IQGAP3 promotes the progression of glioma as an immune and prognostic marker.

Background: IQGAP3 plays a crucial role in regulating cell proliferation, division, and cytoskeletal organization. Abnormal expression of IQGAP3 has been linked to various tumors, but its function in glioma is not well understood. Methods: Various methods, including genetic differential analysis, single-cell analysis, ROC curve analysis, Cox regression, Kaplan-Meier analysis, and enrichment analysis, were employed to analyze the expression patterns, diagnostic potential, prognostic implications, and biological processes involving IQGAP3 in normal and tumor tissues. The impact of IQGAP3 on immune infiltration and the immune microenvironment in gliomas was evaluated using immunofluorescence. Additionally, the cBioPortal database was used to analyze copy number variations and mutation sites of IQGAP3. Experimental validation was also performed to assess the effects of IQGAP3 on glioma cells and explore underlying mechanisms. Results: High IQGAP3 expression in gliomas is associated with an unfavorable prognosis, particularly in wild-type IDH and 1p/19q non-codeleted gliomas. Enrichment analysis revealed that IQGAP3 is involved in regulating the cell cycle, PI3K/AKT signaling, p53 signaling, and PLK1-related pathways. Furthermore, IQGAP3 expression may be closely related to the immunosuppressive microenvironment of glioblastoma. BRD-K88742110 and LY-303511 are potential drugs for targeting IQGAP3 in anti-glioma therapy. In vitro experiments showed that downregulation of IQGAP3 inhibits the proliferation and migration of glioma cells, with the PLK1/PI3K/AKT pathway potentially playing a crucial role in IQGAP3-mediated glioma progression. Conclusion: IQGAP3 shows promise as a valuable biomarker for diagnosis, prognosis, and immunotherapeutic strategies in gliomas.

NeuroSeg-II: A deep learning approach for generalized neuron segmentation in two-photon Ca2+ imaging.

The development of two-photon microscopy and Ca2+ indicators has enabled the recording of multiscale neuronal activities in vivo and thus advanced the understanding of brain functions. However, it is challenging to perform automatic, accurate, and generalized neuron segmentation when processing a large amount of imaging data. Here, we propose a novel deep-learning-based neural network, termed as NeuroSeg-II, to conduct automatic neuron segmentation for in vivo two-photon Ca2+ imaging data. This network architecture is based on Mask region-based convolutional neural network (R-CNN) but has enhancements of an attention mechanism and modified feature hierarchy modules. We added an attention mechanism module to focus the computation on neuron regions in imaging data. We also enhanced the feature hierarchy to extract feature information at diverse levels. To incorporate both spatial and temporal information in our data processing, we fused the images from average projection and correlation map extracting the temporal information of active neurons, and the integrated information was expressed as two-dimensional (2D) images. To achieve a generalized neuron segmentation, we conducted a hybrid learning strategy by training our model with imaging data from different labs, including multiscale data with different Ca2+ indicators. The results showed that our approach achieved promising segmentation performance across different imaging scales and Ca2+ indicators, even including the challenging data of large field-of-view mesoscopic images. By comparing state-of-the-art neuron segmentation methods for two-photon Ca2+ imaging data, we showed that our approach achieved the highest accuracy with a publicly available dataset. Thus, NeuroSeg-II enables good segmentation accuracy and a convenient training and testing process.

Identification of Key Genes and Pathways in Peripheral Blood Mononuclear Cells of Type 1 Diabetes Mellitus by Integrated Bioinformatics Analysis.

BACKGROUND: The onset and progression of type 1 diabetes mellitus (T1DM) is closely related to autoimmunity. Effective monitoring of the immune system and developing targeted therapies are frontier fields in T1DM treatment. Currently, the most available tissue that reflects the immune system is peripheral blood mononuclear cells (PBMCs). Thus, the aim of this study was to identify key PBMC biomarkers of T1DM. METHODS: Common differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) datasets GSE9006, GSE72377, and GSE55098, and PBMC mRNA expression in T1DM patients was compared with that in healthy participants by GEO2R. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses of DEGs were performed using the Cytoscape, DAVID, and STRING databases. The vital hub genes were validated by reverse transcription-polymerase chain reaction using clinical samples. The disease-gene-drug interaction network was built using the Comparative Toxicogenomics Database (CTD) and Drug Gene Interaction Database (DGIdb). RESULTS: We found that various biological functions or pathways related to the immune system and glucose metabolism changed in PBMCs from T1DM patients. In the PPI network, the DEGs of module 1 were significantly enriched in processes including inflammatory and immune responses and in pathways of proteoglycans in cancer. Moreover, we focused on four vital hub genes, namely, chitinase-3-like protein 1 (CHI3L1), C-X-C motif chemokine ligand 1 (CXCL1), matrix metallopeptidase 9 (MMP9), and granzyme B (GZMB), and confirmed them in clinical PBMC samples. Furthermore, the disease-gene-drug interaction network revealed the potential of key genes as reference markers in T1DM. CONCLUSION: These results provide new insight into T1DM pathogenesis and novel biomarkers that could be widely representative reference indicators or potential therapeutic targets for clinical applications.

Restoration of Two-Photon Ca2+ Imaging Data Through Model Blind Spatiotemporal Filtering.

Two-photon Ca2+ imaging is a leading technique for recording neuronal activities in vivo with cellular or subcellular resolution. However, during experiments, the images often suffer from corruption due to complex noises. Therefore, the analysis of Ca2+ imaging data requires preprocessing steps, such as denoising, to extract biologically relevant information. We present an approach that facilitates imaging data restoration through image denoising performed by a neural network combining spatiotemporal filtering and model blind learning. Tests with synthetic and real two-photon Ca2+ imaging datasets demonstrate that the proposed approach enables efficient restoration of imaging data. In addition, we demonstrate that the proposed approach outperforms the current state-of-the-art methods by evaluating the qualities of the denoising performance of the models quantitatively. Therefore, our method provides an invaluable tool for denoising two-photon Ca2+ imaging data by model blind spatiotemporal processing.

Infection Prevention and Control Strategies for the Peri-Operative Period of Emergency Surgery during the Coronavirus Disease 2019 Outbreak in a Neurosurgery Department in Wuhan, China.

Objective: In December 2019, a novel coronavirus infectious disease, coronavirus disease 2019 (COVID-19), began to appear in China. Wuhan, Hubei Province, is the origin and core location of the epidemic. Neurosurgeons were faced with the challenge of balancing treatment of patients with life-threatening conditions and preventing the cross-transmission of the virus. Methods: A series of infection prevention and control strategies was adopted for the peri-operative period of emergency surgeries in our department. These strategies include protective measures for the emergency department (ED) and measures for the peri-operative period of emergency surgery. The propensity score matching (PSM) was used to match COVID-19-related patients with patients before the epidemic. Length of wait time in the ED and duration of operation were compared. Results: From January 23, 2020 to March 18, 2020, we performed emergency surgery for 19 patients who were either COVID-19-related or COVID-19-suspected. None of the medical staff involved in the surgeries developed viral infection, and no peri-operative virus transmission occurred in our hospital. After the PSM, 32 patients were included in the epidemic group and the pre-epidemic group (16 patients in each group). The duration of wait time in the ED of the former group was longer than that of the latter group (z = -3.000; p = 0.003). During the epidemic, the duration of a craniotomy was longer than before the epidemic (z = -2.253; p = 0.024), and there was no difference in the duration of interventional surgery (z = -0.314; p = 0.753). Conclusion: We believe that our experience can provide a useful reference for other surgeons facing the same challenges and as a lesson for similar infectious diseases that may occur in the future.

Tracheal development after left pulmonary artery reimplantation: an individual study.

Pulmonary artery sling (PA sling) often presents as a life-threatening condition requiring urgent surgical correction. We reported 32 cases of PA sling in children who were followed up postoperatively in the past 6 years. All patients with PA slings who were admitted to the hospital from January 2012 to December 2017 and underwent surgery were retrospectively analyzed. The mean age of the 32 patients at repair was 16.97 months (range, 15 days to 128 months). Six patients required ventilator assistance for respiratory failure. All children underwent left pulmonary artery (LPA) reimplantation (n = 32), and 3 patients needed reimplantation slide tracheoplasty (n = 3) due to ventilation weaning failure. Four patients died, 27 patients survived until discharge, and 18 patients were followed up. Pulmonary computed tomography imaging and echocardiography were performed in 18 patients who were followed up. After LPA reimplantation, the tracheal carina area was significantly enlarged compared to that preoperation (p = 0.0002). In this follow-up cohort study, 75% of the patients who underwent LPA reimplantation survived until discharge. The survivors had subsequently well-developed pulmonary arteries and tracheas.

MATRIEX imaging: multiarea two-photon real-time in vivo explorer.

Two-photon laser scanning microscopy has been extensively applied to study in vivo neuronal activity at cellular and subcellular resolutions in mammalian brains. However, the extent of such studies is typically confined to a single functional region of the brain. Here, we demonstrate a novel technique, termed the multiarea two-photon real-time in vivo explorer (MATRIEX), that allows the user to target multiple functional brain regions distributed within a zone of up to 12 mm in diameter, each with a field of view (FOV) of ~200 µm in diameter, thus performing two-photon Ca2+ imaging with single-cell resolution in all of the regions simultaneously. For example, we demonstrate real-time functional imaging of single-neuron activities in the primary visual cortex, primary motor cortex and hippocampal CA1 region of mice in both anesthetized and awake states. A unique advantage of the MATRIEX technique is the configuration of multiple microscopic FOVs that are distributed in three-dimensional space over macroscopic distances (>1 mm) both laterally and axially but that are imaged by a single conventional laser scanning device. In particular, the MATRIEX technique can be effectively implemented as an add-on optical module for an existing conventional single-beam-scanning two-photon microscope without requiring any modification to the microscope itself. Thus, the MATRIEX technique can be readily applied to substantially facilitate the exploration of multiarea neuronal activity in vivo for studies of brain-wide neural circuit function with single-cell resolution.

NeuroSeg: automated cell detection and segmentation for in vivo two-photon Ca2+ imaging data.

Two-photon Ca2+ imaging has become a popular approach for monitoring neuronal population activity with cellular or subcellular resolution in vivo. This approach allows for the recording of hundreds to thousands of neurons per animal and thus leads to a large amount of data to be processed. In particular, manually drawing regions of interest is the most time-consuming aspect of data analysis. However, the development of automated image analysis pipelines, which will be essential for dealing with the likely future deluge of imaging data, remains a major challenge. To address this issue, we developed NeuroSeg, an open-source MATLAB program that can facilitate the accurate and efficient segmentation of neurons in two-photon Ca2+ imaging data. We proposed an approach using a generalized Laplacian of Gaussian filter to detect cells and weighting-based segmentation to separate individual cells from the background. We tested this approach on an in vivo two-photon Ca2+ imaging dataset obtained from mouse cortical neurons with differently sized view fields. We show that this approach exhibits superior performance for cell detection and segmentation compared with the existing published tools. In addition, we integrated the previously reported, activity-based segmentation into our approach and found that this combined method was even more promising. The NeuroSeg software, including source code and graphical user interface, is freely available and will be a useful tool for in vivo brain activity mapping.

Targeted Patching and Dendritic Ca2+ Imaging in Nonhuman Primate Brain in vivo.

Nonhuman primates provide an important model not only for understanding human brain but also for translational research in neurological and psychiatric disorders. However, many high-resolution techniques for recording neural activity in vivo that were initially established for rodents have not been yet applied to the nonhuman primate brain. Here, we introduce a combination of two-photon targeted patching and dendritic Ca2+ imaging to the neocortex of adult common marmoset, an invaluable primate model for neuroscience research. Using targeted patching, we show both spontaneous and sensory-evoked intracellular dynamics of visually identified neurons in the marmoset cortex. Using two-photon Ca2+ imaging and intracellular pharmacological manipulation, we report both action-potential-associated global and synaptically-evoked NMDA (N-methyl-D-aspartate) receptor-mediated local Ca2+ signals in dendrites and spines of the superficial-layer cortical neurons. Therefore, we demonstrate the presence of synaptic Ca2+ signals in neuronal dendrites in living nonhuman primates. This work represents a proof-of-principle for exploring the primate brain functions in vivo by monitoring neural activity and morphology at a subcellular resolution.

Locomotion-Related Population Cortical Ca2+ Transients in Freely Behaving Mice.

Locomotion involves complex neural activity throughout different cortical and subcortical networks. The primary motor cortex (M1) receives a variety of projections from different brain regions and is responsible for executing movements. The primary visual cortex (V1) receives external visual stimuli and plays an important role in guiding locomotion. Understanding how exactly the M1 and the V1 are involved in locomotion requires recording the neural activities in these areas in freely moving animals. Here, we used an optical fiber-based method for the real-time monitoring of neuronal population activities in freely moving mice. We combined the bulk loading of a synthetic Ca2+ indicator and the optical fiber-based Ca2+ recordings of neuronal activities. An optical fiber 200 µm in diameter can detect the coherent activity of a subpopulation of neurons. In layer 5 of the M1 and V1, we showed that population Ca2+ transients reliably occurred preceding the impending locomotion. Interestingly, the M1 Ca2+ transients started ~100 ms earlier than that in V1. Furthermore, the population Ca2+ transients were robustly correlated with head movements. Thus, our work provides a simple but efficient approach for monitoring the cortical Ca2+ activity of a local cluster of neurons during locomotion in freely moving animals.