Quantitative measurement of the ureter on three-dimensional magnetic resonance urography images using deep learning.

BACKGROUND: Accurate measurement of ureteral diameters plays a pivotal role in diagnosing and monitoring urinary tract obstruction (UTO). While three-dimensional magnetic resonance urography (3D MRU) represents a significant advancement in imaging, the traditional manual methods for assessing ureteral diameters are characterized by labor-intensive procedures and inherent variability. In the realm of medical image analysis, deep learning has led to a paradigm shift, yet the development of a comprehensive automated tool for the precise segmentation and measurement of ureters in MR images is an unaddressed challenge. PURPOSE: The ureter was quantitatively measured on 3D MRU images using a deep learning model. METHODS: A retrospective cohort of 445 3D MRU scans (443 patients, 52 ± 18 years; 217 female patients) was collected and split into training, validation, and internal testing cohorts. A 3D V-Net model was trained for urinary tract segmentation, and a post-processing algorithm was developed for ureteral measurements. The accuracy of the segmentation was evaluated using the Dice similarity coefficient (DSC) and volume intraclass correlation coefficient (ICC), with ground truth segmentations provided by experienced radiologists. The external cohort comprised 50 scans (50 patients, 55 ± 21 years; 30 female patients), and the model-predicted ureteral diameter measurements were compared with manual measurements to assess system performance. The various diameter parameters of ureter among the different measurement methods (ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction) were assessed with Friedman tests and post hoc Dunn test. The effectiveness of the UTO diagnosis was assessed by receiver operating characteristic (ROC) curves and their respective areas under the curve (AUC) between different methods. RESULTS: In both the internal test and external cohorts, the mean DSC values for bilateral ureters exceeded 0.70. The ICCs for the bilateral ureter volume obtained by comparing the model and manual segmentation were all greater than 0.96 (p  < â€¯0.05), except for the right ureter in the internal test cohort, for which the ICC was 0.773 (p  < â€¯0.05). The mean DSCs for interobserver and intraobserver reliability were all above 0.97. The maximum diameter of the ureter exhibited no statistically significant differences either in the dilated (p = 0.08) or in the non-dilated (p = 0.32) ureters across the three measurement methods. The AUCs of ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction in diagnosing UTO were 0.988 (95% CI: 0.934, 1.000), 0.961 (95% CI: 0.893, 0.991), and 0.979 (95% CI: 0.919, 0.998), respectively. There was no statistical difference between AUCs of the different methods (p > 0.05). CONCLUSION: The proposed deep learning model and post-processing algorithm provide an effective means for the quantitative evaluation of urinary diseases using 3D MRU images.

Nanozyme-based Clusterphene for Enhanced Electrically Catalytic Cancer Therapy.

Nanozyme mediated catalytic therapy is an attractive strategy for cancer therapy. However, the nanozymes are tended to assemble into 3D architectures, resulting in poor catalytic efficiency for therapy. This study designs the assembly of nanozymes and natural enzymes into the layered structures featuring hexagonal pores as nanozyme clusterphene and investigates their catalytic therapy with the assistance of electric field. The nanozyme-based clusterphene consists of polyoxometalate (POM) and natural glucose oxidase (GOx), named POMG-based clusterphene, which facilitate multi-enzyme activities including peroxidase (POD), catalase (CAT), and glutathione oxidase (GPx). The highly ordered layers with hexagonal pores of POMG units significantly improve the peroxidase-like (POD-like) activity of the nanozyme and thus the sustained production of reactive oxygen species (ROS). At the same time, GOx can increase endogenous H2O2 and produce gluconic acid while consuming glucose, the nutrient of tumor cell growth. The results indicate that the POD-like activity of POMG-based clusterphene increase approximately sevenfold under electrical stimulation compared with Nd-substituted keggin type POM cluster (NdPW11). The experiments both in vitro and in vivo show that the proposed POMG-based clusterphene mediated cascade catalytic therapy is capable of efficient tumor inhibiting and preventing tumor proliferation in tumor-bearing mice model, promising as an excellent candidate for catalytic therapy.

A quantitative evaluation of the deep learning model of segmentation and measurement of cervical spine MRI in healthy adults.

PURPOSE: To evaluate the 3D U-Net model for automatic segmentation and measurement of cervical spine structures using magnetic resonance (MR) images of healthy adults. MATERIALS AND METHODS: MR images of the cervical spine from 160 healthy adults were collected retrospectively. A previously constructed deep-learning model was used to automatically segment anatomical structures. Segmentation and localization results were checked by experienced radiologists. Pearson's correlation analyses were conducted to examine relationships between patient and image parameters. RESULTS: No measurement was significantly correlated with age or sex. The mean values of the areas of the subarachnoid space and spinal cord from the C2/3 (cervical spine 2-3) to C6/7 intervertebral disc levels were 102.85-358.12 mm2 and 53.71-110.32 mm2 , respectively. The ratios of the areas of the spinal cord to the subarachnoid space were 0.25-0.68. The transverse and anterior-posterior diameters of the subarachnoid space were 14.77-26.56 mm and 7.38-17.58 mm, respectively. The transverse and anterior-posterior diameters of the spinal cord were 9.11-16.02 mm and 5.47-10.12 mm, respectively. CONCLUSION: A deep learning model based on 3D U-Net automatically segmented and performed measurements on cervical spine MR images from healthy adults, paving the way for quantitative diagnosis models for spinal cord diseases.

Strategies to Reverse Hypoxic Tumor Microenvironment for Enhanced Sonodynamic Therapy.

Sonodynamic therapy (SDT) has emerged as a highly effective modality for the treatment of malignant tumors owing to its powerful penetration ability, noninvasiveness, site-confined irradiation, and excellent therapeutic efficacy. However, the traditional SDT, which relies on oxygen availability, often fails to generate a satisfactory level of reactive oxygen species because of the widespread issue of hypoxia in the tumor microenvironment of solid tumors. To address this challenge, various approaches are developed to alleviate hypoxia and improve the efficiency of SDT. These strategies aim to either increase oxygen supply or prevent hypoxia exacerbation, thereby enhancing the effectiveness of SDT. In view of this, the current review provides an overview of these strategies and their underlying principles, focusing on the circulation of oxygen from consumption to external supply. The detailed research examples conducted using these strategies in combination with SDT are also discussed. Additionally, this review highlights the future prospects and challenges of the hypoxia-alleviated SDT, along with the key considerations for future clinical applications. These considerations include the development of efficient oxygen delivery systems, the accurate methods for hypoxia detection, and the exploration of combination therapies to optimize SDT outcomes.

Simple and field-adapted species identification of biological specimens combining multiplex multienzyme isothermal rapid amplification, lateral flow dipsticks, and universal primers for initial rapid screening without standard PCR laboratory.

Species identification of biological specimens can provide the valuable clues and accelerate the speed of prosecution material processing for forensic investigation, especially when the case scene is inaccessible and the physical evidence is cumbersome. Thus, establishing a rapid, simple, and field-adapted species identification method is crucial for forensic scientists, particularly as first-line technology at the crime scene for initial rapid screening. In this study, we established a new field-adapted species identification method by combining multiplex multienzyme isothermal rapid amplification (MIRA), lateral flow dipstick (LFD) system, and universal primers. Universal primers targeting COX I and COX II genes were used in multiplex MIRA-LFD system for seven species identification, and a dedicated MIRA-LFD system primer targeting CYT B gene was used to detect the human material. DNA extraction was performed by collecting DNA directly from the centrifuged supernatant. Our study found that the entire amplification process took only 15 min at 37 °C and the results of LFDs could be visually observed after 10 min. The detection sensitivity of human material could reach 10 pg, which is equivalent to the detection of single cell. Different common animal samples mixed at the ratio of 1 ng:1 ng, 10 ng:1 ng, and 1 ng:10 ng could be detected successfully. Furthermore, the damaged and degraded samples could also be detected. Therefore, the convenient, feasible, and rapid approach for species identification is suitable for popularization as first-line technology at the crime scene for initial rapid screening and provides a great convenient for forensic application.

Ethynyl-B(dan) in [3+2] Cycloaddition and Larock Indole Synthesis: Synthesis of Stable Boron-Containing Heteroaromatic Compounds.

The cycloaddition of nitrile oxides with ethynyl-B(dan) (dan=naphthalene-1,8-diaminato) allowed the facile preparation of diverse isoxazolyl-B(dan) compounds, all of which displayed excellent protodeborylation-resistant properties. The dan-installation on the boron center proves vital to the high stability of the products as well as the perfect regioselectivity arising from hydrogen bond-directed orientation in the cycloaddition. The diminished boron-Lewis acidity of ethynyl-B(dan) also renders it amenable to azide-alkyne cycloaddition, Larock indole synthesis and related heteroannulations. The obtained boron-containing triazole, indoles, benzofuran and indenone exhibit sufficient resistance toward protodeborylation. Despite the commonly accepted transmetalation-inactive property derived from the diminished Lewis acidity, the synthesized heteroaryl-B(dan) compound was still found to be convertible to the oligoarene via sequential Suzuki-Miyaura coupling.

Automatic Segmentation and Quantification of Abdominal Aortic Calcification in Lateral Lumbar Radiographs Based on Deep-Learning-Based Algorithms.

To investigate the performance of deep-learning-based algorithms for the automatic segmentation and quantification of abdominal aortic calcification (AAC) in lateral lumbar radiographs, we retrospectively collected 1359 consecutive lateral lumbar radiographs. The data were randomly divided into model development and hold-out test datasets. The model development dataset was used to develop U-shaped fully convolutional network (U-Net) models to segment the landmarks of vertebrae T12-L5, the aorta, and anterior and posterior aortic calcifications. The AAC lengths were calculated, resulting in an automatic Kauppila score output. The vertebral levels, AAC scores, and AAC severity were obtained from clinical reports and analyzed by an experienced expert (reference standard) and the model. Compared with the reference standard, the U-Net model demonstrated a good performance in predicting the total AAC score in the hold-out test dataset, with a correlation coefficient of 0.97 (p <0.001). The overall accuracy for the AAC severity was 0.77 for the model and 0.74 for the clinical report. Additionally, the Kendall coefficient of concordance of the total AAC score prediction was 0.89 between the model-predicted score and the reference standard, and 0.88 between the structured clinical report and the reference standard. In conclusion, the U-Net-based deep learning approach demonstrated a relatively high model performance in automatically segmenting and quantifying ACC.

Recent Advances in Polyoxometalate Based Nanoplatforms Mediated Reactive Oxygen Species Cancer Therapy.

The potential of reactive oxygen species (ROS) cancer therapy in tumor treatment has been greatly enhanced by the introduction of catalytically superior polyoxometalate (POM)-based nanoplatforms, mainly composed of atomic clusters consisting of pre-transition metals and oxygen. These nanoplatforms have unique advantages, such as Fenton activity at neutral pH, induction of cellular ferroptosis instead of just apoptosis, and sensitivity to external field stimulation. However, there are also inevitable challenges such as neutralization of ROS by the antioxidant system of the tumor microenvironment (TME), hypoxia, and limited hydrogen peroxide concentrations. This review article aims to provide an overview of recent research advancements in POM-based nanoplatforms for ROS therapy from the perspective of chemical reactions and biological processes, addressing endogenous and exogenous factors that affect the antitumor efficacy. Endogenous factors include the mechanism of ROS generation by POM, the impact of pH and antioxidant systems on POM, and the various manners of tumor cell death. Exogenous stimuli mainly include light, heat, X-rays, and electricity. The article analyzes the specific mechanisms of action of each influencing factor in the first two sections, concluding with the limitations of the present study and some possible directions for future research.

High Hydrovoltaic Power Density Achieved by Universal Evaporating Potential Devices.

While hydrovoltaic electrical energy generation developments in very recent years have provided an alternative strategy to generate electricity from the direct interaction of materials with water, the two main issues still need to be addressed: achieving satisfactory output power density and understanding the reliable mechanism. In the present work, the integration of capacitors and water evaporation devices is proposed to provide a stable power supply. The feasible device structure consuming only water and air is green and environmentally sustainable, achieving a recorded power density of 142.72 µW cm-2 . The output power of the series of devices is sufficient to drive portable electronic products with different voltage and current requirements, enabling self-driving systems for portable appliances. It has been shown that the working behavior originates from evaporating potential other than streaming potential. The present work provides both theoretical support and an experimental design for realizing practical application of hydrovoltaic electrical energy generation devices.

A Ready-to-Use Purified Exosome Product for Volumetric Muscle Loss and Functional Recovery.

Large skeletal muscle defects owing to trauma or following tumor extirpation can result in substantial functional impairment. Purified exosomes are now available clinically and have been used for wound healing. The objective of this study was to evaluate the regenerative capacity of commercially available exosomes on an animal model of volumetric muscle loss (VML) and its potential translation to human muscle injury. An established VML rat model was used. In the in vitro experiment, rat myoblasts were isolated and cocultured with 5% purified exosome product (PEP) to validate uptake. Myoblast proliferation and migration was evaluated with increasing concentrations of PEP (2.5%, 5%, and 10%) in comparison with control media (F10) and myoblast growth medium (MGM). In the in vivo experiment, a lateral gastrocnemius-VML defect was made in the rat hindlimb. Animals were randomized into four experimental groups; defects were treated with surgery alone, fibrin sealant, fibrin sealant and PEP, or platelet-rich plasma (PRP). The groups were further randomized into four recovery time points (14, 28, 45, or 90 days). The isometric tetanic force (ITF), which was measured as a percentage of force compared with normal limb, was used for functional evaluation. Florescence microscopy confirmed that 5% PEP demonstrated cellular uptake ∼8-12 h. Compared with the control, myoblasts showed faster proliferation with PEP irrespective of concentration. PEP concentrations of 2.5% and 5% promoted myoblast migration faster compared with the control (<0.05). At 90 days postop, both the PEP and fibrin sealant and PRP groups showed greater ITF compared with control and fibrin sealant alone (<0.05). At 45 days postop, PEP with fibrin sealant had greater cellularity compared with control (<0.05). At 90 days postop, both PEP with fibrin sealant and the PRP-treated groups had greater cellularity compared with fibrin sealant and control (<0.05). PEP promoted myoblast proliferation and migration. When delivered to a wound with a fibrin sealant, PEP allowed for muscle regeneration producing greater functional recovery and more cellularity in vivo compared with untreated animals. PEP may promote muscle regeneration in cases of VML; further research is warranted to evaluate PEP for the treatment of clinical muscle defects.

HDAC1/2/3 are major histone desuccinylases critical for promoter desuccinylation.

Lysine succinylation is one of the major post-translational modifications occurring on histones and is believed to have significant roles in regulating chromatin structure and function. Currently, histone desuccinylation is widely believed to be catalyzed by members of the SIRT family deacetylases. Here, we report that histone desuccinylation is in fact primarily catalyzed by the class I HDAC1/2/3. Inhibition or depletion of HDAC1/2/3 resulted in a marked increase of global histone succinylation, whereas ectopic expression of HDAC1/2/3 but not their deacetylase inactive mutants downregulated global histone succinylation. We demonstrated that the class I HDAC1/2/3 complexes have robust histone desuccinylase activity in vitro. Genomic landscape analysis revealed that histone succinylation is highly enriched at gene promoters and inhibition of HDAC activity results in marked elevation of promoter histone succinylation. Furthermore, our integrated analysis revealed that promoter histone succinylation positively correlates with gene transcriptional activity. Collectively, we demonstrate that the class I HDAC1/2/3 but not the SIRT family proteins are the major histone desuccinylases particularly important for promoter histone desuccinylation. Our study thus sheds new light on the role of histone succinylation in transcriptional regulation.

GSK3ß-driven SOX2 overexpression is a targetable vulnerability in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest forms of human malignancy that currently lacks approved targeted therapeutics. Accumulating evidence suggests that SOX2 overexpression is a key driving factor for ESCC and various squamous cell carcinoma. Here, through screening a small-molecule kinase inhibitor library, we identified GSK3ß as a kinase that is critically required for robust SOX2 expression in ESCC cells. GSK3ß did not promote SOX2 transcriptionally but was required for SOX2 protein stability. We demonstrated that GSK3ß interacts with and phosphorylates SOX2 at residue S251, which blocks SOX2 from ubiquitination and proteasome-dependent degradation instigated by ubiquitin E3 ligase CUL4ADET1-COP1. Pharmacological inhibition or knockdown of GSK3ß by RNA interference selectively impaired SOX2-positive ESCC cell proliferation, cancer stemness, and tumor growth in mouse xenograft model, suggesting that GSK3ß promotes ESCC tumorigenesis primarily by driving SOX2 overexpression. GSK3ß was found to be frequently overexpressed in clinical esophageal tumors, and there was a positive correlation between GSK3ß and SOX2 protein levels. Notably, we found that SOX2 enhanced GSK3ß expression transcriptionally, suggesting the existence of a vicious cycle that drives a coordinated GSK3ß and SOX2 overexpression in ESCC cells. Finally, we demonstrated in tumor xenograft model that GSK3ß inhibitor AR-A014418 was effective in suppressing SOX2-positive ESCC tumor progression and inhibited tumor progression cooperatively with chemotherapeutic agent carboplatin. In conclusion, we uncovered a novel role for GSK3ß in driving SOX2 overexpression and tumorigenesis and provided evidence that targeting GSK3ß may hold promise for the treatment of recalcitrant ESCCs.

Enhancing Functional Recovery after Segmental Nerve Defect Using Nerve Allograft Treated with Plasma-Derived Exosome.

BACKGROUND: Nerve injuries can result in detrimental functional outcomes. Currently, autologous nerve graft offers the best outcome for segmental peripheral nerve injury. Allografts are alternatives, but do not have comparable results. This study evaluated whether plasma-derived exosome can improve nerve regeneration and functional recovery when combined with decellularized nerve allografts. METHODS: The effect of exosomes on Schwann cell proliferation and migration were evaluated. A rat model of sciatic nerve repair was used to evaluate the effect on nerve regeneration and functional recovery. A fibrin sealant was used as the scaffold for exosome. Eighty-four Lewis rats were divided into autograft, allograft, and allograft with exosome groups. Gene expression of nerve regeneration factors was analyzed on postoperative day 7. At 12 and 16 weeks, rats were subjected to maximum isometric tetanic force and compound muscle action potential. Nerve specimens were then analyzed by means of histology and immunohistochemistry. RESULTS: Exosomes were readily taken up by Schwann cells that resulted in improved Schwann cell viability and migration. The treated allograft group had functional recovery (compound muscle action potential, isometric tetanic force) comparable to that of the autograft group. Similar results were observed in gene expression analysis of nerve regenerating factors. Histologic analysis showed no statistically significant differences between treated allograft and autograft groups in terms of axonal density, fascicular area, and myelin sheath thickness. CONCLUSIONS: Plasma-derived exosome treatment of decellularized nerve allograft may provide comparable clinical outcomes to that of an autograft. This can be a promising strategy in the future as an alternative for segmental peripheral nerve repair. CLINICAL RELEVANCE STATEMENT: Off-the-shelf exosomes may improve recovery in nerve allografts.

Semiautomated pelvic lymph node treatment response evaluation for patients with advanced prostate cancer: based on MET-RADS-P guidelines.

BACKGROUND: The evaluation of treatment response according to METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) criteria is an important but time-consuming task for patients with advanced prostate cancer (APC). A deep learning-based algorithm has the potential to assist with this assessment. OBJECTIVE: To develop and evaluate a deep learning-based algorithm for semiautomated treatment response assessment of pelvic lymph nodes. METHODS: A total of 162 patients who had undergone at least two scans for follow-up assessment after APC metastasis treatment were enrolled. A previously reported deep learning model was used to perform automated segmentation of pelvic lymph nodes. The performance of the deep learning algorithm was evaluated using the Dice similarity coefficient (DSC) and volumetric similarity (VS). The consistency of the short diameter measurement with the radiologist was evaluated using Bland-Altman plotting. Based on the segmentation of lymph nodes, the treatment response was assessed automatically with a rule-based program according to the MET-RADS-P criteria. Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and two radiologists [attending radiologist (R1) and fellow radiologist (R2)]. RESULTS: The mean DSC and VS of the pelvic lymph node segmentation were 0.82 ± 0.09 and 0.88 ± 0.12, respectively. Bland-Altman plotting showed that most of the lymph node measurements were within the upper and lower limits of agreement (LOA). The accuracies of automated segmentation-based assessment were 0.92 (95% CI: 0.85-0.96), 0.91 (95% CI: 0.86-0.95) and 75% (95% CI: 0.46-0.92) for target lesions, nontarget lesions and nonpathological lesions, respectively. The consistency of treatment response assessment based on automated segmentation and manual segmentation was excellent for target lesions [K value: 0.92 (0.86-0.98)], good for nontarget lesions [0.82 (0.74-0.90)] and moderate for nonpathological lesions [0.71 (0.50-0.92)]. CONCLUSION: The deep learning-based semiautomated algorithm showed high accuracy for the treatment response assessment of pelvic lymph nodes and demonstrated comparable performance with radiologists.

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria.

BACKGROUND: Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation process and improve the efficiency of imaging interpretation. OBJECTIVE: To develop an automated algorithm for segmentation of liver metastases based on a deep learning method and assess its efficacy for treatment response assessment according to the RECIST 1.1 criteria. METHODS: One hundred and sixteen treated patients with clinically confirmed liver metastases were enrolled. All patients had baseline and post-treatment MR images. They were divided into an initial (n = 86) and validation cohort (n = 30) according to the examined time. The metastatic foci on DWI images were annotated by two researchers in consensus. Then the treatment responses were assessed by the two researchers according to RECIST 1.1 criteria. A 3D U-Net algorithm was trained for automated liver metastases segmentation using the initial cohort. Based on the segmentation of liver metastases, the treatment response was assessed automatically with a rule-based program according to the RECIST 1.1 criteria. The segmentation performance was evaluated using the Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD). The area under the curve (AUC) and Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and compared with two radiologists [attending radiologist (R1) and fellow radiologist (R2)] in the validation cohort. RESULTS: In the validation cohort, the mean DSC, VS, and HD were 0.85 ± 0.08, 0.89 ± 0.09, and 25.53 ± 12.11 mm for the liver metastases segmentation. The accuracies of R1, R2 and automated segmentation-based assessment were 0.77, 0.65, and 0.74, respectively, and the AUC values were 0.81, 0.73, and 0.83, respectively. The consistency of treatment response assessment based on automated segmentation and manual annotation was moderate [K value: 0.60 (0.34-0.84)]. CONCLUSION: The deep learning-based liver metastases segmentation was capable of evaluating treatment response according to RECIST 1.1 criteria, with comparable results to the junior radiologist and superior to that of the fellow radiologist.

Black TiO2-Based Dual Photoanodes Boost the Efficiency of Quantum Dot-Sensitized Solar Cells to 11.7.

Quantum dot-sensitized solar cells (QDSSC) have been regarded as one of the most promising candidates for effective utilization of solar energy, but its power conversion efficiency (PCE) is still far from meeting expectations. One of the most important bottlenecks is the limited collection efficiency of photogenerated electrons in the photoanodes. Herein, we design QDSSCs with a dual-photoanode architecture, and assemble the dual photoanodes with black TiO2 nanoparticles (NPs), which were processed by a femtosecond laser in the filamentation regime, and common CdS/CdSe QD sensitizers. A maximum PCE of 11.7% with a short circuit current density of 50.3 mA/cm2 is unambiguously achieved. We reveal both experimentally and theoretically that the enhanced PCE is mainly attributed to the improved light harvesting of black TiO2 due to the black TiO2 shells formed on white TiO2 NPs.

Delayed Supplementation Strategy of Extracellular Vesicles from Adipose-Derived Mesenchymal Stromal Cells with Improved Proregenerative Efficiency in a Fat Transplantation Model.

Background: Mesenchymal stromal cells (MSCs) and their secreted extracellular vesicles (MSC-EVs) possess similar proregenerative effects when injected into defects immediately following trauma. However, MSC-EVs are superior to MSCs in terms of storage and rejection reflection, while immediate administration of MSC-EVs is related to several target cells for most donor cells die within few weeks. Besides, the inflammatory cascade is incited, providing an unfavorable environment for target cells. We hypothesized that delayed injection of MSC-EVs might have priority on tissue regeneration than instant injection. Method: Extracellular vesicles isolated from adipose-derived mesenchymal stromal cells (ADSC-EVs) were administered into human umbilical vein endothelial cells (HUVECs) in vitro at different doses. The migration of HUVECs was assessed using the scratch wound healing assay, whereas the length of tubes and number of vessel-like structures formed by HUVECs were determined using tube formation assay. Next, 24 BALB/c nude mice were randomly divided into three groups (n = 8). For the EV-delayed group, ADSC-EVs were injected into transplanted fat a week later than the EV-immediate group. The volume and weight of grafts were measured at 3 months after fat transplantation. Further, the number of CD31-possitive vessels and CD206-possitive cells in the fat grafts was quantified. Results: Compared with the EV-immediate group, the EV-delayed group had a higher fat tissue retention volume (0.11 ± 0.02 mL versus 0.08 ± 0.01 mL), more neovessels (31.00 ± 4.60 versus 24.20 ± 3.97), and fewer cysts. Furthermore, there were more Ki67-positive cells (25.40 ± 7.14 versus 16.20 ± 4.17) and CD206-positive M2 macrophages cells (23.60 ± 3.44 versus 14.00 ± 3.85) in the EV-delayed group than in the EV-immediate group. Conclusion: Delayed injection of ADSC-EVs promotes fat graft volume retention by stimulating angiogenesis. These findings suggest that delayed supplementation might be a more effective strategy for the application of MSC-EVs in tissue regeneration.

Pearl-inspired graphene oxide-collagen microgel with multi-layer mineralization through microarray chips for bone defect repair.

Biomineralization of natural polymers in simulated body fluid (SBF) can significantly improve its biocompatibility, osteoconductivity, and osteoinductivity because of the hydroxyapatite (HAp) deposition. Nevertheless, the superficial HAp crystal deposition hamper the deep inorganic ions exchange in porous microgels, thus gradually leading to a nonuniform regeneration effect. Inspired by the pearl forming process, this article uses the microarray chips to fabricate the multi-layer mineralized graphene oxide (GO)-collagen (Col)-hydroxyapatite (HAp) microgel, denoted as MMGCH. These fabricated MMGCH microgels exhibit porous structure and uniform HAp distribution. Furthermore, the suitable microenvironment offered by microgel promotes the time-dependent proliferation and osteogenic differentiation of stem cells, which resulted in upregulated osteogenesis-related genes and proteins, such as alkaline phosphatase, osteocalcin, and collagen-1. Finally, the MMGCH microgels possess favorable bone regeneration capacities both in cranial bone defects and mandibular bone defects via providing a suitable microenvironment for host-derived cells to form new bone tissues. This work presents a biomimetic means aiming to achieve full-thickness and uniform HAp deposition in hydrogel for bone defect repair.

Boosting Low-Temperature Resistance of Energy Storage Devices by Photothermal Conversion Effects.

While flexible supercapacitors with high capacitance and energy density is highly desired for outdoor wearable electronics, their application under low-temperature environments, like other energy storage devices, remains an urgent challenge. Solar thermal energy converts solar light into heat and has been extensively applied for solar desalination and power generation. In the present work, to address the failure problem of energy storage devices in a cold environment, solar thermal energy was used to improve flexible supercapacitor performance at low temperature. As a proof of concept presented here, a typical all-solid-state supercapacitor composed of activated carbon electrodes and gel polymer electrolyte was coated by a carbonized melamine sponge. Due to the ability of photothermal conversion of carbonized melamine sponge, the capacitance of the supercapacitor was greatly enhanced, which could be further improved by adding surface plasmonic nanomaterials, for example, Ag nanowires. Compared with the device without photothermal conversion layers, the specific capacitance increased 3.48 times at -20 °C and retained 87% capacitance at room temperature and the specific capacitance increased 6.69 times at -50 °C and retained 73% capacitance at room temperature. The present work may provide new insights on the application of solar energy and the design of energy storage devices with excellent low-temperature resistance.

Enhanced performance of asymmetric supercapacitor based on NiZn-LDH@NiCoSe2electrode materials.

While supercapacitors have been widely studied as the next generation of energy storage devices, to develop active electrode materials for enhancing device performance is still challenging. Herein, we fabricated asymmetric supercapacitors based on NiZn-Layered double hydroxide (LDH) @NiCoSe2hierarchical nanostructures as electrode materials. The NiZn-LDH@NiCoSe2composites are deposited on Ni foam by a two-step strategy, in which NiZn-LDH nanosheets were firstly grown on Ni foam by hydrothermal method, and then NiCoSe2particles were prepared by electrodeposition. Due to the synergistic effect between NiZn-LDH and NiCoSe2, excellent device performance was achieved. In a three-electrode system, the NiZn-LDH@NiCoSe2exhibits a specific capacitance of 2980 F g-1at 1 A g-1. Furthermore, the asymmetric supercapacitor of NiZn-LDH@NiCoSe2//activated carbon (AC) device was assembled, which exhibits the energy density of 49.2 Wh kg-1at the power density of 160 W kg-1, with the capacity retention rate is 91% after 8000 cycles. The results indicates that NiZn-LDH@NiCoSe2is a promising candidate as electrode materials for efficient energy storage devices.