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Glioblastoma multiforme (GBM), a highly malignant and heterogeneous brain tumor, contains various types of tumor and non-tumor cells. Whether GBM cells can trans-differentiate into non-neural cell types, including mural cells or endothelial cells (ECs), to support tumor growth and invasion remains controversial. Here we generated two genetic GBM models de novo in immunocompetent mouse brains, mimicking essential pathological and molecular features of human GBMs. Lineage-tracing and transplantation studies demonstrated that, although blood vessels in GBM brains underwent drastic remodeling, evidence of trans-differentiation of GBM cells into vascular cells was barely detected. Intriguingly, GBM cells could promiscuously express markers for mural cells during gliomagenesis. Furthermore, single-cell RNA sequencing showed that patterns of copy number variations (CNVs) of mural cells and ECs were distinct from those of GBM cells, indicating discrete origins of GBM cells and vascular components. Importantly, single-cell CNV analysis of human GBM specimens also suggested that GBM cells and vascular cells are likely separate lineages. Rather than expansion owing to trans-differentiation, vascular cell expanded by proliferation during tumorigenesis. Therefore, cross-lineage trans-differentiation of GBM cells is very unlikely to occur during gliomagenesis. Our findings advance understanding of cell lineage dynamics during gliomagenesis, and have implications for targeted treatment of GBMs. [ABSTRACT FROM AUTHOR]

Development of cefotaxime-resistance and biofilm formation increase the difficulty to prevent and control the infection and contamination of Salmonella , one of the most important foodborne and zoonotic bacterial pathogen. Our previous study observed that 1/8 minimum inhibitory concentration (MIC) of cefotaxime induced the enhancement of biofilm formation and filamentous morphological change by a monophasic Salmonella Typhimurium strain SH16SP46. This study was designed to explore the role of three penicillin-binding proteins (PBPs) in mediating the induction effect of cefotaxime. Three deletion mutants of the genes mrc A, mrc B, and fts I, encoding the proteins PBP1a, PBP1b, and PBP3, respectively, were constructed using the parental Salmonella strain SH16SP46. Gram staining and scanning electron microscopy showed that these mutants showed normal morphology comparable to the parental strain without cefotaxime treatment. However, under the stress of 1/8 MIC of cefotaxime, the strains WT, Δmrc A, and Δfts I, rather than Δmrc B, exhibited filamentous morphological change. Moreover, cefotaxime treatment significantly enhanced biofilm formation by the strains WT, Δmrc A, and Δfts I, but not by the Δmrc B strain. The complement of mrc B gene in the Δmrc B strain recovered the enhanced biofilm formation and filamentous morphological change induced by cefotaxime. Our results suggest that PBP1b encoded by mrc B gene may be a binding target of cefotaxime for initiating the effect on Salmonella morphology and biofilm formation. The study will contribute to further understanding of the regulatory mechanism of cefotaxime on Salmonella biofilm formation. [ABSTRACT FROM AUTHOR]

Purpose: Surface‐based image‐to‐patient registration in current surgical navigation is mainly achieved by a 3D scanner, which has several limitations in clinical practice such as uncontrollable scanning range, complicated operation, and even high failure rate. An accurate, robust, and easy‐to‐perform image‐to‐patient registration method is urgently required. Methods: An incremental point cloud registration method was proposed for surface‐based image‐to‐patient registration. The point cloud in image space was extracted from the computed tomography (CT) image, and a template matching method was applied to remove the redundant points. The corresponding point cloud in patient space was incrementally collected by an optically tracked pointer, while the nearest point distance (NPD) constraint was applied to ensure the uniformity of the collected points. A coarse‐to‐fine registration method under the constraints of coverage ratio (CR) and outliers ratio (OR) was then proposed to obtain the optimal rigid transformation from image to patient space. The proposed method was integrated in the recently developed endoscopic navigation system, and phantom study and clinical trials were conducted to evaluate the performance of the proposed method. Results: The results of the phantom study revealed that the proposed constraints greatly improved the accuracy and robustness of registration. The comparative experimental results revealed that the proposed registration method significantly outperform the scanner‐based method, and achieved comparable accuracy to the fiducial‐based method. In the clinical trials, the average registration duration was 1.24 ± 0.43 min, the target registration error (TRE) of 294 marker points (59 patients) was 1.25 ± 0.40 mm, and the lower 97.5% confidence limit of the success rate of positioning marker points exceeds the expected value (97.56% vs. 95.00%), revealed that the accuracy of the proposed method significantly met the clinical requirements (TRE ⩽ 2 mm, p < 0.05). Conclusions: The proposed method has both the advantages of high accuracy and convenience, which were absent in the scanner‐based method and the fiducial‐based method. Our findings will help improve the quality of endoscopic sinus and skull base surgery. [ABSTRACT FROM AUTHOR]

Soil-available nitrogen is a vital index related to the growth and development of crops. The real-time and nondestructive detection of the soil-available nitrogen content based on near-infrared (NIR) spectroscopy could improve the accurate management of crop nutrients. In this manuscript, soil NIR spectroscopy and available nitrogen data are used in a stacked framework to develop a reliable and accurate soil-available nitrogen model. The spectral reflectance of the soil samples was collected in the 900 to 1700 nm band with nine pre-processing methods using a handheld micronear-infrared spectrometer. The stacking framework of this manuscript has two layers. Extreme gradient boosting (XGBoost), categorical boosting (CatBoost), a light gradient boosting machine (LightGBM), and a random forest, which are tree-based algorithms, are stacked as base models in the first layer. In the second layer, linear regression is employed in a meta-model to identify the unique learning pattern of the base model. The results show that the range and characteristics of the spectra can be used to make relevant predictions , and the micro-NIR spectra are variable under different pre-treatments. In addition, the stacked model achieves the best performance of all the models tested. Notably, the coefficient of determination (R2) is 0.942, and the relative percent difference is 4.192 with Savitzky–Golay and multiplicative scatter correction. This manuscript presents an efficient method for predicting soil-available nitrogen levels with a handheld micronear-infrared spectrometer. [ABSTRACT FROM AUTHOR]

We present new sufficient conditions for the asymptotic stability of a two-neuron network with different time delays. These conditions lead to delay-dependent and delay-independent asymptotic stabilities, respectively. They are shown to be less conservative and restrictive than those reported in the literature. Some examples are included to illustrate our results. Index Terms--Neural networks, neuron, stability, time delays.