Fillable Magnetic Microrobots for Drug Delivery to Cardiac Tissues in Vitro.

Many cardiac diseases, such as arrhythmia or cardiogenic shock, cause irregular beating patterns that must be regulated to prevent disease progression towards heart failure. Treatments can include invasive surgery or high systemic drug dosages, which lack precision, localization, and control. Drug delivery systems (DDSs) that can deliver cargo to the cardiac injury site could address these unmet clinical challenges. Here, we present a microrobotic DDS that can be mobilized to specific sites via magnetic control. Our DDS incorporates an internal chamber that can protect drug cargo. Furthermore, the DDS contains a tunable thermosensitive sealing layer that gradually degrades upon exposure to body temperature, enabling prolonged drug release. Once loaded with the small molecule drug norepinephrine, our microrobotic DDS modulated beating frequency in induced pluripotent stem-cell derived cardiomyocytes (iPSC-CMs) in a dose-dependent manner, thus simulating drug delivery to cardiac cells in vitro. The DDS also navigated several maze-like structures seeded with cardiomyocytes to demonstrate precise locomotion under a rotating low-intensity magnetic field and on-site drug delivery. This work demonstrates the utility of a magnetically actuating DDS for precise, localized, and controlled drug delivery which is of interest for a myriad of future opportunities such as in treating cardiac diseases. This article is protected by copyright. All rights reserved.

RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis.

Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.

Thermally Robust Solvent-Free Liquid Polyplexes for Heat-Shock Protection and Long-Term Room Temperature Storage of Therapeutic Nucleic Acids.

Nucleic acid therapeutics have attracted recent attention as promising preventative solutions for a broad range of diseases. Nonviral delivery vectors, such as cationic polymers, improve the cellular uptake of nucleic acids without suffering the drawbacks of viral delivery vectors. However, these delivery systems are faced with a major challenge for worldwide deployment, as their poor thermal stability elicits the need for cold chain transportation. Here, we demonstrate a biomaterial strategy to drastically improve the thermal stability of DNA polyplexes. Importantly, we demonstrate long-term room temperature storage with a transfection efficiency maintained for at least 9 months. Additionally, extreme heat shock studies show retained luciferase expression after heat treatment at 70 °C. We therefore provide a proof of concept for a platform biotechnology that could provide long-term room temperature storage for temperature-sensitive nucleic acid therapeutics, eliminating the need for the cold chain, which in turn would reduce the cost of distributing life-saving therapeutics worldwide.

Microneedle-mediated nanomedicine to enhance therapeutic and diagnostic efficacy.

Nanomedicine has been extensively explored for therapeutic and diagnostic applications in recent years, owing to its numerous advantages such as controlled release, targeted delivery, and efficient protection of encapsulated agents. Integration of microneedle technologies with nanomedicine has the potential to address current limitations in nanomedicine for drug delivery including relatively low therapeutic efficacy and poor patient compliance and enable theragnostic uses. In this Review, we first summarize representative types of nanomedicine and describe their broad applications. We then outline the current challenges faced by nanomedicine, with a focus on issues related to physical barriers, biological barriers, and patient compliance. Next, we provide an overview of microneedle systems, including their definition, manufacturing strategies, drug release mechanisms, and current advantages and challenges. We also discuss the use of microneedle-mediated nanomedicine systems for therapeutic and diagnostic applications. Finally, we provide a perspective on the current status and future prospects for microneedle-mediated nanomedicine for biomedical applications.

3,4-Ethylenedioxythiophene Hydrogels: Relating Structure and Charge Transport in Supramolecular Gels.

Ionic charge transport is a ubiquitous language of communication in biological systems. As such, bioengineering is in constant need of innovative, soft, and biocompatible materials that facilitate ionic conduction. Low molecular weight gelators (LMWGs) are complex self-assembled materials that have received increasing attention in recent years. Beyond their biocompatible, self-healing, and stimuli responsive facets, LMWGs can be viewed as a "solid" electrolyte solution. In this work, we investigate 3,4-ethylenedioxythiophene (EDOT) as a capping group for a small peptide library, which we use as a system to understand the relationship between modes of assembly and charge transport in supramolecular gels. Through a combination of techniques including small-angle neutron scattering (SANS), NMR-based Van't Hoff analysis, atomic force microscopy (AFM), rheology, four-point probe, and electrochemical impedance spectroscopy (EIS), we found that modifications to the peptide sequence result in distinct assembly pathways, thermodynamic parameters, mechanical properties, and ionic conductivities. Four-point probe conductivity measurements and electrochemical impedance spectroscopy suggest that ionic conductivity is approximately doubled by programmable gel assemblies with hollow cylinder morphologies relative to gels containing solid fibers or a control electrolyte. More broadly, it is hoped this work will serve as a platform for those working on charge transport of aqueous soft materials in general.

Physical-property-based patterning: simply engineering complex tissues.

The field of biofabrication is rapidly expanding with the advent of new technologies and material systems to engineer complex tissues. In this opinion article, we introduce an emerging tissue patterning method, physical-property-based patterning, that has strong translational potential given its simplicity and limited dependence on external hardware. Physical-property-based patterning relies solely on the intrinsic density, magnetic susceptibility, or compressibility of an object, its surrounding solution, and the noncontact application of a remote field. We discuss how physical properties can be exploited to pattern objects and design a variety of biologic tissues. Finally, we pose several open questions that, if addressed, could transform the status quo of biofabrication, pushing us one step closer to patterning tissues in situ.

Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic Assays.

With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive, lab experiments are necessary for their optimization. This paper presents a transfer learning design of experiments workflow to make this development feasible. By combining a transfer learning surrogate model with Bayesian optimization, we show how the total number of experiments can be reduced by sharing information between optimization tasks. We demonstrate the reduction in the number of experiments using data from the development of DNA competitors for use in an amplification-based diagnostic assay. We use cross-validation to compare the predictive accuracy of different transfer learning models, and then compare the performance of the models for both single objective and penalized optimization tasks.

Extracellular vesicles as a promising source of lipid biomarkers for breast cancer detection in blood plasma.

Extracellular vesicles (EVs), including exosomes and microvesicles, mediate intercellular communication in cancer, from development to metastasis. EV-based liquid biopsy is a promising strategy for cancer diagnosis as EVs can be found in cancer patients' body fluids. In this study, the lipid composition of breast cancer-derived EVs was studied as well as the potential of blood plasma EVs for the identification of lipid biomarkers for breast cancer detection. Initially, an untargeted lipidomic analysis was carried out for a panel of cancerous and non-cancerous mammary epithelial cells and their secreted EVs. We found that breast cancer-derived EVs are enriched in sphingolipids and glycerophospholipids compared to their parental cells. The initial in vitro study showed that EVs and their parental cells can be correctly classified (100% accuracy) between cancerous and non-cancerous, as well as into their respective breast cancer subtypes, based on their lipid composition. Subsequently, an untargeted lipidomic analysis was carried out for blood plasma EVs from women diagnosed with breast cancer (primary or progressive metastatic breast cancer) as well as healthy women. Correspondingly, when blood plasma EVs were analysed, breast cancer patients and healthy women were correctly classified with an overall accuracy of 93.1%, based on the EVs' lipid composition. Similarly, the analysis of patients with primary breast cancer and healthy women showed an overall accuracy of 95% for their correct classification. Furthermore, primary and metastatic breast cancers were correctly classified with an overall accuracy of 89.5%. This reveals that the blood plasma EVs' lipids may be a promising source of biomarkers for detection of breast cancer. Additionally, this study demonstrates the usefulness of untargeted lipidomics in the study of EV lipid composition and EV-associated biomarker discovery studies. This is a proof-of-concept study and a starting point for further analysis on the identification of EV-based biomarkers for breast cancer.

Strain-Promoted Cycloadditions in Lipid Bilayers Triggered by Liposome Fusion.

Due to the variety of roles served by the cell membrane, its composition and structure are complex, making it difficult to study. Bioorthogonal reactions, such as the strain promoted azide-alkyne cycloaddition (SPAAC), are powerful tools for exploring the function of biomolecules in their native environment but have been largely unexplored within the context of lipid bilayers. Here, we developed a new approach to study the SPAAC reaction in liposomal membranes using azide- and strained alkyne-functionalized Förster resonance energy transfer (FRET) dye pairs. This study represents the first characterization of the SPAAC reaction between diffusing molecules inside liposomal membranes. Potential applications of this work include in situ bioorthogonal labeling of membrane proteins, improved understanding of membrane dynamics and fluidity, and the generation of new probes for biosensing assays.

Printed smart devices for anti-counterfeiting allowing precise identification with household equipment.

Counterfeiting has become a serious global problem, causing worldwide losses and disrupting the normal order of society. Physical unclonable functions are promising hardware-based cryptographic primitives, especially those generated by chemical processes showing a massive challenge-response pair space. However, current chemical-based physical unclonable function devices typically require complex fabrication processes or sophisticated characterization methods with only binary (bit) keys, limiting their practical applications and security properties. Here, we report a flexible laser printing method to synthesize unclonable electronics with high randomness, uniqueness, and repeatability. Hexadecimal resistive keys and binary optical keys can be obtained by the challenge with an ohmmeter and an optical microscope. These readout methods not only make the identification process available to general end users without professional expertise, but also guarantee device complexity and data capacity. An adopted open-source deep learning model guarantees precise identification with high reliability. The electrodes and connection wires are directly printed during laser writing, which allows electronics with different structures to be realized through free design. Meanwhile, the electronics exhibit excellent mechanical and thermal stability. The high physical unclonable function performance and the widely accessible readout methods, together with the flexibility and stability, make this synthesis strategy extremely attractive for practical applications.

Magnetically driven formation of 3D freestanding soft bioscaffolds.

3D soft bioscaffolds have great promise in tissue engineering, biohybrid robotics, and organ-on-a-chip engineering applications. Though emerging three-dimensional (3D) printing techniques offer versatility for assembling soft biomaterials, challenges persist in overcoming the deformation or collapse of delicate 3D structures during fabrication, especially for overhanging or thin features. This study introduces a magnet-assisted fabrication strategy that uses a magnetic field to trigger shape morphing and provide remote temporary support, enabling the straightforward creation of soft bioscaffolds with overhangs and thin-walled structures in 3D. We demonstrate the versatility and effectiveness of our strategy through the fabrication of bioscaffolds that replicate the complex 3D topology of branching vascular systems. Furthermore, we engineered hydrogel-based bioscaffolds to support biohybrid soft actuators capable of walking motion triggered by cardiomyocytes. This approach opens new possibilities for shaping hydrogel materials into complex 3D morphologies, which will further empower a broad range of biomedical applications.

4D Multimaterial Printing of Soft Actuators with Spatial and Temporal Control.

Soft actuators (SAs) are devices which can interact with delicate objects in a manner not achievable with traditional robotics. While it is possible to design a SA whose actuation is triggered via an external stimulus, the use of a single stimulus creates challenges in the spatial and temporal control of the actuation. Herein, a 4D printed multimaterial soft actuator design (MMSA) whose actuation is only initiated by a combination of triggers (i.e., pH and temperature) is presented. Using 3D printing, a multilayered soft actuator with a hydrophilic pH-sensitive layer, and a hydrophobic magnetic and temperature-responsive shape-memory polymer layer, is designed. The hydrogel responds to environmental pH conditions by swelling or shrinking, while the shape-memory polymer can resist the shape deformation of the hydrogel until triggered by temperature or light. The combination of these stimuli-responsive layers allows for a high level of spatiotemporal control of the actuation. The utility of the 4D MMSA is demonstrated via a series of cargo capture and release experiments, validating its ability to demonstrate active spatiotemporal control. The MMSA concept provides a promising research direction to develop multifunctional soft devices with potential applications in biomedical engineering and environmental engineering.

Enhanced Antimalarial and Antisequestration Activity of Methoxybenzenesulfonate-Modified Biopolymers and Nanoparticles for Tackling Severe Malaria.

Severe malaria is a life-threatening condition that is associated with a high mortality. Severe Plasmodium falciparum infections are mediated primarily by high parasitemia and binding of infected red blood cells (iRBCs) to the blood vessel endothelial layer, a process known as sequestration. Here, we show that including the 5-amino-2-methoxybenzenesulfonate (AMBS) chemical modification in soluble biopolymers (polyglutamic acid and heparin) and poly(acrylic acid)-exposing nanoparticles serves as a universal tool to introduce a potent parasite invasion inhibitory function in these materials. Importantly, the modification did not add or eliminated (for heparin) undesired anticoagulation activity. The materials protected RBCs from invasion by various parasite strains, employing both major entry pathways. Two further P. falciparum strains, which either expose ligands for chondroitin sulfate A (CSA) or intercellular adhesion molecule 1 (ICAM-1) on iRBCs, were tested in antisequestration assays due to their relevance in placental and cerebral malaria, respectively. Antisequestration activity was found to be more efficacious with nanoparticles vs gold-standard soluble biopolymers (CSA and heparin) against both strains, when tested on receptor-coated dishes. The nanoparticles also efficiently inhibited and reversed the sequestration of iRBCs on endothelial cells. First, the materials described herein have the potential to reduce the parasite burden by acting at the key multiplication stage of reinvasion. Second, the antisequestration ability could help remove iRBCs from the blood vessel endothelium, which could otherwise cause vessel obstruction, which in turn can lead to multiple organ failure in severe malaria infections. This approach represents a further step toward creation of adjunctive therapies for this devastating condition to reduce morbidity and mortality.

The Nanozyme Revolution: Enhancing the Performance of Medical Biosensing Platforms.

Nanozymes represent a class of nanosized materials that exhibit innate catalytic properties similar to biological enzymes. The unique features of these materials have positioned them as promising candidates for applications in clinical sensing devices, specifically those employed at the point-of-care. They notably have found use as a means to amplify signals in nanosensor-based platforms and thereby improve sensor detection limits. Recent developments in the understanding of the fundamental chemistries underpinning these materials have enabled the development of highly effective nanozymes capable of sensing clinically relevant biomarkers at detection limits that compete with "gold-standard" techniques. However, there remain considerable hurdles that need to be overcome before these nanozyme-based sensors can be utilized in a platform ready for clinical use. An overview of the current understandings of nanozymes for disease diagnostics and biosensing applications and the unmet challenges that must be considered prior to their translation in clinical diagnostic tests is provided.

High-throughput measurement of the content and properties of nano-sized bioparticles with single-particle profiler.

We introduce a method, single-particle profiler, that provides single-particle information on the content and biophysical properties of thousands of particles in the size range 5-200 nm. We use our single-particle profiler to measure the messenger RNA encapsulation efficiency of lipid nanoparticles, the viral binding efficiencies of different nanobodies, and the biophysical heterogeneity of liposomes, lipoproteins, exosomes and viruses.

Use of pyridazinediones for tuneable and reversible covalent cysteine modification applied to peptides, proteins and hydrogels.

Reversible cysteine modification has been found to be a useful tool for a plethora of applications such as selective enzymatic inhibition, activity-based protein profiling and/or cargo release from a protein or a material. However, only a limited number of reagents display reliable dynamic/reversible thiol modification and, in most cases, many of these reagents suffer from issues of stability, a lack of modularity and/or poor rate tunability. In this work, we demonstrate the potential of pyridazinediones as novel reversible and tuneable covalent cysteine modifiers. We show that the electrophilicity of pyridazinediones correlates to the rates of the Michael addition and retro-Michael deconjugation reactions, demonstrating that pyridazinediones provide an enticing platform for readily tuneable and reversible thiol addition/release. We explore the regioselectivity of the novel reaction and unveil the reason for the fundamental increased reactivity of aryl bearing pyridazinediones by using DFT calculations and corroborating findings with SCXRD. We also applied this fundamental discovery to making more rapid disulfide rebridging agents in related work. We finally provide the groundwork for potential applications in various areas with exemplification using readily functionalised "clickable" pyridazinediones on clinically relevant cysteine and disulfide conjugated proteins, as well as on a hydrogel material.

In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain-striatum-cortex assembloids.

Ventral midbrain dopaminergic neurons project to the striatum as well as the cortex and are involved in movement control and reward-related cognition. In Parkinson's disease, nigrostriatal midbrain dopaminergic neurons degenerate and cause typical Parkinson's disease motor-related impairments, while the dysfunction of mesocorticolimbic midbrain dopaminergic neurons is implicated in addiction and neuropsychiatric disorders. Study of the development and selective neurodegeneration of the human dopaminergic system, however, has been limited due to the lack of an appropriate model and access to human material. Here, we have developed a human in vitro model that recapitulates key aspects of dopaminergic innervation of the striatum and cortex. These spatially arranged ventral midbrain-striatum-cortical organoids (MISCOs) can be used to study dopaminergic neuron maturation, innervation and function with implications for cell therapy and addiction research. We detail protocols for growing ventral midbrain, striatal and cortical organoids and describe how they fuse in a linear manner when placed in custom embedding molds. We report the formation of functional long-range dopaminergic connections to striatal and cortical tissues in MISCOs, and show that injected, ventral midbrain-patterned progenitors can mature and innervate the tissue. Using these assembloids, we examine dopaminergic circuit perturbations and show that chronic cocaine treatment causes long-lasting morphological, functional and transcriptional changes that persist upon drug withdrawal. Thus, our method opens new avenues to investigate human dopaminergic cell transplantation and circuitry reconstruction as well as the effect of drugs on the human dopaminergic system.

Metal-free photoanodes for C-H functionalization.

Organic semiconductors, such as carbon nitride, when employed as powders, show attractive photocatalytic properties, but their photoelectrochemical performance suffers from low charge transport capability, charge carrier recombination, and self-oxidation. High film-substrate affinity and well-designed heterojunction structures may address these issues, achieved through advanced film generation techniques. Here, we introduce a spin coating pretreatment of a conductive substrate with a multipurpose polymer and a supramolecular precursor, followed by chemical vapor deposition for the synthesis of dual-layer carbon nitride photoelectrodes. These photoelectrodes are composed of a porous microtubular top layer and an interlayer between the porous film and the conductive substrate. The polymer improves the polymerization degree of carbon nitride and introduces C-C bonds to increase its electrical conductivity. These carbon nitride photoelectrodes exhibit state-of-the-art photoelectrochemical performance and achieve high yield in C-H functionalization. This carbon nitride photoelectrode synthesis strategy may be readily adapted to other reported processes to optimize their performance.

Single Particle Chemical Characterisation of Nanoformulations for Cargo Delivery.

Nanoparticles can encapsulate a range of therapeutics, from small molecule drugs to sensitive biologics, to significantly improve their biodistribution and biostability. Whilst the regulatory approval of several of these nanoformulations has proven their translatability, there remain several hurdles to the translation of future nanoformulations, leading to a high rate of candidate nanoformulations failing during the drug development process. One barrier is that the difficulty in tightly controlling nanoscale particle synthesis leads to particle-to-particle heterogeneity, which hinders manufacturing and quality control, and regulatory quality checks. To understand and mitigate this heterogeneity requires advancements in nanoformulation characterisation beyond traditional bulk methods to more precise, single particle techniques. In this review, we compare commercially available single particle techniques, with a particular focus on single particle Raman spectroscopy, to provide a guide to adoption of these methods into development workflows, to ultimately reduce barriers to the translation of future nanoformulations.

Quantifying internal intervertebral disc strains to assess nucleus replacement device designs: a digital volume correlation and ultra-high-resolution MRI study.

Introduction: Nucleus replacement has been proposed as a treatment to restore biomechanics and relieve pain in degenerate intervertebral discs (IVDs). Multiple nucleus replacement devices (NRDs) have been developed, however, none are currently used routinely in clinic. A better understanding of the interactions between NRDs and surrounding tissues may provide insight into the causes of implant failure and provide target properties for future NRD designs. The aim of this study was to non-invasively quantify 3D strains within the IVD through three stages of nucleus replacement surgery: intact, post-nuclectomy, and post-treatment. Methods: Digital volume correlation (DVC) combined with 9.4T MRI was used to measure strains in seven human cadaveric specimens (42 ± 18 years) when axially compressed to 1 kN. Nucleus material was removed from each specimen creating a cavity that was filled with a hydrogel-based NRD. Results: Nucleus removal led to loss of disc height (12.6 ± 4.4%, p = 0.004) which was restored post-treatment (within 5.3 ± 3.1% of the intact state, p > 0.05). Nuclectomy led to increased circumferential strains in the lateral annulus region compared to the intact state (-4.0 ± 3.4% vs. 1.7 ± 6.0%, p = 0.013), and increased maximum shear strains in the posterior annulus region (14.6 ± 1.7% vs. 19.4 ± 2.6%, p = 0.021). In both cases, the NRD was able to restore these strain values to their intact levels (p ≥ 0.192). Discussion: The ability of the NRD to restore IVD biomechanics and some strain types to intact state levels supports nucleus replacement surgery as a viable treatment option. The DVC-MRI method used in the present study could serve as a useful tool to assess future NRD designs to help improve performance in future clinical trials.