The dawn of a new Era: mRNA vaccines in colorectal cancer immunotherapy

Colorectal cancer (CRC) is a typical cancer that accounts for 10% of all new cancer cases annually and nearly 10% of all cancer deaths. Despite significant progress in current classical interventions for CRC, these traditional strategies could be invasive and with numerous adverse effects. The poor prognosis of CRC patients highlights the evident and pressing need for more efficient and targeted treatment. Novel strategies regarding mRNA vaccines for anti-tumor therapy have also been well-developed since the successful application for the prevention of COVID-19. mRNA vaccine technology won the 2023 Nobel Prize in Physiology or Medicine, signaling a new direction in human anti-cancer treatment: mRNA medicine. As a promising new immunotherapy in CRC and other multiple cancer treatments, the mRNA vaccine has higher specificity, better efficacy, and fewer side effects than traditional strategies. The present review outlines the basics of mRNA vaccines and their advantages over other vaccines and informs an available strategy for developing efficient mRNA vaccines for CRC precise treatment. In the future, more exploration of mRNA vaccines for CRC shall be attached, fostering innovation to address existing limitations.

Engineering an artificial catch bond using mechanical anisotropy

Catch bonds are a rare class of protein-protein interactions where the bond lifetime increases under an external pulling force. Here, we report how modification of anchor geometry generates catch bonding behavior for the mechanostable Dockerin G:Cohesin E (DocG:CohE) adhesion complex found on human gut bacteria. Using AFM single-molecule force spectroscopy in combination with bioorthogonal click chemistry, we mechanically dissociate the complex using five precisely controlled anchor geometries. When tension is applied between residue #13 on CohE and the N-terminus of DocG, the complex behaves as a two-state catch bond, while in all other tested pulling geometries, including the native configuration, it behaves as a slip bond. We use a kinetic Monte Carlo model with experimentally derived parameters to simulate rupture force and lifetime distributions, achieving strong agreement with experiments. Single-molecule FRET measurements further demonstrate that the complex does not exhibit dual binding mode behavior at equilibrium but unbinds along multiple pathways under force. Together, these results show how mechanical anisotropy and anchor point selection can be used to engineer artificial catch bonds.

pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis

Objective.Photoplethysmography is a non-invasive optical technique that measures changes in blood volume within tissues. It is commonly and being increasingly used for a variety of research and clinical applications to assess vascular dynamics and physiological parameters. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and limited open tools exist for continuous photoplethysmogram (PPG) analysis. Consequently, the primary objective of this research was to identify, standardize, implement and validate key digital PPG biomarkers.Approach.This work describes the creation of a standard Python toolbox, denotedpyPPG, for long-term continuous PPG time-series analysis and demonstrates the detection and computation of a high number of fiducial points and digital biomarkers using a standard fingerbased transmission pulse oximeter.Main results.The improved PPG peak detector had an F1-score of 88.19% for the state-of-the-art benchmark when evaluated on 2054 adult polysomnography recordings totaling over 91 million reference beats. The algorithm outperformed the open-source original Matlab implementation by ∼5% when benchmarked on a subset of 100 randomly selected MESA recordings. More than 3000 fiducial points were manually annotated by two annotators in order to validate the fiducial points detector. The detector consistently demonstrated high performance, with a mean absolute error of less than 10 ms for all fiducial points.Significance.Based on these fiducial points,pyPPGengineered a set of 74 PPG biomarkers. Studying PPG time-series variability usingpyPPGcan enhance our understanding of the manifestations and etiology of diseases. This toolbox can also be used for biomarker engineering in training data-driven models.pyPPGis available onhttps://physiozoo.com/.

DeepLoc 2.1: multi-label membrane protein type prediction using protein language models

DeepLoc 2.0 is a popular web server for the prediction of protein subcellular localization and sorting signals. Here, we introduce DeepLoc 2.1, which additionally classifies the input proteins into the membrane protein types Transmembrane, Peripheral, Lipid-anchored and Soluble. Leveraging pre-trained transformer-based protein language models, the server utilizes a three-stage architecture for sequence-based, multi-label predictions. Comparative evaluations with other established tools on a test set of 4933 eukaryotic protein sequences, constructed following stringent homology partitioning, demonstrate state-of-the-art performance. Notably, DeepLoc 2.1 outperforms existing models, with the larger ProtT5 model exhibiting a marginal advantage over the ESM-1B model. The web server is available at https://services.healthtech.dtu.dk/services/DeepLoc-2.1.

Engineering Antigen-Specific Tolerance to an Artificial Protein Hydrogel

Artificial protein hydrogels are an emerging class of biomaterials with numerous prospective applications in tissue engineering and regenerative medicine. These materials are likely to be immunogenic due to their frequent incorporation of novel amino acid sequence domains, which often serve a functional role within the material itself. We engineered injectable "self" and "nonself" artificial protein hydrogels, which were predicted to have divergent immune outcomes in vivo on the basis of their primary amino acid sequence. Following implantation in mouse, the nonself gels raised significantly higher antigel antibody titers than the corresponding self gels. Prophylactic administration of a fusion antibody targeting the nonself hydrogel epitopes to DEC-205, an endocytic receptor involved in Treg induction, fully suppressed the elevated antibody titer against the nonself gels. These results suggest that the clinical immune response to artificial protein biomaterials, including those that contain highly antigenic sequence domains, can be tuned through the induction of antigen-specific tolerance.

Survival-Associated Cellular Response Maintained in Pancreatic Ductal Adenocarcinoma (PDAC) Switched Between Soft and Stiff 3D Microgel Culture

Pancreatic ductal adenocarcinoma (PDAC) accounts for about 90% of all pancreatic cancer cases. Five-year survival rates have remained below 12% since the 1970s, in part due to the difficulty in detection prior to metastasis (migration and invasion into neighboring organs and glands). Mechanical memory is a concept that has emerged over the past decade that may provide a path toward understanding how invading PDAC cells "remember" the mechanical properties of their diseased ("stiff", elastic modulus, E ≈ 10 kPa) microenvironment even while invading a healthy ("soft", E ≈ 1 kPa) microenvironment. Here, we investigated the role of mechanical priming by culturing a dilute suspension of PDAC (FG) cells within a 3D, rheologically tunable microgel platform from hydrogels with tunable mechanical properties. We conducted a suite of acute (short-term) priming studies where we cultured PDAC cells in either a soft (E ≈ 1 kPa) or stiff (E ≈ 10 kPa) environment for 6 h, then removed and placed them into a new soft or stiff 3D environment for another 18 h. Following these steps, we conducted RNA-seq analyses to quantify gene expression. Initial priming in the 3D culture showed persistent gene expression for the duration of the study, regardless of the subsequent environments (stiff or soft). Stiff 3D culture was associated with the downregulation of tumor suppressors (LATS1, BCAR3, CDKN2C), as well as the upregulation of cancer-associated genes (RAC3). Immunofluorescence staining (BCAR3, RAC3) further supported the persistence of this cellular response, with BCAR3 upregulated in soft culture and RAC3 upregulated in stiff-primed culture. Stiff-primed genes were stratified against patient data found in The Cancer Genome Atlas (TCGA). Upregulated genes in stiff-primed 3D culture were associated with decreased survival in patient data, suggesting a link between patient survival and mechanical priming.

Clinical application of robots in dentistry: A scoping review

PURPOSE

The surge in digitalization and artificial intelligence has led to the wide application of robots in various fields, but their application in dentistry started relatively late. This scoping review aimed to comprehensively explore and map the current status of the clinical application of robots in dentistry.

STUDY SELECTION

An iterative approach was used to gather as much evidence as possible from four online databases, including PubMed, the China National Knowledge Infrastructure, the Japan Science and Technology Information Aggregator, Electronic, and the Institute of Electrical and Electronics Engineers, from January 1980 to December 2022.

RESULTS

A total of 113 eligible articles were selected from the search results, and it was found that most of the robots were developed and applied in the United States (n = 56; 50%). Robots were clinically applied in oral and maxillofacial surgery, oral implantology, prosthodontics, orthodontics, endodontics, and oral medicine. The development of robots in oral and maxillofacial surgery and oral implantology is relatively fast and comprehensive. About 51% (n = 58) of the systems had reached clinical application, while 49% (n = 55) were at the pre-clinical stage. Most of these are hard robots (90%; n = 103), and their invention and development were mainly focused on university research groups with long research periods and diverse components.

CONCLUSIONS

There are still limitations and gaps between research and application in dental robots. While robotics is threatening to replace clinical decision-making, combining it with dentistry to gain maximum benefit remains a challenge for the future.

Biomechanics of the Human Osteochondral Unit: A Systematic Review

The damping system ensured by the osteochondral (OC) unit is essential to deploy the forces generated within load-bearing joints during locomotion, allowing furthermore low-friction sliding motion between bone segments. The OC unit is a multi-layer structure including articular cartilage, as well as subchondral and trabecular bone. The interplay between the OC tissues is essential in maintaining the joint functionality; altered loading patterns can trigger biological processes that could lead to degenerative joint diseases like osteoarthritis. Currently, no effective treatments are available to avoid degeneration beyond tissues' recovery capabilities. A thorough comprehension on the mechanical behaviour of the OC unit is essential to (i) soundly elucidate its overall response to intra-articular loads for developing diagnostic tools capable of detecting non-physiological strain levels, (ii) properly evaluate the efficacy of innovative treatments in restoring physiological strain levels, and (iii) optimize regenerative medicine approaches as potential and less-invasive alternatives to arthroplasty when irreversible damage has occurred. Therefore, the leading aim of this review was to provide an overview of the state-of-the-art-up to 2022-about the mechanical behaviour of the OC unit. A systematic search is performed, according to PRISMA standards, by focusing on studies that experimentally assess the human lower-limb joints' OC tissues. A multi-criteria decision-making method is proposed to quantitatively evaluate eligible studies, in order to highlight only the insights retrieved through sound and robust approaches. This review revealed that studies on human lower limbs are focusing on the knee and articular cartilage, while hip and trabecular bone studies are declining, and the ankle and subchondral bone are poorly investigated. Compression and indentation are the most common experimental techniques studying the mechanical behaviour of the OC tissues, with indentation also being able to provide information at the micro- and nanoscales. While a certain comparability among studies was highlighted, none of the identified testing protocols are currently recognised as standard for any of the OC tissues. The fibril-network-reinforced poro-viscoelastic constitutive model has become common for describing the response of the articular cartilage, while the models describing the mechanical behaviour of mineralised tissues are usually simpler (i.e., linear elastic, elasto-plastic). Most advanced studies have tested and modelled multiple tissues of the same OC unit but have done so individually rather than through integrated approaches. Therefore, efforts should be made in simultaneously evaluating the comprehensive response of the OC unit to intra-articular loads and the interplay between the OC tissues. In this regard, a multidisciplinary approach combining complementary techniques, e.g., full-field imaging, mechanical testing, and computational approaches, should be implemented and validated. Furthermore, the next challenge entails transferring this assessment to a non-invasive approach, allowing its application in vivo, in order to increase its diagnostic and prognostic potential.

Towards developing a matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) compatible tissue expansion protocol

Mass spectrometry imaging (MSI) visualizes spatial distribution of molecules in a biological tissue. However, compared with traditional microscopy-based imaging, conventional MSI is limited to its spatial resolution, resulting in difficulties in identifying detailed tissue morphological characters, such as lesion boundary or nanoscale structures. On the other hand, expansion microscopy, a tissue expansion method widely used in optical imaging to improve morphological details, has great potential to solve insufficient spatial resolution in mass spectrometry imaging (MSI). However, expansion microscopy was not originally designed for MSI, resulting in problems while combining expansion microscopy and MSI such as expanded sample fragility, vacuum stability and molecule loss during sample preparation. In this research we developed a MALDI MSI compatible expansion protocol by adjusting sample preparation methods during tissue expansion, successfully combining expansion microscopy with MSI. After tissue expansion the expanded sample can be readily applied to MALDI MSI sample preparation and further data acquisition. The MALDI MSI compatible expansion protocol has great potential to be widely applied in MALDI MSI sample preparation to facilitate improvement of MSI spatial resolution.

Cognitive effort detection for tele-robotic surgery via personalized pupil response modeling

PURPOSE

Gaze tracking and pupillometry are established proxies for cognitive load, giving insights into a user's mental effort. In tele-robotic surgery, knowing a user's cognitive load can inspire novel human-machine interaction designs, fostering contextual surgical assistance systems and personalized training programs. While pupillometry-based methods for estimating cognitive effort have been proposed, their application in surgery is limited by the pupil's sensitivity to brightness changes, which can mask pupil's response to cognitive load. Thus, methods considering pupil and brightness conditions are essential for detecting cognitive effort in unconstrained scenarios.

METHODS

To contend with this challenge, we introduce a personalized pupil response model integrating pupil and brightness-based features. Discrepancies between predicted and measured pupil diameter indicate dilations due to non-brightness-related sources, i.e., cognitive effort. Combined with gaze entropy, it can detect cognitive load using a random forest classifier. To test our model, we perform a user study with the da Vinci Research Kit, where 17 users perform pick-and-place tasks in addition to auditory tasks known to generate cognitive effort responses.

RESULTS

We compare our method to two baselines (BCPD and CPD), demonstrating favorable performance in varying brightness conditions. Our method achieves an average true positive rate of 0.78, outperforming the baselines (0.57 and 0.64).

CONCLUSION

We present a personalized brightness-aware model for cognitive effort detection able to operate under unconstrained brightness conditions, comparing favorably to competing approaches, contributing to the advancement of cognitive effort detection in tele-robotic surgery. Future work will consider alternative learning strategies, handling the difficult positive-unlabeled scenario in user studies, where only some positive and no negative events are reliably known.

A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes

BACKGROUND AND PURPOSE

Predicting long-term clinical outcome in acute ischemic stroke is beneficial for prognosis, clinical trial design, resource management, and patient expectations. This study used a deep learning-based predictive model (DLPD) to predict 90-day mRS outcomes and compared its predictions with those made by physicians.

MATERIALS AND METHODS

A previously developed DLPD that incorporated DWI and clinical data from the acute period was used to predict 90-day mRS outcomes in 80 consecutive patients with acute ischemic stroke from a single-center registry. We assessed the predictions of the model alongside those of 5 physicians (2 stroke neurologists and 3 neuroradiologists provided with the same imaging and clinical information). The primary analysis was the agreement between the ordinal mRS predictions of the model or physician and the ground truth using the Gwet Agreement Coefficient. We also evaluated the ability to identify unfavorable outcomes (mRS >2) using the area under the curve, sensitivity, and specificity. Noninferiority analyses were undertaken using limits of 0.1 for the Gwet Agreement Coefficient and 0.05 for the area under the curve analysis. The accuracy of prediction was also assessed using the mean absolute error for prediction, percentage of predictions ±1 categories away from the ground truth (±1 accuracy [ACC]), and percentage of exact predictions (ACC).

RESULTS

To predict the specific mRS score, the DLPD yielded a Gwet Agreement Coefficient score of 0.79 (95% CI, 0.71-0.86), surpassing the physicians' score of 0.76 (95% CI, 0.67-0.84), and was noninferior to the readers (P < .001). For identifying unfavorable outcome, the model achieved an area under the curve of 0.81 (95% CI, 0.72-0.89), again noninferior to the readers' area under the curve of 0.79 (95% CI, 0.69-0.87) (P < .005). The mean absolute error, ±1ACC, and ACC were 0.89, 81%, and 36% for the DLPD.

CONCLUSIONS

A deep learning method using acute clinical and imaging data for long-term functional outcome prediction in patients with acute ischemic stroke, the DLPD, was noninferior to that of clinical readers.

Recent Progress in Peptide-Based Molecular Probes for Disease Bioimaging

Recent strides in molecular pathology have unveiled distinctive alterations at the molecular level throughout the onset and progression of diseases. Enhancing the in vivo visualization of these biomarkers is crucial for advancing disease classification, staging, and treatment strategies. Peptide-based molecular probes (PMPs) have emerged as versatile tools due to their exceptional ability to discern these molecular changes with unparalleled specificity and precision. In this Perspective, we first summarize the methodologies for crafting innovative functional peptides, emphasizing recent advancements in both peptide library technologies and computer-assisted peptide design approaches. Furthermore, we offer an overview of the latest advances in PMPs within the realm of biological imaging, showcasing their varied applications in diagnostic and therapeutic modalities. We also briefly address current challenges and potential future directions in this dynamic field.

Strongly Adhesive, Self-Healing, Hemostatic Hydrogel for the Repair of Traumatic Brain Injury

With wide clinical demands, therapies for traumatic brain injury (TBI) are a major problem in surgical procedures and after major trauma. Due to the difficulty in regeneration of neurons or axons after injury, as well as the inhibition of blood vessel growth by the formation of neural scars, existing treatment measures have limited effectiveness in repairing brain tissue. Herein, the biomultifunctional hydrogels are developed for TBI treatment based on the Schiff base reaction of calcium ion (Ca2+)-cross-linked oxidized sodium alginate (OSA) and carboxymethyl chitosan (CMCS). The obtained COCS hydrogel exhibits excellent adhesion to wet tissues, self-repair capability, and antimicrobial properties. What's particularly interesting is that the addition of Ca2+ increases the hydrogel's extensibility, enhancing its hemostatic capabilities. Biological assessments indicate that the COCS hydrogel demonstrates excellent biocompatibility, hemostatic properties, and the ability to promote arterial vessel repair. Importantly, the COCS hydrogel promotes the growth of cerebral microvessels by upregulating CD31, accelerates the proliferation of astrocytes, enhances the expression of GFAP, and stimulates the expression of neuron-specific markers such as NEUN and β-tubulin. All of these findings highlight that the strongly adhesive, self-healing, hemostatic hydrogel shows great potential for the repair of traumatic brain injury and other tissue repair therapy.

Magnetic Flux Sensor Based on Spiking Neurons with Josephson Junctions

Josephson junctions (JJs) are superconductor-based devices used to build highly sensitive magnetic flux sensors called superconducting quantum interference devices (SQUIDs). These sensors may vary in design, being the radio frequency (RF) SQUID, direct current (DC) SQUID, and hybrid, such as D-SQUID. In addition, recently many of JJ's applications were found in spiking models of neurons exhibiting nearly biological behavior. In this study, we propose and investigate a new circuit model of a sensory neuron based on DC SQUID as part of the circuit. The dependence of the dynamics of the designed model on the external magnetic flux is demonstrated. The design of the circuit and derivation of the corresponding differential equations that describe the dynamics of the system are given. Numerical simulation is used for experimental evaluation. The experimental results confirm the applicability and good performance of the proposed magnetic-flux-sensitive neuron concept: the considered device can encode the magnetic flux in the form of neuronal dynamics with the linear section. Furthermore, some complex behavior was discovered in the model, namely the intermittent chaotic spiking and plateau bursting. The proposed design can be efficiently applied to developing the interfaces between circuitry and spiking neural networks. However, it should be noted that the proposed neuron design shares the main limitation of all the superconductor-based technologies, i.e., the need for a cryogenic and shielding system.

Generation and characterization of a nanobody against the avian influenza virus H7 subtype

Avian influenza virus (AIV) H7N9 diseases have been recently reported, raising concerns about a potential pandemic. Thus, there is an urgent need for effective therapeutics for AIV H7N9 infections. Herein, camelid immunization and yeast two-hybrid techniques were used to identify potent neutralizing nanobodies (Nbs) targeting the H7 subtype hemagglutinin. First, we evaluated the binding specificity and hemagglutination inhibition activity of the screened Nbs against the H7 subtype hemagglutinin. Nb-Z77, with high hemagglutination inhibition activity was selected from the screened Nbs to optimize the yeast expression conditions and construct oligomeric forms of Nb-Z77 using various ligation methods. The oligomers Nb-Z77-DiGS, Nb-Z77-TriGS, Nb-Z77-Fc and Nb-Z77-Foldon were successfully constructed and expressed. Nb-Z77-DiGS and Nb-Z77-Foldon exhibited considerably greater activity than did Nb-Z77 against H7 subtype hemagglutinin, with median effective concentrations of 384.7 and 27.33 pM and binding affinity values of 213 and 5.21 pM, respectively. Nb-Z77-DiGS and Nb-Z77-Foldon completely inhibited the hemagglutination activity of the inactivated virus H7-Re1 at the lowest concentration of 0.938 μg/mL. This study screened a strain of Nb with high hemagglutination inhibition activity and enhanced its antiviral activity through oligomerization, which may have great potential for developing effective agents for the prevention, diagnosis, and treatment of AIV H7 subtype infection.

Synergistic effects of graphene microgrooves and electrical stimulation on M2 macrophage polarization

Macrophages play a crucial role in host response and wound healing, with M2 polarization contributing to the reduction of foreign-body reactions induced by the implantation of biomaterials and promoting tissue regeneration. Electrical stimulation (ES) and micropatterned substrates have a significant impact on the macrophage polarization. However, there is currently a lack of well-established cell culture platforms for studying the synergistic effects of these two factors. In this study, we prepared a graphene free-standing substrate with 20 μm microgrooves using capillary forces induced by water evaporation. Subsequently, we established an ES cell culture platform for macrophage cultivation by integrating a self-designed multi-well chamber cell culture device. We observed that graphene microgrooves, in combination with ES, significantly reduce cell spreading area and circularity. Results from immunofluorescence, ELISA, and flow cytometry demonstrate that the synergistic effect of graphene microgrooves and ES effectively promotes macrophage M2 phenotypic polarization. Finally, RNA sequencing results reveal that the synergistic effects of ES and graphene microgrooves inhibit the macrophage actin polymerization and the downstream PI3K signaling pathway, thereby influencing the phenotypic transition. Our results demonstrate the potential of graphene-based microgrooves and ES to synergistically modulate macrophage polarization, offering promising applications in regenerative medicine.

Bridging the Gap in Cryopreservation Mechanism: Unraveling the Interplay between Structure, Dynamics, and Thermodynamics in Cryoprotectant Aqueous Solutions

Cryoprotectants play a crucial role in preserving biological material, ensuring their viability during storage and facilitating crucial applications such as the conservation of medical compounds, tissues, and organs for transplantation. However, the precise mechanism by which cryoprotectants modulate the thermodynamic properties of water to impede the formation and growth of ice crystals, thus preventing long-term damage, remains elusive. This is evident in the use of empirically optimized recipes for mixtures that typically contain DMSO, glycerol, and various sugar constituents. Here, we use terahertz calorimetry, Overhauser nuclear polarization, and molecular dynamics simulations to show that DMSO exhibits a robust structuring effect on water around its methyl groups, reaching a maximum at a DMSO mole fraction of XDMSO = 0.33. In contrast, glycerol exerts a smaller water-structuring effect, even at higher concentrations (Scheme 1). These results potentially suggest that the wrapped water around DMSO's methyl group, which can be evicted upon ligand binding, may render DMSO a more surface-active cryoprotectant than glycerol, while glycerol may participate more as a viscogen that acts on the entire sample. These findings shed light on the molecular intricacies of cryoprotectant solvation behavior and have potentially significant implications for optimizing cryopreservation protocols.

Melt Electrowriting Combined with Fused Deposition Modeling Printing for the Fabrication of Three-Dimensional Biomimetic Scaffolds for Osteotendinous Junction Regeneration

Purpose

This study aims to explore a novel scaffold for osteotendinous junction regeneration and to preliminarily verify its osteogenic and tenogenic abilities in vitro.

Methods

A polycaprolactone (PCL) scaffold with aligned and orthogonal fibers was created using melt electrowriting (MEW) and fused deposition modeling (FDM). The scaffold was coated with Type I collagen, and hydroxyapatite was carefully added to separate the regions intended for bone and tendon regeneration, before being rolled into a cylindrical shape. Human adipose-derived stem cells (hADSCs) were seeded to evaluate viability and differentiation. Scaffold characterization was performed with Scanning Electron Microscope (SEM). Osteogenesis was assessed by alkaline phosphatase (ALP) and Alizarin red staining, while immunostaining and transcription-quantitative polymerase chain reaction (RT-qPCR) evaluated osteogenic and tendogenic markers.

Results

Scaffolds were developed in four variations: aligned (A), collagen-coated aligned (A+C), orthogonal (O), and mineral-coated orthogonal (O+M). SEM analysis confirmed surface morphology and energy-dispersive X-ray spectroscopy (EDS) verified mineral coating on O+M types. Hydrophilicity and mechanical properties were optimized in modified scaffolds, with A+C showing increased tensile strength and O+M improved in compression. hADSCs demonstrated good viability and morphology across scaffolds, withO+M scaffolds showing higher cell proliferation and osteogenic potential, and A and A+C scaffolds supporting tenogenic differentiation.

Conclusion

This study confirms the potential of a novel PCL scaffold with distinct regions for osteogenic and tenogenic differentiation, supporting the regeneration of osteotendinous junctions in vitro.

Evaluation of sweat-based biomarkers using wearable biosensors for monitoring stress and fatigue: a systematic review

Objectives. This systematic review aims to report the evaluation of wearable biosensors for the real-time measurement of stress and fatigue using sweat biomarkers. Methods. A thorough search of the literature was carried out in databases such as PubMed, Web of Science and IEEE. A three-step approach for selecting research articles was developed and implemented. Results. Based on a systematic search, a total of 17 articles were included in this review. Lactate, cortisol, glucose and electrolytes were identified as sweat biomarkers. Sweat-based biomarkers are frequently monitored in real time using potentiometric and amperometric biosensors. Wearable biosensors such as an epidermal patch or a sweatband have been widely validated in scientific literature. Conclusions. Sweat is an important biofluid for monitoring general health, including stress and fatigue. It is becoming increasingly common to use biosensors that can measure a wide range of sweat biomarkers to detect fatigue during high-intensity work. Even though wearable biosensors have been validated for monitoring various sweat biomarkers, such biomarkers can only be used to assess stress and fatigue indirectly. In general, this study may serve as a driving force for academics and practitioners to broaden the use of wearable biosensors for the real-time assessment of stress and fatigue.

Fundamental, mechanism and development of hydration lubrication: From bio-inspiration to artificial manufacturing

Friction and lubrication are ubiquitous in all kinds of movements and play a vital role in the smooth operation of production machinery. Water is indispensable both in the lubrication systems of natural organisms and in hydration lubrication systems. There exists a high degree of similarity between these systems, which has driven the development of hydration lubrication from biomimetic to artificial manufacturing. In particular, significant advancements have been made in the understanding of the mechanisms of hydration lubrication over the past 30 years. This enhanced understanding has further stimulated the exploration of biomimetic inspiration from natural hydration lubrication systems, to develop novel artificial hydration lubrication systems that are cost-effective, easily transportable, and possess excellent capability. This review summarizes the recent experimental and theoretical advances in the understanding of hydration-lubrication processes. The entire paper is divided into three parts. Firstly, surface interactions relevant to hydration lubrication are discussed, encompassing topics such as hydrogen bonding, hydration layer, electric double layer force, hydration force, and Stribeck curve. The second part begins with an introduction to articular cartilage in biomaterial lubrication, discussing its compositional structure and lubrication mechanisms. Subsequently, three major categories of bio-inspired artificial manufacturing lubricating material systems are presented, including hydrogels, polymer brushes (e.g., neutral, positive, negative and zwitterionic brushes), hydration lubricant additives (e.g., nano-particles, polymers, ionic liquids), and their related lubrication mechanism is also described. Finally, the challenges and perspectives for hydration lubrication research and materials development are presented.

Magnetic biocomposite scaffold based on decellularized tendon ECM and MNP-deposited halloysite nanotubes: physicochemical, thermal, rheological, mechanical andin vitrobiological evaluations

The development of new three-dimensional biomaterials with advanced versatile properties is critical to the success of tissue engineering (TE) applications. Here, (a) bioactive decellularized tendon extracellular matrix (dECM) with a sol-gel transition feature at physiological temperature, (b) halloysite nanotubes (HNT) with known mechanical properties and bioactivity, and (c) magnetic nanoparticles (MNP) with superparamagnetic and osteogenic properties were combined to develop a new scaffold that could be used in prospective bone TE applications. Deposition of MNPs on HNTs resulted in magnetic nanostructures without agglomeration of MNPs. A completely cell-free, collagen- and glycosaminoglycan- rich dECM was obtained and characterized. dECM-based scaffolds incorporated with 1%, 2% and 4% MNP-HNT were analysed for their physical, chemical, andin vitrobiological properties. Fourier-transform infrared spectroscopy, x-ray powder diffractometry and vibrating sample magnetometry analyses confirmed the presence of dECM, HNT and MNP in all scaffold types. The capacity to form apatite layer upon incubation in simulated body fluid revealed that dECM-MNP-HNT is a bioactive material. Combining dECM with MNP-HNT improved the thermal stability and compressive strength of the macroporous scaffolds upto 2% MNP-HNT.In vitrocytotoxicity and hemolysis experiments showed that the scaffolds were essentially biocompatible. Human bone marrow mesenchymal stem cells adhered and proliferated well on the macroporous constructs containing 1% and 2% MNP-HNT; and remained metabolically active for at least 21 din vitro. Collectively, the findings support the idea that magnetic nanocomposite dECM scaffolds containing MNP-HNT could be a potential template for TE applications.

Quantifying the Lymphatic Transport of Model Therapeutics from the Brain in Rats

In recent years, the drainage of fluids, immune cells, antigens, fluorescent tracers, and other solutes from the brain has been demonstrated to occur along lymphatic outflow pathways to the deep cervical lymph nodes in the neck. To the best of our knowledge, no studies have evaluated the lymphatic transport of therapeutics from the brain. The objective of this study was to determine the lymphatic transport of model therapeutics of different molecular weights and lipophilicity from the brain using cervical lymph cannulation and ligation models in rats. To do this, anesthetized Sprague-Dawley rats were cannulated at the carotid artery and cannulated, ligated, or left intact at the cervical lymph duct. Rats were administered 14C-ibuprofen (206.29 g/mol, logP 3.84), 3H-halofantrine HCl (536.89 g/mol, logP 8.06), or 3H-albumin (∼65,000 g/mol) via direct injection into the brain striatum at a rate of 0.5 μL/min over 16 min. Plasma or cervical lymph samples were collected for up to 6-8 h following dosing, and brain and lymph nodes were collected at 6 or 8 h. Samples were subsequently analyzed for radioactivity levels via scintillation counting. For 14C-ibuprofen, plasma concentrations over time (plasma AUC0-6h) were >2 fold higher in lymph-ligated rats than in lymph-intact rats, suggesting that ibuprofen is cleared from the brain primarily via nonlymphatic routes (e.g., across the blood-brain barrier) but that this clearance is influenced by changes in lymphatic flow. For 3H-halofantrine, >73% of the dose was retained at the brain dosing site in lymph-intact and lymph-ligated groups, and plasma AUC0-8h values were low in both groups (<0.3% dose.h/mL), consistent with the high retention in the brain. It was therefore not possible to determine whether halofantrine undergoes lymphatic transport from the brain within the duration of the study. For 3H-albumin, plasma AUC0-8h values were not significantly different between lymph-intact, lymph-ligated, and lymph-cannulated rats. However, >4% of the dose was recovered in cervical lymph over 8 h. Lymph/plasma concentration ratios of 3H-albumin were also very high (up to 53:1). Together, these results indicate that 3H-albumin is transported from the brain not only via lymphatic routes but also via the blood. Similar to other tissues, the lymphatics may thus play a significant role in the transport of macromolecules, including therapeutic proteins, from the brain but are unlikely to be a major transport pathway from the brain for small molecule drugs that are not lipophilic. Our rat cervical lymph cannulation model can be used to quantify the lymphatic drainage of different molecules and factors from the brain.

Bioelectric stimulation controls tissue shape and size

Epithelial tissues sheath organs and electro-mechanically regulate ion and water transport to regulate development, homeostasis, and hydrostatic organ pressure. Here, we demonstrate how external electrical stimulation allows us to control these processes in living tissues. Specifically, we electrically stimulate hollow, 3D kidneyoids and gut organoids and find that physiological-strength electrical stimulation of ∼ 5 - 10 V/cm powerfully inflates hollow tissues; a process we call electro-inflation. Electro-inflation is mediated by increased ion flux through ion channels/transporters and triggers subsequent osmotic water flow into the lumen, generating hydrostatic pressure that competes against cytoskeletal tension. Our computational studies suggest that electro-inflation is strongly driven by field-induced ion crowding on the outer surface of the tissue. Electrically stimulated tissues also break symmetry in 3D resulting from electrotaxis and affecting tissue shape. The ability of electrical cues to regulate tissue size and shape emphasizes the role and importance of the electrical micro-environment for living tissues.

Role of immunotherapies and stem cell therapy in the management of liver cancer: A comprehensive review

Liver cancer (LC) is the sixth most common disease and the third most common cause of cancer-related mortality. The WHO predicts that more than 1 million deaths will occur from LC by 2030. Hepatocellular carcinoma (HCC) is a common form of primary LC. Today, the management of LC involves multiple disciplines, and multimodal therapy is typically selected on an individual basis, considering the intricate interactions between the patient's overall health, the stage of the tumor, and the degree of underlying liver disease. Currently, the treatment of cancers, including LC, has undergone a paradigm shift in the last ten years because of immuno-oncology. To treat HCC, immune therapy approaches have been developed to enhance or cause the body's natural immune response to specifically target tumor cells. In this context, immune checkpoint pathway inhibitors, engineered cytokines, adoptive cell therapy, immune cells modified with chimeric antigen receptors, and therapeutic cancer vaccines have advanced to clinical trials and offered new hope to cancer patients. The outcomes of these treatments are encouraging. Additionally, treatment using stem cells is a new approach for restoring deteriorated tissues because of their strong differentiation potential and capacity to release cytokines that encourage cell division and the formation of blood vessels. Although there is no proof that stem cell therapy works for many types of cancer, preclinical research on stem cells has shown promise in treating HCC. This review provides a recent update regarding the impact of immunotherapy and stem cells in HCC and promising outcomes.

Tumor microenvironment reprogramming combined with immunogenic enhancement by nanoemulsions potentiates immunotherapy

The combination of immune checkpoint inhibitors and immunogenic cell death (ICD) inducers has become a promising strategy for the treatment of various cancers. However, its efficacy remains unmet because of the dense stroma and defective vasculatures in the tumor microenvironment (TME) that restricts the intratumoral infiltration of cytotoxic T lymphocytes (CTLs). Herein, cancer-associated fibroblasts (CAFs)-targeted nanoemulsions are tailored to combine the ICD induction and the TME reprogramming to sensitize checkpoint blockade immunotherapy. Melittin, as an ICD inducer and an antifibrotic agent, is efficiently encapsulated into the nanoemulsion accompanied by a nitric oxide donor to improve its bioavailability and tumor targeting. The nanoemulsions exhibited dual functionality by directly inducing direct cancer cell death and enhancing the tumoral immunogenicity, while also synergistically reprogramming the TME through reversing the activated CAFs, decreasing collagen deposition and restoring tumor vessels. Consequently, these nanemulsions successfully facilitated the CTLs infiltration and suppressing the recruitment of immunosuppressive cells. A combination of AE-MGNPs and anti-CTLA-4 antibody greatly elicited a striking level of antitumor T-cell response to suppress tumor growth in CAFs-rich colorectal tumor models. Our work emphasized the integration of the ICD induction with simultaneous modulation of the TME to enhance the sensitivity of patients to checkpoint blockade immunotherapy.

Chitosan-based hybrid nanospheres for vessel normalization towards enhancing tumor chemotherapy

Vessel normalization has proved imperative in tumor growth inhibition. In this work, biopolymer-based hybrid nanospheres capable of normalizing blood vessels were designed to improve the therapeutic effect of chemotherapeutic drugs. Zn0.4Fe2.6O4 nanoparticles (ZFO NPs) were synthesized, and were encapsulated in cross-inked chitosan (CS) along with a nitric oxide (NO) precursor, DETA NONOate, forming hybrid ZFO/NO@CS nanospheres highly stable in physiological environment. The structure, morphology and size of the nanospheres were characterized. The ZFO/NO@CS nanospheres could release NO under acidic conditions typical of intratumoral and intracellular environment. The results of related factors expression, wound healing and tube formation assays demonstrated that both the encapsulated ZFO NPs and the released NO were able to inhibit angiogenesis in tumors. The ZFO/NO@CS nanospheres enhanced the antitumor efficacy of the chemotherapeutic drug DOX by normalizing tumor vessels, as evidenced by in vivo experiments for CT26 tumor-bearing mice. By analyzing the contents of Fe in the tumor and different organs, the nanospheres were found to accumulate primarily at the tumor site. The blood analysis showed little side effect of the nanospheres. The ZFO/NO@CS nanospheres have great potential in improving tumor therapeutic effect when used in combination with chemotherapeutic drugs.

Redefining hyperviscosity in acute leukemia: Potential implications for red cell transfusions in the microvasculature

Hyperleukocytosis is an emergency of acute leukemia leading to blood hyperviscosity, potentially resulting in life-threatening microvascular obstruction, or leukostasis. Due to the high number of red cells in the circulation, hematocrit/hemoglobin levels (Hct/Hgb) are major drivers of blood viscosity, but how Hct/Hgb mediates hyperviscosity in acute leukemia remains unknown. In vivo hemorheological studies are difficult to conduct and interpret due to issues related to visualizing and manipulating the microvasculature. To that end, a multi-vessel microfluidic device recapitulating the size-scale and geometry of the microvasculature was designed to investigate how Hct/Hgb interacts with acute leukemia to induce "in vitro" leukostasis. Using patient samples and cell lines, the degree of leukostasis was different among leukemia immunophenotypes with respect to white blood cell (WBC) count and Hct/Hgb. Among lymphoid immunophenotypes, severe anemia is protective against in vitro leukostasis and Hct/Hgb thresholds became apparent above which in vitro leukostasis significantly increased, to a greater extent with B-cell acute lymphoblastic leukemia (ALL) versus T-cell ALL. In vitro leukostasis in acute myeloid leukemia was primarily driven by WBC with little interaction with Hct/Hgb. This sets the stage for prospective clinical studies assessing how red cell transfusion may affect leukostasis risk in immunophenotypically different acute leukemia patients.

Effectiveness of Telerehabilitation Programs in Elderly with Hip or Knee Arthroplasty: A Systematic Review

Background: Lower limb osteoarthritis (OA) often generates musculoskeletal pain causing functional impairment and decreasing mobility, autonomy, and quality of life. Patients with OA are commonly prescribed specific care for total hip arthroplasty or total knee arthroplasty (THA or TKA), when patients present symptoms that are refractory to nondrug treatments. Currently, when patients are discharged from orthopedic surgery, they are either referred to a rehabilitation department, or sent directly home with assistance such as remote monitoring by teleconsultation or a mobile application. In recent years, there has been an evolution in digital health and in particular telerehabilitation. To determine utility and effectiveness, the aim of this systematic review was to highlight and evaluate different telerehabilitation programs using new information and communication technologies. Methods: Five databases, ScienceDirect, PubMed, Web of Sciences, Scopus, and Google scholar, were searched until 30 June 30, 2023. All studies written in English and meeting our inclusion criteria were included. Databases were screened for "Total Hip Arthroplasty," "Total Knee Arthroplasty," "Total Hip Replacement," "Total Knee Replacement," "Rehabilitation," "Physical Activity," "Physiotherapy," "Telerehabilitation," "Telecommunication*," "Senior*," and "Elderly" in accordance with PRISMA-ScR guideline. Results: Fourteen articles were selected according to inclusion criteria. Telerehabilitation was offered in seven different ways (video call, applications smartphones, website, etc.). Assessments included were mainly quality of life questionnaires, perceived effort after exercises, field surveys on the tool experience, and physical tests to assess motor functions. Conclusion: This review highlights the importance and relevance of evaluating the contributions and limits of new health technologies to improve patient monitoring and thus enable better remote clinical care.

The geometry of photopolymerized topography influences neurite pathfinding by directing growth cone morphology and migration

Objective. Cochlear implants provide auditory perception to those with severe to profound sensorineural hearing loss: however, the quality of sound perceived by users does not approximate natural hearing. This limitation is due in part to the large physical gap between the stimulating electrodes and their target neurons. Therefore, directing the controlled outgrowth of processes from spiral ganglion neurons (SGNs) into close proximity to the electrode array could provide significantly increased hearing function.Approach.For this objective to be properly designed and implemented, the ability and limits of SGN neurites to be guided must first be determined. In this work, we engineer precise topographical microfeatures with angle turn challenges of various geometries to study SGN pathfinding and use live imaging to better understand how neurite growth is guided by these cues.Main Results.We find that the geometry of the angled microfeatures determines the ability of neurites to navigate the angled microfeature turns. SGN neurite pathfinding fidelity is increased by 20%-70% through minor increases in microfeature amplitude (depth) and by 25% if the angle of the patterned turn is made obtuse. Further, we see that dorsal root ganglion neuron growth cones change their morphology and migration to become more elongated within microfeatures. Our observations also indicate complexities in studying neurite turning. First, as the growth cone pathfinds in response to the various cues, the associated neurite often reorients across the angle topographical microfeatures. Additionally, neurite branching is observed in response to topographical guidance cues, most frequently when turning decisions are most uncertain.Significance.Overall, the multi-angle channel micropatterned substrate is a versatile and efficient system to assess neurite turning and pathfinding in response to topographical cues. These findings represent fundamental principles of neurite pathfinding that will be essential to consider for the design of 3D systems aiming to guide neurite growthin vivo.

The contemplation of amylose for the delivery of ulcerogenic nonsteroidal anti-inflammatory drugs

This manuscript proposes an innovative approach to mitigate the gastrointestinal adversities linked with nonsteroidal anti-inflammatory drugs (NSAIDs) by exploiting amylose as a novel drug delivery carrier. The intrinsic attributes of V-amylose, such as its structural uniqueness, biocompatibility and biodegradability, as well as its capacity to form inclusion complexes with diverse drug molecules, are meticulously explored. Through a comprehensive physicochemical analysis of V-amylose and ulcerogenic NSAIDs, the plausibility of amylose as a protective carrier for ulcerogenic NSAIDs to gastrointestinal regions is elucidated. This review further discusses the potential therapeutic advantages of amylose-based drug delivery systems in the management of gastric ulcers. By providing controlled release kinetics and enhanced bioavailability, these systems offer promising prospects for the development of more effective ulcer therapies.

Learning dynamical models of single and collective cell migration: a review

Single and collective cell migration are fundamental processes critical for physiological phenomena ranging from embryonic development and immune response to wound healing and cancer metastasis. To understand cell migration from a physical perspective, a broad variety of models for the underlying physical mechanisms that govern cell motility have been developed. A key challenge in the development of such models is how to connect them to experimental observations, which often exhibit complex stochastic behaviours. In this review, we discuss recent advances in data-driven theoretical approaches that directly connect with experimental data to infer dynamical models of stochastic cell migration. Leveraging advances in nanofabrication, image analysis, and tracking technology, experimental studies now provide unprecedented large datasets on cellular dynamics. In parallel, theoretical efforts have been directed towards integrating such datasets into physical models from the single cell to the tissue scale with the aim of conceptualising the emergent behaviour of cells. We first review how this inference problem has been addressed in both freely migrating and confined cells. Next, we discuss why these dynamics typically take the form of underdamped stochastic equations of motion, and how such equations can be inferred from data. We then review applications of data-driven inference and machine learning approaches to heterogeneity in cell behaviour, subcellular degrees of freedom, and to the collective dynamics of multicellular systems. Across these applications, we emphasise how data-driven methods can be integrated with physical active matter models of migrating cells, and help reveal how underlying molecular mechanisms control cell behaviour. Together, these data-driven approaches are a promising avenue for building physical models of cell migration directly from experimental data, and for providing conceptual links between different length-scales of description.

Image-guided orbital surgery: a preclinical validation study using a high-resolution physical model

OBJECTIVE

Preclinical validation study to assess the feasibility and accuracy of electromagnetic image-guided systems (EM-IGS) in orbital surgery using high-fidelity physical orbital anatomy simulators.

METHODS

EM-IGS platform, clinical software, navigation instruments and reference system (StealthStation S8, Medtronic) were evaluated in a mock operating theatre at the Royal Victoria Eye and Ear Hospital, a tertiary academic hospital in Dublin, Ireland. Five high-resolution 3D-printed model skulls were created using CT scans of five anonymised patients with an orbital tumour that previously had a successful orbital biopsy or excision. The ability of ophthalmic surgeons to achieve satisfactory system registration in each model was assessed. Subsequently, navigational accuracy was recorded using defined anatomical landmarks as ground truth. Qualitative feedback on the system was also attained.

RESULTS

Three independent surgeons participated in the study, one junior trainee, one fellow and one consultant. Across models, more senior participants were able to achieve a smaller system-generated registration error in a fewer number of attempts. When assessing navigational accuracy, submillimetre accuracy was achieved for the majority of points (16 landmarks per model, per participant). Qualitative surgeon feedback suggested acceptability of the technology, although interference from mobile phones near the operative field was noted.

CONCLUSION

This study suggests the feasibility and accuracy of EM-IGS in a preclinical validation study for orbital surgery using patient specific 3D-printed skulls. This preclinical study provides the foundation for clinical studies to explore the safety and effectiveness of this technology.

Impact of Impedance Levels on Recording Quality in Flexible Neural Probes

Flexible neural probes are attractive emerging technologies for brain recording because they can effectively record signals with minimal risk of brain damage. Reducing the electrode impedance of the probe before recording is a common practice of many researchers. However, studies investigating the impact of low impedance levels on high-quality recordings using flexible neural probes are lacking. In this study, we electrodeposited Pt onto a commercial flexible polyimide neural probe and investigated the relationship between the impedance level and the recording quality. The probe was inserted into the brains of anesthetized mice. The electrical signals of neurons in the brain, specifically the ventral posteromedial nucleus of the thalamus, were recorded at impedance levels of 50, 250, 500 and 1000 kΩ at 1 kHz. The study results demonstrated that as the impedance decreased, the quality of the signal recordings did not consistently improve. This suggests that extreme lowering of the impedance may not always be advantageous in the context of flexible neural probes.

Targeted Biodegradable Near-Infrared Fluorescent Nanoparticles for Colorectal Cancer Imaging

Colorectal cancer (CRC) is the third leading cause of cancer death in the U.S., and early detection and diagnosis are essential for effective treatment. Current methods are inadequate for rapid detection of early disease, revealing flat lesions, and delineating tumor margins with accuracy and molecular specificity. Fluorescence endoscopy can generate wide field-of-view images enabling detection of CRC lesions and margins; increased signal intensity and improved signal-to-noise ratios can increase both speed and sensitivity of cancer detection. For this purpose, we developed targeted near-infrared (NIR) fluorescent silica nanoparticles (FSNs). We tuned their size to 50-200 nm and conjugated their surface with an antibody to carcinoembryonic antigen (CEA) to prepare CEA-FSNs. The physicochemical properties and biodegradable profiles of CEA-FSN were characterized, and molecular targeting was verified in culture using HT29 (CEA positive) and HCT116 (CEA negative) cells. CEA-FSNs bound to the HT29 cells to a greater extent than to the HCT116 cells, and smaller CEA-FSNs were internalized into HT29 cells more efficiently than larger CEA-FSNs. After intravenous administration of CEA-FSNs, a significantly greater signal was observed from the CEA-positive HT29 than the CEA-negative HCT116 tumors in xenografted mice. In F344-PIRC rats, polyps in the intestine were detected by white-light endoscopy, and NIR fluorescent signals were found in the excised intestinal tissue after topical application of CEA-FSNs. Immunofluorescence imaging of excised tissue sections demonstrated that the particle signals coregistered with signals for both CRC and CEA. These results indicate that CEA-FSNs have potential as a molecular imaging marker for early diagnosis of CRC.

A Biomimetic Synthetic Strategy Can Provide Keratan Sulfate I and II Oligosaccharides with Diverse Fucosylation and Sulfation Patterns

Keratan sulfate (KS) is a proteoglycan that is widely expressed in the extracellular matrix of various tissue types, where it performs multiple biological functions. KS is the least understood proteoglycan, which in part is due to a lack of panels of well-defined KS oligosaccharides that are needed for structure-binding studies, as analytical standards, to examine substrate specificities of keratinases, and for drug development. Here, we report a biomimetic approach that makes it possible to install, in a regioselective manner, sulfates and fucosides on oligo-N-acetyllactosamine (LacNAc) chains to provide any structural element of KS by using specific enzyme modules. It is based on the observation that α1,3-fucosides, α2,6-sialosides and C-6 sulfation of galactose (Gal6S) are mutually exclusive and cannot occur on the same LacNAc moiety. As a result, the pattern of sulfation on galactosides can be controlled by installing α1,3-fucosides or α2,6-sialosides to temporarily block certain LacNAc moieties from sulfation by keratan sulfate galactose 6-sulfotransferase (CHST1). The patterns of α1,3-fucosylation and α2,6-sialylation can be controlled by exploiting the mutual exclusivity of these modifications, which in turn controls the sites of sulfation by CHST1. Late-stage treatment with a fucosidase or sialidase to remove blocking fucosides or sialosides provides selectively sulfated KS oligosaccharides. These treatments also unmasked specific galactosides for further modification by CHST1. To showcase the potential of the enzymatic strategy, we have prepared a range of poly-LacNAc derivatives having different patterns of fucosylation and sulfation and several N-glycans decorated by specific arrangements of sulfates.

Nuclear deformation and cell division of single cell on elongated micropatterned substrates fabricated by DMD lithography

Cells sense mechanical signals from the surrounding environment and transmit them to the nucleus through mechanotransduction to regulate cellular behavior. Microcontact printing, which utilizes elastomer stamps, is an effective method for simulating the cellular microenvironment and manipulating cell morphology. However, the conventional fabrication process of silicon masters and elastomer stamps requires complex procedures and specialized equipment, which restricts the widespread application of micropatterning in cell biology and hinders the investigation of the role of cell geometry in regulating cell behavior. In this study, we present an innovative method for convenient resin stamp microfabrication based on digital micromirror device planar lithography. Using this method, we generated a series of patterns ranging from millimeter to micrometer scales and validated their effectiveness in controlling adhesion at both collective and individual cell levels. Additionally, we investigated mechanotransduction and cell behavior on elongated micropatterned substrates. We then examined the effects of cell elongation on cytoskeleton organization, nuclear deformation, focal adhesion formation, traction force generation, nuclear mechanics, and the growth of HeLa cells. Our findings reveal a positive correlation between cell length and mechanotransduction. Interestingly, HeLa cells with moderate length exhibit the highest cell division and proliferation rates. These results highlight the regulatory role of cell elongation in mechanotransduction and its significant impact on cancer cell growth. Furthermore, our methodology for controlling cell adhesion holds the potential for addressing fundamental questions in both cell biology and biomedical engineering.

Nanocarrier-based gene delivery for immune cell engineering

Clinical advances in genetically modified immune cell therapies, such as chimeric antigen receptor T cell therapies, have raised hope for cancer treatment. The majority of these biotechnologies are based on viral methods for ex vivo genetic modification of the immune cells, while the non-viral methods are still in the developmental phase. Nanocarriers have been emerging as materials of choice for gene delivery to immune cells. This is due to their versatile physicochemical properties such as large surface area and size that can be optimized to overcome several practical barriers to successful gene delivery. The in vivo nanocarrier-based gene delivery can revolutionize cell-based cancer immunotherapies by replacing the current expensive autologous cell manufacturing with an off-the-shelf biomaterial-based platform. The aim of this research is to review current advances and strategies to overcome the challenges in nanoparticle-based gene delivery and their impact on the efficiency, safety, and specificity of the process. The main focus is on polymeric and lipid-based nanocarriers, and their recent preclinical applications for cancer immunotherapy.

Computational peptide discovery with a genetic programming approach

The development of peptides for therapeutic targets or biomarkers for disease diagnosis is a challenging task in protein engineering. Current approaches are tedious, often time-consuming and require complex laboratory data due to the vast search spaces that need to be considered. In silico methods can accelerate research and substantially reduce costs. Evolutionary algorithms are a promising approach for exploring large search spaces and can facilitate the discovery of new peptides. This study presents the development and use of a new variant of the genetic-programming-based POET algorithm, called POETRegex , where individuals are represented by a list of regular expressions. This algorithm was trained on a small curated dataset and employed to generate new peptides improving the sensitivity of peptides in magnetic resonance imaging with chemical exchange saturation transfer (CEST). The resulting model achieves a performance gain of 20% over the initial POET models and is able to predict a candidate peptide with a 58% performance increase compared to the gold-standard peptide. By combining the power of genetic programming with the flexibility of regular expressions, new peptide targets were identified that improve the sensitivity of detection by CEST. This approach provides a promising research direction for the efficient identification of peptides with therapeutic or diagnostic potential.

Unlocking Overexpressed Membrane Proteins to Guide Breast Cancer Precision Medicine

Breast cancer (BC) is a prevalent form of cancer affecting women worldwide. However, the effectiveness of current BC drugs is limited by issues such as systemic toxicity, drug resistance, and severe side effects. Consequently, there is an urgent need for new therapeutic targets and improved tumor tracking methods. This study aims to address these challenges by proposing a strategy for identifying membrane proteins in tumors that can be targeted for specific BC therapy and diagnosis. The strategy involves the analyses of gene expressions in breast tumor and non-tumor tissues and other healthy tissues by using comprehensive bioinformatics analysis from The Cancer Genome Atlas (TCGA), UALCAN, TNM Plot, and LinkedOmics. By employing this strategy, we identified four transcripts (LRRC15, EFNA3, TSPAN13, and CA12) that encoded membrane proteins with an increased expression in BC tissue compared to healthy tissue. These four transcripts also demonstrated high accuracy, specificity, and accuracy in identifying tumor samples, as confirmed by the ROC curve. Additionally, tissue microarray (TMA) analysis revealed increased expressions of the four proteins in tumor tissues across all molecular subtypes compared to the adjacent breast tissue. Moreover, the analysis of human interactome data demonstrated the important roles of these proteins in various cancer-related pathways. Taken together, these findings suggest that LRRC15, EFNA3, TSPAN13, and CA12 can serve as potential biomarkers for improving cancer diagnosis screening and as suitable targets for therapy with reduced side effects and enhanced efficacy.

NSF DARE-Transforming modeling in neurorehabilitation: Four threads for catalyzing progress

We present an overview of the Conference on Transformative Opportunities for Modeling in Neurorehabilitation held in March 2023. It was supported by the Disability and Rehabilitation Engineering (DARE) program from the National Science Foundation's Engineering Biology and Health Cluster. The conference brought together experts and trainees from around the world to discuss critical questions, challenges, and opportunities at the intersection of computational modeling and neurorehabilitation to understand, optimize, and improve clinical translation of neurorehabilitation. We organized the conference around four key, relevant, and promising Focus Areas for modeling: Adaptation & Plasticity, Personalization, Human-Device Interactions, and Modeling 'In-the-Wild'. We identified four common threads across the Focus Areas that, if addressed, can catalyze progress in the short, medium, and long terms. These were: (i) the need to capture and curate appropriate and useful data necessary to develop, validate, and deploy useful computational models (ii) the need to create multi-scale models that span the personalization spectrum from individuals to populations, and from cellular to behavioral levels (iii) the need for algorithms that extract as much information from available data, while requiring as little data as possible from each client (iv) the insistence on leveraging readily available sensors and data systems to push model-driven treatments from the lab, and into the clinic, home, workplace, and community. The conference archive can be found at (dare2023.usc.edu). These topics are also extended by three perspective papers prepared by trainees and junior faculty, clinician researchers, and federal funding agency representatives who attended the conference.

Association between commuting time and work-related low back pain with respect to sports and leisure activities in Korean workers

Long commuting times can induce work-related low back pain (LBP), which can be exacerbated by reduced sports and leisure activities. However, there is a lack of empirical research on commuting time and work-related LBP in Korea. In this study, we aimed to investigate the relationship between commuting time and work-related LBP as well as the effect of sports and leisure activities on Korean workers. We utilized data from the sixth Korean Working Conditions Survey to analyze the relationship between commuting time and work-related LBP using multivariable logistic regression. The total number of included workers was 28,202. Workers without sports and leisure activities, and long commuting times (40-59, 60-79, and ≥80 min) showed significantly higher odds ratios for work-related LBP (1.29 [95% Confidence intervals=1.12-1.49], 1.42 [1.22-1.65], and 1.96 [1.68-2.28], respectively). However, in workers with sports and leisure activities, the results were significant only for commuting times of 60-79 and ≥80 min (1.41 [1.13-1.75], 1.60 [1.28-1.99], respectively). Long commuting times were associated with work-related LBP, and engagement in sports and leisure activities was found to play a role in mitigating the impact among Korean wage workers.

Adipose tissue reconstruction facilitated with low immunogenicity decellularized adipose tissue scaffolds

There is currently an urgent need to develop engineered scaffolds to support new adipose tissue formation and facilitate long-term maintenance of function and defect repair to further generate prospective bioactive filler materials capable of fulfilling surgical needs. Herein, adipose regeneration methods were optimized and decellularized adipose tissue (DAT) scaffolds with good biocompatibility were fabricated. Adipose-like tissues were reconstructed using the DAT and 3T3-L1 preadipocytes, which have certain differentiation potential, and the regenerative effects of the engineered adipose tissuesin vitroandin vivowere explored. The method improved the efficiency of adipose removal from tissues, and significantly shortened the time for degreasing. Thus, the DAT not only provided a suitable space for cell growth but also promoted the proliferation, migration, and differentiation of preadipocytes within it. Following implantation of the constructed adipose tissuesin vivo, the DAT showed gradual degradation and integration with surrounding tissues, accompanied by the generation of new adipose tissue analogs. Overall, the combination of adipose-derived extracellular matrix and preadipocytes for adipose tissue reconstruction will be of benefit in the artificial construction of biomimetic implant structures for adipose tissue reconstruction, providing a practical guideline for the initial integration of adipose tissue engineering into clinical medicine.

Meta-analysis to Unravel Core Transcriptomic Responses in Penaeus vannamei Exposed to Biotic and Abiotic Stresses

Shrimp farming, a dominant economic activity in coastal areas, is affected by different abiotic and biotic stress factors. These stressors, under poor management conditions, could affect growth and health of farmed animals. Understanding the common gene expressions in response to stress, regardless of the specific stress factor, holds significant importance in the field of functional genomics. Scope of this study is to identify the core transcriptomic responses in the shrimp species Penaeus vannamei exposed to various abiotic and biotic stress conditions and to decipher their functional importance. To achieve our objective, we gathered and analyzed multiple RNA-seq datasets related to twelve abiotic and nine biotic stress conditions. Through the in silico meta-analysis, we predicted 961 differentially expressed genes (meta-DEGs) for abiotic stress conditions and 517 meta-DEGs for biotic stress conditions, respectively. These meta-DEGs represent genes that are commonly expressed across different stress factors and are indicative of the organism's general response to stress. The annotation of nineteen core up-regulated meta-DEGs revealed their diverse functions in detoxification, cell adhesion, metal ion binding, and oxidative phosphorylation. These genes play a crucial role in stress response and immune defense. For abiotic stress, significant pathways associated with the stress response include tryptophan metabolism, starch and sucrose metabolism, fatty acid degradation, carbohydrate digestion and absorption, phenylalanine metabolism, drug metabolism-other enzymes, arachidonic acid metabolism, and fatty acid elongation. Similarly, for biotic stress, metabolism of xenobiotics by cytochrome P450, pentose and glucuronate interconversions, steroid hormone biosynthesis, and drug metabolism-cytochrome P450 were found to be significant pathway associations. In addition, the study also predicted 17 stress regulatory motifs present in the identified meta-DEGs. These motifs have significance in identifying the stress responses of the organism. The metabolic pathways and regulatory motifs associated with abiotic and biotic stress factors identified through this study could be a valuable resource for developing stress management approaches in shrimp aquaculture.

Deep learning-based computer-aided diagnosis system for the automatic detection and classification of lateral cervical lymph nodes on original ultrasound images of papillary thyroid carcinoma: a prospective diagnostic study

PURPOSE

This study aims to develop a deep learning-based computer-aided diagnosis (CAD) system for the automatic detection and classification of lateral cervical lymph nodes (LNs) on original ultrasound images of papillary thyroid carcinoma (PTC) patients.

METHODS

A retrospective data set of 1801 cervical LN ultrasound images from 1675 patients with PTC and a prospective test set including 185 images from 160 patients were collected. Four different deep leaning models were trained and validated in the retrospective data set. The best model was selected for CAD system development and compared with three sonographers in the retrospective and prospective test sets.

RESULTS

The Deformable Detection Transformer (DETR) model showed the highest diagnostic efficacy, with a mean average precision score of 86.3% in the retrospective test set, and was therefore used in constructing the CAD system. The detection performance of the CAD system was superior to the junior sonographer and intermediate sonographer with accuracies of 86.3% and 92.4% in the retrospective and prospective test sets, respectively. The classification performance of the CAD system was better than all sonographers with the areas under the curve (AUCs) of 94.4% and 95.2% in the retrospective and prospective test sets, respectively.

CONCLUSIONS

This study developed a Deformable DETR model-based CAD system for automatically detecting and classifying lateral cervical LNs on original ultrasound images, which showed excellent diagnostic efficacy and clinical utility. It can be an important tool for assisting sonographers in the diagnosis process.

Current Development of Lanthanide Complexes for Biomedical Applications

Luminescent molecule-based bioimaging system is widely used for precise localization and distinction of cancer/tumor cells. Luminescent lanthanide (Ln(III)) complexes offer long-lived (sub-millisecond time scale) and sharp (FWHM <10 nm) emission, arising from the forbidden 4f-4f electronic transitions. Luminescent Ln(III) complex-based bioimaging has emerged as a promising option for both in vitro and in vivo visualizations. In this mini-review, the historical development and recent significant progress of luminescent Ln(III) probes for bioapplications are introduced. The recent studies are mainly focused on three points: (i) the structural modifications of Ln(III) complexes in both macrocyclic and small ligands, (ii) the acquirement of high resolution luminescence images of cancer/tumor cells and (iii) the constructions of ratiometric biosensors. Furthermore, our recent study is explained as a new Cancer GPS (cancer grade probing for determining tumor grade through photophysical property analyses of intracellular Eu(III) complex.

A deep learning framework for identifying and segmenting three vessels in fetal heart ultrasound images

BACKGROUND

Congenital heart disease (CHD) is one of the most common birth defects in the world. It is the leading cause of infant mortality, necessitating an early diagnosis for timely intervention. Prenatal screening using ultrasound is the primary method for CHD detection. However, its effectiveness is heavily reliant on the expertise of physicians, leading to subjective interpretations and potential underdiagnosis. Therefore, a method for automatic analysis of fetal cardiac ultrasound images is highly desired to assist an objective and effective CHD diagnosis.

METHOD

In this study, we propose a deep learning-based framework for the identification and segmentation of the three vessels-the pulmonary artery, aorta, and superior vena cava-in the ultrasound three vessel view (3VV) of the fetal heart. In the first stage of the framework, the object detection model Yolov5 is employed to identify the three vessels and localize the Region of Interest (ROI) within the original full-sized ultrasound images. Subsequently, a modified Deeplabv3 equipped with our novel AMFF (Attentional Multi-scale Feature Fusion) module is applied in the second stage to segment the three vessels within the cropped ROI images.

RESULTS

We evaluated our method with a dataset consisting of 511 fetal heart 3VV images. Compared to existing models, our framework exhibits superior performance in the segmentation of all the three vessels, demonstrating the Dice coefficients of 85.55%, 89.12%, and 77.54% for PA, Ao and SVC respectively.

CONCLUSIONS

Our experimental results show that our proposed framework can automatically and accurately detect and segment the three vessels in fetal heart 3VV images. This method has the potential to assist sonographers in enhancing the precision of vessel assessment during fetal heart examinations.

Focused Ultrasound-Responsive Nanocomposite with Near-Infrared II Mechanoluminescence for Spatiotemporally Selective Immune Activation in Lymph Nodes

The immune regulation of the lymphatic system, especially the lymph node (LN), is of great significance for the treatment of diseases and the inhibition of pathogenic organisms spreading in the body. However, achieving precise spatiotemporal control of immune cell activation in LN in vivo remains a challenge due to tissue depth and off-target effects. Furthermore, minimally invasive and real-time feedback methods to monitor the regulation of the immune system in LN are lacking. Here, focused ultrasound responsive immunomodulator loaded nanoplatform (FURIN) with near-infrared II (NIR-II) luminescence is designed to achieve spatiotemporally controllable immune activation in LN in vivo. The NIR-II persistent luminescence of FURIN can track its delivery in LN through bioimaging. Under focused ultrasound (FUS) stimulation, the immunomodulator encapsulated in FURIN can be released locally in the LN to activate immune cells such as dendritic cells and the NIR-II mechanoluminescence of FURIN provides real-time optical feedback signals for immune activation. This work points to a FUS mediated, spatiotemporal selective immune activation strategy in vivo with the feedback control of luminescence signals via ultrasound responsive nanocomposite, which is of great significance in improving the efficacy and reducing the side effect of immune regulation for the development of potential immunotherapeutic methods in the future.

Harnessing Catalytic RNA Circuits for Construction of Artificial Signaling Pathways in Mammalian Cells

Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.

Using a probabilistic approach to derive a two-phase model of flow-induced cell migration

Interstitial fluid flow is a feature of many solid tumors. In vitro experiments have shown that such fluid flow can direct tumor cell movement upstream or downstream depending on the balance between the competing mechanisms of tensotaxis (cell migration up stress gradients) and autologous chemotaxis (downstream cell movement in response to flow-induced gradients of self-secreted chemoattractants). In this work we develop a probabilistic-continuum, two-phase model for cell migration in response to interstitial flow. We use a kinetic description for the cell velocity probability density function, and model the flow-dependent mechanical and chemical stimuli as forcing terms that bias cell migration upstream and downstream. Using velocity-space averaging, we reformulate the model as a system of continuum equations for the spatiotemporal evolution of the cell volume fraction and flux in response to forcing terms that depend on the local direction and magnitude of the mechanochemical cues. We specialize our model to describe a one-dimensional cell layer subject to fluid flow. Using a combination of numerical simulations and asymptotic analysis, we delineate the parameter regime where transitions from downstream to upstream cell migration occur. As has been observed experimentally, the model predicts downstream-oriented chemotactic migration at low cell volume fractions, and upstream-oriented tensotactic migration at larger volume fractions. We show that the locus of the critical volume fraction, at which the system transitions from downstream to upstream migration, is dominated by the ratio of the rate of chemokine secretion and advection. Our model also predicts that, because the tensotactic stimulus depends strongly on the cell volume fraction, upstream, tensotaxis-dominated migration occurs only transiently when the cells are initially seeded, and transitions to downstream, chemotaxis-dominated migration occur at later times due to the dispersive effect of cell diffusion.

An update on alternative therapy for Escherichia coli causing urinary tract infections; a narrative review

BACKGROUND

Urinary tract infections (UTIs) are the most common type of nosocomial infection and severe health issues because of the difficulties and frequent recurrence. Today, alternative methods such as sonodynamic therapy (SDT), photodynamic therapy (PDT) and herbal materials use for treating infections like UTI in many countries.

METHOD

We conducted searches of the biomedical databases (Google Scholar, Scopus, PubMed, and Web of sciences) to identify related studies from 2008 to 2023.

RESULT

SDT aims to use ultrasound to activate a sonosensitizer, which causes a biological effect by raising reactive oxygen species (ROS). When bacteria are exposed to ROS, several important effects occur: oxidative damage, DNA damage, protein dysfunction etc. SDT with herbal medicine significantly reduced the number of colony-forming units and bactericidal activity for Klebsiella pneumonia and E. coli. PDT is a promising treatment for cancer and microbial infections, combining a photosensitiser, light and tissue molecular oxygen. It involves a photosensitizer, light source, and oxygen, with variations affecting microbial binding and bactericidal activity. Factors affecting antibacterial properties include plant type, growing conditions, harvesting, and processing. This review highlights the recent advancements in sonodynamic, photodynamic, herbal, and bio-material-based approaches in the treatment of E. coli infections.

CONCLUSIONS

These alternative therapies offer exciting prospects for addressing UTIs, especially in cases where traditional antibiotic treatments may be less effective. Further research and clinical studies are warranted to fully explore the potential of these innovative treatment modalities in combating UTIs and improving patient outcomes.