Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states - A high-density EEG study.

Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.

Probing Intrinsic Neural Timescales in EEG with an Information-Theory Inspired Approach: Permutation Entropy Time Delay Estimation (PE-TD).

Time delays are a signature of many physical systems, including the brain, and considerably shape their dynamics; moreover, they play a key role in consciousness, as postulated by the temporo-spatial theory of consciousness (TTC). However, they are often not known a priori and need to be estimated from time series. In this study, we propose the use of permutation entropy (PE) to estimate time delays from neural time series as a more robust alternative to the widely used autocorrelation window (ACW). In the first part, we demonstrate the validity of this approach on synthetic neural data, and we show its resistance to regimes of nonstationarity in time series. Mirroring yet another example of comparable behavior between different nonlinear systems, permutation entropy-time delay estimation (PE-TD) is also able to measure intrinsic neural timescales (INTs) (temporal windows of neural activity at rest) from hd-EEG human data; additionally, this replication extends to the abnormal prolongation of INT values in disorders of consciousness (DoCs). Surprisingly, the correlation between ACW-0 and PE-TD decreases in a state-dependent manner when consciousness is lost, hinting at potential different regimes of nonstationarity and nonlinearity in conscious/unconscious states, consistent with many current theoretical frameworks on consciousness. In summary, we demonstrate the validity of PE-TD as a tool to extract relevant time scales from neural data; furthermore, given the divergence between ACW and PE-TD specific to DoC subjects, we hint at its potential use for the characterization of conscious states.

Initial CT-based radiomics nomogram for predicting in-hospital mortality in patients with traumatic brain injury: a multicenter development and validation study.

OBJECTIVE: To develop and validate a radiomic prediction model using initial noncontrast computed tomography (CT) at admission to predict in-hospital mortality in patients with traumatic brain injury (TBI). METHODS: A total of 379 TBI patients from three cohorts were categorized into training, internal validation, and external validation sets. After filtering the unstable features with the minimum redundancy maximum relevance approach, the CT-based radiomics signature was selected by using the least absolute shrinkage and selection operator (LASSO) approach. A personalized predictive nomogram incorporating the radiomic signature and clinical features was developed using a multivariate logistic model to predict in-hospital mortality in patients with TBI. The calibration, discrimination, and clinical usefulness of the radiomics signature and nomogram were evaluated. RESULTS: The radiomic signature consisting of 12 features had areas under the curve (AUCs) of 0.734, 0.716, and 0.706 in the prediction of in-hospital mortality in the internal and two external validation cohorts. The personalized predictive nomogram integrating the radiomic and clinical features demonstrated significant calibration and discrimination with AUCs of 0.843, 0.811, and 0.834 in the internal and two external validation cohorts. Based on decision curve analysis (DCA), both the radiomic features and nomogram were found to be clinically significant and useful. CONCLUSION: This predictive nomogram incorporating the CT-based radiomic signature and clinical features had maximum accuracy and played an optimized role in the early prediction of in-hospital mortality. The results of this study provide vital insights for the early warning of death in TBI patients.

sTBI-GAN: An adversarial learning approach for data synthesis on traumatic brain segmentation.

Automatic brain segmentation of magnetic resonance images (MRIs) from severe traumatic brain injury (sTBI) patients is critical for brain abnormality assessments and brain network analysis. Construction of sTBI brain segmentation model requires manually annotated MR scans of sTBI patients, which becomes a challenging problem as it is quite impractical to implement sufficient annotations for sTBI images with large deformations and lesion erosion. Data augmentation techniques can be applied to alleviate the issue of limited training samples. However, conventional data augmentation strategies such as spatial and intensity transformation are unable to synthesize the deformation and lesions in traumatic brains, which limits the performance of the subsequent segmentation task. To address these issues, we propose a novel medical image inpainting model named sTBI-GAN to synthesize labeled sTBI MR scans by adversarial inpainting. The main strength of our sTBI-GAN method is that it can generate sTBI images and corresponding labels simultaneously, which has not been achieved in previous inpainting methods for medical images. We first generate the inpainted image under the guidance of edge information following a coarse-to-fine manner, and then the synthesized MR image is used as the prior for label inpainting. Furthermore, we introduce a registration-based template augmentation pipeline to increase the diversity of the synthesized image pairs and enhance the capacity of data augmentation. Experimental results show that the proposed sTBI-GAN method can synthesize high-quality labeled sTBI images, which greatly improves the 2D and 3D traumatic brain segmentation performance compared with the alternatives. Code is available at .

Alteration in ventral tegmental area and default mode network interplay and prediction of coma recovery in patients with sTBI.

Purpose: To investigate the role of VTA and DMN in modulating human consciousness in patient with sTBI. Methods: We mapped an atlas of VTA in the brainstem and a total of 19 region of interests in the ventral and dorsal DMN onto functional magnetic resonance imaging in 28 patients with sTBI and 28 healthy controls. We assessed the functional connectivity alteration in subcortical VTA and cortical DMN nodes in patients of coma. We evaluated the spatially distribution of FC alteration in VTA and DMN nodes after sTBI and evaluated their predictive value for coma recovery. Results: There was a decrease in FC between VTA and DMN in patients compared to controls. After decomposition, the FC between VTA and 10 DMN nodes were decreased whereas the FC within 2 DMN nodes were increased in patients with acute coma. The FC alteration in DMN nodes provided useful information for the early prediction of 6-month coma recovery in patients with sTBI. Conclusions: We provide initial evidence for the decreased FC between VTA and massive DMN nodes in patients with coma in acute phase of sTBI. We found that the FC alteration within DMN is more useful than the FC alteration between VTA and DMN for predicting coma recovery in patients with sTBI. VTA and DMN connectivity mapping provides an opportunity to advance the cortical-subcortical mechanism of human consciousness.

Default mode network overshadow executive control network in coma emergence and awakening prediction of patients with sTBI.

OBJECTIVE: We aimed to explore the pathogenesis of traumatic coma related to functional connectivity (FC) within the default mode network (DMN), within the executive control network (ECN) and between the DMN and ECN and to investigate its capacity for predicting awakening. METHODS: We carried out resting-state functional magnetic resonance imaging (fMRI) examinations on 28 traumatic coma patients and 28 age-matched healthy controls. DMN and ECN nodes were split into regions of interest (ROIs), and node-to-node FC analysis was conducted on individual participants. To identify coma pathogenesis, we compared the pairwise FC differences between coma patients and healthy controls. Meanwhile, we divided the traumatic coma patients into different subgroups based on their clinical outcome scores at 6 months postinjury. Considering the awakening prediction, we calculated the area under the curve (AUC) to evaluate the predictive ability of changed FC pairs. RESULTS: We found a massive pairwise FC alteration in the patients with traumatic coma compared to the healthy controls [45% (33/74) pairwise FC located in the DMN, 27% (20/74) pairwise FC located in the ECN, and 28% (21/74) pairwise FC located between the DMN and ECN]. Moreover, in the awake and coma groups, there were 67% (12/18) pairwise FC alterations located in the DMN and 33% (6/18) pairwise FC alterations located between the DMN and ECN. We also indicated that pairwise FC that showed a predictive value of 6-month awakening was mainly located in the DMN rather than in the ECN. Specifically, decreased FC between the right superior frontal gyrus and right parahippocampal gyrus (in the DMN) showed the highest predictive ability (AUC = 0.827). CONCLUSION: In the acute phase of severe traumatic brain injury (sTBI), the DMN plays a more prominent role than the ECN and the DMN-ECN interaction in the emergence of traumatic coma and the prediction of 6-month awakening.

Clinical Decision on Disorders of Consciousness After Acquired Brain Injury: Stepping Forward.

Major advances have been made over the past few decades in identifying and managing disorders of consciousness (DOC) in patients with acquired brain injury (ABI), bringing the transformation from a conceptualized definition to a complex clinical scenario worthy of scientific exploration. Given the continuously-evolving framework of precision medicine that integrates valuable behavioral assessment tools, sophisticated neuroimaging, and electrophysiological techniques, a considerably higher diagnostic accuracy rate of DOC may now be reached. During the treatment of patients with DOC, a variety of intervention methods are available, including amantadine and transcranial direct current stimulation, which have both provided class II evidence, zolpidem, which is also of high quality, and non-invasive stimulation, which appears to be more encouraging than pharmacological therapy. However, heterogeneity is profoundly ingrained in study designs, and only rare schemes have been recommended by authoritative institutions. There is still a lack of an effective clinical protocol for managing patients with DOC following ABI. To advance future clinical studies on DOC, we present a comprehensive review of the progress in clinical identification and management as well as some challenges in the pathophysiology of DOC. We propose a preliminary clinical decision protocol, which could serve as an ideal reference tool for many medical institutions.

Characteristics and Functional Application of Cellulose Fibers Extracted from Cow Dung Wastes.

The widespread use of petroleum-based products has led to increasing environmental and ecological problems, while the extraction and application of various natural cellulose fibers have received increasing attention. This research focuses on the extraction of cellulose fibers from cow dung using different treatments: hot water, hydrogen peroxide (H2O2), sodium hydroxide (NaOH) and potassium hydroxide (KOH) boilings, as well as a selection of the best quality cow dung fibers for papermaking with quality control. The study's objective is to find a sustainable method to extract as much material as possible from renewable biomass feedstock. The results show that the best extraction rate is obtained by KOH boiling with 42% cellulose fibers extracted. Corresponding handmade paper has a burst index of 2.48 KPam2/g, a tear index of 4.83 mNm2/g and a tensile index of 26.72 Nm/g. This project expands the sources of natural cellulose fibers to an eco-friendly and sustainable one and opens up new applications for cow dung.

Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage.

Brain network analysis based on structural and functional magnetic resonance imaging (MRI) is considered as an effective method for consciousness evaluation of hydrocephalus patients, which can also be applied to facilitate the ameliorative effect of lumbar cerebrospinal fluid drainage (LCFD). Automatic brain parcellation is a prerequisite for brain network construction. However, hydrocephalus images usually have large deformations and lesion erosions, which becomes challenging for ensuring effective brain parcellation works. In this paper, we develop a novel and robust method for segmenting brain regions of hydrocephalus images. Our main contribution is to design an innovative inpainting method that can amend the large deformations and lesion erosions in hydrocephalus images, and synthesize the normal brain version without injury. The synthesized images can effectively support brain parcellation tasks and lay the foundation for the subsequent brain network construction work. Specifically, the novelty of the inpainting method is that it can utilize the symmetric properties of the brain structure to ensure the quality of the synthesized results. Experiments show that the proposed brain abnormality inpainting method can effectively aid the brain network construction, and improve the CRS-R score estimation which represents the patient's consciousness states. Furthermore, the brain network analysis based on our enhanced brain parcellation method has demonstrated potential imaging biomarkers for better interpreting and understanding the recovery of consciousness in patients with secondary hydrocephalus.

Clinical Characteristics of and Treatment Strategy for Hydrocephalus in Patients With Severe Disorders of Consciousness.

Abstract Making an appropriate diagnosis and administering effective treatment for hydrocephalus in patients with severe disorders of consciousness (DOC) remains controversial and difficult. Given that the typical symptoms are usually concealed by the limited behavioral responsiveness of patients with severe DOC, hydrocephalus diagnosis is likely to be missed in the clinic. Even if not, the presence of hydrocephalus may reduce the likelihood of DOC recovery, posing a conundrum for clinicians. From December 2013 to January 2023, the clinical data and therapeutic schedule of hydrocephalus in patients with severe DOC at Huashan Hospital's Neurosurgical Emergency Center were studied retrospectively. Sixty-eight patients (mean age [± SD] 52.53 ± 17.03 years, 35 males and 33 females) with severe DOC were included. The hydrocephalus was discovered after computed tomography (CT) or magnetic resonance imaging (MRI) revealed enlarged ventricles in the patients. During hospitalization, patients underwent a surgical treatment that included a ventriculoperitoneal (V-P) shunt and/or cranioplasty (CP) implantation. Following the surgery, an individualized V-P pressure was established based on the patient's ventricle size and neurological function variation. To account for the improvement in consciousness in patients with severe DOC, Glasgow Coma Scale (GCS) and Coma Recovery Scale-Revised (CRS-R) assessments were performed before and after hydrocephalus treatment. All patients with severe DOC had varying degrees of ventricular enlargement, deformation, and poor brain compliance. Approximately 60.3% (41/68) of them had low- or negative-pressure hydrocephalus (LPH or NegPH). Of the patients, 45.5% (31/68) had a one-stage V-P shunt and CP operation performed concurrently, whereas the remaining 37 patients had a single V-P shunt operation performed independently. Besides two patients with DOC who developed surgical complications, 92.4% (61/66) of the survivors showed an improvement in consciousness after hydrocephalus treatment. In patients with severe DOC, LPH or NegPH was common. Secondary hydrocephalus in patients with DOC had been largely ignored, hampering their neurological rehabilitation. Even months or years after the onset of severe DOC, active treatment of hydrocephalus can significantly improve patients' consciousness and neurological function. This study summarized several evidence-based treatment experiences of hydrocephalus in patients with DOC.

Clinical application of neuromodulation therapy in patients with disorder of consciousness: A pooled analysis of 544 participants.

BACKGROUND: The number of patients with disorders of consciousness (DoC) has increased dramatically with the advancement of intensive care and emergency medicine, which brings tremendous economic burdens and even ethical issues to families and society. OBJECTIVE: To evaluate the effectiveness of neuromodulation therapy for patients with DoC. METHODS: First, we conducted a literature review of individual patient data (IPD) on PubMed, EMBASE, and Cochrane-controlled trials following PRISMA guidelines. Then, we collected neuromodulation cases from our institution. Finally, we conducted a pooled analysis using the participants from the medical literature (n = 522) and our local institutions (n = 22). RESULTS: In this pooled analysis of 544 patients with DoC with a mean age of 46.33 years, our results revealed that patients have improved CRS-R scores [1.0 points (95% CI, 0.57-1.42)] after neuromodulation. Among them, patients have better effectiveness in traumatic than non-traumatic etiology (P < 0.05). The effectiveness of consciousness improvement could be affected by the age, baseline consciousness state, and duration of stimulation. Compared with non-invasive intervention, an invasive intervention can bring more behavioral improvement (P < 0.0001) to MCS rather than UWS/VS patients. Importantly, neuromodulation is a valuable therapy even years after the onset of DoC. CONCLUSION: This pooled analysis spotlights that the application of neuromodulation can improve the behavioral performance of patients with DoC. A preliminary trend is that age, etiology, baseline consciousness state, and stimulation duration could impact its effectiveness.

Behavioral effects in disorders of consciousness following transcranial direct current stimulation: A systematic review and individual patient data meta-analysis of randomized clinical trials.

Background: In patients with Disorders of Consciousness (DoC), recent evidence suggests that transcranial direct current stimulation (tDCS) can be a promising intervention for them. However, there has been little agreement on the treatment effect and the optimal treatment strategy for the tDCS in patients with DoC. Objective: In this meta-analysis of individual patient data (IPD), we assess whether tDCS could improve DoC patients' behavioral performance. We also determine whether these treatment effects could be modified by patient characteristics or tDCS protocol. Methods: We searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials until 7 April 2022 using the terms "persistent vegetative state," "minimally conscious state," "disorder of consciousness," or "unresponsive wakefulness syndrome," and "transcranial direct current stimulation" to identify Randomized Controlled Trials (RCTs) in English-language publications. Studies were eligible for inclusion if they reported pre- and post-tDCS Coma Recovery Scale-Revised (CRS-R) scores. From the included studies, patients who had incomplete data were excluded. We performed a meta-analysis to assess the treatment effect of the tDCS compared with sham control. Additionally, various subgroup analyses were performed to determine whether specific patient characteristics could modify the treatment effect and to find out the optimal tDCS protocol. Results: We identified 145 papers, but eventually eight trials (including 181 patients) were included in the analysis, and one individual data were excluded because of incomplete data. Our meta-analysis demonstrated a mean difference change in the CRS-R score of 0.89 (95% CI, 0.17-1.61) between tDCS and sham-control, favoring tDCS. The subgroup analysis showed that patients who were male or with a minimally conscious state (MCS) diagnosis were associated with a greater improvement in CRS-R score. We also found that patients who underwent five or more sessions of tDCS protocol had a better treatment effect than just one session. Conclusion: The result shows that tDCS can improve the behavioral performance of DoC patients. The heterogeneity of the treatment effect existed within the patients' baseline conditions and the stimulation protocol. More explorative studies on the optimal tDCS protocol and the most beneficial patient group based on the mechanism of tDCS are required in the future. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD42022331241.

Integrating Lipidomics and Transcriptomics Reveals the Crosstalk Between Oxidative Stress and Neuroinflammation in Central Nervous System Demyelination.

Multiple sclerosis (MS) is an incurable and progressive neurodegenerative disease that affects more than 2.5 million people worldwide and brings tremendous economic pressures to society. However, the pathophysiology of MS is still not fully elucidated, and there is no effective treatment. Demyelination is thought to be the primary pathophysiological alteration in MS, and our previous study found abnormal lipid metabolism in the demyelinated corpus callosum. Growing evidence indicates that central nervous system (CNS) demyelinating diseases never result from one independent factor, and the simultaneous participation of abnormal lipid metabolism, oxidative stress, and neuroinflammation could potentiate each other in the pathogenesis of MS. Therefore, a single omics analysis cannot provide a full description of any neurodegenerative disease. It has been demonstrated that oxidative stress and neuroinflammation are two reciprocal causative reasons for the progression of MS disease. However, the potential crosstalk between oxidative stress and neuroinflammation remains elusive so far. With an integrated analysis of targeted lipidomics and transcriptomics, our research presents the potential interaction between abnormalities of lipid metabolism, mitochondrial dysfunction, oxidative stress, and neuroinflammation in CNS demyelinating diseases. The findings of this paper may be used to identify possible targets for the therapy of CNS demyelinating diseases.

Neuroinflammation Following Traumatic Brain Injury: Take It Seriously or Not.

Traumatic brain injury (TBI) is associated with high mortality and disability, with a substantial socioeconomic burden. With the standardization of the treatment process, there is increasing interest in the role that the secondary insult of TBI plays in outcome heterogeneity. The secondary insult is neither detrimental nor beneficial in an absolute sense, among which the inflammatory response was a complex cascade of events and can thus be regarded as a double-edged sword. Therefore, clinicians should take the generation and balance of neuroinflammation following TBI seriously. In this review, we summarize the current human and animal model studies of neuroinflammation and provide a better understanding of the inflammatory response in the different stages of TBI. In particular, advances in neuroinflammation using proteomic and transcriptomic techniques have enabled us to identify a functional specific delineation of the immune cell in TBI patients. Based on recent advances in our understanding of immune cell activation, we present the difference between diffuse axonal injury and focal brain injury. In addition, we give a figurative profiling of the general paradigm in the pre- and post-injury inflammatory settings employing a bow-tie framework.

Chinese Admission Warning Strategy for Predicting the Hospital Discharge Outcome in Patients with Traumatic Brain Injury.

OBJECTIVE: To develop and validate an admission warning strategy that incorporates the general emergency department indicators for predicting the hospital discharge outcome of patients with traumatic brain injury (TBI) in China. METHODS: This admission warning strategy was developed in a primary cohort that consisted of 605 patients with TBI who were admitted within 6 h of injury. The least absolute shrinkage and selection operator and multivariable logistic regression analysis were used to develop the early warning strategy of selected indicators. Two sub-cohorts consisting of 180 and 107 patients with TBI were used for the external validation. RESULTS: Indicators of the strategy included three categories: baseline characteristics, imaging and laboratory indicators. This strategy displayed good calibration and good discrimination. A high C-index was reached in the internal validation. The multicenter external validation cohort still showed good discrimination C-indices. Decision curve analysis (DCA) showed the actual needs of this strategy when the possibility threshold was 0.01 for the primary cohort, and at thresholds of 0.02-0.83 and 0.01-0.88 for the two sub-cohorts, respectively. In addition, this strategy exhibited a significant prognostic capacity compared to the traditional single predictors, and this optimization was also observed in two external validation cohorts. CONCLUSIONS: We developed and validated an admission warning strategy that can be quickly deployed in the emergency department. This strategy can be used as an ideal tool for predicting hospital discharge outcomes and providing objective evidence for early informed consent of the hospital discharge outcome to the family members of TBI patients.

High PYGL Expression Predicts Poor Prognosis in Human Gliomas.

Background: PYGL has been reported as a glycogen degradation-related gene, which is up-regulated in many tumors. This study was designed to investigate the predictive value of high PYGL expression in patients with gliomas through bioinformatics analysis of the gene transcriptome and the single-cell sequencing data. Methods: The gene transcriptome data of 595 glioma patients from the TCGA database and the single-cell RNA sequencing data of 7,930 GBM cells from the GEO database were included in the study. Differential analysis was used to find the distribution of expression of PYGL in different groups of glioma patients. OS analysis was used to assess the influence of the high expression of PYGL on the prognosis of patients. The reliability of its prediction was evaluated by the AUC of ROC and the C-index. The GSEA be used to reveal potential mechanisms. The single-cell analysis was used to observe the high expression of PYGL in different cell groups to further analyze the mechanism of its prediction. Results: Differential analysis identified the expression level of PYGL is positively associated with glioma malignancy. OS analysis and Cox regression analyses showed high expression of PYGL was an independent factor for poor prognosis of gliomas (p < 0.05). The AUC values were 0.838 (1-year ROC), 0.864 (3-year ROC) and 0.833 (5-year ROC). The C index was 0.81. The GSEA showed that gene sets related to MTORC1 signaling, glycolysis, hypoxia, PI3K/AKT/mTOR signaling, KRAS signaling up and angiogenesis were differentially enriched in the high PYGL expression phenotype. The single-cell sequencing data analysis showed TAMs and malignant cells in GBM tissues expressed a high level of PYGL. Conclusion: The high expression of PYGL is an independent predictor of poor prognosis in patients with glioma.

Case Report: Direct Visualization of the Nervus Intermedius During the Microvascular Decompression Procedure: Should We Take It Seriously?

Background: Nervus intermedius neuralgia (NIN), known as geniculate neuralgia (GN), is an uncommon cranial nerve disease caused by an offending vessel compressing the nervus intermedius (NI). Microvascular decompression (MVD) has now become a valued treatment approach for NIN because it can resolve neurovascular conflict (NVC) at the root entry zone of the NI. In the era of continuously optimizing and improving the surgical technique of MVD, further minimization of all possible postoperative complications is not only welcome but also necessary. Objective: The aim of this work is to assess the postoperative outcome of direct visualization of the NI during the MVD procedure. Methods: This study retrospectively reviewed the clinical records of a group of seven consecutive patients with NIN who underwent MVD in the period of 2013-2020 in our clinic and 16 studies reported NIN patients who underwent MVD in the period of 2007-2020. Results: In total, 91.3% of all patients experienced immediate and complete relief of cranial neuralgia after MVD. Six of 23 patients have experienced direct visualization of the NI intraoperatively, and 66.7% of those patients had complications such as facial paralysis, dysacousia, or a combination of these conditions postoperatively. Slight surgical approach-related complications such as complaints associated with excessive drainage of cerebrospinal fluid (CSF), nausea and vertigo, and delayed wound union were observed in 80% of the remaining 15 patients, and these symptoms are totally relieved in the telephone and outpatient follow-up after 6 months. Conclusion: Our case series shows that MVD produced immediate pain relief in the majority of NIN patients. MVD carries surgical risk, especially in patients who experience direct visualization of the NI after mechanical stretch and blunt dissection in surgical procedures. Attempts to avoid mechanical stretch and blunt dissection of the compressed nerve were important for intraoperative neuroprotection, especially facial nerve protection.

Integration of single-cell and bulk RNA sequencing data reveals key cell types and regulators in traumatic brain injury.

Traumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, whose symptoms ranging from mild to severe, even life-threatening. However, specific cell types and key regulators involved in traumatic brain injury have not been well elucidated. In this study, utilizing single-cell RNA-seq (scRNA-seq) data from mice with TBI, we have successfully identified and characterized 13 cell populations including astrocytes, oligodendrocyte, newly formed oligodendrocytes, microglia, two types of endothelial cells, five types of excitatory and two types of inhibitory neurons. Differential expression analysis and gene set enrichment analysis (GSEA) revealed the upregulation of microglia and endothelial markers, along with the downregulation of markers of excitatory neurons in TBI. The cell-cell communication analysis revealed that microglia and endothelial cell might interact through the interaction of Icam1-Il2rg and C1qa-Cd93, and microglia might also communicate with each other via Icam1-Itagm. The autocrine ligand-receptor in microglia might result in activation of TYROBP causal network via Icam1-Itgam. The cell-cell contact between microglia and endothelial cell might activate integrin signaling pathways. Moreover, we also found that genes involved in microglia activation were highly downregulated in Tyrobp/Dap12-deficient microglia, indicating that the upregulation of Tyrobp and TYROBP causal network in microglia might be a candidate therapeutic target in TBI. In contrast, the excitatory neurons were involved in maintaining normal brain function, and their inactivation might cause dysfunction of nervous system in TBI patients. In conclusion, the present study has discerned major cell types such as microglia, endothelial cells and excitatory neurons, and revealed key regulator such as TYROBP, C1QA, and CD93 in TBI, which shall improve our understanding of the pathogenesis of TBI.

The Gene Coexpression Analysis Identifies Functional Modules Dynamically Changed After Traumatic Brain Injury.

Traumatic brain injury (TBI) is a major cause of morbidity and mortality, both in adult and pediatric populations. However, the dynamic changes of gene expression profiles following TBI have not been fully understood. In this study, we identified the differentially expressed genes (DEGs) following TBI. Remarkably, Serpina3n, Asf1b, Folr1, LOC100366216, Clec12a, Olr1, Timp1, Hspb1, Lcn2, and Spp1 were identified as the top 10 with the highest statistical significance. The weighted gene coexpression analysis (WGCNA) identified 12 functional modules from the DEGs, which showed specific expression patterns over time and were characterized by enrichment analysis. Specifically, the black and turquoise modules were mainly involved in energy metabolism and protein translation. The green yellow and yellow modules including Hmox1, Mif, Anxa2, Timp1, Gfap, Cd9, Gja1, Pdpn, and Gpx1 were related to response to wounding, indicating that expression of these genes such as Hmox1, Anxa2, and Timp1 could protect the brains from brain injury. The green yellow module highlighted genes involved in microglial cell activation such as Tyrobp, Cx3cr1, Grn, Trem2, C1qa, and Aif1, suggesting that these genes were responsible for the inflammatory response caused by TBI. The upregulation of these genes has been validated in an independent dataset. These results indicated that the key genes in microglia cell activation may serve as a promising therapeutic target for TBI. In summary, the present study provided a full view of the dynamic gene expression changes following TBI.

Essential role of ALKBH5-mediated RNA demethylation modification in bile acid-induced gastric intestinal metaplasia.

Bile acid reflux and subsequent caudal-related homeobox 2 (CDX2) activation contribute to gastric intestinal metaplasia (IM), a precursor of gastric cancer; however, the mechanism underlying this phenomenon is unclear. Here, we demonstrate that alkylation repair homolog protein 5 (ALKBH5), a major RNA N6-adenosine demethylase, is required for bile acid-induced gastric IM. Mechanistically, we revealed the N6-methyladenosine (m6A) modification profile in gastric IM for the first time and identified ZNF333 as a novel m6A target of ALKBH5. ALKBH5 was shown to demethylate ZNF333 mRNA, leading to enhanced ZNF333 expression by abolishing m6A-YTHDF2-dependent mRNA degradation. In addition, ALKBH5 activated CDX2 and downstream intestinal markers by targeting the ZNF333/CYLD axis and activating NF-κB signaling. Reciprocally, p65, the key transcription factor of the canonical NF-κB pathway, enhanced the transcription activity of ALKBH5 in the nucleus, thus forming a positive feedforward circuit. Furthermore, ALKBH5 levels were positively correlated with ZNF333 and CDX2 levels in IM tissues, indicating significant clinical relevance. Collectively, our findings suggest that an m6A modification-associated positive feedforward loop between ALKBH5 and NF-κB signaling is involved in generating the IM phenotype of gastric epithelial cells. Targeting the ALKBH5/ZNF333/CYLD/CDX2 axis may be a useful therapeutic strategy for gastric IM in patients with bile regurgitation.