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Abstract Background Hypoxic-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. Methods By 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. Results Transplantation 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. Conclusions Transplanted 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.

Abstract Human stem cells and derivatives transplantation are widely used to treat nervous system diseases, while the fate determination of transplanted cells is not well elucidated. To explore cell fate changes of human brain organoids before and after transplantation, human brain organoids are transplanted into prefrontal cortex (PFC) and hippocampus (HIP), respectively. Single‐cell sequencing is then performed. According to time‐series sample comparison, transplanted cells mainly undergo neural development at 2 months post‐transplantation (MPT) and then glial development at 4MPT, respectively. A different brain region sample comparison shows that organoids grafted to PFC have obtained cell fate close to those of host cells in PFC, other than HIP, which may be regulated by the abundant expression of dopamine (DA) and acetylcholine (Ach) in PFC. Meanwhile, morphological complexity of human astrocyte grafts is greater in PFC than in HIP. DA and Ach both activate the calcium activity and increase morphological complexity of astrocytes in vitro. This study demonstrates that human brain organoids receive host niche factor regulation after transplantation, resulting in the alignment of grafted cell fate with implanted brain regions, which may contribute to a better understanding of cell transplantation and regenerative medicine.

Coastlines play a crucial role in coastal dynamics, and classifying their shape is an essential requirement for coastal analysis. With the development of Coastal Management Systems (CMS), structured and high-resolution vector-format coastlines have become increasingly available compared to remote sensing image coastlines. However, due to the challenges of accurate description and ambiguous classification rules, automatic classification of vector coastlines has been a difficult but urgent problem to solve. In this paper, we propose a data-driven approach for classifying the shape of vector coastlines, according to their morphological characteristics. The method utilizes a sequence-based deep learning algorithm to model and classify coastline segments. We construct a dataset including five representative types of vector coastlines, train and evaluate the model using this dataset. The evaluation results show that the proposed method outperforms all baselines, achieving a classification accuracy of 93.20%. This method can be integrated into existing Coastal Management Systems to enhance their morphological analysis functions, making a valuable contribution to the applications of Artificial Intelligence (AI) in coastal management.

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.

Carbon nanotubes (CNTs) had potential applications in energy conversion and storage devices, and it could be prepared by expanded graphite loaded with catalyst at high temperature, however, the mechanism of carbon nanotube growth in expanded graphite need further confirmation. In this work, carbon nanotubes’ in situ growth in expanded graphite (EG) were prepared via catalytic pyrolysis reaction using carbores P as a carbon source and Co(NO3)3•6H2O as a catalyst. The results of X-ray diffraction (XRD), scanning electron microscope (SEM) and energy dispersive X-ray spectroscope (EDS) indicated the carbon nanotubes could generate in, EG with the presence of carbores P as a carbon source and cobalt nitrate as a catalyst. More interestingly, the growth mechanism of carbon nanotubes could be concluded by the results of differential thermal analysis-thermogravimetry-mass spectrometry (DTA-TG-MS) and X-ray photoelectron spectroscopy (XPS) analysis. The pyrolysis products of carbores P were mainly hydrocarbon gas such as CH4 gas, which reacts with Co(NO3)3·6H2O catalyst to reduces CoOx to Co particles, then the carbon form pyrolysis was deposited the on the surface catalyst Co particles and, after continuous solid dissolution and precipitation, carbon nanotubes were at last generated in EG at last.

Summary: Brain-derived transcriptomes are known to correlate with resting-state brain activity in humans. Whether this association holds in nonhuman primates remains uncertain. Here, we search for such molecular correlates by integrating 757 transcriptomes derived from 100 macaque cortical regions with resting-state activity in separate conspecifics. We observe that 150 noncoding genes explain variations in resting-state activity at a comparable level with protein-coding genes. In-depth analysis of these noncoding genes reveals that they are connected to the function of nonneuronal cells such as oligodendrocytes. Co-expression network analysis finds that the modules of noncoding genes are linked to both autism and schizophrenia risk genes. Moreover, genes associated with resting-state noncoding genes are highly enriched in human resting-state functional genes and memory-effect genes, and their links with resting-state functional magnetic resonance imaging (fMRI) signals are altered in the brains of patients with autism. Our results highlight the potential for noncoding RNAs to explain resting-state activity in the nonhuman primate brain.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the seventh coronavirus (CoV) that has spread in humans and has become a global pandemic since late 2019. Efficient and accurate laboratory diagnostic methods are one of the crucial means to control the development of the current pandemic and to prevent potential future outbreaks. Although real-time reverse transcription-polymerase chain reaction (rRT-PCR) is the preferred laboratory method recommended by the World Health Organization (WHO) for diagnosing and screening SARS-CoV-2 infection, the versatile immunoassays still play an important role for pandemic control. They can be used not only as supplemental tools to identify cases missed by rRT-PCR, but also for first-line screening tests in areas with limited medical resources. Moreover, they are also indispensable tools for retrospective epidemiological surveys and the evaluation of the effectiveness of vaccination. In this review, we summarize the mainstream immunoassay methods for human coronaviruses (HCoVs) and address their benefits, limitations, and applications. Then, technical strategies based on bioinformatics and advanced biosensors were proposed to improve the performance of these methods. Finally, future suggestions and possibilities that can lead to higher sensitivity and specificity are provided for further research.

Summary: Oligodendrocyte spheroids (OL-spheroids) containing oligodendrocytes and neurons provide an accessible system to dissect demyelinating diseases and test therapeutic treatment. However, generation of human OL-spheroids is still technically challenging and time-consuming until now. Here, we presented evidence that overexpression of SOX10 and OLIG2 (SO) in human embryonic stem cells (hESCs)-derived ventral forebrain neural progenitors is sufficient to produce forebrain pre-oligodendrocytes (pre-OLs) and mature oligodendrocytes (OLs) within 20–40 days. More importantly, optimizing this procedure by overexpression of SO in ventral forebrain spheroids, we successfully generated OL-spheroids with pre-OLs, mature OLs, and neurons 40 days after OL-induction. We further demonstrated oligodendrocyte-neuron interactions and obvious axon myelination in OL-spheroids. Finally, over 30% cells developed into mature oligodendrocytes with forebrain identity and myelinate axons in mouse brain 3 months after transplantation. This study provides a strategy to generate forebrain OL-spheroids rapidly and efficiently which would facilitate development of new therapeutics for demyelinating disorders.

Accurate snow water equivalent (SWE) products are vital for monitoring hydrological processes and managing water resources effectively. However, the coarse spatial resolution (typically at 25 km from passive microwave remote sensing images) of the existing SWE products cannot meet the needs of explicit hydrological modeling. Linear regression ignores the spatial autocorrelation (SA) in the variables, and the measure of SA in the data assimilation algorithm is not explicit. This study develops a Resolution-enhanced Multifactor Eigenvector Spatial Filtering (RM-ESF) method to estimate daily SWE in the western United States based on a 6.25 km enhanced-resolution passive microwave record. The RM-ESF method is based on a brightness temperature gradience algorithm, incorporating not only factors including geolocation, environmental, topographical, and snow features but also eigenvectors generated from a spatial weights matrix to take SA into account. The results indicate that the SWE estimation from the RM-ESF method obviously outperforms other SWE products given its overall highest correlation coefficient (0.72) and lowest RMSE (56.70 mm) and MAE (43.88 mm), compared with the AMSR2 (0.33, 131.38 mm, and 115.45 mm), GlobSnow3 (0.50, 100.03 mm, and 83.58 mm), NCA-LDAS (0.48, 98.80 mm, and 81.94 mm), and ERA5 (0.65, 67.33 mm, and 51.82 mm), respectively. The RM-ESF model considers SA effectively and estimates SWE at a resolution of 6.25 km, which provides a feasible and efficient approach for SWE estimation with higher precision and finer spatial resolution.

Human pluripotent stem cell–based (hPSC-based) replacement therapy holds great promise for the treatment of Parkinson’s disease (PD). However, the heterogeneity of hPSC-derived donor cells and the low yield of midbrain dopaminergic (mDA) neurons after transplantation hinder its broad clinical application. Here, we have characterized the single-cell molecular landscape during mDA neuron differentiation. We found that this process recapitulated the development of multiple but adjacent fetal brain regions including the ventral midbrain, the isthmus, and the ventral hindbrain, resulting in a heterogenous donor cell population. We reconstructed the differentiation trajectory of the mDA lineage and identified calsyntenin 2 (CLSTN2) and protein tyrosine phosphatase receptor type O (PTPRO) as specific surface markers of mDA progenitors, which were predictive of mDA neuron differentiation and could facilitate high enrichment of mDA neurons (up to 80%) following progenitor cell sorting and transplantation. Marker-sorted progenitors exhibited higher therapeutic potency in correcting motor deficits of PD mice. Different marker-sorted grafts had a strikingly consistent cellular composition, in which mDA neurons were enriched, while off-target neuron types were mostly depleted, suggesting stable graft outcomes. Our study provides a better understanding of cellular heterogeneity during mDA neuron differentiation and establishes a strategy to generate highly purified donor cells to achieve stable and predictable therapeutic outcomes, raising the prospect of hPSC-based PD cell replacement therapies.

FastCloning, a reliable cloning technique for plasmid construction, is a widely used protocol in biomedical research laboratories. Only two-step molecular manipulations are required to add a gene (cDNA) of interest into the desired vector. However, parallel cloning of the gene into multiple vectors is still a labor-intensive operation, which requires a range of primers for different vectors in high-throughput cloning projects. The situation could even be worse if multiple fragments of DNA are required to be added into one plasmid. Here, we describe a high-throughput FastCloning (HTFC) method, a protocol for parallel cloning by adding an adaptor sequence into all vectors. The target gene and vectors were PCR amplified separately to obtain the insert product and linear vectors with 18-base overlapping at each end of the DNAs required for FastCloning. Furthermore, a method for generating polycistronic bacterial constructs based on the same strategy as that used for HTFC was developed. Thus, the HTFC technique is a simple, effective, reliable, and low-cost tool for parallel cloning.

The scale of digital elevation models (DEMs) is vital for terrain analysis, surface simulation, and other geographic applications. Compared to traditional super-resolution (SR) methods, deep convolutional neural networks (CNNs) have shown great success in DEM SR. However, in terms of these CNN-based SR methods, the features extracted by the stackable residual modules cannot be fully utilized as the depth of the network increases. Therefore, our study proposes an enhanced residual feature fusion network (ERFFN) for DEM SR. The designed residual fusion module groups four residual modules to make better use of the local residual features. Meanwhile, the residual structure is refined by inserting a lightweight enhanced spatial residual attention module into each basic residual block to further strengthen the efficiency of the network. Considering the continuity of terrain features, terrain weight modules are integrated into the loss module. Based on two large-scale datasets, our ERFFN shows a 10–20% reduction in the mean absolute error and the lowest error in terrain features, such as slope, demonstrating the superiority of an ERFFN-based DEM SR over state-of-the-art methods. Finally, to demonstrate potential value in real-world applications, we deploy the ERFFN to reconstruct a large geographic area covering 44,000 km2 which contains missing parts.

Linear regression models are commonly used for estimating ground PM2.5 concentrations, but the global spatial autocorrelation and local spatial heterogeneity of PM2.5 distribution are either ignored or only partially considered in commonly used models for estimating PM2.5 concentrations. Therefore, taking both global spatial autocorrelation and local spatial heterogeneity into consideration, a global-local regression (GLR) model is proposed for estimating ground PM2.5 concentrations in the Yangtze River Delta (YRD) and in the Beijing, Tianjin, Hebei (BTH) regions of China based on the aerosol optical depth data, meteorological data, remote sensing data, and pollution source data. Considering the global spatial autocorrelation, the GLR model extracts global factors by the eigenvector spatial filtering (ESF) method, and combines the fraction of them that passes further filtering with the geographically weighted regression (GWR) method to address the local spatial heterogeneity. Comprehensive results show that the GLR model outperforms the ordinary GWR and ESF models, and the GLR model has the best performance at the monthly, seasonal, and annual levels. The average adjusted R2 of the monthly GLR model in the YRD region (the BTH region) is 0.620 (0.853), which is 8.0% and 7.4% (6.8% and 7.0%) higher than that of the monthly ESF and GWR models, respectively. The average cross-validation root mean square error of the monthly GLR model is 7.024 μg/m3 in the YRD region, and 9.499 μg/m3 in the BTH region, which is lower than that of the ESF and GWR models. The GLR model can effectively address the spatial autocorrelation and spatial heterogeneity, and overcome the shortcoming of the ordinary GWR model that overfocuses on local features and the disadvantage of the poor local performance of the ordinary ESF model. Overall, the GLR model with good spatial and temporal applicability is a promising method for estimating PM2.5 concentrations.

To develop a disease model for the human Alström Syndrome (AS), we used the episomal reprogramming system and CRISPR/Cas9 technology to generate an induced pluripotent stem cell (iPSC) line with the compound heterozygous patient mutation (ALMS1 c.3902C > A, c.6436C > T) along with an isogenic gene-corrected control iPSC line. Both iPSC lines showed normal karyotype, expressed pluripotent markers, and differentiated into cells of three embryonic germ layer. These AS mutant and isogenic iPSC control line will be of great use in investigating the disease mechanisms, drug screening and treatment in patients.

Summary: Long-term potentiation and depression, inferred from analysis on brain slices, are considered the cellular processes underlying learning and memory formation. They have not so far been demonstrated in human stem cell-derived neurons. By expressing channelrhodopsin in hESCs-derived glutamate neurons and co-culturing them with GABA neurons, we found that blue light stimulation increased the frequency of miniature excitatory postsynaptic currents (mEPSCs) and decreased the ratio of paired pulse facilitation (PPF) in non-ChR2-expressing GABA neurons, indicating a facilitating action at the presynaptic terminals. When paired with postsynaptic depolarization, the repetitive stimulation significantly increased the amplitude of light-evoked EPSCs that persisted during the period, indicating long-term potentiation (LTP). In contrast, low-frequency light stimulation induced long-term depression (LTD). These effects were blocked by N-methyl-D-aspartic acid (NMDA) receptor antagonists, suggesting NMDA receptor-mediated synaptic plasticity in human neural networks. Furthermore, induced pluripotent stem cell (iPSC)-derived neurons of patient with Down syndrome showed absence of LTP or LTD. Thus, our platform offers a versatile model for assessing human neural plasticity under physiological and pathological conditions. : Neuroscience; Cellular Neuroscience; Techniques in Neuroscience Subject Areas: Neuroscience, Cellular Neuroscience, Techniques in Neuroscience

Human GABAergic interneurons (GIN) are implicated in normal brain function and in numerous mental disorders. However, the generation of functional human GIN subtypes from human pluripotent stem cells (hPSCs) has not been established. By expressing LHX6, a transcriptional factor that is critical for GIN development, we induced hPSCs to form GINs, including somatostatin (SST, 29%) and parvalbumin (PV, 21%) neurons. Our RNAseq results also confirmed the alteration of GIN identity with the overexpression of LHX6. Five months after transplantation into the mouse brain, the human GABA precursors generated increased population of SST and PV neurons by overexpressing LHX6. Importantly, the grafted human GINs exhibited functional electrophysiological properties and even fast-spiking-like action potentials. Thus, expression of the single transcription factor LHX6 under our GIN differentiation condition is sufficient to robustly induce human PV and SST subtypes.

Rectangular short-crested weirs are widely used for simple structure and high discharge capacity. As one of the most important and influential factors of discharge capacity, side slope can improve the hydraulic characteristics of weirs at special conditions. In order to systemically study the effects of upstream and downstream slope coefficients S1 and S2 on overflow discharge coefficient in a rectangular short-crested weir the Volume of Fluid (VOF) method and the Renormalization Group (RNG) κ-ε turbulence model are used. In this study, the slope coefficient ranges from V to 3H:1V and each model corresponds to five total energy heads of H0 ranging from 8.0 to 24.0 cm. Comparisons of discharge coefficients and free surface profiles between simulated and laboratory results display a good agreement. The simulated results show that the difference of discharge coefficients will decrease with upstream slopes and increase with downstream slopes as H0 increases. For a given H0, the discharge coefficient has a convex parabolic relation with S1 and a piecewise linearity relation with S2. The maximum discharge coefficient is always obtained at S2 = 0.8. There exists a difference between upstream and downstream slope coefficients in the influence range of free surface curvatures. Furthermore, a proposed discharge coefficient equation by nonlinear regression is a function of upstream and downstream slope coefficients.

The G protein-coupled receptor kinases (GRKs) phosphorylate agonist occupied G protein-coupled receptors (GPCRs) and desensitize GPCR-mediated signaling. Recent studies indicate they also function non-catalytically via interaction with other proteins. In this study, a proteomic approach was used to screen interacting proteins of GRK5 in MDA-MB-231 cells and HUVEC cells. Mass spectrometry analysis reveals several proteins in the GRK5 immunocomplex including damaged DNA-binding protein 1 (DDB1), an adaptor subunit of the CUL4-ROC1 E3 ubiquitin ligase complex. Co-immunoprecipitation experiments confirmed the association of GRK5 with DDB1-CUL4 complex, and reveal that DDB1 acts as an adapter to link GRK5 to CUL4 to form the complex. Overexpression of DDB1 promoted, whereas knockdown of DDB1 inhibited the ubiquitination of GRK5, and the degradation of GRK5 was reduced in cells deficient of DDB1. Furthermore, the depletion of DDB1 decreased Hsp90 inhibitor-induced GRK5 destabilization and UV irradiation-induced GRK5 degradation. Thus, our study identified potential GRK5 interacting proteins, and reveals the association of GRK5 with DDB1 in cell and the regulation of GRK5 level by DDB1-CUL4 ubiquitin ligase complex-dependent proteolysis pathway.