Intra-articular sustained-release of pirfenidone as a disease-modifying treatment for early osteoarthritis.

Osteoarthritis (OA) is a major clinical challenge, and effective disease-modifying drugs for OA are still lacking due to the complicated pathology and scattered treatment targets. Effective early treatments are urgently needed to prevent OA progression. The excessive amount of transforming growth factor ß (TGFß) is one of the major causes of synovial fibrosis and subchondral bone sclerosis, and such pathogenic changes in early OA precede cartilage damage. Herein we report a novel strategy of intra-articular sustained-release of pirfenidone (PFD), a clinically-approved TGFß inhibitor, to achieve disease-modifying effects on early OA joints. We found that PFD effectively restored the mineralization in the presence of excessive amount of TGFß1 (as those levels found in patients' synovial fluid). A monthly injection strategy was then designed of using poly lactic-co-glycolic acid (PLGA) microparticles and hyaluronic acid (HA) solution to enable a sustained release of PFD (the "PLGA-PFD + HA" strategy). This strategy effectively regulated OA progression in destabilization of the medial meniscus (DMM)- induced OA mice model, including preventing subchondral bone loss in early OA and subchondral bone sclerosis in late OA, and reduced synovitis and pain with cartilage preservation effects. This finding suggests the promising clinical application of PFD as a novel disease-modifying OA drug.

Effects of resistance training with elastic bands on bone mineral density, body composition, and osteosarcopenic obesity in elderly women: A meta-analysis.

Background: Elastic band exercises can improve bone density, muscle quality, and body fat in elderly patients with Sarcopenic Obesity Syndrome (SOS), a common diagnosis. Encouraging this exercise can bring significant benefits. Methods: We conducted a comprehensive search until April 1, 2023, covering UpToDate, PubMed, and Web of Science databases. The analysis focused on osteosarcopenic obesity and resistance training, involving four randomized controlled trials with 108 participants. After collecting key information, the methodological quality was assessed using the PEDro scale. Outcome quality was graded using the GRADE technique, and bias risk was evaluated using the Cochrane Bias Risk tool. Statistical analysis was performed using Review Manager 5.4. Results: After a 12-week elastic band resistance training regimen, the meta-analysis revealed significant improvement. The study focused on age-related osteoporosis and obesity in older women, evaluating parameters such as bone mineral density (BMD) (P < 0.001, I2 = 98 %, CI: 0.39-0.71), decreased body fat percentage (BFP) (CI: -262.55-260.11, P < 0.001, I2 = 100 %), and skeletal muscle mass index (SMI) (P < 0.001, I2 = 98 %, CI: 0.31-0.71). T-score (P < 0.001, I2 = 97 %, CI: -2.85-1.27), Time to Chair Rise (TCR) (P < 0.001, I2 = 100 %, CI: -24.28-23.44), and Gait Speed (GS) (P < 0.001, I2 = 100 %, CI: 9.84-9.88) were also evaluated. Conclusion: Following a 12-week elastic band resistance exercise regimen, older women showed notable improvements, particularly those with age-related osteoporosis and obesity.

Comparison of double chevron-cut and biplanar distal femoral osteotomy techniques: A biomechanical study.

OBJECTIVE: This study aimed to compare the stability and mechanical properties of the double chevron-cut (DCC) and biplanar (BP) distal femoral osteotomy (DFO) techniques, along with analyzing their respective contact surface areas. METHODS: Biomechanical testing was performed using sawbone and 3D modeling techniques to assess axial and torsional stability, torsional stiffness, and maximum torque of both osteotomy configurations. Additionally, 3D models of the sawbone femur were created to calculate and compare the contact surface area of the DCC, BP, and conventional single-plane DFO techniques. RESULTS: Axial stiffness and maximum strength did not significantly differ between the two osteotomy techniques. However, in terms of torsional properties, the DCC technique exhibited superior torsional stiffness compared to the BP group (27 ± 7.7 Nm/° vs. 4.5 ± 1.5 Nm/°, p = 0.008). Although the difference in maximum torque did not reach statistical significance (63 ± 10.6 vs. 56 ± 12.1, p = 0.87), it is noteworthy that the DCC group sawbone model exhibited fracture in the shaft region instead of at the osteotomy site. Therefore, the actual maximum torque of the DCC construct may not be accurately reflected by the numerical values obtained in this study. The contact surface area analysis revealed that the BP configuration had the largest contact surface area, 111% larger than that of the single-plane configuration. but 60% of it relied on the less reliable axial cut. Conversely, the DCC osteotomy offered a 31% larger contact surface area than the single-plane configuration, with both surfaces being weight-bearing. CONCLUSION: The DCC osteotomy exhibited superior mechanical stability, showing improved rotational stiffness and maximum torque when compared to the BP osteotomy. Although the BP osteotomy resulted in a larger contact surface area than the DCC osteotomy, both were larger than the conventional single-plane configuration. In clinical practice, both the DCC and BP techniques should be evaluated based on patient-specific characteristics and surgical goals.

Precision Identification of Locally Advanced Rectal Cancer in Denoised CT Scans Using EfficientNet and Voting System Algorithms.

BACKGROUND AND OBJECTIVE: Local advanced rectal cancer (LARC) poses significant treatment challenges due to its location and high recurrence rates. Accurate early detection is vital for treatment planning. With magnetic resonance imaging (MRI) being resource-intensive, this study explores using artificial intelligence (AI) to interpret computed tomography (CT) scans as an alternative, providing a quicker, more accessible diagnostic tool for LARC. METHODS: In this retrospective study, CT images of 1070 T3-4 rectal cancer patients from 2010 to 2022 were analyzed. AI models, trained on 739 cases, were validated using two test sets of 134 and 197 cases. By utilizing techniques such as nonlocal mean filtering, dynamic histogram equalization, and the EfficientNetB0 algorithm, we identified images featuring characteristics of a positive circumferential resection margin (CRM) for the diagnosis of locally advanced rectal cancer (LARC). Importantly, this study employs an innovative approach by using both hard and soft voting systems in the second stage to ascertain the LARC status of cases, thus emphasizing the novelty of the soft voting system for improved case identification accuracy. The local recurrence rates and overall survival of the cases predicted by our model were assessed to underscore its clinical value. RESULTS: The AI model exhibited high accuracy in identifying CRM-positive images, achieving an area under the curve (AUC) of 0.89 in the first test set and 0.86 in the second. In a patient-based analysis, the model reached AUCs of 0.84 and 0.79 using a hard voting system. Employing a soft voting system, the model attained AUCs of 0.93 and 0.88, respectively. Notably, AI-identified LARC cases exhibited a significantly higher five-year local recurrence rate and displayed a trend towards increased mortality across various thresholds. Furthermore, the model's capability to predict adverse clinical outcomes was superior to those of traditional assessments. CONCLUSION: AI can precisely identify CRM-positive LARC cases from CT images, signaling an increased local recurrence and mortality rate. Our study presents a swifter and more reliable method for detecting LARC compared to traditional CT or MRI techniques.

Modulation of experimental acute lung injury by exosomal miR-7704 from mesenchymal stromal cells acts through M2 macrophage polarization.

Acute lung injury (ALI) is a life-threatening condition with limited treatment options. The pathogenesis of ALI involves macrophage-mediated disruption and subsequent repair of the alveolar barriers, which ultimately results in lung damage and regeneration, highlighting the pivotal role of macrophage polarization in ALI. Although exosomes derived from mesenchymal stromal cells have been established as influential modulators of macrophage polarization, the specific role of exosomal microRNAs (miRNAs) remains underexplored. This study aimed to elucidate the role of specific exosomal miRNAs in driving macrophage polarization, thereby providing a reference for developing novel therapeutic interventions for ALI. We found that miR-7704 is the most abundant and efficacious miRNA for promoting the switch to the M2 phenotype in macrophages. Mechanistically, we determined that miR-7704 stimulates M2 polarization by inhibiting the MyD88/STAT1 signaling pathway. Notably, intra-tracheal delivery of miR-7704 alone in a lipopolysaccharide-induced murine ALI model significantly drove M2 polarization in lung macrophages and remarkably restored pulmonary function, thus increasing survival. Our findings highlight miR-7704 as a valuable tool for treating ALI by driving the beneficial M2 polarization of macrophages. Our findings pave the way for deeper exploration into the therapeutic potential of exosomal miRNAs in inflammatory lung diseases.

Utilizing multimodal approach to identify candidate pathways and biomarkers and predicting frailty syndrome in individuals from UK Biobank.

Frailty, a prevalent clinical syndrome in aging adults, is characterized by poor health outcomes, represented via a standardized frailty-phenotype (FP), and Frailty Index (FI). While the relevance of the syndrome is gaining awareness, much remains unclear about its underlying biology. Further elucidation of the genetic determinants and possible underlying mechanisms may help improve patients' outcomes allowing healthy aging.Genotype, clinical and demographic data of subjects (aged 60-73 years) from UK Biobank were utilized. FP was defined on Fried's criteria. FI was calculated using electronic-health-records. Genome-wide-association-studies (GWAS) were conducted and polygenic-risk-scores (PRS) were calculated for both FP and FI. Functional analysis provided interpretations of underlying biology. Finally, machine-learning (ML) models were trained using clinical, demographic and PRS towards identifying frail from non-frail individuals.Thirty-one loci were significantly associated with FI accounting for 12% heritability. Seventeen of those were known associations for body-mass-index, coronary diseases, cholesterol-levels, and longevity, while the rest were novel. Significant genes CDKN2B and APOE, previously implicated in aging, were reported to be enriched in lipoprotein-particle-remodeling. Linkage-disequilibrium-regression identified specific regulation in limbic-system, associated with long-term memory and cognitive-function. XGboost was established as the best performing ML model with area-under-curve as 85%, sensitivity and specificity as 0.75 and 0.8, respectively.This study provides novel insights into increased vulnerability and risk stratification of frailty syndrome via a multi-modal approach. The findings suggest frailty as a highly polygenic-trait, enriched in cholesterol-remodeling and metabolism and to be genetically associated with cognitive abilities. ML models utilizing FP and FI + PRS were established that identified frailty-syndrome patients with high accuracy.

Task-adaptive physical reservoir computing.

Reservoir computing is a neuromorphic architecture that may offer viable solutions to the growing energy costs of machine learning. In software-based machine learning, computing performance can be readily reconfigured to suit different computational tasks by tuning hyperparameters. This critical functionality is missing in 'physical' reservoir computing schemes that exploit nonlinear and history-dependent responses of physical systems for data processing. Here we overcome this issue with a 'task-adaptive' approach to physical reservoir computing. By leveraging a thermodynamical phase space to reconfigure key reservoir properties, we optimize computational performance across a diverse task set. We use the spin-wave spectra of the chiral magnet Cu2OSeO3 that hosts skyrmion, conical and helical magnetic phases, providing on-demand access to different computational reservoir responses. The task-adaptive approach is applicable to a wide variety of physical systems, which we show in other chiral magnets via above (and near) room-temperature demonstrations in Co8.5Zn8.5Mn3 (and FeGe).

Single-cell transcriptome analysis reveals the effectiveness of cytokine priming irrespective of heterogeneity in mesenchymal stromal cells.

BACKGROUND AIMS: Mesenchymal stromal cells (MSCs) are recognized as a potential cell-based therapy for regenerative medicine. Short-term inflammatory cytokine pre-stimulation (cytokine priming) is a promising approach to enhance regenerative efficacy of MSCs. However, it is unclear whether their intrinsic heterogenic nature causes an unequal response to cytokine priming, which might blunt the accessibility of clinical applications. METHODS: In this study, by analyzing the single-cell transcriptomic landscape of human bone marrow MSCs from a naïve to cytokine-primed state, we elucidated the potential mechanism of superior therapeutic potential in cytokine-primed MSCs. RESULTS: We found that cytokine-primed MSCs had a distinct transcriptome landscape. Although substantial heterogeneity was identified within the population in both naïve and primed states, cytokine priming enhanced the several characteristics of MSCs associated with therapeutic efficacy irrespective of heterogeneity. After cytokine-priming, all sub-clusters of MSCs possessed high levels of immunoregulatory molecules, trophic factors, stemness-related genes, anti-apoptosis markers and low levels of multi-lineage and senescence signatures, which are critical for their therapeutic potency. CONCLUSIONS: In conclusion, our results provide new insights into MSC heterogeneity under cytokine stimulation and suggest that cytokine priming reprogrammed MSCs independent of heterogeneity.

Mesenchymal stem cells alleviate dexamethasone-induced muscle atrophy in mice and the involvement of ERK1/2 signalling pathway.

BACKGROUND: High dosage of dexamethasone (Dex) is an effective treatment for multiple diseases; however, it is often associated with severe side effects including muscle atrophy, resulting in higher risk of falls and poorer life quality of patients. Cell therapy with mesenchymal stem cells (MSCs) holds promise for regenerative medicine. In this study, we aimed to investigate the therapeutic efficacy of systemic administration of adipose-derived mesenchymal stem cells (ADSCs) in mitigating the loss of muscle mass and strength in mouse model of DEX-induced muscle atrophy. METHODS: 3-month-old female C57BL/6 mice were treated with Dex (20 mg/kg body weight, i.p.) for 10 days to induce muscle atrophy, then subjected to intravenous injection of a single dose of ADSCs ([Formula: see text] cells/kg body weight) or vehicle control. The mice were killed 7 days after ADSCs treatment. Body compositions were measured by animal DXA, gastrocnemius muscle was isolated for ex vivo muscle functional test, histological assessment and Western blot, while tibialis anterior muscles were isolated for RNA-sequencing and qPCR. For in vitro study, C2C12 myoblast cells were cultured under myogenic differentiation medium for 5 days following 100 [Formula: see text]M Dex treatment with or without ADSC-conditioned medium for another 4 days. Samples were collected for qPCR analysis and Western blot analysis. Myotube morphology was measured by myosin heavy chain immunofluorescence staining. RESULTS: ADSC treatment significantly increased body lean mass (10-20%), muscle wet weight (15-30%) and cross-sectional area (CSA) (~ 33%) in DEX-induced muscle atrophy mice model and down-regulated muscle atrophy-associated genes expression (45-65%). Hindlimb grip strength (~ 37%) and forelimb ex vivo muscle contraction property were significantly improved (~ 57%) in the treatment group. Significant increase in type I fibres (~ 77%) was found after ADSC injection. RNA-sequencing results suggested that ERK1/2 signalling pathway might be playing important role underlying the beneficial effect of ADSC treatment, which was confirmed by ERK1/2 inhibitor both in vitro and in vivo. CONCLUSIONS: ADSCs restore the pathogenesis of Dex-induced muscle atrophy with an increased number of type I fibres, stronger muscle strength, faster recovery rate and more anti-fatigue ability via ERK1/2 signalling pathway. The inhibition of muscle atrophy-associated genes by ADSCs offered this treatment as an intervention option for muscle-associated diseases. Taken together, our findings suggested that adipose-derived mesenchymal stem cell therapy could be a new treatment option for patient with Dex-induced muscle atrophy.

Long-term outcomes of liver transplantation for alcohol-related liver disease.

BACKGROUND: Liver transplantation (LT) is being increasingly performed for alcohol-related liver disease (ALD). It is unclear whether the increasing frequency of LTs in ALD patients has a negative impact on deceased-donor (DDLT) allocation and whether the current policy of 6 months of abstinence before transplantation effectively prevents recidivism after transplantation or improves long-term outcomes. METHODS: A total of 506 adult LT recipients, including 97 ALD patients, were enrolled. The outcomes of ALD patients were compared with those of non-ALD patients. The 97 ALD patients were further divided into group A (6-month abstinence) and group N (nonabstinence) based on the pretransplant alcohol withdrawal period. The incidence of relapsed drinking and the long-term outcomes were compared between the two groups. RESULTS: The prevalence of LT for ALD significantly increased after 2016 (27.0% vs 14.0%; p < 0.01), but the frequency of DDLT for ALD remained unchanged (22.6% vs 34.1%, p = 0.210). After a median follow-up of 56.9 months, patient survival was comparable between the ALD and non-ALD patients (1, 3, and 5 years posttransplant: 87.6%, 84.3%, and 79.5% vs 82.8%, 76.6%, and 72.2%, respectively; p = 0.396). The results were consistent irrespective of the transplant type and disease severity. In ALD patients, 22 of the 70 (31.4%) patients reported relapsed drinking after transplantation, and the prevalence in group A had a higher tendency than that in group N (38.3% vs 17.4%, p = 0.077). Six months of abstinence or nonabstinence did not result in a survival difference, and de novo malignancies were the leading cause of late patient death in ALD patients. CONCLUSION: LT achieves favorable outcomes for ALD patients. Six months of abstinence pretransplant did not predict the risk of recidivism after transplantation. The high incidence of de novo malignancies in these patients warrants a more comprehensive physical evaluation and better lifestyle modifications to improve long-term outcomes.

Mechanotransduction of mesenchymal stem cells and hemodynamic implications.

Mesenchymal stem cells (MSCs) possess the capacity for self-renewal and multipotency. The traditional approach to manipulating MSC's fate choice predominantly relies on biochemical stimulation. Accumulating evidence also suggests the role of physical input in MSCs differentiation. Therefore, investigating mechanotransduction at the molecular level and related to tissue-specific cell functions sheds light on the responses secondary to mechanical forces. In this review, a new frontier aiming to optimize the cultural parameters was illustrated, i.e. spatial boundary condition, which recapitulates in vivo physiology and facilitates the investigations of cellular behavior. The concept of mechanical memory was additionally addressed to appreciate how MSCs store imprints from previous culture niches. Besides, different types of forces as physical stimuli were of interest based on the association with the respective signaling pathways and the differentiation outcome. The downstream mechanoreceptors and their corresponding effects were further pinpointed. The cardiovascular system or immune system may share similar mechanisms of mechanosensing and mechanotransduction; for example, resident stem cells in a vascular wall and recruited MSCs in the bloodstream experience mechanical forces such as stretch and fluid shear stress. In addition, baroreceptors or mechanosensors of endothelial cells detect changes in blood flow, pass over signals induced by mechanical stimuli and eventually maintain arterial pressure at the physiological level. These mechanosensitive receptors transduce pressure variation and regulate endothelial barrier functions. The exact signal transduction is considered context dependent but still elusive. In this review, we summarized the current evidence of how mechanical stimuli impact MSCs commitment and the underlying mechanisms. Future perspectives are anticipated to focus on the application of cardiovascular bioengineering and regenerative medicine.

Ginkgolide B facilitates muscle regeneration via rejuvenating osteocalcin-mediated bone-to-muscle modulation in aged mice.

BACKGROUND: The progressive deterioration of tissue-tissue crosstalk with aging causes a striking impairment of tissue homeostasis and functionality, particularly in the musculoskeletal system. Rejuvenation of the systemic and local milieu via interventions such as heterochronic parabiosis and exercise has been reported to improve musculoskeletal homeostasis in aged organisms. We have shown that Ginkgolide B (GB), a small molecule from Ginkgo biloba, improves bone homeostasis in aged mice by restoring local and systemic communication, implying a potential for maintaining skeletal muscle homeostasis and enhancing regeneration. In this study, we investigated the therapeutic efficacy of GB on skeletal muscle regeneration in aged mice. METHODS: Muscle injury models were established by barium chloride induction into the hind limb of 20-month-old mice (aged mice) and into C2C12-derived myotubes. Therapeutic efficacy of daily administrated GB (12 mg/kg body weight) and osteocalcin (50 µg/kg body weight) on muscle regeneration was assessed by histochemical staining, gene expression, flow cytometry, ex vivo muscle function test and rotarod test. RNA sequencing was used to explore the mechanism of GB on muscle regeneration, with subsequent in vitro and in vivo experiments validating these findings. RESULTS: GB administration in aged mice improved muscle regeneration (muscle mass, P = 0.0374; myofiber number/field, P = 0.0001; centre nucleus, embryonic myosin heavy chain-positive myofiber area, P = 0.0144), facilitated the recovery of muscle contractile properties (tetanic force, P = 0.0002; twitch force, P = 0.0005) and exercise performance (rotarod performance, P = 0.002), and reduced muscular fibrosis (collagen deposition, P < 0.0001) and inflammation (macrophage infiltration, P = 0.03). GB reversed the aging-related decrease in the expression of osteocalcin (P < 0.0001), an osteoblast-specific hormone, to promote muscle regeneration. Exogenous osteocalcin supplementation was sufficient to improve muscle regeneration (muscle mass, P = 0.0029; myofiber number/field, P < 0.0001), functional recovery (tetanic force, P = 0.0059; twitch force, P = 0.07; rotarod performance, P < 0.0001) and fibrosis (collagen deposition, P = 0.0316) in aged mice, without an increased risk of heterotopic ossification. CONCLUSIONS: GB treatment restored the bone-to-muscle endocrine axis to reverse aging-related declines in muscle regeneration and thus represents an innovative and practicable approach to managing muscle injuries. Our results revealed the critical and novel role of osteocalcin-GPRC6A-mediated bone-to-muscle communication in muscle regeneration, which provides a promising therapeutic avenue in functional muscle regeneration.

Nonlinear Magnon Polaritons.

We experimentally and theoretically demonstrate that nonlinear spin-wave interactions suppress the hybrid magnon-photon quasiparticle or "magnon polariton" in microwave spectra of a yttrium iron garnet film detected by an on-chip split-ring resonator. We observe a strong coupling between the Kittel and microwave cavity modes in terms of an avoided crossing as a function of magnetic fields at low microwave input powers, but a complete closing of the gap at high powers. The experimental results are well explained by a theoretical model including the three-magnon decay of the Kittel magnon into spin waves. The gap closure originates from the saturation of the ferromagnetic resonance above the Suhl instability threshold by a coherent backreaction from the spin waves.

Application of a deep learning system in glaucoma screening and further classification with colour fundus photographs: a case control study.

BACKGROUND: To verify efficacy of automatic screening and classification of glaucoma with deep learning system. METHODS: A cross-sectional, retrospective study in a tertiary referral hospital. Patients with healthy optic disc, high-tension, or normal-tension glaucoma were enrolled. Complicated non-glaucomatous optic neuropathy was excluded. Colour and red-free fundus images were collected for development of DLS and comparison of their efficacy. The convolutional neural network with the pre-trained EfficientNet-b0 model was selected for machine learning. Glaucoma screening (Binary) and ternary classification with or without additional demographics (age, gender, high myopia) were evaluated, followed by creating confusion matrix and heatmaps. Area under receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and F1 score were viewed as main outcome measures. RESULTS: Two hundred and twenty-two cases (421 eyes) were enrolled, with 1851 images in total (1207 normal and 644 glaucomatous disc). Train set and test set were comprised of 1539 and 312 images, respectively. If demographics were not provided, AUC, accuracy, precision, sensitivity, F1 score, and specificity of our deep learning system in eye-based glaucoma screening were 0.98, 0.91, 0.86, 0.86, 0.86, and 0.94 in test set. Same outcome measures in eye-based ternary classification without demographic data were 0.94, 0.87, 0.87, 0.87, 0.87, and 0.94 in our test set, respectively. Adding demographics has no significant impact on efficacy, but establishing a linkage between eyes and images is helpful for a better performance. Confusion matrix and heatmaps suggested that retinal lesions and quality of photographs could affect classification. Colour fundus images play a major role in glaucoma classification, compared to red-free fundus images. CONCLUSIONS: Promising results with high AUC and specificity were shown in distinguishing normal optic nerve from glaucomatous fundus images and doing further classification.

Immunometabolism of macrophages regulates skeletal muscle regeneration.

Sarcopenia is an age-related progressive loss of skeletal muscle mass, quality, and strength disease. In addition, sarcopenia is tightly correlated with age-associated pathologies, such as sarcopenic obesity and osteoporosis. Further understanding of disease mechanisms and the therapeutic strategies in muscle regeneration requires a deeper knowledge of the interaction of skeletal muscle and other cells in the muscle tissue. Skeletal muscle regeneration is a complex process that requires a series of highly coordinated events involving communication between muscle stem cells and niche cells, such as muscle fibro/adipogenic progenitors and macrophages. Macrophages play a critical role in tissue regeneration and the maintenance of muscle homeostasis by producing growth factors and cytokines that regulate muscle stem cells and myofibroblast activation. Furthermore, the aging-related immune dysregulation associated with the release of trophic factors and the polarization in macrophages transiently affect the inflammatory phase and impair muscle regeneration. In this review, we focus on the role and regulation of macrophages in skeletal muscle regeneration and homeostasis. The aim of this review is to highlight the important roles of macrophages as a therapeutic target in age-related sarcopenia and the increasing understanding of how macrophages are regulated will help to advance skeletal muscle regeneration.

Functioning tailor-made 3D-printed vascular graft for hemodialysis.

BACKGROUND: The two ends of arteriovenous graft (AVG) are anastomosed to the upper limb vessels by surgery for hemodialysis therapy. However, the size of upper limb vessels varies to a large extent among different individuals. METHODS: According to the shape and size of neck vessels quantified from the preoperative computed tomography angiographic scan, the ethylene-vinyl acetate (EVA)-based AVG was produced in H-shape by the three-dimensional (3D) printer and then sterilized. This study investigated the function of this novel 3D-printed AVG in vitro and in vivo. RESULTS: This 3D-printed AVG can be implanted in the rabbit's common carotid artery and common jugular vein with ease and functions in vivo. The surgical procedure was quick, and no suture was required. The blood loss was minimal, and no hematoma was noted at least 1 week after the surgery. The blood flow velocity within the implanted AVG was 14.9 ± 3.7 cm/s. Additionally, the in vitro characterization experiments demonstrated that this EVA-based biomaterial is biocompatible and possesses a superior recovery property than ePTFE after hemodialysis needle cannulation. CONCLUSIONS: Through the 3D printing technology, the EVA-based AVG can be tailor-made to fit the specific vessel size. This kind of 3D-printed AVG is functioning in vivo, and our results realize personalized vascular implants. Further large-animal studies are warranted to examine the long-term patency.

Demystifying the long noncoding RNA landscape of small EVs derived from human mesenchymal stromal cells.

INTRODUCTION: The regenerative capacity of mesenchymal stromal cells or medicinal signaling cells (MSCs) is largely mediated by their secreted small extracellular vesicles (sEVs), and the therapeutic efficacy of sEVs can be enhanced by licensing approaches (e.g., cytokines, hypoxia, chemicals, and genetic modification). Noncoding RNAs within MSC-derived sEVs (MSC-sEVs) have been demonstrated to be responsible for tissue regeneration. However, unlike miRNA fingerprints, which have been explored, the landscape of long noncoding RNAs (lncRNAs) in MSC-sEVs remains to be described. OBJECTIVES: To characterize lncRNA signatures in sEVs of human adipose-derived MSCs with or without inflammatory cytokine licensing and depict MSC-sEV-specific and MSC-enriched lncRNA repertoires. METHODS: sEVs were isolated from MSCs with or without TNF-α and IFN-γ (20 ng/mL) stimulation. High-throughput lncRNA sequencing and an in silico approach were employed to analyze the profile of lncRNAs in sEVs and predict lncRNA-protein interactomes. RESULTS: sEVs derived from human MSCs and fibroblasts carried a unique landscape of lncRNAs distinct from the lncRNAs inside these cells. Compared with fibroblast-derived sEVs (F-sEVs), 194 MSC-sEV-specific and 8 upregulated lncRNAs in MSC-sEVs were considered "medicinal signaling lncRNAs"; inflammatory cytokines upregulated 27 lncRNAs in MSC-sEVs, which were considered "licensing-responsive lncRNAs". Based on lncRNA-protein interactome prediction and enrichment analysis, we found that the proteins interacting with medicinal signaling lncRNAs or licensing-responsive lncRNAs have a tight interaction network involved in chromatin remodeling, SWI/SNF superfamily type complexes, and histone binding. CONCLUSION: In summary, our study depicts the landscape of lncRNAs in MSC-sEVs and predicts their potential functions via the lncRNA-protein interactome. Elucidation of the lncRNA landscape of MSC-sEVs will facilitate defining the therapeutic potency of MSC-sEVs and the development of sEV-based therapeutics.

Application of a Deep Learning System in Pterygium Grading and Further Prediction of Recurrence with Slit Lamp Photographs.

BACKGROUND: The aim of this study was to evaluate the efficacy of a deep learning system in pterygium grading and recurrence prediction. METHODS: This was a single center, retrospective study. Slit-lamp photographs, from patients with or without pterygium, were collected to develop an algorithm. Demographic data, including age, gender, laterality, grading, and pterygium area, recurrence, and surgical methods were recorded. Complex ocular surface diseases and pseudopterygium were excluded. Performance of the algorithm was evaluated by sensitivity, specificity, F1 score, accuracy, and area under the receiver operating characteristic curve. Confusion matrices and heatmaps were created to help explain the results. RESULTS: A total of 237 eyes were enrolled, of which 176 eyes had pterygium and 61 were non-pterygium eyes. The training set and testing set were comprised of 189 and 48 photographs, respectively. In pterygium grading, sensitivity, specificity, F1 score, and accuracy were 80% to 91.67%, 91.67% to 100%, 81.82% to 94.34%, and 86.67% to 91.67%, respectively. In the prediction model, our results showed sensitivity, specificity, positive predictive value, and negative predictive values were 66.67%, 81.82%, 33.33%, and 94.74%, respectively. CONCLUSIONS: Deep learning systems can be useful in pterygium grading based on slit lamp photographs. When clinical parameters involved in the prediction of pterygium recurrence were included, the algorithm showed higher specificity and negative predictive value in prediction.

Development of deep learning algorithms to discriminate giant cell tumors of bone from adjacent normal tissues by confocal Raman spectroscopy.

Raman spectroscopy is a non-destructive analysis technique that provides detailed information about the chemical structure of tumors. Raman spectra of 52 giant cell tumors of bone (GCTB) and 21 adjacent normal tissues of formalin-fixed paraffin embedded (FFPE) and frozen specimens were obtained using a confocal Raman spectrometer and analyzed with machine learning and deep learning algorithms. We discovered characteristic Raman shifts in the GCTB specimens. They were assigned to phenylalanine and tyrosine. Based on the spectroscopic data, classification algorithms including support vector machine, k-nearest neighbors and long short-term memory (LSTM) were successfully applied to discriminate GCTB from adjacent normal tissues of both the FFPE and frozen specimens, with the accuracy ranging from 82.8% to 94.5%. Importantly, our LSTM algorithm showed the best performance in the discrimination of the frozen specimens, with a sensitivity and specificity of 93.9% and 95.1% respectively, and the AUC was 0.97. The results of our study suggest that confocal Raman spectroscopy accomplished by the LSTM network could non-destructively evaluate a tumor margin by its inherent biochemical specificity which may allow intraoperative assessment of the adequacy of tumor clearance.