Search

Abstract Background The integration of 7 Tesla (7T) magnetic resonance imaging (MRI) with advanced multimodal artificial intelligence (AI) models represents a promising frontier in neuroimaging. The superior spatial resolution of 7TMRI provides detailed visualizations of brain structure, which are crucial forunderstanding complex central nervous system diseases and tumors. Concurrently, the application of multimodal AI to medical images enables interactive imaging‐based diagnostic conversation. Methods In this paper, we systematically investigate the capacity and feasibility of applying the existing advanced multimodal AI model ChatGPT‐4V to 7T MRI under the context of brain tumors. First, we test whether ChatGPT‐4V has knowledge about 7T MRI, and whether it can differentiate 7T MRI from 3T MRI. In addition, we explore whether ChatGPT‐4V can recognize different 7T MRI modalities and whether it can correctly offer diagnosis of tumors based on single or multiple modality 7T MRI. Results ChatGPT‐4V exhibited accuracy of 84.4% in 3T‐vs‐7T differentiation and accuracy of 78.9% in 7T modality recognition. Meanwhile, in a human evaluation with three clinical experts, ChatGPT obtained average scores of 9.27/20 in single modality‐based diagnosis and 21.25/25 in multiple modality‐based diagnosis. Our study indicates that single‐modality diagnosis and the interpretability of diagnostic decisions in clinical practice should be enhanced when ChatGPT‐4V is applied to 7T data. Conclusions In general, our analysis suggests that such integration has promise as a tool to improve the workflow of diagnostics in neurology, with a potentially transformative impact in the fields of medical image analysis and patient management.

Abstract The heterogeneous molecular subtypes of gliomas demonstrate varied responses to chemotherapy and distinct prognostic outcomes. Gliomas with Isocitrate dehydrogenase 1 (IDH1) mutation are associated with better outcomes and are more responsive to temozolomide (TMZ) compared to those without IDH1 mutation. IDH1-mutant gliomas elevate D-2-hydroxyglutarate (D-2HG) levels, with potential dual effects on tumor progression. Limited research has explored the potential anti-glioma effects of D-2HG in combination with TMZ. Clinical data from over 2500 glioma patients in our study confirms that those with IDH1 mutations exhibit enhanced responsiveness to TMZ chemotherapy and a significantly better prognosis compared to IDH1 wild-type patients. In subsequent cellular experiments, we found that the IDH1-mutant metabolite D-2HG suppresses Integrin subunit beta 4 (ITGB4) expression, and down-regulate the phosphorylation levels of PI3K and AKT, ultimately inhibiting cell proliferation while promoting apoptosis, thereby improving glioma prognosis. Additionally, we have demonstrated the synergistic effect of D-2HG and TMZ in anti-glioma therapy involved inhibiting the proliferation of glioma cells and promoting apoptosis. Finally, by integrating data from the CGGA and TCGA databases, it was validated that ITGB4 expression was lower in IDH1-mutant gliomas, and patients with lower ITGB4 expression were associated with better prognosis. These findings indicate that ITGB4 may be a promising therapeutic target for gliomas and D-2HG inhibits proliferation and sensitizes glioma to temozolomide via down-regulating ITGB4/PI3K/AKT. These findings drive theoretical innovation and research progress in glioma therapy.

Abstract Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

Abstract Gliomas are highly heterogenous diseases with poor prognosis. Precise survival prediction could benefit further clinical decision‐making, clinical trial incursion, and health economics. Recent research has emphasized the prognostic value of magnetic resonance imaging, pathological specimens, and circulating biomarkers. However, the integrative potential and efficacy of these modalities require to be further validated. After incorporating 218 patients of The Cancer Genome Atlas glioma datasets of and 54 patients of the Huashan cohort with complementary prognostic information, we established a squeeze‐and‐excitation deep learning feature extractor for T1‐contrast enhanced images and histological slides and explored to screen significant circulating 5‐hydroxymethylcytosines (5hmC) profiles for glioma survival by least absolute shrinkage and selection operator‐Cox regression. Therefore, a prognostication predictive model with high efficiency was obtained through survival support vector machine multimodal integration of radiologic imaging, histopathologic imaging features, genome‐wide 5hmC in circulating cell‐free DNA and clinical variables, suggesting a valid strategy (concordance‐index = 0.897; Brier score = 0.118) for improved survival risk stratification of glioma patients.

Abstract Engineered whole lungs may one day expand therapeutic options for patients with end-stage lung disease. However, the feasibility of ex vivo lung regeneration remains limited by the inability to recapitulate mature, functional alveolar epithelium. Here, we modulate multimodal components of the alveolar epithelial type 2 cell (AEC2) niche in decellularized lung scaffolds in order to guide AEC2 behavior for epithelial regeneration. First, endothelial cells coordinate with fibroblasts, in the presence of soluble growth and maturation factors, to promote alveolar scaffold population with surfactant-secreting AEC2s. Subsequent withdrawal of Wnt and FGF agonism synergizes with tidal-magnitude mechanical strain to induce the differentiation of AEC2s to squamous type 1 AECs (AEC1s) in cultured alveoli, in situ. These results outline a rational strategy to engineer an epithelium of AEC2s and AEC1s contained within epithelial-mesenchymal-endothelial alveolar-like units, and highlight the critical interplay amongst cellular, biochemical, and mechanical niche cues within the reconstituting alveolus.

Background and goalNoninvasive prediction of isocitrate dehydrogenase (IDH) mutation status in glioma guides surgical strategies and individualized management. We explored the capability on preoperatively identifying IDH status of combining a convolutional neural network (CNN) and a novel imaging modality, ultra-high field 7.0 Tesla (T) chemical exchange saturation transfer (CEST) imaging.MethodWe enrolled 84 glioma patients of different tumor grades in this retrospective study. Amide proton transfer CEST and structural Magnetic Resonance (MR) imaging at 7T were performed preoperatively, and the tumor regions are manually segmented, leading to the “annotation” maps that offers the location and shape information of the tumors. The tumor region slices in CEST and T1 images were further cropped out as samples and combined with the annotation maps, which were inputted to a 2D CNN model for generating IDH predictions. Further comparison analysis to radiomics-based prediction methods was performed to demonstrate the crucial role of CNN for predicting IDH based on CEST and T1 images.ResultsA fivefold cross-validation was performed on the 84 patients and 4090 slices. We observed a model based on only CEST achieved accuracy of 74.01% ± 1.15%, and the area under the curve (AUC) of 0.8022 ± 0.0147. When using T1 image only, the prediction performances dropped to accuracy of 72.52% ± 1.12% and AUC of 0.7904 ± 0.0214, which indicates no superiority of CEST over T1. However, when we combined CEST and T1 together with the annotation maps, the performances of the CNN model were further boosted to accuracy of 82.94% ± 1.23% and AUC of 0.8868 ± 0.0055, suggesting the importance of a joint analysis of CEST and T1. Finally, using the same inputs, the CNN-based predictions achieved significantly improved performances above those from radiomics-based predictions (logistic regression and support vector machine) by 10% to 20% in all metrics.Conclusion7T CEST and structural MRI jointly offer improved sensitivity and specificity of preoperative non-invasive imaging for the diagnosis of IDH mutation status. As the first study of CNN model on imaging acquired at ultra-high field MR, our results could demonstrate the potential of combining ultra-high-field CEST and CNN for facilitating decision-making in clinical practice. However, due to the limited cases and B1 inhomogeneities, the accuracy of this model will be improved in our further study.

Abstract This paper describes the 3D printing of a ternary composite of polydimethylsiloxane (PDMS) and nanoparticles of iron oxide and barium titanate. The composite was printed using a commercially available 3D printer. Thermal curing of the composite during printing allowed for overall low process times of a few minutes. Scanning electron microscopy indicated uniform composite layers. The resulting composite films showed ferromagnetic behaviour, and applicability in magnetic actuation and piezoelectric energy harvesting.

Cerebral neoplasms like gliomas may cause intracranial pressure increasing, neural tract deviation, infiltration, or destruction in peritumoral areas, leading to neuro-functional deficits. Novel tracking technology, such as DTI, can objectively reveal and visualize three-dimensional white matter trajectories; in combination with intraoperative navigation, it can help achieve maximum resection whilst minimizing neurological deficit. Since the reconstruction of DTI raw data largely relies on the technical engineering and anatomical experience of the operator; it is time-consuming and prone to operator-induced bias. Here, we develop new user-friendly software to automatically segment and reconstruct functionally active areas to facilitate precise surgery. In this pilot trial, we used an in-house developed software (DiffusionGo) specially designed for neurosurgeons, which integrated a reliable diffusion-weighted image (DWI) preprocessing pipeline that embedded several functionalities from software packages of FSL, MRtrix3, and ANTs. The preprocessing pipeline is as follows: 1. DWI denoising, 2. Gibbs-ringing removing, 3. Susceptibility distortion correction (process if opposite polarity data were acquired), 4. Eddy current and motion correction, and 5. Bias correction. Then, this fully automatic multiple assigned criteria algorithms for fiber tracking were used to achieve easy modeling and assist precision surgery. We demonstrated the application with three language-related cases in three different centers, including a left frontal, a left temporal, and a left frontal-temporal glioma, to achieve a favorable surgical outcome with language function preservation or recovery. The DTI tracking result using DiffusionGo showed robust consistency with direct cortical stimulation (DCS) finding. We believe that this fully automatic processing pipeline provides the neurosurgeon with a solution that may reduce time costs and operating errors and improve care quality and surgical procedure quality across different neurosurgical centers.

Tracheal replacement using tissue engineering technologies offers great potential to improve previously intractable clinical interventions, and interest in this area has increased in recent years. Many engineered airway constructs currently rely on decellularized native tracheas to serve as the scaffold for tissue repair. Yet, mechanical failure leading to airway narrowing and collapse remains a major cause of morbidity and mortality following clinical implantation of decellularized tracheal grafts. To understand better the factors contributing to mechanical failure in vivo, we characterized the histo-mechanical properties of tracheas following two different decellularization protocols, including one that has been used clinically. All decellularized tracheas deviated from native mechanical behavior, which may provide insights into observed in vivo graft failures. We further analyzed protein content by western blot and analyzed microstructure by histological staining and found that the specific method of decellularization resulted in significant differences in the depletion of proteoglycans and degradation of collagens I, II, III, and elastin. Taken together, this work demonstrates that the heterogeneous architecture and mechanical behavior of the trachea is severely compromised by decellularization. Such structural deterioration may contribute to graft failure clinically and limit the potential of decellularized native tracheas as viable long-term orthotopic airway replacements.

China is currently experiencing a severe issue of excessive fertilization. Variable rate fertilization (VRF) technology is key to solving this issue in precision agriculture, and one way to implement VRF is through management zone (MZ) delineation. This study is aimed at evaluating the feasibility and potential benefits of VRF based on site-specific MZs in smallholder farm fields. This study determined the amounts of basal and top-dressing fertilizers in different spatial units, based on soil nutrient MZs and crop growth MZs, respectively. The potential agronomic, economic, and environmental advantages of spatial variable rate fertilization were further assessed by comparing the farmer’s treatment, the expert’s treatment, and the variable rate fertilization treatment based on management zones (VR-MZ). The results showed that VR-MZ reduced the use of nitrogen (N), phosphorus (P), and potassium (K) fertilizers by 22.90–43.95%, 59.11–100%, and 8.21–100%, respectively, and it also increased the use efficiency of N, P, and K by 12.27–28.71, 89.64–176.85, and 5.48–266.89 kg/kg, respectively, without yield loss. The net incomes of VR-MZ were 15.5–449.61 USD ha−1 higher than that of traditional spatially uniform rate fertilization. Meanwhile, less nitrous oxide emission (23.50–45.81%), ammonia volatilization (19.38–51.60%), and nitrate ion leaching amounts (28.77–53.98%) were found in VR-MZ compared to those in uniform fertilization. The results suggest that the VR-MZ has great potential for saving fertilizers, significantly increasing farmers’ net income, reducing environmental pollution, and promoting the sustainable use of resources. This study provides a theoretical basis and technical support for exploring a VRF suitable for village-scale farming.

BackgroundCrohn’s disease (CD) is a type of heterogeneous, dysfunctional immune-mediated intestinal chronic and recurrent inflammation caused by a variety of etiologies. Cuproptosis is a newly discovered form of programmed cell death that seems to contribute to the advancement of a variety of illnesses. Consequently, the major purpose of our research was to examine the role of cuproptosis-related genes in CD.MethodsWe obtained two CD datasets from the gene expression omnibus (GEO) database, and immune cell infiltration was created to investigate immune cell dysregulation in CD. Based on differentially expressed genes (DEGs) and the cuproptosis gene set, differentially expressed genes of cuproptosis (CuDEGs) were found. Then, candidate hub cuproptosis-associated genes were found using machine learning methods. Subsequently, using 437 CD samples, we explored two distinct subclusters based on hub cuproptosis-related genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, Gene set variation analysis (GSVA) and immune infiltration analysis studies were also used to assess the distinct roles of the subclusters.ResultsOverall, 25 CuDEGs were identified, including ABCB6, BACE1, FDX1, GLS, LIAS, MT1M, PDHA1, etc. And most CuDEGs were expressed at lower levels in CD samples and were negatively related to immune cell infiltration. Through the machine learning algorithms, a seven gene cuproptosis-signature was identified and two cuproptosis-related subclusters were defined. Cluster-specific differentially expressed genes were found only in one cluster, and functional analysis revealed that they were involved in several immune response processes. And the results of GSVA showed positive significant enrichment in immune-related pathways in cluster A, while positive significant enrichment in metabolic pathways in cluster B. In addition, an immune infiltration study indicated substantial variation in immunity across different groups. Immunological scores were higher and immune infiltration was more prevalent in Cluster A.ConclusionAccording to the current research, the cuproptosis phenomenon occurs in CD and is correlated with immune cell infiltration and metabolic activity. This information indicates that cuproptosis may promote CD progression by inducing immunological response and metabolic dysfunction. This research has opened new avenues for investigating the causes of CD and developing potential therapeutic targets for the disease.

BackgroundGliomas are the most malignant central nervous system tumors. With the development of sequencing technology, more potential biomarkers related to the treatment, prognosis, and molecular classification of glioma have been identified. Here, we intend to investigate the potential biological function and clinical value of a new biomarker in glioma.MethodsKDELR1 expression data and the corresponding clinical information were downloaded from public databases and then preprocessed using R language. Correlation, Kaplan–Meier survival, and Cox regression analyses were performed to explore the clinical significance of KDELR1 in glioma patients. Furthermore, the immune infiltration and microenvironment parameters were evaluated via TIMER and CIBERSORT. Immunohistochemistry was conducted to confirm the KDELR1 expression and its correlation with immunity infiltration and prognosis.ResultsKDELR1 was upregulated in glioma samples compared with normal brain tissues, and its expression was significantly correlated with age, the World Health Organization (WHO) grade, recurrence, necrosis, microvascular proliferation, molecular classification, isocitrate dehydrogenase (IDH) mutation, and 1p/19q codeletion status. In addition, survival analysis showed that glioma patients with KDELR1 overexpression had shorter overall survival (OS) and disease-free survival times, and Cox regression analysis revealed that KDELR1 acted as an independent prognostic factor of OS in glioma patients. Gene set enrichment analysis indicated a significant enrichment of metabolism-associated pathways. KDELR1 expression was positively associated with immune infiltration (including infiltration by CD8+ T cells, CD4+ T cells, macrophages, and so on) and microenvironment parameters (including stromal, immune, and ESTIMATE scores) in gliomas. The expression of KDELR1 and its correlation with the tumor grade and prognosis were confirmed by immunohistochemistry in clinical samples (n = 119, P < 0.05).ConclusionsTaken together, these findings suggest that KDELR1 is correlated with the tumor grade, molecular classifications, and immune infiltration; highlighting that KDELR1 is a novel and promising biomarker for molecular classification, treatment, and prognostic assessment may further indicate the treating effect of immune therapy.

Abstract Introduction Chronic cerebral hypoperfusion has been considered the etiology for sporadic Alzheimer's disease (AD). However, no valid clinical evidence exists due to the similar risk factors between cerebrovascular disease and AD. Methods We used moyamoya disease (MMD) as a model of chronic hypoperfusion and cognitive impairment, without other etiology interference. Results Based on the previous reports and preliminary findings, we hypothesized that chronic cerebral hypoperfusion could be an independent upstream crucial variable, resulting in AD, and induce pathological hallmarks such as amyloid beta peptide and hyperphosphorylated tau accumulation. Discussion Timely intervention with revascularisation would help reverse the brain damage with AD hallmarks and lead to cognitive improvement.

The development of an in vitro system for the study of lung vascular disease is critical to understanding human pathologies. Conventional culture systems fail to fully recapitulate native microenvironmental conditions and are typically limited in their ability to represent human pathophysiology for the study of disease and drug mechanisms. Whole organ decellularization provides a means to developing a construct that recapitulates structural, mechanical, and biological features of a complete vascular structure. Here, we developed a culture protocol to improve endothelial cell coverage in whole lung scaffolds and used single-cell RNA-sequencing analysis to explore the impact of decellularized whole lung scaffolds on endothelial phenotypes and functions in a biomimetic bioreactor system. Intriguingly, we found that the phenotype and functional signals of primary pulmonary microvascular revert back—at least partially—toward native lung endothelium. Additionally, human induced pluripotent stem cell-derived endothelium cultured in decellularized lung systems start to gain various native human endothelial phenotypes. Vascular barrier function was partially restored, while small capillaries remained patent in endothelial cell-repopulated lungs. To evaluate the ability of the engineered endothelium to modulate permeability in response to exogenous stimuli, lipopolysaccharide (LPS) was introduced into repopulated lungs to simulate acute lung injury. After LPS treatment, proinflammatory signals were significantly increased and the vascular barrier was impaired. Taken together, these results demonstrate a novel platform that recapitulates some pulmonary microvascular functions and phenotypes at a whole organ level. This development may help pave the way for using the whole organ engineering approach to model vascular diseases.

Soil is characterized by high spatiotemporal variability due to the combined influence of internal and external factors. The most efficient approach for addressing spatial variability is the use of management zones (MZs). Common approaches for delineating MZs include K-means and fuzzy C-means cluster analysis algorithms. However, these clustering methods have been used to delineate MZs independent of the spatial dependence of soil variables. Thus, the accuracy of the clustering results has been limited. In this study, six soil variables (soil pH, total nitrogen, organic matter, available phosphorus, available potassium, and soil apparent electrical conductivity) were used to characterize the spatial variability within a representative village in Suining County, Jiangsu Province, China. Two variable reduction techniques (PCA, multivariate spatial analysis based on Moran’s index; MULTISPATI-PCA) and three different clustering algorithms (fuzzy C-means clustering, iterative self-organizing data analysis techniques algorithm, and Gaussian mixture model; GMM) were used to optimize the MZ delineation. Different clustering model composites were evaluated using yield data collected after the wheat harvest in 2020. The results indicated that the variable reduction technologies in conjunction with clustering algorithms provided better performance in MZ delineation, with average silhouette coefficient (ASC) and variance reduction (VR) of 0.48–0.57, and 13.35–23.13%, respectively. Moreover, the MULTISPATI-PCA approach was more conducive to identifying variables requiring MZ delineation than traditional PCA methods. Combining MULTISPATI-PCA and the GMM algorithm yielded the greatest VR and ASC values in this study. These results can guide the optimization of MZ delineation in intensive agricultural systems, thus enabling more precise nutrient management.

For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST and MRS to predict glioma infiltration. Eighteen glioma patients of different tumor grades were enrolled in this study; 18F-fluoroethyltyrosine (FET)-PET, amide proton transfer CEST at 7 Tesla(T), MRS and conventional MR at 3T were conducted preoperatively. Multi modalities and their association were evaluated using Pearson correlation analysis patient-wise and voxel-wise. Both CEST (R = 0.736, p < 0.001) and MRS (R = 0.495, p = 0.037) correlated with FET-PET, while the correlation between CEST and MRS was weaker. In subgroup analysis, APT values were significantly higher in high grade glioma (3.923 ± 1.239) and IDH wildtype group (3.932 ± 1.264) than low grade glioma (3.317 ± 0.868, p < 0.001) or IDH mutant group (3.358 ± 0.847, p < 0.001). Using high FET uptake as the standard, the CEST/MRS combination (AUC, 95% CI: 0.910, 0.907–0.913) predicted tumor infiltration better than CEST (0.812, 0.808–0.815) or MRS (0.888, 0.885–0.891) alone, consistent with contrast-enhancing and T2-hyperintense areas. Probability maps of tumor presence constructed from the CEST/MRS combination were preliminarily verified by multi-region biopsies. The combination of 7T CEST/MRS might serve as a promising non-radioactive alternative to delineate glioma infiltration, thus reshaping the guidance for tumor resection and irradiation.

Summary: Cell-based therapies have shown promise for treating myriad chronic pulmonary diseases through direct application of epithelial progenitors or by way of engineered tissue grafts or whole organs. To elucidate environmental effects on epithelial regenerative outcomes in vitro, here, we isolate and culture a population of pharmacologically expanded basal cells (peBCs) from rat tracheas. At peak basal marker expression, we simultaneously split peBCs into four in vitro platforms: organoid, air-liquid interface (ALI), engineered trachea, and engineered lung. Following differentiation, these samples are evaluated using single-cell RNA sequencing (scRNA-seq) and computational pipelines are developed to compare samples both globally and at the population level. A sample of native rat tracheal epithelium is also evaluated by scRNA-seq as a control for engineered epithelium. Overall, this work identifies platform-specific effects that support the use of engineered models to achieve the most physiologic differential outcomes in pulmonary epithelial regenerative applications. : Greaney et al. compare pulmonary epithelial regeneration across multiple modalities in vitro, finding that decellularized scaffolds achieved the most physiologic differentiation over more artificial platforms. scRNA-seq enables high-resolution comparison between engineered and native cell populations, thereby better gauging progress toward the generation of a tissue that may function on implantation. Keywords: Pulmonary Cell Biology, Regenerative Medicine, Tissue Engineering, Primary Epithelial Cells

Smooth muscle cells (SMCs) are key regulators of vascular disease and circulating smooth muscle progenitor cells may play important roles in vascular repair or remodelling. We developed enhanced protocols to derive smooth muscle progenitors from murine bone marrow and tested whether factors that are increased in atherosclerotic plaques, namely platelet-derived growth factor-BB (PDGF-BB) and monomeric collagen, can influence the smooth muscle specific differentiation, proliferation, and survival of mouse bone marrow-derived progenitor cells. During a 21 day period of culture, bone marrow cells underwent a marked increase in expression of the SMC markers α-SMA (1.93 ± 0.15 vs. 0.0008 ± 0.0003 (ng/ng GAPDH) at 0 d), SM22-α (1.50 ± 0.27 vs. 0.005 ± 0.001 (ng/ng GAPDH) at 0 d) and SM-MHC (0.017 ± 0.004 vs. 0.001 ± 0.001 (ng/ng GAPDH) at 0 d). Bromodeoxyuridine (BrdU) incorporation experiments showed that in early culture, the smooth muscle progenitor subpopulation could be identified by high proliferative rates prior to the expression of smooth muscle specific markers. Culture of fresh bone marrow or smooth muscle progenitor cells with PDGF-BB suppressed the expression of α-SMA and SM22-α, in a rapidly reversible manner requiring PDGF receptor kinase activity. Progenitors cultured on polymerized collagen gels demonstrated expression of SMC markers, rates of proliferation and apoptosis similar to that of cells on tissue culture plastic; in contrast, cells grown on monomeric collagen gels displayed lower SMC marker expression, lower growth rates (319 ± 36 vs. 635 ± 97 cells/mm2), and increased apoptosis (5.3 ± 1.6% vs. 1.0 ± 0.5% (Annexin 5 staining)). Our data shows that the differentiation and survival of smooth muscle progenitors are critically affected by PDGF-BB and as well as the substrate collagen structure.

Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy-and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware. [ABSTRACT FROM AUTHOR]

Iron content in gasification slag is second only to silicon and aluminum, which is expected to be a new breakthrough in the integrated application of gasification slag. Magnetization roasting is an efficient method to change the form of iron-containing phases as well as to enhance magnetic properties from slags. The magnetic variation of different particle size fractions of gasification slags (GS1, GS2) during roasting was investigated by the yield of magnetic ash particles. The magnetic transformation mechanism of iron-containing phases was revealed by the vibrating sample magnetometer (VSM), X–ray diffractometer (XRD), and scanning electron microscopy with energy-dispersive spectrometry (SEM–EDS). The results showed that the magnetic ash particle yield rose as the roasting temperature increased. When the roasting temperature was 750°C, the magnetic ash particle yield of each particle size fractions increased from 14%–21% (GS1) and 7%–18% (GS2) to 81%–99% and 29%–96%, respectively. Specially, the magnetic ash particle yield of 0.125–0.074 mm fractions increased from 21% (GS1) and 18% (GS2) to 98% and 94%, and the saturation magnetization increased from 1.80 emu/g (GS1) and 5.45 emu/g (GS2) to 10.25 emu/g and 8.23 emu/g, under the conditions of 750°C (roasting temperature), 30 min (roasting time) and 2.5 A (magnetic excitation current) when the gasification slag was roasted in air, a part of iron–containing phases was transformed from Fe(II) to Fe3O4 and γ-Fe2O3, another part of iron-containing phases could be substituted into the feldspar and pyroxene minerals by homogeneous substitution. Furthermore, residue carbon combustion and gas diffusion lead to reduction of ash particle size, rough and porous surface, and increase of magnetization reaction sites, which can strengthen the mass transfer process and promote magnetic transformation of iron-containing phases in slags. [ABSTRACT FROM AUTHOR]