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.

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.

Mechanism of inflammatory response and therapeutic effects of stem cells in ischemic stroke:current evidence and future perspectives

Ischemic stroke is a leading cause of death and disability worldwide,with an increasing trend and tendency for onset at a younger age.China,in particular,bears a high burden of stroke cases.In recent years,the inflammatory response after stroke has become a research hotspot:understanding the role of inflammatory response in tissue damage and repair following ischemic stroke is an important direction for its treatment.This review summarizes several major cells involved in the inflammatory response following ischemic stroke,including microglia,neutrophils,monocytes,lymphocytes,and astrocytes.Additionally,we have also highlighted the recent progress in various treatments for ischemic stroke,particularly in the field of stem cell therapy.Overall,understanding the complex interactions between inflammation and ischemic stroke can provide valuable insights for developing treatment strategies and improving patient outcomes.Stem cell therapy may potentially become an important component of ischemic stroke treatment.

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.

Functional Liver Imaging Score Derived from Gadoxetic Acid-enhanced MRI Predicts Cachexia and Prognosis in Hepatocellular Carcinoma Patients

Objective Cachexia occurs in approximately half of hepatocellular carcinoma(HCC)patients as the disease progresses and is correlated with a poor prognosis.Therefore,early identification of HCC patients at risk of developing cachexia and their prognosis is crucial.This study investigated the functional liver imaging score(FLIS)derived from gadoxetic acid-enhanced magnetic resonance imaging(MRI)to identify cachexia in HCC patients and their prognosis.Methods Pretreatment clinical and MRI data from 339 HCC patients who underwent gadoxetic acid-enhanced MRI scans were retrospectively collected.Patient weights were recorded for 6 months following the MRI scan to diagnose cachexia.The FLIS was calculated as the sum of the enhancement quality score,the excretion quality score,and the portal vein sign quality score.A Cox proportional hazards model was used to determine the significant factors affecting overall survival(OS).Multivariable logistic regression was then conducted to identify variables predicting cachexia in HCC patients,which were subsequently used to predict OS.Results Cox regression analysis revealed a significant association between cachexia and worse OS.Both FLIS(0–4 vs.5–6 points)(OR,9.20;95%CI:4.68–18.10;P<0.001)andα-fetoprotein>100 ng/mL(OR,4.08;95%CI:2.13–7.83;P<0.001)emerged as significant predictors of cachexia in patients with HCC.Furthermore,FLIS(0–4 vs.5–6 points)(HR,1.73;95%CI:1.19–2.51;P=0.004)was significantly associated with OS.Patients in the FLIS 0–4 points group had shorter OS than those in the FLIS 5–6 points group[20 months(95%CI,14.7–25.3)vs.43 months(95%CI,27.7–58.3);P=0.001].Conclusion Cachexia was associated with worse OS.The functional liver imaging score emerged as a significant predictor of cachexia in HCC patients and their prognosis.

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.

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).

Meningeal lymphatic vessel crosstalk with central nervous system immune cells in aging and neurodegenerative diseases

Meningeal lymphatic vessels form a relationship between the nervous system and periphery, which is relevant in both health and disease. Meningeal lymphatic vessels not only play a key role in the drainage of brain metabolites but also contribute to antigen delivery and immune cell activation. The advent of novel genomic technologies has enabled rapid progress in the characterization of myeloid and lymphoid cells and their interactions with meningeal lymphatic vessels within the central nervous system. In this review, we provide an overview of the multifaceted roles of meningeal lymphatic vessels within the context of the central nervous system immune network, highlighting recent discoveries on the immunological niche provided by meningeal lymphatic vessels. Furthermore, we delve into the mechanisms of crosstalk between meningeal lymphatic vessels and immune cells in the central nervous system under both homeostatic conditions and neurodegenerative diseases, discussing how these interactions shape the pathological outcomes. Regulation of meningeal lymphatic vessel function and structure can influence lymphatic drainage, cerebrospinal fluid-borne immune modulators, and immune cell populations in aging and neurodegenerative disorders, thereby playing a key role in shaping meningeal and brain parenchyma immunity.

Treatment of spinal cord injury with biomaterials and stem cell therapy in non-human primates and humans

Spinal cord injury results in the loss of sensory,motor,and autonomic functions,which almost always produces permanent physical disability.Thus,in the search for more effective treatments than those already applied for years,which are not entirely efficient,researches have been able to demonstrate the potential of biological strategies using biomaterials to tissue manufacturing through bioengineering and stem cell therapy as a neuroregenerative approach,seeking to promote neuronal recovery after spinal cord injury.Each of these strategies has been developed and meticulously evaluated in several animal models with the aim of analyzing the potential of interventions for neuronal repair and,consequently,boosting functional recovery.Although the majority of experimental research has been conducted in rodents,there is increasing recognition of the importance,and need,of evaluating the safety and efficacy of these interventions in non-human primates before moving to clinical trials involving therapies potentially promising in humans.This article is a literature review from databases(PubMed,Science Direct,Elsevier,Scielo,Redalyc,Cochrane,and NCBI)from 10 years ago to date,using keywords(spinal cord injury,cell therapy,non-human primates,humans,and bioengineering in spinal cord injury).From 110 retrieved articles,after two selection rounds based on inclusion and exclusion criteria,21 articles were analyzed.Thus,this review arises from the need to recognize the experimental therapeutic advances applied in non-human primates and even humans,aimed at deepening these strategies and identifying the advantages and influence of the results on extrapolation for clinical applicability in humans.

Induced pluripotent stem cell-related approaches to generate dopaminergic neurons for Parkinson's disease

The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.

Modulation of the Nogo signaling pathway to overcome amyloid-β-mediated neurite inhibition in human pluripotent stem cell-derived neurites

Neuronal cell death and the loss of connectivity are two of the primary pathological mechanisms underlying Alzheimer's disease.The accumulation of amyloid-βpeptides,a key hallmark of Alzheimer's disease,is believed to induce neuritic abnormalities,including reduced growth,extension,and abnormal growth cone morphology,all of which contribute to decreased connectivity.However,the precise cellular and molecular mechanisms governing this response remain unknown.In this study,we used an innovative approach to demonstrate the effect of amyloid-βon neurite dynamics in both two-dimensional and three-dimensional cultu re systems,in order to provide more physiologically relevant culture geometry.We utilized various methodologies,including the addition of exogenous amyloid-βpeptides to the culture medium,growth substrate coating,and the utilization of human-induced pluripotent stem cell technology,to investigate the effect of endogenous amyloid-βsecretion on neurite outgrowth,thus paving the way for potential future applications in personalized medicine.Additionally,we also explore the involvement of the Nogo signaling cascade in amyloid-β-induced neurite inhibition.We demonstrate that inhibition of downstream ROCK and RhoA components of the Nogo signaling pathway,achieved through modulation with Y-27632(a ROCK inhibitor)and Ibuprofen(a Rho A inhibitor),respectively,can restore and even enhance neuronal connectivity in the presence of amyloid-β.In summary,this study not only presents a novel culture approach that offers insights into the biological process of neurite growth and inhibition,but also proposes a specific mechanism for reduced neural connectivity in the presence of amyloid-βpeptides,along with potential intervention points to restore neurite growth.Thereby,we aim to establish a culture system that has the potential to serve as an assay for measuring preclinical,predictive outcomes of drugs and their ability to promote neurite outgrowth,both generally and in a patient-specific manner.

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.