Search

Ageing is a critical factor in spinal-cord-associated disorders1, yet the ageing-specific mechanisms underlying this relationship remain poorly understood. Here, to address this knowledge gap, we combined single-nucleus RNA-sequencing analysis with behavioural and neurophysiological analysis in non-human primates (NHPs). We identified motor neuron senescence and neuroinflammation with microglial hyperactivation as intertwined hallmarks of spinal cord ageing. As an underlying mechanism, we identified a neurotoxic microglial state demarcated by elevated expression of CHIT1 (a secreted mammalian chitinase) specific to the aged spinal cords in NHP and human biopsies. In the aged spinal cord, CHIT1-positive microglia preferentially localize around motor neurons, and they have the ability to trigger senescence, partly by activating SMAD signalling. We further validated the driving role of secreted CHIT1 on MN senescence using multimodal experiments both in vivo, using the NHP spinal cord as a model, and in vitro, using a sophisticated system modelling the human motor-neuron–microenvironment interplay. Moreover, we demonstrated that ascorbic acid, a geroprotective compound, counteracted the pro-senescent effect of CHIT1 and mitigated motor neuron senescence in aged monkeys. Our findings provide the single-cell resolution cellular and molecular landscape of the aged primate spinal cord and identify a new biomarker and intervention target for spinal cord degeneration.Motor neuron senescence and neuroinflammation with microglial hyperactivation are intertwined hallmarks of spinal cord ageing. [ABSTRACT FROM AUTHOR]

Background: Maresin-1 plays an important role in diabetic illnesses and ferroptosis is associated with pathogenic processes of diabetic retinopathy (DR). The goal of this study is to explore the influence of maresin-1 on ferroptosis and its molecular mechanism in DR. Methods: ARPE-19 cells were exposed to high glucose (HG) condition for developing a cellular model of DR. The CCK-8 assay and flow cytometry were used to assess ARPE-19 cell proliferation and apoptosis, respectively. Furthermore, the GSH content, MDA content, ROS level, and Fe2+ level were measured by using a colorimetric GSH test kit, a Lipid Peroxidation MDA Assay Kit, a DCFH-DA assay and the phirozine technique, respectively. Immunofluorescence labelling was used to detect protein levels of ACSL4 and PTGS2. Messenger RNA and protein expression of HO-1, GPX4 and Nrf2 was evaluated through western blotting and quantitative real time-polymerase chain reaction (qRT-PCR). To establish a diabetic mouse model, mice were intraperitoneally injected 150 mg/kg streptozotocin. The MDA content, ROS level and the iron level were detected by using corresponding commercial kits. Results: Maresin-1 promoted cell proliferation while reducing the apoptotic process in HG-induced ARPE-19 cells. Maresin-1 significantly reduced ferroptosis induced by HG in ARPE-19 cells, as demonstrated as a result of decreased MDA content, ROS level, Fe2+ level, PTGS2 expression, ACSL4 expression and increased GSH content. With respect to mechanisms, maresin-1 treatment up-regulated the mRNA expression and protein expression of HO-1, GPX4 and Nrf2 in HG-induced ARPE-19 cells. Nrf2 inhibitor reversed the inhibitory effects of maresin-1 on ferroptosis in HG-induced ARPE-19 cells. In vivo experiments, we found that Maresin-1 evidently repressed ferroptosis a mouse model of DR, as evidenced by the decreased MDA content, ROS level and iron level in retinal tissues of mice. Conclusion: Maresin-1 protects ARPE cells from HG-induced ferroptosis via activating the Nrf2/HO-1/GPX4 pathway, suggesting that maresin-1 prevents DR development. [ABSTRACT FROM AUTHOR]

Analysis of primate behavior is crucial for neuroscience research and drug evaluation. Although many methods of automatically recording animal behavior have been proposed, none of them can meet the requirements of both speed and accuracy. In order to implement real-time and high-precision automatic recording of primate behavior, we proposed a novel Joint Detection and Classification (JDC) model to predict the location, identity and actions of monkeys simultaneously. Different from the existing complex non-end-to-end models, our model is the first end-to-end method in this field. In order to explore how to efficiently fuse spatiotemporal information, we constructed the JDC model with a single frame or different fusion approaches. In addition, we collected a new dataset named Spatiotemporal Action Localization of Monkeys in a Group (SALMG), which is the first one containing the location, identity and actions of monkeys in a group. The JDC model with middle fusion approach (JDC-MF) on the SALMG dataset outperforms all compared methods. The F1 score of the JDC-MF is 81.4%, which is 15.3% and 10.6% higher than the Separate Detection and Classification model and the two-stage model, respectively. Moreover, the JDC-MF achieves the highest accuracy of 99.1 % on public Pig Novelty Preference Behavior dataset, which is 4.1% higher than the second-best model. The JDC-MF only takes 0.027 s for a clip on a Nvidia GeForce RTX 2080 Ti. Therefore, the JDC-MF can realize real-time and high-precision spatiotemporal action localization of monkeys, and provide an effective reference scheme for automatic recording and analysis of animal behavior. Code has been made available at: https://github.com/Kewei-Liang/JDC-MF. [ABSTRACT FROM AUTHOR]

Introduction: Currently, it is still controversial to treat stroke with ticagrelor alone. The purpose of our study was to systematically review and analyze the efficacy and safety of ticagrelor on cerebrovascular outcomes in patients with vascular risk factors. Methods: The PubMed, Cochrane Library, and Embase databases were systematically searched using the keywords stroke, ticagrelor, clopidogrel, and aspirin to identify randomized controlled trials (RCTs). Primary outcomes included reported stroke, ischemic stroke, and complex events; the secondary outcome was hemorrhagic stroke. The safety outcomes included major bleeding events, major or minor bleeding, and intracranial bleeding. The pooled odds ratio (OR), hazard ratios (HRs), and 95% confidence interval (CI) were calculated. We used I2 statistics to assess statistical heterogeneity. Results: This meta-analysis included 15 RCTs involving 63,865 patients. Compared to the control group, ticagrelor reduced the risk of stroke (OR: 0.90; 95% CI: 0.81–0.99, p = 0.03; I2 = 3%), ischemic stroke (OR: 0.81; 95% CI: 0.74–0.90, p < 0.0001; I2 = 0%). Ticagrelor was not associated with an increased risk of all-cause mortality (OR: 0.94; 95% CI: 0.84–1.06, p = 0.31; I2 = 62%), major bleeding (OR: 1.06; 95% CI: 0.97–1.15, p = 0.20; I2 = 17%), hemorrhagic strokes (OR: 1.22, 95% CI: 0.76–1.96, p = 0.41; I2 = 0%), and intracranial hemorrhage (OR: 1.06; 95% CI: 0.78–1.43, p = 0.71; I2 = 12%). There was an increased risk of major or minor bleeding with ticagrelor compared to the control group (OR: 1.40; 95% CI: 1.19–1.66, p < 0.0001; I2 = 56%). Additional analyses demonstrated that ticagrelor reduced the risk of incident recurrent stroke (HR: 0.83; 95% CI: 0.75–0.93, p = 0.0009; I2 = 0%), recurrent ischemic stroke (HR: 0.79; 95% CI: 0.71–0.89, p < 0.0001; I2 = 0%) among patients with a history of acute ischemic stroke (AIS) or transient ischemic attack (TIA). There were no significant differences in safety outcomes. Conclusion: Ticagrelor is slightly better than clopidogrel and aspirin in preventing stroke, especially ischemic stroke, with significant safety risks. For patients with a history of AIS/TIA, the use of ticagrelor was superior to the use of clopidogrel or aspirin in reducing the risk of subsequent stroke. We believe that ticagrelor is a potential alternative to aspirin or clopidogrel in some cases, especially for patients with CYP2C19 deficiency. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) has become a common health problem of mankind, and the prevalence and mortality of CVD are rising on a year-to-year basis. Blood pressure (BP) is an important physiological parameter of the human body and also an important physiological indicator for the prevention and treatment of CVD. Existing intermittent measurement methods do not fully indicate the real BP status of the human body and cannot get rid of the restraining feeling of a cuff. Accordingly, this study proposed a deep learning network based on the ResNet34 framework for continuous prediction of BP using only the promising PPG signal. The high-quality PPG signals were first passed through a multi-scale feature extraction module after a series of pre-processing to expand the perceptive field and enhance the perception ability on features. Subsequently, useful feature information was then extracted by stacking multiple residual modules with channel attention to increase the accuracy of the model. Lastly, in the training stage, the Huber loss function was adopted to stabilize the iterative process and obtain the optimal solution of the model. On a subset of the MIMIC dataset, the errors of both SBP and DBP predicted by the model met the AAMI standards, while the accuracy of DBP reached Grade A of the BHS standard, and the accuracy of SBP almost reached Grade A of the BHS standard. The proposed method verifies the potential and feasibility of PPG signals combined with deep neural networks in the field of continuous BP monitoring. Furthermore, the method is easy to deploy in portable devices, and it is more consistent with the future trend of wearable blood-pressure-monitoring devices (e.g., smartphones and smartwatches). [ABSTRACT FROM AUTHOR]

Flexible wearable sweat sensors allow continuous, real-time, noninvasive detection of sweat analytes, provide insight into human physiology at the molecular level, and have received significant attention for their promising applications in personalized health monitoring. Electrochemical sensors are the best choice for wearable sweat sensors due to their high performance, low cost, miniaturization, and wide applicability. Recent developments in soft microfluidics, multiplexed biosensing, energy harvesting devices, and materials have advanced the compatibility of wearable electrochemical sweat-sensing platforms. In this review, we summarize the potential of sweat for medical detection and methods for sweat stimulation and collection. This paper provides an overview of the components of wearable sweat sensors and recent developments in materials and power supply technologies and highlights some typical sensing platforms for different types of analytes. Finally, the paper ends with a discussion of the challenges and a view of the prospective development of this exciting field. [ABSTRACT FROM AUTHOR]

Objective. To review the progress of research on photoplethysmography- (PPG-) based cuffless continuous blood pressure monitoring technologies and prospect the challenges that need to be addressed in the future. Methods. Using Web of Science and PubMed as search engines, the literature on cuffless continuous blood pressure studies using PPG signals in the recent five years were searched. Results. Based on the retrieved literature, this paper describes the available open datasets, commonly used signal preprocessing methods, and model evaluation criteria. Early researches employed multisite PPG signals to calculate pulse wave velocity or time and predicted blood pressure by a simple linear equation. Later, extensive researches were dedicated to mine the features of PPG signals related to blood pressure and regressed blood pressure by machine learning models. Most recently, many researches have emerged to experiment with complex deep learning models for blood pressure prediction with the raw PPG signal as input. Conclusion. This paper summarized the methods in the retrieved literature, provided insight into the artificial intelligence algorithms employed in the literature, and concluded with a discussion of the challenges and opportunities for the development of cuffless continuous blood pressure monitoring technologies. [ABSTRACT FROM AUTHOR]

Objective. Fluorescence molecular tomography (FMT) is a promising non-invasive optical molecular imaging technology with strong specificity and sensitivity that has great potential for preclinical and clinical studies in tumor diagnosis, drug development and therapeutic evaluation. However, the strong scattering of photons and insufficient surface measurements make it very challenging to improve the quality of FMT image reconstruction and its practical application for early tumor detection. Therefore, continuous efforts have been made to explore more effective approaches or solutions in the pursuit of high-quality FMT reconstructions. Approach. This review takes a comprehensive overview of advances in imaging methodology for FMT, mainly focusing on two critical issues in FMT reconstructions: improving the accuracy of solving the forward physical model and mitigating the ill-posed nature of the inverse problem from a methodological point of view. More importantly, numerous impressive and practical strategies and methods for improving the quality of FMT reconstruction are summarized. Notably, deep learning methods are discussed in detail to illustrate their advantages in promoting the imaging performance of FMT thanks to large datasets, the emergence of optimized algorithms and the application of innovative networks. Main results. The results demonstrate that the imaging quality of FMT can be effectively promoted by improving the accuracy of optical parameter modeling, combined with prior knowledge, and reducing dimensionality. In addition, the traditional regularization-based methods and deep neural network-based methods, especially end-to-end deep networks, can enormously alleviate the ill-posedness of the inverse problem and improve the quality of FMT image reconstruction. Significance. This review aims to illustrate a variety of effective and practical methods for the reconstruction of FMT images that may benefit future research. Furthermore, it may provide some valuable research ideas and directions for FMT in the future, and could promote, to a certain extent, the development of FMT and other methods of optical tomography. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality on a global scale, and the development of accurate detection and imaging methods for HCC cells is urgently needed. Herein, by connecting peptide L5, which can specifically bind to the overexpressed Glypican-3 (GPC-3) protein of HCC cells with aggregation-induced emission (AIE) moiety ammonium cation-functionalized 9,10-distyrylanthracene (NDSA) via the "click" reaction, we synthesized a fluorescent probe NDSA-L5. In an aqueous solution, the probe shows weak emission, whereas, in the presence of the GPC-3 protein, bright fluorescence can be obtained since NDSA-L5 binds to the GPC-3 protein, leading to the restricted intramolecular movement of AIE-active NDSA-L5. The imaging and flow cytometry experiments demonstrate that the NDSA-L5 probe can rapidly accumulate in the subcutaneous HCC cells and liver tumor tissue and shows a potential application in early detection and surgical navigation for HCC cancer. [ABSTRACT FROM AUTHOR]

Craniopharyngioma is a congenital brain tumor with clinical characteristics of hypothalamic-pituitary dysfunction, increased intracranial pressure, and visual field disorder, among other injuries. Its clinical diagnosis mainly depends on radiological examinations (such as Computed Tomography, Magnetic Resonance Imaging). However, assessing numerous radiological images manually is a challenging task, and the experience of doctors has a great influence on the diagnosis result. The development of artificial intelligence has brought about a great transformation in the clinical diagnosis of craniopharyngioma. This study reviewed the application of artificial intelligence technology in the clinical diagnosis of craniopharyngioma from the aspects of differential classification, prediction of tissue invasion and gene mutation, prognosis prediction, and so on. Based on the reviews, the technical route of intelligent diagnosis based on the traditional machine learning model and deep learning model were further proposed. Additionally, in terms of the limitations and possibilities of the development of artificial intelligence in craniopharyngioma diagnosis, this study discussed the attentions required in future research, including few-shot learning, imbalanced data set, semi-supervised models, and multi-omics fusion. [ABSTRACT FROM AUTHOR]

Objectives: To explore the MRI-based differential diagnosis of deep learning with data enhancement for cerebral glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and tumefactive demyelinating lesion (TDL). Materials and Methods: This retrospective study analyzed the MRI data of 261 patients with pathologically diagnosed solitary and multiple cerebral GBM (n = 97), PCNSL (n = 92), and TDL (n = 72). The 3D segmentation model was trained to capture the lesion. Different enhancement data were generated by changing the pixel ratio of the lesion and non-lesion areas. The 3D classification network was trained by using the enhancement data. The accuracy, sensitivity, specificity, and area under the curve (AUC) were used to assess the value of different enhancement data on the discrimination performance. These results were then compared with the neuroradiologists' diagnoses. Results: The diagnostic performance fluctuated with the ratio of lesion to non-lesion area changed. The diagnostic performance was best when the ratio was 1.5. The AUCs of GBM, PCNSL, and TDL were 1.00 (95% confidence interval [CI]: 1.000–1.000), 0.96 (95% CI: 0.923–1.000), and 0.954 (95% CI: 0.904–1.000), respectively. Conclusions: Deep learning with data enhancement is useful for the accurate identification of GBM, PCNSL, and TDL, and its diagnostic performance is better than that of the neuroradiologists. [ABSTRACT FROM AUTHOR]

Purpose: Magnetoacoustic tomography with magnetic induction (MAT‐MI) is a technique that utilizes the acoustic signals induced by magnetic stimulation to reconstruct the electrical impedance distribution in biological tissues. Most algorithms ignored the fact that acoustic properties in human tissues are heterogeneous, which lead to distortion and blurring of small reconstructed objects. In this study, a novel algorithm is proposed for exact reconstruction of the sound source distribution in acoustic heterogeneous tissues. Methods: Based on the ring transducer array, we develop an algorithm which combines algebraic reconstruction technique (ART) and time reversal method. Different to existing reconstruction methods, the ultrasonic transmission tomography (UTT) and the MAT‐MI can be completed in same system, which decreases the system complexity. The sound velocity distribution is reconstructed with the ART so that the propagation time of the magnetoacoustic signals in the heterogeneous tissue is corrected. And then, the sound source image is reconstructed based on the time reversal method from new sound pressure data. Both numerical simulations and phantom experiments are established to validate the proposed method. Results: Compared with the results without consideration of the variation on acoustic speed, sound sources reconstructed by our method are more consistent with the model in terms of size and shape. Conclusions: The novel algorithm can be used to reconstruct the high‐accuracy image of MAT‐MI sound source in the sound velocity inhomogeneous media. In addition, this method is applicable to scenarios that the prior knowledge of the imaging targets is unknown. The signal acquisition time of MAT‐MI in acoustically heterogeneity media is greatly reduced due to the introduction of ring transducer array into the imaging system. Therefore, our method will promote the application of MAT‐MI in noninvasive early diagnosis of tumor for preclinical study. [ABSTRACT FROM AUTHOR]

Our understanding of how aging affects the cellular and molecular components of the vasculature and contributes to cardiovascular diseases is still limited. Here we report a single-cell transcriptomic survey of aortas and coronary arteries in young and old cynomolgus monkeys. Our data define the molecular signatures of specialized arteries and identify eight markers discriminating aortic and coronary vasculatures. Gene network analyses characterize transcriptional landmarks that regulate vascular senility and position FOXO3A, a longevity-associated transcription factor, as a master regulator gene that is downregulated in six subtypes of monkey vascular cells during aging. Targeted inactivation of FOXO3A in human vascular endothelial cells recapitulates the major phenotypic defects observed in aged monkey arteries, verifying FOXO3A loss as a key driver for arterial endothelial aging. Our study provides a critical resource for understanding the principles underlying primate arterial aging and contributes important clues to future treatment of age-associated vascular disorders. Arterial degeneration, closely associated with cardiovascular diseases, is driven by aging-related vascular cell-specific transcriptomics changes. This study provides a single-cell transcriptomic atlas for senile aortic and coronary arteries and underscores FOXO3A-based the transcriptional network in vasoprotection during aging. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer (PCa) is a common malignant tumor of the urinary system in males. LncRNA taurine-upregulated gene 1 (TUG1) has been verified to play a crucial role in progression and prognosis of PCa. However, the functional mechanism of TUG1 remains unclear with radiosensitivity of PCa. Methods: Quantitative real-time PCR (qRT-PCR) was conducted to measure the transcription levels of genes. 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay and flow cytometry analysis were employed to assess cell proliferation and apoptosis, respectively. Moreover, colony formation assay was used to measure colony survival. Western blot was performed to detect the relative proteins expression. The interaction among variables was predicted by online tool starbase, and then confirmed using the dual luciferase reporter assay. A xenograft mouse model was constructed to investigate the effect of TUG1 on tumor growth in vivo. Results: The levels of lncRNA TUG1 and SMC1A were remarkably increased, while miR-139-5p was downregulated in PCa. Patients with high expression of TUG1 showed a lower survival rate and poor prognosis. Knockdown of TUG1 inhibited PCa cell proliferation and colony survival fraction, and promoted apoptosis. Downregulation of miR-139-5p reversed the effects of TUG1 deletion on proliferation, apoptosis and colony survival fraction in PCa cells treated with 4 Gy of X-ray radiation. Moreover, TUG1 sponged miR-139-5p to regulate SMC1A expression. SMC1A deletion blocked the effects of TUG1 on the progression of PCa cells treated with 4 Gy of X-ray radiation. The tumor volume and weight were illustriously reduced with radiation and TUG1 silencing in xenograft model. Conclusion: Knockdown of lncRNA TUG1 enhanced radiosensitivity in PCa via the TUG1/miR-139-5p/SMC1A axis. It may become a promising target for PCa treatment. [ABSTRACT FROM AUTHOR]

Fluorescence molecular tomography (FMT), as a powerful imaging technique in preclinical research, can offer the three-dimensional distribution of biomarkers by detecting the fluorescently labelled probe noninvasively. However, because of the light scattering effect and the ill-pose of inverse problem, it is challenging to develop an efficient reconstruction method, which can provide accurate location and morphology of the fluorescence distribution. In this research, we proposed a novel adaptive Gaussian weighted Laplace prior (AGWLP) regularization method, which assumed the variance of fluorescence intensity between any two voxels had a non-linear correlation with their Gaussian distance. It utilized an adaptive Gaussian kernel parameter strategy to achieve accurate morphological reconstructions in FMT. To evaluate the performance of the AGWLP method, we conducted numerical simulation and in vivo experiments. The results were compared with fast iterative shrinkage (FIS) thresholding method, split Bregman-resolved TV (SBRTV) regularization method, and Gaussian weighted Laplace prior (GWLP) regularization method. We validated in vivo imaging results against planar fluorescence images of frozen sections. The results demonstrated that the AGWLP method achieved superior performance in both location and shape recovery of fluorescence distribution. This enabled FMT more suitable and practical for in vivo visualization of biomarkers. [ABSTRACT FROM AUTHOR]

High-quality multimodal imaging requires exogenous contrast agents with high sensitivity, spatial–temporal resolution, and high penetration depth for the accurate diagnosis and surveillance of cancer. Herein, we design a highly efficient fluorescent and magnetic multimodal probe by doping fluorescent molecule 2-(4-bromophenyl)-3-(4-(4-(diphenylamino)styryl)phenyl)fumaronitrile (TB) with near-infrared (NIR) fluorescent emission (714 nm) and superparamagnetic iron oxide (SPIO) into a polystyrene-polyethylene glycol (PS-PEG) matrix to form TB/SPIO@PS-PEG nanoparticles (TSP NPs). The as-prepared TSP NPs exhibit red aggregation-induced emission (AIE) with a maximum wavelength at 655 nm and high fluorescence quantum yield (QY) of 14.6%, facilitating the improvement of sensitivity and signal-to-background ratio for fluorescence molecular imaging (FMI). Phase behavior investigation of the TB/SPIO@PS-PEG probe system by Flory–Huggins lattice theory elucidates the highly efficient fluorescence of the multimodal probe, originating from the poor miscibility between TB and SPIO. Meanwhile, the TSP NPs possess good superparamagnetism and relaxivity and can thus be used as appropriate magnetic contrast agents for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI). In addition, the good biocompatibility and photostability of the TSP NPs make them suitable for long-term monitoring. In vivo fluorescence imaging results indicate that the TSP NPs can facilitate monitoring of subcutaneous tumor growth for more than 24 days in a real-time manner. Multimodal imaging consisting of FMI, MRI, and MPI reveals that TSP NPs can monitor a liver tumor in situ with almost unlimited depth in tissues and high temporal–spatial resolution. As a multimodal probe, the TSP NPs manifest obvious synergistic advantages of long-term monitoring and high penetration depth and hold great prospects in tumor imaging. [ABSTRACT FROM AUTHOR]

The last couple of decades have seen brilliant progress in stem cell therapies, including native, genetically modified, and engineered stem cells, for osteonecrosis of the femoral head (ONFH). In vitro studies evaluate the effect of endogenous or exogenous factor or gene regulation on osteogenic phenotype maintenance and/or differentiation towards osteogenic lineage. The preclinical and clinical outcomes accelerate the clinical translation. Bone marrow mesenchymal stem cells and adipose-derived stem cells have demonstrated better effects in the treatment of femoral head necrosis. Various materials have been used widely in the ONFH treatment in both preclinical and clinical trials. In a word, in vivo and multiscale efforts are expected to overcome obstacles in the approaches for treating ONFH and provide clinical relevance and commercial strategies in the future. Therefore, we will discuss the above aspects in this paper and present our opinions. [ABSTRACT FROM AUTHOR]

Fluorescence molecular tomography (FMT), as a promising imaging modality in preclinical research, can obtain the three-dimensional (3-D) position information of the stem cell in mice. However, because of the ill-posed nature and sensitivity to noise of the inverse problem, it is a challenge to develop a robust reconstruction method, which can accurately locate the stem cells and define the distribution. In this paper, we proposed a sparsity adaptive correntropy matching pursuit (SACMP) method. SACMP method is independent on the noise distribution of measurements and it assigns small weights on severely corrupted entries of data and large weights on clean ones adaptively. These properties make it more suitable for in vivo experiment. To analyze the performance in terms of robustness and practicability of SACMP, we conducted numerical simulation and in vivo mice experiments. The results demonstrated that the SACMP method obtained the highest robustness and accuracy in locating stem cells and depicting stem cell distribution compared with stagewise orthogonal matching pursuit and sparsity adaptive subspace pursuit reconstruction methods. To the best of our knowledge, this is the first study that acquired such accurate and robust FMT distribution reconstruction for stem cell tracking in mice brain. This promotes the application of FMT in locating stem cell and distribution reconstruction in practical mice brain injury models. [ABSTRACT FROM AUTHOR]

Tumor cell complete extinction is a crucial measure to evaluate antitumor efficacy. The difficulties in defining tumor margins and finding satellite metastases are the reason for tumor recurrence. A synergistic method based on multimodality molecular imaging needs to be developed so as to achieve the complete extinction of the tumor cells. In this study, graphene oxide conjugated with gold nanostars and chelated with Gd through 1,4,7,10-tetraazacyclododecane-N,N′,N,N′-tetraacetic acid (DOTA) (GO-AuNS-DOTA-Gd) were prepared to target HCC-LM3-fLuc cells and used for therapy. For subcutaneous tumor, multimodality molecular imaging including photoacoustic imaging (PAI) and magnetic resonance imaging (MRI) and the related processing techniques were used to monitor the pharmacokinetics process of GO-AuNS-DOTA-Gd in order to determine the optimal time for treatment. For orthotopic tumor, MRI was used to delineate the tumor location and margin in vivo before treatment. Then handheld photoacoustic imaging system was used to determine the tumor location during the surgery and guided the photothermal therapy. The experiment result based on orthotopic tumor demonstrated that this synergistic method could effectively reduce tumor residual and satellite metastases by 85.71% compared with the routine photothermal method without handheld PAI guidance. These results indicate that this multimodality molecular imaging-guided photothermal therapy method is promising with a good prospect in clinical application. [ABSTRACT FROM AUTHOR]

Abstract: Renal‐clearable nanoparticles have made it possible to overcome the toxicity by nonspecific accumulation in healthy tissues/organs due to their highly efficient clearance characteristics. However, their tumor uptake is relatively low due to the short blood circulation time and rapid body elimination. Here, this problem is addressed by developing renal‐clearable nanoparticles by controlled coating of sub‐6 nm CuS nanodots (CuSNDs) on doxorubicin ladened mesoporous silica nanoparticles (pore size ≈6 nm) for multimodal application. High tumor uptake of the as‐synthesized nanoparticles (abbreviated as MDNs) is achieved due to the longer blood circulation time. The MDNs also show excellent performance in bimodal imaging. Moreover, the MDNs demonstrated a photothermally sensitive drug release and pronounced synergetic effects of chemo‐photothermal therapy, which were confirmed by two different tumor models in vivo. A novel key feature of the proposed synthesis is the use of renal‐clearable CuSNDs and biodegradable mesoporous silica nanoparticles which also are renal‐clearable after degradation. Therefore, the MDNs would be rapidly degraded and excreted in a reasonable period in living body and avoid long‐term toxicity. Such biodegradable and clearable single‐compartment theranostic agents applicable in highly integrated multimodal imaging and multiple therapeutic functions may have substantial potentials in clinical practice. [ABSTRACT FROM AUTHOR]

The primate frontal lobe (FL) is sensitive to aging-related neurocognitive decline. However, the aging-associated molecular mechanisms remain unclear. Here, using physiologically aged non-human primates (NHPs), we depicted a comprehensive landscape of FL aging with multidimensional profiling encompassing bulk and single-nucleus transcriptomes, quantitative proteome, and DNA methylome. Conjoint analysis across these molecular and neuropathological layers underscores nuclear lamina and heterochromatin erosion, resurrection of endogenous retroviruses (ERVs), activated pro-inflammatory cyclic GMP-AMP synthase (cGAS) signaling, and cellular senescence in post-mitotic neurons of aged NHP and human FL. Using human embryonic stem-cell-derived neurons recapitulating cellular aging in vitro , we verified the loss of B-type lamins inducing resurrection of ERVs as an initiating event of the aging-bound cascade in post-mitotic neurons. Of significance, these aging-related cellular and molecular changes can be alleviated by abacavir, a nucleoside reverse transcriptase inhibitor, either through direct treatment of senescent human neurons in vitro or oral administration to aged mice. [Display omitted] • Multi-omics profiling of primate frontal lobe (FL) aging • Neuronal-specific nuclear lamina erosion as a hallmark and driver of FL aging • Consequent ERV activation induces neuronal senescence and inflammation • The NRT inhibitor mitigates human neuronal senescence and mouse brain aging Zhang et al. establish a granular view of the molecular alterations underlying primate FL aging through multi-omics profiling, neuropathological examination, and in vitro modeling. It reveals that, during neuronal aging, nuclear lamina erosion induces the reactivation of ERVs and contributes to neuronal degeneration. [ABSTRACT FROM AUTHOR]

Optical molecular imaging has been rapidly developed to noninvasively visualize in vivo physiological and pathological processes involved in normal and suffering organisms at the cellular and molecular levels, in which advanced optical imaging technology and modern molecular biology are being combined to provide a state-of-the-art tool for preclinical biomedical research. Among optical molecular imaging modalities, bioluminescence tomography (BLT) has experienced considerable growth and attracted much attention in recent years for its excellent performance, unique advantages, and high cost-effectiveness. This article focuses on the genesis and development of BLT, especially for its computational methodology, imaging system, and biomedical application. An overview of the advantages and challenges of the conventional planar bioluminescence imaging technique is first described in comparison with currently available molecular imaging modalities. The imaging algorithms for inverse source reconstruction are classified and summarized according to different a priori knowledge, followed by a simple depiction of the uniqueness theorems of BLT solution. Diverse imaging systems for obtaining three-dimensional quantitative information of internal bioluminescent sources are then reviewed. The latest application examples of BLT in tumor study and drug discovery are introduced and compared with other mature imaging technologies. Finally, the paper is concluded and an attractive prospect for BLT is predicted. [ABSTRACT FROM AUTHOR]

As a novel molecular imaging technology, bioluminescence tomography (BLT) has become an important tool for biomedical research in recent years, which can perform a quantitative reconstruction of an internal light source distribution with the scattered and transmitted bioluminescent signals measured on the external surface of a small animal. However, BLT is severely ill-posed because of complex photon propagation in the biological tissue and limited boundary measured data with noise. Therefore, sufficient a priori knowledge should be fused for the uniqueness and stability of BLT solution. Permissible source region strategy and spectrally resolved measurements are two kinds of a priori knowledge commonly used in BLT reconstruction. This paper compares their performance with simulation and in vivo heterogeneous mouse experiments. In order to improve the efficiency of large-scale source restoration, this paper introduces an efficient iterative shrinkage thresholding method that not only has faster convergence rate but also has better reconstruction accuracy than the modified Newton-type optimization approach. Finally, a discussion of these two kinds of a priori knowledge is given based on the comparison results. (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

A correction to the article "Recent advances in bioluminescence tomography: methodology and system as well as application" by Chenghu Qin and colleagues, that was published in the August 8, 2012 issue is presented.