Identification of a Novel Five-Gene Prognostic Model for Laryngeal Cancer Associated with Mitophagy Using Integrated Bioinformatics Analysis and Experimental Verification.

Laryngeal cancer (LC) is a prevailing tumor with a high mortality rate. The pivotal role of mitophagy in LC is acknowledged; however, a comprehensive analysis of the corresponding genes has not been conducted. In the present study, we proposed a prognostic model consisting of mitophagy-related genes in LC. Clinical information and transcriptome profiling of patients with LC and mitophagy-related genes were retrieved from open-source databases. Gene set variation analysis (GSVA) and Weighted Gene Co-expression Network Analysis (WGCNA) were used to identify core mitophagy-related genes and construct gene co-expression networks. Functional enrichment analysis was employed to analyze the enriched regulatory pathways of the mitophagy-related genes. Kaplan-Meier curves (KM), Cox, and LASSO regression were applied to explore their prognostic effects. Finally, quantitative real-time PCR (RT-qPCR) further verified the bioinformatics prediction. A total of 45 genes related to mitochondrial pathways was collected. GSVA analysis demonstrated that these genes in tumor samples mainly referred to the mitochondrial pathway. Among these genes, five mitophagy-related-gene signatures (CERCAM, CHPF, EPHX3, EXT2, and MED15) were further identified to construct the prognostic model. KM and Cox regression analyses indicated that this model had an accurate prognostic prediction for LC. RT-qPCR showed that CERCAM, CHPF, EXT2, and MED15 expression were upregulated, and EPHX3 level was decreased in LC cells. The present study established a five-mitophagy-related-gene model that can predict the prognosis of LC patients, thus laying the foundation for a better understanding and potential advancements in clinical treatments for LC.

The prognostic genes model of breast cancer drug resistance based on single-cell sequencing analysis and transcriptome analysis.

Breast cancer (BC) represents a multifaceted malignancy, with escalating incidence and mortality rates annually. Chemotherapy stands as an indispensable approach for treating breast cancer, yet drug resistance poses a formidable challenge. Through transcriptome data analysis, we have identified two sets of genes exhibiting differential expression in this context. Furthermore, we have confirmed the overlap between these genes and those associated with exosomes, which were subsequently validated in cell lines. The investigation screened the identified genes to determine prognostic markers for BC and utilized them to formulate a prognostic model. The disparities in prognosis and immunity between the high- and low-risk groups were validated using the test dataset. We have discerned different BC subtypes based on the expression levels of prognostic genes in BC samples. Variations in prognosis, immunity, and drug sensitivity among distinct subtypes were examined. Leveraging data from single-cell sequencing and prognostic gene expression, the AUCell algorithm was employed to score individual cell clusters and analyze the pathways implicated in high-scoring groups. Prognostic genes (CCT4, CXCL13, MTDH, PSMD2, and RAB27A) were subsewoquently validated using RT-qPCR. Consequently, we have established a model for predicting prognosis in breast cancer that hinges on drug resistance and ERGs. Furthermore, we have evaluated the prognostic value of this model. The genes identified as prognostic markers can now serve as a reference for precise treatment of this condition.

Bispectral Index Monitoring in the Nursing of Patients With Paroxysmal Sympathetic Hyperactivity.

AIM: To investigate the clinical nursing effect of bispectral index (BIS) monitoring for paroxysmal sympathetic hyperactivity (PSH) patients in the neurosurgical intensive care unit (NICU). METHODS: From January 2022 to June 2023, a total of 30 patients with PSH secondary to moderate to severe craniocerebral injury in the NICU were monitored for BIS. The patients' paroxysmal sympathetic hyperactivity-assessment measure (PSH-AM) scores were recorded. PSH patients generally appear in 3 states: calm state, seizure state, and postmedication state. Thirty PSH patients' BIS values were recorded during the calm period, during the seizure state, and postmedication state, and these 3 different stages' BIS values were divided into groups A, B, and C, using the Kruskal-Wallis H test to compare groups. RESULTS: The Kruskal-Wallis H test yielded a value of H=22.599, P<0.001. H0 was rejected against the test standard of α=0.05, and the BIS values of groups A, B, and C differed. The BIS values of group A and group B differed after a pairwise comparison, and the difference was statistically significant (adjusted P=0.001). Group B and group C had different BIS values, and the difference was statistically significant (adjusted P=0.001); group A and Group C had no difference in BIS values, and the difference was not statistically significant (adjusted P=1.00). CONCLUSIONS: Taking BIS value as the nursing observation index for PSH patients can make nursing work more objective, reasonable, and accurate, reduce the inducing factors of PSH attack, further reduce the attack of PSH, save nursing resources, and help guide the safety assessment of sedative use.

Single-cell atlas reveals the immunosuppressive microenvironment and Treg cells landscapes in recurrent Glioblastoma.

Patients diagnosed with glioblastoma (GBM) have the most aggressive tumor progression and lethal recurrence. Research on the immune microenvironment landscape of tumor and cerebrospinal fluid (CSF) is limited. At the single-cell level, we aim to reveal the recurrent immune microenvironment of GBM and the potential CSF biomarkers and compare tumor locations. We collected four clinical samples from two patients: malignant samples from one recurrent GBM patient and non-malignant samples from a patient with brain tumor. We performed single-cell RNA sequencing (scRNA-seq) to reveal the immune landscape of recurrent GBM and CSF. T cells were enriched in the malignant tumors, while Treg cells were predominately found in malignant CSF, which indicated an inhibitory microenvironment in recurrent GBM. Moreover, macrophages and neutrophils were significantly enriched in malignant CSF. This indicates that they an important role in GBM progression. S100A9, extensively expressed in malignant CSF, is a promising biomarker for GBM diagnosis and recurrence. Our study reveals GBM's recurrent immune microenvironment after chemoradiotherapy and compares malignant and non-malignant CSF samples. We provide novel targets and confirm the promise of liquid CSF biopsy for patients with GBM.

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.

In situ detection of exosomal RNAs for cancer diagnosis.

Exosomes are considered as biomarkers reflecting the physiological state of the human body. Studies have revealed that the expression levels of specific exosomal RNAs are closely associated with certain cancers. Thus, detection of exosomal RNA offers a new avenue for liquid biopsy of cancers. Many exosomal RNA detection methods based on various principles have been developed, and most of the methods detect the extracted RNAs after lysing exosomes. Besides complex and time-consuming extraction steps, a major drawback of this approach is the degradation of the extracted RNAs in the absence of plasma membrane and cytosol. In addition, there is considerable loss of RNAs during their extraction. In situ detection of exosomal RNAs can avoid these drawbacks, thus allowing higher diagnostic reliability. In this paper, in situ detection of exosomal RNAs was systematically reviewed from the perspectives of detection methods, transport methods of the probe systems, probe structures, signal amplification strategies, and involved functional materials. Furthermore, the limitations and possible improvements of the current in situ detection methods for exosomal RNAs towards the clinical diagnostic application are discussed. This review aims to provide a valuable reference for the development of in situ exosomal RNA detection strategies for non-invasive diagnosis of cancers. STATEMENT OF SIGNIFICANCE: Certain RNAs have been identified as valuable biomarkers for some cancers, and sensitive detection of cancer-related RNAs is expected to achieve better diagnostic efficacy. Currently, the detection of exosomal RNAs is receiving increasing attention due to their high stability and significant concentration differences between patients and healthy individuals. In situ detection of exosomal RNAs has greater diagnostic reliability due to the avoidance of RNA degradation and loss. However, this mode is still limited by some factors such as detection methods, transport methods of the probe systems, probe structures, signal amplification strategies, etc. This review focuses on the progress of in situ detection of exosomal RNAs and aims to promote the development of this field.

Prognostic value of the systemic inflammation response index in patients with aneurismal subarachnoid hemorrhage and a Nomogram model construction.

OBJECTIVE: To investigate the prognostic value of inflammatory markers, including neutrophil/lymphocyte ratio (NLR), derived neutrophil/lymphocyte ratio (dNLR), platelet/lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), prognostic nutritional index (PNI), and systemic inflammation response index (SIRI) in patients with aneurismal subarachnoid hemorrhage (aSAH), and then develop a Nomogram prognostic model. METHODS: We analysed 178 aSAH patients who underwent surgery at Subei People's Hospital of Jiangsu province from January 2015 to December 2017. Patients were divided into two groups according to Glasgow outcome scale (GOS) score at 3 months. Univariate and multivariate analysis were used to identify the association between inflammatory markers and prognosis. Subsequently, we identified the best cutoff of SIRI for unfavorable outcome using receiver operating characteristic (ROC) curve analysis and compared the clinical data between high and low SIRI levels. We further evaluated the additive value of SIRI by comparing prognostic nomogram models with and without it. RESULTS: A total of 47 (26.4%) patients had a poor outcome. Multivariate logistic regression analysis showed that SIRI was an independent risk factor of poor outcome. The SIRI of 4.105 × 109/L was identified as the optimal cutoff value, patients with high SIRI levels had worse clinical status and higher rates of unfavorable outcome. ROC analysis showed that a nomogram model combining the SIRI and other conventional factors showed more favorable predictive ability than the model without the SIRI. CONCLUSIONS: SIRI was independently correlated with unfavorable outcome in SAH patients, and the nomogram model combining the SIRI had more favorable discrimination ability.

Prediction of Catheter-Associated Urinary Tract Infections Among Neurosurgical Intensive Care Patients: A Decision Tree Analysis.

BACKGROUND: Catheter-associated urinary tract infections (CAUTIs) are the most common device-associated infections in hospitals and can be prevented. To identify the risk factors and develop a risk prediction model for CAUTIs among neurosurgical intensive care unit (NICU) patients. METHODS: All patients admitted to the NICU of a tertiary hospital between January 2019 and January 2020 were enrolled. Two decision tree models were applied to analyze the risk factors associated with CAUTIs in NICU patients. The performance of the decision tree model was evaluated. RESULTS: A total of 537 patients admitted to the NICU with indwelling catheters were recruited for this study. The rate of CAUTIs was 4.44 per 1000 catheter days, and Escherichia coli was the predominant pathogen causing CAUTIs among indwelling catheter patients. The classification and regression tree model displayed good power of prediction (area under the curve : 0.920). Nine CAUTI risk factors (age ≥60 years (P = 0.004), Glasgow Coma Scale score ≤8 (P = 0.009), epilepsy at admission (P = 0.007), admission to the hospital during the summer (P < 0.001), ventilators use (P = 0.007), receiving less than 2 types of antibiotics (P < 0.001), albumin level <35 g/L (P = 0.002), female gender (P = 0.002), and having an indwelling catheter for 7-14 days (P = 0.001) were also identified. CONCLUSION: We developed a novel scoring model for predicting the risk of CAUTIs in patients with neuro-critical illness in daily clinical practice. This model identified several risk factors for CAUTI among NICU patients, novel factors including epilepsy and admission during the summer, can be used to help providers prevent and reduce the risk of CAUTI among vulnerable groups.

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.

Development and validation of a user-friendly risk nomogram for the prediction of catheter-associated urinary tract infection in neuro-intensive care patients.

OBJECTIVE: This study aimed to develop a user-friendly nomogram model to evaluate the risk of catheter-associated urinary tract infections in neuro-critically ill patients. METHODS: A retrospective cohort analysis was conducted on 537 patients with indwelling catheters admitted to the neuro-intensive care unit. Patients' general information, laboratory examination findings, and clinical characteristics were collected. Multivariate regression analysis was applied to develop the nomogram for the prediction of catheter-associated urinary tract infections in this group of patients. The discriminative capacity, calibration ability, and clinical effectiveness of the nomogram were evaluated. RESULTS: The occurrence of catheter-associated urinary tract infections was 3.91 % and Escherichia coli was the major causative pathogen. Multivariate regression analysis showed that age ≥ 60 years (odds ratio: 35.2, 95 % confidence interval: 2.3-550.8), epilepsy (39.3, 5.1-301.4), a length of neuro-intensive care stay > 30 days (272.2, 8.3-8963.5), and low albumin levels (<35 g/L) (12.1, 2.1-69.9) were independent risk factors associated with catheter-associated urinary tract infection in neuro-intensive care patients. The nomogram demonstrated good calibration and discrimination in both the training and the validation sets. The model exhibited good clinical use since the decision curve analysis covered a large threshold probability. CONCLUSIONS: We developed a user-friendly nomogram to predict catheter-associated urinary tract ibfection in neuro-intensive care patients. The nomogram incorporated clinical variables collected on admission (age, admission diagnosis, and albumin levels) and the length of stay and enabled the effective prediction of the likelihood of catheter-associated urinary tract infections.

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.

si-PDGFRß-Loaded Exosomes Suppress the Progression of Glioma by Inhibiting the Oxidative Associated PI3K/Akt/EZH2 Signaling Pathway.

This study investigated the possibility of exosomes loaded with si-PDGFRß ability to suppress the progression of glioma. Common gliomas develop from neuroglial progenitor cells. Many variables affect the survival rate and occurrence of gliomas. Understanding oxidative stress processes and creating new, efficient treatments are crucial because oxidative stress is linked to the development of brain tumors. For this purpose, selected clinical samples were subjected to various tests like quantitative real-time PCR, Cignal Finder RTK signaling 7-pathway reporter array analysis, CCK-8 analysis, flow cytometry, and immunoblotting. Here, we demonstrated that PDGFRß expression was increased in glioma patients. Following that, cell-derived exosomes were extracted and collected and traced in vivo, and selected tissue samples were subjected to immunohistochemical analysis. The results indicated that the knockdown of PDGFRß (si-PDGFRß) inhibited the proliferation of glioma cells. Besides this, si-PDGFRß-loaded exosomes induced a similar antitumor effect in glioma cells. The anticancer effect of si-PDGFRß-loaded exosomes was mediated by the inactivation of the PI3K/Akt/EZH2 pathway. Finally, we verified that this exosome delivery system, si-PDGFRß-loaded exosomes, had robust targeting and no associated toxicity. In conclusion, the study confirmed that si-PDGFRß-loaded exosomes inhibit glioma progression via inactivating the PI3K/Akt/EZH2 signaling pathway.

Vitamin D categories and postpartum thyroid function in women with hypothyroidism.

Objective: To analyze the related factors of the postpartum thyroid function in women with overt hypothyroidism (OH)/subclinical hypothyroidism (SCH) and explore the effects of vitamin D categories. Methods: Thyroid hormones, thyroid autoantibody, and serum 25OHD levels were continuously recorded from the first trimester of pregnancy (T1) to the 12th postpartum month. Logistic regression analysis and Cox regression analysis were used to screen the related factors of postpartum thyroid function, and the Latent Class Growth Model was performed to analyze the trajectory characteristics of serum 25OHD levels. Results: Totally, 252 pregnant women with OH/SCH were enrolled in the study. In the 12th month postpartum, 36.5% of the patients improved thyroid function, 37.3% continued hypothyroidism, and 26.2% developed thyroid dysfunction. Vitamin D sufficiency, positive TPOAb, and positive TgAb in T1 were independent prognostic factors of postpartum thyroid function. Vitamin D sufficiency in T1 was illustrated as an independent factor of the improved postpartum thyroid function, but the protective effect for the developed postpartum thyroid dysfunction was only confirmed in TPOAb-positive patients. Cox regression analysis further confirmed the effects of vitamin D categories. Notably, the high-level 25OHD trajectory during pregnancy and postpartum could predict improved postpartum thyroid function and decrease the risk of developed postpartum thyroid dysfunction. Conclusion: Appropriate vitamin D nutrition during pregnancy and postpartum may be beneficial to postpartum thyroid function.

Crosstalk Between the Gut and Brain: Importance of the Fecal Microbiota in Patient With Brain Tumors.

Background: Variations in the gut microbiota may affect the metabolism, inflammation and immune response of the host. Microbiota dysbiosis has been extensively investigated in neurological disorders and diseases of the central nervous system (CNS). However, the alterations of the gut microbiota in patients suffering from brain tumors and the associations of the gut microbiota with these diseases remain unknown. Herein, we investigate the alterations of the gut microbiota community in patients with brain tumors and the associations between the two and further explore microbial markers used for the diagnosis of brain tumors. Methods: In our study, we recruited 158 participants, consisting of 101 brain tumor patients (65 benign and 36 malignant cases) and 57 age- and sex-matched healthy controls (HCs). We characterized the gut microbial community by using 16S rRNA gene amplicon sequencing and investigated its correlations with clinical features. Results: The results showed remarkably less microbial ecosystem richness and evenness in patients with brain tumors than in HCs. The gut microbiota community structure underwent profound changes in the brain tumor group, including an increase in the abundances of pathogenic bacteria, such as Fusobacteriota and Proteobacteria and a reduction in the abundances of probiotic bacteria, such as Bifidobacterium or Lachnospira. Moreover, our study indicated more significant correlations and clustering of pathogens in the malignant brain tumor group. Furthermore, a biomarker panel was used to discriminate the brain tumor patients from the healthy controls (AUC: 0.77). Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation revealed an accumulation of harmful metabolites and disorders of the basic physiological pathways in the brain tumor group. Conclusions: Our study revealed that brain tumor patients may possess divergent host-microbe interactions from those of healthy controls, especially in malignant brain tumor patients. In addition, the intestinal flora may be involved in immune responses and metabolism in the microenvironment of brain tumors. All evidence, including the biomarker panel, suggests that the intestinal flora may be a useful diagnostic and predictive tool and an important preventive target for brain tumors.

Targeting co-delivery of doxorubicin and gefitinib by biotinylated Au NCs for overcoming multidrug resistance in imaging-guided anticancer therapy.

Drug resistance and potential cardiotoxicity severely limit the DOX-mediated chemotherapy in clinical. Multi-drug combination is conducive to the realization of multi-modal synergy at the molecular level, which is crucial in drug dose optimization and improvement of therapeutic effect. In this work, fluorescent biotinylated Au Nanoclusters as an active targeting carrier was developed to realize real-time biological imaging and dual-drug delivery simultaneously. DNA toxin doxorubicin (DOX) and tyrosinase inhibitor gefitinib (GEF) were selected as dual-drug models for the treatment of human non-small cell lung cancer. The in vitro and in vivo results showed that dual-drug combination suppressed cancer cell growth more efficiently than any single formula at the same concentrations. GEF can block signaling in target cancer cells with mutated and overactive EGFR, thereby inhibiting tumor growth and metastasis and promoting tumor cell apoptosis. Combined with DOX chemotherapy, it will effectively overcome the problem of DOX resistance. In addition, the dual-drug delivery system produced excellent synergistic therapeutic effects without extra adverse toxicities. It provides a reference for the design and clinical application of the dual-drug delivery system.

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.

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.

Surgical treating lumbar intraspinal tumor through a para-split laminotomy.

BACKGROUND: to explore the feasibility and effectiveness of para-split laminotomy in the treatment of lumbar intraspinal tumors. METHODS: We retrospectively review the clinical data of 15 patients suffering lumbar intraspinal tumors, who underwent tumor resection using the para-split laminotomy, from October 2016 to May 2018. Observation indicators were as follows: (1) surgical and postoperative recovery situations; (2) the neurological function of the spinal cord and the follow-up situations. RESULTS: Mean blood loss was 95.3 ± 58.2 ml, and the mean duration of the surgical procedure was 176.7 ± 35.2 min. All lumbar intraspinal tumors were resected completely. There were no operative complications. The postoperative CT scans showed no pedicle or vertebral fractures. During the follow-up period of 6-18 months (average 10.8 ± 3.9 months), no tumor recurrence or spinal deformation was found according to the imaging examination. CT 3D reconstructions showed that the split laminae tended to heal. The average preoperative JOA score was 15.5 ± 4.9 and the average postoperative JOA score improved to 24.0 ± 3.5 (average improvement rate 65.9 ± 19.6%). CONCLUSION: The para-split laminotomy could reduce the damage to the posterior spinal tension band and help to protect the stability of the spine. It is feasible and effective to apply the para-split laminotomy to the operation of a lumbar intraspinal tumor, and this technique may be a promising option when considering surgical methods for some multilevel well-circumscribed intraspinal tumors.

Does erythropoietin affect the outcome and complication rates of patient with traumatic brain injury? A pooled-analysis.

OBJECTIVE: The aim of this meta-analysis was to review the scientific literature published until April 18, 2021, to summarize existing knowledge on the efficacy and safety of erythropoietin (EPO) for traumatic brain injury (TBI). METHODS: This systematic review followed PRISMA guidelines. Randomized controlled trials (RCTs) reporting on the efficacy and safety of EPO in the treatment of TBI were systematically searched in relevant electronic databases according to a pre-designed search strategy. The primary outcomes are the mortality; and secondary outcomes are the good functional outcome (GFO) and adverse events (AEs). RESULTS: A total of 10 RCTs involving 2,402 participants fulfilled the inclusion criteria. The results showed that there is a significant difference in terms of the mortality (RR = 0.67, 95% CI = 0.54-0.84, P = 0.0003) and seizure rate (RR = 0.52, 95% CI = 0.29-0.96, P = 0.04) between the EPO groups compared to those in the control groups. However, compared with the control groups, the GFO in the EPO groups was not statistically significant (RR = 1.18, 95% CI = 0.93-1.48, P = 0.17). CONCLUSIONS: Findings of the present meta-analysis suggest that the use of EPO could reduce mortality rate in patients with TBI, without increasing the incidence of AEs. EPO has potential research and application value in the treatment of TBI.