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The generation and differentiation of cortical projection neurons are extensively regulated by interactive programs of transcriptional factors. Here, we report the cooperative functions of transcription factors Bcl11a and Bcl11b in regulating the development of cortical projection neurons. Among the cells derived from the cortical neural stem cells, Bcl11a is expressed in the progenitors and the projection neurons, while Bcl11b expression is restricted to the projection neurons. Using conditional knockout mice, we show that deficiency of Bcl11a leads to reduced proliferation and precocious differentiation of cortical progenitor cells, which is exacerbated when Bcl11b is simultaneously deleted. Besides defective neuronal production, the differentiation of cortical projection neurons is blocked in the absence of both Bcl11a and Bcl11b: Expression of both pan-cortical and subtype-specific genes is reduced or absent; axonal projections to the thalamus, hindbrain, spinal cord, and contralateral cortical hemisphere are reduced or absent. Furthermore, neurogenesis-to-gliogenesis switch is accelerated in the Bcl11a-CKO and Bcl11a/b-DCKO mice. Bcl11a likely regulates neurogenesis through repressing the Nr2f1 expression. These results demonstrate that Bcl11a and Bcl11b jointly play critical roles in the generation and differentiation of cortical projection neurons and in controlling the timing of neurogenesis-to-gliogenesis switch.

Mouse cortical radial glial cells (RGCs) are primary neural stem cells that give rise to cortical oligodendrocytes, astrocytes, and olfactory bulb (OB) GABAergic interneurons in late embryogenesis. There are fundamental gaps in understanding how these diverse cell subtypes are generated. Here, by combining single-cell RNA-Seq with intersectional lineage analyses, we show that beginning at around E16.5, neocortical RGCs start to generate ASCL1+EGFR+ apical multipotent intermediate progenitors (MIPCs), which then differentiate into basal MIPCs that express ASCL1, EGFR, OLIG2, and MKI67. These basal MIPCs undergo several rounds of divisions to generate most of the cortical oligodendrocytes and astrocytes and a subpopulation of OB interneurons. Finally, single-cell ATAC-Seq supported our model for the genetic logic underlying the specification and differentiation of cortical glial cells and OB interneurons. Taken together, this work reveals the process of cortical radial glial cell lineage progression and the developmental origins of cortical astrocytes and oligodendrocytes. Supplementary Information The online version of this article (10.1007/s12264-021-00640-9) contains supplementary material, which is available to authorized users.

It is still a big challenge to design Gd3+ based nanoparticles (NPs) for T1 MRI (Magnetic Resonance Imaging) with high performance and clarify the effects of relative time parameters on longitudinal relaxivity r1. In this paper, we simulated the influences of different time parameters on the longitudinal relaxivity of Gd3+ based NPs with inner-sphere and outer-sphere theories, respectively. In particular, we investigated the effects of τR (the rotational time), τM (the residence time), Tie (the electronic relation time) and τd (the diffusion time) on longitudinal relaxivity. In the relaxation process of Gd3+ based NPs, the inner-sphere plays a dominant role, in which τR and τM have a greater impact on r1. Based on the simulation results, we proposed a design strategy of Gd3+ based NPs for T1 MRI, which focuses on the rational decrease of hydrated radius, and the optimal range of the hydrated radius is about 0.8–2.5 nm. In addition, we synthesized ultrasmall Gd2O3 NPs with a hydrated radius of about 2.5 nm, which have a high longitudinal relaxivity r1 of 10.8 mM−1 s−1 at 3.0 T. Moreover, the in vivo imaging results confirm that the ultrasmall Gd2O3 NPs have a good imaging effect on the tumor, and it can be a good candidate as a T1 MRI contrast agent with high performance.

The striatum is primarily composed of two types of medium spiny neurons (MSNs) expressing either D1- or D2-type dopamine receptors. However, the fate determination of these two types of neurons is not fully understood. Here, we found that D1 MSNs undergo fate switching to D2 MSNs in the absence of

The striatum is a central regulator of behavior and motor function through the actions of D1 and D2 medium-sized spiny neurons (MSNs), which arise from a common lateral ganglionic eminence (LGE) progenitor. The molecular mechanisms of cell fate specification of these two neuronal subtypes are incompletely understood. Here, we found that deletion of murine Meis2, which is highly expressed in the LGE and derivatives, led to a large reduction in striatal MSNs due to a block in their differentiation. Meis2 directly binds to the Zfp503 and Six3 promoters and is required for their expression and specification of D1 and D2 MSNs, respectively. Finally, Meis2 expression is regulated by Dlx1/2 at least partially through the enhancer hs599 in the LGE subventricular zone. Overall, our findings define a pathway in the LGE whereby Dlx1/2 drives expression of Meis2, which subsequently promotes the fate determination of striatal D1 and D2 MSNs via Zfp503 and Six3.

The striatum is structurally highly diverse, and its organ functionality critically depends on normal embryonic development. Although several studies have been conducted on the gene functional changes that occur during striatal development, a system-wide analysis of the underlying molecular changes is lacking. Here, we present a comprehensive transcriptome profile that allows us to explore the trajectory of striatal development and identify the correlation between the striatal development and Huntington’s disease (HD). Furthermore, we applied an integrative transcriptomic profiling approach based on machine learning to systematically map a global landscape of 277 transcription factor (TF) networks. Most of these TF networks are linked to biological processes, and some unannotated genes provide information about the corresponding mechanisms. For example, we found that the Meis2 and Six3 were crucial for the survival of striatal neurons, which were verified using conditional knockout (CKO) mice. Finally, we used RNA-Seq to speculate their downstream targets.

Specification of the progenitors’ regional identity is a pivotal step during development of the cerebral cortex and basal ganglia. The molecular mechanisms underlying progenitor regionalization, however, are poorly understood. Here we showed that the transcription factors Vax1 was highly expressed in the developing subpallium. In its absence, the RNA-Seq analysis, in situ RNA hybridization, and immunofluorescence staining results showed that the cell proliferation was increased in the subpallium, but the neuronal differentiation was blocked. Moreover, the dLGE region severely expanded ventrally at the expense of the vLGE, MGE, and septum. Finally, overexpressed VAX1 in the LGE progenitors strongly inhibits Gsx2 expression. Taken together, our findings show that Vax1 is crucial for subpallium regionalization by repressing Gsx2.

The striatum is structurally highly diverse, and its organ functionality critically depends on normal embryonic development. Although several studies have been conducted on the gene functional changes that occur during striatal development, a system-wide analysis of the underlying molecular changes is lacking. Here, we present a comprehensive transcriptome profile that allowed us to explore the trajectory of striatal development and identify the correlation between the striatal development and Huntington’s disease (HD). Furthermore, we applied an integrative transcriptomic profiling approach based on machine learning to systematically map a global landscape of 277 transcription factor (TF) networks. Most of these TF networks are linked to biological processes, and some unannotated genes provide information about the corresponding mechanisms. For example, we found that the Meis2 and Six3 were crucial for the survival of striatal neurons, which was verified using conditional knockout (CKO) mice. Finally, we used RNA-Seq to speculate their downstream targets.

The extraction of urban area's variation info from remote sensing image is an important step for monitoring and measuring urban change. In this paper, a structural method will construct for automatically extracting variation information of urban area. The methodology is constructed by L-Ratio method which is base on PCA, method of digital image processing (threshold value, mask layer and so on) and opening of mathematical morphology. It acquired a good experimental effect.

Generally the surround space constant of Retinex's center/surround algorithm is an empirical value that is between 25 and 250, and it is of small images. For the larger engineering images, how much should the parameter value be? In addition, in this algorithm, convolution is an operation whose efficiency is very low. It is a bottleneck that has impact on this algorithm's application in image engineering. How to solve this problem will have impact on the algorithm's application in the practical engineering.

Many monitoring and reconnaissance images are shot in night without auxiliary light, so those images are usually very dim and need enhancement processing which can be realized by Retinex with a good effect, but Retinex needs the color restoration. Based on the contrastive analysis on the RGB and the HSI color space, the differences, advantages and disadvantages are compared considering the transformation of Retinex algorithm from the RGB to the HSI to construct the SSRHSI algorithm to obtain the new effect on the color restoration.

Infrared color remote sensing is always possessed of the consequence. The level of the virescence is a quite important synthetic index for appraising a city, so infrared color remote sensing is brought into play to it's the important function in the application of detecting urban virescence. But in the city, ground- object complexity, high-building gather, a mass of shadows being, and numbers of color ground-object being. All of them are main disturbing source to extracting vegetation information. That is a topic of the day how resists their disturbance. This paper just about aim at the problems, to discuss Retinex helpfully to attaint goal that resisting disturbance of the hereinbefore disturbing sources in extracting vegetation information from infrared color remote sensing images.

Useful methods of urban vegetation coverage extraction on Kunming urban areas are proposed in the paper using advanced DMC imagery. The spectral response of typical ground objects has been studied and the methods of vegetation coverage extraction are developed to evaluate the accurate and reliable vegetation cover maps. The success of the project shows the methods presented in the paper are valid and useful. These approaches can be expanding to further extensive applications in remote sensing imagery.

At present, Mammography is one of the most effective methods to detect early breast cancers. However, the signs of most micro-calcifications that are the early signs of malignant tumours cannot appear clearly in an inhomogeneous background because of the complicated structures in breast. As a rule, a tool of magnified glass is required to enlarge mammograph views to check the characteristics of a suspected lesion, but there is at least 15 percent of breast cancer that is still missed. Without specific feature, when doctors have to relay on clinical histology, this will causes a large number of misdiagnosis with false negative or false positive even decrease the rate of detection, furthermore, causing pain to the patients. Therefore, it is a crucial task to need a reliable and effective approach to assist the micro-calcifications detection. This paper uses a new technology to extract micro-calcifications clusters with accurate edge effects to obtain much more hidden information which can't be detected by the naked eye on mammograms in order to help the doctors in diagnosing early breast cancer. In this paper, this research combines the findings of histopathology in benign or malignant calcifications and uses the typical application examples with the contrastive analysis to do a relevant expatiation.

The colored ground-object is one of main disturbance sources in the application of extracting urban vegetation information from infrared color aerial photograph. This paper presents a project to extract vegetation information from infrared color aerial photograph in Kunming. It is based on image segmentation and layered processing and adopts a means that multiple wave bands are used in the Normalized Difference Vegetation Index (NDVI). It is of not only efficiency but also low-complexity. The project gains better visual effect by resists colored ground-object's disturbance.