolymer had no significant effect on the swarming motility of E. coli. In addition, the biopolymer showed high antibacterial capacities, especially against S. aureus. Plasmid DNA was observed to be effectively protected from oxidative stresses by the biopolymer. Furthermore, the biopolymer exhibited greatly suppressed haemolysis (lower than 2%), notwithstanding the elevated concentration of 50 mg/mL. These results indicated that this novel biopolymer formulation could be further developed for wound care and contamination prevention.

Advances in the Optimization of Fe Nanoparticles: Unlocking Antifungal Properties for Biomedical Applications.

In recent years, nanotechnology has achieved a remarkable status in shaping the future of biological applications, especially in combating fungal diseases. Owing to excellence in nanotechnology, iron nanoparticles (Fe NPs) have gained enormous attention in recent years. In this review, we have provided a comprehensive overview of Fe NPs covering key synthesis approaches and underlying working principles, the factors that influence their properties, essential characterization techniques, and the optimization of their antifungal potential. In addition, the diverse kinds of Fe NP delivery platforms that command highly effective release, with fewer toxic effects on patients, are of great significance in the medical field. The issues of biocompatibility, toxicity profiles, and applications of optimized Fe NPs in the field of biomedicine have also been described because these are the most significant factors determining their inclusion in clinical use. Besides this, the difficulties and regulations that exist in the transition from laboratory to experimental clinical studies (toxicity, specific standards, and safety concerns) of Fe NPs-based antifungal agents have been also summarized.

Self-Immolative Domino Dendrimers as Anticancer-Drug Delivery Systems: A Review.

Worldwide cancer statistics have indicated about 20 million new cancer cases and over 10 million deaths in 2022 (according to data from the International Agency for Research on Cancer). One of the leading cancer treatment strategies is chemotherapy, using innovative drug delivery systems (DDSs). Self-immolative domino dendrimers (SIDendr) for triggered anti-cancer drugs appear to be a promising type of DDSs. The present review provides an up-to-date survey on the contemporary advancements in the field of SIDendr-based anti-cancer drug delivery systems (SIDendr-ac-DDSs) through an exhaustive analysis of the discovery and application of these materials in improving the pharmacological effectiveness of both novel and old drugs. In addition, this article discusses the designing, chemical structure, and targeting techniques, as well as the properties, of several SIDendr-based DDSs. Approaches for this type of targeted DDSs for anti-cancer drug release under a range of stimuli are also explored.

A Comparison of Three-Layer and Single-Layer Small Vascular Grafts Manufactured via the Roto-Evaporation Method.

This study used the roto-evaporation technique to engineer a 6 mm three-layer polyurethane vascular graft (TVG) that mimics the architecture of human coronary artery native vessels. Two segmented polyurethanes were synthesized using lysine (SPUUK) and ascorbic acid (SPUAA), and the resulting materials were used to create the intima and adventitia layers, respectively. In contrast, the media layer of the TVG was composed of a commercially available polyurethane, Pearlbond 703 EXP. For comparison purposes, single-layer vascular grafts (SVGs) from individual polyurethanes and a polyurethane blend (MVG) were made and tested similarly and evaluated according to the ISO 7198 standard. The TVG exhibited the highest circumferential tensile strength and longitudinal forces compared to single-layer vascular grafts of lower thicknesses made from the same polyurethanes. The TVG also showed higher suture and burst strength values than native vessels. The TVG withstood up to 2087 ± 139 mmHg and exhibited a compliance of 0.15 ± 0.1%/100 mmHg, while SPUUK SVGs showed a compliance of 5.21 ± 1.29%/100 mmHg, akin to coronary arteries but superior to the saphenous vein. An indirect cytocompatibility test using the MDA-MB-231 cell line showed 90 to 100% viability for all polyurethanes, surpassing the minimum 70% threshold needed for biomaterials deemed cytocompatibility. Despite the non-cytotoxic nature of the polyurethane extracts when grown directly on the surface, they displayed poor fibroblast adhesion, except for SPUUK. All vascular grafts showed hemolysis values under the permissible limit of 5% and longer coagulation times.

Chitosan-2D Nanomaterial-Based Scaffolds for Biomedical Applications.

Chitosan (CS) and two-dimensional nanomaterial (2D nanomaterials)-based scaffolds have received widespread attention in recent times in biomedical applications due to their excellent synergistic potential. CS has garnered much attention as a biomedical scaffold material either alone or in combination with some other material due to its favorable physiochemical properties. The emerging 2D nanomaterials, such as black phosphorus (BP), molybdenum disulfide (MoS2), etc., have taken huge steps towards varying biomedical applications. However, the implementation of a CS-2D nanomaterial-based scaffold for clinical applications remains challenging for different reasons such as toxicity, stability, etc. Here, we reviewed different types of CS scaffold materials and discussed their advantages in biomedical applications. In addition, a different CS nanostructure, instead of a scaffold, has been described. After that, the importance of 2D nanomaterials has been elaborated on in terms of physiochemical properties. In the next section, the biomedical applications of CS with different 2D nanomaterial scaffolds have been highlighted. Finally, we highlighted the existing challenges and future perspectives of using CS-2D nanomaterial scaffolds for biomedical applications. We hope that this review will encourage a more synergistic biomedical application of the CS-2D nanomaterial scaffolds and their utilization clinical applications.

Bio(sensors) based on molecularly imprinted polymers and silica materials used for food safety and biomedical analysis: Recent trends and future prospects.

In recent decades, analytical techniques have increasingly focused on the precise quantification. Achieving this goal has been accomplished with conventional analytical approaches that typically require extensive pretreatment methods, significant reagent usage, and expensive instruments. The need for rapid, simple, and highly selective identification platforms has become increasingly pronounced. Molecularly imprinted polymer (MIP) has emerged as a promising avenue for developing advanced sensors that can potentially surpass the limitations of conventional detection methods. In recent years, the application of MIP-silica materials-based sensors has garnered significant attention owing to their distinctive characteristics. These types of probes hold a distinct advantage in their remarkable stability and durability, all of which provide a suitable sensing platform in severe environments. Moreover, the substrate composed of silica materials offers a vast surface area for binding, thereby facilitating the efficient detection of even minuscule concentrations of targets. As a result, sensors based on MIP-silica materials have the potential to be widely applied in various industries, including medical diagnosis, and food safety. In the present review, we have conducted an in-depth analysis of the latest research developments in the field of MIPs-silica materials based sensors, with a focus on succinctly summarizing and elucidating the most crucial findings. This is the first comprehensive review of integration MIPs with silica materials in electrochemical (EC) and optical probes for biomedical analysis and food safety.

Bibliometric study of the advances made in clinical dermatological research in Spain from 2015 through 2021: update of the MaIND project and interactive online map. / Estudio bibliométrico sobre la evolución de la investigación clínica dermatológica española entre 2015 y 2021: actualización del proyecto MaIND y mapa interactivo en línea.

INTRODUCTION: A clinical dermatological research was conducted in Spain from 2005 through 2014 as part of the MaIND project with the provinces or centers with the highest number of published articles. However, a low level of evidence in scientific production was confirmed as the overall result. The aim of this study is to update the Spanish clinical dermatological research in bibliometric terms from 2015 through 2021 with comparisons between both periods of time. MATERIAL AND METHODS: We conducted a bibliometric study to replicate the methodology used in the article to be updated. We included articles whose corresponding authors' affiliation was a Spanish dermatological center, which met the criteria for clinical research in dermatology, including a level of evidence ≤ 4. RESULTS: A total of 1674 out of the 10199 articles met the inclusion criteria. An interactive map representing quantitative and qualitative indicators calculated for the 2005-2021 is presented here. In the study period, we found an increasing trend both in the number of published articles (p < 0.002) and in the mean number of citation-years per article (p < 0.01). A total of 22 of the articles had a level of evidence > 4, with a positive trend towards more articles having a higher level of evidence (p < 0.03). Actas Dermosifilográficas still maintains its position as the journal with the highest number of articles received (18%, a total of 302 articles). CONCLUSIONS: The results of this study show that, in Spain, the scientific production of dermatology represents an upward trend in quantity, impact, and level of evidence.

Advances in enhancing the mechanical properties of hydrogels through multi-strategic approaches based on biopolymer platforms.

The limited mechanical properties of biopolymer-based hydrogels have hindered their widespread applications in biomedicine and tissue engineering. In recent years, researchers have shown significant interest in developing novel approaches to enhance the mechanical performance of hydrogels. This review focuses on key strategies for enhancing mechanical properties of hydrogels, including dual-crosslinking, double networks, and nanocomposite hydrogels, with a comprehensive analysis of their underlying mechanisms, benefits, and limitations. It also introduces the classic application scenarios of biopolymer-based hydrogels and the direction of future research efforts, including wound dressings and tissue engineering based on 3D bioprinting. This review is expected to deepen the understanding of the structure-mechanical performance-function relationship of hydrogels and guide the further study of their biomedical applications.

Feasibility of continuous non-invasive delivery of oxygen monitoring in cardiac surgical patients: a proof-of-concept preliminary study.

PURPOSE: Oxygen delivery (DO2) and its monitoring are highlighted to aid postoperative goal directed therapy (GDT) to improve perioperative outcomes such as acute kidney injury (AKI) after high-risk cardiac surgeries associated with multiple morbidities and mortality. However, DO2 monitoring is neither routine nor done postoperatively, and current methods are invasive and only produce intermittent DO2 trends. Hence, we proposed a novel algorithm that simultaneously integrates cardiac output (CO), hemoglobin (Hb) and oxygen saturation (SpO2) from the Edwards Life Sciences ClearSight System® and Masimo SET Pulse CO-Oximetry® to produce a continuous, real-time DO2 trend. METHODS: Our algorithm was built systematically with 4 components - machine interface to draw data with PuTTY, data extraction with parsing, data synchronization, and real-time DO2 presentation using a graphic-user interface. Hb readings were validated. RESULTS: Our algorithm was implemented successfully in 93% (n = 57 out of 61) of our recruited cardiac surgical patients. DO2 trends and AKI were studied. CONCLUSION: We demonstrated a novel proof-of-concept and feasibility of continuous, real-time, non-invasive DO2 monitoring, with each patient serving as their own control. Our study also lays the foundation for future investigations aimed at identifying personalized critical DO2 thresholds and optimizing DO2 as an integral part of GDT to enhance outcomes in perioperative cardiac surgery.

Effects of buoyancy on the dispersion of drugs released intrathecally in the spinal canal.

This paper investigates the transport of drugs delivered by direct injection into the cerebrospinal fluid (CSF) that fills the intrathecal space surrounding the spinal cord. Because of the small drug diffusivity, the dispersion of neutrally buoyant drugs has been shown in previous work to rely mainly on the mean Lagrangian flow associated with the CSF oscillatory motion. Attention is given here to effects of buoyancy, arising when the drug density differs from the CSF density. For the typical density differences found in applications, the associated Richardson number is shown to be of order unity, so that the Lagrangian drift includes a buoyancy-induced component that depends on the spatial distribution of the drug, resulting in a slowly evolving cycle-averaged flow problem that can be analysed with two-time scale methods. The asymptotic analysis leads to a nonlinear integro-differential equation for the spatiotemporal solute evolution that describes accurately drug dispersion at a fraction of the cost involved in direct numerical simulations of the oscillatory flow. The model equation is used to predict drug dispersion of positively and negatively buoyant drugs in an anatomically correct spinal canal, with separate attention given to drug delivery via bolus injection and constant infusion.