The microbiome is prevalent throughout human bodies, with profound health implications. However, it remains unclear whether it is present and active in human CSF, which has been long considered aseptic due to the blood-brain barrier.

Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope. Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage. Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly. Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists. Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.

Objective: Tuberculosis infection of the Central Nervous System can cause severe inflammation in microglia, and NLRP3 inflammasome is also an important source of inflammation in microglia. Therefore, in this study, we used a co-culture model of rat microglia and tuberculosis H37Ra strain to explore the influence of tuberculosis infection on the NLRP3 inflammasome in microglia and its regulation mechanism.Methods: We cultured primary microglia from SD rats and co-cultured with tuberculosis H37Ra strain for 4 hours to establish a co-culture model. At the same time, MCC950, Z-YVAD-FMK, BAY-11-7082, Dexamethasone, RU486, BzATP, BBG and extracellular high potassium environment were used to intervene the co-cultivation process. Subsequently, western blot, real-time PCR, ELISA and other methods were used to detect the changes of NLRP3 inflammasome-related molecules in microglia.Results: After co-cultivation, the NLRP3 inflammasomes in microglia were activated and released a large amount of IL-18 and IL-1β. By regulating NLRP3 inflammasome complex, caspase-1, NF-κB and P2X7R during the co-culture process, it could effectively reduce the release of IL-18 and IL-1β, and the mortality of microglia.Conclusion: Our results indicate that the NLRP3 inflammasome pathway is an important part of the inflammatory response of microglia caused by tuberculosis infection. By intervening the NLRP3 inflammasome pathway, it can significantly reduce the inflammatory response and mortality of microglia during the tuberculosis H37Ra strain infection. This research can help us further understand the inflammatory response mechanism of the central nervous system during tuberculosis infection and improve its treatment.

Background: As one of the leading causes of morbidity and mortality, stroke and its recurrence has attracted more and more attention. Dl-3-n-butylphthalidle(NBP) has been widely used for treating acute ischemic stroke in China and shows a great clinical effect. NBP plays a role in different pathophysiological processes in the treatment of ischemic stroke, including antioxidants, anti-inflammatory, anti-apoptotic, anti-thrombosis, and mitochondrial protection. Many randomized, double-blind, placebo-controlled, multicenter clinical trials suggest that NBP is a safe and effective treatment for ischemic stroke. To sum up, the current research is mainly focused on the short-term treatment of stroke patients with RCT (randomized controlled trial). Therefore, we designed this study to confirm the role of butylphthalide in secondary stroke prevention in the real world.Methods: This study will be a multicenter, prospective real-world trial. We would recruit 8000 patients with ischemic stroke from 78 public hospitals in China. All participants will be allocated to one of two parallel treatment groups according to their own wills: (1) butylphthalide group: 0.2 g of butylphthalide capsules three times daily plus routine treatment (aspirin 50-300 mg/d, clopidogrel 75 mg/d, etc.); (2) control group: routine treatment (aspirin 50-300 mg/d, clopidogrel 75 mg/d, etc.). Treatment duration is 90 consecutive days or more. The primary outcome is recurrence rate of stroke within 1 month, 3 months, 6 months and 1 year in butylphthalide group and control group. The secondary outcomes included NIHSS score, the mRS score, other clinical cardiovascular events within one year (sudden death / myocardial infarction / arrhythmia / heart failure, etc.), and adverse events of patients in groups. NIHSS will be captured in the first month after discharge, and the others will be captured at the same time points as the primary end point.Discussion: This trial will be exploring the efficacy and safety of butylphthalide in secondary prevention of ischemic stroke to expand the scope of application of butylphthalide soft capsules and provide new ideas for enriching the secondary prevention of stroke.Trial registration: Chinese Clinical Trial Registry (ChiCTR). Trial registration number: ChiCTR2000034481. Registered on 6 July 2020,http://www.chictr.org.cn/showproj.aspx?proj=55800

Ischemic stroke, a neurological condition with a complicated etiology that is accompanied by severe inflammation and oxidative stress, and ethanol (EtOH) may aggravate ischemia/reperfusion (I/R)-induced brain damage. However, the effect of prolonged alcohol intake on acute brain injury remains ambiguous. As part of the mitogen-activated protein kinase (MAPK) family, p38γ is involved in ferroptosis and inflammation in various diseases. This study explored how p38γ is involved in the effects of chronic EtOH consumption and brain injury caused by cerebral I/R. Brain damage was induced in the mice via the administration of a liquid alcohol-containing diet for 8 weeks, middle cerebral artery occlusion reperfusion (MCAO/R), or a combination of both. We verified that EtOH significantly exacerbated MCAO/R-induced brain damage, ferroptosis and inflammation. Notably, p38γ levels were increased in experimental mouse and cell models. p38γ knockdown markedly attenuated brain tissue damage, oxidative stress, and inflammatory cell infiltration in EtOH + MCAO/R-treated mice. Mechanistic experiments revealed that p38γ may regulate inflammation and ferroptosis through the p53/SLC7A11 pathway. Overall, our experimental results indicate that p38γ is crucial for regulating EtOH- and I/R-induced brain damage by modulating the p53/SLC7A11 pathway.