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Background: The discovery of driver genes such as EGFR, KRAS, and ALK, has dramatically shifted treatment patterns in patients harboring these oncogenes. However, dissemination into the central nervous system (CNS) is a severe complication. In addition, the particular anatomical structure of the CNS has made it difficult to obtain tissue specimens from brain metastases (BM) to generate a gene map, as such, potential predictive markers for survival in patients with non-small cell lung cancer (NSCLC) and BM (NSCLC-BM) remain unclear. Methods: Data from 28 patients diagnosed with NSCLC-BM between June 2019 and May 2021 at Guangdong Sanjiu Brain Hospital (Guangzhou, China), were reviewed. Targeted next-generation sequencing (NGS) of a 168 cancer-related gene panel was available for surgically resected brain tissues from all patients. In addition, molecular characteristics and overall survival (OS) were analyzed to determine potential predictive markers. Results: Among patients with NSCLC-BM, NGS revealed that TP53 was the most frequent mutation (61 %), with a detection rate of 39 %, closely by EGFR amplification. Additionally, CDKN2A, MYC, LRP1B, and RNF43 were frequently observed (18 %). The median OS was significantly shorter in the TP53 mutation group than in the wildtype group (14 versus undefined months, p = 0.014). Similar results were also found in the genetic alteration of EGFR amplification, suggesting that EGFR amplification was associated with worse OS (14 vs. 24 months, p = 0.039). Interestingly, NGS revealed that gene alternations such as TP53, EGFR amplification, and CDKN2A, tended to coexist and such a co-alteration panel indicated worse clinical outcomes (median OS, 5 months). In addition, the detection rate of negative survival genes, including TP53 or EGFR amplification, was much higher in tumor tissues than in plasma samples, indicating the limited predictive value of matched PLA samples. Conclusions: Gene signatures, such as TP53 or EGFR amplification, were associated with worse survival in patients diagnosed with NSCLC-BM. These valuable findings may shed light on new strategies for the prognostic assessment of specific patient groups.

Abstract Objective Stroke is a rare but fatal complication of advanced cancer with Trousseau syndrome, especially as initial symptoms. Here, we report the clinical characteristics, treatment, and prognosis of patients with non-small cell lung cancer (NSCLC) who initially presenting with acute multiple cerebral infarction. Methods The clinical characteristics, imaging, treatment, and oncological outcomes of 10 patients diagnosed with Trousseau syndrome and NSCLC between 2015 and 2021 at Guangdong Sanjiu Brain Hospital were retrospectively collected and analyzed. The clinical course of two typical cases were presented. Results All 10 patients with pathologically confirmed lung adenocarcinoma initially presented with neurological symptoms, including hemiplegic paralysis (7 patients, 70%), dizziness (5 patients, 50%), and unclear speech (3 patients, 30%). The median age was 63.5 years. Eight and two cases were stage III and IV, respectively, at the initial diagnosis. Five patients underwent driver gene testing, revealing three patients with EGFR-sensitive mutations, one patient with ALK fusion, and one patient with wild-type EGFR. All 10 patients received antiplatelet therapy, and six patients subsequently received anti-cancer treatment. The median overall survival of the patients was 8.5 months (95% confidence interval) and 1-year survival rate was 57.1%. Patients who received antitumor treatment, especially those harboring driver gene mutations and received tyrosine kinase inhibitors, had better neurological symptom recovery and superior oncological prognosis (median overall survival, not reached versus 7.4 months, p = 0.038). Conclusion Trousseau syndrome, presenting as multiple cerebral infarctions, is a rare complication of lung adenocarcinoma. Both antiplatelet and antitumor treatment are recommended to achieve better neurological recovery and oncological prognosis in these patients.

Abstract Background The aim of this study was to evaluate the efficacy and safety of osimertinib for the treatment of leptomeningeal metastases (LM) from epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC). Methods We conducted a systematic review and meta-analysis to aggregate the clinical outcomes of patients with LM from EGFR-mutant NSCLC treated with osimertinib. A comprehensive literature search for published and unpublished studies was implemented in April 2021 of PubMed, EMBASE, the Cochrane Library, and several international conference databases, in accordance with the PRISMA guidelines. Meta-analysis of proportions was conducted to calculate the pooled rate of overall response rate (ORR), disease control rate (DCR), one-year overall survival (OS), and adverse events (AEs). Results A total of eleven studies (five prospective and six retrospective) including 353 patients were included. The majority of patients (346/353, 98.0%) received osimertinib as ≥ 2nd-line treatment for LM, either at a dosage of 80 mg (161/353, 45.6%) or 160 mg (191/353, 54.1%). The pooled rates of ORR and DCR were 42% (95% CI 24% to 59%) and 93% (95% CI 88% to 97%), respectively. The pooled one-year OS rate was 59% (95% CI 53% to 65%) in 233 patients from five studies. The highest incidence of AEs of all grades was rash (53%), followed by diarrhea (45%), paronychia (35%), decreased appetite (35%), and dry skin (27%), based on data from four studies. Conclusions Our study highlighted and confirmed the meaningful efficacy and a manageable safety profile of osimertinib for the treatment of LM from EGFR-mutant advanced NSCLC.

Abstract Brain metastasis (BM) is an important cause of mortality for cancer patients. Many patients were diagnosed with brain metastases at their first visit who have not received any treatment while a subset of patients did not have distant metastases at the first visit and brain metastases were detected during the course of systemic therapies. The difference in their genomic characterization is unclear. 96 lung adenocarcinoma patients were enrolled in our study. 53 patients (55%) had synchronous metastatic brain tumors. 43 (45%) patients had metachronous brain metastases. We performed 168 panel-targeted gene sequencing cerebrospinal fluid (CSF) and plasma samples from patients to identify genomic features of synchronous brain metastases (SBM) and metachronous brain metastases (MBM). In conclusion, CSF liquid biopsies have a priority in detecting gene alteration. A comprehensive comparison of molecular profiling between SBM and MBM revealed the most frequently altered genes in both groups were EGFR and TP53, but with different exon point mutations. RTK-RAS and TP53 pathways were the most affected pathways.

Abstract Infant‐type hemispheric glioma, a new subtype of pediatric high‐grade glioma, arises in the cerebral hemispheres. Despite better survival outcomes, the treatment of infant‐type hemispheric glioma is still facing challenges. Here, we reported a case of QKI‐ALK fusion, infant‐type hemispheric glioma with lung metastasis who achieved a complete clinical response after lorlatinib treatment. This typical case demonstrated the importance of appropriate molecularly targeted treatments in ALK‐fused tumors, and lorlatinib may serve as an effective complement to conventional chemotherapy and radiotherapy in primary glioma harboring ALK fusions and its metastasis.

As a disease causing a global pandemic, the progression of symptoms to severe disease in patients with COVID-19 often has adverse outcomes, but research on the immunopathology of COVID-19 severe disease remains limited. In this study, we used mRNA-seq data from the peripheral blood of COVID-19 patients to identify six COVID-19 severe immune characteristic genes (FPR1, FCGR2A, TLR4, S100A12, CXCL1, and L TF), and found neutrophils to be the critical immune cells in COVID-19 severe disease. Subsequently, using scRNA-seq data from bronchoalveolar lavage fluid from COVID-19 patients, neutrophil subtypes highly expressing the S100A family were found to be located at the end of cellular differentiation and tended to release neutrophil extracellular traps. Finally, it was also found that alveolar macrophages, macrophages, and monocytes with a high expression of COVID-19 severe disease immune characteristic genes may influence neutrophils through intercellular ligand–receptor pairs to promote neutrophil extracellular trap release. This study provides immune characteristic genes, critical immune pathways, and immune cells in COVID-19 severe disease, explores intracellular immune transitions of critical immune cells and pit-induced intercellular communication of immune transitions, and provides new biomarkers and potential drug targets for the treatment of patients with COVID-19 severe disease.

Objective To investigate the X-ray-specific sensitive genes and potential signaling pathways involved in the latent period of radiation-induced lung injury (RILI) in mouse models. Method Mice were randomized into groups for whole thoracic irradiation with a single fraction of 20 Gy X-ray or 12.5 Gy carbon heavy ion. Lungs were harvested 3 weeks after the irradiation, whole RNA was extracted and detected with the genome-wide transcriptional microarrays. Differentially expressed genes (DEGs) were calculated for each group and the X-ray-specific sensitive genes were determined, followed by the gene enrichment analysis of those DEGs exploring the potentially relevant signaling pathways and biological processes in latent RILI. Results Three weeks after irradiation, gene expression levels varied between groups. 76 up-regulated DEGs were determined with mice in the X-ray group and gene ontology enrichment analysis for biological process (GO-BP) obtained several processes which were associated with radiation reaction, mitotic, immune cell chemotaxis or metastasis, immune factors, p53 apoptosis, and tissue remodeling. KEGG signaling pathway enrichment analysis showed that those 76 up-regulated DEGs were enriched in p53, IL-17, FoXO, melanoma, and non-small-cell lung cancer signaling pathways. By comparing the DEGs in X-ray and heavy ion groups, X-ray-specific sensitive genes were determined, the top 10 genes were Adamts9, Aacs, Col6a2, Fdps, Mdk, Mcam, Stbd1, Lbh, Ak3, and Emid1. The expression level of the top 10 genes was found to be significantly higher in the X-ray group than in the control and heavy ion groups. Conclusion Our research determined the X-ray-specific sensitive gene set in mice lungs after exposure to radiation. The gene set could be used as a genetic marker to suggest the latency of RILI. The enrichment analysis results suggested that the relevant signaling pathways were potentially involved in the development of RILI. Further validation of those genes and signaling pathways is needed to confirm these findings.

Introduction: Metastases to the central nervous system (CNS) are devastating neurological complications. Circulating cell-free tumor DNA (ctDNA) from cerebrospinal fluid (CSF) better represents genomic alterations in CNS tumors compared to plasma (PLA). However, the clinical value of cerebrospinal fluid (CSF) as a liquid biopsy medium in non-small cell lung cancer patients with leptomeningeal metastases (NSCLC-LM), regardless of extracranial evolution, remains unclear. Patients and methods: 14/48 NSCLC-BM patients and 34/48 NSCLC-LM patients were enrolled in this study. The genomic mutation profiles in CSF and matched PLA for patients with single CNS progression (cohort one, N = 22) or intracranial progression with extracranial disease progression (cohort two, N = 12) were compared. ctDNA in the CSF and simultaneously collected PLA was subjected to next-generation target sequencing (NGS) of 168 cancer-relevant genes. Results: CSF is more comprehensive of driver genomic mutation profile than in matched PLA in patients with a single CNS progression. In addition, potential prognostic markers are much higher in CSF samples than related PLA. For example, the detection rate of EGFR-amp in CSF was more than twice of the rate in matched PLA. Moreover, CDKN2A/B, PIK3CA/G, CDK4/6, and MET were detected uniquely in CSF samples and, all of these genetic mutations were correlated with poor outcomes.Almost all genetic mutation profiles detected in PLA could be seen in matched CSF samples in cohort two. With the driver genes, such as EGFR or ALK, have a higher detection rate in CSF compared to PLA. Moreover, the potential survival maker genes CDK4/6 (6/12, 50%), CDKN2A/B (2/12, 17%), EGFR-amp (1/12, 8%), MET (1/12, 8%), and PIK3CA (1/12, 8%) were unique to the CSF samples. Conclusion: For NSCLC -LM patients, regardless of single intracranial progression or intracranial progression simultaneously with extracranial evolution, CSF is superior to matched PLA.

BackgroundLeptomeningeal metastases (LM) have become increasingly common in non-small cell lung cancer (NSCLC) patients who harbor epidermal growth factor receptor (EGFR) mutation treated with EGFR-TKI and are correlated with inferior prognosis. Evidence in prior research demonstrated that EGFR amplification was more likely presented in advanced clinical stages and was associated with worse survival. However, whether EGFR amplification is a prognostic marker in NSCLC–LM is still inconclusive.MethodsThis study enrolled patients diagnosed with NSCLC–LM from June 2019 to September 2021 and who had received previous EGFR-TKI at Guangdong Sanjiu Brain Hospital. Cerebrospinal fluid (CSF) samples were collected and subjected to targeted next-generation sequencing of 168 cancer-related genes. Clinical characteristics and overall survival (OS) were compared in patients with and without EGFR amplification.ResultsThis study enrolled 53 NSCLC–LM patients, all of whom had EGFR mutations. TP53 and EGFR amplifications are the two most frequent mutations in the study cohort, presenting at 72% (38 of 53) and 40% (21 of 53), respectively. The rate of EGFR amplification was much higher at the time of leptomeningeal progression than at initial diagnosis (p < 0.01). Karnoskfy performance status was poorer (p = 0.021), and CSF pressure was higher (p = 0.0067) in patients with EGFR amplification than those without. A multivariable Cox proportional hazard regression model showed that EGFR amplification was an independent prognostic factor for poorer OS (8.3 vs. 15 months; p = 0.017). The median OS was shorter in NSCLC–LM patients with mutated TP53 than those with wild-type TP53, but the difference was not statistically significant (10 vs. 17.3 months, p = 0.184).ConclusionsEGFR gene amplification could be a potential resistance mechanism to EGFR-TKI failure in NSCLC–LM and is associated with inferior clinical outcomes.

Abstract Background and purpose Leptomeningeal metastasis (LM) is a rare but detrimental complication in patients with non-small cell lung cancer (NSCLC). Although whole brain radiotherapy (WBRT) is used to eliminating cancer cells or microscopic foci, it is becoming less favorable due to the concerns over neurocognitive toxicity. This study aimed to re-evaluate the role of WBRT in the setting of modern targeted therapy. Materials and methods From December 2014 to March 2019, 80 NSCLC patients with cytologically and/or radiologically proven LM diagnosis were retrospectively analyzed. Results The median OS (mOS) after diagnosis of LM was 8.0 (95%CI: 4.4 to 11.6) months, and the one-year OS was 39.4%. The mOS for EGFR-mutated LM patients was 12.6 (3.0 to 22.2) months versus only 4.1 (2.8 to 5.4) for patients with wild-type EGFR (P

Coiled tubing technology is widely used in drilling and repairing operations, and the quality of bias weld directly determines the fatigue life of the coiled tubing. The microstructures consistency between the bias weld and the base metal determines that whether the fatigue resistance of the weld reaches the level of the base metal. In this paper, multi-frequency eddy current testing technique is used to detect the reactance of the bias weld zone and the base material zone within coiled tubing steel strip, which can be used to determine the microstructure consistency between the base metal area and the weld area, and in turn to improve the welding technology and heat treatment process. In this work, CT100 and CT90 materials with the bias weld for coiled tubing were used as the test samples, and the on-line real-time non-destructive testing technology was used to judge whether welding technology and heat treatment technology have been improved. The basis for determination is whether the mechanical properties and fatigue properties of the welding site reach the base material level. The weld zone and base metal zone can be identified by analyzing the characteristic cloud map of the detection signal, and then the quality of partial weld can be evaluated according to the difference of microstructure between them, which is of guiding significance for quality control and improvement of coiled tubing production process.

To make full use of road resources, improve the operation efficiency of the road network system, and alleviate the coexistence between traffic congestion and road resources idle caused by the traffic tidal phenomenon, the impact of the number of lanes on traffic capacity is examined, and the mixed-integer bilevel programming model for reversible lane optimization is established with the aim to minimalize the total travel time of the system. Taking a test road network as an example, the influence of the reversible lane optimization on characteristic values of sections, the route travel time between OD pairs, and the total time of the system are analyzed. The results indicate that the reversible lane optimization can make full use of the idle road resources and make the road network structure match the travel demands better, and the system index after the reversible lane optimization is obviously better than the original system index.

Considering the impact of informatization condition, vehicles on the road network are divided into connected automated vehicles (CAVs) and human-driven vehicles (HDVs), which follow the principle of system optimization and stochastic user equilibrium, respectively. Taking the road network reserve capacity maximization model under the condition of road capacity constraint as the upper-level programming and the traffic assignment model under heterogeneous flow environment as the lower level programming, then a bilevel programming model is constructed. Among them, the nonuniform demand growth multiplier is adopted for each OD pair to reflect the inconsistency of traffic demand structure growth, and the calculation of link capacity is related to the market penetration of CAVs. The incremental method, method of successive averages, and simulated annealing algorithm are used to solve the model, and the effects of different market penetration on road network capacity, travel time, and saturation are analyzed through a numerical example. The relevant data under different weights are normalized and the optimal deployment scheme of CAVs and HDVs in different periods is obtained by comprehensive evaluation. Meanwhile, the mixed equilibrium flow state is explored under the premise of given market penetration to verify the feasibility of the model and algorithm.

Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses’ survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG.

The accurate detection of burned forest area is essential for post-fire management and assessment, and for quantifying carbon budgets. Therefore, it is imperative to map burned areas accurately. Currently, there are few burned-area products around the world. Researchers have mapped burned areas directly at the pixel level that is usually a mixture of burned area and other land cover types. In order to improve the burned area mapping at subpixel level, we proposed a Burned Area Subpixel Mapping (BASM) workflow to map burned areas at the subpixel level. We then applied the workflow to Sentinel 2 data sets to obtain burned area mapping at subpixel level. In this study, the information of true fire scar was provided by the Department of Emergency Management of Hunan Province, China. To validate the accuracy of the BASM workflow for detecting burned areas at the subpixel level, we applied the workflow to the Sentinel 2 image data and then compared the detected burned area at subpixel level with in situ measurements at fifteen fire-scar reference sites located in Hunan Province, China. Results show the proposed method generated successfully burned area at the subpixel level. The methods, especially the BASM-Feature Extraction Rule Based (BASM-FERB) method, could minimize misclassification and effects due to noise more effectively compared with the BASM-Random Forest (BASM-RF), BASM-Backpropagation Neural Net (BASM-BPNN), BASM-Support Vector Machine (BASM-SVM), and BASM-notra methods. We conducted a comparison study among BASM-FERB, BASM-RF, BASM-BPNN, BASM-SVM, and BASM-notra using five accuracy evaluation indices, i.e., overall accuracy (OA), user’s accuracy (UA), producer’s accuracy (PA), intersection over union (IoU), and Kappa coefficient (Kappa). The detection accuracy of burned area at the subpixel level by BASM-FERB’s OA, UA, IoU, and Kappa is 98.11%, 81.72%, 74.32%, and 83.98%, respectively, better than BASM-RF’s, BASM-BPNN’s, BASM-SVM’s, and BASM-notra’s, even though BASM-RF’s and BASM-notra’s average PA is higher than BASM-FERB’s, with 89.97%, 91.36%, and 89.52%, respectively. We conclude that the newly proposed BASM workflow can map burned areas at the subpixel level, providing greater accuracy in regards to the burned area for post-forest fire management and assessment.

It is well-known that genomic mutational analysis plays a significant role in patients with NSCLC for personalized treatment. Given the increasing use of stereotactic radiosurgery (SRS) for brain metastases (BM), there is an emerging need for more precise assessment of survival outcomes after SRS. Patients with BM and treated by SRS were eligible in this study. The primary endpoint was overall survival (OS). Cox regression models were used to identify independent prognostic factors. A survival predictive nomogram was developed and evaluated by Concordance-index (C-index), area under the curve (AUC), and calibration curve. From January 2016 to December 2019, a total of 356 BM patients were eligible. The median OS was 17.7 months [95% confidence interval (CI) 15.5–19.9] and the actual OS at 1- and 2-years measured 63.2 and 37.6%, respectively. A nomogram for OS was developed by incorporating four independent prognostic factors: Karnofsky Performance Score, cumulative tumor volume, gene mutation status, and serum lactate dehydrogenase. The nomogram was validated in a separate cohort and demonstrated good calibration and good discriminative ability (C-index = 0.780, AUC = 0.784). The prognostic accuracy of the nomogram (0.792) was considerably enhanced when compared with classical prognostic indices, including the Graded Prognostic Assessment (0.708), recursive partitioning analysis (0.587), and the SRS (0.536). Kaplan–Meier curves showed significant differences in OS among the stratified low-, median- and high-risk groups (P < 0.001). In conclusion, we developed and validated an individualized prognostic nomogram by integrating physiological, volumetric, clinical chemistry, and molecular biological surrogates. Although this nomogram should be validated by independent external study, it has a potential to facilitate more precise risk-stratifications to guide personalized treatment for BM.

Forest fires are among the biggest threats to forest ecosystems and forest resources, and can lead to ecological disasters and social crises. Therefore, it is imperative to detect and extinguish forest fires in time to reduce their negative impacts. Satellite remote sensing, especially meteorological satellites, has been a useful tool for forest-fire detection and monitoring because of its high temporal resolution over large areas. Researchers monitor forest fires directly at pixel level, which usually presents a mixture of forest and fire, but the low spatial resolution of such mixed pixels cannot accurately locate the exact position of the fire, and the optimal time window for fire suppression can thus be missed. In order to improve the positioning accuracy of the origin of forest fire (OriFF), we proposed a mixed-pixel unmixing integrated with pixel-swapping algorithm (MPU-PSA) model to monitor the OriFFs in time. We then applied the model to the Japanese Himawari-8 Geostationary Meteorological Satellite data to obtain forest-fire products at subpixel level. In this study, the ground truth data were provided by the Department of Emergency Management of Hunan Province, China. To validate the positioning accuracy of MPU-PSA for OriFFs, we applied the model to the Himawari-8 satellite data and then compared the derived fire results with fifteen reference forest-fire events that occurred in Hunan Province, China. The results show that the extracted forest-fire locations using the proposed method, referred to as forest fire locations at subpixel (FFLS) level, were far closer to the actual OriFFs than those from the modified Himawari-8 Wild Fire Product (M-HWFP). This improvement will help to reduce false fire claims in the Himawari-8 Wild Fire Product (HWFP). We conducted a comparative study of M-HWFP and FFLS products using three accuracy-evaluation indexes, i.e., Euclidean distance, RMSE, and MAE. The mean distances between M-HWFP fire locations and OriFFs and between FFLS fire locations and OriFFs were 3362.21 m and 1294.00 m, respectively. The mean RMSEs of the M-HWFP and FFLS products are 1225.52 m and 474.93 m, respectively. The mean MAEs of the M-HWFP and FFLS products are 992.12 m and 387.13 m, respectively. We concluded that the newly proposed MPU-PSA method can extract forest-fire locations at subpixel level, providing higher positioning accuracy of forest fires for their suppression.

Background: Gliomas are the malignance of a poor prognosis. The current WHO classification remains unable to predict survival outcomes accurately. Novel surrogates are highly required for improved stratification of patients and hence, allowing to delivery of the most appropriate treatment. Methods: Transcriptional profiles of 301 glioma cases on the platform of Chinese Glioma Genome Atlas (CGGA) were retrospectively studied. Results: Extracellular matrix (ECM) scores were established by integrating a panel of most featured gene-signatures, correlating well with pathological tumor stages. Linear regression analysis revealed that the ECM score corroborated with the infiltration status of monocytes, M0 and M1 macrophages. Furthermore, the WHO stage II-IV dependent abundance of those 3 immune cells was determined. Univariate and multivariate analysis of clinicopathological characteristics in the GBM cohort identified M1 enrichment score as an independent risk factor. A high abundance of M1 macrophages was associated with poor survival outcomes and radiotherapy response in IDH-wildtype GBM. Conclusions: Our study demonstrated that M1 macrophages correlated with WHO grades and predicted robustly for the survival performance for GBM patients. Increased infiltration of M1 macrophages was associated with a poor radiation response for IDH-wildtype GBM. Together, it will facilitate more precise stratifications of glioma patients based on molecular and immunological surrogates.

When a wellhead gas production tree in a certain oilfield block fracturing completed 12 layers and 22 layers and then the bottom-up discharge operation was performed, the Wellhead four-way suddenly suffered erosion failure. This is the seventh failure of this operation. In order to obtain the cause of failure, the chemical analysis, hardness testing, tensile property testing, and finite element structural dynamic analysis are used to analyze the failure of the cross connection. The results of physical and chemical analysis show that the chemical composition, hardness, and tensile properties of the failed parts meet the requirements of the standard, not the problem of the material of the work piece. Due to the high-frequency vibration generated by the three-phase fluid in the pipeline during the discharge process, different types of vibration and deformation of the four-way valve and the valve body occur. The dimensions of the on-site structural parts were measured, and the bolt sizes were found to be different. A finite element model was established based on the measured data for dynamic analysis. Through physical and chemical tests and theoretical calculations, it is found that the cause of failure is the unbalanced load and resonance of the bolt, and the nut undercuts under high-frequency vibration, which causes leakage at the flange connection and eventually causes erosion failure. It is recommended to regularly use an electronic torque wrench to test the pretightening force of each bolt to prevent vibration and failure due to inconsistent pretightening force of the bolts.

The biosensor based on surface acoustic wave is of great significance for the application of biological clinical detection, but the sensitivity and specificity of surface acoustic wave biosensor still need to be improved. In this article, the structure of surface acoustic wave biosensor and interdigital transducer is designed by studying the theoretical model of surface acoustic wave biosensor. Then the amplitude–frequency response of the device is studied. Later, the simulation model of surface acoustic wave biosensor structure is established, and the performance of surface acoustic wave device is numerically calculated. Meanwhile, the relationship between the applied excitation signal and the resonant frequency is considered, and the performance of the surface wave propagation and attenuation characteristics are analyzed. In addition, the influence of the material of the piezoelectric substrate and the structure of the interdigitated electrode on the surface acoustic wave propagation are studied. The response potential curve and the total displacement of the particle vibration are analyzed, and the structure of the surface acoustic wave device is optimized.