Primed 3D injectable microniches enabling low-dosage cell therapy for critical limb ischemia.

The promise of cell therapy for repair and restoration of damaged tissues or organs relies on administration of large dose of cells whose healing benefits are still limited and sometimes irreproducible due to uncontrollable cell loss and death at lesion sites. Using a large amount of therapeutic cells increases the costs for cell processing and the risks of side effects. Optimal cell delivery strategies are therefore in urgent need to enhance the specificity, efficacy, and reproducibility of cell therapy leading to minimized cell dosage and side effects. Here, we addressed this unmet need by developing injectable 3D microscale cellular niches (microniches) based on biodegradable gelatin microcryogels (GMs). The microniches are constituted by in vitro priming human adipose-derived mesenchymal stem cells (hMSCs) seeded within GMs resulting in tissue-like ensembles with enriched extracellular matrices and enhanced cell-cell interactions. The primed 3D microniches facilitated cell protection from mechanical insults during injection and in vivo cell retention, survival, and ultimate therapeutic functions in treatment of critical limb ischemia (CLI) in mouse models compared with free cell-based therapy. In particular, 3D microniche-based therapy with 10(5) hMSCs realized better ischemic limb salvage than treatment with 10(6) free-injected hMSCs, the minimum dosage with therapeutic effects for treating CLI in literature. To the best of our knowledge, this is the first convincing demonstration of injectable and primed cell delivery strategy realizing superior therapeutic efficacy for treating CLI with the lowest cell dosage in mouse models. This study offers a widely applicable cell delivery platform technology to boost the healing power of cell regenerative therapy.

Fast reconstruction of fluorophore concentration variation based on the derivation of the diffusion equation.

The information of fluorophore concentration variation (FCV) has the potential for drug development and tumor studies, but the reconstruction of FCV is time-consuming in dynamic fluorescence molecular tomography (DFMT). In this paper, a time-efficient reconstruction method for FCV is presented. The system equation of this method is derived from the derivation of the diffusion equation, and its size does not change with the number of frames. The computational time can be significantly reduced by using this method because the images of different frames are reconstructed separately. Simulations and phantom experiments are performed to validate the performance of the proposed method. The results show that compared with the previous method, the proposed method can obtain better results and consumes less computational time with the same number of iterations. In addition, the time consumption in a single iteration of the proposed method increases much slower with the number of frames.

Integrated Analysis of Metabolomics Combined with Network Pharmacology and Molecular Docking Reveals the Effects of Processing on Metabolites of Dendrobium officinale.

Dendrobium officinale (D. officinale) is a precious medicinal species of Dendrobium Orchidaceae, and the product obtained by hot processing is called "Fengdou". At present, the research on the processing quality of D. officinale mainly focuses on the chemical composition indicators such as polysaccharides and flavonoids content. However, the changes in metabolites during D. officinale processing are still unclear. In this study, the process was divided into two stages and three important conditions including fresh stems, semiproducts and "Fengdou" products. To investigate the effect of processing on metabolites of D. officinale in different processing stages, an approach of combining metabolomics with network pharmacology and molecular docking was employed. Through UPLC-MS/MS analysis, a total of 628 metabolites were detected, and 109 of them were identified as differential metabolites (VIP ≥ 1, |log2 (FC)| ≥ 1). Next, the differential metabolites were analyzed using the network pharmacology method, resulting in the selection of 29 differential metabolites as they have a potential pharmacological activity. Combining seven diseases, 14 key metabolites and nine important targets were screened by constructing a metabolite-target-disease network. The results showed that seven metabolites with potential anticoagulant, hypoglycemic and tumor-inhibiting activities increased in relative abundance in the "Fengdou" product. Molecular docking results indicated that seven metabolites may act on five important targets. In general, processing can increase the content of some active metabolites of D. officinale and improve its medicinal quality to a certain extent.

Mixing Matrix-corrected Whole-body Pharmacokinetic Modeling Using Longitudinal Micro-computed Tomography and Fluorescence-mediated Tomography.

PURPOSE: Pharmacokinetic modeling can be applied to quantify the kinetics of fluorescently labeled compounds using longitudinal micro-computed tomography and fluorescence-mediated tomography (µCT-FMT). However, fluorescence blurring from neighboring organs or tissues and the vasculature within tissues impede the accuracy in the estimation of kinetic parameters. Contributions of elimination and retention activities of fluorescent probes inside the kidneys and liver can be hard to distinguish by a kinetic model. This study proposes a deconvolution approach using a mixing matrix to model fluorescence contributions to improve whole-body pharmacokinetic modeling. PROCEDURES: In the kinetic model, a mixing matrix was applied to unmix the fluorescence blurring from neighboring tissues and blood vessels and unmix the fluorescence contributions of elimination and retention in the kidney and liver compartments. Accordingly, the kinetic parameters of the hepatobiliary and renal elimination routes and five major retention sites (the kidneys, liver, bone, spleen, and lung) were investigated in simulations and in an in vivo study. In the latter, the pharmacokinetics of four fluorescently labeled compounds (indocyanine green (ICG), HITC-iodide-microbubbles (MB), Cy7-nanogels (NG), and OsteoSense 750 EX (OS)) were evaluated in BALB/c nude mice. RESULTS: In the simulations, the corrected modeling resulted in lower relative errors and stronger linear relationships (slopes close to 1) between the estimated and simulated parameters, compared to the uncorrected modeling. For the in vivo study, MB and NG showed significantly higher hepatic retention rates (P<0.05 and P<0.05, respectively), while OS had smaller renal and hepatic retention rates (P<0.01 and P<0.01, respectively). Additionally, the bone retention rate of OS was significantly higher (P<0.01). CONCLUSIONS: The mixing matrix correction improves pharmacokinetic modeling and thus enables a more accurate assessment of the biodistribution of fluorescently labeled pharmaceuticals by µCT-FMT.

Comparative Metabolomic Analysis of Dendrobium officinale under Different Cultivation Substrates.

Dendrobium officinale, a precious herbal medicine, has been used for a long time in Chinese history. The metabolites of D. officinale, regarded as its effective components to fight diseases, are significantly affected by cultivation substrates. In this study, ultra-performance liquid chromatography mass spectrometry (UPLC-MS/MS) was conducted to analyze D. officinale stems cultured in three different substrates: pine bark (PB), coconut coir (CC), and a pine bark: coconut coir 1:1 mix (PC). A total of 529 metabolites were identified. Multivariate statistical analysis methods were employed to analyze the difference in the content of metabolites extracted from different groups. By the criteria of variable importance in projection (VIP) value ≥1 and absolute log2 (fold change) ≥1, there were a total of 68, 51, and 57 metabolites, with significant differences in content across groups being filtrated out between PB and PC, PB and CC, and PC and CC, respectively. The comparisons among the three groups revealed that flavonoids were the metabolites that fluctuated most. The results suggested the D. officinale stems from the PB group possessed a higher flavonoid content. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that the significantly regulated metabolites were mainly connected with flavonoid biosynthesis. A comprehensive profile of the metabolic differentiation of D. officinale planted in different substrates was provided, which supports the selection of an optimum cultivation substrate for a higher biomass yield of D. officinale.

Multiparametric evaluation of hindlimb ischemia using time-series indocyanine green fluorescence imaging.

Peripheral arterial disease (PAD) can further cause lower limb ischemia. Quantitative evaluation of the vascular perfusion in the ischemic limb contributes to diagnosis of PAD and preclinical development of new drug. In vivo time-series indocyanine green (ICG) fluorescence imaging can noninvasively monitor blood flow and has a deep tissue penetration. The perfusion rate estimated from the time-series ICG images is not enough for the evaluation of hindlimb ischemia. The information relevant to the vascular density is also important, because angiogenesis is an essential mechanism for post-ischemic recovery. In this paper, a multiparametric evaluation method is proposed for simultaneous estimation of multiple vascular perfusion parameters, including not only the perfusion rate but also the vascular perfusion density and the time-varying ICG concentration in veins. The target method is based on a mathematical model of ICG pharmacokinetics in the mouse hindlimb. The regression analysis performed on the time-series ICG images obtained from a dynamic reflectance fluorescence imaging system. The results demonstrate that the estimated multiple parameters are effective to quantitatively evaluate the vascular perfusion and distinguish hypo-perfused tissues from well-perfused tissues in the mouse hindlimb. The proposed multiparametric evaluation method could be useful for PAD diagnosis. The estimated perfusion rate and vascular perfusion density maps (left) and the time-varying ICG concentration in veins of the ankle region (right) of the normal and ischemic hindlimbs.

Noninvasive Assessment of Elimination and Retention using CT-FMT and Kinetic Whole-body Modeling.

Fluorescence-mediated tomography (FMT) is a quantitative three-dimensional imaging technique for preclinical research applications. The combination with micro-computed tomography (µCT) enables improved reconstruction and analysis. The aim of this study is to assess the potential of µCT-FMT and kinetic modeling to determine elimination and retention of typical model drugs and drug delivery systems. We selected four fluorescent probes with different but well-known biodistribution and elimination routes: Indocyanine green (ICG), hydroxyapatite-binding OsteoSense (OS), biodegradable nanogels (NG) and microbubbles (MB). µCT-FMT scans were performed in twenty BALB/c nude mice (5 per group) at 0.25, 2, 4, 8, 24, 48 and 72 h after intravenous injection. Longitudinal organ curves were determined using interactive organ segmentation software and a pharmacokinetic whole-body model was implemented and applied to compute physiological parameters describing elimination and retention. ICG demonstrated high initial hepatic uptake which decreased rapidly while intestinal accumulation appeared for around 8 hours which is in line with the known direct uptake by hepatocytes followed by hepatobiliary elimination. Complete clearance from the body was observed at 48 h. NG showed similar but slower hepatobiliary elimination because these nanoparticles require degradation before elimination can take place. OS was strongly located in the bones in addition to high signal in the bladder at 0.25 h indicating fast renal excretion. MB showed longest retention in liver and spleen and low signal in the kidneys likely caused by renal elimination or retention of fragments. Furthermore, probe retention was found in liver (MB, NG and OS), spleen (MB) and kidneys (MB and NG) at 72 h which was confirmed by ex vivo data. The kinetic model enabled robust extraction of physiological parameters from the organ curves. In summary, µCT-FMT and kinetic modeling enable differentiation of hepatobiliary and renal elimination routes and allow for the noninvasive assessment of retention sites in relevant organs including liver, kidney, bone and spleen.

Iterative Correction Scheme Based on Discrete Cosine Transform and L1 Regularization for Fluorescence Molecular Tomography With Background Fluorescence.

GOAL: High-intensity background fluorescence is generally encountered in fluorescence molecular tomography (FMT), because of the accumulation of fluorescent probes in nontarget tissues or the existence of autofluorescence in biological tissues. The reconstruction results are affected or even distorted by the background fluorescence, especially when the distribution of fluorescent targets is relatively sparse. The purpose of this paper is to reduce the negative effect of background fluorescence on FMT reconstruction. METHODS: After each iteration of the Tikhonov regularization algorithm, 3-D discrete cosine transform is adopted to filter the intermediate results. And then, a sparsity constraint step based on L1 regularization is applied to restrain the energy of the objective function. RESULTS: Phantom experiments with different fluorescence intensities of homogeneous and heterogeneous background are carried out to validate the performance of the proposed scheme. The results show that the reconstruction quality can be improved with the proposed iterative correction scheme. CONCLUSION AND SIGNIFICANCE: The influence of background fluorescence in FMT can be reduced effectively because of the filtering of the intermediate results, the detail preservation, and noise suppression of L1 regularization.

Reconstruction of fluorophore concentration variation in dynamic fluorescence molecular tomography.

Dynamic fluorescence molecular tomography (DFMT) is a potential approach for drug delivery, tumor detection, diagnosis, and staging. The purpose of DFMT is to quantify the changes of fluorescent agents in the bodies, which offer important information about the underlying physiological processes. However, the conventional method requires that the fluorophore concentrations to be reconstructed are stationary during the data collection period. As thus, it cannot offer the dynamic information of fluorophore concentration variation within the data collection period. In this paper, a method is proposed to reconstruct the fluorophore concentration variation instead of the fluorophore concentration through a linear approximation. The fluorophore concentration variation rate is introduced by the linear approximation as a new unknown term to be reconstructed and is used to obtain the time courses of fluorophore concentration. Simulation and phantom studies are performed to validate the proposed method. The results show that the method is able to reconstruct the fluorophore concentration variation rates and the time courses of fluorophore concentration with relative errors less than 0.0218.

An adaptive support driven reweighted L1-regularization algorithm for fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) is a promising in vivo functional imaging modality in preclinical study. When solving the ill-posed FMT inverse problem, L1 regularization can preserve the details and reduce the noise in the reconstruction results effectively. Moreover, compared with the regular L1 regularization, reweighted L1 regularization is recently reported to improve the performance. In order to realize the reweighted L1 regularization for FMT, an adaptive support driven reweighted L1-regularization (ASDR-L1) algorithm is proposed in this work. This algorithm has two integral parts: an adaptive support estimate and the iteratively updated weights. In the iteratively reweighted L1-minimization sub-problem, different weights are equivalent to different regularization parameters at different locations. Thus, ASDR-L1 can be considered as a kind of spatially variant regularization methods for FMT. Physical phantom and in vivo mouse experiments were performed to validate the proposed algorithm. The results demonstrate that the proposed reweighted L1-reguarization algorithm can significantly improve the performance in terms of relative quantitation and spatial resolution.