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Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignant tumor with a high metastatic potential. Perineural invasion (PNI) occurs in the early stages of PDAC with a high incidence rate and is directly associated with a poor prognosis. It involves close interaction among PDAC cells, nerves and the tumor microenvironment. In this review, we detailed discuss PNI-related pain, six specific steps of PNI, and treatment of PDAC with PNI and emphasize the importance of novel technologies for further investigation.

BackgroundChronic pain poses a significant social burden. Spinal cord stimulation (SCS) is considered to be the most promising treatment for refractory pain. The aim of this study was to summarize the current research hotspots on SCS for pain treatment during the past two decades and to predict the future research trends by bibliometric analysis.MethodsThe literature over the last two decades (2002–2022) which was related to SCS in pain treatment was obtained from the Web of Science Core Collection. Bibliometric analyses were conducted based on the following aspects: (1) Annual publication and citation trends; (2) Annual publication changes of different publication types; (3) Publications and citations/co-citations of different country/institution/journal/author; (4) Citations/co-citation and citation burst analysis of different literature; and (5) Co-occurrence, cluster, thematic map, trend topics, and citation burst analysis of different keywords. (6) Comparison between the United States and Europe. All analyses were performed on CiteSpace, VOSviewer, and R bibliometrix package.ResultsA total of 1,392 articles were included in this study, with an increasing number of publications and citations year by year. The most highly published type of literature was clinical trial. United States was the country with the most publications and citations; Johns Hopkins University was the institution with the most publications; NEUROMODULATION published the most papers; the most published author was Linderoth B; and the most cited paper was published in the PAIN by Kumar K in 2007. The most frequently occurring keywords were “spinal cord stimulation,” “neuropathic pain,” and “chronic pain,” etc.ConclusionThe positive effect of SCS on pain treatment has continued to arouse the enthusiasm of researchers in this field. Future research should focus on the development of new technologies, innovative applications, and clinical trials for SCS. This study might facilitate researchers to comprehensively understand the overall perspective, research hotspots, and future development trends in this field, as well as seek collaboration with other researchers.

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer. It has a poor response to conventional therapy and has an extremely poor 5-year survival rate. PDAC is driven by multiple oncogene mutations, with the highest mutation frequency being observed in KRAS. The KRAS protein, which binds to GTP, has phosphokinase activity, which further activates downstream effectors. KRAS mutation contributes to cancer cell proliferation, metabolic reprogramming, immune escape, and therapy resistance in PDAC, acting as a critical driver of the disease. Thus, KRAS mutation is positively associated with poorer prognosis in pancreatic cancer patients. This review focus on the KRAS mutation patterns in PDAC, and further emphases its role in signal transduction, metabolic reprogramming, therapy resistance and prognosis, hoping to provide KRAS target therapy strategies for PDAC.

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.

Quantitative and mechanistic understanding of learning and long-term memory at the level of single neurons in living brains require highly demanding techniques. A specific need is to precisely label one cell whose firing output property is pinpointed amidst a functionally characterized large population of neurons through the learning process and then investigate the distribution and properties of dendritic inputs. Here, we disseminate an integrated method of daily two-photon neuronal population Ca2+ imaging through an auditory associative learning course, followed by targeted single-cell loose-patch recording and electroporation of plasmid for enhanced chronic Ca2+ imaging of dendritic spines in the targeted cell. Our method provides a unique solution to the demand, opening a solid path toward the hard-cores of how learning and long-term memory are physiologically carried out at the level of single neurons and synapses.

ObjectivesThe study aimed to conduct a bibliometric analysis of publications concerning lumbar spondylolisthesis, as well as summarize its research topics and hotspot trends with machine-learning based text mining.MethodsThe data were extracted from the Web of Science Core Collection (WoSCC) database and then analyzed in Rstudio1.3.1 and CiteSpace5.8. Annual publication production and the top-20 productive authors over time were obtained. Additionally, top-20 productive journals and top-20 influential journals were compared by spine-subspecialty or not. Similarly, top-20 productive countries/regions and top-20 influential countries/regions were compared by they were developed countries/regions or not. The collaborative relationship among countries and institutions were presented. The main topics of lumbar spondylolisthesis were classified by Latent Dirichlet allocation (LDA) analysis, and the hotspot trends were indicated by keywords with strongest citation bursts.ResultsUp to 2021, a total number of 4,245 articles concerning lumbar spondylolisthesis were finally included for bibliometric analysis. Spine-subspecialty journals were found to be dominant in the productivity and the impact of the field, and SPINE, EUROPEAN SPINE JOURNAL and JOURNAL OF NEUROSURGERY-SPINE were the top-3 productive and the top-3 influential journals in this field. USA, Japan and China have contributed to over half of the publication productivity, but European countries seemed to publish more influential articles. It seemed that developed countries/regions tended to produce more articles and more influential articles, and international collaborations mainly occurred among USA, Europe and eastern Asia. Publications concerning surgical management was the major topic, followed by radiographic assessment and epidemiology for this field. Surgical management especially minimally invasive technique for lumbar spondylolisthesis were the recent hotspots over the past 5 years.ConclusionsThe study successfully summarized the productivity and impact of different entities, which should benefit the journal selection and pursuit of international collaboration for researcher who were interested in the field of lumbar spondylolisthesis. Additionally, the current study may encourage more researchers joining in the field and somewhat inform their research direction in the future.

BackgroundThis study aimed to conduct a bibliometric analysis of publications on connectomes and illustrate its trends and hotspots using a machine-learning-based text mining algorithm.MethodsDocuments were retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases and analyzed in Rstudio 1.3.1. Through quantitative and qualitative methods, the most productive and impactful academic journals in the field of connectomes were compared in terms of the total number of publications and h-index over time. Meanwhile, the countries/regions and institutions involved in connectome research were compared, as well as their scientific collaboration. The study analyzed topics and research trends by R package “bibliometrix.” The major topics of connectomes were classified by Latent Dirichlet allocation (LDA).ResultsA total of 14,140 publications were included in the study. NEUROIMAGE ranked first in terms of publication volume (1,427 articles) and impact factor (h-index:122) among all the relevant journals. The majority of articles were published by developed countries, with the United States having the most. Harvard Medical School and the University of Pennsylvania were the two most productive institutions. Neuroimaging analysis technology and brain functions and diseases were the two major topics of connectome research. The application of machine learning, deep learning, and graph theory analysis in connectome research has become the current trend, while an increasing number of studies were concentrating on dynamic functional connectivity. Meanwhile, researchers have begun investigating alcohol use disorders and migraine in terms of brain connectivity in the past 2 years.ConclusionThis study illustrates a comprehensive overview of connectome research and provides researchers with critical information for understanding the recent trends and hotspots of connectomes.

Astrocytic Ca2+ transients are essential for astrocyte integration into neural circuits. These Ca2+ transients are primarily sequestered in subcellular domains, including primary branches, branchlets and leaflets, and endfeet. In previous studies, it suggests that aging causes functional defects in astrocytes. Until now, it was unclear whether and how aging affects astrocytic Ca2+ transients at subcellular domains. In this study, we combined a genetically encoded Ca2+ sensor (GCaMP6f) and in vivo two-photon Ca2+ imaging to determine changes in Ca2+ transients within astrocytic subcellular domains during brain aging. We showed that aging increased Ca2+ transients in astrocytic primary branches, higher-order branchlets, and terminal leaflets. However, Ca2+ transients decreased within astrocytic endfeet during brain aging, which could be caused by the decreased expressions of Aquaporin-4 (AQP4). In addition, aging-induced changes of Ca2+ transient types were heterogeneous within astrocytic subcellular domains. These results demonstrate that the astrocytic Ca2+ transients within subcellular domains are affected by aging differently. This finding contributes to a better understanding of the physiological role of astrocytes in aging-induced neural circuit degeneration.

IntroductionThree-dimensional (3D) reconstruction of fracture fragments on hip Computed tomography (CT) may benefit the injury detail evaluation and preoperative planning of the intertrochanteric femoral fracture (IFF). Manually segmentation of bony structures was tedious and time-consuming. The purpose of this study was to propose an artificial intelligence (AI) segmentation tool to achieve semantic segmentation and precise reconstruction of fracture fragments of IFF on hip CTs.Materials and MethodsA total of 50 labeled CT cases were manually segmented with Slicer 4.11.0. The ratio of training, validation and testing of the 50 labeled dataset was 33:10:7. A simplified V-Net architecture was adopted to build the AI tool named as IFFCT for automatic segmentation of fracture fragments. The Dice score, precision and sensitivity were computed to assess the segmentation performance of IFFCT. The 2D masks of 80 unlabeled CTs segmented by AI tool and human was further assessed to validate the segmentation accuracy. The femoral head diameter (FHD) was measured on 3D models to validate the reliability of 3D reconstruction.ResultsThe average Dice score of IFFCT in the local test dataset for “proximal femur”, “fragment” and “distal femur” were 91.62%, 80.42% and 87.05%, respectively. IFFCT showed similar segmentation performance in cross-dataset, and was comparable to that of human expert in human-computer competition with significantly reduced segmentation time (p 0.05). All ICCs were greater than 0.8.ConclusionThe proposed AI segmentation tool could effectively segment the bony structures from IFF CTs with comparable performance of human experts. The 2D masks and 3D models generated from automatic segmentation were effective and reliable, which could benefit the injury detail evaluation and preoperative planning of IFFs.

Two-photon Ca2+ imaging is a widely used technique for investigating brain functions across multiple spatial scales. However, the recording of neuronal activities is affected by movement of the brain during tasks in which the animal is behaving normally. Although post-hoc image registration is the commonly used approach, the recent developments of online neuroscience experiments require real-time image processing with efficient motion correction performance, posing new challenges in neuroinformatics. We propose a fast and accurate image density feature-based motion correction method to address the problem of imaging animal during behaviors. This method is implemented by first robustly estimating and clustering the density features from two-photon images. Then, it takes advantage of the temporal correlation in imaging data to update features of consecutive imaging frames with efficient calculations. Thus, motion artifacts can be quickly and accurately corrected by matching the features and obtaining the transformation parameters for the raw images. Based on this efficient motion correction strategy, our algorithm yields promising computational efficiency on imaging datasets with scales ranging from dendritic spines to neuronal populations. Furthermore, we show that the proposed motion correction method outperforms other methods by evaluating not only computational speed but also the quality of the correction performance. Specifically, we provide a powerful tool to perform motion correction for two-photon Ca2+ imaging data, which may facilitate online imaging experiments in the future.

BackgroundThis study aimed to investigate risk factors and prognostic factors in patients with clear cell renal cell carcinoma (ccRCC) with bone metastasis (BM) and establish nomograms to provide a quantitative prediction of the risk of BM and survival probability.MethodsThe clinicopathological characteristics of patients with ccRCC between January 2010 and December 2015 were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Independent factors for BM in ccRCC patients were identified using univariate and multivariate logistic regression analyses. Prognostic factors for predicting cancer-specific death were evaluated using univariate and multivariate analyses based on a competing risk regression model. We then constructed a diagnostic nomogram and a prognostic nomogram. The two nomograms were evaluated using calibration curves, receiver operating characteristic curves, and decision curve analysis.ResultsOur study included 34,659 patients diagnosed with ccRCC in the SEER database, with 1,415 patients who presented with bone metastasis. Risk factors for BM in patients with ccRCC included age, stage T, stage N, brain metastasis, liver metastasis, lung metastasis, tumor size, and laterality. Independent prognostic factors for patients with ccRCC patients with BM were Fuhrman grade, tumor size, T stage, N stage, brain metastases, lung metastasis, and surgery. For the diagnostic nomogram, the area under the curve values in the training and testing cohorts were 0.863 (95% CI, 0.851–0.875) and 0.859 (95% CI, 0.839–0.878), respectively. In the prognostic cohort, the area under the curve values for 1-, 2-, and 3-year cancer-specific survival rates in the training cohort were 0.747, 0.774, and 0.780, respectively, and 0.671, 0.706, and 0.696, respectively, in the testing cohort. Through calibration curves and decision curve analyses, the nomograms displayed excellent performance.ConclusionsSeveral factors related to the development and prognosis of BM in patients with ccRCC were identified. The nomograms constructed in this study are expected to become effective and precise tools for clinicians to improve cancer management.

BackgroundThe study aimed to investigate the prognostic factors of spinal cord astrocytoma (SCA) and establish a nomogram prognostic model for the management of patients with SCA.MethodsPatients diagnosed with SCA between 1975 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training and testing datasets (7:3). The primary outcomes of this study were overall survival (OS) and cancer-specific survival (CSS). Cox hazard proportional regression model was used to identify the prognostic factors of patients with SCA in the training dataset and feature importance was obtained. Based on the independent prognostic factors, nomograms were established for prognostic prediction. Calibration curves, concordance index (C-index), and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the calibration and discrimination of the nomogram model, while Kaplan-Meier (KM) survival curves and decision curve analyses (DCA) were used to evaluate the clinical utility. Web-based online calculators were further developed to achieve clinical practicability.ResultsA total of 818 patients with SCA were included in this study, with an average age of 30.84 ± 21.97 years and an average follow-up time of 117.57 ± 113.51 months. Cox regression indicated that primary site surgery, age, insurance, histologic type, tumor extension, WHO grade, chemotherapy, and post-operation radiotherapy (PRT) were independent prognostic factors for OS. While primary site surgery, insurance, tumor extension, PRT, histologic type, WHO grade, and chemotherapy were independent prognostic factors for CSS. For OS prediction, the calibration curves in the training and testing dataset illustrated good calibration, with C-indexes of 0.783 and 0.769. The area under the curves (AUCs) of 5-year survival prediction were 0.82 and 0.843, while 10-year survival predictions were 0.849 and 0.881, for training and testing datasets, respectively. Moreover, the DCA demonstrated good clinical net benefit. The prediction performances of nomograms were verified to be superior to that of single indicators, and the prediction performance of nomograms for CSS is also excellent.ConclusionsNomograms for patients with SCA prognosis prediction demonstrated good calibration, discrimination, and clinical utility. This result might benefit clinical decision-making and patient management for SCA. Before further use, more extensive external validation is required for the established web-based online calculators.

Nanozymes, a new generation of enzyme mimics, have recently attracted great attention. Nanozymes could catalyze chemical reactions as biological enzymes under physiologically mild conditions with higher-efficiency catalytic activities. Moreover, nanozymes could overcome the shortcomings of natural enzymes, such as easy inactivation, high cost, and low yield. With the development of more and more smart and multi-functional nanosystems, nanozymes display great achievement in tumor biology. In this review, we outline the recent advances of nanozymes in tumor and tumor microenvironment diagnosis, therapy, and theranostics.

Intracerebral hemorrhage (ICH) accounts for ~15% of all strokes and is associated with high mortality and disability rates. The systemic inflammation response index (SIRI) is a novel systemic inflammatory marker based on peripheral neutrophil, monocyte, and lymphocyte counts. This study aimed to evaluate the prognostic significance of admission SIRI in patients with spontaneous ICH and compare its predictive ability with that of the neutrophil-to-lymphocyte ratio (NLR). This retrospective study was conducted based on a prospectively collected database of patients with ICH between June 2016 and January 2019. Propensity score matching (PSM) was conducted to adjust for potential imbalances in the clinical parameters. A total of 403 patients were included in the original cohort. The optimal SIRI cut-off value was 2.76. After 1:1 PSM based on potential confounding variables, a new cohort containing 262 patients was established for further analysis. In the original cohort, SIRI served as an independent predictor of 3-month functional outcome [odds ratio (OR), 1.302; 95% CI, 1.120–1.512; p = 0.001] and 1-month mortality (OR, 1.072; 95% CI, 1.020–1.126; p = 0.006), while NLR was independently associated with only 3-month functional outcomes (OR, 1.051; 95% CI, 1.004–1.100; p = 0.031) and not 1-month mortality. The same applied to the PSM cohort. Receiver operating characteristic analyses and predictive models indicated that in most instances, SIRI was superior to NLR and their components in predicting the outcomes of patients with ICH. Our study found that SIRI is determined to be an independent predictive indicator for ICH patients in 3-month functional outcomes and 1-month mortality. The prognostic predictive ability of SIRI was stronger than that of NLR.

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.

Monitoring astrocytic Ca2+ activity is essential to understand the physiological and pathological roles of astrocytes in the brain. However, previous commonly used methods for studying astrocytic Ca2+ activities can be applied in only anesthetized or head-fixed animals, which significantly affects in vivo astrocytic Ca2+ dynamics. In the current study, we combined optic fiber recordings with genetically encoded Ca2+ indicators (GECIs) to monitor astrocytic activity in freely behaving mice. This approach enabled selective and reliable measurement of astrocytic Ca2+ activity, which was verified by the astrocyte-specific labeling of GECIs and few movement artifacts. Additionally, astrocytic Ca2+ activities induced by locomotion or footshock were stably recorded in the cortices and hippocampi of freely behaving mice. Furthermore, this method allowed for the longitudinal study of astrocytic activities over several weeks. This work provides a powerful approach to record astrocytic activity selectively, stably, and chronically in freely behaving mice.

Oxytocin (OT), a neuropeptide involved in the regulation of complex social and sexual behavior in mammals, has been proposed as a treatment for a number of psychiatric disorders including pain. It has been well documented that central administration of OT elicits strong scratching and grooming behaviors in rodents. However, these behaviors were only described as symptoms, few studies have investigated their underlying neural mechanisms. Thus, we readdressed this question and undertook an analysis of spinal circuits underlying OT-induced scratching behavior in the present study. We demonstrated that intrathecal OT induced robust but transient hindpaw scratching behaviors by activating spinal OT receptors (OTRs). Combining the pre-clinical and clinical evidence, we speculated that OT-induced scratching may be an itch symptom. Further RNAscope studies revealed that near 80% spinal GRP neurons expressed OTRs. OT activated the expression of c-fos mRNA in spinal GRP neurons. Chemical ablation of GRPR neurons significantly reduced intrathecal OT-induced scratching behaviors. Given GRP/GRPR pathway plays an important role in spinal itch transmission, we proposed that OT binds to the OTRs expressed on the GRP neurons, and activates GRP/GRPR pathway to trigger itch-scratching behaviors in mice. These findings provide novel evidence relevant for advancing understanding of OT-induced behavioral changes, which will be important for the development of OT-based drugs to treat a variety of psychiatric disorders.

Understanding the complex neural mechanisms controlling urinary bladder activity is an extremely important topic in both neuroscience and urology. Simultaneously recording of the bladder activity and neural activity in related brain regions will largely advance this field. However, such recording approach has long been restricted to anesthetized animals, whose bladder function and urodynamic properties are largely affected by anesthetics. In our recent report, we found that it is feasible to record bladder pressure (cystometry) and the related cortical neuron activity simultaneously in freely moving mice. Here, we aimed to demonstrate the use of this combined method in freely moving mice for recording the activity of the pontine micturition center (PMC), a more difficultly approachable small region deeply located in the brainstem and a more popularly studied hub for controlling bladder function. Interestingly, we found that the duration of urination events linearly correlated to the time course of neuronal activity in the PMC. We observed that the activities of PMC neurons highly correlated with spike-like increases in bladder pressure, reflecting bladder contractions. We also found that anesthesia evoked prominent changes in the dynamics of the Ca2+ signals in the PMC during the bladder contraction and even induced the dripping overflow incontinence due to suppression of the neural activity in the PMC. In addition, we described in details both the system for cystometry in freely moving mice and the protocols for how to perform this combined method. Therefore, this work provides a powerful approach that enables the simultaneous measurement of neuronal activity of the PMC or any other brain sites and bladder function in freely behaving mice. This approach offers a promising possibility to examine the neural mechanisms underlying neurogenic bladder dysfunction.

In vivo two-photon Ca2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca2+ indicators, we recorded the Ca2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca2+ indicators (GECIs), we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors.

Neurological diseases are destructive, mainly characterized by the failure of endogenous repair, the inability to recover tissue damage, resulting in the increasing loss of cognitive and physical function. Although some clinical drugs can alleviate the progression of these diseases, but they lack therapeutic effect in repairing tissue injury and rebuilding neurological function. More and more studies have shown that cell therapy has made good achievements in the application of nerve injury. Olfactory ensheathing cells (OECs) are a special type of glial cells, which have been proved to play an important role as an alternative therapy for neurological diseases, opening up a new way for the treatment of neurological problems. The functional mechanisms of OECs in the treatment of neurological diseases include neuroprotection, immune regulation, axon regeneration, improvement of nerve injury microenvironment and myelin regeneration, which also include secreted bioactive factors. Therefore, it is of great significance to better understand the mechanism of OECs promoting functional improvement, and to recognize the implementation of these treatments and the effective simulation of nerve injury disorders. In this review, we discuss the function of OECs and their application value in the treatment of neurological diseases, and position OECs as a potential candidate strategy for the treatment of nervous system diseases. [ABSTRACT FROM AUTHOR]

Neurological diseases are destructive, mainly characterized by the failure of endogenous repair, the inability to recover tissue damage, resulting in the increasing loss of cognitive and physical function. Although some clinical drugs can alleviate the progression of these diseases, but they lack therapeutic effect in repairing tissue injury and rebuilding neurological function. More and more studies have shown that cell therapy has made good achievements in the application of nerve injury. Olfactory ensheathing cells (OECs) are a special type of glial cells, which have been proved to play an important role as an alternative therapy for neurological diseases, opening up a new way for the treatment of neurological problems. The functional mechanisms of OECs in the treatment of neurological diseases include neuroprotection, immune regulation, axon regeneration, improvement of nerve injury microenvironment and myelin regeneration, which also include secreted bioactive factors. Therefore, it is of great significance to better understand the mechanism of OECs promoting functional improvement, and to recognize the implementation of these treatments and the effective simulation of nerve injury disorders. In this review, we discuss the function of OECs and their application value in the treatment of neurological diseases, and position OECs as a potential candidate strategy for the treatment of nervous system diseases. [ABSTRACT FROM AUTHOR]

Background: Synchronous multiple primary malignant neoplasms occurring at the same time (SMPMNS) are not currently uncommon in clinical oncological practice; however, the diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for SMPMNS needs further elucidation. Purpose: This study aimed to evaluate the application of 18F-FDG PET/CT in patients with SMPMNS. Materials and methods: The clinical and imaging data of 37 patients with SMPMNS who had undergone 18F-FDG PET/CT from October 2010 to December 2020 were retrospectively analyzed. The kappa consistency test was applied to evaluate the consistency of the diagnostic performance between PET/CT and conventional imaging (CI). The sensitivity, specificity, and accuracy of PET/CT and CI in the detection of metastatic lesions were compared. Results: This retrospective diagnostic study included 74 lesions identified in 37 patients with SMPMNS, with 94.6% of patients having double primary tumors. Of the incidences of SMPMNS, 18.9% occurred in the same organ system, with respiratory tumors being the most common type of neoplasm (43.2%) and the lung being the most common primary site (40.5%). The overall survival of SMPMNS patients without metastases was longer than that of those with metastases (c2 = 12.627, p = 0.000). The maximum standardized uptake value (SUVmax), the SUVmax ratio (larger SUVmax/smaller SUVmax), and the difference index of SUVmax (DISUVmax) [(larger SUVmax − smaller SUVmax)/ larger SUVmax ] of the primary lesions ranged from 0.9 to 41.7 (average = 12.3 ± 7.9), from 0.3 to 26.7 (average = 4.4 ± 6.9), and from 0.0% to 96.3% (average = 50.3% ± 29.3%), respectively. With regard to diagnostic accuracy, PET/CT and CI showed poor consistency (k = 0.096, p = 0.173). For the diagnosis of primary lesions (diagnosed and misdiagnosed), PET/CT and CI also showed poor consistency (k = 0.277, p = 0.000), but the diagnostic performance of PET/CT was better than that of CI. In the diagnosis of metastases, the patient-based sensitivity, specificity, and accuracy of PET/CT were 100.0%, 81.8%, and 89.2%, respectively, while those of CI were 73.3%, 100.0%, 89.2%, respectively. The sensitivity and specificity values were significantly different, with PET/CT having higher sensitivity (p = 0.02) and CI showing higher specificity (p = 0.02). Conclusions: 18F-FDG PET/CT improves the diagnostic performance for SMPMNS and is a good imaging modality for patients with SMPMNS [ABSTRACT FROM AUTHOR]

Astrocytic Ca2+ transients are essential for astrocyte integration into neural circuits. These Ca2+ transients are primarily sequestered in subcellular domains, including primary branches, branchlets and leaflets, and endfeet. In previous studies, it suggests that aging causes functional defects in astrocytes. Until now, it was unclear whether and how aging affects astrocytic Ca2+ transients at subcellular domains. In this study, we combined a genetically encoded Ca2+ sensor (GCaMP6f) and in vivo two-photon Ca2+ imaging to determine changes in Ca2+ transients within astrocytic subcellular domains during brain aging. We showed that aging increased Ca2+ transients in astrocytic primary branches, higher-order branchlets, and terminal leaflets. However, Ca2+ transients decreased within astrocytic endfeet during brain aging, which could be caused by the decreased expressions of Aquaporin4 (AQP4). In addition, aging-induced changes of Ca2+ transient types were heterogeneous within astrocytic subcellular domains. These results demonstrate that the astrocytic Ca2+ transients within subcellular domains are affected by aging differently. This finding contributes to a better understanding of the physiological role of astrocytes in aging-induced neural circuit degeneration. [ABSTRACT FROM AUTHOR]

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 mm 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. [ABSTRACT FROM AUTHOR]

P2X7 receptor (P2X7) is a non-selective and ATP-sensitive ligand-gated cation channel. Studies have confirmed that it is expressed in a variety of cells and correlates with their function, frequently in immune cells and tumor cells. We found increased expression of this receptor in many tumor cells, and it has a role in tumor survival and progression. In immune cells, upregulation of the receptor has a double effect on tumor suppression as well as tumor promotion. This review describes the structure of P2X7 and its role in the tumor microenvironment and presents possible mechanisms of P2X7 in tumor invasion and metastasis. Understanding the potential of P2X7 for tumor treatment, we also present several therapeutic agents targeting P2X7 and their mechanisms of action. In conclusion, the study of P2X7 is an important guideline for the use of clinical tumor therapy and may be able to provide a new idea for tumor treatment, but considering the complexity of the biological effects of P2X7, the drugs should be used with caution in clinical practice.

IntroductionBody size regulates all biological processes, including growth, reproduction, metabolism, trophic interactions, etc., and is the master trait across organisms, populations, and communities. Despite a rich literature on the impacts of human and natural disturbances on body size, a clear knowledge gap is the effect of the submarine canyons on the benthic size structures in the deep sea, hindering our understanding of the ecological processes of these dominant ecosystems on the continental margin.MethodsTherefore, we conducted repeated sediment sampling to compare meiofauna and macrofauna biomass body-size spectrum, growth, metabolism, and size composition from a high-energy submarine canyon, Gaoping Submarine Canyon (GPSC), and the adjacent continental slope off SW Taiwan. The GPSC is a dynamic ecosystem connected to a high sediment-yield small mountain river subjected to strong internal-tide energy, swift bottom currents, frequent mass wasting events, and high terrestrial sediment inputs.ResultsWe found that the meiofauna and macrofauna were characterized by relatively larger individuals dominating on the slope to smaller ones dominating in the canyon. As a result, the community biomass, secondary production, and respiration were depressed with distinctive biomass-size composition in the canyon compared to the non-canyon slope. The environmental factors related to internal tide disturbance (i.e., bottom current velocity, duration of sediment erosion, or low light transmission) substantially influence the body size composition of the canyon benthos, while food supplies (i.e., TOC and C/N ratio) and sediment characters (i.e., grain size and porosity) correlated closely with the slope communities.DiscussionWe concluded that the disturbed condition in the GPSC may have wiped out or depressed the local benthic assemblages, and only the smaller, more resilient species could persist. Our results also highlight that the alterations of the canyon benthic community could be a reference to deep-sea ecosystems under anthropogenic disturbances or global climate change.

BackgroundSynchronous multiple primary malignant neoplasms occurring at the same time (SMPMNS) are not currently uncommon in clinical oncological practice; however, the diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for SMPMNS needs further elucidation.PurposeThis study aimed to evaluate the application of 18F-FDG PET/CT in patients with SMPMNS.Materials and methodsThe clinical and imaging data of 37 patients with SMPMNS who had undergone 18F-FDG PET/CT from October 2010 to December 2020 were retrospectively analyzed. The kappa consistency test was applied to evaluate the consistency of the diagnostic performance between PET/CT and conventional imaging (CI). The sensitivity, specificity, and accuracy of PET/CT and CI in the detection of metastatic lesions were compared.ResultsThis retrospective diagnostic study included 74 lesions identified in 37 patients with SMPMNS, with 94.6% of patients having double primary tumors. Of the incidences of SMPMNS, 18.9% occurred in the same organ system, with respiratory tumors being the most common type of neoplasm (43.2%) and the lung being the most common primary site (40.5%). The overall survival of SMPMNS patients without metastases was longer than that of those with metastases (χ2 = 12.627, p = 0.000). The maximum standardized uptake value (SUVmax), the SUVmax ratio (larger SUVmax/smaller SUVmax), and the difference index of SUVmax (DISUVmax) [(larger SUVmax − smaller SUVmax)/larger SUVmax] of the primary lesions ranged from 0.9 to 41.7 (average = 12.3 ± 7.9), from 0.3 to 26.7 (average = 4.4 ± 6.9), and from 0.0% to 96.3% (average = 50.3% ± 29.3%), respectively. With regard to diagnostic accuracy, PET/CT and CI showed poor consistency (κ = 0.096, p = 0.173). For the diagnosis of primary lesions (diagnosed and misdiagnosed), PET/CT and CI also showed poor consistency (κ = 0.277, p = 0.000), but the diagnostic performance of PET/CT was better than that of CI. In the diagnosis of metastases, the patient-based sensitivity, specificity, and accuracy of PET/CT were 100.0%, 81.8%, and 89.2%, respectively, while those of CI were 73.3%, 100.0%, 89.2%, respectively. The sensitivity and specificity values were significantly different, with PET/CT having higher sensitivity (p = 0.02) and CI showing higher specificity (p = 0.02).Conclusions18F-FDG PET/CT improves the diagnostic performance for SMPMNS and is a good imaging modality for patients with SMPMNS.

Gaoping Submarine Canyon (GPSC) off southwestern Taiwan is a high energy canyon connected to a small mountain river with extremely high sediment load (∼10 kt km–2 y–1). Due to heavy seasonal precipitation (>3,000 mm y–1) and high tectonic activity in the region, the GPSC is known for active sediment transport processes and associated submarine geohazards (e.g., submarine cable breaks). More importantly, strong internal tides have been recorded in the GPSC to drive head-ward, bottom-intensified currents, which result in sediment erosion and resuspension in response to the tidal cycles. To understand the effects of extreme physical conditions on marine nematodes, we sampled the surface sediments along the thalweg of upper GPSC and adjacent slope (200–1,100 m) using a multicorer in the summer and fall of 2015. We found that the nematode species, functional, trophic diversity and maturity dropped significantly in the GPSC as compared with slope communities, but the nematode abundances were not affected by the adverse conditions in the canyon. The non-selective deposit-feeding, fast colonizing nematodes (e.g., Sabatieria, Daptonema, Axonolaimus, and Metadesmolaimus) dominated the canyon seafloor. In contrast, other species of non-selective deposit feeders (Setosabatieria and Elzalia), epigrowth feeders (Craspodema), omnivores/predators (Paramesacanthion), and other species constituted the diverse nematode assemblages on the slope. We found that the strong bottom currents in the GPSC may depress the local nematode diversity by removing the organic-rich, fine-grained sediments; therefore, only the resilient or fast recovering nematode species could survive and prevail. The high species turnover with depth and between the canyon and slope habitats demonstrates that strong environmental filtering processes were the primary mechanism shaping the nematode community assembly off SW Taiwan. Between the canyon and slope, a considerable contribution of nestedness pattern also indicates some degree of local extinction and dispersal limitation in the dynamic GPSC.