Identification of novel key markers that are induced during traumatic brain injury in mice.

Background: Traumatic brain injury (TBI) has emerged as an increasing public health problem but has not been well studied, particularly the mechanisms of brain cellular behaviors during TBI. Methods: In this study, we established an ischemia/reperfusion (I/R) brain injury mice model using transient middle cerebral artery occlusion (tMCAO) strategy. After then, RNA-sequencing of frontal lobes was performed to screen key inducers during TBI. To further verify the selected genes, we collected peripheral blood mononuclear cells (PBMCs) from TBI patients within 24 h who attended intensive care unit (ICU) in the Affiliated Hospital of Yangzhou University and analyzed the genes expression using RT-qPCR. Finally, the receiver operator characteristic (ROC) curves and co-expression with cellular senescence markers were applied to evaluate the predictive value of the genes. Results: A total of six genes were screened out from the RNA-sequencing based on their novelty in TBI and implications in apoptosis and cellular senescence signaling. RT-qPCR analysis of PBMCs from patients showed the six genes were all up-regulated during TBI after comparing with healthy volunteers who attended the hospital for physical examination. The area under ROC (AUC) curves were all >0.7, and the co-expression scores of the six genes with senescence markers were all significantly positive. We thus identified TGM1, TGM2, ATF3, RCN3, ORAI1 and ITPR3 as novel key markers that are induced during TBI, and these markers may also serve as potential predictors for the progression of TBI.

The diagnostic and prognostic value of glial fibrillary acidic protein in traumatic brain injury: a systematic review and meta-analysis.

OBJECTIVES: Over the years, blood biomarkers have been extensively applied for diagnostic and prognostic assessment of traumatic brain injury (TBI). Herein, we conducted a meta-analysis to evaluate the diagnostic and prognostic value of glial fibrillary acidic protein (GFAP) for TBI patients. METHODS: The online databases, including PubMed, Embase, Cochrane Library, CNKI, and WFSD, were systematically retrieved from inception until May 2021. The RevMan 5.3 software and Stata 15 were used to conduct data analysis. RESULTS: A total of 22 eligible studies comprising 3709 patients were included in this meta-analysis. The pooled results indicated that serum GFAP had a diagnostic value in detecting traumatic intracranial lesions (AUC 0.81; 95% CI 0.77-0.84; p < 0.00001). The pooled sensitivity and specificity were 0.93 (95% CI 0.81-0.98), and 0.66 (95% 0.53-0.77; p < 0.00001), respectively. For assessment of unfavorable outcome, the pooled sensitivity, specificity and AUC value were 0.66 (95% CI 0.54-0.76; p < 0.00001), 0.82(95% CI 0.72-0.90; p < 0.00001), and 0.82 (95% CI 0.76-0.88; p < 0.00001), respectively. Besides, GFAP exhibited a significant value in predicting mortality (AUC 0.81; 95% CI 0.77-0.84; p < 0.00001), with high sensitivity and specificity (0.86, 95% CI 0.79-0.92, p < 0.00001, and 0.66, 95% CI 0.52-0.77, p < 0.00001). The subgroup analysis indicated that the type of TBI and cut-off value were potential sources of heterogeneity, which influenced the pooled AUC values for mortality prediction. CONCLUSIONS: Our meta-analysis indicated that GFAP had diagnostic and prognostic value for TBI patients, especially during the early TBI.

Aberrant brain functional hubs convergence in the acute severe traumatic brain injury patients with rapidly recovering.

PURPOSE: We aimed to identify the aberrant functional hubs in patients with acute severe traumatic brain injury (sTBI) and investigate whether they could help inform prognosis. METHODS: Twenty-eight sTBI patients and health controls underwent imaging scanning. The graph-theoretical measure of degree centrality (DC) was applied to identify the abnormal brain functional hubs and conjoined with regions of interest-based analysis to investigate their interaction and impact on whole-brain. We further split sTBI patients into two subgroups according to their recovery to explore whether the fractional amplitude of low-frequency fluctuation (fALFF) roles in functional connectivity (FC) differential areas to help inform the patients' long-term prognosis. RESULTS: We identified the part of prefrontal cortex (PFC), precentral and postcentral gyrus (Pre-/Post-CG), cingulate gyrus (CgG), posterior medial cortex (PMC), and brainstem that could be core hubs whose DC was significantly increased in patients with acute sTBI. The interaction strength of the paired hubs could be enhanced (CG-PFC, CgG-PFC, CG-brainstem, CgG-brainstem, PMC-brainstem, and PFC-brainstem) and weakened (CG-CgG, CG-PMC, CgG-PMC, and PMC-PFC), compared with healthy controls. We also found abnormal FC in 5 hubs to whole-brain. The spontaneous brain activities in the FC differential regions [e.g., the fALFF and mean fALFF value] were valid to predict outcome at 6-month in patients with sTBI. CONCLUSION: We demonstrated a compensatory mechanism that part of brain regions will converge into abnormal functional hubs in patients with acute sTBI, which provides a potential approach to objectively predicting patients' long-term outcome.

Mental health and fatigue status of the medical workforce during the COVID-19 outbreak in the Yangzhou city, China.

Background: When the coronavirus disease 2019 (COVID-19) erupted in Yangzhou, China, at the end of July 2021, medical workers in Yangzhou immediately joined the frontline for the fight against the pandemic. This study aimed to identify the mental health and fatigue experienced by the medical workers in Yangzhou during the COVID-19 outbreak. Methods: We included 233 medical workers who participated in the front-line work for more than 1 month through the questionnaire, including doctors, nurses, medical technicians and medical students. The generalized anxiety disorder-7 (GAD-7), patient health questionnaire-9 (PHQ-9), and Fatigue self-assessment scale (FSAS) were administered to the participants and their responses were evaluated. Results: A total of 233 eligible questionnaires were received. Among them, 130 people (57.08%) were probably anxious and 141 (60.52%) people were clinically depressed. Poor sleep was considered an independent risk factor for anxiety (OR = 7.164, 95% CI: 3.365 15.251, p = 0.000) and depression (OR = 6.899, 95% CI: 3.392 14.030, p = 0.000). A high PHQ-9 score was considered an independent risk factor for general fatigue (OR = 1.697, 95% CI: 1.481 1.944, p = 0.000). Mental fatigue (OR = 1.092, 95% CI: 1.027 1.161, p = 0.005) and fatigue response to sleep/rest (OR = 1.043, 95% CI: 1.011 1.076 p = 0.008) were considered independent risk factors for general fatigue. Conclusion: Poor quality of sleep led to probable anxiety, depression, and general fatigue. Mental fatigue and fatigue response to sleep/rest were independent risk factors for depression, which merits attention for battling COVID-19.

Investigating the mechanism and prognosis of patients with disorders of consciousness on the basis of brain networks between the thalamus and whole-brain.

Purpose: This study aimed to investigate the changes in the functional connectivity between the bilateral thalamus and the whole-brain in patients with severe traumatic brain injury (sTBI) patients suffering from disorders of consciousness (DOC) and to explore their potential prognostic representation capacity. Methods: The sTBI patients suffering from DOC and healthy controls underwent functional magnetic resonance imaging. We defined patients with the Extended Glasgow Outcome Score (GOS-E) ≥ 3 as the wake group and GOS-E = 2 as the coma group. The differences in functional connectivity between sTBI and healthy controls and between wake and coma groups were compared. Based on the brain regions with altered functional connectivity between wake and coma groups, they were divided into 26 regions of interest. Based on the Z-values of regions of interest, the receiver operating characteristic analysis was conducted to classify the prognosis of patients. Results: A total of 28 patients and 15 healthy controls were finally included. Patients who had DOC indicated a significant disruption of functional connectivity between the bilateral thalamus and the whole-brain (FDR corrected, P < 0.0007). The functional connectivity strength (bilateral thalamus to whole-brain) was significantly different between coma patients who went on to wake and those who were eventually non-awake at 6 months after sTBI (Alphasim corrected, P < 0.05). Furthermore, the 26 regions of interest had a similar or even better prognostic distinction ability than the admission Glasgow coma score. Conclusion: The thalamus-based system of consciousness of sTBI patients suffering from DOC is disrupted. There are differences in the thalamus-to-whole-brain network between wake and coma groups and these differences have potential prognostic characterization capability.

Abnormal default mode network could be a potential prognostic marker in patients with disorders of consciousness.

OBJECTIVES: The study aimed to investigate disorders of consciousness (DOC) mechanisms of patients with severe traumatic brain injury (sTBI) related to default mode network (DMN) and to introduce a machine learning model that predicts the prognosis of these patients for 6 months. METHODS: The sTBI patients suffering from DOC and healthy controls underwent functional magnetic resonance imaging. We defined patients with Extended Glasgow Outcome Score ≥ 5 as good outcome group, otherwise they were poor outcome group. The differences of DMN between sTBI and healthy controls and between good and poor outcome groups were compared. Based on the brain regions with altered functional connectivity between good and poor outcome groups, they were divided into 8 regions of interests according to side. The Z values of the regions of interests were extracted by Rest 1.8. Based on Z values, the Subspace K-Nearest Neighbor (Subspace KNN) was conducted to classify prognosis of sTBI patients suffering from DOC. RESULTS: A total of 84 DMNs derived from patients and 45 DMNs from healthy controls were finally analyzed. The connectivity of the DMN was significantly decreased in sTBI patients suffering from DOC (Alphasim corrected, P < 0.05). In addition, compared with the poor outcome group (DMN samples = 60), the brain regions of DMN with decreased functional connectivity in the good outcome group (DMN samples = 24) the following bilateral areas: brodman Area 11, anterior cingulate and paracingulate gyri, brodman Area 25, olfactory cortex (Alphasim corrected, P < 0.05). The ability of Subspace KNN machine learning to distinguish the prognosis of patients (area under curve) was 0.97. CONCLUSIONS: The interruption of DMN may be one of the reasons for DOC in patients with sTBI. Furthermore, based on early DMN (1-4 weeks), Subspace KNN machine learning has the potential value to distinguish the prognosis (6 months after brain trauma) of sTBI patients suffering from DOC.

The role of gut microbiota in patients with benign and malignant brain tumors: a pilot study.

Gut microbiota is associated with the growth of various tumors, including malignant gliomas, through the brain-gut axis. Moreover, the gut microbiota in patients with malignant tumors may considerably differ from those with benign tumors. However, the associations of gut microbiota with benign and malignant brain tumors remain unclear. Hence, in order to explore these underlying relationships, patients with benign meningioma (n = 32), malignant glioma (n = 27), and healthy individuals (n = 41) were selected to participate in this study. The results showed that the diversity of the microbial ecosystem in brain tumor patients were less than the healthy controls, while no significant differences were observed between the meningioma and glioma groups. The microbial composition also differed significantly between individuals with brain tumors and healthy participants. In meningioma group, pathogenic bacteria like Enterobacteriaceae were increased, whereas certain carcinogenic bacteria were overrepresented in the glioma group, including Fusobacterium and Akkermansia. Furthermore, benign and malignant brain tumor patients lacked SCFA-producing probiotics. Thus, a microbial biomarker panel including Fusobacterium, Akkermansia, Escherichia/Shigella, Lachnospira, Agathobacter, and Bifidobacterium was established. Diagnostic models confirmed that this panel could distinguish between brain tumor patients and healthy patients. Additionally, gut microbiota can affect the differentiation and proliferation of brain tumors via several metabolic pathways based on annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG). This is the first study designed to investigate whether gut microbiota differs between benign and malignant brain tumor patients, and our work concluded that intestinal flora is a valuable tool for the diagnosis and treatment of brain tumors.

Circular RNA circRNA_0067934 promotes glioma development by modulating the microRNA miR-7/ Wnt/ß-catenin axis.

Glioma, one of the most prevalent malignant tumors, is well-known for its poor prognosis and low survival rate among patients. As a type of non-coding RNA, circular RNAs (circRNAs) play a significant role in tumor progression. However, the function and role of circRNAs in glioma development remain unclarified. In our experiments, the relative expression level of circRNA_0067934 and miR-7 in glioma tissue was detected by qRT-PCR, and specific gene knockdown was mediated by siRNA and miRNA-inhibitor. Dual-luciferase reporter assay was carried out to determine whether miR-7 successfully targeted circRNA_0067934. Also, CCK-8 and Transwell were performed to evaluate the malignant behaviors of glioma tissues. Western blotting and immunofluorescence were used to evaluate relative protein expression levels. The results of qRT-PCR indicated that circRNA_0067934 was over-expressed in glioma tissues, and down regulation of circRNA_0067934 reduced the tumor progression by inhibiting cell proliferation, invasion, and migration. The relative expression level of miR-7 was significantly reduced in glioma tissues, which showed a negative association with the expression of circRNA_0067934. CircRNA_0067934 could tagete the miR-7 to regulate progression of glioma cell. In addition, the Wnt/ß-catenin signaling pathway might involve in down stream regulation of circRNA_0067934 and miR-7. In conclusion, our results revealed that circRNA_0067934 regulates glioma cells progression by targeting miR-7/ Wnt/ß-catenin axis.

Injectable platelet rich fibrin facilitates hair follicle regeneration by promoting human dermal papilla cell proliferation, migration, and trichogenic inductivity.

Hair follicle regeneration has been successful in mice but failed in human being for years. Dermal papilla cells, a specialized mesenchymal stem cell derived from dermal papilla within hair follicles, is considered the key cells for hair follicle regeneration function as both regeneration initiator and regulator. Injectable platelet rich fibrin (i-PRF), a novel biomaterial rich in a variety of growth factors and three-dimensional scaffolds, has shown promising effects on tissue regeneration. In this study, we aimed to evaluate the application of i-PRF in human hair follicle regeneration by examining the biological effects of i-PRF on human dermal papilla cells (hDPCs). Biomaterial compatibility, cell viability, proliferation, migration, alkaline phosphatase activity and trichogenic inductivity were assessed after exposing hDPCs to different concentrations of i-PRF extracts. In addition, we investigated the ultrastructure of i-PRF with all cell components filtered. The results revealed that i-PRF possessing excellent biocompatibility and could significantly promote hDPCs proliferation, migration, and trichogenic inductivity. Furthermore, the concentration of i-PRF is able to remarkably influence hDPCs behavior in a dose-dependent pattern. Different concentrations exhibited differential effects on hDPCs behavior. In general, lower concentration promotes cell proliferation better than higher concentration, while higher concentration promotes cell function better reversely. Best concentration for hDPCs in vitro expending is 1% concentration. 20% concentration is optimal for hair follicle regeneration. In summary, our findings concluded that i-PRF facilitates hair follicle regeneration by promoting human dermal papilla cell proliferation, migration, and trichogenic inductivity.

Incidence of cerebrovascular disease as a comorbidity in patients with COVID-19: A meta-analysis.

It is essential to know whether COVID-19 patients have a history of cerebrovascular disease, as it may be predictive of prognosis and useful for allocation of limited medical resources. This meta-analysis was performed to assess the incidence of cerebrovascular disease as a comorbidity in COVID-19 patients. The PubMed, Cochrane Library, Embase, CNKI, WFSD, and VIP databases were systematically searched. The pooled analysis of relevant data was conducted using RevMan 5.3 software. The primary outcome was incidence of cerebrovascular disease as a comorbidity. Forty-seven studies involving 16,143 COVID-19 patients were included in this analysis. The incidences of a history of cerebrovascular disease and hypertension in COVID-19 patients were estimated to be 3.0% (95% CI, 2.0%-4.0%; P<0.00001) and 23.0% (95% CI, 16.0%-29.0%; P<0.00001), respectively. The incidence of dizziness/headache as the first symptom in COVID-19 patients was estimated to be 14.0% (95% CI, 8.0%-20.0%; P<0.00001). Subgroup analyses indicated that country, sex ratio, and sample size are potential influencing factors affecting the incidences of cerebrovascular disease, hypertension, and dizziness/headache. These findings suggest that cerebrovascular disease is an underlying comorbidity among patients with COVID-19. In addition, patients experiencing dizziness/headache as the first symptom of COVID-19 should receive a neurological examination.