Evaluation of the learning curve and complications in unilateral biportal endoscopic transforaminal lumbar interbody fusion: cumulative sum analysis and risk-adjusted cumulative sum analysis.

PURPOSE: To evaluate the learning curve and complications in unilateral biportal endoscopic transforaminal lumbar interbody fusion (ULIF) using the Cumulative Sum (CUSUM) analysis and Risk-adjusted Cumulative Sum (RA-CUSUM) analysis. METHODS: This study retrospectively analyzed 184 consecutive patients who received ULIF in our hospital, including 104 males and 80 females. CUSUM analysis and RA-CUSUM analysis were used to evaluate the learning curve of ULIF based on the operation time and surgical failure rate, respectively. All postoperative complications were defined as surgical failure. Variables of different phases were compared based on the learning curve. RESULTS: The CUSUM analysis showed the cutoff point for ULIF was 29 cases, and the RA-CUSUM analysis showed the cutoff point for ULIF was 41 cases. Operating time and hospital stay were significantly decreased as the learning curve progressed (P < 0.05). Visual analogue score (VAS) and Oswestry disability index (ODI) at the last follow-up were significantly lower than preoperatively. At the last follow-up, a total of 171 patients reached intervertebral fusion, with a fusion rate of 92.9% (171/184). A total of eleven complications were observed, and RA-CUSUM analysis showed that the incidence of complications in the early phase was 17.07% and in the late phase was 2.6%, with a significant difference (P < 0.05). CONCLUSION: ULIF is an effective minimally invasive lumbar fusion surgical technique. But a learning curve of at least 29 cases will be required to master ULIF, while 41 cases will be required to achieve a stable surgical success rate.

Pleiotropic immunoregulation by growth-blocking peptide in Ostrinia furnacalis.

Insects rely on their innate immune system to eliminate pathogenic microbes. As a system component, cytokines transmit intercellular signals to control immune responses. Growth-blocking peptide (GBP) is a member of the stress-responsive peptide family of cytokines found in several orders of insects, including Drosophila. However, the physiological role of GBP in defence against pathogens is not thoroughly understood. In this study, we explored the functions of GBP in a lepidopteran pest, Ostrinia furnacalis. Injection of recombinant O. furnacalis GBP (OfGBP) precursor (proGBP) and chemically synthesised GBP significantly induced the transcription of antimicrobial peptides (AMPs) and other immunity-related genes including immune deficiency (IMD) and Dorsal. The level of OfGBP mRNA was upregulated after bacterial infection. Knockdown of OfGBP expression led to a decrease in IMD, Relish, MyD88 and Dorsal mRNA levels. OfGBP induced phenoloxidase activity and affected hemocyte behaviours in O. furnacalis larvae. In summary, GBP is a potent cytokine, effectively regulating AMP synthesis, melanization response and cellular immunity to eliminate invading pathogens.

Recurrent Cushing's Disease Caused by a TPIT-Lineage Densely Granulated Corticotroph Pituitary Neuroendocrine Tumor: A Case Report.

INTRODUCTION: Recurrent Cushing's disease (recurrent CD) is an uncommon and intricate clinical form of Cushing's syndrome. However, the connection between the pathological types of ACTH-secreting PitNETs and the clinical signs of recurrent CD remains uncertain. CASE DESCRIPTION: A 64-year-old woman, previously diagnosed with renal carcinoma, was admitted to our hospital due to recent weight gain. Previous endocrine tests indicated fluctuating hypercortisolemia and a recurrent pituitary tumor over the past six years. She underwent two transsphenoidal hypophysectomies, and histopathological analysis of the tumor revealed it as a densely granulated corticotroph tumor (DGCT), a subtype of TPIT-lineage PitNET, accompanied by tumor apoplexy. CONCLUSION: This case highlights the connection between recurrent CD and the pathological subtypes of TPIT-lineage DGCT-PitNETs.

Safety and Efficacy Outcomes Following Spinal Endoscopic Procedures for Thoracic Ligamentous Ossification: A Systematic Review and Meta-Analysis.

STUDY DESIGN: A systematic review and meta-analysis. OBJECTIVE: This study systematically reviewed and evaluated the safety and efficacy of spinal endoscopic techniques as a treatment for thoracic ligamentum flavum ossification (TOLF). SUMMARY OF BACKGROUND DATA: The use of spinal endoscopic techniques for the treatment of TOLF has increased in recent years. The present study is the first comprehensive systematic review and meta-analysis focused on the use of spinal endoscopic techniques for TOLF. MATERIALS AND METHODS: The Cochrane Central, PubMed, Web of Science, and Embase databases were systematically searched for studies focused on patients undergoing spinal endoscopic techniques to treat symptomatic TOLF. RESULTS: This meta-analysis included 23 studies. We included 323 patients (177 males, 146 females) with a mean age of 58.40±10.06 years, with 304 total recorded lesion locations of which 245 were located in the lower thoracic spine. Complications affected 35/323 patients, and the mean operative duration for 305 patients was 108.15±47.34 minutes. For 187 patients, the mean operative bleeding was 25.13±12.54 mL, while for 87 patients the mean duration of hospitalization was 4.59±1.93 days. At last follow-up, functional assessment was performed for 260 patients, of whom 200 were in excellent condition, visual analog scale (VAS) scores were assessed for 160 patients, with a mean improvement of 4.40 (3.95, 4.86) Japanese Orthopedic Association (JOA) scores were recorded for 115 patients, with a mean improvement of 3.49 (2.79,4.18), and modified Japanese Orthopedic Association (mJOA) scores were recorded for 208 patients, with a mean improvement of 3.62 (2.89,4.35). CONCLUSIONS: These results support several advantages of spinal endoscopic techniques for the treatment of symptomatic TOLF. These include low complication rates, rapid postoperative recovery, and good functional recovery when used for single-segment, non-nodular ossification and no combined dural ossification.

Clinical comparison of unilateral biportal endoscopic transforaminal lumbar interbody fusion verse 3D microscope-assisted transforaminal lumbar interbody fusion in the treatment of single-segment lumbar spondylolisthesis with lumbar spinal stenosis: a retrospective study with 24-month follow-up.

OBJECTIVE: To explore the safety and the mid-term efficacy of unilateral biportal endoscopic transforaminal lumbar interbody fusion (UBE-TLIF) and 3D microscope-assisted transforaminal lumbar interbody fusion (MMIS-TLIF) for treating single-segment lumbar spondylolisthesis with lumbar spinal stenosis (DLS-LSS). METHODS: The clinical data of 49 patients who underwent UBE-TLIF or MMIS-TLIF in our hospital were retrospectively analyzed, including 26 patients who underwent the UBE-TLIF and 23 patients who underwent the MMIS-TLIF. The demographic and perioperative outcomes of patients before and after surgery were reviewed. Visual analogue scale (VAS) and Oswestry disability index (ODI) were used to evaluate the clinical outcomes of patients before surgery and at 1, 3, 6, 12 and 24 months after surgery. The lumbar lordosis angle (LL), disc height (DH) and lumbar intervertebral fusion rate were assessed before surgery and at the last follow-up. RESULTS: The VAS and ODI scores of the two groups were improved compared with those before surgery. The ODI of UBE-TLIF group was lower than that of MMIS-TLIF group at 1, 3, 6, and 12 months after surgery, and there were no significant differences between the two groups at other time points (P > 0.05). There were no significant differences in VAS between the two groups at each time point (P > 0.05). However, the UBE-TLIF group had more advantages in blood loss and hospital stay. The complications between the UBE-TLIF group (11.54%) and the MMIS-TLIF group (17.39%) were comparable (P > 0.05). Radiographic outcomes showed that the LL and DH of the two groups were improved compared with those before surgery, and the difference before and after surgery was not significant (P > 0.05). The fusion rate was 96.2% in the UBE-TLIF group and 95.7% in the MMIS-TLIF group. There was no significant difference in the fusion rate between the two groups (P > 0.05). CONCLUSIONS: Both UBE-TLIF and MMIS-TLIF have favorable outcomes for treating single-segment DLS-LSS. Both groups have the advantages of clear surgical vision, high surgical efficiency, and favorable mid-term efficacy. In addition, compared with MMIS-TLIF, UBE-TLIF causes less intraoperative bleeding and faster postoperative recovery.

Xoo-YOLO: a detection method for wild rice bacterial blight in the field from the perspective of unmanned aerial vehicles.

Wild rice, a natural gene pool for rice germplasm innovation and variety improvement, holds immense value in rice breeding due to its disease-resistance genes. Traditional disease resistance identification in wild rice heavily relies on labor-intensive and subjective manual methods, posing significant challenges for large-scale identification. The fusion of unmanned aerial vehicles (UAVs) and deep learning is emerging as a novel trend in intelligent disease resistance identification. Detecting diseases in field conditions is critical in intelligent disease resistance identification. In pursuit of detecting bacterial blight in wild rice within natural field conditions, this study presents the Xoo-YOLO model, a modification of the YOLOv8 model tailored for this purpose. The Xoo-YOLO model incorporates the Large Selective Kernel Network (LSKNet) into its backbone network, allowing for more effective disease detection from the perspective of UAVs. This is achieved by dynamically adjusting its large spatial receptive field. Concurrently, the neck network receives enhancements by integrating the GSConv hybrid convolution module. This addition serves to reduce both the amount of calculation and parameters. To tackle the issue of disease appearing elongated and rotated when viewed from a UAV perspective, we incorporated a rotational angle (theta dimension) into the head layer's output. This enhancement enables precise detection of bacterial blight in any direction in wild rice. The experimental results highlight the effectiveness of our proposed Xoo-YOLO model, boasting a remarkable mean average precision (mAP) of 94.95%. This outperforms other models, underscoring its superiority. Our model strikes a harmonious balance between accuracy and speed in disease detection. It is a technical cornerstone, facilitating the intelligent identification of disease resistance in wild rice on a large scale.

Preoperative albumin-to-globulin ratio and prognostic nutritional index predict the prognosis of colorectal cancer: a retrospective study.

The immunonutritional status has important effects on outcomes for cancer patients. Albumin-to-globulin ratio (AGR) and the prognostic nutrition index (PNI) are often used to assess the immunonutritional status of cancer patients. However, the clinical significance of these factors in colorectal cancer (CRC) remains unclear. We aimed to evaluate the clinical significance of the AGR and PNI in CRC. We reviewed the clinical data of 511 patients with CRC in two hospitals. Data from one institution was used as the training cohort. The optimal cutoff values for AGR and PNI in the training cohort were 1.4 and 48.65, respectively. Patients in both the low AGR and low PNI groups had poor overall survival (OS) and progression-free survival (PFS), while those in the low AGR-low PNI group had the lowest OS and PFS. Multivariate analysis revealed that preoperative AGR, preoperative PNI, gross type, and TNM stage were independent prognostic factors influencing OS in patients with CRC. Preoperative AGR, preoperative PNI, and TNM stage were independently associated with PFS in patients with CRC. According to the results of multivariate analysis in the training cohort, we developed the nomograms for OS and PFS and performed internal and external validation, which showed good prediction ability of the nomograms. In conclusion, preoperative AGR and PNI can be used as effective indicators to predict survival for patients with CRC. AGR and PNI may help develop effective adjuvant-therapy schedules.

Uncertainty-guided transformer for brain tumor segmentation.

Multi-model data can enhance brain tumor segmentation for the rich information it provides. However, it also introduces some redundant information that interferes with the segmentation estimation, as some modalities may catch features irrelevant to the tissue of interest. Besides, the ambiguous boundaries and irregulate shapes of different grade tumors lead to a non-confidence estimate of segmentation quality. Given these concerns, we exploit an uncertainty-guided U-shaped transformer with multiple heads to construct drop-out format masks for robust training. Specifically, our drop-out masks are composed of boundary mask, prior probability mask, and conditional probability mask, which can help our approach focus more on uncertainty regions. Extensive experimental results show that our method achieves comparable or higher results than previous state-of-the-art brain tumor segmentation methods, achieving average dice coefficients of [Formula: see text] and Hausdorff distance of 4.91 on the BraTS2021 dataset. Our code is freely available at https://github.com/chaineypung/BTS-UGT.

Long-Life, High-Rate Rechargeable Lithium Batteries Based on Soluble Bis(2-pyrimidyl) Disulfide Cathode.

Organosulfides are promising candidates as cathode materials for the development of electric vehicles and energy storage systems due to their low-cost and high capacity properties. However, they generally suffer from slow kinetics because of the large rearrangement of S-S bonds and structural degradation upon cycling in batteries. In this paper, we reveal that soluble bis(2-pyrimidyl) disulfide (Pym2 S2 ) can be a high-rate cathode material for rechargeable lithium batteries. Benefiting from the superdelocalization of pyrimidyl group, the extra electrons prefer to be localized on the π* (pyrimidyl group) than σ* (S-S bond) molecular orbitals initially, generating the anion-like intermedia of [Pym2 S2 ]2- and thus decreasing the dissociation energy of the S-S bond. It makes the intrinsic energy barrier of dissociative electron transfer depleted, therefore the lithium half cell exhibits 2000 cycles at 5 C. This study provides a distinct pathway for the design of high-rate, long-cycle-life organic cathode materials.

Analysis of Medication Rules of Traditional Chinese Medicine for Malaria Treatment Based on Data Mining.

Objective To analyze the medication rules of traditional Chinese medicine (TCM) for malaria treatment.Methods Statistical analysis was conducted on the basic attributes of TCM drugs with regard to property, therapeutic methods, flavor, and meridian tropism. A complex network of TCM drug associations was constructed. Cluster analysis was applied to obtain the core drugs for malaria treatment. The Apriori algorithm was applied to analyze the association rules of these core drugs.Results A total of 357 herbs were used 3,194 times in 461 prescriptions for malaria treatment. Radix Glycyrrhizae (), Rhizoma Pinelliae (), Radix Bupleuri (), and Radix Dichroae () were the frequently used herbs through supplementing, exterior-releasing, heat-clearing, qi-rectifying, and damp-resolving therapeutic methods. Such herbs had warm, natural, and cold herbal properties; pungent, bitter, and sweet flavors; and spleen, lung, and stomach meridian tropisms. Cluster analysis showed 61 core drugs, including Radix Glycyrrhizae, Rhizoma Pinelliae, Radix Bupleuri, and Radix Scutellariae (). Apriori association rule analysis yielded 12 binomial rules (herb pairs) and 6 trinomial rules (herb combinations). Radix Bupleuri plus Radix Scutellariae was the core herbal pair for treating malaria. This pair could be combined with Rhizoma Atractylodis Macrocephalae () for treating warm or cold malaria, combined with Pericarpium Citri Reticulatae () or Radix Dichroae () for treating miasmic malaria, or combined with turtle shells () for treating malaria with splenomegaly.Conclusions TCM can be used to classify and treat malaria in accordance with the different stages of development. As the core herbal pair, Radix Bupleuri and Radix Scutellariae can be combined with other drugs to treat malaria with different syndrome types.

Rapid and Sensitive Diagnosis of COVID-19 Using an Electricity-Free Self-Testing System.

Rapid and sensitive detection of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for early diagnosis and effective treatment. Nucleic acid testing has been considered the gold standard method for the diagnosis of COVID-19 for its high sensitivity and specificity. However, the polymerase chain reaction (PCR)-based method in the central lab requires expensive equipment and well-trained personnel, which makes it difficult to be used in resource-limited settings. It highlights the need for a sensitive and simple assay that allows potential patients to detect SARS-CoV-2 by themselves. Here, we developed an electricity-free self-testing system based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) that allows for rapid and accurate detection of SARS-CoV-2. Our system employs a heating bag as the heat source, and a 3D-printed box filled with phase change material (PCM) that successfully regulates the temperature for the RT-LAMP. The colorimetric method could be completed in 40 min and the results could be read out by the naked eye. A ratiometric measurement for exact readout was also incorporated to improve the detection accuracy of the system. This self-testing system is a promising tool for point-of-care testing (POCT) that enables rapid and sensitive diagnosis of SARS-CoV-2 in the real world and will improve the current COVID-19 screening efforts for control and mitigation of the pandemic.

Three-Dimensional Digital Reconstruction of the Cerebellar Cortex: Lobule Thickness, Surface Area Measurements, and Layer Architecture.

The cerebellum is ontogenetically one of the first structures to develop in the central nervous system; nevertheless, it has been only recently reconsidered for its significant neurobiological, functional, and clinical relevance in humans. Thus, it has been a relatively under-studied compared to the cerebrum. Currently, non-invasive imaging modalities can barely reach the necessary resolution to unfold its entire, convoluted surface, while only histological analyses can reveal local information at the micrometer scale. Herein, we used the BigBrain dataset to generate area and point-wise thickness measurements for all layers of the cerebellar cortex and for each lobule in particular. We found that the overall surface area of the cerebellar granular layer (including Purkinje cells) was 1,732 cm2 and the molecular layer was 1,945 cm2. The average thickness of the granular layer is 0.88 mm (± 0.83) and that of the molecular layer is 0.32 mm (± 0.08). The cerebellum (both granular and molecular layers) is thicker at the depth of the sulci and thinner at the crowns of the gyri. Globally, the granular layer is thicker in the lateral-posterior-inferior region than the medial-superior regions. The characterization of individual layers in the cerebellum achieved herein represents a stepping-stone for investigations interrelating structural and functional connectivity with cerebellar architectonics using neuroimaging, which is a matter of considerable relevance in basic and clinical neuroscience. Furthermore, these data provide templates for the construction of cerebellar topographic maps and the precise localization of structural and functional alterations in diseases affecting the cerebellum.

Prediction of the Sound Absorption Coefficient of Three-Layer Aluminum Foam by Hybrid Neural Network Optimization Algorithm.

The combination of multilayer aluminum foam can have high sound absorption coefficients (SAC) at low and medium frequencies, and predicting its absorption coefficient can help the optimal structural design. In this study, a hybrid EO-GRNN model was proposed for predicting the sound absorption coefficient of the three-layer composite structure of the aluminum foam. The generalized regression neural network (GRNN) model was used to predict the sound absorption coefficient of three-layer composite structural aluminum foam due to its outstanding nonlinear problem-handling capability. An equilibrium optimization (EO) algorithm was used to determine the parameters in the neuronal network. The prediction results show that this method has good accuracy and high precision. The calculation result shows that this proposed hybrid model outperforms the single GRNN model, the GRNN model optimized by PSO (PSO-GRNN), and the GRNN model optimized by FOA(FOA-GRNN). The prediction results are expressed in terms of root mean square error (RMSE), absolute error, and relative error, and this method performs well with an average RMSE of only 0.011.

LncPheDB: a genome-wide lncRNAs regulated phenotypes database in plants.

LncPheDB (https://www.lncphedb.com/) is a systematic resource of genome-wide long non-coding RNAs (lncRNAs)-phenotypes associations for multiple species. It was established to display the genome-wide lncRNA annotations, target genes prediction, variant-trait associations, gene-phenotype correlations, lncRNA-phenotype correlations, and the similar non-coding regions of the queried sequence in multiple species. LncPheDB sorted out a total of 203,391 lncRNA sequences, 2000 phenotypes, and 120,271 variants of nine species (Zea mays L., Gossypium barbadense L., Triticum aestivum L., Lycopersicon esculentum Mille, Oryza sativa L., Hordeum vulgare L., Sorghum bicolor L., Glycine max L., and Cucumis sativus L.). By exploring the relationship between lncRNAs and the genomic position of variants in genome-wide association analysis, a total of 68,862 lncRNAs were found to be related to the diversity of agronomic traits. More importantly, to facilitate the study of the functions of lncRNAs, we analyzed the possible target genes of lncRNAs, constructed a blast tool for performing similar fragmentation studies in all species, linked the pages of phenotypic studies related to lncRNAs that possess similar fragments and constructed their regulatory networks. In addition, LncPheDB also provides a user-friendly interface, a genome visualization platform, and multi-level and multi-modal convenient data search engine. We believe that LncPheDB plays a crucial role in mining lncRNA-related plant data. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-022-00084-3.

Identification of candidate genes and clarification of the maintenance of the green pericarp of weedy rice grains.

The weedy rice (Oryza sativa f. spontanea) pericarp has diverse colors (e.g., purple, red, light-red, and white). However, research on pericarp colors has focused on red and purple, but not green. Unlike many other common weedy rice resources, LM8 has a green pericarp at maturity. In this study, the coloration of the LM8 pericarp was evaluated at the cellular and genetic levels. First, an examination of their ultrastructure indicated that LM8 chloroplasts were normal regarding plastid development and they contained many plastoglobules from the early immature stage to maturity. Analyses of transcriptome profiles and differentially expressed genes revealed that most chlorophyll (Chl) degradation-related genes in LM8 were expressed at lower levels than Chl a/b cycle-related genes in mature pericarps, suggesting that the green LM8 pericarp was associated with inhibited Chl degradation in intact chloroplasts. Second, the F2 generation derived from a cross between LM8 (green pericarp) and SLG (white pericarp) had a pericarp color segregation ratio of 9:3:4 (green:brown:white). The bulked segregant analysis of the F2 populations resulted in the identification of 12 known genes in the chromosome 3 and 4 hotspot regions as candidate genes related to Chl metabolism in the rice pericarp. The RNA-seq and sqRT-PCR assays indicated that the expression of the Chl a/b cycle-related structural gene DVR (encoding divinyl reductase) was sharply up-regulated. Moreover, genes encoding magnesium-chelatase subunit D and the light-harvesting Chl a/b-binding protein were transcriptionally active in the fully ripened dry pericarp. Regarding the ethylene signal transduction pathway, the CTR (encoding an ethylene-responsive protein kinase) and ERF (encoding an ethylene-responsive factor) genes expression profiles were determined. The findings of this study highlight the regulatory roles of Chl biosynthesis- and degradation-related genes influencing Chl accumulation during the maturation of the LM8 pericarp.

Resource Allocation and Computation Offloading for Wireless Powered Mobile Edge Computing.

In this paper, we investigate a resource allocation and computation offloading problem in a heterogeneous mobile edge computing (MEC) system. In the considered system, a wireless power transfer (WPT) base station (BS) with an MEC sever is able to deliver wireless energy to the mobile devices (MDs), and the MDs can utilize the harvested energy for local computing or task offloading to the WPT BS or a Macro BS (MBS) with a stronger computing server. In particular, we consider that the WPT BS can utilize full- or half-duplex wireless energy transmission mode to empower the MDs. The aim of this work focuses on optimizing the offloading decision, full/half-duplex energy harvesting mode and energy harvesting (EH) time allocation with the objective of minimizing the energy consumption of the MDs. As the formulate problem has a non-convex mixed integer programming structure, we use the quadratically constrained quadratic program (QCQP) and semi-definite relaxation (SDR) methods to solve it. The simulation results demonstrate the effectiveness of the proposed scheme.

Pan-immune-inflammation value is associated with the clinical stage of colorectal cancer.

Objective: We investigated the clinical significance of preoperative pan-immune-inflammation value (PIV) in patients with colorectal cancer (CRC). Methods: In this retrospective study, 366 cases who underwent surgery for CRC were enrolled. Their clinical data were collected. PIV was calculated with the formula PIV = [neutrophil count (109/L)× platelet count (109/L) × monocyte count (109/L) /lymphocyte count (109/L). Patients were divided into high PIV (> median PIV) and low PIV (< median PIV) groups. The relationship between PIV and clinicopathological features of CRC was investigated. Receiver operating characteristic (ROC) curve was plotted to indicate the value of immune-inflammatory biomarkers (IIBs) in predicting the TNM stage of CRC, and the area under the curve (AUC) was calculated to evaluate the actual clinical value of IIBs. AUC > 0.5 and closer to 1 indicated the better predictive efficacy. The influencing factors of PIV in CRC were analyzed. Results: We found that PIV was positively correlated with tumor size (r = 0.300, p < 0.05), carcinoembryonic antigen (CEA) (r = 0.214, p < 0.05) and carbohydrate antigen 125 (CA-125) (r = 0.249, p < 0.05), but negatively correlated with albumin (Alb) (r = -0.242, p < 0.05). PIV was significantly different in patients with different tumor locations (left or right), surgical methods (laparotomy versus laparoscopic surgery) (p < 0.05), and patients with different pathological T stages, N-stage and TNM stages (p < 0.05). ROC curve analysis of IIBs showed the AUC of PIV was greater than other markers when combined with CEA or carbohydrate antigen 19-9 (CA19-9). Multivariate regression analysis identified T stage, CEA, Alb, and tumor size as the independent influential factors of PIV in CRC. Conclusion: PIV is associated with the tumor stage in patients with CRC, which may be useful in preoperative assessment of CRC.

Detection of mutation profiles and tumor mutation burden of cerebrospinal fluid circulating DNA by a cancer genomic panel sequencing in glioma patients.

BACKGROUND AND AIMS: Circulating tumor DNA (ctDNA) has been recognized as a reliable source to reflect the molecular and genetic landscape of corresponding tumors in recent years. In this study, we tested the application of a cancer genomic panel sequencing on the cerebrospinal fluid (CSF)-derived ctDNA for the less invasive detection and diagnosis of glioma. MATERIALS AND METHODS: CtDNA was extracted from 26 CSF samples and subject to a cancer genomic panel sequencing of 520 genes to analyze the mutation profiles and tumor mutation burden (TMB), which were compared with their corresponding tumor DNA samples. Associations between mutations or TMB and clinical characteristics were also evaluated. RESULTS: A high detection rate of ctDNA (24/26, 92.3%) was observed in CSF. CtDNA mutations had high concordance rates with tumor DNA, especially in non-copy number variations and in glioblastoma. CSF ctDNA TMB also exhibited a strong correlation with tumor DNA TMB (R2 = 0.879, P < 0.001), particularly in glioblastoma (R2 = 0.992, P < 0.001). Age was significantly associated with CSF ctDNA TMB in glioma patients. CONCLUSION: We established a less invasive but effective molecular diagnostic approach using a cancer genomic panel sequencing system targeting CSF ctDNA for glioma, especially in glioblastoma.