Pancreatic cancer is a highly aggressive and often fatal disease, with early detection being a key factor for improving patient survival. Recent advances in artificial intelligence (AI), particularly deep learning, have demonstrated significant potential in disease diagnosis based on histopathological images. This study investigates the effectiveness of two deep learning models, residual neural network (ResNet) and visual geometry group network (VGG), in distinguishing pancreatic cancer tissue from normal pancreatic tissue using histological images. A total of 3,000 hematoxylin and eosin (H&E) stained pathological images were collected for both normal pancreatic tissue and pancreatic cancer tissue. The images were acquired using a microscopic slide scanning system in our laboratory. After preprocessing steps such as cropping, resizing, and normalization, the images were input into two deep neural networks, ResNet and VGG, for training and testing. The deep learning models were implemented using the PyTorch framework and tested on a CUDA10 parallel computing platform. ResNet achieved an accuracy of 92.27% and an F1-score of 0.92, outperforming VGG, which achieved an accuracy of 86.01% and an F1-score of 0.86. K-fold cross-validation was performed to evaluate the generalization ability of the models. The results showed that deep learning models, particularly ResNet, offer substantial promise for improving the accuracy of pancreatic cancer diagnosis, potentially facilitating earlier and more accurate detection in clinical settings.

Uremic cardiomyopathy (UCM) is the leading cause of hemodialysis patient mortality. Indoxyl sulfate (IS), a key uremic toxin, activates multiple signaling pathways, causing cardiac hypertrophy and apoptosis. We previously demonstrated that core fucosylation (CF), a post-translational modification, is crucial in activating these pathways. Additionally exosome-mediated cardiac microvascular endothelial cell (CMEC)-cardiomyocyte (CM) crosstalk is important for UCM progression. However, the characteristics and roles of CF modification in IS-induced CMEC-derived exosomes (IS-Exos) that cause CM injury remain unexplored. Our studies have revealed that hemodialysis patients had significantly higher serum IS and α1,6-fucosyltransferase (FUT8), which were positively correlated with the severity of cardiac injury. Using a microfluidic chip model of IS-induced cardiac injury, we visualized exosome transfer from CMECs to CMs, which caused mitochondrial impairment, hypertrophy and apoptosis in CMs, with elevated CF levels playing critical roles. To investigate this further, we performed FUT8 knockout in IS-mice treated with IS-Exos and transfected FUT8 siRNA into CMs exposed to IS-Exos. We found that the inhibition of FUT8 leads to a reduction in ARG2 expression, which consequently diminishes reactive oxygen species (ROS) and ameliorates cardiac hypertrophy and apoptosis. Mechanistically, miR-27a-5p was markedly downregulated in IS-Exos. CD44 on IS-Exos interacts with EGFR in CMs, enhancing cardiac injury. Supplementation with miR-27a-5p in vivo and in vitro specifically targets USF2, leading to a downregulation of FUT8 expression. This cascade leads to a diminished expression of ARG2, alleviation of ROS, and the reversal of cardiac hypertrophy and apoptosis. Our findings offer new insights, suggesting that targeting CF modification may represent a promising therapeutic strategy for alleviating UCM in the future.

The low in vivo yield of midbrain dopaminergic (mDA) neurons and uncertain lineage fates of donor cells following transplantation impede clinical application of human pluripotent stem cell (hPSC)-based cell therapy for Parkinson’s disease (PD). We developed a three-dimensional (3D) differentiation method, SphereDiff, to generate high-purity mDA progenitors (mDAPs), leading to a significant enrichment of mDA neurons post transplantation. Grafted mDA neurons fully restored dopamine levels and corrected motor deficits in PD model mice. Single-cell spatial transcriptomics revealed a patterned distribution of mDA neuron subtypes and glial cells. Using cross-transplantation single-cell split barcoding (TX-SISBAR), we elucidated the clonal lineage fates of donor cells post transplantation, revealing the mDA neuron and astrocyte fates of mDAPs and glutamatergic neuron fates of diencephalic progenitors. Leveraging these lineage insights, we further refined SphereDiff and eliminated off-target lineage cells. Producing high in vivo efficacy, lineage-defined donor cells supports safer and more effective PD cell therapy in regenerative medicine.

Following the publication of the above article, a concerned reader drew to the Editor's attention that, regarding the immunohistochemical staining experiments shown in Fig. 2, the insets for the data panels 2A and B, and 2C and D, respectively were remarkably similar, such that these data may not have consistently been identifiable with the main images proper for these figure parts. Secondly, with the western blot data shown in Fig. 3c, the PTCH1/Huh7 and ATAD2/siRNA‑HCCLM3 protein bands were remarkably similar, such that the same data were likely to have been duplicated in the figure where different experiments were intended to have been portrayed. Finally, the two sets of flow cytometric plots shown in Fig. 2A appeared to show similar groupings of dots, which would not have been anticipated if these experiments had been performed discretely under different experimental conditions, suggesting a fundamental flaw either in the way in which these experiments were performed, or in how the results were outputted. After having conducted an internal investigation of the data in this paper, the Editor of International Journal of Oncology has decided that this article should be retracted from the journal on the grounds of an overall lack of confidence in the data. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor sincerely apologizes to the readership for any inconvenience caused, and we thank the reader for bringing this matter to our attention. [International Journal of Oncology 45: 351‑361, 2014; DOI: 10.3892/ijo.2014.2416].

Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified Pou3f1 as a marker gene enriched in neurons projecting to the lateral hypothalamus, denoting a distinct subset with collateral projections to both dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.

A wavelet transform assisted laser-induced fluorescence detector with high sensitivity was developed and evaluated. An unconventional microscope objective with a numerical aperture (NA) of 0.5 and a working distance (WD) of 4.0 mm was employed, which improved fluorescence collection efficiency, increasing SNR to about 5 times. An aspherical lens was used in the collection optical path to reduce the diameter of the fluorescence imaging size, increasing the SNR to about 1.3 times. The "inverted suction injection" method of flow injection analysis (FIA) was used for the first time in LIF evaluation to reduce contamination errors and improve the accuracy of ultra-trace analysis. The wavelet transform method was proposed for data processing of LIF signals, which can reduce noise from 0.009 mV to 0.002 mV without changing the peak height and peak width. The limit of detection (LOD, 3σ method) for sodium fluorescein was 9.7 × 10-14 M or 3.9 fluorescein molecules in 68 pL detection volume, which was the lowest level of LIFs evaluated by FIA mode. The LIF combined with capillary electrophoresis (CE) achieved an LOD of 4.9 × 10-15 M for fluorescein sodium, which is the best level that has been reported.

BackgroundHypoxic-ischemic encephalopathy (HIE) is a major cause of neonatal disability and mortality. Although intensive studies and therapeutic approaches, there are limited restorative treatments till now. Human embryonic stem cell (hESCs)-derived cortical neural progenitors have shown great potentials in ischemic stroke in adult brain. However, it is unclear whether they are feasible for cortical reconstruction in immature brain with hypoxic-ischemic encephalopathy.MethodsBy using embryonic body (EB) neural differentiation method combined with DAPT pre-treatment and quantitative cell transplantation, human cortical neuroblasts were obtained and transplanted into the cortex of hypoxic-ischemic injured brain with different dosages 2 weeks after surgery. Then, immunostaining, whole-cell patch clamp recordings and behavioral testing were applied to explore the graft survival and proliferation, fate commitment of cortical neuroblasts in vitro, neural circuit reconstruction and the therapeutic effects of cortical neuroblasts in HIE brain.ResultsTransplantation of human cortical neural progenitor cells (hCNPs) in HIE-injured cortex exhibited long-term graft overgrowth. DAPT pre-treatment successfully synchronized hCNPs from different developmental stages (day 17, day 21, day 28) to deep layer cortical neuroblasts which survived well in HIE injured brain and greatly prevented graft overgrowth after transplantation. Importantly, the cortical neuroblasts primarily differentiated into deep-layer cortical neurons and extended long axons to their projection targets, such as the cortex, striatum, thalamus, and internal capsule in both ipsilateral and contralateral HIE-injured brain. The transplanted cortical neurons established synapses with host cortical neurons and exhibited spontaneous excitatory or inhibitory post-synaptic currents (sEPSCs or sIPSCs) five months post-transplantation. Rotarod and open field tests showed greatly improved animal behavior by intra-cortex transplantation of deep layer cortical neuroblasts in HIE injured brain.ConclusionsTransplanted hESCs derived cortical neuroblasts survive, project to endogenous targets, and integrate into host cortical neural circuits to rescue animal behavior in the HIE-injured brain without graft overgrowth, providing a novel and safe cell replacement strategy for the future treatment of HIE.

Ubiquitination of the proteins is crucial for governing protein degradation and regulating fundamental cellular processes. Deubiquitinases (DUBs) have emerged as significant regulators of multiple pathways associated with cancer and other diseases, owing to their capacity to remove ubiquitin from target substrates and modulate signaling. Consequently, they represent potential therapeutic targets for cancer and other life-threatening conditions. USP43 belongs to the DUBs family involved in cancer development and progression. This review aims to provide a comprehensive overview of the existing scientific evidence implicating USP43 in cancer development. Additionally, it will investigate potential small-molecule inhibitors that target DUBs that may have the capability to function as anti-cancer medicines.

Thyroid cancer (TC) is a kind of cancer with high heterogeneity, which leads to significant difference in prognosis. The prognostic molecular processes are not well understood. Cancer cells and tumor microenvironment (TME) cells jointly determine the heterogeneity. However, quite a little attention was paid to cells in the TME in the past years. In this study, we not only reveal that endothelial cells (ECs) are strongly associated with the progress of papillary thyroid cancer (PTC) using single-cell RNA-seq (scRNA-seq) data downloaded from Gene Expression Omnibus (GEO) and WGCNA, but also screen 5 crucial genes of ECs: CLDN5, ABCG2, NOTCH4, PLAT, and TMEM47. Furthermore, the 5-gene molecular prognostic model is constructed, which can predict how well a patient will do on PD-L1 blockade immunotherapy for TC and evaluate prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis demonstrates that PLAT is decreased in TC and the increase of PLAT can restrain the migratory capacity of TC cells. Meanwhile, in TC cells, PLAT suppresses VEGFa/VEGFR2-mediated human umbilical vascular endothelial cell (HUVEC) proliferation and tube formation. Totally, we construct the 5-gene molecular prognostic model from the perspective of EC and provide a new idea for immunotherapy of TC.

BACKGROUND:Accumulating studies have disclosed that circular RNAs (circRNAs) are closely associated with the malignant progression of colorectal cancer (CRC). The aim of our work was to reveal the function of circ_0038718 in CRC. METHODS:The level of genes and proteins were assessed by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. In vitro researches were executed via utilizing cell counting Kit-8 (CCK-8), EdU, flow cytometry analysis and wound-healing assay, individually. The target relationship was validated by Dual-luciferase reporter assay. In vivo assay was employed through establishing xenograft tumor model. RESULTS:Circ_0038718 was identified to be increased in CRC tissues and cells. Circ_0038718 downregulation suppressed cell proliferation, migration and facilitated apoptosis of CRC. Mechanistically, circ_0038718 could sponge miR-761 and miR-214-3p to modulate the expression of ITGA6. The rescue experiments proved that miR-761 or miR-214-3p inhibitor attenuated the repressive impact of circ_0038718 inhibition on CRC cells progression, and overexpressed ITGA6 could weaken the inhibitory effect of miR-761 or miR-214-3p on tumor cells. Furthermore, depletion of circ_0038718 confined the tumor growth in vivo. CONCLUSION:Circ_0038718 aggravated the progression of CRC cells via mediating ITGA6 expression through targeting miR-761 and miR-214-3p, providing a new therapeutic target for CRC patients.

Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC. Papillary thyroid cancers (PTC) generally have good prognosis, but their recurrence rate remains high. Here, the authors use proteogenomics and metabolomics to identify molecular features in PTC tumours and determine PTC subtypes that are associated with prognosis and potential targeted therapies.

Abstract In thermal power plants, coal conveyor belts pose significant risks that jeopardize the stability of the energy supply, underscoring the need for effective risk management. To address the complexity, uncertainty, and polymorphism issues in belt conveyor systems, we introduce a BT-UFDBN risk analysis method specifically for coal conveyor belts. This method develops a typical Bow-tie model, identifies potential risk factors for unplanned stoppages, and utilizes fuzzy evaluation methods and an improved SAM method to determine prior probabilities. The Bow-tie (BT) model is then mapped into a Dynamic Bayesian Network (DBN). To manage uncertainties within the DBN, the Leaky Noisy-OR gate model, stationarity, and first-order Markov assumptions are employed to ensure the model’s validity and practical relevance. This paper uses a belt conveyor system from a thermal power plant as a case study to validate the model’s effectiveness in predicting accident consequences, diagnosing fault causes, and proposing targeted preventive measures for identified weak points. The study provides theoretical guidance for risk management of coal conveyor belts in power plants.

Consensus on the stage of liver hepatocellular carcinoma (LIHC) in patients is difficult, which restricts the diagnosis and treatment of liver cancer. Molecular typing based on genes related to the lipid metabolism pathways can reflect deeper characteristics of liver cancer and complement the deficiency of the clinical staging system. In this study, we constructed and verified two cell subtypes: C1 and C2 in LIHC, based on six lipid metabolic pathway-associated genes identified in two independent external validation cohorts comprising single-cell RNA-sequencing technology (scRNA-Seq) data and bulk RNA-seq data downloaded from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The C2 subtype showed poorer prognosis, higher immune scores, and greater correlation with pathways associated with tumor progression as compared to the C1 subtype. Moreover, the sensitivity of many tested targeted drugs in C1 was relative to C2. Furthermore, Gene Set Enrichment Analysis (GSEA) revealed several significantly enriched oncological signatures and metabolic processes, which might help elucidate the underlying molecular mechanisms. At the same time, we identified there were significantly different metabolites in C1 and C2 subtypes using 11 LIHC tissue samples. In conclusion, we constructed two molecular subtypes based on the lipid metabolism-associated genes, which may provide valuable information to further study the pathogenesis and devise clinical management strategies for LIHC.

Introduction: Monitoring the response after treatment of liver cancer and timely adjusting the treatment strategy are crucial to improve the survival rate of liver cancer. At present, the clinical monitoring of liver cancer after treatment is mainly based on serum markers and imaging. Morphological evaluation has limitations, such as the inability to measure small tumors and the poor repeatability of measurement, which is not applicable to cancer evaluation after immunotherapy or targeted treatment. The determination of serum markers is greatly affected by the environment and cannot accurately evaluate the prognosis. With the development of single cell sequencing technology, a large number of immune cell-specific genes have been identified. Immune cells and microenvironment play an important role in the process of prognosis. We speculate that the expression changes of immune cell-specific genes can indicate the process of prognosis. Method: Therefore, this paper first screened out the immune cell-specific genes related to liver cancer, and then built a deep learning model based on the expression of these genes to predict metastasis and the survival time of liver cancer patients. We verified and compared the model on the data set of 372 patients with liver cancer. Result: The experiments found that our model is significantly superior to other methods, and can accurately identify whether liver cancer patients have metastasis and predict the survival time of liver cancer patients according to the expression of immune cell-specific genes. Discussion: We found these immune cell-specific genes participant multiple cancer-related pathways. We fully explored the function of these genes, which would support the development of immunotherapy for liver cancer.

The cell lineages across developmental stages remain to be elucidated. Here, we developed single-cell split barcoding (SISBAR) that allows clonal tracking of single-cell transcriptomes across stages in an in vitro model of human ventral midbrain-hindbrain differentiation. We developed "potential-spective"and "origin-spective"analyses to investigate the cross-stage lineage relationships and mapped a multi-level clonal lineage landscape depicting the whole differentiation process. We uncovered many previously unchar-acterized converging and diverging trajectories. Furthermore, we demonstrate that a transcriptome-defined cell type can arise from distinct lineages that leave molecular imprints on their progenies, and the multilineage fates of a progenitor cell-type represent the collective results of distinct rather than similar clonal fates of individual progenitors, each with distinct molecular signatures. Specifically, we uncovered a ventral midbrain progenitor cluster as the common clonal origin of midbrain dopaminergic (mDA) neurons, midbrain glutama-tergic neurons, and vascular and leptomeningeal cells and identified a surface marker that can improve graft outcomes.

Background. Pancreatic ductal adenocarcinoma (PDAC) is a devastating cancer, and the therapy options for PDAC remain restricted. The distinctive tumor immunological microenvironment (TIME) of PDAC, comprising a high number of stromal cells and a limited infiltration of cytotoxic T lymphocytes (CTLs), rendered immunotherapy ineffective. The protein level of ubiquitin-specific protease 43 (USP43) was a prognostic predictor in numerous cancers; however, its function in PDAC is limited. This article focuses on the influence of USP43 expression on PDAC prognosis and TIME alteration. Methods. Based on TCGA database and tissue microarray staining, the expression of USP43 in PDAC was evaluated. The association between USP43 and prognosis was then investigated using tissue samples and online databases. In PDAC tumor tissues, the correlation between USP43 expression and clinicopathological characteristics, immune cell infiltration, and prognosis was investigated. The expression of USP43 in PDAC cell lines was evaluated using quantitative polymerase chain reaction. Using a cell counting kit-8 (CCK-8) and a cell colony formation test, the viability of the cells was determined. On the basis of online databases and tissue samples, the link between USP43 and immune cell infiltration around PDAC was also examined. For statistical analyses, the software GraphPad, R, and SPSS 26.0 were utilized. Results. The expression of USP43 was considerably higher in PDAC compared to normal pancreatic tissue in both the TCGA database and the tissue microarrays of PDAC patients (P<0.001). High USP43 expression was associated with poor overall survival in both the TCGA database and the tissue microarray of PDAC patients (P=0.046 and 0.021, respectively). USP43 overexpression promoted PANC-1 cell proliferation (P=0.0018), but USP43 knockdown decreased PANC02 cell proliferation (P<0.001). According to the TCGA database, USP43 is associated with T cell activation and inhibits CD8+ T cell activation in PDAC, as proven by a study of cell lines. Moreover, in both TCGA and PDAC cell lines, USP43 expression was negatively linked with the chemokine signaling pathway. Conclusions. Overexpression of USP43 is a potential prognostic indicator for PDAC patients. USP43 is a potential biomarker associated with T cell activation, suppression of CD8+ T cell enrichment, and the cytokine signal pathway. Future multicenter studies are needed to confirm our findings and their potential application in the treatment of PDAC patients.

Intrahepatic cholangiocarcinoma (iCCA) is a highly fatal malignancy with rapidly increasing incidence and mortality worldwide. Currently, gemcitabine-based systemic chemotherapy is the main clinical therapeutic regimen; however, its efficacy is poor, and its mechanism has not been elucidated. In this study, we use a Seahorse Extracellular Flux analyser to measure glycolysis capacity (extracellular acidification rate, ECAR) and oxygen consumption rate (OCR). The glucose uptake or lactic acid content is detected, and the effects of saikosaponin D, an active compound derived from Bupleuri Radix (a traditional Chinese medicine for soothing the liver and relieving depression), on gemcitabine cytotoxicity in norepinephrine-stimulated iCCA cells are analysed. We find that adrenergic signaling plays a fundamental role in chronic stress-induced therapeutic resistance in iCCA. Norepinephrine (NE) and epinephrine (E) enhance the proliferation of iCCA cells and interfere with the response to gemcitabine through activation of the β2-adrenergic receptor (ADRB2). Furthermore, we find that NE upregulates the expressions of several drug efflux-related genes (such as ABCG2 and MDR1) and promotes glycolysis in iCCA cells. In addition, saikosaponin D reverses the poor response of iCCA cells to gemcitabine by downregulating ADRB2 level. Furthermore, saikosaponin D inhibits drug efflux and glycolysis in iCCA cells by regulating the expressions of MDR1, ABCG2, HK2, and GLUT1. Collectively, saikosaponin D enhances the antitumor effect of gemcitabine by controlling glucose metabolism and drug efflux by inhibiting the ADRB2 signaling. Therefore, the combination of saikosaponin D and gemcitabine may be a potential therapeutic strategy for the treatment of iCCA.

Background. The molecular classification of HCC premised on metabolic genes might give assistance for diagnosis, therapy, prognosis prediction, immune infiltration, and oxidative stress in addition to supplementing the limitations of the clinical staging system. This would help to better represent the deeper features of HCC. Methods. TCGA datasets combined with GSE14520 and HCCDB18 datasets were used to determine the metabolic subtype (MC) using ConsensusClusterPlus. ssGSEA method was used to calculate the IFNγ score, the oxidative stress pathway scores, and the score distribution of 22 distinct immune cells, and their differential expressions were assessed with the use of CIBERSORT. To generate a subtype classification feature index, LDA was utilized. Screening of the metabolic gene coexpression modules was done with the help of WGCNA. Results. Three MCs (MC1, MC2, and MC3) were identified and showed different prognoses (MC2-poor and MC1-better). Although MC2 had a high immune microenvironment infiltration, T cell exhaustion markers were expressed at a high level in MC2 in contrast with MC1. Most oxidative stress-related pathways are inhibited in the MC2 subtype and activated in the MC1 subtype. The immunophenotyping of pan-cancer showed that the C1 and C2 subtypes with poor prognosis accounted for significantly higher proportions of MC2 and MC3 subtypes than MC1, while the better prognostic C3 subtype accounted for significantly lower proportions of MC2 than MC1. As per the findings of the TIDE analysis, MC1 had a greater likelihood of benefiting from immunotherapeutic regimens. MC2 was found to have a greater sensitivity to traditional chemotherapy drugs. Finally, 7 potential gene markers indicate HCC prognosis. Conclusion. The difference (variation) in tumor microenvironment and oxidative stress among metabolic subtypes of HCC was compared from multiple angles and levels. A complete and thorough clarification of the molecular pathological properties of HCC, the exploration of reliable markers for diagnosis, the improvement of the cancer staging system, and the guiding of individualized treatment of HCC all gain benefit greatly from molecular classification associated with metabolism.

Abstract Perinatal hypoxic–ischaemic encephalopathy is the leading cause of neonatal death and permanent neurological deficits, while the basal ganglia is one of the major nuclei that is selectively and greatly affected in the brains of hypoxic–ischaemic encephalopathy patients, especially in severe cases. Human embryonic stem cell-derived neurons have shown great potential in different types of brain disorders in adults. However, it remains unknown whether and how grafted human embryonic stem cell-derived neurons can repair immature brains with hypoxic–ischaemic encephalopathy. Here, by administrating genetically labelled human embryonic stem cell-derived striatal neural progenitors into the ipsilateral striatum of hypoxic–ischaemic encephalopathy-injured mice, we found that the grafted cells gradually matured into GABA spiny projection neurons morphologically and electrophysiologically, and significantly rescued the area loss of hypoxic–ischaemic encephalopathy-injured brains. Intriguingly, using immunohistochemical staining combined with enhanced ascorbate peroxidase-based immunoelectron microscopy and rabies virus-mediated trans-synaptic tracing, we show that the grafts start to extend axonal projections to the endogenous target areas (globus pallidus externa, globus pallidus internus, substantia nigra), form synapses with host striatal, globus pallidus and nigra neurons, and receive extensive and stable synaptic inputs as early as 2 months post-transplantation. Importantly, we further demonstrated functional neural circuits re-established between the grafted neurons and host cortical, striatal and substantial nigra neurons at 3–6 months post-transplantation in the hypoxic–ischaemic encephalopathy-injured brain by optogenetics combined with electrophysiological recording. Finally, the transplanted striatal spiny projection neurons but not spinal GABA neurons restored the motor defects of hypoxic–ischaemic encephalopathy, which were reversed by clozapine-N-oxide-based inhibition of graft function. These findings demonstrate anatomical and functional reconstruction of the basal ganglia neural circuit including multiple loops by striatal spiny projection neurons in hypoxic–ischaemic encephalopathy-injured immature brains, which raises the possibility of such a cell replacement therapeutic strategy for hypoxic–ischaemic encephalopathy in neonates.

A fundamental interest in developmental neuroscience lies in the ability to map the complete single-cell lineages within the brain. To this end, we developed a CRISPR editing-based lineage-specific tracing (CREST) method for clonal tracing in Cre mice. We then used two complementary strategies based on CREST to map single-cell lineages in developing mouse ventral midbrain (vMB). By applying snapshotting CREST (snapCREST), we constructed a spatiotemporal lineage landscape of developing vMB and identified six progenitor archetypes that could represent the principal clonal fates of individual vMB progenitors and three distinct clonal lineages in the floor plate that specified glutamatergic, dopaminergic or both neurons. We further created pandaCREST (progenitor and derivative associating CREST) to associate the transcriptomes of progenitor cells in vivo with their differentiation potentials. We identified multiple origins of dopaminergic neurons and demonstrated that a transcriptome-defined progenitor type comprises heterogeneous progenitors, each with distinct clonal fates and molecular signatures. Therefore, the CREST method and strategies allow comprehensive single-cell lineage analysis that could offer new insights into the molecular programs underlying neural specification.