-
Cell Death & Disease Jul 2024The present study aims to develop and characterize a controlled-release delivery system for protein therapeutics in skeletal muscle regeneration following an acute...
The present study aims to develop and characterize a controlled-release delivery system for protein therapeutics in skeletal muscle regeneration following an acute injury. The therapeutic protein, a membrane-GPI anchored protein called Cripto, was immobilized in an injectable hydrogel delivery vehicle for local administration and sustained release. The hydrogel was made of poly(ethylene glycol)-fibrinogen (PEG-Fibrinogen, PF), in the form of injectable microspheres. The PF microspheres exhibited a spherical morphology with an average diameter of approximately 100 micrometers, and the Cripto protein was uniformly entrapped within them. The release rate of Cripto from the PF microspheres was controlled by tuning the crosslinking density of the hydrogel, which was varied by changing the concentration of poly(ethylene glycol) diacrylate (PEG-DA) crosslinker. In vitro experiments confirmed a sustained-release profile of Cripto from the PF microspheres for up to 27 days. The released Cripto was biologically active and promoted the in vitro proliferation of mouse myoblasts. The therapeutic effect of PF-mediated delivery of Cripto in vivo was tested in a cardiotoxin (CTX)-induced muscle injury model in mice. The Cripto caused an increase in the in vivo expression of the myogenic markers Pax7, the differentiation makers eMHC and Desmin, higher numbers of centro-nucleated myofibers and greater areas of regenerated muscle tissue. Collectively, these results establish the PF microspheres as a potential delivery system for the localized, sustained release of therapeutic proteins toward the accelerated repair of damaged muscle tissue following acute injuries.
Topics: Animals; Muscle, Skeletal; Mice; Polyethylene Glycols; Delayed-Action Preparations; Microspheres; Fibrinogen; Hydrogels; Regeneration; Myoblasts; Humans; Cell Proliferation; PAX7 Transcription Factor; Male; Mice, Inbred C57BL; Muscular Diseases
PubMed: 38956034
DOI: 10.1038/s41419-024-06645-2 -
Cardiovascular Engineering and... Jul 2024Advanced material models and material characterization of soft biological tissues play an essential role in pre-surgical planning for vascular surgeries and... (Review)
Review
BACKGROUND AND OBJECTIVE
Advanced material models and material characterization of soft biological tissues play an essential role in pre-surgical planning for vascular surgeries and transcatheter interventions. Recent advances in heart valve engineering, medical device and patch design are built upon these models. Furthermore, understanding vascular growth and remodeling in native and tissue-engineered vascular biomaterials, as well as designing and testing drugs on soft tissue, are crucial aspects of predictive regenerative medicine. Traditional nonlinear optimization methods and finite element (FE) simulations have served as biomaterial characterization tools combined with soft tissue mechanics and tensile testing for decades. However, results obtained through nonlinear optimization methods are reliable only to a certain extent due to mathematical limitations, and FE simulations may require substantial computing time and resources, which might not be justified for patient-specific simulations. To a significant extent, machine learning (ML) techniques have gained increasing prominence in the field of soft tissue mechanics in recent years, offering notable advantages over conventional methods. This review article presents an in-depth examination of emerging ML algorithms utilized for estimating the mechanical characteristics of soft biological tissues and biomaterials. These algorithms are employed to analyze crucial properties such as stress-strain curves and pressure-volume loops. The focus of the review is on applications in cardiovascular engineering, and the fundamental mathematical basis of each approach is also discussed.
METHODS
The review effort employed two strategies. First, the recent studies of major research groups actively engaged in cardiovascular soft tissue mechanics are compiled, and research papers utilizing ML and deep learning (DL) techniques were included in our review. The second strategy involved a standard keyword search across major databases. This approach provided 11 relevant ML articles, meticulously selected from reputable sources including ScienceDirect, Springer, PubMed, and Google Scholar. The selection process involved using specific keywords such as "machine learning" or "deep learning" in conjunction with "soft biological tissues", "cardiovascular", "patient-specific," "strain energy", "vascular" or "biomaterials". Initially, a total of 25 articles were selected. However, 14 of these articles were excluded as they did not align with the criteria of focusing on biomaterials specifically employed for soft tissue repair and regeneration. As a result, the remaining 11 articles were categorized based on the ML techniques employed and the training data utilized.
RESULTS
ML techniques utilized for assessing the mechanical characteristics of soft biological tissues and biomaterials are broadly classified into two categories: standard ML algorithms and physics-informed ML algorithms. The standard ML models are then organized based on their tasks, being grouped into Regression and Classification subcategories. Within these categories, studies employ various supervised learning models, including support vector machines (SVMs), bagged decision trees (BDTs), artificial neural networks (ANNs) or deep neural networks (DNNs), and convolutional neural networks (CNNs). Additionally, the utilization of unsupervised learning approaches, such as autoencoders incorporating principal component analysis (PCA) and/or low-rank approximation (LRA), is based on the specific characteristics of the training data. The training data predominantly consists of three types: experimental mechanical data, including uniaxial or biaxial stress-strain data; synthetic mechanical data generated through non-linear fitting and/or FE simulations; and image data such as 3D second harmonic generation (SHG) images or computed tomography (CT) images. The evaluation of performance for physics-informed ML models primarily relies on the coefficient of determination . In contrast, various metrics and error measures are utilized to assess the performance of standard ML models. Furthermore, our review includes an extensive examination of prevalent biomaterial models that can serve as physical laws for physics-informed ML models.
CONCLUSION
ML models offer an accurate, fast, and reliable approach for evaluating the mechanical characteristics of diseased soft tissue segments and selecting optimal biomaterials for time-critical soft tissue surgeries. Among the various ML models examined in this review, physics-informed neural network models exhibit the capability to forecast the mechanical response of soft biological tissues accurately, even with limited training samples. These models achieve high values ranging from 0.90 to 1.00. This is particularly significant considering the challenges associated with obtaining a large number of living tissue samples for experimental purposes, which can be time-consuming and impractical. Additionally, the review not only discusses the advantages identified in the current literature but also sheds light on the limitations and offers insights into future perspectives.
PubMed: 38956008
DOI: 10.1007/s13239-024-00737-y -
Documenta Ophthalmologica. Advances in... Jul 2024Multiple sclerosis (MS) is a neuro-inflammatory disease affecting the central nervous system (CNS), where the immune system targets and damages the protective myelin...
PURPOSE
Multiple sclerosis (MS) is a neuro-inflammatory disease affecting the central nervous system (CNS), where the immune system targets and damages the protective myelin sheath surrounding nerve fibers, inhibiting axonal signal transmission. Demyelinating optic neuritis (ON), a common MS symptom, involves optic nerve damage. We've developed NeuroVEP, a portable, wireless diagnostic system that delivers visual stimuli through a smartphone in a headset and measures evoked potentials at the visual cortex from the scalp using custom electroencephalography electrodes.
METHODS
Subject vision is evaluated using a short 2.5-min full-field visual evoked potentials (ffVEP) test, followed by a 12.5-min multifocal VEP (mfVEP) test. The ffVEP evaluates the integrity of the visual pathway by analyzing the P100 component from each eye, while the mfVEP evaluates 36 individual regions of the visual field for abnormalities. Extensive signal processing, feature extraction methods, and machine learning algorithms were explored for analyzing the mfVEPs. Key metrics from patients' ffVEP results were statistically evaluated against data collected from a group of subjects with normal vision. Custom visual stimuli with simulated defects were used to validate the mfVEP results which yielded 91% accuracy of classification.
RESULTS
20 subjects, 10 controls and 10 with MS and/or ON were tested with the NeuroVEP device and a standard-of-care (SOC) VEP testing device which delivers only ffVEP stimuli. In 91% of the cases, the ffVEP results agreed between NeuroVEP and SOC device. Where available, the NeuroVEP mfVEP results were in good agreement with Humphrey Automated Perimetry visual field analysis. The lesion locations deduced from the mfVEP data were consistent with Magnetic Resonance Imaging and Optical Coherence Tomography findings.
CONCLUSION
This pilot study indicates that NeuroVEP has the potential to be a reliable, portable, and objective diagnostic device for electrophysiology and visual field analysis for neuro-visual disorders.
PubMed: 38955958
DOI: 10.1007/s10633-024-09980-z -
European Radiology Experimental Jul 2024Computed tomography (CT) is the usual modality for diagnosing stroke, but conventional CT angiography reconstructions have limitations.
BACKGROUND
Computed tomography (CT) is the usual modality for diagnosing stroke, but conventional CT angiography reconstructions have limitations.
METHODS
A phantom with tubes of known diameters and wall thickness was scanned for wall detectability, wall thickness, and contrast-to-noise ratio (CNR) on conventional and spectral black-blood (SBB) images. The clinical study included 34 stroke patients. Diagnostic certainty and conspicuity of normal/abnormal intracranial vessels using SBB were compared to conventional. Sensitivity/specificity/accuracy of SBB and conventional were compared for plaque detectability. CNR of the wall/lumen and quantitative comparison of remodeling index, plaque burden, and eccentricity were obtained for SBB imaging and high-resolution magnetic resonance imaging (hrMRI).
RESULTS
The phantom study showed improved detectability of tube walls using SBB (108/108, 100% versus conventional 81/108, 75%, p < 0.001). CNRs were 75.9 ± 62.6 (mean ± standard deviation) for wall/lumen and 22.0 ± 17.1 for wall/water using SBB and 26.4 ± 15.3 and 101.6 ± 62.5 using conventional. Clinical study demonstrated (i) improved certainty and conspicuity of the vessels using SBB versus conventional (certainty, median score 3 versus 0; conspicuity, median score 3 versus 1 (p < 0.001)), (ii) improved sensitivity/specificity/accuracy of plaque (≥ 1.0 mm) detectability (0.944/0.981/0.962 versus 0.239/0.743/0.495) (p < 0.001), (iii) higher wall/lumen CNR of SBB of (78.3 ± 50.4/79.3 ± 96.7) versus hrMRI (18.9 ± 8.4/24.1 ± 14.1) (p < 0.001), and (iv) excellent reproducibility of remodeling index, plaque burden, and eccentricity using SBB versus hrMRI (intraclass correlation coefficient 0.85-0.94).
CONCLUSIONS
SBB can enhance the detectability of intracranial plaques with an accuracy similar to that of hrMRI.
RELEVANCE STATEMENT
This new spectral black-blood technique for the detection and characterization of intracranial vessel atherosclerotic disease could be a time-saving and cost-effective diagnostic step for clinical stroke patients. It may also facilitate prevention strategies for atherosclerosis.
KEY POINTS
• Blooming artifacts can blur vessel wall morphology on conventional CT angiography. • Spectral black-blood (SBB) images are generated from material decomposition from spectral CT. • SBB images reduce blooming artifacts and noise and accurately detect small plaques.
Topics: Humans; Phantoms, Imaging; Male; Female; Middle Aged; Intracranial Arteriosclerosis; Aged; Computed Tomography Angiography; Sensitivity and Specificity; Stroke; Tomography, X-Ray Computed
PubMed: 38955951
DOI: 10.1186/s41747-024-00473-x -
Techniques in Coloproctology Jul 2024Laser hemorrhoidoplasty has demonstrated significant therapeutic effectiveness. To diminish postoperative bleeding and enhance overall outcomes, we have additionally...
BACKGROUND
Laser hemorrhoidoplasty has demonstrated significant therapeutic effectiveness. To diminish postoperative bleeding and enhance overall outcomes, we have additionally adopted suture ligating the feeding vessels. This study aimed to understand the treatment outcomes and any associated complications.
METHODS
This study comprised patients with symptomatic grade II-III hemorrhoids who underwent laser hemorrhoidoplasty with feeding vessel suture ligation and Milligan-Morgan hemorrhoidectomy between 1 September 2020, and 31 August 2022. Surgical-related details, postoperative pain, discomfort after discharge, hemorrhoid recurrence, and any complications were collected from inpatient records, outpatient follow-ups, and telephone interviews. Initially, we will analyze the distinctions between the laser group and the traditional group, followed by an investigation into complications and satisfaction within the laser surgery subgroup.
RESULTS
The study included 323 patients, with 173 undergoing laser hemorrhoidoplasty (LHP) and 150 undergoing Milligan-Morgan hemorrhoidectomy. Regarding pain assessment, the LHP group exhibited superior performance compared to traditional surgery at postoperative 4 h, before discharge, and during the first and second outpatient visits, with statistically significant differences. Additionally, the LHP group had a lower rate of urinary retention and experienced significantly less pain, with statistically significant differences.
CONCLUSIONS
Laser hemorrhoidoplasty with feeding vessels suture ligation has been shown to reduce postoperative pain and appears to be a promising minimally invasive treatment option for symptomatic grade II and III hemorrhoids.
Topics: Humans; Hemorrhoids; Ligation; Female; Retrospective Studies; Male; Hemorrhoidectomy; Middle Aged; Treatment Outcome; Adult; Pain, Postoperative; Laser Therapy; Suture Techniques; Aged; Recurrence; Postoperative Complications; Patient Satisfaction; Sutures
PubMed: 38955875
DOI: 10.1007/s10151-024-02940-4 -
Mikrochimica Acta Jul 2024CoFe@C was first prepared by calcining the precursor of CoFe-metal-organic framework-74 (CoFe-MOF-74), then an electrochemical sensor for the determination of...
CoFe@C was first prepared by calcining the precursor of CoFe-metal-organic framework-74 (CoFe-MOF-74), then an electrochemical sensor for the determination of neohesperidin dihydrochalcone (NHDC) was constructed, which was stemmed from the novel CoFe@C/Nafion composite film modified glassy carbon electrode (GCE). The CoFe@C/Nafion composite was verified by field-emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM). Electrochemical impedance spectroscopy (EIS) was used to evaluate its electrical properties as a modified material for an electrochemical sensor. Compared with CoFe-MOF-74 precursor modified electrode, CoFe@C/Nafion electrode exhibited a great synergic catalytic effect and extremely increased the oxidation peak signal of NHDC. The effects of various experimental conditions on the oxidation of NHDC were investigated and the calibration plot was tested. The results bespoken that CoFe@C/Nafion GCE has good reproducibility and anti-interference under the optimal experimental conditions. In addition, the differential pulse current response of NHDC was linear with its concentration within the range 0.08 ~ 20 µmol/L, and the linear regression coefficient was 0.9957. The detection limit was as low as 14.2 nmol/L (S/N = 3). In order to further verify the feasibility of the method, it was successfully used to determine the content of NHDC in Chinese medicine, with a satisfactory result, good in accordance with that of high performance liquid chromatography (HPLC).
Topics: Electrodes; Cobalt; Metal-Organic Frameworks; Limit of Detection; Chalcones; Electrochemical Techniques; Drugs, Chinese Herbal; Hesperidin; Fluorocarbon Polymers; Oxidation-Reduction; Carbon; Reproducibility of Results; Iron
PubMed: 38955844
DOI: 10.1007/s00604-024-06525-8 -
Clinical and Translational Science Jul 2024Ovaries play a crucial role in the regulation of numerous essential processes that occur within the intricate framework of female physiology. They are entrusted with the... (Review)
Review
Ovaries play a crucial role in the regulation of numerous essential processes that occur within the intricate framework of female physiology. They are entrusted with the responsibility of both generating a new life and orchestrating a delicate hormonal symphony. Understanding their functioning is crucial for gaining insight into the complexities of reproduction, health, and fertility. In addition, ovaries secrete hormones that are crucial for both secondary sexual characteristics and the maintenance of overall health. A three-dimensional (3D) prosthetic ovary has the potential to restore ovarian function and preserve fertility in younger females who have undergone ovariectomies or are afflicted with ovarian malfunction. Clinical studies have not yet commenced, and the production of 3D ovarian tissue for human implantation is still in the research phase. The main challenges faced while creating a 3D ovary for in vivo implantation include sustenance of ovarian follicles, achieving vascular infiltration into the host tissue, and restoring hormone circulation. The complex ovarian microenvironment that is compartmentalized and rigid makes the biomimicking of the 3D ovary challenging in terms of biomaterial selection and bioink composition. The successful restoration of these properties in animal models has led to expectations for the development of human ovaries for implantation. This review article summarizes and evaluates the optimal 3D models of ovarian structures and their safety and efficacy concerns to provide concrete suggestions for future research.
Topics: Female; Humans; Ovary; Printing, Three-Dimensional; Animals; Tissue Engineering; Fertility; Fertility Preservation; Tissue Scaffolds
PubMed: 38955776
DOI: 10.1111/cts.13863 -
The Journal of Prosthetic Dentistry Jul 2024Additive and subtractive manufacturing have become alternative technologies for fabricating occlusal devices. However, knowledge of the long-term stability of occlusal...
STATEMENT OF PROBLEM
Additive and subtractive manufacturing have become alternative technologies for fabricating occlusal devices. However, knowledge of the long-term stability of occlusal devices fabricated using these recent technologies is limited.
PURPOSE
The purpose of this in vitro study was to evaluate the cameo and intaglio surface stability and variability of additively, subtractively, and conventionally manufactured occlusal devices after 18 months of storage.
MATERIAL AND METHODS
A standard tessellation language (STL) file of a dentate maxillary typodont was used to design a master occlusal device. The STL file of this design was used to fabricate occlusal devices additively either with a digital light processing (AM-1) or a continuous liquid interface production (AM-2) printer, subtractively with 2 different 5-axis milling units (SM-1 and SM-2), and conventionally (TM-HP) (n=10). STL files of each device's cameo and intaglio surfaces were generated using a laboratory scanner after fabrication and after 18 months of storage in a moist environment. These generated files were imported into an analysis software program (Geomagic Control X) to analyze the dimensional stability of tested devices by using the root mean square method. The average deviation values defined the variability of measured changes over time. Cameo and intaglio surface deviations were analyzed using the Kruskal-Wallis and Dunn tests, while the variability of measured deviations was analyzed with 1-way analysis of variance and the Tukey HSD tests (α=.05).
RESULTS
Significant differences were observed among tested devices when the intaglio surface deviations and the cameo surface variability were considered (P<.001). SM-2 had significantly higher intaglio surface deviations than AM-1, SM-1, and AM-2 (P≤.036). Among the test groups, AM-1 had the greatest cameo surface variability (P≤.004).
CONCLUSIONS
SM-2 resulted in lower intaglio surface stability than the additive and the other subtractive manufacturing technologies, while AM-1 led to the highest cameo surface variability among the test groups.
PubMed: 38955603
DOI: 10.1016/j.prosdent.2024.06.008 -
Neurospine Jun 2024This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced...
OBJECTIVE
This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans.
METHODS
Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net's segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness.
RESULTS
The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements.
CONCLUSION
Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.
PubMed: 38955536
DOI: 10.14245/ns.2448060.030 -
Neurospine Jun 2024Cervical hybrid surgery optimizes the use of cervical disc arthroplasty (CDA) and zero-profile (ZOP) devices in anterior cervical discectomy and fusion (ACDF) but lacks...
OBJECTIVE
Cervical hybrid surgery optimizes the use of cervical disc arthroplasty (CDA) and zero-profile (ZOP) devices in anterior cervical discectomy and fusion (ACDF) but lacks uniform combination and biomechanical standards, especially in revision surgery (RS). This study aimed to investigate the biomechanical characteristics of adjacent segments of the different hybrid RS constructs in ACDF RS.
METHODS
An intact 3-dimensional finite element model generated a normal cervical spine (C2-T1). This model was modified to the primary C5-6 ACDF model. Three RS models were created to treat C4-5 adjacent segment degeneration through implanting cages plus plates (Cage-Cage), ZOP devices (ZOP-Cage), or Bryan discs (CDA-Cage). A 1.0-Nm moment was applied to the primary C5-6 ACDF model to generate total C2-T1 range of motions (ROMs). Subsequently, a displacement load was applied to all RS models to match the total C2-T1 ROMs of the primary ACDF model.
RESULTS
The ZOP-Cage model showed lower biomechanical responses including ROM, intradiscal pressure, maximum von Mises stress in discs, and facet joint force in adjacent segments compared to the Cage-Cage model. The CDA-Cage model exhibited the lowest biomechanical responses and ROM ratio at adjacent segments among all RS models, closely approached or lower than those in the primary ACDF model in most motion directions. Additionally, the maximum von Mises stress on the C3-4 and C6-7 discs increased in the Cage-Cage and ZOP-Cage models but decreased in the CDA-Cage model when compared to the primary ACDF model.
CONCLUSION
The CDA-Cage construct had the lowest biomechanical responses with minimal kinematic change of adjacent segments. ZOP-Cage is the next best choice, especially if CDA is not suitable. This study provides a biomechanical reference for clinical hybrid RS decision-making to reduce the risk of ASD recurrence.
PubMed: 38955532
DOI: 10.14245/ns.2347330.665