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Polydimethylsiloxane (PDMS) has become a popular material in microfluidic and macroscale in vitro models due to its elastomeric properties and versatility. PDMS-based biomodels are widely used in blood flow studies, offering a platform for improving flow models and validating numerical simulations. This review highlights recent advances in bioflow studies conducted using both PDMS microfluidic devices and macroscale biomodels, particularly in replicating physiological environments. PDMS microchannels are used in studies of blood cell deformation under confined conditions, demonstrating the potential to distinguish between healthy and diseased cells. PDMS also plays a critical role in fabricating arterial models from real medical images, including pathological conditions such as aneurysms. Cutting-edge applications, such as nanofluid hemodynamic studies and nanoparticle drug delivery in organ-on-a-chip platforms, represent the latest developments in PDMS research. In addition to these applications, this review critically discusses PDMS properties, fabrication methods, and its expanding role in micro- and nanoscale flow studies. [ABSTRACT FROM AUTHOR]

Purpose: We aim to investigate the integration of augmented reality (AR) within the context of increasingly complex surgical procedures and instrument handling toward the transition to smart operating rooms (OR). In contrast to cumbersome paper-based surgical instrument manuals still used in the OR, we wish to provide surgical staff with an AR head-mounted display that provides in-situ visualization and guidance throughout the assembly process of surgical instruments. Our requirement analysis supports the development and provides guidelines for its transfer into surgical practice. Methods: A three-phase user-centered design approach was applied with online interviews, an observational study, and a workshop with two focus groups with scrub nurses, circulating nurses, surgeons, manufacturers, clinic IT staff, and members of the sterilization department. The requirement analysis was based on key criteria for usability. The data were analyzed via structured content analysis. Results: We identified twelve main problems with the current use of paper manuals. Major issues included sterile users' inability to directly handle non-sterile manuals, missing details, and excessive text information, potentially delaying procedure performance. Major requirements for AR-driven guidance fall into the categories of design, practicability, control, and integration into the current workflow. Additionally, further recommendations for technical development could be obtained. Conclusion: In conclusion, our insights have outlined a comprehensive spectrum of requirements that are essential for the successful implementation of an AI- and AR-driven guidance for assembling surgical instruments. The consistently appreciative evaluation by stakeholders underscores the profound potential of AR and AI technology as valuable assistance and guidance. [ABSTRACT FROM AUTHOR]

Efficient and reliable storage, analysis, and transmission of medical images are imperative for accurate diagnosis, treatment, and management of various diseases. Since quantum computing can revolutionize big data analytics by providing faster solutions and security tactics, numerous studies in this field have focused on the use of quantum and quantum-inspired algorithms to enhance the performance of traditional medical image processing approaches. This review aims to provide readers with a succinct yet adequate compendium of the advances in medical image processing combined with quantum behaviors for disease diagnosis and medical image security. Some open challenges are outlined, identifying the performance limitations of current quantum technology in their applications, while addressing the short-, medium-, and long-term development plans of this field in designing future quantum healthcare systems. We hope that this review will provide full guidance for upcoming researchers interested in this area and will stimulate further appetite of experts already active in this area aimed at the pursuit of more advanced quantum paradigms in medical image processing applications. [ABSTRACT FROM AUTHOR]

To enable interactive remote education on electrical safety in biomedical engineering, a real-life problem-based laboratory module is proposed, implemented and evaluated. The laboratory module was implemented in a freestanding distance course in hospital safety for three consecutive years and was based on electrical safety for medical devices, where standard equipment existing in most hospitals could be used. The course participants were from a total of 42 geographical locations in or near Sweden. To allow a high level of interaction, especially among peer students, a graphical digital platform (Gather Town) was used. The digital platform was additionally used in two group work sessions. The experience of the participants in terms of usefulness and satisfaction was rated on a range of [-2, 2] using a van der Laan 5-point Likert-based acceptance scale questionnaire. The laboratory module overall was scored 4.1/5 by the participants (n = 29) in the final course assessments. The evaluation of the digital platform alone showed that in the first usage instance, the participants (n = 21) found the platform to be useful (0.54 ± 0.67) and satisfactory (0.37 ± 0.60). The participants' experience of the digital platform improved when comparing two identical group work assignments so that ratings of usefulness and satisfaction were 1.11 ± 0.59 and 1 ± 0.71, respectively, after they had used it in the second group work session (n = 38). This study provides an instance of an interactive remote electrical safety laboratory module that is envisioned to contribute to further implementations of sustainable education in biomedical engineering. [ABSTRACT FROM AUTHOR]

Advances in additive manufacturing technologies have enabled the fabrication of intricate bioscaffolds with tailored geometry, porosity, and material composition, offering new possibilities in biomedical engineering, drug screening, and cell scaffold applications. This study introduces a novel printable flexible soft ceramic material prepared by a combination of silica sol–gel processing and crosslinking of a dissolvable polyvinyl‐trimesic acid polymeric network. The material's printability is showcased by creating 3D 90° grid scaffolds using an in‐house extrusion‐based printer, demonstrating a flexible response to compressive stress with minimal deformation over multiple cycles. Supercritical extraction and drying transform the printed structure into a highly porous, ultralow‐density scaffold for cell culture. The MDCK cells cultured within the 3D biocompatible ceramic scaffold exhibit uniform growth and proliferation, maintaining viability for up to 35 days. When exposed to the environmental toxin, mercury, MDCK cells in a 2D culture show susceptibility at a low lethal concentration (0.075 mg·L−1), while the 3D cell culture displays enhanced tolerance (4.0 mg·L−1). It emphasizes the significance of the 3D microenvironment in mimicking physiological conditions more accurately, enabling a more precise assessment of environmental toxicants. [ABSTRACT FROM AUTHOR]

BACKGROUND: Bioactive glass is a multifunctional synthetic composite material that releases active ions slowly and exhibits certain biological activities after affinity with tissues. Their versatility stems from the versatility of their preparation processes and components, allowing them to be applied in different clinical scenarios. OBJECTIVE: To review the main application forms, application fields of bioactive glass, as well as the influence of doping different elements on its function. METHODS: A literature search was conducted across WanFang Medical Database, CNKI Database, PubMed Database, and Web of Science Database, using the search terms “bioactive glass, slow-release ions, bone tissue engineering, composite scaffold, tissue regeneration and repair, biomedical engineering” in Chinese and English. The timeframe was limited from 2000 to 2023. Finally, 88 articles were included for review. RESULTS AND CONCLUSION: (1) In terms of application forms, bioactive glass can be fabricated as coatings, particles, bone cements, and scaffolds according to needs. Coatings have the potential to enhance the biological activity of implants, yet they are susceptible to instability as a result of degradation. Particles offer a viable solution for the repair of irregular bone defects; however, particles produced through traditional methods often possess limited functionality. Bone cement provides the benefits of minimal invasiveness and injectability, yet its application is restricted to smaller bone defects. Scaffolds exhibit excellent mechanical properties and are commonly used for larger-sized bone defects, yet they have limited toughness. (2) In terms of applications, bioactive glass can be used in a variety of tissue regeneration and repair and disease treatment fields, including dentistry, orthopedics, soft tissue engineering, and cancer. (3) In terms of element doping, the addition of specific elements to bioactive glass not only improves its mechanical properties but also endows it with special biological functions such as bioactivity, degradability, and antibacterial properties. (4) Biologically active glass is a versatile material that can be used in different forms and functions by adjusting the preparation process and element doping to meet various clinical needs in bone tissue engineering and is widely used in the field of biomedical engineering. [ABSTRACT FROM AUTHOR]

To an individual, pain is unambiguously real. To a caregiver, assessing pain in others is a challenging process shrouded in doubt. To explain this challenge, many assume that pain "belongs" exclusively to the bearer of that experience and accept the dogma that pain is private. However, privacy also entails that it is not possible to identify, share, or communicate that experience with others. Obviously, this is not true and the consequences of pain privacy would be devastating for healthcare. Pain is indeed unique and subjective, but not necessarily private. Pain is in fact readily communicable, though perhaps not as effectively and reliably as caregivers would like. On the other hand, healthcare systems mandate objective metrics in pain diagnosis. Smiley face caricatures are a staple of clinical practice and a universal standard for reporting pain levels. These conditions create a double paradox: Assess a private experience that is inaccessible, and use numerical scales to measure subjective attributes. Navigating this stressful environment, medical professionals experience intellectual dissonance, patients are frustrated, and value-based care is undermined. Offering a way out, first, we refute the privacy and objectification of pain citing philosophical, behavioral, and neuroscientific arguments. We discuss Wittgensteinian views against privacy, explore the clear evolutionary advantage of communicating pain to others, and identify neural circuits in the mammalian brain that contribute to empathy. Second, we highlight the subjectivity of pain, embracing the complexity and uniqueness of an individual's pain. We also provide compelling evidence for brain mechanisms that actively shape the pain experience according to predictive coding principles. Third, we offer a vision for the development of biomarker technologies that assess pain fairly without engendering bias against the patient's narrative. Our recommendations are based on the overwhelming appreciation that "medicine by emoji" is inadequate for capturing the multidimensional nature of pain. Our view is that the most promising candidates for pain biomarkers consist of self-reports as ground truth augmented by physiological signatures of biological relevance to pain. Integration of subjective and objective multimodal features will be key for the development of comprehensive pain assessment models. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) is vital in many fields because of its high sensitivity, fast response, and fingerprint effect. The surface-enhanced Raman mechanisms are generally electromagnetic enhancement (EM), which is mainly based on noble metals (Au, Ag, etc.), and chemical enhancement (CM). With more and more studies on CM mechanism in recent years, non-noble metal nanomaterial SERS substrates gradually became widely researched and applied due to their superior economy, stability, selectivity, and biocompatibility compared to noble metal. In addition, non-noble metal substrates also provide an ideal new platform for SERS technology to probe the mechanism of biomolecules. In this paper, we review the applications of non-noble metal nanomaterials in SERS detection for biomedical engineering in recent years. Firstly, we introduce the development of some more common non-noble metal SERS substrates and discuss their properties and enhancement mechanisms. Subsequently, we focus on the progress of the application of SERS detection of non-noble metal nanomaterials, such as analysis of biomarkers and the detection of some contaminants. Finally, we look forward to the future research process of non-noble metal substrate nanomaterials for biomedicine, which may draw more attention to the biosensor applications of non-noble metal nanomaterial-based SERS substrates. [ABSTRACT FROM AUTHOR]

Exposure of cell membranes to reactive oxygen species can cause oxidation of membrane lipids. Oxidized lipids undergo drastic conformational changes, compromising the mechanical integrity of the membrane and causing cell death. For giant unilamellar vesicles, a classic cell mimetic system, a range of mechanical responses under oxidative assault has been observed including formation of nanopores, transient micron‐sized pores, and total sudden catastrophic collapse (i.e., explosion). However, the physical mechanism regarding how lipid oxidation causes vesicles to explode remains elusive. Here, with light‐induced asymmetric oxidation experiments, the role of spontaneous curvature on vesicle instability and its link to the conformational changes of oxidized lipid products is systematically investigated. A comprehensive membrane model is proposed for pore‐opening dynamics incorporating spontaneous curvature and membrane curling, which captures the experimental observations well. The kinetics of lipid oxidation are further characterized and how light‐induced asymmetric oxidation generates spontaneous curvature in a non‐monotonic temporal manner is rationalized. Using the framework, a phase diagram with an analytical criterion to predict transient pore formation or catastrophic vesicle collapse is provided. The work can shed light on understanding biomembrane stability under oxidative assault and strategizing release dynamics of vesicle‐based drug delivery systems. [ABSTRACT FROM AUTHOR]

Preclinical animal models are crucial for advancing the clinical management of acute respiratory distress syndrome (ARDS). However, there is a lack of positive findings from preclinical studies that translate into clinical practice. One possible reason for this is the inadequate optimization of positive end-expiratory pressure (PEEP) during injury development in animal models. Insufficient PEEP levels can lead to the inclusion of subjects with mild lung injury, resulting in erroneous conclusions. Therefore, it is important to prioritize PEEP optimization in preclinical ARDS models to achieve consistent and clinically relevant lung injury. A study conducted on an ovine model of ARDS found that optimizing PEEP during injury development can significantly alter injury levels and align them more accurately with clinical practice. Future preclinical studies should also incorporate clinically relevant adjunctive therapies to better replicate the complexity of ARDS in real-world scenarios. [Extracted from the article]

Patients and healthcare practitioners have commended the systems' effectiveness, ease, and user-friendliness in several situations. Utilizing cutting-edge ideas and methods from the multidisciplinary domains of electricity, computing, medical engineering, and medicine, mobile healthcare (m-health) technology advances these professions' contributions to healthcare systems. The monitoring and delivery of healthcare interventions are becoming increasingly dependent on mobile phones. Because of their sophisticated processing functions, improved preferences, and wide range of capabilities, they are frequently referred to as pocket computers. Their advanced sensors and intricate software programmers increase the viability and innovation of m-health solutions. To design the m-health application, the design science research methodology (DSRM) framework was used. Additionally, the architecture for connecting the hospital information system and mobile device network together was established. Additionally, a few exemplary intelligent healthcare applications are examined to demonstrate how data analytics and mobile computing can be used to improve the quality of healthcare services. [ABSTRACT FROM AUTHOR]

Featured Application: Featured Application: The potential application of the work relates to novel digital twins of patients or their organs based on artificial intelligence. Digital society strategies in healthcare include the rapid development of digital twins (DTs) for patients and human organs in medical research and the use of artificial intelligence (AI) in clinical practice to develop effective treatments in a cheaper, quicker, and more effective manner. This is facilitated by the availability of large historical datasets from previous clinical trials and other real-world data sources (e.g., patient biometrics collected from wearable devices). DTs can use AI models to create predictions of future health outcomes for an individual patient in the form of an AI-generated digital twin to support the rapid assessment of in silico intervention strategies. DTs are gaining the ability to update in real time in relation to their corresponding physical patients and connect to multiple diagnostic and therapeutic devices. Support for this form of personalized medicine is necessary due to the complex technological challenges, regulatory perspectives, and complex issues of security and trust in this approach. The challenge is also to combine different datasets and omics to quickly interpret large datasets in order to generate health and disease indicators and to improve sampling and longitudinal analysis. It is possible to improve patient care through various means (simulated clinical trials, disease prediction, the remote monitoring of apatient's condition, treatment progress, and adjustments to the treatment plan), especially in the environments of smart cities and smart territories and through the wider use of 6G, blockchain (and soon maybe quantum cryptography), and the Internet of Things (IoT), as well as through medical technologies, such as multiomics. From a practical point of view, this requires not only efficient validation but also seamless integration with the existing healthcare infrastructure. [ABSTRACT FROM AUTHOR]

This study explores the fabrication and characterisation of 3D-printed polylactic acid (PLA) scaffolds reinforced with calcium hydroxyapatite (cHAP) for bone tissue engineering applications. By varying the cHAP content, we aimed to enhance PLA scaffolds' mechanical and thermal properties, making them suitable for load-bearing biomedical applications. The results indicate that increasing cHAP content improves the tensile and compressive strength of the scaffolds, although it also increases brittleness. Notably, incorporating cHAP at 7.5% and 10% significantly enhances thermal stability and mechanical performance, with properties comparable to or exceeding those of human cancellous bone. Furthermore, this study integrates machine learning techniques to predict the mechanical properties of these composites, employing algorithms such as XGBoost and AdaBoost. The models demonstrated high predictive accuracy, with R2 scores of 0.9173 and 0.8772 for compressive and tensile strength, respectively. These findings highlight the potential of using data-driven approaches to optimise material properties autonomously, offering significant implications for developing custom-tailored scaffolds in bone tissue engineering and regenerative medicine. The study underscores the promise of PLA/cHAP composites as viable candidates for advanced biomedical applications, particularly in creating patient-specific implants with improved mechanical and thermal characteristics. [ABSTRACT FROM AUTHOR]

Medical image segmentation plays a critical role in accurate diagnosis and treatment planning, enabling precise analysis across a wide range of clinical tasks. This review begins by offering a comprehensive overview of traditional segmentation techniques, including thresholding, edge-based methods, region-based approaches, clustering, and graph-based segmentation. While these methods are computationally efficient and interpretable, they often face significant challenges when applied to complex, noisy, or variable medical images. The central focus of this review is the transformative impact of deep learning on medical image segmentation. We delve into prominent deep learning architectures such as Convolutional Neural Networks (CNNs), Fully Convolutional Networks (FCNs), U-Net, Recurrent Neural Networks (RNNs), Adversarial Networks (GANs), and Autoencoders (AEs). Each architecture is analyzed in terms of its structural foundation and specific application to medical image segmentation, illustrating how these models have enhanced segmentation accuracy across various clinical contexts. Finally, the review examines the integration of deep learning with traditional segmentation methods, addressing the limitations of both approaches. These hybrid strategies offer improved segmentation performance, particularly in challenging scenarios involving weak edges, noise, or inconsistent intensities. By synthesizing recent advancements, this review provides a detailed resource for researchers and practitioners, offering valuable insights into the current landscape and future directions of medical image segmentation. [ABSTRACT FROM AUTHOR]

Background: Effective rehabilitation following total knee arthroplasty (TKA) is crucial for enhancing both range of motion (ROM) and functional outcomes. While robotics has demonstrated its potential in various medical contexts, the evidence on its application in TKA rehabilitation is still scarce. The marsi active knee (MAK), a robotic device that has already proven to be safe and beneficial in people with neurological disease, has been tested to facilitate the rehabilitation of TKA patients. Objective: This study aims to evaluate the safety, patient satisfaction, and clinical impact of integrating the MAK into an early rehabilitation regimen for TKA patients. Methods: The intervention comprised 14 one‐hour sessions administered thrice a week, utilizing the MAK within 48 h post‐TKA surgery. The rehabilitation sessions incorporated exercises involving passive mobilizations, sit‐to‐stand transitions, and gait training. Comprehensive data encompassing safety parameters, patient satisfaction, and clinical outcomes were meticulously collected and analyzed. Results: Six participants successfully completed the rehabilitation protocol with the MAK device. Notably, no significant adverse events were documented. Application of the device corresponded to perceptible reductions in self‐reported pain levels. Vital signs remained within minimal variance pre‐ and post‐rehabilitation. Participants proficiently engaged in all assisted exercises facilitated by the device, culminating in a high overall satisfaction rating of 4.6 ± 0.5 out of 5. Conclusion: The findings indicate that the MAK device exhibits a commendable level of safety while obtaining considerable patient satisfaction during the early rehabilitation phase following TKA, suggesting this device may be a reliable adjunct to TKA protocols. [ABSTRACT FROM AUTHOR]

Purpose: To develop and assess the utility of an ophthalmic viscosurgical device (OVD) manufactured with fluoresceinconjugated hyaluronic acid (conjHA). Setting: Department of Biomedical Engineering and the Wilmer Eye Institute, Johns Hopkins University and School of Medicine, Baltimore, Maryland. Design: Laboratory study. Methods: ConjHA and unconjugated HA (unconjHA) at varied ratios were used to produce OVD (conjOVD) with varied fluorescence intensity. The conjHA:unconjHA ratio was optimized to maximize clarity under white light and fluorescence intensity under cobalt blue light (CBL), allowing for conditional visualization. The effect of conjugation on conjOVD viscosity was assessed by rotational rheometry. Intraocular lenses (IOLs) were immersed in conjOVD for 4 hours to assess staining of IOLs. A proof-of-concept study was performed in ex vivo porcine eyes. After injection and visualization, the OVDs were removed from the eyes by irrigation/aspiration (I/A). Results: 0.5 mg/mL of conjHA (degree of substitution = 0.005) enabled robust fluorescence of conjOVD under CBL. Fluorescein conjugation did not significantly affect conjOVD viscosity (P > .05 for mean difference in viscosity at all shear rates tested). No staining of IOLs was appreciated. ConjOVD was visualized under CBL when injected ex vivo and maintained clarity of the anterior chamber under white light. Importantly, conjHA enabled delineation of retained OVD after I/A. Conclusions: Use of OVD composed of fluorescein-conjugated HA is a feasible method to enable conditional visualization of OVD intraoperatively without nonspecific staining of ocular structures. Further development of this technology may enable accelerated OVD removal in ocular surgery or decreased OVD retention postoperatively. [ABSTRACT FROM AUTHOR]

Porous hydrogels have brought more advantages than conventional hydrogels when used as chromatographic materials, controlled release vehicles for drugs and proteins, matrices for immobilization or separation of molecules and cells, or as scaffolds in tissue engineering. Polysaccharide-based porous hydrogels, in particular, can address challenges related to bioavailability, solubility, stability, and targeted delivery of natural antioxidant compounds. Their porous structure enables the facile encapsulation and controlled release of these compounds, enhancing their therapeutic effectiveness. In this context, in the present study, the cryogelation technique has been adopted to prepare novel dextran (Dx)-based porous hydrogels embedding polyphenol-rich natural extract from Picea abies spruce bark (SBE). The entrapment of the SBE within the Dx network was proved by FTIR, SEM, and energy-dispersive X-ray spectroscopy (EDX). SEM analysis showed that entrapment of SBE resulted in denser cryogels with smaller and more uniform pores. Swelling kinetics confirmed that higher concentrations of Dx, EGDGE, and SBE reduced water uptake. The release studies demonstrated the effective stabilization of SBE in the Dx-based cryogels, with minimal release irrespective of the approach selected for SBE incorporation, i.e., during synthesis (~3–4%) or post-synthesis (~15–16%). In addition, the encapsulation of SBE within the Dx network endowed the hydrogels with remarkable antioxidant and antimicrobial properties. These porous biomaterials could have broad applications in areas such as biomedical engineering, food preservation, and environmental protection, where stability, efficacy, and safety are paramount. [ABSTRACT FROM AUTHOR]

Simple Summary: Glioblastoma (GBM), a serious brain cancer, has poor treatment outcomes despite surgery, radiation, and chemotherapy. The blood–brain barrier (BBB) makes GBM-targeted drug delivery difficult. Recent studies have shown that nanomedicine delivery systems (NDDSs) can target GBM safely and effectively. In this review, we look at ways to overcome the BBB with NDDSs in preclinical studies, summarize the clinical progress, and discuss strategies to improve NDDSs and speed up their use in GBM treatment through clinical trials. Glioblastoma (GBM) is a prevalent type of malignancy within the central nervous system (CNS) that is associated with a poor prognosis. The standard treatment for GBM includes the surgical resection of the tumor, followed by radiotherapy and chemotherapy; yet, despite these interventions, overall treatment outcomes remain suboptimal. The blood–brain barrier (BBB), which plays a crucial role in maintaining the stability of brain tissue under normal physiological conditions of the CNS, also poses a significant obstacle to the effective delivery of therapeutic agents to GBMs. Recent preclinical studies have demonstrated that nanomedicine delivery systems (NDDSs) offer promising results, demonstrating both effective GBM targeting and safety, thereby presenting a potential solution for targeted drug delivery. In this review, we first explore the various strategies employed in preclinical studies to overcome the BBB for drug delivery. Subsequently, the results of the clinical translation of NDDSs are summarized, highlighting the progress made. Finally, we discuss potential strategies for advancing the development of NDDSs and accelerating their translational research through well-designed clinical trials in GBM therapy. [ABSTRACT FROM AUTHOR]

Biopolymer materials have attracted attention due to their richness, sustainability, environmental friendliness, and biodegradability properties. This review explores recent advances in biopolymer synthesis, properties, and their commercial applications. Biopolymers, derived from renewable sources, have garnered significant attention due to their environmental benefits and potential to replace conventional petrochemical-based plastics. The synthesis of biopolymer delves into innovative biopolymer production techniques, including microbial fermentation, chemical modifications, and novel biotechnological approaches. A detailed examination of the unique properties of biopolymers, including physical, thermal, mechanical, and optical characteristics of naturally generated biopolymers. It explores the diverse range of applications of biopolymers across industries, including packaging for the food industry, biomedical engineering, cosmetics, and different mechanical applications. The review further discusses the growing commercial applications of biopolymers across various industries, such as packaging, agriculture, medicine, and textiles. This review aims to provide an understanding of the current method of synthesis properties and future potential application of biopolymers in advancing sustainable materials science. [Display omitted] • The biopolymeric materials synthesis techniques are discussed. • Potential of biomass wastes towards the extraction of biopolymer is explored. • Biopolymeric material properties and applications are summarized. • Recent development of biopolymer for different application are discussed [ABSTRACT FROM AUTHOR]

• A dynamic theory of the HMS curved rod under 3D large deformation is presented. • The "tension-bending" and "shear-torsion" coupling effects of curved rod emerge in our model. • The finite element formulation and exact linearization of the dynamical problem are obtained. • An implementation based on Newmark algorithm and some numerical examples are presented. • Several experiments about a quarter arc HMS robotic arm are presented. Magnetorheological elastomers are active materials which can be actuated by the applied magnetic field. Hard magnetic soft (HMS) materials, a type of magnetorheological elastomers, show great potential in the fields of biomedical engineering and soft robotics, due to their short response time, remote operation, and shape programmability. To exploit its potential, a series of theoretical frameworks of HMS rods have been developed, but they are mainly limited to the static rod models or classical curved rod models that fail to consider the effect of the "initial curvature" on the distribution of the stress. In this work, we develop a curved rod theory to predict the 3D dynamic motion of the rod-like HMS robotics under large deformation. Based on the geometrically exact rod theory, we include the heterogeneous initial length of the longitudinal fiber caused by "initial curvature" into our model and obtain the reduced balance equations of the HMS robotics. As a result, the "tension-bending" and "shear-torsion" coupling effects of curved rods emerge in the present model. A numerical implementation of our model based on the classical Newmark algorithm is presented. To validate our model, three numerical examples, including the dynamic snap-through behavior of a bistable arch, are performed and compared with the simulation or experiment results reported in literatures, which show a good agreement. Finally, we experimentally study the 2D and 3D static and dynamic motion of a quarter arc HMS robotic arm under an applied magnetic field of 10 mT, and our model gives a satisfactory prediction, especially for static deformation. [ABSTRACT FROM AUTHOR]

In this era, feature clustering is a prominent technique in data mining. Feature clustering has also huge applications in biomedical research for multiple purposes including grouping, feature reduction, and many more. The Internet of Medical Things (IoMT) is a promising and emerging field of research that is having a major impact on knowledge retrieval and networking. IoMT also has significant application in biomedical research regarding remote monitoring and remote healthcare services. In this COVID-19 pandemic situation, psychological effects and human reactions have become a major concern of further research. A dataset can be reduced in size by using feature selection techniques. To facilitate subsequent processing, this will make the data easier to manage. Feature selection is also used to clean, reduce, and reduce dimensions of data. The clustering method has proven to be a powerful tool for finding patterns and structures in both labeled and unlabeled datasets. Our study basically provides various state-of-the-art methods regarding medical IoMT for remote healthcare, feature clustering for information retrieval regarding biomedical science. In this study, we have studied five different types of feature selection algorithms such as minimum redundancy maximum relevance (mRMR), random forest, normalized mutual information feature selection (NMIFS), F-test, and chi-square and five different types of clustering algorithms like hierarchical clustering, density-based spatial clustering of applications with noise (DBSCAN) clustering, K-means clustering, shrinkage clustering, and fuzzy C-means clustering. Finally, this study is very useful to understand and apply the appropriate IoMT, feature clustering, and catharsis on the various biomedical applications for the benevolence of society. [ABSTRACT FROM AUTHOR]

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The manufacturing Industry in Europe plays a significant role in economic growth and development. Given the increased role of technology in this sector, the Industrial Internet of Things (IIoT) is one of the technological advancements that improve the Business Model (BM) efficacy in various manufacturing industries. However, research into the role of IIoT as a BM in the manufacturing industry is limited despite its contribution to the success and performance of the firms. Therefore, this study explores the role that IIoT plays as a BM in various manufacturing industries. A survey was conducted utilizing open-ended questionnaires across 60 manufacturing firms in Europe including automotive suppliers, information and communication, machine and plant engineering, electrical engineering, and medical engineering. The findings indicate that IIoT as a BM has different levels of contribution across the manufacturing industry with glaring variations in terms of performance between information and communication firms as well as automotive. This study can act as a guideline for further research on the complex relationship between IIoT as a BM and firms' performance to influence decision-making processes within the manufacturing industry. Given that this is a pre-study, the limitations, and recommendations for future research are highlighted. [ABSTRACT FROM AUTHOR]

Cell micromanipulation is an important technique in the field of biomedical engineering. Microgrippers play a crucial role in connecting macroscopic and microscopic objects in micromanipulation systems. However, since the operated biological cells are deformable, vulnerable, and typically distributed in sizes ranging from micrometers to millimeters, it poses a huge challenge to microgripper performance. To solve this problem, this paper develops a dual-driven piezoelectric microgripper with a high displacement amplification ratio, large stroke, and parallel gripping. By adopting modular configuration, three kinds of flexure-based mechanisms, including the lever mechanism, Scott–Russell mechanism, and parallelogram mechanism are connected in series to realize three-stage amplification, which effectively makes up for the shortage of small output displacement of the piezoelectric actuator. At the same time, the use of the parallelogram mechanism also isolates the parasitic rotation movement, and realizes the parallel movement of the gripping jaws. In addition, the kinematics, statics, and dynamics models of the microgripper are established by using the pseudo-rigid body and Lagrange methods, and the key geometric parameters are also optimized. Finite element simulation and experimental tests verify the effectiveness of the developed microgripper. The results show that the developed microgripper allows an amplification ratio of 46.4, a clamping stroke of 2180 μ m, and a natural frequency of 203.1 Hz. Based on the developed microgripper, the nondestructive micromanipulation of zebrafish embryos is successfully realized. [ABSTRACT FROM AUTHOR]

Amidst rapid technological and healthcare advancements, biomedical data classification using machine learning (ML) is pivotal for revolutionizing medical diagnosis, treatment, and research by organizing vast healthcarerelated data. Despite efforts to apply single ML models on clean datasets, satisfactory classification accuracy can still be elusive. In such cases, MLbased ensembles offer a promising solution. This paper explores cascaded ensembles as highly accurate methods. Existing cascade classifiers often partition large datasets into equal unique parts, limiting accuracy due to insufficient amount of useful information processed by weak classifiers of all levels of the cascade ensemble. To address this, we propose an improved cascaded ensemble scheme using a different data sampling approach. Our method forms larger subsamples at each cascade level, enhancing accuracy, and generalization properties during biomedical data analysis. Experimental comparisons demonstrate substantial increases in classification accuracy and generalization properties of the improved cascade ensemble. [ABSTRACT FROM AUTHOR]

Hydrogels have garnered significant attention for their versatile applications across various fields, including biomedical engineering. This review delves into the fundamentals of hydrogels, exploring their definition, properties, and classification. Hydrogels, as three-dimensional networks of crosslinked polymers, possess tunable properties such as biocompatibility, mechanical strength, and hydrophilicity, making them ideal for medical applications. Uniquely, this article offers original insights into the application of hydrogels specifically for corneal tissue engineering, bridging a gap in current research. The review further examines the anatomical and functional complexities of the cornea, highlighting the challenges associated with corneal pathologies and the current reliance on donor corneas for transplantation. Considering the global shortage of donor corneas, this review discusses the potential of hydrogel-based materials in corneal tissue engineering. Emphasis is placed on the synthesis processes, including physical and chemical crosslinking, and the integration of bioactive molecules. Stimuli-responsive hydrogels, which react to environmental triggers, are identified as promising tools for drug delivery and tissue repair. Additionally, clinical applications of hydrogels in corneal pathologies are explored, showcasing their efficacy in various trials. Finally, the review addresses the challenges of regulatory approval and the need for further research to fully realize the potential of hydrogels in corneal tissue engineering, offering a promising outlook for future developments in this field. [ABSTRACT FROM AUTHOR]

Collagen is the oldest and most abundant extracellular matrix protein and has many applications in biomedical, food, cosmetic, and other industries. Previous reviews have already introduced collagen's sources, structures, and biosynthesis. The biological and mechanical properties of collagen-based composite materials, their modification and application forms, and their interactions with host tissues are pinpointed. It is worth noting that self-assembly behavior is the main characteristic of collagen molecules. However, there is currently relatively little review on collagen-based composite materials based on self-assembly. Herein, we briefly reviewed the biosynthesis, extraction, structure, and properties of collagen, systematically presented an overview of the various factors and corresponding characterization techniques that affect the collagen self-assembly process, and summarize and discuss the preparation methods and application progress of collagen-based composite materials in different fields. By combining the self-assembly behavior of collagen with preparation methods of collagen-based composite materials, collagen-based composite materials with various functional reactions can be selectively prepared, and these experiences and outcomes can provide inspiration and practical techniques for the future development directions and challenges of collagen-based composite biomaterials in related applications fields. [ABSTRACT FROM AUTHOR]

Nanogels represent a significant innovation in the fields of nanotechnology and biomedical engineering, combining the properties of hydrogels and nanoparticles to create versatile platforms for drug delivery, tissue engineering, bioimaging, and other biomedical applications. These nanoscale hydrogels, typically ranging from 10 to 1000 nm, possess unique characteristics such as high water content, biocompatibility, and the ability to encapsulate both hydrophilic and hydrophobic molecules. The review explores the synthesis, structural configurations, and stimuli‐responsive nature of nanogels, highlighting their adaptability for targeted drug delivery, including across challenging barriers like the blood–brain barrier. Furthermore, the paper delves into the biomedical applications of nanogels, particularly in drug delivery systems, tissue engineering, and bioimaging, demonstrating their potential to revolutionize these fields. Despite the promising preclinical results, challenges remain in translating these technologies into clinical practice, including issues related to stability, scalability, and regulatory approval. The review concludes by discussing future perspectives, emphasizing the need for further research to optimize the properties and applications of nanogels, ultimately aiming to enhance their efficacy and safety in clinical settings. [ABSTRACT FROM AUTHOR]

Hydrogel materials are continually developing in biomedical engineering and recently a lot of effort has gone into their engineered performance in physiological applications. Porosity is an important characteristic for tissue engineering scaffolds to allow enhanced biocompatibility and the pore size needed is dependent on the application and type of tissue for which the hydrogel is being used to regenerate. Regarding biomedical applications, the use of conducting polymers is gaining in popularity due to their promising biocompatibility and potential to stimulate cell growth and proliferation through electrical stimulation. Building on previous hydrogel development by the authors, this study focuses on developing a biocompatible hydrogel scaffold with adjustable porosity and swelling capabilities, robust mechanical properties, electrical conductivity, and high thermal stability. The objective of this work is to examine the effect of freezing temperature, cross‐linker and porosity on the final characteristics of the scaffold and to then determine possible applications. The porosity, swelling degree, compression strength, biocompatibility, electrical conductivity, and thermal characteristics of the final material were analyzed and were found to be affected by the varied synthesis methods used. Overall, the synthesized scaffolds exhibit good biocompatibility with increased fluorescence over 3 days and over 70% cell viability, thermal stability up to 200°C and a range of swelling of 1725% to 8472%. They also portray robust mechanical properties with a Young's Moduli range of 11 kPa to 4.54 MPa and a porosity range of 0.78–71.98 μm depending on the synthesis methods used. Through variations in synthesis methods, highly porous, absorbent, and stable scaffolds have been synthesized. Notably, this single recipe is highly tailorable for use in a range of biomedical applications from tissue engineering to drug delivery and wound repair. [ABSTRACT FROM AUTHOR]

Aims & Objectives: The primary aim of this paper is to determine whether smart glasses or head-mounted displays improve efficiency in a procedural or theatre setting without compromising the quality of the procedure performed. Additionally, this paper aims to qualitatively explore applications in surgical education, whilst on-call, consulting and patient observation. Design: This paper is a systematic review of the literature available on the topic of smart glasses or head-mounted displays in surgical or procedural settings. Methods: A search of Pubmed, Cochrane and the Wiley Online Library was performed in accordance with the PRISMA guidelines. Procedural times and adverse outcomes were compared between the smart glass and non-smart glass groups in each of the quantitative studies. A literature review of studies, including those not satisfying the primary aim was conducted and is included in this paper. Results: 32 studies were identified that complied with the inclusion criteria of this paper. 8 of these studies focused on procedural times and adverse outcomes, with and without smart glass usage. Procedural time was reduced when smart glass technology was used, without an increase in adverse patient outcomes. Conclusions: Surgeons should consider whether the relatively short reduction in procedural time is worth the high cost, privacy issues, battery complaints and user discomfort involved with these devices. There are promising applications of this technology in the areas of surgical education and consultation. However, more trials are necessary to assess the value of using smart glasses in these settings. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) printing has become a potent production tool in the field of biomedical engineering over the past 20 years. Through layer-by-layer deposition of materials, proteins, and even living cells, it offers considerable advantages in the creation of sophisticated and individualized biomedical products with accuracy, efficiency, cost effectiveness, and reproducibility. Despite the tremendous advances made in 3D printing, more work needs to be done to improve the quality of biomedical goods created with this technology. To assure the creation of remarkable and ground-breaking goods that address patients' demands, numerous challenges in 3D printing processes, materials, and applications must be addressed. It is necessary to incorporate developments in physics, materials science, engineering, biological sciences, and medicine to meet these problems. This article reviews a variety of 3D printing-related issues in the biomedical industry, including processes, post-processing techniques, applications, and related difficulties. It analyzes the difficulties 3D printing in biomedical engineering faces and makes suggestions for potential future advancements. It is obvious that 3D printing is becoming more and more important in this field and has the ability to provide a wide variety of useful biological items. This review seeks to identify future directions for research and development while also advancing understanding of the existing state of 3D printing and the effect of post-processing in biomedical engineering. [ABSTRACT FROM AUTHOR]

The swift increase in antimicrobial resistance across the world presents a significant challenge, further raised by insufficient advancement in the design of new antimicrobial agents. Over the past two decades, a variety of sources has been investigated for generating new antimicrobials. Recently, antimicrobial polymers (APs) have emerged as multifaceted agents, displaying effectiveness against a range of pathogens such as bacteria, fungi, and viruses. Their notable biocompatibility, efficiency, multifunctionality, and ease of modification make them a focal point of antimicrobial research. APs are particularly valued for their structural versatility, which allows for the integration of antimicrobial functional groups. Polymer functionalization does not only enhance or introduce antimicrobial properties but also maintains high levels of biocompatibility. This review reveals broad antimicrobial breadth of APs, which can be potentially used in antiseptics, food packaging, and in biomedical sector, as e.g. medical implants’ coatings. In laboratory settings, APs have shown promising therapeutic effects, however there remains an urgent need for computational biology to fully understand their antimicrobial behaviour and stability. Recombinant biotechnological approaches are essential for facilitating the production of APs and require industrial collaboration to effectively optimize and scale up these production processes.

Abstract Breathing patterns (respiratory kinematics) contain vital prognostic information. This dimension of physiology is not captured by conventional vital signs. We sought to determine the feasibility and utility of quantifying respiratory kinematics. Using inertial sensors, we analyzed upper rib, lower rib, and abdominal motion of 108 patients with respiratory symptoms during a hospital encounter (582 two-minute recordings). We extracted 34 features based on an explainable correspondence with well-established breathing patterns. K-means clustering revealed that respiratory kinematics had three dimensions apart from the respiratory rate. We represented these dimensions using respiratory rate variability, respiratory alternans (rib-predominant breaths alternating with abdomen-predominant ones), and recruitment of accessory muscles (increased upper rib excursion). Latent profile analysis of the kinematic measures revealed two profiles consistent with the established clinical constructs of labored and unlabored breathing. In logistic regression, the labored breathing profile improved model discrimination for critical illness beyond the Sequential Organ Failure Assessment (SOFA) score (AUROC 0.77 v/s 0.72; p = 0.02). These findings quantitatively confirm the prior understanding that the respiratory rate alone does not adequately represent the complexity of respiratory kinematics; they demonstrate that high-dimensional signatures of labored breathing can be quantified in routine practice settings, and they can improve predictions of clinical deterioration.

PurposeTo understand differences in measures of depression, stress, and social support by gender among those diagnosed with glaucoma.MethodsWe obtained a cohort of glaucoma patients (any type) ages 18 years and over who answered the COVID-19 Participant Experience (COPE) survey of the NIH All of Us Research Program. We analyzed several measures of depression, stress, and social support by gender. Logistic regression was used to evaluate the association among reported stress associated with social distancing, depression (using Patient Health Questionnaire-9 [PHQ-9] scores), and measures of social support by self-reported gender, with men as the reference group. Multivariable models were adjusted for age, race and ethnicity, health insurance status, education, and income.ResultsOf 3633 glaucoma patients, 56.8% were women. Many patients had a PHQ-9 score > 4 (33.3%), indicating mild, moderate, or severe depression. In multivariable models, women were significantly more likely to report a PHQ-9 score > 4 (odds ratio [OR] = 1.40; 95% confidence interval [CI], 1.20-1.62; P < 0.001) and some or a lot of stress (OR = 1.34; 95% CI, 1.14-1.57; P < 0.001) compared with men. Further, women were significantly less likely to report having help all or most of the time if they needed someone to prepare meals (OR = 0.78; 95% CI, 0.67-0.92; P = 0.002) or perform daily chores (OR = 0.79; 95% CI, 0.67-0.91; P = 0.003) than men.ConclusionsWomen with glaucoma were more likely to experience depression and stress and were less likely to have social support on some measures than men.Translational relevanceThe disproportionate burden of psychosocial factors among women may complicate glaucoma management.

Imaging infections in patients is challenging using conventional methods, motivating the development of positron emission tomography (PET) radiotracers targeting bacteria-specific metabolic pathways. Numerous techniques have focused on the bacterial cell wall, although peptidoglycan-targeted PET tracers have been generally limited to the short-lived carbon-11 radioisotope (t1/2 = 20.4 min). In this article, we developed and tested new tools for infection imaging using an amino sugar component of peptidoglycan, namely, derivatives of N-acetyl muramic acid (NAM) labeled with the longer-lived fluorine-18 (t1/2 = 109.6 min) radioisotope. Muramic acid was reacted directly with 4-nitrophenyl 2-[18F]fluoropropionate ([18F]NFP) to afford the enantiomeric NAM derivatives (S)-[18F]FMA and (R)-[18F]FMA. Both diastereomers were easily isolated and showed robust accumulation by human pathogens in vitro and in vivo, including Staphylococcus aureus. These results form the basis for future clinical studies using fluorine-18-labeled NAM-derived PET radiotracers.

Insulin is an essential regulator of blood glucose homeostasis that is produced exclusively byβcells within the pancreatic islets of healthy individuals. In those affected by diabetes, immune inflammation, damage, and destruction of isletβcells leads to insulin deficiency and hyperglycemia. Current efforts to understand the mechanisms underlyingβcell damage in diabetes rely onin vitro-cultured cadaveric islets. However, isolation of these islets involves removal of crucial matrix and vasculature that supports islets in the intact pancreas. Unsurprisingly, these islets demonstrate reduced functionality over time in standard culture conditions, thereby limiting their value for understanding native islet biology. Leveraging a novel, vascularized micro-organ (VMO) approach, we have recapitulated elements of the native pancreas by incorporating isolated human islets within a three-dimensional matrix nourished by living, perfusable blood vessels. Importantly, these islets show long-term viability and maintain robust glucose-stimulated insulin responses. Furthermore, vessel-mediated delivery of immune cells to these tissues provides a model to assess islet-immune cell interactions and subsequent islet killing-key steps in type 1 diabetes pathogenesis. Together, these results establish the islet-VMO as a novel,ex vivoplatform for studying human islet biology in both health and disease.

Histological staining of tissue biopsies, especially hematoxylin and eosin (H&E) staining, serves as the benchmark for disease diagnosis and comprehensive clinical assessment of tissue. However, the process is laborious and time-consuming, often limiting its usage in crucial applications such as surgical margin assessment. To address these challenges, we combine an emerging 3D quantitative phase imaging technology, termed quantitative oblique back illumination microscopy (qOBM), with an unsupervised generative adversarial network pipeline to map qOBM phase images of unaltered thick tissues (i.e., label- and slide-free) to virtually stained H&E-like (vH&E) images. We demonstrate that the approach achieves high-fidelity conversions to H&E with subcellular detail using fresh tissue specimens from mouse liver, rat gliosarcoma, and human gliomas. We also show that the framework directly enables additional capabilities such as H&E-like contrast for volumetric imaging. The quality and fidelity of the vH&E images are validated using both a neural network classifier trained on real H&E images and tested on virtual H&E images, and a user study with neuropathologists. Given its simple and low-cost embodiment and ability to provide real-time feedback in vivo, this deep learning-enabled qOBM approach could enable new workflows for histopathology with the potential to significantly save time, labor, and costs in cancer screening, detection, treatment guidance, and more.

There is a growing need for applications capable of handling large synthesis biology experiments. At the core of synthetic biology is the process of cloning and manipulating DNA as plasmids. Here, we report the development of an application named DNAda capable of writing automation instructions for any given DNA construct design generated by the J5 DNA assembly program. We also describe the automation pipeline and several useful features. The pipeline is particularly useful for the construction of combinatorial DNA assemblies. Furthermore, we demonstrate the platform by constructing a library of polyketide synthase parts, which includes 120 plasmids ranging in size from 7 to 14 kb from 4 to 7 DNA fragments.

Benchmarking compares the performance of a product or service with a competitor. In a biofoundry context, capability benchmarking enables more effective use of development resources and furthering business development efforts. Biofoundries considering benchmarking activities are immediately faced with many implementation questions and decisions. While differing circumstances between biofoundries may lead to different answers to those same questions, a common framework for the benchmarking process is desirable. Perhaps the framework described here, and developed for the United States Department of Energy Agile BioFoundry, will be useful to other biofoundries around the world.

Between 1982 and 1986, 126 patients who had undergoneACL reconstruction were followed in a prospectivemanner. One year follow-up statistics were reviewedfor the presence of 13 different complications.The most prevalent complications were quadricepsweakness, flexion contracture, and patellofemoral pain.Quadriceps weakness (strength less than 80% of thenormal side) was present in 65% of patients and correlatedpositively with flexion contracture, patellar irritability,and ACL reconstructions using patellar tendongrafts. Flexion contracture of 5° or more was presentin 24% of patients and correlated positively with increasedage and patellar irritability. Patellofemoral painwas present in 19% of patients and correlated positivelywith flexion contracture.Clinical relevance: The three most common complicationsof knee ligament surgery are shown to bestrongly interrelated. It is likely that a causal relationshipis present in which flexion contracture causes patellofemoralirritability, and that both of these factors, aloneor in combination, result in quadriceps weakness. If thistheory is correct, then it is crucial that postoperativerehabilitation programs place a major emphasis on theavoidance of flexion contracture.

With the advent of induced pluripotent stem cells and modern differentiation protocols, many advances in our understanding of disease have been made possible by in vitro disease modeling; in some cases, their use may have supplanted animal models. Yet in vitro models often rely on rigid cell culture substrates that could limit our ability to completely reproduce human disease in a dish. Nascent work, however, suggests that the combination of biomaterials and/or advanced microphysiological systems-which better recapitulate tissue properties-with stem cells expressing disease mimicking genetics, could substantially improve current disease modeling efforts where genetics alone is insufficient. This review will highlight such recent advances as well as review current challenges that the fields must overcome to create more personalized therapeutics in the future.

Glaucoma is a group of eye diseases characterized by the thinning of the retinal nerve fiber layer (RNFL), which is primarily caused by the progressive death of retinal ganglion cells (RGCs). Precise monitoring of these changes at a cellular resolution in living eyes is significant for glaucoma research. In this study, we aimed to assess the effectiveness of temporal speckle averaging optical coherence tomography (TSA-OCT) and dynamic OCT (dOCT) in examining the static and potential dynamic properties of RGCs and RNFL in living mouse eyes. We evaluated parameters such as RNFL thickness and possible dynamics, as well as compared the ganglion cell layer (GCL) soma density obtained from in vivo OCT, fluorescence scanning laser ophthalmoscopy (SLO), and ex vivo histology.

Vibrational sum-frequency generation (VSFG), a second-order nonlinear optical signal, has traditionally been used to study molecules at interfaces as a spectroscopy technique with a spatial resolution of ~100 µm. However, the spectroscopy is not sensitive to the heterogeneity of a sample. To study mesoscopically heterogeneous samples, we, along with others, pushed the resolution limit of VSFG spectroscopy down to ~1 µm level and constructed the VSFG microscope. This imaging technique not only can resolve sample morphologies through imaging, but also record a broadband VSFG spectrum at every pixel of the images. Being a second-order nonlinear optical technique, its selection rule enables the visualization of non-centrosymmetric or chiral self-assembled structures commonly found in biology, materials science, and bioengineering, among others. In this article, the audience will be guided through an inverted transmission design that allows for imaging unfixed samples. This work also showcases that VSFG microscopy can resolve chemical-specific geometric information of individual self-assembled sheets by combining it with a neural network function solver. Lastly, the images obtained under brightfield, SHG, and VSFG configurations of various samples briefly discuss the unique information revealed by VSFG imaging.

Significance: Aquaporins and ion channels establish and regulate gradients of calcium, sodium, potassium, chloride, water, and protons in the epidermis. These elements have been found to play significant roles in skin biology and wound healing. In this study, we review our understanding of these channels and ion gradients, with a special emphasis on their role in acute wound healing. Recent Advances: Specifically, we assess the temporal and spatial arrangements of ions and their respective channels in the intact skin and during wound and healing to provide a novel perspective of the role of ionic gradients through the various stages of wound healing. Critical Issues: The roles of gradients of ions and channels in wound healing are currently not well understood. A collective analysis of their traits and arrangements in the skin during wound healing may provide a new perspective and understanding of the functionality of gradients of ions and channels in skin biology and wound healing. Future Directions: It is important to elucidate how the gradients of ions and ion channels regulate and facilitate wound healing. A better understanding of the ionic environments may identify novel therapeutic targets and improved strategies to promote wound healing and possibly treat other cutaneous diseases.

Pro-preadipocytes are adipocyte progenitor cells within subcutaneous adipose tissue that are conserved in human adipose tissue with distinct cellular energetics. Here, we detail a protocol to quantify cellular oxygen consumption rates of primary human cells harvested from adipose tissue. We describe steps for primary cell expansion, cell seeding, transfection, differentiation, and respirometry followed by Agilent Seahorse Analytics. The measurement of bioenergetic profiles and resulting data further expand our knowledge of the functional properties of primary cells isolated from adipose tissue. For complete details on the use and execution of this protocol, please refer to Chen et al. (2023).1.

ObjectiveCartilage tissue engineering strategies that use autologous chondrocytes require in vitro expansion of cells to obtain enough cells to produce functional engineered tissue. However, chondrocytes dedifferentiate during expansion culture, limiting their ability to produce chondrogenic tissue and their utility for cell-based cartilage repair strategies. The current study identified conditions that favor cartilage production and the mechanobiological mechanisms responsible for these benefits.DesignChondrocytes were isolated from juvenile bovine knee joints and cultured with (primed) or without (unprimed) a growth factor cocktail. Gene expression, cell morphology, cell adhesion, cytoskeletal protein distribution, and cell mechanics were assessed. Following passage 5, cells were embedded into agarose hydrogels to evaluate functional properties of engineered cartilage.ResultsPriming cells during expansion culture altered cell phenotype and chondrogenic tissue production. Unbiased RNA-sequencing analysis suggested, and experimental studies confirmed, that growth factor priming delays dedifferentiation associated changes in cell adhesion and cytoskeletal organization. Priming also overrode mechanobiological pathways to prevent chondrocytes from remodeling their cytoskeleton to accommodate the stiff, monolayer microenvironment. Passage 1 primed cells deformed less and had lower YAP1 activity than unprimed cells. Differences in cell adhesion, morphology, and cell mechanics between primed and unprimed cells were mitigated by passage 5.ConclusionsPriming suppresses mechanobiologic cytoskeletal remodeling to prevent chondrocyte dedifferentiation, resulting in more cartilage-like tissue-engineered constructs.

Tendons are dense connective tissues with relatively few cells which makes studying the molecular profile of the tissue challenging. There is not a consensus on the spatial location of various cell types within a tendon, nor the accompanying transcriptional profile. In the present study, we used two male rat patellar tendon samples for sequencing-based spatial transcriptomics to determine the gene expression profile. We integrated our data with a mouse Achilles single cell dataset to predict the cell type composition of the patellar tendon as a function of location within the tissue. The spatial location of the predicated cell types suggested that there were two populations of tendon fibroblasts, one located in the tendon midsubstance, while the other localized with red blood cells, pericytes, and immune cells to the tendon peripheral connective tissue. Of the highest expressed spatially variable genes, there were multiple genes with known function in tendon: Col1a1, Col1a2, Dcn, Fmod, Sparc, and Comp. Further, a novel spatially regulated gene (AABR07000398.1) with no known function was identified. The spatial gene expression of tendon associated genes (Scx, Thbs4, Tnmd, Can, Bgn, Lum, Adamts2, Lox, Ppib, Col2a1, Col3a1, Col6a2) was also visualized. Both patellar tendon samples had similar expression patterns for all these genes. This dataset provides new spatial insights into gene expression in a healthy tendon.

Understanding the biomechanical behavior of the intervertebral disc is crucial for studying disease mechanisms and developing tissue engineering strategies for managing disc degeneration. We used synchrotron small-angle X-ray scattering to investigate how changes to collagen behavior contribute to alterations in the disc's ability to resist compression. Coccygeal motion segments from 6-month-old lean Sprague-Dawley rats ( n=7) and diabetic obese University of California Davis type 2 diabetes mellitus (UCD-T2DM) rats ( n=6, diabetic for 68±7 days) were compressed during simultaneous synchrotron scanning to measure collagen strain at the nanoscale (beamline 7.3.3 of the Advanced Light Source). After compression, the annulus fibrosus was assayed for nonenzymatic cross-links. In discs from lean rats, resistance to compression involved two main energy-dissipation mechanisms at the nanoscale: (1) rotation of the two groups of collagen fibrils forming the annulus fibrosus and (2) straightening (uncrimping) and stretching of the collagen fibrils. In discs from diabetic rats, both mechanisms were significantly impaired. Specifically, diabetes reduced fibril rotation by 31% and reduced collagen fibril strain by 30% (compared to lean discs). The stiffening of collagen fibrils in the discs from diabetic rats was consistent with a 31% higher concentration of nonenzymatic cross-links and with evidence of earlier onset plastic deformations such as fibril sliding and fibril-matrix delamination. These findings suggest that fibril reorientation, stretching, and straightening are key deformation mechanisms that facilitate whole-disc compression, and that type 2 diabetes impairs these efficient and low-energy elastic deformation mechanisms, thereby altering whole-disc behavior and inducing the earlier onset of plastic deformation.