NEATmap: a high-efficiency deep learning approach for whole mouse brain neuronal activity trace mapping.

Quantitative analysis of activated neurons in mouse brains by a specific stimulation is usually a primary step to locate the responsive neurons throughout the brain. However, it is challenging to comprehensively and consistently analyze the neuronal activity trace in whole brains of a large cohort of mice from many terabytes of volumetric imaging data. Here, we introduce NEATmap, a deep learning-based high-efficiency, high-precision and user-friendly software for whole-brain neuronal activity trace mapping by automated segmentation and quantitative analysis of immunofluorescence labeled c-Fos+ neurons. We applied NEATmap to study the brain-wide differentiated neuronal activation in response to physical and psychological stressors in cohorts of mice.

Research on the impact mechanism of changes in the production of medical solid waste in China before and after COVID-19.

The changes of medical solid waste (MSW) output in recent years have had a significant impact on the spread of the virus. There is a high-risk transmission of MSW in various stages such as storage, transportation, and treatment during the COVID-19. To cope with the risks brought by the epidemic, normalized prevention consumes a large amount of protective clothing, medical masks, goggles, packaging bags, and other related medical supplies. There is a significant uncertainty in the amount of MSW output that poses a risk of COVID-19 infection in the event of an emergency, which increases the difficulty of collecting and handling epidemic prevention MSW. The analysis of MSW data from 2000 to 2022 found a stable growth trend before 2019. However, the MSW data was a sudden increase trend from 2020 to 2022, and the COVID-19 in China was characterized by an initial stage, an outbreak stage, and a stable growth stage. The range of MSW output during the epidemic was (1.19-1.75) × 106 t a-1. The amount of MSW was approximately 1.19 × 106 t a-1 during the normalized epidemic period, and its treatment cost was as high as 3.57 × 109 yuan (RMB)·a-1. The distribution of MSW output was uneven due to factors such as climate conditions, population data, and local economy. This study has important reference value for epidemic medical material reserves and MSW treatment.

The Effect of Low HBV-DNA Viral Load on Recurrence in Hepatocellular Carcinoma Patients Who Underwent Primary Locoregional Treatment and the Development of a Nomogram Prediction Model.

(1) Background: HBV-DNA is an essential clinical indicator of primary hepatocellular carcinoma (HCC) prognosis. Our study aimed to investigate the prognostic implication of a low load of HBV-DNA in HCC patients who underwent local treatment. Additionally, we developed and validated a nomogram to predict the recurrence of patients with low (20-100 IU/mL) viral loads (L-VL). (2) Methods: A total of 475 HBV-HCC patients were enrolled, including 403 L-VL patients and 72 patients with very low (<20 IU/mL) viral loads (VL-VL). L-VL HCC patients were randomly divided into a training set (N = 282) and a validation set (N = 121) at a ratio of 7:3. Utilizing the Lasso-Cox regression analysis, we identified independent risk factors for constructing a nomogram. (3) Results: L-VL patients had significantly shorter RFS than VL-VL patients (38.2 m vs. 23.4 m, p = 0.024). The content of the nomogram included gender, BCLC stage, Glob, and MLR. The C-index (0.682 vs. 0.609); 1-, 3-, and 5-year AUCs (0.729, 0.784, and 0.783, vs. 0.631, 0.634, the 0.665); calibration curves; and decision curve analysis (DCA) curves of the training and validation cohorts proved the excellent predictive performance of the nomogram. There was a statistically significant difference in RFS between the low-, immediate-, and high-risk groups both in the training and validation cohorts (p < 0.001); (4) Conclusions: Patients with L-VL had a worse prognosis. The nomogram developed and validated in this study has the advantage of predicting patients with L-VL.

Osteo-immunomodulatory effects of macrophage-derived extracellular vesicles treated with biphasic calcium phosphate ceramics on bone regeneration.

Literature on osteoimmunology has demonstrated that macrophages have a great influence on biomaterial-induced bone formation. However, there are almost no reports clarifying the osteo-immunomodulatory capacity of macrophage-derived extracellular vesicles (EVs). This study comprehensively investigated the effects of EVs derived from macrophages treated with biphasic calcium phosphate (BCP) ceramics (BEVs) on vital events associated with BCP-induced bone formation such as immune response, angiogenesis, and osteogenesis. It was found that compared with EVs derived from macrophages alone (control, CEVs), BEVs preferentially promoted macrophage polarization towards a wound-healing M2 phenotype, enhanced migration, angiogenic differentiation, and tube formation of human umbilical vein endothelial cells, and induced osteogenic differentiation of mesenchymal stem cells. Analysis of 15 differentially expressed microRNAs (DEMs) related to immune, angiogenesis, and osteogenesis suggested that BEVs exhibited good immunomodulatory, pro-angiogenic, and pro-osteogenic abilities, which might be attributed to their specific miRNA cargos. These findings not only deepen our understanding of biomaterial-mediated osteoinduction, but also suggest that EVs derived from biomaterial-treated macrophages hold great promise as therapeutic agents with desired immunomodulatory capacity for bone regeneration.

IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data.

Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.

High-Voltage Cable Buffer Layer Ablation Fault Identification Based on Artificial Intelligence and Frequency Domain Impedance Spectroscopy.

In recent years, the occurrence of high-voltage cable buffer layer ablation faults has become frequent, posing a serious threat to the safe and stable operation of cables. Failure to promptly detect and address such faults may lead to cable breakdowns, impacting the normal operation of the power system. To overcome the limitations of existing methods for identifying buffer layer ablation faults in high-voltage cables, a method for identifying buffer layer ablation faults based on frequency domain impedance spectroscopy and artificial intelligence is proposed. Firstly, based on the cable distributed parameter model and frequency domain impedance spectroscopy, a mathematical model of the input impedance of a cable containing buffer layer ablation faults is derived. Through a simulation, the input impedance spectroscopy at the first end of the cables under normal conditions, buffer layer ablation, local aging, and inductive faults is performed, enabling the identification of inductive and capacitive faults through a comparative analysis. Secondly, the frequency domain amplitude spectroscopy of the buffer layer ablation and local aging faults are used as datasets and are input into a neural network model for training and validation to identify buffer layer ablation and local aging faults. Finally, using multiple evaluation metrics to assess the neural network model validates the superiority of the MLP neural network in cable fault identification models and experimentally confirms the effectiveness of the proposed method.

Sjögren's syndrome and Parkinson's Disease: A bidirectional two-sample Mendelian randomization study.

BACKGROUND: Previous observational studies have reported an association between Sjögren's syndrome (SS) and an increased risk of Parkinson's Disease (PD). However, the causal relationship between these conditions remains unclear. The objective of this study was to investigate the causal impact of SS on the risk of developing PD, utilizing the Mendelian randomization (MR) approach. METHODS: We conducted a bidirectional MR analysis using publicly available genome-wide association studies (GWAS) data. The primary analysis utilized the inverse-variance weighted (IVW) method. Complementary methods, such as MR-Egger regression, weighted mode, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were utilized to identify and correct for the presence of horizontal pleiotropy. RESULTS: The IVW MR analysis revealed no significant association between SS and PD (IVW: OR = 1.00, 95% CI = 0.94-1.07, P = 0.95). Likewise, the reverse MR analysis did not identify any significant causal relationship between PD and SS (IVW: OR = 0.98, 95% CI = 0.85-1.12, P = 0.73). The results from MR-Egger regression, weighted median, and weighted mode approaches were consistent with the IVW method. Sensitivity analyses suggested that horizontal pleiotropy is unlikely to introduce bias to the causal estimates. CONCLUSION: This study does not provide evidence to support the assertion that SS has a conclusive impact on the risk of PD, which contradicts numerous existing observational reports. Further investigation is necessary to determine the possible mechanisms behind the associations observed in these observational studies.

A Comprehensive Evaluation Algorithm of Multi-Point Relay Based on Link-State Awareness for UANETs.

The Multi-Point Relay (MPR) is one of the core technologies for Optimizing Link State Routing (OLSR) protocols, offering significant advantages in reducing network overhead, enhancing throughput, maintaining network scalability, and adaptability. However, due to the restriction that only MPR nodes can forward control messages in the network, the current evaluation criteria for selecting MPR nodes are relatively limited, making it challenging to flexibly choose MPR nodes based on current link states in dynamic networks. Therefore, the selection of MPR nodes is crucial in dynamic networks. To address issues such as unstable links, poor transmission accuracy, and lack of real-time performance caused by mobility in dynamic networks, we propose a comprehensive evaluation algorithm of MPR based on link-state awareness. This algorithm defines five state evaluation parameters from the perspectives of node mobility and load. Subsequently, we use the entropy weight method to determine weight coefficients and employing the method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for comprehensive evaluation to select MPR nodes. Finally, the Comprehensive Evaluation based on Link-state awareness of OLSR (CEL-OLSR) protocol is proposed, and simulated experiments are conducted using NS-3. The results indicate that, compared to PM-OLSR, ML-OLSR, LD-OLSR, and OLSR, CEL-OLSR significantly improves network performance in terms of packet delivery rate, average end-to-end delay, network throughput, and control overhead.

Feasibility of a low-cost magnet tracking device in confirming nasogastric tube placement at point of care, a clinical trial.

An affordable and reliable way of confirming the placement of nasogastric tube (NGT) at point-of-care is an unmet need. Using a novel algorithm and few sensors, we developed a low-cost magnet tracking device and showed its potential to localize the NGT preclinically. Here, we embark on a first-in-human trial. Six male and 4 female patients with NGT from the general ward of an urban hospital were recruited. We used the device to localize the NGT and compared that against chest X-ray (CXR). In 5 patients, with the sensors placed on the sternal angle, the trajectory of the NGT was reproduced by the tracking device. The tracked location of the NGT deviated from CXR by 0.55 to 1.63 cm, and a downward tracking range of 17 to 22 cm from the sternal angle was achieved. Placing the sensors on the xiphisternum, however, resulted in overt discordance between the device's localization and that on CXR. Short distance between the sternal angle and the xiphisternum, and lower body weight were observed in patients in whom tracking was feasible. Tracking was quick and well tolerated. No adverse event occurred. This device feasibly localized the NGT in 50% of patients when appropriately placed. Further refinement is anticipated.ClinicalTrials.gov identifier: NCT05204901.

eEF1A2 promotes PTEN-GSK3ß-SCF complex-dependent degradation of Aurora kinase A and is inactivated in breast cancer.

The translation elongation factor eEF1A promotes protein synthesis. Its methylation by METTL13 increases its activity, supporting tumor growth. However, in some cancers, a high abundance of eEF1A isoforms is associated with a good prognosis. Here, we found that eEF1A2 exhibited oncogenic or tumor-suppressor functions depending on its interaction with METTL13 or the phosphatase PTEN, respectively. METTL13 and PTEN competed for interaction with eEF1A2 in the same structural domain. PTEN-bound eEF1A2 promoted the ubiquitination and degradation of the mitosis-promoting Aurora kinase A in the S and G2 phases of the cell cycle. eEF1A2 bridged the interactions between the SKP1-CUL1-FBXW7 (SCF) ubiquitin ligase complex, the kinase GSK3ß, and Aurora-A, thereby facilitating the phosphorylation of Aurora-A in a degron site that was recognized by FBXW7. Genetic ablation of Eef1a2 or Pten in mice resulted in a greater abundance of Aurora-A and increased cell cycling in mammary tumors, which was corroborated in breast cancer tissues from patients. Reactivating this pathway using fimepinostat, which relieves inhibitory signaling directed at PTEN and increases FBXW7 expression, combined with inhibiting Aurora-A with alisertib, suppressed breast cancer cell proliferation in culture and tumor growth in vivo. The findings demonstrate a therapeutically exploitable, tumor-suppressive role for eEF1A2 in breast cancer.

The antioxidant activity of polysaccharides from Armillaria gallica.

The purpose of this study was to investigate the antioxidant activity of Armillaria gallica polysaccharides. It explored whether Armillaria gallica polysaccharides (AgP) could prevent HepG2 cells from H2O2-induced oxidative damage. The results demonstrated that HepG2 cells were significantly protected by AgP, and efficiently suppressed the production of reactive oxygen species (ROS) in HepG2 cells. Additionally, AgP significantly decreased the abnormal leakage of alanine aminotransferase (ALT) and lactate dehydrogenase (LDH) caused by H2O2, protecting cell membrane integrity. It was discovered that AgP was also found to regulate the activities of antioxidant enzymes, superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-PX), while reducing malondialdehyde (MDA), thus protecting cells from oxidative damage. According to the flow cytometry analysis and measurement of caspase-3, caspase-8, and caspase-9 activities, AgP could modulate apoptosis-related proteins and attenuate ROS-mediated cell apoptosis.

TIM22 and TIM29 inhibit HBV replication by up-regulating SRSF1 expression.

Hepatitis B virus (HBV) infection is a serious global health problem. After the viruses infect the human body, the host can respond to the virus infection by coordinating various cellular responses, in which mitochondria play an important role. Evidence has shown that mitochondrial proteins are involved in host antiviral responses. In this study, we found that the overexpression of TIM22 and TIM29, the members of the inner membrane translocase TIM22 complex, significantly reduced the level of intracellular HBV DNA and RNA and secreted HBV surface antigens and E antigen. The effects of TIM22 and TIM29 on HBV replication and transcription is attributed to the reduction of core promoter activity mediated by the increased expression of SRSF1 which acts as a suppressor of HBV replication. This study provides new evidence for the critical role of mitochondria in the resistance of HBV infection and new targets for the development of treatment against HBV infection.

Flucloxacillin worsens while imipenem-cilastatin protects against vancomycin-induced kidney injury in a translational rat model.

BACKGROUND AND PURPOSE: Vancomycin is one of the most common clinical antibiotics, yet acute kidney injury is a major limiting factor. Common combinations of antibiotics with vancomycin have been reported to worsen and improve vancomycin-induced kidney injury. We aimed to study the impact of flucloxacillin and imipenem-cilastatin on kidney injury when combined with vancomycin in our translational rat model. EXPERIMENTAL APPROACH: Male Sprague-Dawley rats received allometrically scaled (1) vancomycin, (2) flucloxacillin, (3) vancomycin + flucloxacillin, (4) vancomycin + imipenem-cilastatin or (5) saline for 4 days. Kidney injury was evaluated via drug accumulation and urinary biomarkers including urinary output, kidney injury molecule-1 (KIM-1), clusterin and osteopontin. Relationships between vancomycin accumulation in the kidney and urinary kidney injury biomarkers were explored. KEY RESULTS: Urinary output increased every study day for vancomycin + flucloxacillin, but after the first dose only in the vancomycin group. In the vancomycin + flucloxacillin group, urinary KIM-1 increased on all days compared with vancomycin. In the vancomycin + imipenem-cilastatin group, urinary KIM-1 was decreased on Days 1 and 2 compared with vancomycin. Similar trends were observed for clusterin. More vancomycin accumulated in the kidney with vancomycin + flucloxacillin compared with vancomycin and vancomycin + imipenem-cilastatin. The accumulation of vancomycin in the kidney tissue correlated with increasing urinary KIM-1. CONCLUSIONS AND IMPLICATIONS: Vancomycin + flucloxacillin caused more kidney injury compared with vancomycin alone and vancomycin + imipenem-cilastatin in a translational rat model. The combination of vancomycin + imipenem-cilastatin was nephroprotective.

Tick salivary protein Cystatin: structure, anti-inflammation and molecular mechanism.

Ticks are blood-sucking ectoparasites that secrete immunomodulatory substances in saliva to hosts during engorging. Cystatins, a tick salivary protein and natural inhibitor of Cathepsins, are attracting growing interest globally because of the immunosuppressive activities and the feasibility as an antigen for developing anti-tick vaccines. This review outlines the classification and the structure of tick Cystatins, and focuses on the anti-inflammatory effects and molecular mechanisms. Tick Cystatins can be divided into four families based on structures and cystatin 1 and cystatin 2 are the most abundant. They are injected into hosts during blood feeding and effectively mitigate the host inflammatory response. Mechanically, tick Cystatins exert anti-inflammatory properties through the inhibition of TLR-NF-κb, JAK-STAT and p38 MAPK signaling pathways. Further investigations are crucial to confirm the reduction of inflammation in other cell types like neutrophils and mast cells, and fully elucidate the underlying mechanism (like the structural mechanism) to make Cystatin a potential candidate for the development of novel anti-inflammation agents.

Integrative lncRNA, circRNA, and mRNA analysis reveals expression profiles of six forensic body fluids/tissue.

RNAs have attracted much attention in forensic body fluid/tissue identification (BFID) due to their tissue-specific expression characteristics. Among RNAs, long RNAs (e.g., mRNA) have a higher probability of containing more polymorphic sites that can be used to assign the specific donor of the body fluid/tissue. However, few studies have characterized their overall profiles in forensic science. In this study, we sequenced the transcriptomes of 30 samples from venous blood, menstrual blood, semen, saliva, vaginal secretion, and skin tissue, obtaining a comprehensive picture of mRNA, lncRNA, and circRNA profiles. A total of 90,305 mRNAs, 102,906 lncRNAs (including 19,549 novel lncRNAs), and 40,204 circRNAs were detected. RNA type distribution, length distribution, and expression distribution were presented according to their annotation and expression level, and many novel body fluid/tissue-specific RNA markers were identified. Furthermore, the cognate relations among the three RNAs were analyzed according to gene annotations. Finally, SNPs and InDels from RNA transcripts were genotyped, and 21,611 multi-SNP and 4,471 multi-InDel transcriptomic microhaplotypes (tMHs) were identified. These results provide a comprehensive understanding of transcriptome profiles, which could provide new avenues for tracing the origin of the body fluid/tissue and identifying an individual.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study.

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

Phylogeny and molecular evolution of the first local monkeypox virus cluster in Guangdong Province, China.

The first local mpox outbreak in Guangdong Province, China occurred in June 2023. However, epidemiological data have failed to quickly identify the source and transmission of the outbreak. Here, phylogeny and molecular evolution of 10 monkeypox virus (MPXV) genome sequences from the Guangdong outbreak were characterized, revealing local silent transmissions that may have occurred in Guangdong whose mpox outbreaks suggested a molecular epidemiological correlation with Portugal and several regions of China during the same period. The lineage IIb C.1, which includes all 10 MPXV from Guangdong, shows consistent temporal continuity in both phylogenetic characteristics and unique molecular evolutionary mutation spectrum, reflected in the continuous increase of single nucleotide polymorphisms (SNPs) and shared mutations over time. Compared with the Japan MPXV, the Guangdong MPXV showed higher genomic nucleotide differences and separated 14 shared mutations from the B.1 lineage, comprising 6 non-synonymous mutations in genes linked to host regulation, virus infection, and virus life cycle. The unique mutation spectrum with temporal continuity in IIb C.1, related to apolipoprotein B mRNA-editing catalytic polypeptide-like 3, promotes rapid viral evolution and diversification. The findings contribute to understanding the ongoing mpox outbreak in China and offer insights for developing joint prevention and control strategies.

Ecological factors associated with child sexual abuse among 15- to 17-year-old adolescents in mainland China: implications for intervention.

Background: Child sexual abuse is a major public health problem with adverse consequences for victims' physical, mental, and reproductive health. This cross-sectional study aimed to determine the prevalence of child sexual abuse and its associated factors among 15- to 17-year-old adolescents in mainland China. Methods: From September 8, 2019 to January 17, 2020, a total of 48,660 participants were recruited by 58 colleges and universities across the whole country to complete the self-administered, structured, online questionnaire. This analysis was restricted to 3,215 adolescents aged between 15 and 17 years in mainland China. Chi-square tests and multivariate Logistic regression analyses were performed to identify individual, relationship, and community factors associated with child sexual abuse. Results: The overall prevalence of child sexual abuse was 12.0%. More specifically, 13.0% of girls and 10.6% of boys reported that they were sexually abused prior to 18 years of age. At the individual level, being female, sexual minority identity, younger age, and higher levels of knowledge, skills and self-efficacy regarding condom use were significantly related to increased odds of reporting sexual abuse. At the relationship and community level, adolescents from disrupted families and those entering into a marriage, having casual sexual partners, and having first intercourse at a younger age were more likely to report sexual abuse. On the contrary, those who had never discussed sex-related topics with their family members at home and were offered school-based sexuality education later (vs. earlier) were less likely to report sexual abuse. Conclusion: Multilevel prevention programs and strategies, including targeting adolescents with high-risk characteristics, educating young children and their parents about child sexual abuse prevention and optimizing the involvement of parents, school, community, society and government in comprehensive sexuality education, should be taken to reduce child sexual abuse among 15- to 17-year-old adolescents.

Polyphyllin VII induces CTC anoikis to inhibit lung cancer metastasis through EGFR pathway regulation.

Circulating tumor cells (CTCs) are cells that detach from the primary tumor and enter the bloodstream, playing a crucial role in the metastasis of lung cancer. Unfortunately, there is currently a lack of drugs specifically designed to target CTCs and prevent tumor metastasis. In this study, we present evidence that polyphyllin VII, a potent anticancer compound, effectively inhibits the metastasis of lung cancer by inducing a process called anoikis in CTCs. We observed that polyphyllin VII had significant cytotoxicity and inhibited colony formation, migration, and invasion in both our newly established cell line CTC-TJH-01 and a commercial lung cancer cell line H1975. Furthermore, we found that polyphyllin VII induced anoikis and downregulated the TrkB and EGFR-MEK/ERK signaling pathways. Moreover, activation of TrkB protein did not reverse the inhibitory effect of polyphyllin VII on CTCs, while upregulation of EGFR protein effectively reversed it. Furthermore, our immunodeficient mouse models recapitulated that polyphyllin VII inhibited lung metastasis, which was associated with downregulation of the EGFR protein, and reduced the number of CTCs disseminated into the lungs by inducing anoikis. Together, these results suggest that polyphyllin VII may be a promising compound for the treatment of lung cancer metastasis by targeting CTCs.