Rapid Mass Spectrometry-Based Multiattribute Method for Glycation Analysis with Integrated Afucosylation Detection Capability.

The multiattribute method (MAM) has emerged as a powerful tool for simultaneously screening multiple product quality attributes of therapeutic antibodies. One such potential critical quality attribute (CQA) is glycation, a common modification that can impact the heterogeneity, functional activity, and immunogenicity of therapeutic antibodies. However, current methods for monitoring glycation levels in MAM are rare and not sufficiently rapid and accurate. In this study, an improved mass spectrometry (MS)-based MAM was developed to simultaneously monitor glycation and other quality attributes including afucosylation. The method was evaluated using two therapeutic antibodies with different glycosylation site numbers. Treatment with IdeS, Endo F2, and dithiothreitol generated three distinct subunits, and the glycation results obtained were similar to those treated with PNGase F, which is routinely used to release glycans; the sample processing time was greatly reduced while providing additional quality attribute information. The MS-based MAM was also employed to assess the glycation progression following forced glycation in various buffer solutions. A significant increase in oxidation was observed when forced glycation was conducted in an ammonium bicarbonate buffer solution, and a total of 23 potential glycation sites and 4 significantly oxidized sites were identified. Notably, we found that ammonium bicarbonate was found to specifically stimulate oxidation, while glycation had a synergistic effect on oxidation. These findings establish this study as a novel methodology for achieving a technologically advanced platform and concept that enhances the efficacy of product development and quality control, characterized by its broad-spectrum, rapid, and accurate nature.

Detection of virtual reality motion sickness based on EEG using asymmetry of entropy and cross-frequency coupling.

The existence of Virtual Reality Motion Sickness (VRMS) is a key factor restricting the further development of the VR industry, and the premise to solve this problem is to be able to accurately and effectively detect its occurrence. In view of the current lack of high-accuracy and effective detection methods, this paper proposes a VRMS detection method based on entropy asymmetry and cross-frequency coupling value asymmetry of EEG. First of all, the EEG of the four selected pairs of electrodes on the bilateral brain are subjected to Multivariate Variational Mode Decomposition (MVMD) respectively, and three types of entropy values on the low-frequency and high-frequency components are calculated, namely approximate entropy, fuzzy entropy and permutation entropy, as well as three types of phase-amplitude coupling features between the low-frequency and high-frequency components, namely the mean value, standard deviation and correlation coefficient; Secondly, the difference of the entropies and the cross-frequency coupling features between the left electrodes and the right electrodes are calculated; Finally, the final feature set are selected via t-test and fed into the SVM for classification, thus realizing the automatic detection of VRMS. The results show that the three classification indexes under this method, i.e., accuracy, sensitivity and specificity, reach 99.5 %, 99.3 % and 99.7 %, respectively, and the value of the area under the ROC curve reached 1, which proves that this method can be an effective indicator for detecting the occurrence of VRMS.

EEG classification model for virtual reality motion sickness based on multi-scale CNN feature correlation.

BACKGROUND: Virtual reality motion sickness (VRMS) is a key issue hindering the development of virtual reality technology, and accurate detection of its occurrence is the first prerequisite for solving the issue. OBJECTIVE: In this paper, a convolutional neural network (CNN) EEG detection model based on multi-scale feature correlation is proposed for detecting VRMS. METHODS: The model uses multi-scale 1D convolutional layers to extract multi-scale temporal features from the multi-lead EEG data, and then calculates the feature correlations of the extracted multi-scale features among all the leads to form the feature adjacent matrixes, which converts the time-domain features to correlation-based brain network features, thus strengthen the feature representation. Finally, the correlation features of each layer are fused. The fused features are then fed into the channel attention module to filter the channels and classify them using a fully connected network. Finally, we recruit subjects to experience 6 different modes of virtual roller coaster scenes, and collect resting EEG data before and after the task to verify the model. RESULTS: The results show that the accuracy, precision, recall and F1-score of this model for the recognition of VRMS are 98.66 %, 98.65 %, 98.68 %, and 98.66 %, respectively. The proposed model outperforms the current classic and advanced EEG recognition models. SIGNIFICANCE: It shows that this model can be used for the recognition of VRMS based on the resting state EEG.

Development of a reliable cell-based reporter gene assay to measure the bioactivity of anti-HER2 therapeutic antibodies.

Human epidermal growth factor receptor 2 (HER2) is a key player in the pathogenesis and progression of breast cancer and is currently a primary target for breast cancer immunotherapy. Bioactivity determination is necessary to guarantee the safety and efficacy of therapeutic antibodies targeting HER2. Nevertheless, currently available bioassays for measuring the bioactivity of anti-HER2 mAbs are either not representative or have high variability. Here, we established a reliable reporter gene assay (RGA) based on T47D-SRE-Luc cell line that expresses endogenous HER2 and luciferase controlled by serum response element (SRE) to measure the bioactivity of anti-HER2 antibodies. Neuregulin-1 (NRG-1) can lead to the heterodimerization of HER2 on the cell membrane and induce the expression of downstream SRE-controlled luciferase, while pertuzumab can dose-dependently reverse the reaction, resulting in a good dose-response curve reflecting the activity of the antibody. After optimizing the relevant assay parameters, the established RGA was fully validated based on ICH-Q2 (R1), which demonstrated that the method had excellent specificity, accuracy, precision, linearity, and stability. In summary, this robust and innovative bioactivity determination assay can be applied in the development and screening, release control, biosimilar assessment and stability studies of anti-HER2 mAbs.

SOAT1 regulates cholesterol metabolism to induce EMT in hepatocellular carcinoma.

Cholesterol metabolism reprogramming is one of the significant characteristics of hepatocellular carcinoma (HCC). Cholesterol increases the risk of epithelial-mesenchymal transition (EMT) in cancer. Sterol O-acyltransferases 1 (SOAT1) maintains the cholesterol homeostasis. However, the exact mechanistic contribution of SOAT1 to EMT in HCC remains unclear. Here we demonstrated that SOAT1 positively related to poor prognosis of HCC, EMT markers and promoted cell migration and invasion in vitro, which was mediated by the increased cholesterol in plasmalemma and cholesterol esters accumulation. Furthermore, we reported that SOAT1 disrupted cholesterol metabolism homeostasis to accelerate tumorigenesis and development in HCC xenograft and NAFLD-HCC. Also, we detected that nootkatone, a sesquiterpene ketone, inhibited EMT by targeting SOAT1 in vitro and in vivo. Collectively, our finding indicated that SOAT1 promotes EMT and contributes to hepatocarcinogenesis by increasing cholesterol esterification, which is suppressed efficiently by nootkatone. This study demonstrated that SOAT1 is a potential biomarker and therapeutic target in NAFLD-HCC and SOAT1-targeting inhibitors are expected to be the potential new therapeutic treatment for HCC.

Improving product quality and productivity of an antibody-based biotherapeutic using inverted frustoconical shaking bioreactors.

The Chinese hamster ovarian (CHO) cells serve as a common choice in biopharmaceutical production, traditionally cultivated in stirred tank bioreactors (STRs). Nevertheless, the pursuit of improved protein quality and production output for commercial purposes demand exploration into new bioreactor types. In this context, inverted frustoconical shaking bioreactors (IFSB) present unique physical properties distinct from STRs. This study aims to compare the production processes of an antibody-based biotherapeutic in both bioreactor types, to enhance production flexibility. The findings indicate that, when compared to STRs, IFSB demonstrates the capability to produce an antibody-based biotherapeutic with either comparable or enhanced bioprocess performance and product quality. IFSB reduces shear damage to cells, enhances viable cell density (VCD), and improves cell state at a 5-L scale. Consequently, this leads to increased protein expression (3.70 g/L vs 2.56 g/L) and improved protein quality, as evidenced by a reduction in acidic variants from 27.0% to 21.5%. Scaling up the culture utilizing the Froude constant and superficial gas velocity ensures stable operation, effective mixing, and gas transfer. The IFSB maintains a high VCD and cell viability at both 50-L and 500-L scales. Product expression levels range from 3.0 to 3.6 g/L, accompanied by an improved acidic variants attribute of 20.6%-22.7%. The IFSB exhibits superior productivity and product quality, underscoring its potential for incorporation into the manufacturing process for antibody-based biotherapeutics. These results establish the foundation for IFSB to become a viable option in producing antibody-based biotherapeutics for clinical and manufacturing applications.

Stable-Isotope N-Me Aziridination Enables Accurate Quantitative C═C Isomeric Lipidomics.

Accurate lipid quantification is essential to revealing their roles in physiological and pathological processes. However, difficulties in the structural resolution of lipid isomers hinder their further accurate quantification. To address this challenge, we developed a novel stable-isotope N-Me aziridination strategy that enables simultaneous qualification and quantification of unsaturated lipid isomers. The one-step introduction of the 1-methylaziridine structure not only serves as an activating group for the C═C bond to facilitate positional identification but also as an isotopic inserter to achieve accurate relative quantification. The high performance of this reaction for the identification of unsaturated lipids was verified by large-scale resolution of the C═C positions of 468 lipids in serum. More importantly, by using this bifunctional duplex labeling method, various unsaturated lipids such as fatty acids, phospholipids, glycerides, and cholesterol ester were accurately and individually quantified at the C═C bond isomeric level during the mouse brain ischemia. This study provides a new approach to quantitative structural lipidomics.

Highly drug/target-tolerant neutralizing antibody (NAb) assay development through target-based drug depletion and drug-based NAb extraction for an anti-EGFR therapeutic monoclonal antibody.

The reduction of immunogenicity is fundamental for the development of biobetter Erbitux, given that the development of an immune response reduces treatment efficacy and may lead to potential side effects. One of the requirements for the clinical research of a Erbitux biobetter candidate (CMAB009) is to develop a neutralizing antibody (NAb) assay, and sufficient drug and target tolerance for the assay is necessary. Here, we describe the development of a competitive ligand binding (CLB) assay for CMAB009 with high drug and target tolerance through target-based drug depletion and drug-based NAb extraction, the integrated experimental strategy was implemented to simultaneously mitigate drug interference and enhance target tolerance. Following troubleshooting and optimization, the NAb assay was validated for clinical sample analysis with the sensitivity of 92 ng/mL, drug tolerance of 70 µg/mL and target tolerance of 798 ng/mL. The innovative drug depletion and NAb extraction achieved though the combination of drug and target beads would enable the development of reliable NAb assays for many other therapeutics that overcome drug and its target interference for more precise and sensitive NAb assessment.

Efficient treatment of colon cancer with codelivery of TRAIL and imatinib by liposomes.

To solve the problem of resistance of tumor cells to TRAIL and the inevitable side effects of imatinib during treatment, we successfully prepared a kind of multifunctional liposome that encapsulated imatinib in its internal water phase and inserted TRAIL on its membrane in this study, which named ITLPs. The liposomes appeared uniform spherical and the particle size was approximately 150 nm. ITLPs showed high accumulation in TRAIL-resistance cells and HT-29 tumor-bearing mice model. In vitro cytotoxicity assay results showed that the killing activity of HT-29 cells treated with ITLPs increased by 50% and confirmed that this killing activity was mediated by the apoptosis pathway. Through mechanism studies, it was found that ITLPs arrested up to 32.3% of cells in phase M to exert anti-tumor effects. In vivo anti-tumor study showed that ITLPs achieved 61.8% tumor suppression and little toxicity in the HT-29 tumor-bearing mice model. Overall results demonstrated that codelivery of imatinib and TRAIL via liposomes may be a prospective method in the treatment of the TRAIL-resistance tumor.

Effect of cesarean section on the risk of autism spectrum disorders/attention deficit hyperactivity disorder in offspring: a meta-analysis.

PURPOSE: This study was conducted to investigate the relationship between cesarean section (CS) offspring and autism spectrum disorders (ASD)/attention deficit hyperactivity disorder (ADHD). METHODS: Searching of the databases (PubMed, Web of Science, Embase, and Cochrane Library) for studies on the relationship between mode of delivery and ASD/ADHD until August 2022. The primary outcome was the incidence of ASD/ADHD in the offspring. RESULTS: This meta-analysis included 35 studies (12 cohort studies and 23 case-control studies). Statistical results showed a higher risk of ASD (odds ratio (OR) = 1.25, P < 0.001) and ADHD (OR = 1.11, P < 0.001) in CS offspring compared to the VD group. Partial subgroup analysis showed no difference in ASD risk between CS and VD offspring in sibling-matched groups (OR = 0.98, P = 0.625). The risk of ASD was higher in females (OR = 1.66, P = 0.003) than in males (OR = 1.17, P = 0.004) in the CS offspring compared with the VD group. There was no difference in the risk of ASD between CS under regional anesthesia group and VD group (OR = 1.07, P = 0.173). However, the risk of ASD was higher in the CS offspring under general anesthesia than in the VD offspring (OR = 1.62, P < 0.001). CS offspring developed autism (OR = 1.38, P = 0.011) and pervasive developmental disorder-not otherwise specified (OR = 1.46, P = 0.004) had a higher risk than VD offspring, but there was no difference in Asperger syndrome (OR = 1.19, P = 0.115). Offspring born via CS had a higher incidence of ADHD in different subgroup analyses (sibling-matched, type of CS, and study design). CONCLUSIONS: In this meta-analysis, CS was a risk factor for ASD/ADHD in offspring compared with VD.

pH Sensitive Quercetin Nanoparticles Ameliorate DSS-Induced Colitis in Mice by Colon-Specific Delivery.

SCOPE: Ulcerative colitis (UC) is a classic inflammatory bowel disease (IBD) that represents a serious threat to human health. As a natural flavonoid with multiple biological activities, quercetin (QCT) suffers from low bioavailability through limitations in chemical stability. Here, the study investigates the regulatory effects of quercetin nanoparticles (QCT NPs) on dextran sulfate sodium (DSS) induced colitis mice. METHODS AND RESULTS: Chitosan is modified to obtain N-succinyl chitosan (NSC) with superior water solubility. Nanoparticles composed of sodium alginate (SA) and NSC can encapsulate QCT after cross-linking, forming QCT NPs. In vitro drug release assays demonstrate the pH sensitivity of QCT NPs. Compared with free quercetin, QCT NPs have better therapeutic efficacy in modulating gut microbiota and its metabolites short chain fatty acid (SCFAs) to relieve DSS-induced colitis in mice, thereby alleviating colon inflammatory infiltration, increasing goblet cells density and mucus protein, ameliorating TNF-α, IL-1ß, IL-6, IL-10, and Myeloperoxidase (MPO) levels, and recovering intestinal barrier integrity. CONCLUSION: pH sensitive QCT nanoparticles can reduce inflammatory reaction, improve gut microbiota, and repair intestinal barrier by targeting colon, thus improving DSS induced colitis in mice, providing reference for the treatment of colitis.

Real driving environment EEG-based detection of driving fatigue using the wavelet scattering network.

BACKGROUND: Driving fatigue is one of the main factors leading to traffic accidents. So, it is necessary to detect driver fatigue accurately and quickly. NEW METHOD: To precisely detect driving fatigue in a real driving environment, this paper adopts a classification method for driving fatigue based on the wavelet scattering network (WSN). Firstly, electroencephalogram (EEG) signals of 12 subjects in the real driving environment are collected and categorized into two states: fatigue and awake. Secondly, the WSN algorithm extracts wavelet scattering coefficients of EEG signals, and these coefficients are used as input in support vector machine (SVM) as feature vectors for classification. RESULTS: The results showed that the average classification accuracy of 12 subjects reached 99.33%; the average precision rate reached 99.28%; the average recall rate reached 98.27%; the average F1 score reached 98.74%; and the average classification accuracy of the public data set SEED-VIG reached 99.39%. The average precision, recall rate and F1 score reached 99.27%, 98.41% and 98.83% respectively. COMPARISON WITH EXISTING METHODS: In addition, the WSN algorithm is compared with traditional convolutional neural network (CNN), Sparse-deep belief networks (SDBN), Spatio-temporal convolutional neural networks (STCNN), Long short-term memory (LSTM), and other methods, and it is found that WSN has higher classification accuracy. CONCLUSION: Furthermore, this method has good versatility, providing excellent recognition effect on small sample data sets, and fast running time, making it convenient for real-time online monitoring of driver fatigue. Therefore, the WSN algorithm is promising in efficiently detecting driving fatigue state of drivers in real environments, contributing to improved traffic safety.

Motor intent recognition of multi-feature fusion EEG signals by UMAP algorithm.

The key to the analysis of electroencephalogram (EEG) signals lies in the extraction of effective features from the raw EEG signals, which can then be utilized to augment the classification accuracy of motor imagery (MI) applications in brain-computer interface (BCI). It can be argued that the utilization of features from multiple domains can be a more effective approach to feature extraction for MI pattern classification, as it can provide a more comprehensive set of information that the traditional single feature extraction method may not be able to capture. In this paper, a multi-feature fusion algorithm based on uniform manifold approximate and projection (UMAP) is proposed for motor imagery EEG signals. The brain functional network and common spatial pattern (CSP) are initially extracted as features. Subsequently, UMAP is utilized to fuse the extracted multi-domain features to generate low-dimensional features with improved discriminative capability. Finally, the k-nearest neighbor (KNN) classifier is applied in a lower dimensional space. The proposed method is evaluated using left-right hand EEG signals, and achieved the average accuracy of over 92%. The results indicate that, compared with single-domain-based feature extraction methods, multi-feature fusion EEG signal classification based on the UMAP algorithm yields superior classification and visualization performance. Feature extraction and fusion based on UMAP algorithm of left-right hand motor imagery.

Codelivery of TRAIL and Mitomycin C via Liposomes Shows Improved Antitumor Effect on TRAIL-Resistant Tumors.

Although tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) constitutes a promising antitumor drug, tumor resistance to TRAIL has become a major obstacle in its clinical application. Mitomycin C (MMC) is an effective TRAIL-resistant tumor sensitizer, which indicates a potential utility of combination therapy. However, the efficacy of this combination therapy is limited owing to its short half-life and the cumulative toxicity of MMC. To address these issues, we successfully developed a multifunctional liposome (MTLPs) with human TRAIL protein on the surface and MMC encapsulated in the internal aqueous phase to codeliver TRAIL and MMC. MTLPs are uniform spherical particles that exhibit efficient cellular uptake by HT-29 TRAIL-resistant tumor cells, thereby inducing a stronger killing effect compared with control groups. In vivo assays revealed that MTLPs efficiently accumulated in tumors and safely achieved 97.8% tumor suppression via the synergistic effect of TRAIL and MMC in an HT-29 tumor xenograft model while ensuring biosafety. These results suggest that the liposomal codelivery of TRAIL and MMC provides a novel approach to overcome TRAIL-resistant tumors.

Lipidomic Characterization of Oocytes at Single-Cell Level Using Nanoflow Chromatography-Trapped Ion Mobility Spectrometry-Mass Spectrometry.

Mass spectrometry (MS)-based lipidomic has become a powerful tool for studying lipids in biological systems. However, lipidome analysis at the single-cell level remains a challenge. Here, we report a highly sensitive lipidomic workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry (TIMS)-MS. This approach enables the high-coverage identification of lipidome landscape at the single-oocyte level. By using the proposed method, comprehensive lipid changes in porcine oocytes during their maturation were revealed. The results provide valuable insights into the structural changes of lipid molecules during porcine oocyte maturation, highlighting the significance of sphingolipids and glycerophospholipids. This study offers a new approach to the single-cell lipidomic.

Liposome-Based Co-Immunotherapy with TLR Agonist and CD47-SIRPα Checkpoint Blockade for Efficient Treatment of Colon Cancer.

Antitumor immunity is an essential component of cancer therapy and is primarily mediated by the innate immune response, which plays a critical role in initiating and shaping the adaptive immune response. Emerging evidence has identified innate immune checkpoints and pattern recognition receptors, such as CD47 and Toll-like receptor 7 (TLR7), as promising therapeutic targets for cancer treatment. Based on the fusion protein Fc-CV1, which comprises a high-affinity SIRPα variant (CV1), and the Fc fragment of the human IgG1 antibody, we exploited a preparation which coupled Fc-CV1 to imiquimod (TLR7 agonist)-loaded liposomes (CILPs) to actively target CT26. WT syngeneic colon tumor models. In vitro studies revealed that CILPs exhibited superior sustained release properties and cell uptake efficiency compared to free imiquimod. In vivo assays proved that CILPs exhibited more efficient accumulation in tumors, and a more significant tumor suppression effect than the control groups. This immunotherapy preparation possessed the advantages of low doses and low toxicity. These results demonstrated that a combination of immune checkpoint blockade (ICB) therapy and innate immunity agonists, such as the Fc-CV1 and imiquimod-loaded liposome preparation utilized in this study, could represent a highly effective strategy for tumor therapy.

Sea Cucumber Hydrolysate Alleviates Immunosuppression and Gut Microbiota Imbalance Induced by Cyclophosphamide in Balb/c Mice through the NF-κB Pathway.

This study aimed to investigate the effect of sea cucumber hydrolysate (SCH) on immunosuppressed mice induced by cyclophosphamide (Cy). Our findings demonstrated that SCH could increase the thymus index and spleen index, decrease the serum alanine transaminase (ALT) and aspartate aminotransferase (AST) levels, increase the serum IgG and small intestinal sIgA levels, reduce small intestinal and colon tissue damage, and activate the nuclear factor-κB (NF-κB) pathway by increasing TRAF6 and IRAK1 protein levels, as well as the phosphorylation levels of IκBα and p65, thereby enhancing immunity. In addition, SCH alleviated the imbalance of the gut microbiota by altering the composition of the gut microbiota in immunosuppressed mice. At the genus level, when compared with the model group, the relative abundance of Dubosiella, Lachnospiraceae, and Ligilactobacillus increased, while that of Lactobacillus, Bacteroides, and Turicibacter decreased in the SCH groups. Moreover, 26 potential bioactive peptides were identified by oligopeptide sequencing and bioactivity prediction. This study's findings thus provide an experimental basis for further development of SCH as a nutritional supplement to alleviate immunosuppression induced by Cy as well as provides a new idea for alleviating intestinal damage induced by Cy.

Efficacy of kangaroo mother care combined with neonatal phototherapy in newborns with non-pathological jaundice: A meta-analysis.

Background: The kangaroo-mother care method (KMC) is a skin-to-skin contact-centered care approach with numerous benefits for neonates, but its impact on the treatment of jaundiced neonates is unknown. This study aimed to investigate the efficacy of KMC combined with neonatal phototherapy (NNPT) in treating neonates with non-pathological jaundice. Methods: Relevant articles were searched in PubMed, Embase, Web of Science, and Cochrane Library databases from database establishment to April 2022. The outcomes included, without limitation, serum bilirubin levels, and duration of phototherapy. Results: This meta-analysis included five studies (4 randomized controlled trials and 1 observational study) involving four hundred eighty-two neonates with non-pathological jaundice. The results showed that the group receiving KMC combined with NNPT had lower serum bilirubin at 72 h after intervention [weighted mean difference (WMD) = -1.51, p = 0.03], shorter duration of phototherapy [standard mean difference (SMD) = -1.45, p < 0.001] and shorter duration of hospitalization (SMD = -1.32, p = 0.002) compared to NNPT group. There was no difference in peak bilirubin in both groups of neonates (WMD = -0.12, p = 0.62). Conclusions: KMC combined with NNPT helped to treat non-pathological jaundice in newborns compared to NNPT alone.

EEG-based driver states discrimination by noise fraction analysis and novel clustering algorithm.

Driver states are reported as one of the principal factors in driving safety. Distinguishing the driving driver state based on the artifact-free electroencephalogram (EEG) signal is an effective means, but redundant information and noise will inevitably reduce the signal-to-noise ratio of the EEG signal. This study proposes a method to automatically remove electrooculography (EOG) artifacts by noise fraction analysis. Specifically, multi-channel EEG recordings are collected after the driver experiences a long time driving and after a certain period of rest respectively. Noise fraction analysis is then applied to remove EOG artifacts by separating the multichannel EEG into components by optimizing the signal-to-noise quotient. The representation of data characteristics of the EEG after denoising is found in the Fisher ratio space. Additionally, a novel clustering algorithm is designed to identify denoising EEG by combining cluster ensemble and probability mixture model (CEPM). The EEG mapping plot is used to illustrate the effectiveness and efficiency of noise fraction analysis on the denoising of EEG signals. Adjusted rand index (ARI) and accuracy (ACC) are used to demonstrate clustering performance and precision. The results showed that the noise artifacts in the EEG were removed and the clustering accuracy of all participants was above 90%, resulting in a high driver fatigue recognition rate.

Association of cesarean section with risk of childhood leukemia: A meta-analysis from an observational study.

Recent studies suggest that children born via cesarean section (CS) are predisposed to immune-mediated diseases later in life. The association between CS and childhood leukemia was investigated in this meta-analysis of observational studies. Two researchers independently searched PubMed, Web of Science, Embase, and Cochrane Library for literature on the association between CS and childhood leukemia before February 2022. And pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated to determine the link between CS and childhood leukemia. The preliminary search resulted in 1321 articles and 16 articles were finally included after screening. The primary outcome was the risk of leukemia in children born via CS versus those born vaginally. The results revealed that having a CS was associated with an increased risk of childhood leukemia compared to having vaginal section (VS) (OR = 1.07, 95% CI: 1.02-1.13, p = 0.01), especially for acute lymphoblastic leukemia (ALL) (OR = 1.09, 95% CI: 1.03-1.16, p = 0.004). Children delivered via elective CS had a higher risk of ALL (OR = 1.18, 95% CI: 1.07-1.31, p = 0.001), but emergency CS did not. It is worth noting that neither emergency CS nor elective CS were found to be associated with acute myeloid leukemia. Compared to VS, CS increased the risk of leukemia in children, with elective CS significantly increasing ALL risk.