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Small molecules (SMs) play a pivotal role in regulating microRNAs (miRNAs). Existing prediction methods for associations between SM-miRNA have overlooked crucial aspects: the incorporation of local topological features between nodes, which represent either SMs or miRNAs, and the effective fusion of node features with topological features. This study introduces a novel approach, termed high-order topological features for SM-miRNA association prediction (HTFSMMA), which specifically addresses these limitations. Initially, an association graph is formed by integrating SM-miRNA association data, SM similarity, and miRNA similarity. Subsequently, we focus on the local information of links and propose target neighborhood graph convolutional network for extracting local topological features. Then, HTFSMMA employs graph attention networks to amalgamate these local features, thereby establishing a platform for the acquisition of high-order features through random walks. Finally, the extracted features are integrated into the multilayer perceptron to derive the association prediction scores. To demonstrate the performance of HTFSMMA, we conducted comprehensive evaluations including five-fold cross-validation, leave-one-out cross-validation (LOOCV), SM-fixed local LOOCV, and miRNA-fixed local LOOCV. The area under receiver operating characteristic curve values were 0.9958 ± 0.0024 (0.8722 ± 0.0021), 0.9986 (0.9504), 0.9974 (0.9111), and 0.9977 (0.9074), respectively. Our findings demonstrate the superior performance of HTFSMMA over existing approaches. In addition, three case studies and the DeLong test have confirmed the effectiveness of the proposed method. These results collectively underscore the significance of HTFSMMA in facilitating the inference of associations between SMs and miRNAs.
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Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis and development of targeted prevention and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analysis of disease datasets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and mechanobiology. Our 3D convolutional neural network recognized TMJ disorder patients through subject-specific morphological features in condylar, ramus, and chin. Driven by deep learning model outputs, biomechanical modeling revealed that small mandibular size and flat condylar shape were associated with increased TMJ disorder risk through increased joint force, decreased tissue nutrient availability and cell ATP production, and increased TMJ disc strain energy density. Combining explainable deep learning and multiscale biomechanical modeling addresses the "mechanism unknown" limitation undermining translational confidence in clinical applications of deep learning and increases methodological accessibility for smaller clinical datasets by providing the crucial biomechanical context.
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Hypermobile Ehlers-Danlos syndrome (hEDS) is a common heritable connective tissue disorder that lacks a known genetic etiology. To identify genetic contributions to hEDS, whole exome sequencing was performed on families and a cohort of sporadic hEDS patients. A missense variant in Kallikrein-15 (KLK15 p. Gly226Asp), segregated with disease in two families and genetic burden analyses of 197 sporadic hEDS patients revealed enrichment of variants within the Kallikrein gene family. To validate pathogenicity, the variant identified in familial studies was used to generate knock-in mice. Consistent with our clinical cohort, Klk15 G224D/+ mice displayed structural and functional connective tissue defects within multiple organ systems. These findings support Kallikrein gene variants in the pathogenesis of hEDS and represent an important step towards earlier diagnosis and better clinical outcomes.
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Cartilage endplates (CEPs) act as protective mechanical barriers for intervertebral discs (IVDs), yet their heterogeneous structure-function relationships are poorly understood. This study addressed this gap by characterizing and correlating the regional biphasic mechanical properties and biochemical composition of human lumbar CEPs. Samples from central, lateral, anterior, and posterior portions of the disc (n = 8/region) were mechanically tested under confined compression to quantify swelling pressure, equilibrium aggregate modulus, and hydraulic permeability. These properties were correlated with CEP porosity and glycosaminoglycan (s-GAG) content, which were obtained by biochemical assays of the same specimens. Both swelling pressure (142.79 ± 85.89 kPa) and aggregate modulus (1864.10 ± 1240.99 kPa) were found to be regionally dependent (p = 0.0001 and p = 0.0067, respectively) in the CEP and trended lowest in the central location. No significant regional dependence was observed for CEP permeability (1.35 ± 0.97 * 10-16 m4/Ns). Porosity measurements correlated significantly with swelling pressure (r = -0.40, p = 0.0227), aggregate modulus (r = -0.49, p = 0.0046), and permeability (r = 0.36, p = 0.0421), and appeared to be the primary indicator of CEP biphasic mechanical properties. Second harmonic generation microscopy also revealed regional patterns of collagen fiber anchoring, with fibers inserting the CEP perpendicularly in the central region and at off-axial directions in peripheral regions. These results suggest that CEP tissue has regionally dependent mechanical properties which are likely due to the regional variation in porosity and matrix structure. This work advances our understanding of healthy baseline endplate biomechanics and lays a groundwork for further understanding the role of CEPs in IVD degeneration.
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Disco Intervertebral , Vértebras Lumbares , Humanos , Vértebras Lumbares/fisiología , Disco Intervertebral/fisiología , Persona de Mediana Edad , Masculino , Femenino , Porosidad , Adulto , Anciano , Glicosaminoglicanos/metabolismo , Fenómenos Biomecánicos , Cartílago/fisiología , Estrés MecánicoRESUMEN
[This retracts the article DOI: 10.3892/ol.2018.8695.].
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A broadband and narrowband switchable terahertz (THz) absorber based on a bulk Dirac semimetal (BDS) and strontium titanate (STO) is proposed. Narrowband and broadband absorption can be switched by adjusting the Fermi level of the BDS. When the Fermi level of the BDS is 100 meV, the device is an absorber with three narrowband absorption peaks. The frequencies are 0.44, 0.86, and 1.96 THz, respectively, when the temperature of STO is 250 K. By adjusting the temperature of STO from 250 to 500 K, the blue shifts of the frequencies are approximately 0.14, 0.32, and 0.60 THz, respectively. The sensitivities of the three absorption peaks are 0.56, 1.27, and 2.38 GHz/K, respectively. When the Fermi level of the BDS is adjusted from 100 to 30 meV, the device can be switched to a broadband absorber with a bandwidth of 0.70 THz. By adjusting the temperature of STO from 250 to 500 K, the central frequency shifts from 1.40 to 1.79 THz, and the bandwidth broadens from 0.70 to 0.96 THz. The sensitivity of the central frequency is 1.57 GHz/K. The absorber also has a wide range of potential applications in multifunctional tunable devices, such as temperature sensors, stealth equipment, and filters.
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OBJECTIVE: To analyze and compare the effects of a traditional laboratory-fabricated Hyrax expander (T-Hyrax) and two different 3D-printed Hyrax expander models relative to tension points, force distribution, and areas of concentration in the craniofacial complex during maxillary expansion using finite element analysis. MATERIALS AND METHODS: Three maxillary expanders with similar designs, but various alloys were modeled: a T-Hyrax, a fully printed Hyrax (F-Hyrax), and a hybrid printed Hyrax (H-Hyrax). The stress distributions and magnitude of displacements were assessed with a 5 mm expansion in a symmetrical finite element model. The areas of interest included the teeth, alveolar processes, midpalatal suture, nasal complex, circummaxillary sutures (CS), and the expanders themselves. RESULTS: The highest stress value (29.2 MPa) was found at the midpalatal suture of the F-Hyrax, while the lowest stress (0.90 MPa) was found at the temporozygomatic suture in the T-Hyrax. On average, the F-Hyrax increased stress at the CS by 24.76% compared with the T-Hyrax and H-Hyrax. The largest displacements were found at the upper incisor (U1) and anterior nasal spine (ANS). The findings indicated an average increase of 12.80% displacement at the CS using the F-Hyrax compared to the T-Hyrax. CONCLUSION: The F-Hyrax exerts more stress and displacement on the maxilla than both the T-Hyrax and H-Hyrax, where the weak link appears to be the solder joint.
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Damanes , Maxilar , Humanos , Animales , Análisis de Elementos Finitos , Incisivo , Impresión TridimensionalRESUMEN
Immunotherapy has revolutionized cancer treatment by boosting the immune system and preventing disease escape mechanisms. Despite its potential, challenges like limited response rates and adverse immune effects impede its widespread clinical adoption. Ultrasound (US), known for its safety and effectiveness in tumor diagnosis and therapy, has been shown to significantly enhance immunotherapy when used with nanosystems. High-intensity focused ultrasound (HIFU) can obliterate tumor cells and elicit immune reactions through the creation of immunogenic debris. Low-intensity focused ultrasound (LIFU) bolsters tumor immunosuppression and mitigates metastasis risk by concentrating dendritic cells. Ultrasonic cavitation (UC) produces microbubbles that can transport immune enhancers directly, thus strengthening the immune response and therapeutic impact. Sonodynamic therapy (SDT) merges nanotechnology with immunotherapy, using specialized sonosensitizers to kill cancer cells and stimulate immune responses, increasing treatment success. This review discusses the integration of ultrasound-responsive nanosystems in tumor immunotherapy, exploring future opportunities and current hurdles.
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Neoplasias , Terapia por Ultrasonido , Humanos , Neoplasias/patología , Ultrasonografía , Inmunoterapia , Línea Celular Tumoral , Especies Reactivas de OxígenoRESUMEN
Transforming polyolefin waste into liquid alkanes through tandem cracking-alkylation reactions catalyzed by Lewis-acid chlorides offers an efficient route for single-step plastic upcycling. Lewis acids in dichloromethane establish a polar environment that stabilizes carbenium ion intermediates and catalyzes hydride transfer, enabling breaking of polyethylene C-C bonds and forming C-C bonds in alkylation. Here, we show that efficient and selective deconstruction of low-density polyethylene (LDPE) to liquid alkanes is achieved with anhydrous aluminum chloride (AlCl3) and gallium chloride (GaCl3). Already at 60 °C, complete LDPE conversion was achieved, while maintaining the selectivity for gasoline-range liquid alkanes over 70 %. AlCl3 showed an exceptional conversion rate of 5000 g L D P E m o l c a t - 1 h - 1 ${{{\rm g}}_{{\rm L}{\rm D}{\rm P}{\rm E}}{{\rm \ }{\rm m}{\rm o}{\rm l}}_{{\rm c}{\rm a}{\rm t}}^{-1}{{\rm \ }{\rm h}}^{-1}}$ , surpassing other Lewis acid catalysts by two orders of magnitude. Through kinetic and mechanistic studies, we show that the rates of LDPE conversion do not correlate directly with the intrinsic strength of the Lewis acids or steric constraints that may limit the polymer to access the Lewis acid sites. Instead, the rates for the tandem processes of cracking and alkylation are primarily governed by the rates of initiation of carbenium ions and the subsequent intermolecular hydride transfer. Both jointly control the relative rates of cracking and alkylation, thereby determining the overall conversion and selectivity.
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In order to improve the accuracy of transformer fault diagnosis and improve the influence of unbalanced samples on the low accuracy of model identification caused by insufficient model training, this paper proposes a transformer fault diagnosis method based on SMOTE and NGO-GBDT. Firstly, the Synthetic Minority Over-sampling Technique (SMOTE) was used to expand the minority samples. Secondly, the non-coding ratio method was used to construct multi-dimensional feature parameters, and the Light Gradient Boosting Machine (LightGBM) feature optimization strategy was introduced to screen the optimal feature subset. Finally, Northern Goshawk Optimization (NGO) algorithm was used to optimize the parameters of Gradient Boosting Decision Tree (GBDT), and then the transformer fault diagnosis was realized. The results show that the proposed method can reduce the misjudgment of minority samples. Compared with other integrated models, the proposed method has high fault identification accuracy, low misjudgment rate and stable performance.
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The shortage of suitable donor meniscus grafts from the knee and temporomandibular joint (TMJ) impedes treatments for millions of patients. Vitrification offers a promising solution by transitioning these tissues into a vitreous state at cryogenic temperatures, protecting them from ice crystal damage using high concentrations of cryoprotectant agents (CPAs). However, vitrification's success is hindered for larger tissues (>3 mL) due to challenges in CPA penetration. Dense avascular meniscus tissues require extended CPA exposure for adequate penetration; however, prolonged exposure becomes cytotoxic. Balancing penetration and reducing cell toxicity is required. To overcome this hurdle, a simulation-based optimization approach is developed by combining computational modeling with microcomputed tomography (µCT) imaging to predict 3D CPA distributions within tissues over time accurately. This approach minimizes CPA exposure time, resulting in 85% viability in 4-mL meniscal specimens, 70% in 10-mL whole knee menisci, and 85% in 15-mL whole TMJ menisci (i.e., TMJ disc) post-vitrification, outperforming slow-freezing methods (20%-40%), in a pig model. The extracellular matrix (ECM) structure and biomechanical strength of vitreous tissues remain largely intact. Vitreous meniscus grafts demonstrate clinical-level viability (≥70%), closely resembling the material properties of native tissues, with long-term availability for transplantation. The enhanced vitrification technology opens new possibilities for other avascular grafts.
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More and more studies have shown that microRNAs (miRNAs) play an indispensable role in the study of complex diseases in humans. Traditional biological experiments to detect miRNA-disease associations are expensive and time-consuming. Therefore, it is necessary to propose efficient and meaningful computational models to predict miRNA-disease associations. In this study, we aim to propose a miRNA-disease association prediction model based on sparse learning and multilayer random walks (SLMRWMDA). The miRNA-disease association matrix is decomposed and reconstructed by the sparse learning method to obtain richer association information, and at the same time, the initial probability matrix for the random walk with restart algorithm is obtained. The disease similarity network, miRNA similarity network, and miRNA-disease association network are used to construct heterogeneous networks, and the stable probability is obtained based on the topological structure features of diseases and miRNAs through a multilayer random walk algorithm to predict miRNA-disease potential association. The experimental results show that the prediction accuracy of this model is significantly improved compared with the previous related models. We evaluated the model using global leave-one-out cross-validation (global LOOCV) and fivefold cross-validation (5-fold CV). The area under the curve (AUC) value for the LOOCV is 0.9368. The mean AUC value for 5-fold CV is 0.9335 and the variance is 0.0004. In the case study, the results show that SLMRWMDA is effective in inferring the potential association of miRNA-disease.
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MicroARNs , Humanos , MicroARNs/genética , Algoritmos , Área Bajo la Curva , Biología Computacional/métodos , Predisposición Genética a la EnfermedadRESUMEN
Mastication is a vital human function and uses an intricate coordination of muscle activation to break down food. Collection of detailed muscle activation patterns is complex and commonly only masseter and anterior temporalis muscle activation are recorded. Chewing is the orofacial task with the highest muscle forces, potentially leading to high temporomandibular joint (TMJ) loading. Increased TMJ loading is often associated with the onset and progression of temporomandibular disorders (TMD). Hence, studying TMJ mechanical stress during mastication is a central task. Current TMD self-management guidelines suggest eating small and soft pieces of food, but patient safety concerns inhibit in vivo investigations of TMJ biomechanics and currently no in silico model of muscle recruitment and TMJ biomechanics during chewing exists. For this purpose, we have developed a state-of-the-art in silico model, combining rigid body bones, finite element TMJ discs and line actuator muscles. To solve the problems regarding muscle activation measurement, we used a forward dynamics tracking approach, optimizing muscle activations driven by mandibular motion. We include a total of 256 different combinations of food bolus size, stiffness and position in our study and report kinematics, muscle activation patterns and TMJ disc von Mises stress. Computed mandibular kinematics agree well with previous measurements. The computed muscle activation pattern stayed stable over all simulations, with changes to the magnitude relative to stiffness and size of the bolus. Our biomedical simulation results agree with the clinical guidelines regarding bolus modifications as smaller and softer food boluses lead to less TMJ loading. The computed mechanical stress results help to strengthen the confidence in TMD self-management recommendations of eating soft and small pieces of food to reduce TMJ pain.
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Masticación , Trastornos de la Articulación Temporomandibular , Humanos , Masticación/fisiología , Articulación Temporomandibular/fisiología , Disco de la Articulación Temporomandibular/fisiología , MúsculosRESUMEN
Wearable heaters are essential for people living in cold regions, but creating heaters that are low-cost, lightweight, and high air permeability poses challenges. In this study, we developed a wearable heater using carbon nanotube/water polyurethane (CNT/WPU) nanocomposite fibers that achieve high extension rate and conductivity. We produced low-cost and mass-produced fibers using the wet spinning. With heat treatment, we increased the elongation rate of the fibers to 1893.8% and decreased the resistivity to 0.07 Ω*m. then wove the fibers into a heating fabric using warp knitting, that resistance is 493 Ω. Achieved a uniform temperature of 58 °C at voltage of 36 V, with a thermal stability fluctuation of -5.0 °C to +6.3 °C when bent from 0° to 360°. Our results show that wearable heaters have excellent flexibility and stretchability, due to nanocomposite fibers and special braided structure, which offer a novel idea for wearable heaters.
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OBJECTIVE: To analyze and compare the clinical and laboratory characteristics of macrophage activation syndrome (MAS) in patients with systemic lupus erythematosus (SLE) and adult-onset Still's disease (AOSD), and to evaluate the applicability of the 2016 European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organization classification criteria for MAS complicating systemic juvenile idiopathic arthritis (sJIA) in different auto-immune diseases contexts and to propose new diagnostic predictive indicators. METHODS: A retrospective analysis was conducted on the clinical and laboratory data of 24 SLE patients with MAS (SLE-MAS) and 24 AOSD patients with MAS (AOSD-MAS) who were hospitalized at Peking University People's Hospital between 2000 and 2018. Age- and sex-matched SLE (50 patients) and AOSD (50 patients) diagnosed in the same period without MAS episodes were selected as controls. The cutoff values for laboratory indicators predicting SLE-MAS and AOSD-MAS were determined using receiver operating characteristic (ROC) curves. Furthermore, the laboratory diagnostic predictive values for AOSD-MAS were used to improve the classification criteria for systemic juvenile idiopathic arthritis-associated MAS (sJIA-MAS), and the applicability of the revised criteria for AOSD-MAS was explored. RESULTS: Approximately 60% of SLE-MAS and 40% of AOSD-MAS occurred within three months after the diagnosis of the underlying diseases. The most frequent clinical feature was fever. In addition to the indicators mentioned in the diagnosis criteria for hemophagocytic syndrome revised by the International Society for Stem Cell Research, the MAS patients also exhibited significantly elevated levels of aspartate aminotransferase and lactate dehydrogenase, along with a significant decrease in albumin. Hemophagocytosis was observed in only about half of the MAS patients. ROC curve analysis demonstrated that the optimal discriminative values for diagnosing MAS was achieved when SLE patients had ferritin level≥1 010 µg/L and lactate dehydroge-nase levels≥359 U/L, while AOSD patients had fibrinogen levels≤225.5 mg/dL and triglyceride levels≥2.0 mmol/L. Applying the 2016 sJIA-MAS classification criteria to AOSD-MAS yielded a diagnostic sensitivity of 100% and specificity of 62%. By replacing the less specific markers ferritin and fibrinogen in the 2016 sJIA-MAS classification criteria with new cutoff values, the revised criteria for classifying AOSD-MAS had a notable increased specificity of 86%. CONCLUSION: Secondary MAS commonly occurs in the early stages following the diagnosis of SLE and AOSD. There are notable variations in laboratory indicators among different underlying diseases, which may lead to misdiagnosis or missed diagnosis when using uniform classification criteria for MAS. The 2016 sJIA-MAS classification criteria exhibit high sensitivity but low specificity in diagnosing AOSD-MAS. Modification of the criteria can enhance its specificity.
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Artritis Juvenil , Lupus Eritematoso Sistémico , Síndrome de Activación Macrofágica , Enfermedad de Still del Adulto , Adulto , Humanos , Niño , Síndrome de Activación Macrofágica/etiología , Síndrome de Activación Macrofágica/complicaciones , Artritis Juvenil/complicaciones , Artritis Juvenil/diagnóstico , Enfermedad de Still del Adulto/complicaciones , Enfermedad de Still del Adulto/diagnóstico , Estudios Retrospectivos , Lupus Eritematoso Sistémico/complicaciones , Lupus Eritematoso Sistémico/diagnóstico , Fibrinógeno , FerritinasRESUMEN
Objective: Myocardial infarction (MI) is a common and serious cardiovascular disease with increasing incidence and mortality rates, making it a major global public health issue. Molecular biology research has shown that the cleavage products miR-208 and miR-92a are microRNAs (miRNAs) associated with myocardial injury. Therefore, this study aims to establish a predictive model and explore the application value of the combined detection of miR-208 and miR-92a in the early diagnosis of MI in microRNA. Methods: Plasma samples were collected from 231 volunteers divided into 30 healthy and 201 diseased subjects From January 1st, 2021 to December 30th, 2021. Plasma RNA was extracted using a TRIZOL kit, and levels of miR-208 and miR-92a were determined using a real-time polymerase chain reaction (PCR) assay. Subsequently, the logistic regression model, decision tree model analysis, and receiver operating characteristic (ROC) curve were used to evaluate whether miR-208 combined with miR-92a could be used as a biomarker for MI early diagnosis. Results: In this study, the ROC curve evaluation of the logistic regression model and pruned decision tree model found that age, miR-208, and miR-92a had high early diagnostic accuracy for MI, and the area under the curve (AUC) reached 0.928, showing good predictive value. It was also found that the AUC, optimal threshold, sensitivity, and specificity of age, miR-208, and miR-92a were higher than those of age and miR-208. This indicates that the combination of age, miR-208, and miR-92a has more value in the early diagnosis of MI. Conclusion: The combined diagnosis of miR-208 and miR-92a is helpful for the early diagnosis of myocardial infarction, which might serve as a new marker of MI benefiting from its early diagnosis.
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Objective: Chondrocyte viability (CV) can be measured with the label-free method using second harmonic generation (SHG) and two-photon excitation autofluorescence (TPAF) imaging. To automate the image processing for the label-free CV measurement, we previously demonstrated a two-step deep-learning method: Step 1 used a U-Net to segment the lacuna area on SHG images; Step 2 used dual CNN networks to count live cells and the total number of cells in extracted cell clusters from TPAF images. This study aims to develop one-step deep learning methods to improve the efficiency of CV measurement. Method: TPAF/SHG images were acquired simultaneously on cartilage samples from rats and pigs using two-photon microscopes and were merged to form RGB color images with red, green, and blue channels assigned to emission bands of oxidized flavoproteins, reduced forms of nicotinamide adenine dinucleotide, and SHG signals, respectively. Based on the Mask R-CNN, we designed a deep learning network and its denoising version using Wiener deconvolution for CV measurement. Results: Using training and test datasets from rat and porcine cartilage, we have demonstrated that Mask R-CNN-based networks can segment and classify individual cells with a single-step processing flow. The absolute error (difference between the measured and the ground-truth CV) of the CV measurement using the Mask R-CNN with or without Wiener deconvolution denoising reaches 0.01 or 0.08, respectively; the error of the previous CV networks is 0.18, significantly larger than that of the Mask R-CNN methods. Conclusions: Mask R-CNN-based deep-learning networks improve efficiency and accuracy of the label-free CV measurement.
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OBJECTIVE: To investigate the clinical efficacy of electrophysiological appropriateness technique (EAT) therapy based on the traditional Chinese medicine (TCM) meridian theory in managing postoperative pain after urethral reconstruction surgery. METHODS: Using the real-world study approach, we enrolled 61 male patients undergoing urethral reconstruction and divided them into a control group (n = 30) and an observation group (n = 31), the former receiving patient-controlled intravenous analgesia (PCIA), while the latter PCIA plus EAT at 4 pairs of acupoints (Hegu, Neiguan, Zusanli and Sanyinjiao bilaterally) and the Ashi point, with 100 mg tramadol hydrochloride given orally as remedial analgesia in both groups in case of postoperative Visual Analogue Scale (VAS) score ≥4. We compared the VAS scores at 4, 12, 24 and 48 hours postoperatively, the dose of cumulative fentanyl used at 48 hours, the number of cases needing remedial analgesia, the time to first flatus and the incidence of adverse reactions between the two groups of patients. RESULTS: The VAS scores were markedly lower in the observation than in the control group at 4, 12, 24 and 48 hours after surgery (P < 0.05), with statistically significant differences in time-dependent effect and interactive effect (P < 0.05). Significant reduction was observed in the doses of cumulative fentanyl (P < 0.05) and remedial tramadol analgesia (P < 0.05), time to first flatus (P < 0.05), and incidence of adverse reactions (P < 0.05) in the observation group in comparison with the controls. CONCLUSION: Electrophysiological therapy based on the TCM meridian theory can safely and effectively alleviate postoperative pain after urethral reconstruction, reduce opioid consumption, and decrease adverse events.
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Meridianos , Tramadol , Humanos , Masculino , Medicina Tradicional China , Flatulencia , Dolor Postoperatorio/tratamiento farmacológico , Analgesia Controlada por el Paciente/métodos , Analgésicos Opioides/uso terapéutico , Tramadol/uso terapéutico , Fentanilo/uso terapéuticoRESUMEN
Pelvic organ prolapse (POP) is one of the common diseases in middle-aged and elderly women, caused by weakened pelvic floor muscle ligament tissue support. Pelvic floor reconstruction with mesh implantation has been proven to be an effective treatment for POP. However, traditional non-degradable and inflexible pelvic floor implantation meshes have been associated with pain, vaginal infections, and the need for additional surgeries. In this study, novel meshes with pre-designed structures were fabricated with solution-based electrohydrodynamic printing (EHDP) technology, using a series of polycaprolactone/silk fibroin composites as bioinks. The PCL/SF mesh mechanical performances were particularly enhanced with the addition of silk II, leading it to obtain higher adaptability with soft tissue repair. The mesh containing SF showed more robust degradation performance in the in vitro degradation assay. Furthermore, biocompatibility tests conducted on mouse embryonic fibroblasts (NIH/3T3) revealed enhanced cell affinity. Finally, the biocompatibility and tissue repair properties of PCL/SF mesh were verified through the implantation of meshes in the muscle defect site of mice. The results demonstrated that the 3D printed PCL/SF mesh prepared by EHDP exhibits superior mechanical properties, biocompatibility, biodegradability, as well as ligament and muscle fiber repair ability. The novel implantable meshes are promising for curing POP.
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Osteoarthritis is a degenerative joint disease that causes pain, degradation, and dysfunction. Excessive canonical Wnt signaling in osteoarthritis contributes to chondrocyte phenotypic instability and loss of cartilage homeostasis; however, the regulatory niche is unknown. Using the temporomandibular joint as a model in multiple species, we identify Lgr5-expressing secretory cells as forming a Wnt inhibitory niche that instruct Wnt-inactive chondroprogenitors to form the nascent synovial joint and regulate chondrocyte lineage and identity. Lgr5 ablation or suppression during joint development, aging, or osteoarthritis results in depletion of Wnt-inactive chondroprogenitors and a surge of Wnt-activated, phenotypically unstable chondrocytes with osteoblast-like properties. We recapitulate the cartilage niche and create StemJEL, an injectable hydrogel therapy combining hyaluronic acid and sclerostin. Local delivery of StemJEL to post-traumatic osteoarthritic jaw and knee joints in rabbit, rat, and mini-pig models restores cartilage homeostasis, chondrocyte identity, and joint function. We provide proof of principal that StemJEL preserves the chondrocyte niche and alleviates osteoarthritis.