Detection of Two Different Inner-Sphere Solvent Species in a Eu3+-Based ParaCEST Agent Dissolved in a Mixture of Methanol and Water: The Impact of Solvents on Exchange Dynamics

Solvent binding and exchange kinetics are of fundamental importance for lanthanide-based MRI contrast agents, and these properties are critically affected by solvents. In the present work, a water and methanol mixture was used to investigate solvent exchange kinetics in a Eu3+-DOTA-tetraamide complex by high-resolution 1H NMR and CEST methods. Two distinct solvated complexes were observed by NMR, one complex capped by a single water molecule and the other by a single methanol molecule. CEST methods were used to measure exchange between all -OH species (free and bound water and methanol) and between exchanging methanol species via methyl proton resonances. The -CH3 CEST experiment offers the simplicity of monitoring exchange between two pools versus conventional -OH CEST, which must be described using a five-pool exchange model. The combined data showed that the two solvated species have similar solvent exchange kinetic constants (kex = 1.7 ± 0.3 × 103 and 1.1 ± 0.2 × 103 s-1 (methanol and water, respectively)). In water/methanol (1:4), solvent exchange became more rapid in both solvated species, 4-fold for (H2O)EuL and 2.6-fold for (MeOH)EuL. This suggests that the solvent shell around the EuL complex in a water/methanol mixture is less organized compared to a more highly organized solvent shell formed in a single solvent.

Foldable 3D opto-electro array for optogenetic neuromodulation and physiology recording

This paper presents a thin-film, three-dimensional (3D) opto-electro array featuring four addressable microscale light-emitting diodes (LEDs) for surface cortex illumination and nine penetrating electrodes for simultaneous recording of light-evoked neural activities. Inspired by the origami concept, we have developed a meticulously designed "bridge+trench" structure that facilitates the transformation of the array from 2D to 3D while preventing damage to the thin film metal. Prior to device transformation, the shape and dimensions of the 2D array can be customized, enhancing its versatility for various applications. In addition, the arched base offers strong mechanical support to facilitate the direct insertion of the probe into tissue without any mechanical reinforcement. The array was encapsulated using polyimide and epoxy to ensure mechanical flexibility and biocompatibility of the device. The efficacy of the device was evaluated through comprehensive in vitro and in vivo characterization.

A hierarchical model of early brain functional network development

Functional brain networks emerge prenatally, grow interactively during the first years of life, and optimize both within-network topology and between-network interactions as individuals age. This review summarizes research that has characterized this process over the past two decades, and aims to link functional network growth with emerging behaviors, thereby developing a more holistic understanding of the developing brain and behavior from a functional network perspective. This synthesis suggests that the development of the brain's functional networks follows an overlapping hierarchy, progressing from primary sensory/motor to socioemotional-centered development and finally to higher-order cognitive/executive control networks. Risk-related alterations, resilience factors, treatment effects, and novel therapeutic opportunities are also discussed to encourage the consideration of future imaging-assisted methods for identifying risks and interventions.

Preventing respiratory viral transmission in healthcare settings

PURPOSE OF REVIEW

The COVID-19 pandemic catalyzed new insights into respiratory viral transmission mechanisms and prevention. We review the most practical and impactful measures to prevent SARS-CoV-2 and other nosocomial respiratory viral infections in healthcare.

RECENT FINDINGS

Nosocomial respiratory viral infection rates mirror viral activity levels in the surrounding community. During peak periods ∼15-20% of hospitalized patients with respiratory viral infections may have acquired their virus in the hospital. Nosocomial respiratory viral infections are associated with increased lengths-of-stay, risk of respiratory failure, and hospital death. Most procedures contribute minimally to aerosol production compared to labored breathing, coughing, and forced expiration. Masking for source control and exposure control both decrease transmission risk, respirators more so than masks. Likewise, vaccinating healthcare workers decreases transmission risk and is associated with lower patient mortality rates, particularly in long-term care facilities. Increasing air changes, ultraviolet irradiation, and portable HEPA filtration units may also decrease transmission rates but their marginal benefit relative to current healthcare ventilation standards has yet to be established.

SUMMARY

Practical strategies to prevent nosocomial respiratory viral infections include maximizing staff and patient influenza and SARS-CoV-2 vaccination rates and implementing routine masking during patient interactions when community incidence is high.

Nuclear envelope proteins, mechanotransduction, and their contribution to breast cancer progression

Breast cancer cells frequently exhibit changes in the expression of nuclear envelope (NE) proteins such as lamins and emerin that determine the physical properties of the nucleus and contribute to cellular mechanotransduction. This review explores the emerging interplay between NE proteins, the physical challenges incurred during metastatic progression, and mechanotransduction. Improved insights into the underlying mechanisms may ultimately lead to better prognostic tools and treatment strategies for metastatic breast cancer.

Deep learning-based MRI reconstruction with Artificial Fourier Transform Network (AFTNet)

Deep complex-valued neural networks (CVNNs) provide a powerful way to leverage complex number operations and representations and have succeeded in several phase-based applications. However, previous networks have not fully explored the impact of complex-valued networks in the frequency domain. Here, we introduce a unified complex-valued deep learning framework - Artificial Fourier Transform Network (AFTNet) - which combines domain-manifold learning and CVNNs. AFTNet can be readily used to solve image inverse problems in domain transformation, especially for accelerated magnetic resonance imaging (MRI) reconstruction and other applications. While conventional methods typically utilize magnitude images or treat the real and imaginary components of k-space data as separate channels, our approach directly processes raw k-space data in the frequency domain, utilizing complex-valued operations. This allows for a mapping between the frequency (k-space) and image domain to be determined through cross-domain learning. We show that AFTNet achieves superior accelerated MRI reconstruction compared to existing approaches. Furthermore, our approach can be applied to various tasks, such as denoised magnetic resonance spectroscopy (MRS) reconstruction and datasets with various contrasts. The AFTNet presented here is a valuable preprocessing component for different preclinical studies and provides an innovative alternative for solving inverse problems in imaging and spectroscopy. The code is available at: https://github.com/yanting-yang/AFT-Net.

LPS-enriched interaction drives spectrum conversion in antimicrobial peptides: Design and optimization of AA16 derivatives for targeting gram-negative bacteria

The increasing prevalence of antibiotic-resistant Gram-negative bacteria necessitates the development of novel antimicrobial agents with targeted specificity. In this study, we designed and optimized derivatives of the antimicrobial peptide AA16, which truncated from CD14 protein α-helical region, to selectively target Gram-negative bacteria by enhancing lipopolysaccharide (LPS)-enriched interactions, thereby achieving antibacterial spectrum conversion. Starting from the parent peptide AA16 (Ac-AARIPSRILFGALRVL-Amide), we performed strategic amino acid substitutions based on structure-activity relationship analysis. This led to the identification of AA16-10R, a derivative with a specific substitution at position 10, which demonstrated significantly enhanced antibacterial activity against Gram-negative strains such as Escherichia coli and Pseudomonas aeruginosa, while maintaining low hemolytic activity. Mechanistic studies revealed that AA16-10R exhibited a strong binding affinity to LPS (Kd = 0.15 μM), and its interaction with LPS induced the formation of an α-helical structure. This conformational change facilitated its accumulation on the bacterial outer membrane and disrupted membrane integrity. Our innovative approach of exploiting LPS-enriched interactions successfully converted the antimicrobial spectrum of AA16 derivatives from broad-spectrum to Gram-negative-specific. This study highlights a novel strategy for the rational design of antimicrobial peptides based on specific protein-protein interactions, offering a promising avenue for targeted antimicrobial therapy against Gram-negative pathogens.

Decoding the role of the arginine dihydrolase pathway in shaping human gut community assembly and health-relevant metabolites

The arginine dihydrolase pathway (arc operon) provides a metabolic niche by transforming arginine into metabolic byproducts. We investigate the role of the arc operon in probiotic Escherichia coli Nissle 1917 on human gut community assembly and health-relevant metabolite profiles. By stabilizing environmental pH, the arc operon reduces variability in community composition in response to pH perturbations and frequently enhances butyrate production in synthetic communities. We use a tailored machine learning model for microbiomes to predict community assembly in response to variation in initial media pH and arc operon activity. This model uncovers the pH- and arc operon-dependent interactions shaping community assembly. Human gut species display altered colonization dynamics in response to the arc operon in the murine gut. In sum, our framework to quantify the contribution of a specific pathway to microbial community assembly and metabolite production can reveal new engineering strategies. A record of this paper's transparent peer review process is included in the supplemental information.

The synergistic potential of mechanotherapy and sonopermeation to enhance cancer treatment effectiveness

Inefficient drug delivery in tumors, especially in desmoplastic cancers, arises from blood vessel collapse due to tumor stiffening and mechanical compression. Vessel collapse also leads to hypoxia, immune evasion, and metastasis, reducing treatment efficacy. Mechanotherapeutics and ultrasound sonopermeation, which address tumor stiffness and enhance vessel permeability, respectively, show promise in restoring tumor microenvironment abnormalities and improving drug delivery. This perspective highlights their independent and combined potential to optimize cancer therapy.

Large animal model of controlled peripheral artery calcification

Peripheral artery disease (PAD) in the lower extremity arteries leads to significant morbidity and mortality. Arterial calcification contributes to poor clinical outcomes and greatly increases the risk of amputation. Current treatments for calcific lesions are limited and yield suboptimal results. A large animal model that closely mimics calcific PAD and accommodates human-sized devices could enhance the development of safer and more effective therapies. Our objective was to create a swine model of late-stage arterial calcification to test the efficacy and side effects of surgical interventions. To induce lesions, swine received injections of CaCl2 directly into the media and periadventitial spaces of the iliac, femoral, and popliteal arteries using a micro-needle catheter. The injection sites were varied to create eccentric and concentric lesions of differing lengths and patterns. Adjacent non-calcified arterial segments served as intersubject controls. The lesions were allowed to mature, and Computed Tomography Angiography and Intravascular Ultrasound imaging demonstrated ring-like calcification patterns and no pulsatility as early as 4 weeks after induction. Mechanical testing of excised arteries mirrored the mechanical properties of calcified human vessels, including characteristic stiffening. Histological analysis further confirmed that the calcified arteries in this model closely resembled human calcified femoropopliteal vessels, displaying inflammation, accumulation of collagen and glycosaminoglycans, elastin degradation, and smooth muscle cell loss within a degenerated tunica media. This porcine model replicates key pathological features of human calcific disease and provides a robust platform to evaluate the impacts and mechanisms of calcium-modifying treatments. STATEMENT OF SIGNIFICANCE: Arterial calcification is a key contributor to poor outcomes in peripheral artery disease (PAD). Our study presents a swine model of controlled peripheral artery calcification produced using targeted calcium chloride injections delivered endovascularly via a microneedle catheter. This approach creates arterial calcific lesions that closely replicate the mechanical, structural, and histological features of human calcified arteries. Additionally, the model accommodates human-sized devices, providing a robust platform for testing advanced biomaterials, devices, and therapies designed to modify or reverse calcification. By addressing a significant gap in preclinical research, our work aims to enhance treatment strategies for PAD, with the potential to reduce amputation rates and improve patient outcomes.

Peptide Amphiphile-Nanoparticle Assemblies for Mechano-Chemo Combination Therapy

Mechanical tumor ablation using focused ultrasound (FUS) offers minimally invasive ablation of solid tumors. However, mechanical tumor ablation requires highly intense FUS pulses, which may generate off-target effects. In addition, residual cancer cells that survive ablation can cause recurrence. To overcome these challenges, we developed a dual-functional nanomaterial by assembling peptide amphiphiles on hydrophobically modified nanoparticles. The hydrophobic nanoparticle core allows for the generation of cavitating bubbles at low FUS intensities to effectively ablate tumors. Peptide amphiphile shells interact dynamically with the hydrophobic nanoparticle surfaces and cell membranes, which improved tumor retention and cellular internalization of payloads attached to them. By conjugating a highly potent agent, Monomethyl auristatin E, to the peptide amphiphiles, we showed synergistic mechano- and chemotherapy using in vitro and in vivo models of human melanoma. This work presents a new nanoparticle approach to improving the outcomes of mechanical tumor ablation.

Meningeal lymphatic drainage: novel insights into central nervous system disease

In recent years, increasing evidence has suggested that meningeal lymphatic drainage plays a significant role in central nervous system (CNS) diseases. Studies have indicated that CNS diseases and conditions associated with meningeal lymphatic drainage dysfunction include neurodegenerative diseases, stroke, infections, traumatic brain injury, tumors, functional cranial disorders, and hydrocephalus. However, the understanding of the regulatory and damage mechanisms of meningeal lymphatics under physiological and pathological conditions is currently limited. Given the importance of a profound understanding of the interplay between meningeal lymphatic drainage and CNS diseases, this review covers seven key aspects: the development and structure of meningeal lymphatic vessels, methods for observing meningeal lymphatics, the function of meningeal lymphatics, the molecular mechanisms of meningeal lymphatic injury, the relationships between meningeal lymphatic vessels and CNS diseases, potential regulatory mechanisms of meningeal lymphatics, and conclusions and outstanding questions. We will explore the relationship between the development, structure, and function of meningeal lymphatics, review current methods for observing meningeal lymphatic vessels in both animal models and humans, and identify unresolved key points in meningeal lymphatic research. The aim of this review is to provide new directions for future research and therapeutic strategies targeting meningeal lymphatics by critically analyzing recent advancements in the field, identifying gaps in current knowledge, and proposing innovative approaches to address these gaps.

Accelerated ultrashort echo time quantitative magnetization transfer (UTE-qMT) imaging of macromolecular fraction (MMF) in cortical bone based on a self-attention convolutional neural network

PURPOSE

To combine ultrashort echo time quantitative magnetization transfer (UTE-qMT) imaging with a self-attention convolutional neural network (SAT-Net) for accelerated mapping of macromolecular fraction (MMF) in cortical bone.

MATERIALS AND METHODS

This institutional review board-approved study involved 31 young female subjects (young control, <45 years) and 50 postmenopausal subjects (6 normal (old control), 14 with osteopenia (osteopenia group), and 30 with osteoporosis (OP group)). After written informed consent was obtained from each subject, 15 UTE-qMT images of the tibial midshaft were acquired with three saturation powers (500°, 1000°, and 1500°) and five frequency offsets (2, 5, 10, 20, and 50 kHz) for each power to estimate the baseline MMF using a two-pool model. The densely connected SAT-Net model was used to predict bone MMF maps based on seven evenly distributed UTE-qMT images, which were well separated in terms of MT powers and frequency offsets (namely 5 and 20 kHz for 500° and 1500°, and 2, 10, 50 kHz for 1000°). Errors relative to the baseline MMF were calculated. Linear regression was used to assess the performance of the SAT-Net model. The mean MMF values for different groups were calculated.

RESULTS

Conventional two-pool modeling of seven evenly distributed UTE-qMT input images shows a significant relative error of ∼34 %. In comparison, the SAT-Net model accurately predicted MMF values for the tibial midshafts of 81 human subjects with a high correlation (R2 = 0.97, P < 0.0001) between the baseline and predicted values. The SAT-Net model accelerated UTE-qMT data acquisition by 2.1-fold, with relative errors in MMF mapping less than 2.4 %. The average MMF values were 46.10 ± 13.25 % for the young control group, 40.03 ± 2.56 % for the old control group, 31.22 ± 13.18 % for the osteopenia group, and 22.53 ± 8.12 % for the OP group.

CONCLUSION

While it is difficult to accelerate MMF mapping in bone using conventional two-pool modeling, the SAT-Net model allows accurate MMF mapping with a substantial reduction in the number of UTE-qMT input images. UTE-qMT with SAT-Net makes clinical evaluation of bone matrix possible.

Recent developments in probing the levels and flux of selected organellar cations as well as organellar mechanosensitivity

Electrochemical gradients exist not only across the plasma membrane (PM) but also across membranes of organelles. Various endomembrane-localised ion channels and transporters have been identified, the activity of which is critical for organellar (and also cellular) ionic homeostasis that underpins diverse cellular processes. Aberrant organellar ion flux underlies several diseases, identifying organellar channels and transporters as potential drug targets. Therefore, the need for probing the functions of these proteins in situ cannot be overemphasised. The acidic interior of a few organelles as well as the dynamic nature of most organelles historically presented challenges for reliable estimation of luminal ionic concentrations. But there have been significant methodological and technical advancements by now, allowing measurement of levels of specific ions within these organelles as well as their flux across endomembranes with increasing precision. Evidence also continues to amass reporting mechanosensitivity of the endomembranes and its physiological significance. Here we highlight some recent developments in tools and techniques for measuring the levels and movement of some selected organellar cations as well as organellar mechanosensitivity.

Assessing amyloid fibrils and amorphous aggregates: A review

Protein misfolding and aggregation play a central role in the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's. These aggregates manifest either as structured amyloid fibrils enriched in β-sheet conformations or as irregular amorphous aggregates with diverse morphologies. Understanding their formation, structure, and behavior is critical for deciphering disease mechanisms and developing targeted diagnostics and therapeutics. This review presents an integrated overview of both conventional and advanced techniques used to detect, distinguish, and structurally characterize these protein aggregates. It covers a range of spectroscopic and spectrometric tools, such as fluorescence, Raman, and mass spectrometry that facilitate aggregate identification. Microscopy methods, including atomic force and electron microscopy, are highlighted for morphological analysis. The review also discusses in situ detection strategies using fluorescent dyes, conformation-specific antibodies, enzymatic reporters, and real-time imaging. Separation methods like centrifugation, electrophoresis, and chromatography are outlined alongside structural analysis tools such as X-ray diffraction. Furthermore, the growing utility of computational approaches and artificial intelligence in predicting aggregation propensities and integrating biological data is emphasized. By critically evaluating each method's capabilities and limitations, this review provides a practical and forward-looking resource for researchers studying the complex landscape of protein aggregation.

Structural Investigation of the Anti-CRISPR Protein AcrIE7

The CRISPR-Cas system is an adaptive immune system in prokaryotes that provides protection against bacteriophages. As a countermeasure, bacteriophages have evolved various anti-CRISPR proteins that neutralize CRISPR-Cas immunity. Here, we report the structural and functional investigation of AcrIE7, which inhibits the type I-E CRISPR-Cas system in Pseudomonas aeruginosa. We determined both crystal and solution structures of AcrIE7, which revealed a novel helical fold. In binding assays using various biochemical methods, AcrIE7 did not tightly interact with a single Cas component in the type I-E Cascade complex or the CRISPR adaptation machinery. In contrast, AlphaFold modeling with our experimentally determined AcrIE7 structure predicted that AcrIE7 interacts with Cas3 in the type I-E CRISPR-Cas system in P. aeruginosa. Our findings are consistent with a model where AcrIE7 inhibits Cas3 and also highlight the effectiveness and limitations of AlphaFold modeling.

Pulsed Nd:YAG laser therapy accelerates fracture healing in a rat femoral osteotomy model

Aims

This study aimed to evaluate the effects of Nd:YAG laser treatment on fracture healing in a rat model. We hypothesized that laser therapy would accelerate healing by stimulating early neovascularization and osteoblast recruitment.

Methods

A total of 54 male Sprague-Dawley rats received intramedullary Kirschner wire (K-wire) osteosynthesis following femoral osteotomy, and were randomly divided into two groups (n = 27 each): the control group, and the laser group that received daily pulsed Nd:YAG laser for ten days immediately after osteotomy. Fracture sites were assessed using micro-CT (μCT; n = 8 at each timepoint), histology (n = 4), and three-point bending tests (n = 4) at week 2, week 4, and week 6, respectively. At week 2, an additional three rats per group were selected for the western blot tests.

Results

Compared to controls, the laser group showed higher vascular endothelial growth factor (VEGF), CD31, and Runx2 protein expression, and significantly higher neovascular area density and osteoblast density (p = 0.025 and p = 0.008, respectively) at week 2. At week 4, the laser treatment led to higher histological fracture healing scale and flexural modulus, and less strain (p = 0.001, p = 0.020, and p = 0.004, respectively). Macroscopically, the laser group showed higher mature bone volume fraction and radiological union score at weeks 4 and 6 (volume fraction: p = 0.017 and p = 0.001; union score: p = 0.001 and p = 0.024, respectively).

Conclusion

Pulsed Nd:YAG laser therapy accelerates multiple quantitative indicators of fracture healing within six weeks in a rat femoral osteotomy model, which was associated with enhanced angiogenesis and osteogenesis during the early healing phase.

In situ protein corona-camouflaged supramolecular assemblies remodel thrombotic microenvironment for improved arterial homeostasis

Arterial thrombosis is commonly accompanied by poor recanalization and high recurrence, typically caused by a fibrinolysis-resistant microenvironment. We identify elevated levels of plasminogen activator inhibitor-1 (PAI-1) and, notably, its strong correlation with inflammation in arterial thrombosis. To address this, small molecular inhibitors of PAI-1 and inflammation are used as bioregulators to restore vascular homeostasis. We design a carrier-free supramolecular system based on the bioregulators-tuned self-assembly of a near-infrared thrombus probe, which preferentially forms protein corona in situ to enhance plasma stability. Under acidic conditions and increased shear stress, the supramolecular assemblies disintegrate, enabling site-specific cargo release. In vivo, the probe accumulates 22.8-fold more in the thrombotic than contralateral artery. Functionally, this nanomedicine improves outcomes in mice with carotid artery thrombosis and chronic cerebral ischemia. Mechanistically, it down-regulates NF-κB signaling, inhibits NETosis and glycolysis, and up-regulates cGMP-mediated signaling, thereby alleviating inflammation and promoting fibrinolysis. This study offers an innovative codelivery strategy using supramolecular assemblies to advance therapies for arterial thrombosis.

Recent progress on glucose dehydrogenase: multifaceted applications in industrial biocatalysis, cofactor regeneration, glucose sensors, and biofuel cells

Glucose dehydrogenase (GDH) is an enzyme that catalyzes the oxidation of glucose. Through the oxidation process, glucose is converted into gluconic acid, releasing electrons in the process, which plays a crucial role in various biological and industrial applications. GDH is widely applied in molecular biology, medicine, and industry. Currently, glucose dehydrogenase is a core component in glucose test strips, commonly used in blood glucose monitoring. Additionally, due to its catalytic properties, GDH is also employed in industrial biocatalysis, coenzyme regeneration, synthetic biology, and biofuel cells. Despite being studied for many years and having achieved industrial applications in glucose biosensors, advanced research and development on glucose dehydrogenase still continues. In recent years, more attention has been focused on improving the enzyme's performance through molecular engineering or novel immobilization techniques, as well as expanding its application fields. These efforts aim to enhance the enzyme's contribution to global challenges, such as human health diagnostics, industrial biocatalysis upgrades, and the development of bioenergy. This review summarizes the recent advancements in glucose dehydrogenase research, focusing on enzyme molecular engineering and performance enhancement, novel immobilization strategies, and the latest applications in biosensors, biocatalysis, and biofuel cells.

Multichannel convolutional transformer for detecting mental disorders using electroancephalogrpahy records

Mental disorders represent a critical global health challenge that affects millions around the world and significantly disrupts daily life. Early and accurate detection is paramount for timely intervention, which can lead to improved treatment outcomes. Electroencephalography (EEG) provides the non-invasive means for observing brain activity, making it a useful tool for detecting potential mental disorders. Recently, deep learning techniques have gained prominence for their ability to analyze complex datasets, such as electroencephalography recordings. In this study, we introduce a novel deep-learning architecture for the classification of mental disorders such as post-traumatic stress disorder, depression, or anxiety, using electroencephalography data. Our proposed model, the multichannel convolutional transformer, integrates the strengths of both convolutional neural networks and transformers. Before feeding the model as low-level features, the input is pre-processed using a common spatial pattern filter, a signal space projection filter, and a wavelet denoising filter. Then the EEG signals are transformed using continuous wavelet transform to obtain a time-frequency representation. The convolutional layers tokenize the input signals transformed by our pre-processing pipeline, while the Transformer encoder effectively captures long-range temporal dependencies across sequences. This architecture is specifically tailored to process EEG data that has been preprocessed using continuous wavelet transform, a technique that provides a time-frequency representation, thereby enhancing the extraction of relevant features for classification. We evaluated the performance of our proposed model on three datasets: the EEG Psychiatric Dataset, the MODMA dataset, and the EEG and Psychological Assessment dataset. Our model achieved classification accuracies of 87.40% on the EEG and Psychological Assessment dataset, 89.84% on the MODMA dataset, and 92.28% on the EEG Psychiatric dataset. Our approach outperforms every concurrent approaches on the datasets we used, without showing any sign of over-fitting. These results underscore the potential of our proposed architecture in delivering accurate and reliable mental disorder detection through EEG analysis, paving the way for advancements in early diagnosis and treatment strategies.

Application of new approach methodologies for nonclinical safety assessment of drug candidates

The development of new approach methodologies (NAMs) and advances with in vitro testing systems have prompted revisions in regulatory guidelines and inspired dedicated in vitro/ex vivo studies for nonclinical safety assessment. This Review by a safety reflection initiative subgroup of the European Federation of Pharmaceutical Industries and Associations (EFPIA)/Preclinical Development Expert Group (PDEG) summarizes the current state and potential application of in vitro studies using human-derived material for safety assessment in drug development. It focuses on case studies from recent projects in which animal models alone proved to be limited or inadequate for safety testing. It further highlights four categories of drug candidates for which alternative in vitro approaches are applicable and discusses progress in using in vitro testing solutions for safety assessment in these categories. Finally, the article highlights new risk assessment strategies, initiatives and consortia promoting the advancement of NAMs. This collective work is meant to encourage the use of NAMs for more human-relevant safety assessment, which should ultimately result in reduced animal testing for drug development.

Development of the mechanoresponsive pericellular matrix of chondrons

Physical properties of cartilage are conferred by the composition and ultrastructure of the extracellular matrix. This study focuses on the development of the pericellular matrix (PCM), a domain that directly contacts the chondrocyte and is a key regulator of biomechanical and biochemical signaling. Using three-dimensional cell culture, microfluidic cell compression platforms, and genetic mouse models, we demonstrated that collagen VI is initially assembled at the cell surface and then displaced to form a shell at the PCM-territorial matrix boundary. Cell surface-bound hyaluronan is crucial for the assembly process, and hyaluronan-aggrecan complexes drive displacement. Integrin adhesion is not required early but is crucial to determine the final placement of the collagen VI shell. Dynamic compression accelerated PCM maturation except in aggrecan mutants. Together, these findings provide key insights into the development of the mechanosensitive PCM and establish an in vitro platform to support studies of matrix biology in normal and disease models.

Comparison of accumulation and distribution of PEGylated and CD-47-functionalized magnetic nanoporous silica nanoparticles in an in vivo mouse model of implant infection

INTRODUCTION

Drug targeting using nanoparticles is a much-researched topic. Rapid interactions of nanoparticles with the host's immune system and clearance from the circulation is a major problem resulting in non-satisfying accumulation rates in the desired region. The aim of the presented study was to compare organ distribution and implant accumulation of magnetic nanoporous silica nanoparticles (MNPSNP) functionalized with either Polyethylenglycol (PEG) or CD-47 in vivo in a mouse model of implant infection.

METHODS

Synthesis and functionalization of the magnetic core-shell nanoparticles is described. In the in vivo study, 32 mice were included and received an in staphylococcus aureus solution preincubated magnetic implant subcutaneously on the left and a nonmagnetic implant on the right hind leg. MNPSNP accumulation in the inner organs as well as on and around the implants was analyzed in dependence on the functionalization.

RESULTS

MNPSNP were successfully functionalized with PEG or CD-47. In vivo, unexpectedly both nanoparticle variants accumulated mainly in liver and spleen. In the tissue, surrounding the implants higher nanoparticle accumulation was seen in areas with more severe signs of inflammation Nanoparticles were detectable on both implant materials, but accumulation rate was very low.

CONCLUSION

Although various literature describes higher accumulation rates for nanoparticles functionalized with CD-47 in target areas and a reduced accumulation in liver and spleen, this could not be shown within this study. Possible instability or rapid agglomeration of the particles are conceivable reasons. Higher accumulation rates in areas with more severe signs of inflammation indicate that inflammatory cells might be essential for the delivery of nanoparticles into inflamed regions.

Differences and Commonalities of Electrical Stimulation Paradigms After Central Paralysis and Amputation

BACKGROUND

Patients with spinal cord injury (SCI) or with severe brain stroke suffer from life-lasting functional and sensory impairments. Other traumatic injuries such as limb loss after an accident or disease also affect motor function and sensory feedback and impair quality of life in those individuals. Invasive and non-invasive functional electrical stimulation (FES) is a well-established method to partially restore function and sensory feedback of paralyzed and phantom limbs. It is also a supporting technology for the rehabilitation of the neuromuscular system and for complementing assistive devices.

METHODS

This work reviews the current state-of-the-art of FES as a technology for restoring function and supporting rehabilitation therapy and assistive devices.

RESULTS

Electrodes, electrical stimulation, use of brain signals for rehabilitation and control, and sensory feedback are covered as parts of the whole. A perspective is given on how clinical and research protocols developed for patients with SCI and brain injuries can be translated to the treatment of patients with an amputation and vice versa. We further elaborate on how motor learning strategies with quantitative electrophysiological and kinematic measurements may help caregivers in the rehabilitation process. Insights from practitioners (collected during a workshop of the IFESS 2025) have been integrated to summarize common needs, open questions, and challenges.

CONCLUSIONS

The information from the literature and from practitioners was integrated to propose the next steps towards establishing common guidelines and measures of FES in clinical practice towards evidence-driven treatment and objective assessments.

Cellular determinants influence the red blood cell adsorption efficiency of poly(amine-co-ester) nanoparticles

Many poly(amine-co-ester) (PACE) nanoparticles, drug delivery vehicles for nucleic acid and small molecule cargoes, accumulate in the liver and spleen following intravenous administration, limiting delivery to nonhepatosplenic tissues. Red blood cell (RBC) hitchhiking, a strategy in which nanoparticles are nonspecifically adsorbed to RBCs prior to administration, has been used to modulate nanoparticle biodistribution, enabling enrichment in organs immediately downstream from the site of vascular infusion. We find that scarcely investigated cellular determinants-namely, storage duration, membrane stiffness, and membrane-bound sialic acid quantity-substantially affect PACE nanoparticle adsorption efficiency. Following development of an optimized adsorption protocol, RBC hitchhiking was shown to enhance PACE nanoparticle cargo delivery to pulmonary tissue while also increasing exposure to other assayed organs. These findings inform future RBC hitchhiking study design, implicate cellular variables as potential obstacles or boons to clinical translation, and demonstrate the delivery of nucleic acids using this strategy with the PACE nanoparticle platform.

Smart Probiotic Solutions for Mycotoxin Mitigation: Innovations in Food Safety and Sustainable Agriculture

Mycotoxin contamination poses severe risks to food safety and agricultural sustainability. Probiotic-based interventions offer a promising strategy for mitigating these toxic compounds through adsorption, biodegradation, and gut microbiota modulation. This review examines the mechanisms by which specific probiotic strains inhibit mycotoxin biosynthesis, degrade existing toxins, and enhance host detoxification pathways. Emphasis is placed on strain-specific interactions, genetic and metabolic adaptations, and advancements in formulation technologies that improve probiotic efficacy in food matrices. Also, the review explores smart delivery systems, such as encapsulation techniques and biofilm applications, to enhance probiotic stability and functionality. Issues related to regulatory approval, strain viability, and large-scale implementation are also discussed. By integrating molecular insights, applied case studies, and innovative probiotic-based solutions, this review provides a roadmap for advancing safe and sustainable strategies to combat mycotoxin contamination in food and agricultural systems.

Unraveling the unique amyloid-like aggregation behavior of the tumor suppressor p53 mutants in human cancers

Missense mutations in the tumor suppressor p53 significantly disrupt its native structure and functions, playing a pivotal role in human cancer pathogenesis. Oncogenic mutant p53 (mutp53) not only loses its tumor-suppressive capabilities but also acquires oncogenic functions, driving cancer progression, metastasis, and chemoresistance. Despite extensive research on mutp53, the role of missense mutations in triggering amyloid-like aggregation of p53 remains an underexplored and fascinating area of study. To date, over 36 proteins are known to form amyloid-like aggregates due to abnormal folding, resulting in insoluble protein fibrils that contribute to various protein misfolding diseases, including cancer. However, the precise mechanisms by which aggregated proteins induce cancer remain inadequately understood. Notably, certain p53 mutations promote its aggregation, which has emerged as a critical factor in protein aggregation-induced oncogenesis. This review delves into the mechanisms underpinning mutp53 aggregation, emphasizing unique properties such as coaggregation, bio-isolation, prion-like cell-to-cell transmission, and chemoresistance promotion. Leveraging diverse in-silico, biophysical, and biochemical approaches, we comprehensively analyzed the aggregating potential of 26 mutp53 variants among 1297 missense mutations identified in human cancers. These findings shed light on the multifaceted roles of mutp53 aggregates in oncogenesis and tumor progression. Lastly, we present an integrative exploration of emerging therapeutic strategies designed to disaggregate mutp53 aggregates, offering promising directions for targeted cancer therapy. By addressing this enigmatic aspect of mutp53 biology, our review advances the understanding of protein aggregation in cancer and identifies avenues for innovative therapeutic interventions.

Artificial intelligence for osteoporosis detection on panoramic radiography: A systematic review and meta analysis

INTRODUCTION

Osteoporosis is a disease characterized by low bone mineral density and an increased risk of fractures. In dentistry, mandibular bone morphology, assessed for example on panoramic images, has been employed to detect osteoporosis. Artificial intelligence (AI) can aid in diagnosing bone diseases from radiographs. We aimed to systematically review, synthesize and appraise the available evidence supporting AI in detecting osteoporosis on panoramic radiographs.

DATA

Studies that used AI to detect osteoporosis on dental panoramic images were included.

SOURCES

On April 8, 2023, a first comprehensive search of electronic databases was conducted, including PubMed, Scopus, Embase, IEEE, arXiv, and Google Scholar (grey literature). This search was subsequently updated on October 6, 2024.

STUDY SELECTION

The Quality Assessment and Diagnostic Accuracy Tool-2 was employed to determine the risk of bias in the studies. Quantitative analyses involved meta-analyses of diagnostic accuracy measures, including sensitivity and specificity, yielding Diagnostic Odds Ratios (DOR) and synthesized positive likelihood ratios (LR+). The certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation system.

RESULTS

A total of 24 studies were included. Accuracy ranged from 50% to 99%, sensitivity from 50% to 100%, and specificity from 38% to 100%. A minority of studies (n=10) had a low risk of bias in all domains, while the majority (n=18) showed low risk of applicability concerns. Pooled sensitivity was 87.92% and specificity 81.93%. DOR was 32.99, and L+ 4.87. Meta-regression analysis indicated that sample size had only a marginal impact on heterogeneity (R² = 0.078, p = 0.052), suggesting other study-level factors may contribute to variability. Egger's test suggested potential small-study effects (p < 0.001), indicating a risk of publication bias.

CONCLUSION

AI, particularly deep learning, showed high diagnostic accuracy in detecting osteoporosis on panoramic radiographs. The results indicate a strong potential for AI to enhance osteoporosis screening in dental settings. However, significant heterogeneity across studies and potential small-study effects highlight the need for further validation, standardization, and larger, well-powered studies to improve model generalizability.

CLINICAL SIGNIFICANCE

The application of AI in analyzing panoramic radiographs could transform osteoporosis screening in routine dental practice by providing early and accurate diagnosis. This has the potential to integrate osteoporosis detection seamlessly into dental workflows, improving patient outcomes and enabling timely referrals for medical intervention. Addressing issues of model validation and comparability is critical to translating these findings into widespread clinical use.

Self-assembled organoid-tissue modules for scalable organoid engineering: Application to chondrogenic regeneration

Tissue engineering has made significant strides in creating biomimetic grafts for the repair and regeneration of damaged tissues; however, the scalability of engineered tissue constructs remains a major technical hurdle. This study introduces a method for generating organoid-tissue modules (Organoid-TMs) through scaffold-free self-assembly of microblocks (MiBs) derived from adipose-derived mesenchymal stem cells (ADMSCs). The key parameters influencing Organoid-TM formation were identified as the density of MiBs and the controlled mixing ratio of large and small MiBs. The resulting Organoid-TM exhibited a distinctive cup-shaped morphology, a millimeter-scale structure with enhanced nutrient and oxygen diffusion compared to conventional spherical aggregates. Despite their larger size, Organoid-TMs maintained ADMSC stemness and differentiation potential, while stemness and differentiation were halted during fabrication. Organoid-TMs receiving chondrogenic cues during fabrication were transplanted into cartilage defect sites in animal models, demonstrating cartilage regeneration efficacy in a scaffold-independent and xeno-free manner. This fabrication method represents a highly reproducible and consistent process for developing spheroids or organoids, offering a robust platform for regenerative medicine applications. Specifically, Organoid-TMs provide a foundational framework for therapeutic strategies targeting cartilage defects and osteoarthritis, paving the way for advancements in tissue-engineered therapeutics. STATEMENT OF SIGNIFICANCE: This study introduces a distinct approach in tissue engineering, utilizing self-assembled Organoid-Tissue Modules (Organoid-TMs) to address persistent challenges in scalable organoid production and cartilage regeneration. By leveraging adipose-derived mesenchymal stem cells (ADMSCs) and carefully optimizing the size, ratio, and spatial organization of microblocks (MiBs), we successfully generated millimeter-scale Organoid-TMs. The distinctive cup-shaped architecture of these Organoid-TMs enhances oxygen and nutrient diffusion, effectively overcoming limitations such as core necrosis typically encountered in large-scale organoid culture. This system demonstrated substantial regenerative potential, particularly in chondrogenic differentiation and cartilage repair in both rabbit and pig models, without the use of artificial scaffolds or xenogenic materials.

The biomedical application of inorganic metal nanoparticles in aging and aging-associated diseases

Aging and aging-associated diseases (AAD), including neurodegenerative disease, cancer, cardiovascular diseases, and diabetes, are inevitable process. With the gradual improvement of life style, life expectancy is gradually extended. However, the extended lifespan has not reduced the incidence of disease, and most elderly people are in ill-health state in their later years. Hence, understanding aging and AAD are significant for reducing the burden of the elderly. Inorganic metal nanoparticles (IMNPs) predominantly include gold, silver, iron, zinc, titanium, thallium, platinum, cerium, copper NPs, which has been widely used to prevent and treat aging and AAD due to their superior properties (essential metal ions for human body, easily synthesis and modification, magnetism). Therefore, a systematic review of common morphological alternations of senescent cells, altered genes and signal pathways in aging and AAD, and biomedical applications of IMNPs in aging and AAD is crucial for the further research and development of IMNPs in aging and AAD. This review focus on the existing research on cellular senescence, aging and AAD, as well as the applications of IMNPs in aging and AAD in the past decade. This review aims to provide cutting-edge knowledge involved with aging and AAD, the application of IMNPs in aging and AAD to promote the biomedical application of IMNPs in aging and AAD.

Exploring the diagnostic landscape: Portable aptasensors in point-of-care testing

Aptamers, discovered in the 1990s, have marked a significant milestone in the fields of therapeutics and diagnostics. This review provides a comprehensive survey of aptamers, focusing on their diagnostic applications. It especially encapsulates a decade of aptamer, encompassing research, patents, and market trends. The unique properties and inherent stability of aptamers are discussed, highlighting their potential for various clinical applications. It goes on to introduce biosensor design, emphasizing the advantages of aptamers over antibodies as conventional molecular recognition interface. The operation and design of aptasensors are examined, with a focus on single- and dual-site binding configurations and their respective recognition modes. Paper-based sensors are highlighted as cost-effective, user-friendly alternatives that are gaining widespread adoption, particularly in point-of-care platforms.

Effects of decellularization on glycosaminoglycans and collagen macromolecules in bovine bone extracellular matrix

Bovine bones were decellularized to obtain extracellular matrices with potential use for Tissue Bioengineering. The objective of the present study was to develop a decellularization protocol for bovine trabecular bone while maintaining the integrity of the extracellular matrix (ECM). The protocol proved to be effective in significantly reducing the Amount of genetic material and cellular content, and it was considered innovative, being filed as a patent. The scaffold obtained showed a reduction in the content of glycosaminoglycans (GAGs) and collagen. Even with the loss of these ECM components, the material obtained can be considered an alternative for use in Tissue Engineering and Regenerative Medicine.

Hydrogel Adhesive Integrated-Microstructured Electrodes for Cuff-Free, Less-Invasive, and Stable Interface for Vagus Nerve Stimulation

Vagus nerve stimulation (VNS) is a recognized treatment for neurological disorders, yet the surgical procedure carries significant risks. During the process of isolating or cuffing the vagus nerve, there is a danger of damaging the nerve itself or the adjacent carotid artery or jugular vein. To minimize this risk, here we introduce a novel hydrogel adhesive-integrated and stretchable microdevice that provides a less invasive,  cuff-free option for interfacing with the vagus nerve. The device features a novel hydrogel adhesive formulation that enables crosslinking on biological tissue. The inclusion of kirigami structures within the thin-film microdevice creates space for uniform hydrogel-to-epineurium contact while accommodating the stiffness changes of the hydrogel upon hydration. Using a rodent model, we demonstrate a robust device adhesion on a partially exposed vagus nerve in physiological fluid even without the vagus nerve isolation and cuffing process. Our device elicted stable and clear evoked compound action potential (~1500 µV peak-to-peak) in C-fibers with a current amplitude of 0.4 mA. We believe this innovative platform provides a novel, less-risky approach to interface with fragile nerve and vascular structures during VNS implantation.

Unravelling molecular dynamics in living cells: Fluorescent protein biosensors for cell biology

Genetically encoded, fluorescent protein (FP)-based Förster resonance energy transfer (FRET) biosensors are microscopy imaging tools tailored for the precise monitoring and detection of molecular dynamics within subcellular microenvironments. They are characterised by their ability to provide an outstanding combination of spatial and temporal resolutions in live-cell microscopy. In this review, we begin by tracing back on the historical development of genetically encoded FP labelling for detection in live cells, which lead us to the development of early biosensors and finally to the engineering of single-chain FRET-based biosensors that have become the state-of-the-art today. Ultimately, this review delves into the fundamental principles of FRET and the design strategies underpinning FRET-based biosensors, discusses their diverse applications and addresses the distinct challenges associated with their implementation. We place particular emphasis on single-chain FRET biosensors for the Rho family of guanosine triphosphate hydrolases (GTPases), pointing to their historical role in driving our understanding of the molecular dynamics of this important class of signalling proteins and revealing the intricate relationships and regulatory mechanisms that comprise Rho GTPase biology in living cells.

Trends in nanobody radiotheranostics

As the smallest antibody fragment with specific binding affinity, nanobody-based nuclear medicine has demonstrated significant potential to revolutionize the field of precision medicine, supported by burgeoning preclinical investigations and accumulating clinical evidence. However, the visualization of nanobodies has also exposed their suboptimal biodistribution patterns, which has spurred collaborative efforts to refine their pharmacokinetic and pharmacodynamic profiles for improved therapeutic efficacy. In this review, we present clinical results that exemplify the benefits of nanobody-based molecular imaging in cancer diagnosis. Moreover, we emphasize the indispensable role of molecular imaging as a tool for evaluating and optimizing nanobodies, thereby expanding their therapeutic potential in cancer treatment in the foreseeable future.

Harnessing Thrombospondin-1-Enabled Decellularized Nucleus Pulposus Matrices and Elastin-Like Recombinamers to Rebuild an Avascular Analogue of the Intervertebral Disc

With the degeneration of the intervertebral disc (IVD), the ingrowth of vascular and neural structures occurs. Both nerves and blood vessels engage in the development of inflammation and the onset of discogenic pain. The present study aimed to produce a hierarchical biomaterial capable of inhibiting angiogenesis by emulating the microenvironment of non-degenerated IVDs. To this end, we have incorporated an angiogenesis modulator-thrombospondin-1 (TSP-1) into a three-dimensional (3D) hydrogel network containing decellularized nucleus pulposus (dNPs) and azide-cyclooctyne modified elastin-like recombinamers (ELRs). Following the decellularization of nucleus pulposus (NPs) isolated from bovine tissues, pre-gels (pGs) were assembled based on the acid-pepsin extraction of soluble collagens found in the dNPs. Given the inherent affinity of these macromolecules to TSP-1, which was corroborated by immunohistochemical analysis and FT-IR spectroscopy, the pGs were supplemented with two concentrations of TSP-1. Angiogenesis was evaluated using the chick chorioallantoic membrane (CAM) in vivo model. Conjugation of TSP-1 with the pGs resulted in a synergistic suppression of blood vessel formation. Complexation with the ELRs improved the viscoelastic moduli and the structural stability of the hydrogels, which maintained their hydration and osmolarity properties due to the presence of the dNPs. When placed in direct contact with human primary fibroblasts, the materials displayed high cytocompatibility and tunable degradation rates. Our findings indicate that TSP-1-enabled dNP-derived pGs inhibit angiogenesis in vivo, while the presence of the ELRs aids in improving the mechanical properties of the hydrogels, thus providing a platform for rebuilding an avascular analogue of the healthy IVD.

Transport across the thoracic aortic wall: implications for aneurysm pathobiology, diagnosis, and treatment

Thoracic aortic aneurysms (TAAs) are a dilation of the aorta that may fatally dissect or rupture. The current clinical management for TAA is continuous monitoring and surgical replacement once the aortic diameter reaches a specified size or rate of growth. Although operative intervention is often successful in preventing fatal outcomes, not all patients will reach surgical criteria before an aortic event, and the surgery carries significant risk with a potential requirement for reoperation. There is a need for patient-specific diagnostic tools and/or novel therapeutics to treat TAA. In this review, we discuss fluid and solute transport through the aortic wall (transmural aortic transport), its potential contributions to TAA progression, and possible applications for diagnosis and treatment. We first discuss the structural organization of the aortic wall with a focus on cellular and extracellular matrix (ECM) changes associated with TAA that may alter transmural transport. We then focus on aortic transmural transport processes defined with biphasic and multiphasic theory. Biphasic theory describes fluid interactions with a porous solid (i.e., the aortic wall), whereas multiphasic theory describes fluid and solute(s) interactions with a porous solid. We summarize experimental and computational methods to quantify transport through the aortic wall. Finally, we discuss how transmural transport may be used to diagnose, monitor, or treat TAA. Further understanding of transmural transport may lead to new insights into TAA pathobiology and future clinical solutions.

Significant Radiation Reduction Using Cloud-Based AI Imaging in Manually Matched Cohort of Complex Aneurysm Repair

BACKGROUND

Cloud-based, surgical augmented intelligence (Cydar Medical, Cambridge, United Kingdom) can be used for surgical planning and intraoperative imaging guidance during complex endovascular aortic procedures. We aim to evaluate radiation exposure, operative safety metrics, and postoperative renal outcomes following implementation of Cydar imaging guidance using a manually matched cohort of aortic procedures.

METHODS

We retrospectively reviewed our prospectively maintained database of endovascular aortic cases. Patients repaired using Cydar imaging were matched to patients who underwent a similar procedure without using Cydar. Matching was performed manually on a 1:1 basis using anatomy, device configuration, number of branches/fenestrations, and adjunctive procedures including in-situ laser fenestration. Radiation, contrast use, and other operative metrics were compared. Preoperative and postoperative maximum creatinine was compared to assess for acute kidney injury (AKI) based on risk, injury, failure, loss of kidney function, and end-stage kidney disease (RIFLE) criteria.

RESULTS

Hundred patients from 2012 to 2023 were identified: 50 cases (38 fenestrated endovascular aortic repairs, 2 thoracic endovascular aortic repairs, 3 octopus-type thoracoabdominal aortic aneurysm repair, 7 endovascular aneurysm repairs) where Cydar imaging was used, with suitable matches to 50 non-Cydar cases. Baseline characteristics including body mass index did not differ significantly between the 2 groups (27.8 ± 5.6 vs. 26.7 ± 6.1; P = 0.31). Radiation dose was significantly lower in the Cydar group (2529 ± 2256 vs. 3676 ± 2976 mGy; P < 0.03), despite there being no difference in fluoroscopy time (51 ± 29.4 vs. 58 ± 37.2 min; P = 0.37). Contrast volume (94 ± 37.4 vs. 93 ± 43.9 mL; P = 0.73), estimated blood loss (169 ± 223 vs. 193 ± 222 mL; P = 0.97), and procedure time (154 ± 78 vs. 165 ± 89.1 min) did not differ significantly. Additionally, Cydar versus non-Cydar patients did not show a significant difference between precreatinine and postcreatinine changes (0.13 ± 0.08 vs. 0.05 ± 0.07; P = 0.34). Only one patient in the non-Cydar group met RIFLE criteria for AKI postoperatively.

CONCLUSION

The use of cloud-based augmented intelligence imaging was associated with a significant reduction in radiation dose in a cohort of matched aortic procedures but did not appear to affect other parameters or renal function. Even with advanced imaging, surgeons should remain conscientious about radiation safety and administration of nephrotoxic contrast agents.

A Hundred Ways to Encode Sound Signals for Cochlear Implants

Cochlear implants are the most successful neural prostheses used to restore hearing in severe-to-profound hearing-impaired individuals. The field of cochlear implant coding investigates interdisciplinary approaches to translate acoustic signals into electrical pulses transmitted at the electrode-neuron interface, ranging from signal preprocessing algorithms, enhancement, and feature extraction methodologies to electric signal generation. In the last five decades, numerous coding strategies have been proposed clinically and experimentally. Initially developed to restore speech perception, increasing computational possibilities now allow coding of more complex signals, and new techniques to optimize the transmission of electrical signals are constantly gaining attention. This review provides insights into the history of multichannel coding and presents an extensive list of implemented strategies. The article briefly addresses each method and considers promising future directions of neural prostheses and possible signal processing, with the ultimate goal of providing a current big picture of the large field of cochlear implant coding.

Utilizing Pix2Pix conditional generative adversarial networks to recover missing data in preclinical PET scanner sinogram gaps

BACKGROUND

The presence of a gap between adjacent detector blocks in Positron Emission Tomography (PET) scanners introduces a partial loss of projection data, which can degrade the image quality and quantitative accuracy of reconstructed PET images. This study suggests a novel approach for filling missing data from sinograms generated from preclinical PET scanners using a combination of an inpainting method and the Pix2Pix conditional generative adversarial network (cGAN).

MATERIALS AND METHODS

Twenty mice and Image Quality (IQ) phantom were scanned by a small animal Xtrim PET scanner, resulting in 7500 raw sinograms used for network training and test datasets. The absence of gap-free sinograms as the target for neural network training was a challenge. This issue was solved by artificially generating gap-free sinograms from the original sinogram. To assess the performance of the proposed approach, the sinograms were reconstructed using the ordered subset expectation maximization (OSEM) algorithm. The overall performance of the proposed network and the quality of the resulting images were quantitatively compared using various metrics, including the root mean squared error (RMSE), structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR).

RESULTS

The Pix2Pix cGAN approach achieved an RMSE of 9.34 × 10-4 ± 5.7 × 10-5 and an SSIM of 99.984 × 10-2 ± 1.8 × 10-5, considering the corresponding inpainted sinograms as the target.

CONCLUSION

The proposed approach can retrieve missing sinogram data by learning a map derived from the whole sinogram compared to the adjacent pixels, which leads to better quantitative accuracy and improved reconstructed images.

NIR-Propelled Thermosensitive Bowl-Shaped Nanomotors with High Penetration and Targeting for Photoacoustic Imaging Guided Thrombolysis Therapy

Traditional antithrombotic therapeutic strategies encounter challenges including heightened bleeding risks, short circulation times, low targeting ability, and inferior thrombus penetration. Therefore, a novel thrombolysis nanodrug (APBUL) is designed that incorporates urokinase (UK) loaded onto the surface of bowl-shaped nanomotors (APBs) encapsulated within fibrin peptide (CREKA)-modified thermosensitive liposomes, presenting an innovative therapeutic platform for thrombolysis. APBUL leverages CREKA's targeting ability for thrombus accumulation. Subsequently, under the irradiation of near-infrared light, the thermosensitive liposomal shell undergoes controlled disruption, releasing internal APBs and UK. Then, the APBs move directionally though thermophoresis effect, facilitating photothermal therapy and deep thrombus penetration, and synergistically enhancing UK release and diffusion to optimize thrombolysis. Moreover, the APBUL possesses a catalase-like activity, catalyzing hydrogen peroxide into oxygen to alleviate oxidative stress and inflammatory factors at the thrombus site, thereby lowering the recurrence risk. Combined with the ability of APBUL's photoacoustic imaging, this new strategy is expected to provide an inspiring idea for the integrated use of clinical thrombolytic therapy in diagnosis, imaging, and treatment.

Machine learning models based on FEM simulation of hoop mode vibrations to enable ultrasonic cuffless measurement of blood pressure

Blood pressure (BP) is one of the vital physiological parameters, and its measurement is done routinely for almost all patients who visit hospitals. Cuffless BP measurement has been of great research interest over the last few years. In this paper, we aim to establish a method for cuffless measurement of BP using ultrasound. In this method, the arterial wall is pushed with an acoustic radiation force impulse (ARFI). After the completion of the ARFI pulse, the artery undergoes impulsive unloading which stimulates a hoop mode vibration. We designed two machine learning (ML) models which make it possible to estimate the internal pressure of the artery using ultrasonically measurable parameters. To generate the training data for the ML models, we did extensive finite element method (FEM) eigen frequency simulations for different tubes under pressure by sweeping through a range of values for inner lumen diameter (ILD), tube density (TD), elastic modulus, internal pressure (IP), tube length, and Poisson's ratio. Through image processing applied on images of different eigen modes supported for each simulated case, we identified its hoop mode frequency (HMF). Two different ML models were designed based on the simulated data. One is a four-parameter model (FPM) that takes tube thickness (TT), TD, ILD, and HMF as the inputs and gives out IP as output. Second is a three-parameter model (TPM) that takes TT, ILD, and HMF as inputs and IP as output. The accuracy of these models was assessed using simulated data, and their performance was confirmed through experimental verification on two arterial phantoms across a range of pressure values. The first prediction model (FPM) exhibited a mean absolute percentage error (MAPE) of 5.63% for the simulated data and 3.68% for the experimental data. The second prediction model (TPM) demonstrated a MAPE of 6.5% for simulated data and 8.73% for experimental data. We were able to create machine learning models that can measure pressure within an elastic tube through ultrasonically measurable parameters and verified their performance to be adequate for BP measurement applications. This work establishes a pathway for cuffless, continuous, real-time, and non-invasive measurement of BP using ultrasound.

Bioaugmented design and functional evaluation of low damage implantable array electrodes

Implantable neural electrodes are key components of brain-computer interfaces (BCI), but the mismatch in mechanical and biological properties between electrode materials and brain tissue can lead to foreign body reactions and glial scarring, and subsequently compromise the long-term stability of electrical signal transmission. In this study, we proposed a new concept for the design and bioaugmentation of implantable electrodes (bio-array electrodes) featuring a heterogeneous gradient structure. Different composite polyaniline-gelatin-alginate based conductive hydrogel formulations were developed for electrode surface coating. In addition, the design, materials, and performance of the developed electrode was optimized through a combination of numerical simulations and physio-chemical characterizations. The long-term biological performance of the bio-array electrodes were investigated in vivo using a C57 mouse model. It was found that compared to metal array electrodes, the surface charge of the bio-array electrodes increased by 1.74 times, and the impedance at 1 kHz decreased by 63.17 %, with a doubling of the average capacitance. Long-term animal experiments showed that the bio-array electrodes could consistently record 2.5 times more signals than those of the metal array electrodes, and the signal-to-noise ratio based on action potentials was 2.1 times higher. The study investigated the mechanisms of suppressing the scarring effect by the bioaugmented design, revealing reduces brain damage as a result of the interface biocompatibility between the bio-array electrodes and brain tissue, and confirmed the long-term in vivo stability of the bio-array electrodes.

Importance of Considering Temporal Variations in Pulse Wave Velocity for Accurate Blood Pressure Prediction

PURPOSE

Continuous, cuffless blood pressure (BP) monitoring devices based on measuring pulse wave velocity (PWV) or pulse transit time (PTT) are emerging but are often plagued by large prediction errors. A key issue is that these techniques typically rely on a single PWV value, assuming a linear response and small arterial wall deformations. However, arterial response to BP is inherently nonlinear, with PWV varying over time [PWV(t)] by up to 50% during a cardiac cycle. This study evaluates the impact of assuming a single PWV on BP prediction accuracy.

METHOD

Using a Fluid-structure Interaction (FSI) testbed, we simulate the radial and common carotid arteries with the Holzapfel-Gasser-Ogden (HGO) constitutive model to capture nonlinear arterial behavior under a pulsatile physiological blood flow. Pressure data from FSI simulation are used as the ground truth, while inner area A(t) and two PWV values, at diastole and systole, serve as inputs to BP prediction models. Two models are tested: one using a single PWV value, emulating existing PWV-based BP prediction methods; another using the two PWV values to account for PWV(t).

RESULTS

The single-PWV BP model produced prediction errors of 17.44 mmHg and 6.57 mmHg for the radial and carotid arteries, respectively. The model incorporating two PWV values reduced these errors by 90.6% and 96.8%, respectively.

CONCLUSION

Relying on a single PWV in BP prediction models can lead to significant errors. To improve BP accuracy, future efforts should focus on incorporating PWV(t), or at least both diastolic and systolic PWV values, into these models.

Evaluation of the effect of grape seed extract- loaded chitosan nanoparticles on cryptosporidiosis in dexamethasone immunosuppressed male mice

Cryptosporidiosis is a worldwide health problem that results in an economic loss. The disease is caused by the protozoan Cryptosporidium spp. Individuals with suppressed immunity, like those with organ transplantation, cancer and human immunodeficiency virus syndrome, suffer from the infection that may lead to the death. Nitazoxanide (NTZ) is the approved FDA treatment for cryptosporidiosis in immunocompetent individuals. There is an urgent need to find a new natural treatment that can replace NTZ in immunosuppressed hosts. The study aimed to use grape seed extract loaded chitosan nanoparticles (GSEx-CHNPs) in treatment of cryptosporidiosis in immunosuppressed male mice. GSEx was prepared by the alcoholic extraction method followed by the identification of its bioactive components. GSEx-CHNPs were synthesized by ionic gelation method and physically characterized then their activities were examined in vitro. The experimental groups, included immunocompetent and immunosuppressed groups, was treated with NPs for 14 days post infection (PI). The results showed the presence of many phenolic compounds in the GSEx. GSEx-CHNPs significantly improved the loss in animals body weight, cleared the infection and amolerated the serum cytokines levels. GSEx-CHNPs showed anti-cryptosporidial activity especially in immunosuppressed mice model. Where, it ameliorated the disturbance in the cytokine profile leading to an anti-inflammatory response.

Understanding the Lymphatic System: Tissue-on-Chip Modeling

The lymphatic vasculature plays critical roles in maintaining fluid homeostasis, transporting lipid, and facilitating immune surveillance. A growing body of work has identified lymphatic dysfunction as contributing to the severity of myriad diseases and to systemic inflammation, as well as modulating drug responses. Here, we review efforts to reconstruct lymphatic vessels in vitro toward establishing humanized, functional models to advance understanding of lymphatic biology and pathophysiology. We first review lymphatic endothelial cell biology and the biophysical lymphatic microenvironment, with a focus on features that are unique to the lymphatics and that have been used as design parameters for lymphatic-on-chip devices. We then discuss the state of the art for recapitulating lymphatic function in vitro, and we acknowledge limitations and challenges to current approaches. Finally, we discuss opportunities and the need for further development of microphysiological lymphatic systems to bridge the gap in model systems between lymphatic cell culture and animal physiology.

A new model of heart failure with preserved ejection fraction induced by metabolic syndrome in Ossabaw miniature swine

A major obstacle to progress in heart failure with preserved ejection fraction (HFpEF) is the paucity of clinically relevant animal models. We developed a large, translationally relevant model in Ossabaw minipigs, which are genetically predisposed to the metabolic syndrome (MetS). Pigs were fed a "Western diet" high in calories, fructose, fat, cholesterol, and salt and received 1-2 deoxy-corticosterone acetate (DOCA) depots (n = 10). After 6 months, they exhibited liver function abnormalities and marked increases in body weight, arterial blood pressure, serum cholesterol and triglycerides, and plasma glucose and insulin levels (glucose tolerance test), indicating the development of a full MetS. Echocardiography demonstrated no change in LV ejection fraction but progressive concentric LV hypertrophy and left atrial dilatation. Doppler echocardiography showed increased E/e' ratio and increased peak early (E) and peak late atrial (A) transmitral inflow velocities, with no change in E/A ratio. Right heart catheterization demonstrated increased central venous pressure, pulmonary arterial systolic pressure, and pulmonary capillary wedge pressure. Clinically, pigs exhibited impaired exercise capacity, assessed by treadmill tests, associated with chronotropic incompetence. Pathologic examination showed significant myocardial fibrosis, myocyte hypertrophy, and liver fibrosis. In contrast, lean pigs fed a standard diet (n = 3) did not show any changes at 6 months. The Ossabaw porcine model described herein is unique in that it recapitulates the entire constellation of major multiorgan comorbidities and hemodynamic, clinical, and metabolic features of MetS-driven human HFpEF: obesity, arterial hypertension, hyperlipidemia, glucose intolerance, insulin resistance, liver fibrosis and dysfunction, pulmonary hypertension, increased LV filling pressures, concentric LV hypertrophy, LV diastolic dysfunction with preserved systolic function, and impaired exercise capacity. Because of its high clinical relevance, this model is well-suited for exploring the pathophysiology of MetS-driven HFpEF and the efficacy of new therapies.

Conformable Piezoelectric Devices and Systems for Advanced Wearable and Implantable Biomedical Applications

With increasing demands for continuous health monitoring remotely, wearable and implantable devices have attracted considerable interest. To fulfill such demands, novel materials and device structures have been investigated, since commercial biomedical devices are not compatible with flexible and conformable form factors needed for soft tissue monitoring and intervention. Among various materials, piezoelectric materials have been widely adopted for multiple applications including sensing, energy harvesting, neurostimulation, drug delivery, and ultrasound imaging owing to their unique electromechanical conversion properties. In this review, we provide a comprehensive overview of piezoelectric-based wearable and implantable biomedical devices. We first provide the basic principles of piezoelectric devices and device design strategies for wearable and implantable form factors. Then, we discuss various state-of-the-art applications of wearable and implantable piezoelectric devices and their design strategies. Finally, we demonstrate several challenges and outlooks for designing piezoelectric-based conformable biomedical devices.

Conveying tactile object characteristics through customized intracortical microstimulation of the human somatosensory cortex

Microstimulation of the somatosensory cortex can evoke tactile percepts in people with spinal cord injury, providing a means to restore touch. While location and intensity can be reliably conveyed, two issues that prevent creating more complex naturalistic sensations are a lack of methods to effectively scan the large stimulus parameter space and difficulties with assessing percept quality. Here, we address both challenges with an experimental paradigm that enables three male individuals with tetraplegia to control their stimulation parameters in a blinded fashion to create sensations for different virtual objects. Using this method, participants can reliably create object-specific sensations and report vivid object-appropriate characteristics. Moreover, both linear classifiers and participants can match stimulus profiles with their respective objects significantly above chance without any visual cues. Confusion between two sensations increases as the associated objects share more tactile characteristics. We conclude that while visual information contributes to the experience of the artificially evoked sensations, microstimulation in the somatosensory cortex itself can evoke intuitive percepts with a variety of tactile properties. This self-guided stimulation approach may be used to effectively characterize percepts from future stimulation paradigms.