Multiplexed stimulated emission depletion nanoscopy(mSTED)for 5-color live-cell long-term imaging of organelle interactome

Stimulated emission depletion microscopy(STED)holds great potential in biological science applications,especially in studying nanoscale subcellular structures.However,multi-color STED imaging in live-cell remains challenging due to the limited excitation wavelengths and large amount of laser radiation.Here,we develop a multiplexed live-cell STED method to observe more structures simultaneously with limited photo-bleaching and photo-cytotoxicity.By separating live-cell fluorescent probes with similar spectral properties using phasor analysis,our method enables five-color live-cell STED imaging and reveals long-term interactions between different subcellular structures.The results here provide an avenue for understanding the complex and delicate interactome of subcellular structures in live-cell.

MACS-W:A modified optical clearing agent for imaging 3D cell cultures

Three-dimensional(3D)cell cultures have contributed to a variety of biological research fields by filling the gap between monolayers and animal models.The modern optical sectioning microscopic methods make it possible to probe the complexity of 3D cell cultures but are limited by the inherent opaqueness.While tissue optical clearing methods have emerged as powerful tools for investigating whole-mount tissues in 3D,they often have limitations,such as being too harsh for fragile 3D cell cultures,requiring complex handling protocols,or inducing tissue deformation with shrinkage or expansion.To address this issue,we proposed a modified optical clearing method for 3D cell cultures,called MACS-W,which is simple,highly efficient,and morphology-preserving.In our evaluation of MACS-W,we found that it exhibits excellent clearing capability in just 10 min,with minimal deformation,and helps drug evaluation on tumor spheroids.In summary,MACS-W is a fast,minimally-deformative and fluorescence compatible clearing method that has the potential to be widely used in the studies of 3D cell cultures.

Multimodal imaging in the diagnosis of bone giant cell tumors:A retrospective study

BACKGROUND Giant cell tumor of bone is a locally aggressive and rarely metastasizing tumor,and also a potential malignant tumor that may develop into a primary malignant giant cell tumor.AIM To evaluate the role of multimodal imaging in the diagnosis of giant cell tumors of bone.METHODS The data of 32 patients with giant cell tumor of bone confirmed by core-needle biopsy or surgical pathology at our hospital between March 2018 and March 2023 were retrospectively selected.All the patients with giant cell tumors of the bone were examined by X-ray,computed tomography(CT)and magnetic resonance imaging(MRI),and 7 of them were examined by positron emission tomography(PET)-CT.RESULTS X-ray imaging can provide overall information on giant cell tumor lesions.CT and MRI can reveal the characteristics of the internal structure of the tumor as well as the adjacent relationships of the tumor,and these methods have unique advantages for diagnosing tumors and determining the scope of surgery.PET-CT can detect small lesions and is highly valuable for identifying benign and malignant tumors to aid in the early diagnosis of metastasis.CONCLUSION Multimodal imaging plays an important role in the diagnosis of giant cell tumor of bone and can provide a reference for the treatment of giant cell tumors.

Medical imaging for the diagnosis,recurrence and metastasis evaluation of clear cell sarcoma

Clear cell sarcoma(CCS)of soft tissue is extremely rare,accounting for approximately 1%of all soft tissue tumours.It is very difficult to diagnose CCS based on clinical manifestations.Magnetic resonance imaging(MRI)provides highresolution images of soft tissues and pathological features such as mucus,necrosis,bleeding,and fat through high and low signals on T1 weighted image(T1WI)and T2 weighted image(T2WI).On the other hand,the paramagnetism of melanin in CCS shortens the relaxation time of T1 and T2,and high signal intensity on T1WI and low signal intensity on T2WI can be found.This is different from most other soft tissue sarcomas.At present,the treatment method for CCS is surgical resection.MRI can effectively display the tumour edge,extent of surrounding oedema,and extent of fat involvement,which is highly important for guiding surgical resection and predicting postoperative recurrence.As an invasive sarcoma,CCS has a high risk of metastasis.Regardless of the pathological condition of the resected tumour,MRI or computed tomography(CT)should be performed every 1-2 years to assess recurrence at the primary site and to screen for metastasis in the lungs,liver,and bones.If necessary,PET-CT can be performed to evaluate the overall condition of the patient.

Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging

BACKGROUND The liver imaging reporting and data system(LI-RADS)diagnostic table has 15 cells and is too complex.The diagnostic performance of LI-RADS for hepatocellular carcinoma(HCC)is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging(EOB-MRI).AIM To evaluate the ability of the simplified LI-RADS(sLI-RADS)to diagnose HCC on EOB-MRI.METHODS A total of 331 patients with 356 hepatic observations were retrospectively analysed.The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLIRADS.The algorithms of sLI-RADS A-D are as follows:The single threshold for sLI-RADS A and B was 10 mm,that is,classified observations≥10mm using an algorithm of 10-19 mm observations(sLI-RADS A)and≥20 mm observations(sLI-RADS B)in the diagnosis table of LI-RADS v2018,respectively,while the classification algorithm remained unchanged for observations<10 mm;the single threshold for sLI-RADS C and D was 20 mm,that is,for<20 mm observations,the algorithms for<10 mm observations(sLI-RADS C)and 10-19 mm observations(sLI-RADS D)were used,respectively,while the algorithm remained unchanged for observations≥20 mm.With hepatobiliary phase(HBP)hypointensity as a major feature(MF),the final sLI-RADS(F-sLI-RADS)was formed according to the optimal sLI-RADS,and its diagnostic performance was evaluated.The times needed to classify the observations according to F-sLIRADS and LI-RADS v2018 were compared.RESULTS The optimal sLI-RADS was sLI-RADS D(with a single threshold of 20 mm),because its sensitivity was greater than that of LI-RADS v2018(89.8%vs 87.0%,P=0.031),and its specificity was not lower(89.4%vs 90.1%,P>0.999).With HBP hypointensity as an MF,the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018(93.0%vs 87.0%,P<0.001)and sLI-RADS D(93.0%vs 89.8%,P=0.016),without a lower specificity(86.5%vs 90.1%,P=0.062;86.5%vs 89.4%,P=0.125).Compared with that of LI-RADS v2018,the time to classify lesions according to FsLI-RADS was shorter(51±21 s vs 73±24 s,P<0.001).CONCLUSION The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.

Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma:A quantitative review with Radiomics Quality Score

BACKGROUND Radiomics is a promising tool that may increase the value of magnetic resonance imaging(MRI)for different tasks related to the management of patients with hepatocellular carcinoma(HCC).However,its implementation in clinical practice is still far,with many issues related to the methodological quality of radiomic studies.AIM To systematically review the current status of MRI radiomic studies concerning HCC using the Radiomics Quality Score(RQS).METHODS A systematic literature search of PubMed,Google Scholar,and Web of Science databases was performed to identify original articles focusing on the use of MRI radiomics for HCC management published between 2017 and 2023.The methodological quality of radiomic studies was assessed using the RQS tool.Spearman’s correlation(ρ)analysis was performed to explore if RQS was correlated with journal metrics and characteristics of the studies.The level of statistical significance was set at P<0.05.RESULTS One hundred and twenty-seven articles were included,of which 43 focused on HCC prognosis,39 on prediction of pathological findings,16 on prediction of the expression of molecular markers outcomes,18 had a diagnostic purpose,and 11 had multiple purposes.The mean RQS was 8±6.22,and the corresponding percentage was 24.15%±15.25%(ranging from 0.0% to 58.33%).RQS was positively correlated with journal impact factor(IF;ρ=0.36,P=2.98×10^(-5)),5-years IF(ρ=0.33,P=1.56×10^(-4)),number of patients included in the study(ρ=0.51,P<9.37×10^(-10))and number of radiomics features extracted in the study(ρ=0.59,P<4.59×10^(-13)),and time of publication(ρ=-0.23,P<0.0072).CONCLUSION Although MRI radiomics in HCC represents a promising tool to develop adequate personalized treatment as a noninvasive approach in HCC patients,our study revealed that studies in this field still lack the quality required to allow its introduction into clinical practice.

Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma:Retrospective study

BACKGROUND Despite continuous changes in treatment methods,the survival rate for advanced hepatocellular carcinoma(HCC)patients remains low,highlighting the importance of diagnostic methods for HCC.AIM To explore the efficacy of texture analysis based on multi-parametric magnetic resonance(MR)imaging(MRI)in predicting microvascular invasion(MVI)in preoperative HCC.METHODS This study included 105 patients with pathologically confirmed HCC,categorized into MVI-positive and MVI-negative groups.We employed Original Data Analysis,Principal Component Analysis,Linear Discriminant Analysis(LDA),and Non-LDA(NDA)for texture analysis using multi-parametric MR images to predict preoperative MVI.The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software,with results expressed as the misjudgment rate(MCR).RESULTS Texture analysis using multi-parametric MRI,particularly the MI+PA+F dimensionality reduction method combined with NDA discrimination,demonstrated the most effective prediction of MVI in HCC.Prediction accuracy in the pulse and equilibrium phases was 83.81%.MCRs for the combination of T2-weighted imaging(T2WI),arterial phase,portal venous phase,and equilibrium phase were 22.86%,16.19%,20.95%,and 20.95%,respectively.The area under the curve for predicting MVI positivity was 0.844,with a sensitivity of 77.19%and specificity of 91.67%.CONCLUSION Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI,portal venous,and equilibrium phases.This study provides an objective,non-invasive method for preoperative prediction of MVI,offering a theoretical foundation for the selection of clinical therapy.

Data augmentation of ultrasound imaging for non-invasive white blood cell in vitro peritoneal dialysis

The limited amount of data in the healthcare domain and the necessity of training samples for increased performance of deep learning models is a recurrent challenge,especially in medical imaging.Newborn Solutions aims to enhance its non-invasive white blood cell counting device,Neosonics,by creating synthetic in vitro ultrasound images to facilitate a more efficient image generation process.This study addresses the data scarcity issue by designing and evaluating a continuous scalar conditional Generative Adversarial Network(GAN)to augment in vitro peritoneal dialysis ultrasound images,increasing both the volume and variability of training samples.The developed GAN architecture incorporates novel design features:varying kernel sizes in the generator’s transposed convolutional layers and a latent intermediate space,projecting noise and condition values for enhanced image resolution and specificity.The experimental results show that the GAN successfully generated diverse images of high visual quality,closely resembling real ultrasound samples.While visual results were promising,the use of GAN-based data augmentation did not consistently improve the performance of an image regressor in distinguishing features specific to varied white blood cell concentrations.Ultimately,while this continuous scalar conditional GAN model made strides in generating realistic images,further work is needed to achieve consistent gains in regression tasks,aiming for robust model generalization.

Pre-operative enhanced magnetic resonance imaging combined with clinical features predict early recurrence of hepatocellular carcinoma after radical resection

BACKGROUND Indentifying predictive factors for postoperative recurrence of hepatocellular carcinoma(HCC)has great significance for patient prognosis.AIM To explore the value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced magnetic resonance imaging(MRI)combined with clinical features in predicting early recurrence of HCC after resection.METHODS A total of 161 patients with pathologically confirmed HCC were enrolled.The patients were divided into early recurrence and non-early recurrence group based on the follow-up results.The clinical,laboratory,pathological results and Gd-EOB-DTPA enhanced MRI imaging features were analyzed.RESULTS Of 161 patients,73 had early recurrence and 88 were had non-early recurrence.Univariate analysis showed that patient age,gender,serum alpha-fetoprotein level,the Barcelona Clinic Liver Cancer stage,China liver cancer(CNLC)stage,microvascular invasion(MVI),pathological satellite focus,tumor size,tumor number,tumor boundary,tumor capsule,intratumoral necrosis,portal vein tumor thrombus,large vessel invasion,nonperipheral washout,peritumoral enhancement,hepatobiliary phase(HBP)/tumor signal intensity(SI)/peritumoral SI,HBP peritumoral low signal and peritumoral delay enhancement were significantly associated with early recurrence of HCC after operation.Multivariate logistic regression analysis showed that patient age,MVI,CNLC stage,tumor boundary and large vessel invasion were independent predictive factors.External data validation indicated that the area under the curve of the combined predictors was 0.861,suggesting that multivariate logistic regression was a reasonable predictive model for early recurrence of HCC.CONCLUSION Gd-EOB-DTPA enhanced MRI combined with clinical features would help predicting the early recurrence of HCC after operation.

Nomogram prediction of vessels encapsulating tumor clusters in small hepatocellular carcinoma≤3 cm based on enhanced magnetic resonance imaging

BACKGROUND Vessels encapsulating tumor clusters(VETC)represent a recently discovered vascular pattern associated with novel metastasis mechanisms in hepatocellular carcinoma(HCC).However,it seems that no one have focused on predicting VETC status in small HCC(sHCC).This study aimed to develop a new nomogram for predicting VETC positivity using preoperative clinical data and image features in sHCC(≤3 cm)patients.AIM To construct a nomogram that combines preoperative clinical parameters and image features to predict patterns of VETC and evaluate the prognosis of sHCC patients.METHODS A total of 309 patients with sHCC,who underwent segmental resection and had their VETC status confirmed,were included in the study.These patients were recruited from three different hospitals:Hospital 1 contributed 177 patients for the training set,Hospital 2 provided 78 patients for the test set,and Hospital 3 provided 54 patients for the validation set.Independent predictors of VETC were identified through univariate and multivariate logistic analyses.These independent predictors were then used to construct a VETC prediction model for sHCC.The model’s performance was evaluated using the area under the curve(AUC),calibration curve,and clinical decision curve.Additionally,Kaplan-Meier survival analysis was performed to confirm whether the predicted VETC status by the model is associated with early recurrence,just as it is with the actual VETC status and early recurrence.RESULTS Alpha-fetoprotein_lg10,carbohydrate antigen 199,irregular shape,non-smooth margin,and arterial peritumoral enhancement were identified as independent predictors of VETC.The model incorporating these predictors demonstrated strong predictive performance.The AUC was 0.811 for the training set,0.800 for the test set,and 0.791 for the validation set.The calibration curve indicated that the predicted probability was consistent with the actual VETC status in all three sets.Furthermore,the decision curve analysis demonstrated the clinical benefits of our model for patients with sHCC.Finally,early recurrence was more likely to occur in the VETC-positive group compared to the VETC-negative group,regardless of whether considering the actual or predicted VETC status.CONCLUSION Our novel prediction model demonstrates strong performance in predicting VETC positivity in sHCC(≤3 cm)patients,and it holds potential for predicting early recurrence.This model equips clinicians with valuable information to make informed clinical treatment decisions.

Omics-imaging signature-based nomogram to predict the progression-free survival of patients with hepatocellular carcinoma after transcatheter arterial chemoembolization

BACKGROUND Enhanced magnetic resonance imaging(MRI)is widely used in the diagnosis,treatment and prognosis of hepatocellular carcinoma(HCC),but it can not effectively reflect the heterogeneity within the tumor and evaluate the effect after treatment.Preoperative imaging analysis of voxel changes can effectively reflect the internal heterogeneity of the tumor and evaluate the progression-free survival(PFS).AIM To predict the PFS of patients with HCC before operation by building a model with enhanced MRI images.METHODS Delineate the regions of interest(ROI)in arterial phase,portal venous phase and delayed phase of enhanced MRI.After extracting the combinatorial features of ROI,the features are fused to obtain deep learning radiomics(DLR)_Sig.DeLong's test was used to evaluate the diagnostic performance of different typological features.K-M analysis was applied to assess PFS in different risk groups,and the discriminative ability of the model was evaluated using the Cindex.RESULTS Tumor diameter and diolame were independent factors influencing the prognosis of PFS.Delong's test revealed multi-phase combined radiomic features had significantly greater area under the curve values than did those of the individual phases(P<0.05).In deep transfer learning(DTL)and DLR,significant differences were observed between the multi-phase and individual phases feature sets(P<0.05).K-M survival analysis revealed a median survival time of high risk group and low risk group was 12.8 and 14.2 months,respectively,and the predicted probabilities of 6 months,1 year and 2 years were 92%,60%,40%and 98%,90%,73%,respectively.The C-index was 0.764,indicating relatively good consistency between the predicted and observed results.DTL and DLR have higher predictive value for 2-year PFS in nomogram.CONCLUSION Based on the multi-temporal characteristics of enhanced MRI and the constructed Nomograph,it provides a new strategy for predicting the PFS of transarterial chemoembolization treatment of HCC.

Contributing to the prediction of prognosis for treated hepatocellular carcinoma: Imaging aspects that sculpt the future

A novel nomogram model to predict the prognosis of hepatocellular carcinoma(HCC)treated with radiofrequency ablation and transarterial chemoembolization was recently published in the World Journal of Gastrointestinal Surgery.This model includes clinical and laboratory factors,but emerging imaging aspects,partic-ularly from magnetic resonance imaging(MRI)and radiomics,could enhance the predictive accuracy thereof.Multiparametric MRI and deep learning radiomics models significantly improve prognostic predictions for the treatment of HCC.In-corporating advanced imaging features,such as peritumoral hypointensity and radiomics scores,alongside clinical factors,can refine prognostic models,aiding in personalized treatment and better predicting outcomes.This letter underscores the importance of integrating novel imaging techniques into prognostic tools to better manage and treat HCC.

Preoperative prediction of hepatocellular carcinoma microvascular invasion based on magnetic resonance imaging feature extraction artificial neural network

BACKGROUND Hepatocellular carcinoma(HCC)recurrence is highly correlated with increased mortality.Microvascular invasion(MVI)is indicative of aggressive tumor biology in HCC.AIM To construct an artificial neural network(ANN)capable of accurately predicting MVI presence in HCC using magnetic resonance imaging.METHODS This study included 255 patients with HCC with tumors<3 cm.Radiologists annotated the tumors on the T1-weighted plain MR images.Subsequently,a three-layer ANN was constructed using image features as inputs to predict MVI status in patients with HCC.Postoperative pathological examination is considered the gold standard for determining MVI.Receiver operating characteristic analysis was used to evaluate the effectiveness of the algorithm.RESULTS Using the bagging strategy to vote for 50 classifier classification results,a prediction model yielded an area under the curve(AUC)of 0.79.Moreover,correlation analysis revealed that alpha-fetoprotein values and tumor volume were not significantly correlated with the occurrence of MVI,whereas tumor sphericity was significantly correlated with MVI(P<0.01).CONCLUSION Analysis of variable correlations regarding MVI in tumors with diameters<3 cm should prioritize tumor sphericity.The ANN model demonstrated strong predictive MVI for patients with HCC(AUC=0.79).

Imaging-based prediction of hepatocellular carcinoma recurrence after microwave ablation as bridge therapy: A glimpse into the future

Liver transplantation(LT)remains the treatment of choice for early-stage hepato-cellular carcinoma(HCC)and offers the best long-term oncological outcomes.However,the increasing waiting list for LT has led to a significant dropout rate as patients experience tumor progression beyond the Milan criteria.Currently,locoregional therapies,such as microwave ablation(MWA),have emerged as promising bridge treatments for patients awaiting LT.These therapies have shown promising results in preventing tumor progression,thus reducing the dropout rate of LT candidates.Despite the efficacy of MWA in treating HCC,tumoral recurrence after ablation remains a major challenge and significantly impacts the prognosis of HCC patients.Therefore,accurately diagnosing tumoral recurrence post-ablation is crucial.Recent studies have developed novel imaging features based on magnetic resonance imaging of HCC,which could provide essential information for predicting early tumoral recurrence after MWA.These advancements could address this unresolved challenge,improving the clinical outcomes of patients on the LT waiting list.This article explored the current landscape of MWA as a bridge therapy for HCC within the Milan criteria,high-lighting the emerging role of novel imaging-based features aimed at improving the prediction of tumor recurrence after MWA.

Magnetic resonance imaging focused on the ferritin heavy chain 1 reporter gene detects neuronal differentiation in stem cells

The neuronal differentiation of mesenchymal stem cells offers a new strategy for the treatment of neurological disorders.Thus,there is a need to identify a noninvasive and sensitive in vivo imaging approach for real-time monitoring of transplanted stem cells.Our previous study confirmed that magnetic resonance imaging,with a focus on the ferritin heavy chain 1 reporter gene,could track the proliferation and differentiation of bone marrow mesenchymal stem cells that had been transduced with lentivirus carrying the ferritin heavy chain 1 reporter gene.However,we could not determine whether or when bone marrow mesenchymal stem cells had undergone neuronal differentiation based on changes in the magnetic resonance imaging signal.To solve this problem,we identified a neuron-specific enolase that can be differentially expressed before and after neuronal differentiation in stem cells.In this study,we successfully constructed a lentivirus carrying the neuron-specific enolase promoter and expressing the ferritin heavy chain 1 reporter gene;we used this lentivirus to transduce bone marrow mesenchymal stem cells.Cellular and animal studies showed that the neuron-specific enolase promoter effectively drove the expression of ferritin heavy chain 1 after neuronal differentiation of bone marrow mesenchymal stem cells;this led to intracellular accumulation of iron and corresponding changes in the magnetic resonance imaging signal.In summary,we established an innovative magnetic resonance imaging approach focused on the induction of reporter gene expression by a neuron-specific promoter.This imaging method can be used to noninvasively and sensitively detect neuronal differentiation in stem cells,which may be useful in stem cell-based therapies.

采用Cell-SELEX技术的核酸适配体在肿瘤靶向治疗的研究进展

阐述细胞-配体指数富集系统进化(Cell-SELEX)技术特点,以及通过该技术筛选得到的核酸适配体在肿瘤靶向治疗中的应用进展和挑战,通过查阅近年的相关文献,综述核酸适配体作为药物及药物载体在肿瘤靶向治疗中的应用研究进展。结果表明:基于Cell-SELEX技术筛选得到的核酸适配体在肿瘤靶向治疗中的疗效显著,可开发成为肿瘤靶向治疗的潜力药物及良好的药物载体。

Simultaneous Morphologies and Luminescence Control of NaYF_(4)∶Yb/Er Nanophosphors by Surfactants for Cancer Cell Imaging

Hydrophilic rare-earth up-conversion nanophosphors(UCNPs)with small sizes and a strong up-conversion luminescence have attracted much interest.Herein the simultaneous control of morphologies and the up-conversion luminescence intensities was reported for NaYF_(4)∶Yb/Er nanophosphors by a facile hydrothermal procedure with different surfactants.With the change of the surfactants from polyvinylpyrrolidone(PVP)to sodium citrate(CIT),edetate disodium(EDTA)or sodium dodecyl benzenesulfonate(SDBS),the morphology of NaYF_(4)∶Yb/Er nanophosphors transformed from nanoparticles with a diameter of about 70.0 nm to hexagonal nanoblocks with a thickness of about 125.0 nm and a length of about 240.0 nm,nanorods with a diameter of about 700.0 nm and a length of about 2.6μm,or nanowires with a diameter of 250.0 nm and a length of about 3.2μm.Simultaneously,their up-conversion luminescence intensity went down gradually under laser irradiation at a wavelength of 980 nm due to the increase of photobleaching.PVP-capped NaYF_(4)∶Yb/Er nanoparticles exhibited the smallest size and the strongest up-conversion luminescence intensity.Biological experiment results revealed that NaYF_(4)∶Yb/Er nanophosphors exhibited a high biocompatibility and could be used as biological labels with a perfect signal-to-noise ratio for cancer cell imaging.

3D imaging lipidometry in single cell by in-flow holographic tomography

The most recent discoveries in the biochemical field are highlighting the increasingly important role of lipid droplets(LDs)in several regulatory mechanisms in living cells.LDs are dynamic organelles and therefore their complete characterization in terms of number,size,spatial positioning and relative distribution in the cell volume can shed light on the roles played by LDs.Until now,fluorescence microscopy and transmission electron microscopy are assessed as the gold standard methods for identifying LDs due to their high sensitivity and specificity.However,such methods generally only provide 2D assays and partial measurements.Furthermore,both can be destructive and with low productivity,thus limiting analysis of large cell numbers in a sample.Here we demonstrate for the first time the capability of 3D visualization and the full LD characterization in high-throughput with a tomographic phase-contrast flow-cytometer,by using ovarian cancer cells and monocyte cell lines as models.A strategy for retrieving significant parameters on spatial correlations and LD 3D positioning inside each cell volume is reported.The information gathered by this new method could allow more in depth understanding and lead to new discoveries on how LDs are correlated to cellular functions.

Detection of cells by flow cytometry:Counting,imaging,and cell classification

The study of circulating cells in the blood stream is critical,as it covers many felds of biomed-icine,including immunology,cell biology,oncology,and reproductive medicine.In-viuo flowcytometry(IVFC)is a new tool to monitor and count cells in real time for long durations in theirnative biological environment.This review describes two main categories of IVFC,ie.,labeledand label-free IVFC.It focuses on label-free IVFC and introduces its technological developmentand related biological applications.Because cell recognition is the basis of flow cytometrycounting,this review also describes various methods for the classification of unlabeled cells,including the latest machine learning-based technologies.

The combined application of stem cells and three-dimensional bioprinting scaffolds for the repair of spinal cord injury

Spinal cord injury is considered one of the most difficult injuries to repair and has one of the worst prognoses for injuries to the nervous system.Following surgery,the poor regenerative capacity of nerve cells and the generation of new scars can make it very difficult for the impaired nervous system to restore its neural functionality.Traditional treatments can only alleviate secondary injuries but cannot fundamentally repair the spinal cord.Consequently,there is a critical need to develop new treatments to promote functional repair after spinal cord injury.Over recent years,there have been seve ral developments in the use of stem cell therapy for the treatment of spinal cord injury.Alongside significant developments in the field of tissue engineering,three-dimensional bioprinting technology has become a hot research topic due to its ability to accurately print complex structures.This led to the loading of three-dimensional bioprinting scaffolds which provided precise cell localization.These three-dimensional bioprinting scaffolds co uld repair damaged neural circuits and had the potential to repair the damaged spinal cord.In this review,we discuss the mechanisms underlying simple stem cell therapy,the application of different types of stem cells for the treatment of spinal cord injury,and the different manufa cturing methods for three-dimensional bioprinting scaffolds.In particular,we focus on the development of three-dimensional bioprinting scaffolds for the treatment of spinal cord injury.