[Expression and significance of hypoxia-inducible factor 1α and Bcl-2/adenovirus E1B19kDa-interacting protein 3 in children with traumatic brain injury]. / ç¼ºæ°§è¯±å¯¼å› å­1α、Bcl-2/è ºç— æ¯’E1B19kDa相互作用蛋白3在儿童创伤性脑损伤中的表达及意义.

OBJECTIVES: To dynamically observe the changes in hypoxia-inducible factor 1α (HIF-1α) and Bcl-2/adenovirus E1B19kDa-interacting protein 3 (BNIP3) in children with traumatic brain injury (TBI) and evaluate their clinical value in predicting the severity and prognosis of pediatric TBI. METHODS: A prospective study included 47 children with moderate to severe TBI from January 2021 to July 2023, categorized into moderate (scores 9-12) and severe (scores 3-8) subgroups based on the Glasgow Coma Scale. A control group consisted of 30 children diagnosed and treated for inguinal hernia during the same period, with no underlying diseases. The levels of HIF-1α, BNIP3, autophagy-related protein Beclin-1, and S100B were compared among groups. The predictive value of HIF-1α, BNIP3, Beclin-1, and S100B for the severity and prognosis of TBI was assessed using receiver operating characteristic (ROC) curves. RESULTS: Serum levels of HIF-1α, BNIP3, Beclin-1, and S100B in the TBI group were higher than those in the control group (P<0.05). Among the TBI patients, the severe subgroup had higher levels of HIF-1α, BNIP3, Beclin-1, and S100B than the moderate subgroup (P<0.05). Correlation analysis showed that the serum levels of HIF-1α, BNIP3, Beclin-1, and S100B were negatively correlated with the Glasgow Coma Scale scores (P<0.05). After 7 days of treatment, serum levels of HIF-1α, BNIP3, Beclin-1, and S100B in both non-surgical and surgical TBI patients decreased compared to before treatment (P<0.05). ROC curve analysis indicated that the areas under the curve for predicting severe TBI based on serum levels of HIF-1α, BNIP3, Beclin-1, and S100B were 0.782, 0.835, 0.872, and 0.880, respectively (P<0.05), and for predicting poor prognosis of TBI were 0.749, 0.775, 0.814, and 0.751, respectively (P<0.05). CONCLUSIONS: Serum levels of HIF-1α, BNIP3, and Beclin-1 are significantly elevated in children with TBI, and their measurement can aid in the clinical assessment of the severity and prognosis of pediatric TBI.

Immune patterns of cuproptosis in ischemic heart failure: A transcriptome analysis.

Cuproptosis is a recently discovered programmed cell death pattern that affects the tricarboxylic acid (TCA) cycle by disrupting the lipoylation of pyruvate dehydrogenase (PDH) complex components. However, the role of cuproptosis in the progression of ischemic heart failure (IHF) has not been investigated. In this study, we investigated the expression of 10 cuproptosis-related genes in samples from both healthy individuals and those with IHF. Utilizing these differential gene expressions, we developed a risk prediction model that effectively distinguished healthy and IHF samples. Furthermore, we conducted a comprehensive evaluation of the association between cuproptosis and the immune microenvironment in IHF, encompassing infiltrated immunocytes, immune reaction gene-sets and human leukocyte antigen (HLA) genes. Moreover, we identified two different cuproptosis-mediated expression patterns in IHF and explored the immune characteristics associated with each pattern. In conclusion, this study elucidates the significant influence of cuproptosis on the immune microenvironment in ischemic heart failure (IHF), providing valuable insights for future mechanistic research exploring the association between cuproptosis and IHF.

Mechanistic insight into glioma through spatially multidimensional proteomics.

Characterizing the tumor microenvironment at the molecular level is essential for understanding the mechanisms of tumorigenesis and evolution. However, the specificity of the blood proteome in localized region of the tumor and its linkages with other systems is difficult to investigate. Here, we propose a spatially multidimensional comparative proteomics strategy using glioma as an example. The blood proteome signature of tumor microenvironment was specifically identified by in situ collection of arterial and venous blood from the glioma region of the brain for comparison with peripheral blood. Also, by integrating with different dimensions of tissue and peripheral blood proteomics, the information on the genesis, migration, and exchange of glioma-associated proteins was revealed, which provided a powerful method for tumor mechanism research and biomarker discovery. The study recruited multidimensional clinical cohorts, allowing the proteomic results to corroborate each other, reliably revealing biological processes specific to gliomas, and identifying highly accurate biomarkers.

Identification and validation of chromatin regulator-related signatures as a novel prognostic model for low-grade gliomas using translational bioinformatics.

AIMS: The purpose of this study is to explore the potential biological role and prognostic significance of chromatin regulators (CRs) in low-grade gliomas (LGGs). MAIN METHODS: CRs were obtained from the FACER database. Transcription profiles of LGG patients were collected from the TCGA and CGGA databases. Differentially expressed CRs (DECRs) between LGGs and normal controls were identified using DESeq2. The consensus clustering algorithm was employed to distinguish subtypes of LGGs based on prognosis-related DECRs. The differences in clinical and molecular characteristics between different subtypes were explored. R packages, GSVA, ssGSEA, and ESTIMATE were utilized to elucidate the tumor microenvironment and activated pathways in different subtypes. Subsequently, a CRs-related signature was developed using LASSO Cox regression. Its performance was evaluated by Kaplan-Meier curve and ROC curve analyses. In vitro experiments were performed to explore the function of JADE3 in LGGs, which predominantly expressed in glioma cells. KEY FINDINGS: We identified 43 DECRs and two CRs-related subtypes of LGGs. The subtype characterized by shorter survival displayed significant enrichment for pathways associated with DNA damage response and repair, along with heightened immune cell infiltration. Furthermore, the CRs-based signature exhibited excellent prognostic performance in both the TCGA and CGGA databases. Knockdown of JADE3 significantly increased the invasion, migration, and proliferation abilities of Hs683. SIGNIFICANCE: Our study reveals the aberrant expression and prognostic value of CRs in LGGs. It emphasizes the potential regulatory role of CRs in the microenvironment and DNA damage repair in LGGs. JADE3 could be a possible therapeutic target for LGGs.

GSLCDA: An Unsupervised Deep Graph Structure Learning Method for Predicting CircRNA-Disease Association.

Growing studies reveal that Circular RNAs (circRNAs) are broadly engaged in physiological processes of cell proliferation, differentiation, aging, apoptosis, and are closely associated with the pathogenesis of numerous diseases. Clarification of the correlation among diseases and circRNAs is of great clinical importance to provide new therapeutic strategies for complex diseases. However, previous circRNA-disease association prediction methods rely excessively on the graph network, and the model performance is dramatically reduced when noisy connections occur in the graph structure. To address this problem, this paper proposes an unsupervised deep graph structure learning method GSLCDA to predict potential CDAs. Concretely, we first integrate circRNA and disease multi-source data to constitute the CDA heterogeneous network. Then the network topology is learned using the graph structure, and the original graph is enhanced in an unsupervised manner by maximize the inter information of the learned and original graphs to uncover their essential features. Finally, graph space sensitive k-nearest neighbor (KNN) algorithm is employed to search for latent CDAs. In the benchmark dataset, GSLCDA obtained 92.67% accuracy with 0.9279 AUC. GSLCDA also exhibits exceptional performance on independent datasets. Furthermore, 14, 12 and 14 of the top 16 circRNAs with the most points GSLCDA prediction scores were confirmed in the relevant literature in the breast cancer, colorectal cancer and lung cancer case studies, respectively. Such results demonstrated that GSLCDA can validly reveal underlying CDA and offer new perspectives for the diagnosis and therapy of complex human diseases.

MAGCDA: A Multi-Hop Attention Graph Neural Networks Method for CircRNA-Disease Association Prediction.

With a growing body of evidence establishing circular RNAs (circRNAs) are widely exploited in eukaryotic cells and have a significant contribution in the occurrence and development of many complex human diseases. Disease-associated circRNAs can serve as clinical diagnostic biomarkers and therapeutic targets, providing novel ideas for biopharmaceutical research. However, available computation methods for predicting circRNA-disease associations (CDAs) do not sufficiently consider the contextual information of biological network nodes, making their performance limited. In this work, we propose a multi-hop attention graph neural network-based approach MAGCDA to infer potential CDAs. Specifically, we first construct a multi-source attribute heterogeneous network of circRNAs and diseases, then use a multi-hop strategy of graph nodes to deeply aggregate node context information through attention diffusion, thus enhancing topological structure information and mining data hidden features, and finally use random forest to accurately infer potential CDAs. In the four gold standard data sets, MAGCDA achieved prediction accuracy of 92.58%, 91.42%, 83.46% and 91.12%, respectively. MAGCDA has also presented prominent achievements in ablation experiments and in comparisons with other models. Additionally, 18 and 17 potential circRNAs in top 20 predicted scores for MAGCDA prediction scores were confirmed in case studies of the complex diseases breast cancer and Almozheimer's disease, respectively. These results suggest that MAGCDA can be a practical tool to explore potential disease-associated circRNAs and provide a theoretical basis for disease diagnosis and treatment.

SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution.

Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influence of non-Euclidean data and multisource information, and there is still a critical issue for graph neural networks regarding how to set the feature diffuse distance. To solve the problems, we proposed SiSGC, which makes full use of the biological knowledge information as initial features and learns the structure information from the constructed heterogeneous graph with the adaptive selection of the information diffuse distance. Then, the structural features are fused with the denoised similarity information and fed to the advanced classifier of CatBoost to make predictions. Three different data sets are used to confirm the robustness and generalization of SiSGC under two splitting strategies. Experiment results demonstrate that the proposed model achieves superior performance compared with the six leading methods and four variants. Our case study on breast neoplasms further indicates that SiSGC is trustworthy and robust yet simple. We also present four drugs for breast cancer treatment with high confidence and further give an explanation for demonstrating the rationality. There is no doubt that SiSGC can be used as a beneficial supplement for drug repositioning.

KS-CMI: A circRNA-miRNA interaction prediction method based on the signed graph neural network and denoising autoencoder.

Circular RNA (circRNA) plays an important role in the diagnosis, treatment, and prognosis of human diseases. The discovery of potential circRNA-miRNA interactions (CMI) is of guiding significance for subsequent biological experiments. Limited by the small amount of experimentally supported data and high randomness, existing models are difficult to accomplish the CMI prediction task based on real cases. In this paper, we propose KS-CMI, a novel method for effectively accomplishing CMI prediction in real cases. KS-CMI enriches the 'behavior relationships' of molecules by constructing circRNA-miRNA-cancer (CMCI) networks and extracts the behavior relationship attribute of molecules based on balance theory. Next, the denoising autoencoder (DAE) is used to enhance the feature representation of molecules. Finally, the CatBoost classifier was used for prediction. KS-CMI achieved the most reliable prediction results in real cases and achieved competitive performance in all datasets in the CMI prediction.

Transcriptome analysis revealed the mechanism of Luciobarbus capito (L. capito) adapting high salinity: Antioxidant capacity, heat shock proteins, immunity.

Salinity has a significant influence on the physiology of freshwater aquatic organisms. However, there are few studies on the hematology and immunology of freshwater fish under high salinity. In the current study, we aimed to analyze the adaptive effect of salt stress on L. capito spleen immune function and hematology using transcriptomic analysis. We replicated a L. capito acute salinity stress model, and collected blood and spleens from freshwater and saltwater fish. It was found that salinity affected significantly the numbers of leukocytes, lymphocytes, neutrophils, and red blood cells, as well as the content of haemoglobin. Salt treatment resulted in a significant increase in the expression of HSP70, HSP90, CAT, SOD, and GPX1 genes in L. capito spleens. Transcriptomic analysis revealed a total of 546 differentially expressed genes (DEGs) in spleens, including 224 up-regulated DEGs and 322 down-regulated DEGs. In addition, GO enrichment analysis revealed immune system process, multicellular organismal process, and biological regulation of genes with the most differences in biological processes. KEGG enrichment analysis showed that the regulation of lipolysis in adipocyte, FoxO signaling pathway, Hematopoietic cell lineage signaling pathway, and HIF-1 signaling pathway were significantly enriched. L. capito adapted oxidative to high salinity through FoxO signaling pathway and immune to high salinity through Hematopoietic cell lineage signaling pathway. At the same time, we selected 10 DEGs for qRT-PCR detection, and the results showed that the qRT-PCR results were consistent with our RNA-Seq results, indicating that transcriptome sequencing was accurate and reliable. In conclusion, our results demonstrated that the improvement of antioxidant capacity, heat shock protein and immunity are involved in the molecular mechanism of L. capito adapting to high salinity. Our findings provided a rationale for further study on high salinity adaptation and related enrichment pathways.

Adaptive deep propagation graph neural network for predicting miRNA-disease associations.

BACKGROUND: A large number of experiments show that the abnormal expression of miRNA is closely related to the occurrence, diagnosis and treatment of diseases. Identifying associations between miRNAs and diseases is important for clinical applications of complex human diseases. However, traditional biological experimental methods and calculation-based methods have many limitations, which lead to the development of more efficient and accurate deep learning methods for predicting miRNA-disease associations. RESULTS: In this paper, we propose a novel model on the basis of adaptive deep propagation graph neural network to predict miRNA-disease associations (ADPMDA). We first construct the miRNA-disease heterogeneous graph based on known miRNA-disease pairs, miRNA integrated similarity information, miRNA sequence information and disease similarity information. Then, we project the features of miRNAs and diseases into a low-dimensional space. After that, attention mechanism is utilized to aggregate the local features of central nodes. In particular, an adaptive deep propagation graph neural network is employed to learn the embedding of nodes, which can adaptively adjust the local and global information of nodes. Finally, the multi-layer perceptron is leveraged to score miRNA-disease pairs. CONCLUSION: Experiments on human microRNA disease database v3.0 dataset show that ADPMDA achieves the mean AUC value of 94.75% under 5-fold cross-validation. We further conduct case studies on the esophageal neoplasm, lung neoplasms and lymphoma to confirm the effectiveness of our proposed model, and 49, 49, 47 of the top 50 predicted miRNAs associated with these diseases are confirmed, respectively. These results demonstrate the effectiveness and superiority of our model in predicting miRNA-disease associations.

Effect of Anterior Cervical Decompression Fusion and Partial Resection of Uncinate Vertebra Joint on Cervical Sagittal Sequence in Patients with Non-Single-Segment Radiculopathy and its Correlation with Curative Effect: A Retrospective Analysis.

OBJECTIVE: Analyze the effect of preservation or resection of the partial uncinate joint on the sagittal sequence of the cervical vertebrae in patients with non-single-segment radiculopathy and the correlation between the sagittal sequence of the cervical vertebrae and the long-term effect after surgery, we explored whether it is necessary to perform partial resection of the uncinate joint in patients with cervical spondylotic radiculopathy undergoing anterior cervical decompression and fusion (ACDF). METHODS: The study retrospectively analyzed 96 patients with cervical spondylotic radiculopathy with more than two segments from August 2016 to January 2021, who underwent ACDF (ACDF group, 45 patients) or ACDF combined with partial uncinate joint resection (ACDF + UT group, 51 patients). Partial resection of the uncinate joint indicated removal of part of the uncinate joint and osteophyte based on the compression of the nerve root during surgery, whereas the uncinate joints in the ACDF group were retained completely. The imaging data and functional scores of the two groups were recorded before surgery, 1 month after surgery, and at the last follow-up. A paired t-test or rank sum test was applied to analyze the data. In addition, the correlation between the imaging parameters and functional scores was validated using the Pearson's test. RESULTS: All 96 patients successfully completed the surgery and were followed up for at least 12 months, with an average follow-up time of 14 months. At the last follow-up, the pain visual analog scale (VAS), neck disability index (NDI), and neck pain and disability scale (NPAD) scores of the two groups were significantly lower than those before surgery, and the Japanese Orthopaedic Association (JOA) score was significantly higher than that before surgery. At the last follow-up, compared with the ACDF+UT group, the NDI and NPAD scores in the ACDF group decreased more significantly (p < 0.05), and C2-7SVA, △C2-7SVA (the difference between C2-7 SVA at last follow-up and before operation), and T1S values decreased significantly (p < 0.05). The C2-7 Cobb angle was positively correlated with the JOA score and T1S (p < 0.05) and negatively correlated with the VAS, NDI, and NPAD scores and CGH-C7SVA (p < 0.05). C2-7SVA was positively correlated with CGH-C7SVA and T1S (p < 0.05). CONCLUSION: Patients with non-single-segmental cervical spondylotic radiculopathy and ACDF with or without uncinate joint resection can have effective improvement in the clinical effect and sagittal balance; however, partial uncinate joint resection has a certain negative impact on the long-term reconstruction of sagittal balance and long-term effects in patients after surgery.

A neurodevelopmental epigenetic programme mediated by SMARCD3-DAB1-Reelin signalling is hijacked to promote medulloblastoma metastasis.

How abnormal neurodevelopment relates to the tumour aggressiveness of medulloblastoma (MB), the most common type of embryonal tumour, remains elusive. Here we uncover a neurodevelopmental epigenomic programme that is hijacked to induce MB metastatic dissemination. Unsupervised analyses of integrated publicly available datasets with our newly generated data reveal that SMARCD3 (also known as BAF60C) regulates Disabled 1 (DAB1)-mediated Reelin signalling in Purkinje cell migration and MB metastasis by orchestrating cis-regulatory elements at the DAB1 locus. We further identify that a core set of transcription factors, enhancer of zeste homologue 2 (EZH2) and nuclear factor I X (NFIX), coordinates with the cis-regulatory elements at the SMARCD3 locus to form a chromatin hub to control SMARCD3 expression in the developing cerebellum and in metastatic MB. Increased SMARCD3 expression activates Reelin-DAB1-mediated Src kinase signalling, which results in a MB response to Src inhibition. These data deepen our understanding of how neurodevelopmental programming influences disease progression and provide a potential therapeutic option for patients with MB.

Visualization balloon occlusion-assisted technique in the treatment of large or giant paraclinoid aneurysms: A study of 17 cases series.

Objective: Although balloon-assisted techniques are valuable in aneurysm clipping, repeated angiography and fluoroscopy are required to understand the location and shape of the balloon. This study investigated the value of visualization balloon occlusion-assisted techniques in aneurysm hybridization procedures. Methods: We propose a visualization balloon technique that injects methylene blue into the balloon, allowing it to be well visualized under a microscope without repeated angiography. This study retrospects the medical records of 17 large or giant paraclinoid aneurysms treated by a visualization balloon occlusion-assisted technique in a hybrid operating room. Intraoperative surgical techniques, postoperative complications, and immediate and long-term angiographic findings are highlighted. Results: All 17 patients had safe and successful aneurysm clipping surgery with complete angiographic occlusion. Under the microscope, the balloon injected with methylene blue is visible through the arterial wall. The position and shape of the balloon can be monitored in real time without repeated angiography and fluoroscopic guidance. Two cases of intraoperative visualization balloon shift and slip into the aneurysm cavity were detected in time, and there were no cases of balloon misclipping or difficult removal. Of 17 patients, four patients (23.5%) experienced short-term complications, including pulmonary infection (11.8%), abducens nerve paralysis (5.9%), and thalamus hemorrhage (5.9%). The rate of vision recovery among patients with previous visual deficits was 70% (7 of 10 patients). The mean follow-up duration was 32.76 months. No aneurysms or neurological deficits recurred among all patients who completed the follow-up. Conclusion: Our study indicates that microsurgical clipping with the visualization balloon occlusion-assisted technique seems to be a safe and effective method for patients with large or giant paraclinoid aneurysms to reduce the surgical difficulty and simplify the operation process of microsurgical treatment alone.

SPRDA: a link prediction approach based on the structural perturbation to infer disease-associated Piwi-interacting RNAs.

piRNA and PIWI proteins have been confirmed for disease diagnosis and treatment as novel biomarkers due to its abnormal expression in various cancers. However, the current research is not strong enough to further clarify the functions of piRNA in cancer and its underlying mechanism. Therefore, how to provide large-scale and serious piRNA candidates for biological research has grown up to be a pressing issue. In this study, a novel computational model based on the structural perturbation method is proposed to predict potential disease-associated piRNAs, called SPRDA. Notably, SPRDA belongs to positive-unlabeled learning, which is unaffected by negative examples in contrast to previous approaches. In the 5-fold cross-validation, SPRDA shows high performance on the benchmark dataset piRDisease, with an AUC of 0.9529. Furthermore, the predictive performance of SPRDA for 10 diseases shows the robustness of the proposed method. Overall, the proposed approach can provide unique insights into the pathogenesis of the disease and will advance the field of oncology diagnosis and treatment.

Predicting Mirna-Disease Associations Based on Neighbor Selection Graph Attention Networks.

Numerous experiments have shown that the occurrence of complex human diseases is often accompanied by abnormal expression of microRNA (miRNA). Identifying the associations between miRNAs and diseases is of great significance in the development of clinical medicine. However, traditional experimental methods are often time-consuming and inefficient. To this end, we proposed a deep learning method based on neighbor selection graph attention networks for predicting miRNA-disease associations (NSAMDA). Specifically, we firstly fused miRNA sequence similarity information and miRNA integrated similarity information to enrich miRNA feature information. Secondly, we used the fused miRNA feature information and disease integrated similarity information to construct a miRNA-disease heterogeneous graph. Thirdly, we introduced a neighbor selection method based on graph attention networks to select k-most important neighbors for aggregation. Finally, we used the inner product decoder to score miRNA-disease pairs. The results of five-fold cross-validation show that the mean AUC of NSAMDA is 93.69% on HMDD v2.0 dataset. In addition, case studies on the esophageal neoplasm, lung neoplasm and lymphoma were carried out to further confirm the effectiveness of the NSAMDA model. The results showed that the NSAMDA method achieves satisfactory performance on predicting miRNA-disease associations and is superior to the most advanced model.

Predicting MiRNA-Disease Associations by Graph Representation Learning Based on Jumping Knowledge Networks.

Growing studies have shown that miRNAs are inextricably linked with many human diseases, and a great deal of effort has been spent on identifying their potential associations. Compared with traditional experimental methods, computational approaches have achieved promising results. In this article, we propose a graph representation learning method to predict miRNA-disease associations. Specifically, we first integrate the verified miRNA-disease associations with the similarity information of miRNA and disease to construct a miRNA-disease heterogeneous graph. Then, we apply a graph attention network to aggregate the neighbor information of nodes in each layer, and then feed the representation of the hidden layer into the structure-aware jumping knowledge network to obtain the global features of nodes. The output features of miRNAs and diseases are then concatenated and fed into a fully connected layer to score the potential associations. Through five-fold cross-validation, the average AUC, accuracy and precision values of our model are 93.30%, 85.18% and 88.90%, respectively. In addition, for three case studies of the esophageal tumor, lymphoma and prostate tumor, 46, 45 and 45 of the top 50 miRNAs predicted by our model were confirmed by relevant databases. Overall, our method could provide a reliable alternative for miRNA-disease association prediction.

CENPA acts as a prognostic factor that relates to immune infiltrates in gliomas.

Background: Glioma is the most common primary tumor of the central nervous system (CNS). Centromere protein A (CENPA) plays an essential role in ensuring that mitosis proceeds normally. The effect of CENPA on glioma is rarely reported. However, the current study aims to explore whether aberrant CENPA expression promotes glioma progression and the potential mechanisms involved. Methods: The GEPIA website, The Cancer Genome Atlas, and the Gene Expression Omnibus (GEO) were used to assess the expression of CENPA in glioma. The results were validated by real-time quantitative polymerase chain reaction and immunohistochemical staining of clinical samples. The relationship between the expression and prognostic value of the CENPA gene in glioma was investigated by Kaplan-Meier (KM) survival analysis with RNA-seq and clinical profiles downloaded from the Chinese Glioma Genome Atlas (CGGA) and UCSC Xena. The association between CENPA and clinical characteristics was also evaluated. Cell Counting Kit-8 (CCK8) assay, wound healing assay using two glioma cell lines, gene set enrichment analysis (GSEA), KEGG and gene ontology (GO) enrichment analysis, immune infiltration analysis, temozolomide (TMZ) sensitivity analysis, and single-cell sequence analysis were performed to explore the underlying mechanisms of high CENPA expression and its effect on glioma development. Finally, we performed a Cox analysis based on the expression of CENPA to predict patient prognosis. Results: CENPA was significantly upregulated in glioma tissue samples and correlated with patient prognosis. Moreover, the downregulation of CENPA inhibited the migration and proliferation of glioma cells. In addition, the expression level of CENPA was significantly correlated with the grade, primary-recurrent-secondary (PRS) type, IDH mutation status, and 1p19q codeletion status. Furthermore, CENPA could serve as an independent prognostic factor for glioma that mainly interferes with the normal progression of mitosis and regulates the tumor immune microenvironment favoring glioma development. Conclusion: CENPA may act as a prognostic factor in patients with glioma and provide a novel target for the treatment of gliomas.

A new neurosurgical adjustable pressure suction apparatus with a mechanically controlled air inlet: the study of precise regulation and atraumatic suction.

Background: An essential surgical tool in neurosurgery is the suction tube. The skillful and accurate use of a suction tube facilitates the neurosurgical operation. Objective: This study is to verify the practicality of an adjustable pressure suction tube (APS tube) and to explore the ideal APS tube diameter and tip negative pressure for different intracranial structures. Methods: APS tubes were used to aspirate brain tissues and carotid arteries of rats. Laser speckle contrast imaging (LSCI) was used to record the blood flow velocity (BFV). We measured APS tube diameter, air inlet size, tip negative pressure and central negative pressure and calculated the correlation between them. In our department, intraoperative real-time parameters including APS tube diameter, length, air inlet size, and central negative pressure were recorded, and the tube tip negative pressure suitable for different intracranial structures and parts was calculated. Results: All experiments were carried out using APS tubes. Experiments on rats objectively reflected a severe structural damage to the brain and blood vessels by the suction tube, which might even result in an irreversible reduction in blood flow., Rat carotid arteries and brain tissue suffered severe damage when the tip negative pressure exceeded 33.4 ± 1.8 and 29.2 ± 2.0 kPa, respectively. BFV failed to return to the preoperative level 3 min after the operation (p < 0.05), and this decrease was more pronounced when the suction tube diameter was large (p < 0.05). The tip negative pressure was positively and negatively correlated with central negative pressure and the air inlet size, and was independent of APS tube diameter. A total of 50 operations including 39 tumor resection operations and 11 moyamoya disease bypass operations were recorded. Large-diameter APS tubes (3.5 mm) with an closed air inlet were frequently used to maintain a greater tip negative pressure before the incision of dura mater. When important structures such as motor cortex and brainstem were involved, 1.5- or 2.0-mm-diameter APS tubes were mostly used, and an air inlet was opened up to 0.7-2.1 mm to maintain a safe tip negative pressure (7.4-27.9 kPa). Conclusion: APS tubes with a mechanical knob provide stable and precise adjustment of the tip negative pressure, avoiding excessive negative pressure that causes serious damage to the intracranial structure. And, this allows the surgeon to hold the suction tube more freely and operate at any angle with an appropriate fulcrum near the incision to achieve efficient atraumatic suction and enhance surgical safety.

Novel Covert-Inferior Pelvic Approach with a Subpubic Plate for Anterior Pelvic Ring Fractures: Preliminary Results.

BACKGROUND: Anterior pelvic ring injuries can be treated via Pfannenstiel, modified Stoppa, or ilioinguinal approaches, but these require exposing the abdominal soft tissues and may damage pelvic organs. The scar on the abdominal wall is also unacceptable for some patients. The minimally invasive anterior pelvic ring internal fixator (INFIX) is not ideal for thin patients with easily irritated skin, and it is associated with complications such as femoral nerve palsy, vascular occlusion, and lateral femoral cutaneous nerve injury. In this study, we designed a new external pelvic approach for the treatment of an anterior pelvic ring fracture. METHODS: We retrospectively reviewed 28 patients with 36 pubic ramus fractures that had been treated via the covert-inferior pelvic approach. All patients underwent a surgical procedure between August 2019 and January 2021. According to the Nakatani classification, there were 6 cases of type-I fracture, 25 cases of type-II fracture, and 5 cases of type-III fracture. Operative time, blood loss, and postoperative radiographic and computed tomographic (CT) findings were recorded. Patients were followed for fracture healing time, functional status, esthetic satisfaction, and complications. RESULTS: A total of 27 patients had follow-up for at least 12 months (range, 12 to 29 months). Postoperative radiographs and CT scans showed well-positioned plates and screws. The mean preoperative time was 9.4 ± 3.8 days, the mean operative time was 61.3 ± 22.67 minutes, the mean intraoperative blood loss was 63.6 ± 42.62 mL, the mean fracture healing time was 4.1 ± 1.6 months, and the mean Majeed score was 89.74 ± 8.07. There were no complications of nonunion, internal fixation failure, vascular injury, nerve palsy, or hernia. All of the patients were esthetically satisfied with the scar. CONCLUSIONS: The covert-inferior pelvic approach combined with a subpubic plate effectively fixed Nakatani type-I, II, and III fractures. The advantages of this method include rapid recovery after the surgical procedure, safety, simplicity, a short learning curve, no damage to abdominal soft tissue, no effect on pubic symphysis micromotion, and esthetic benefits. It may be another option for anterior pelvic ring fractures and can supplement other approaches. LEVEL OF EVIDENCE: Therapeutic Level III . See Instructions for Authors for a complete description of levels of evidence.

Hybrid surgery for coexistence of cerebral arteriovenous malformation and primitive trigeminal artery: A case report and literature review.

The primitive trigeminal artery (PTA), an abnormal carotid-basilar anastomosis, forms the vascular anomaly connection between the internal carotid artery and vertebrobasilar system. Rarely, PTA can be complicated by several other cerebrovascular disease, including arteriovenous malformations (AVMs), intracranial aneurysms, moyamoya disease, and carotid-cavernous malformations. Herein, we reported a rare case of PTA combined with an AVM in a male patient. The patient was a 28-year-old male with epileptic seizures at the onset of symptoms. Magnetic resonance imaging showed abnormal signal foci and localized softening foci formation with gliosis in the right parietal temporal lobe. Furthermore, using a digital subtraction angiogram (DSA), it was found that an abnormal carotid-basilar anastomosis had developed through a PTA originating from the cavernous portion of the right internal carotid artery (ICA) and a large AVM on the surface of the right carotid artery. The lesion of AVM tightly developed and draining into superior sagittal sinus. A hybrid operating room was used for the surgery. The main feeding arteries of the AVM originating from three major arteries, including the right middle cerebral artery, the right anterior cerebral artery, and the right posterior cerebral artery, were clipped and subsequently, then the AVM was thoroughly removed. The intraoperative DSA showed that the AVM had been resected completely. Postoperative pathological examination of the resected specimen indicated the presence of an AVM. The patient recovered well after surgery and has been symptom-free for more than 3 months. In summary, the pathogenesis of the coexistence of PTA and AVM remains unknown. As highlighted in this case report, hybrid surgery can be used to remove AVMs and can improve the patients' prognosis. To our best knowledge, this is the first case in the literature of successful AVM treatment using hybrid surgery.