Risk prediction and analysis of gallbladder polyps with deep neural network.

The aim of this study is to analyze the risk factors associated with the development of adenomatous and malignant polyps in the gallbladder. Adenomatous polyps of the gallbladder are considered precancerous and have a high likelihood of progressing into malignancy. Preoperatively, distinguishing between benign gallbladder polyps, adenomatous polyps, and malignant polyps is challenging. Therefore, the objective is to develop a neural network model that utilizes these risk factors to accurately predict the nature of polyps. This predictive model can be employed to differentiate the nature of polyps before surgery, enhancing diagnostic accuracy. A retrospective study was done on patients who had cholecystectomy surgeries at the Department of Hepatobiliary Surgery of the Second People's Hospital of Shenzhen between January 2017 and December 2022. The patients' clinical characteristics, lab results, and ultrasonographic indices were examined. Using risk variables for the growth of adenomatous and malignant polyps in the gallbladder, a neural network model for predicting the kind of polyps will be created. A normalized confusion matrix, PR, and ROC curve were used to evaluate the performance of the model. In this comprehensive study, we meticulously analyzed a total of 287 cases of benign gallbladder polyps, 15 cases of adenomatous polyps, and 27 cases of malignant polyps. The data analysis revealed several significant findings. Specifically, hepatitis B core antibody (95% CI -0.237 to 0.061, p < 0.001), number of polyps (95% CI -0.214 to -0.052, p = 0.001), polyp size (95% CI 0.038 to 0.051, p < 0.001), wall thickness (95% CI 0.042 to 0.081, p < 0.001), and gallbladder size (95% CI 0.185 to 0.367, p < 0.001) emerged as independent predictors for gallbladder adenomatous polyps and malignant polyps. Based on these significant findings, we developed a predictive classification model for gallbladder polyps, represented as follows, Predictive classification model for GBPs = -0.149 * core antibody - 0.033 * number of polyps + 0.045 * polyp size + 0.061 * wall thickness + 0.276 * gallbladder size - 4.313. To assess the predictive efficiency of the model, we employed precision-recall (PR) and receiver operating characteristic (ROC) curves. The area under the curve (AUC) for the prediction model was 0.945 and 0.930, respectively, indicating excellent predictive capability. We determined that a polyp size of 10 mm served as the optimal cutoff value for diagnosing gallbladder adenoma, with a sensitivity of 81.5% and specificity of 60.0%. For the diagnosis of gallbladder cancer, the sensitivity and specificity were 81.5% and 92.5%, respectively. These findings highlight the potential of our predictive model and provide valuable insights into accurate diagnosis and risk assessment for gallbladder polyps. We identified several risk factors associated with the development of adenomatous and malignant polyps in the gallbladder, including hepatitis B core antibodies, polyp number, polyp size, wall thickness, and gallbladder size. To address the need for accurate prediction, we introduced a novel neural network learning algorithm. This algorithm utilizes the aforementioned risk factors to predict the nature of gallbladder polyps. By accurately identifying the nature of these polyps, our model can assist patients in making informed decisions regarding their treatment and management strategies. This innovative approach aims to improve patient outcomes and enhance the overall effectiveness of care.

Integrated analysis of the microbiome and transcriptome in stomach adenocarcinoma.

We aimed to characterize the stomach adenocarcinoma (STAD) microbiota and its clinical value using an integrated analysis of the microbiome and transcriptome. Microbiome and transcriptome data were downloaded from the Cancer Microbiome Atlas and the Cancer Genome Atlas databases. We identified nine differentially abundant microbial genera, including Helicobacter, Mycobacterium, and Streptococcus, which clustered patients into three subtypes with different survival rates. In total, 74 prognostic genes were screened from 925 feature genes of the subtypes, among which five genes were identified for prognostic model construction, including NTN5, MPV17L, MPLKIP, SIGLEC5, and SPAG16. The prognostic model could stratify patients into different risk groups. The high-risk group was associated with poor overall survival. A nomogram established using the prognostic risk score could accurately predict the 1, 3, and 5 year overall survival probabilities. The high-risk group had a higher proportion of histological grade 3 and recurrence samples. Immune infiltration analysis showed that samples in the high-risk group had a higher abundance of infiltrating neutrophils. The Notch signaling pathway activity showed a significant difference between the high- and low-risk groups. In conclusion, a prognostic model based on five feature genes of microbial subtypes could predict the overall survival for patients with STAD.

Prognostic value of autophagy-related genes based on single-cell RNA-sequencing in colorectal cancer.

Background: Colorectal cancer (CRC) is the second most common cancer in China. Autophagy plays an important role in the initiation and development of CRC. Here, we assessed the prognostic value and potential functions of autophagy-related genes (ARGs) using integrated analysis using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA). Methods: We analyzed GEO-scRNA-seq data from GEO using various single-cell technologies, including cell clustering, and identification of differentially expressed genes (DEGs) in different cell types. Additionally, we performed gene set variation analysis (GSVA). The differentially expressed ARGs among different cell types and those between CRC and normal tissues were identified using TCGA-RNA-seq data, and the hub ARGs were screened. Finally, a prognostic model based on the hub ARGs was constructed and validated, and patients with CRC in TCGA datasets were divided into high- and low-risk groups based on their risk-score, and immune cells infiltration and drug sensitivity analyses between the two groups were performed. Results: We obtained single-cell expression profiles of 16,270 cells, and clustered them into seven types of cells. GSVA revealed that the DEGs among the seven types of cells were enriched in many signaling pathways associated with cancer development. We screened 55 differentially expressed ARGs, and identified 11 hub ARGs. Our prognostic model revealed that the 11 hub ARGs including CTSB, ITGA6, and S100A8, had a good predictive ability. Moreover, the immune cell infiltrations in CRC tissues were different between the two groups, and the hub ARGs were significantly correlated with the enrichment of immune cell infiltration. The drug sensitivity analysis revealed that the patients in the two risk groups had difference in their response to anti-cancer drugs. Conclusion: We developed a novel prognostic 11-hub ARG risk model, and these hubs may act as potential therapeutic targets for CRC.

Construction of Dual-Shell Mo2C/C Microsphere towards Efficient Electromagnetic Wave Absorption.

Carbon-based carbides have attracted tremendous attention for electromagnetic energy attenuation due to their adjustable dielectric properties, oxidation resistance, and good chemical stability. Herein, we reasonably regulate the growth of dopamine hydrochloride on the surface of the Mo-glycerate (Mo-GL) microsphere and then transform the resultant Mo-polydopamine (Mo-PD) microsphere into a dual-shell Mo2C/C (DS-Mo2C/C) microsphere in a high-temperature pyrolysis process under an inert atmosphere. It is found that the pyrolysis temperature plays an important role in the graphitization degree of the carbon matrix and internal architecture. The fabrication of a dual-shell structure can be propitious to the optimization of impedance matching, and the introduction of Mo2C nanoparticles also prompts the accumulation of polarization loss. When the pyrolysis temperature reaches 800 °C, the optimized composite of DS-Mo2C/C-800 exhibits good EM absorption performance in the frequency range of 2.0-18.0 GHz. DS-Mo2C/C-800's qualified bandwidth can reach 4.4 GHz at a matching thickness of 1.5 mm, and the integrated qualified bandwidth (QBW) even exceeds 14.5 GHz with a thickness range of 1.5-5.0 mm. The positive effects of the dual-shell structure and Mo2C nanoparticles on EM energy attenuation may render the DS-Mo2C/C microsphere as a promising candidate for lightweight and broad bandwidth EM absorption materials in the future.

Eupalinolide A induces autophagy via the ROS/ERK signaling pathway in hepatocellular carcinoma cells in vitro and in vivo.

Hepatocellular carcinoma is the most common primary malignancy of the liver. The current systemic drugs used to treat hepatocellular carcinoma result in low overall survival time. It has therefore been suggested that new small­molecule drugs should be developed for treating hepatocellular carcinoma. Eupatorium lindleyanum DC. (EL) has been used to treat numerous diseases, particularly respiratory diseases; however, to the best of our knowledge, studies have not yet fully elucidated the effect of EL on hepatocellular carcinoma. In the present study, the effect of eupalinolide A (EA), one of the extracts of EL, was evaluated on tumor growth in a xenograft model of human hepatocellular carcinoma cells, and on the proliferation and migration of hepatocellular carcinoma cell lines. Cell cycle progression and the type of cell death were then evaluated using the Cell Counting Kit 8 assay, flow cytometry, electron microscopy and western blotting. EA significantly inhibited cell proliferation and migration by arresting the cell cycle at the G1 phase and inducing autophagy in hepatocellular carcinoma cells. EA­induced autophagy was mediated by reactive oxygen species (ROS) and ERK signaling activation. Specific inhibitors of ROS, autophagy and ERK inhibited EA­induced cell death and migration. In conclusion, the present study revealed that EA may inhibit the proliferation and migration of hepatocellular carcinoma cells, highlighting its potential as a promising antitumor compound for treating hepatocellular carcinoma.

Eupalinolide B inhibits hepatic carcinoma by inducing ferroptosis and ROS-ER-JNK pathway.

Primary hepatic carcinoma is a common malignant tumor. The classic molecular targeted drug sorafenib is costly and is only effective for some patients. Therefore, it is of great clinical significance to search for new molecular targeted drugs. Eupalinolide B (EB) from Eupatorium lindleyanum DC. is used to treat chronic tracheitis in clinical practice. However, the role of EB in hepatic carcinoma is unknown. In this study, we first measure the effect of EB on tumor growth in a xenograft model and PDX model. The cell proliferation and migration are also detected in human hepatocarcinoma cell lines (SMMC-7721 and HCCLM3). Then, we investigate cell cycle, cell apoptosis, cell necrosis, cell autophagy, and ferroptosis by flow cytometry, western blot analysis and electron microscopy. The results demonstrate that EB exerts anti-proliferative activity in hepatic carcinoma by blocking cell cycle arrest at S phase and inducing ferroptosis mediated by endoplasmic reticulum (ER) stress, as well as HO-1 activation. When HO-1 is inhibited, EB-induced cell death and ER protein expression are rescued. The migration-related mechanism consists of activation of the ROS-ER-JNK signaling pathway and is not connected to ferroptosis. In summary, we first discover that EB inhibits cell proliferation and migration in hepatic carcinoma, and thus EB is a promising anti-tumor compound that can be used for hepatic carcinoma.

MicroRNA-135a expression is upregulated in hepatocellular carcinoma and targets long non-coding RNA TONSL-AS1 to suppress cell proliferation.

Dysregulation of long non-coding RNAs (lncRNAs) results in development of human diseases, including hepatocellular carcinoma (HCC). lncRNA TONSL-AS1 has been reported to act as a tumor suppressor in gastric cancer. The present study aimed to investigate the role of TONSL-AS1 in hepatocellular carcinoma (HCC). Reverse transcription-quantitative PCR analysis was performed to detect the expression levels of TONSL-AS1 and microRNA (miRNA/miR)-135a in HCC tissues and paired adjacent normal tissues. A 5-year follow-up study was performed to determine the prognostic value of TONSL-AS1 in HCC. The association between miR-135a and TONSL-AS1 was assessed via overexpression experiments. The Cell Counting Kit-8 assay was performed to assess cell proliferation. The results demonstrated that TONSL-AS1 expression was downregulated in HCC tissues, which was associated with a lower survival rate in patients with HCC. TONSL-AS1 and miR-135a were predicted to interact with each other, whereby overexpression of miR-135a downregulated TONSL-AS1 expression. The results demonstrated that TONSL-AS1 and miR-135a were inversely correlated with each other. Notably, overexpression of TONSL-AS1 inhibited HCC cell proliferation, while overexpression of miR-135a promoted HCC cell proliferation and decreased the effect of overexpression of TONSL-AS1 on cell proliferation. Taken together, the results of the present study suggest that miR-135a expression is upregulated in HCC and targets lncRNA TONSL-AS1 to suppress cell proliferation.

Self-Ensembling Co-Training Framework for Semi-Supervised COVID-19 CT Segmentation.

The coronavirus disease 2019 (COVID-19) has become a severe worldwide health emergency and is spreading at a rapid rate. Segmentation of COVID lesions from computed tomography (CT) scans is of great importance for supervising disease progression and further clinical treatment. As labeling COVID-19 CT scans is labor-intensive and time-consuming, it is essential to develop a segmentation method based on limited labeled data to conduct this task. In this paper, we propose a self-ensembled co-training framework, which is trained by limited labeled data and large-scale unlabeled data, to automatically extract COVID lesions from CT scans. Specifically, to enrich the diversity of unsupervised information, we build a co-training framework consisting of two collaborative models, in which the two models teach each other during training by using their respective predicted pseudo-labels of unlabeled data. Moreover, to alleviate the adverse impacts of noisy pseudo-labels for each model, we propose a self-ensembling strategy to perform consistency regularization for the up-to-date predictions of unlabeled data, in which the predictions of unlabeled data are gradually ensembled via moving average at the end of every training epoch. We evaluate our framework on a COVID-19 dataset containing 103 CT scans. Experimental results show that our proposed method achieves better performance in the case of only 4 labeled CT scans compared to the state-of-the-art semi-supervised segmentation networks.

Analysis of Differentially Expressed Proteins Involved in miR-449a for Hepatocellular Carcinoma by iTRAQ Proteomics.

BACKGROUND: To investigate the relationship between down-regulation of miR-449a and prognosis of hepatocellular carcinoma (HCC) and to elucidate the potential target proteins of miR-449a. MATERIAL AND METHODS: The expression of miR-449a in 142 HCC tissues was detected by RT-PCR. The correlation between down-regulation of miR-449a and prognosis of HCC was statistically analyzed during clinical follow-up. The Bel-7042 HCC cell line in miR-449a-mimic and miR-449a-inhihbitor model was used, and the potential target protein of miR-449a was screened by isobaric tags for relative and absolute quantitation (iTRAQ) technology. RESULTS: miR-449a was significantly down-regulated in HCC tissues, which was significantly associated with post-operative metastasis (p < 0.0001) and recurrence (p < 0.0001). The median overall survival time in the low-expression group of miR-449a was significantly lower than that of the high-expression group (19 months vs. 37 months, p = 0.001). In addition, the tumor-free survival time of the low-expression group was significantly lower than that of the high-expression group (14 months vs. 24 months, p = 0.001). iTRAQ analysis screened out 137 differential proteins, among which 88 were up-regulated and 49 were down-regulated. GO clustering, KEGG pathway, and STRING analysis were performed, suggesting that these differential proteins have complicated functions, such as ATP binding, metal ion binding, RNA binding, human papillomavirus infection, and Epstein-Barr virus infection. CONCLUSIONS: miR-449a was negatively correlated with HCC prognosis. The differential proteins screened by iTRAQ can provide the basis for studying the target proteins regulated by miR-449a and understanding the pathogenesis of HCC.

hNTCP­expressing primary pig hepatocytes are a valuable tool for investigating hepatitis B virus infection and antiviral drugs.

Primary human hepatocytes (PHHs) are the 'gold standard' for investigating hepatitis B virus (HBV) infection and antiviral drugs. However, poor availability, variation between batches and ethical issues regarding PHHs limit their applications. The discovery of human sodium taurocholate co­transporting polypeptide (hNTCP) as a functional HBV receptor has enabled the development of a surrogate model to supplement the use of PHHs. In the present study, the evolutionary distance of seven species was assessed based on single­copy homologous genes. Based on the evolutionary distance and availability, PHHs and primary rabbit hepatocytes (PRHs) were isolated and infected with hNTCP­recombinant lentivirus, and susceptibility to HBV infection in the two cell types was tested and compared. In addition, HBV infection efficiency of hNTCP­expressing PPHs with pooled HBV­positive serum and purified particles was determined. The potential use of HBV­infected hNTCP­expressing PPHs for drug screening was assessed. The results demonstrated that pigs and rabbits are closer to humans in the divergence tree compared with mice and rats, indicating that pigs and rabbits were more likely to facilitate the HBV post­entry lifecycle. Following hNTCP complementation and HBV infection, PPHs and Huh7D human hepatocellular carcinoma cells, but not PRHs, exhibited increased hepatitis B surface antigen and hepatitis B e­antigen secretion, covalently closed circular DNA formation and infectious particle secretion. hNTCP­expressing PPHs were susceptible to infection with HBV particles purified from pooled HBV­positive sera, but were poisoned by raw HBV­positive sera. The use of HBV­infected hNTCP­expressing PPHs for viral entry inhibitor screening was revealed to be applicable and reproducible. In conclusion, hNTCP­expressing PPHs may be valuable tool for investigating HBV infection and antiviral drugs.

Diagnostic accuracy of serum dickkopf-1 protein in diagnosis hepatocellular carcinoma: An updated meta-analysis.

BACKGROUND: To verify the accuracy of serum dickkopf-1 protein (DKK-1) in the diagnosis of hepatocellular carcinoma (HCC) by an updated meta-analysis. METHODS: We searched potential eligible studies in PubMed and Embase before July 8, 2018. Sensitivity (SN), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), summary receiver operating characteristics curve (sROC), and diagnostic odds ratio (DOR) were pooled with their 95% confidence intervals CIs) using a bivariate random-effects model. RESULTS: A total of 8 articles contained 10 studies on diagnosis of HCC with DKK-1 alone,7 articles contained 9 studies on diagnosis of HCC with a-fetoprotein (AFP) alone and 5 articles contained 7 studies on diagnosis of HCC with DKK-1 + AFP were identified. The pooled SN, SP, PLR, NLR, and DOR of DKK-1 alone, AFP alone and DKK-1 + AFP were 0.72 (95% CI: 0.70-0.75), 0.62 (95% CI:0.59-0.64) and 0.80 (95% CI:0.78-0.83), 0.86 (95% CI: 0.84-0.87), 0.82 (95% CI:0.80-0.84) and 0.87 (95% CI: 0.85-0.88), 4.91 (95% CI: 2.73-8.83), 3.60 (95% CI:2.01-6.44) and 6.18 (95% CI: 4.68-8.16), 0.32 (95% CI: 0.22-0.47), 0.49 (95% CI:0.40-0.60) and 0.20 (95% CI: 0.15-0.26), and 17.21 (95% CI: 9.10-32.57), 7.45 (95% CI:3.69-15.01) and 31.39 (95% CI: 23.59-43.20), respectively. The area under the sROC was 0.88, 0.70, and 0.92 for the 3 diagnostic methods. CONCLUSIONS: Serum DKK-1 + AFP showed a high accuracy for diagnosis of HCC, and serum DKK-1 alone had moderate accuracy as compared to a previous meta-analysis, while AFP alone owned an unsatisfied diagnostic behavior for HCC. Due to the limitations of the current analysis, further well-designed studies are needed to confirm the diagnostic value of DKK-1 and DKK-1 + AFP in HCC diagnosis.

MicroRNA-449a suppresses hepatocellular carcinoma cell growth via G1 phase arrest and the HGF/MET c-Met pathway.

BACKGROUND: Accumulating evidence demonstrates that microRNAs (miRNAs) play essential roles in tumorigenesis and cancer progression of hepatocellular carcinoma (HCC). Average targets of a miRNA were more than 100. And one miRNA may act in tumor via regulating several targets. The present study aimed to explore more potential targets of miR-449a by proteomics technology and further uncover the role of miR-449a in HCC tumorigenesis. METHODS: Technologies such as iTRAQ-based quantitative proteomic were used to investigate the effect of miR-449a on HCC. The expression of c-Met and miR-449a was detected by qRT-PCR in HCC samples. Gain- and loss-of-function experiments were performed to identify the function and potential target of miR-449a in HCC cells. RESULTS: In HCC, miR-449a was significantly downregulated, while c-Met was upregulated concurrently. Quantitative proteomics and luciferase reporter assay identified c-Met as a direct target of miR-449a. Moreover, miR-449a inhibited HCC growth not only by targeting CDK6 but also by suppressing c-Met/Ras/Raf/ERK signaling pathway. Furthermore, the inhibition of c-Met expression with a specific siRNA significantly inhibited cells growth and deregulated the ERK pathway in HCC. CONCLUSION: The tumor suppressor miR-449a suppresses HCC tumorigenesis by repressing the c-Met/ERK pathway.

A Fast and Robust Non-Sparse Signal Recovery Algorithm for Wearable ECG Telemonitoring Using ADMM-Based Block Sparse Bayesian Learning.

Wearable telemonitoring of electrocardiogram (ECG) based on wireless body Area networks (WBAN) is a promising approach in next-generation patient-centric telecardiology solutions. In order to guarantee long-term effective operation of monitoring systems, the power consumption of the sensors must be strictly limited. Compressed sensing (CS) is an effective method to alleviate this problem. However, ECG signals in WBAN are usually non-sparse, and most traditional compressed sensing recovery algorithms have difficulty recovering non-sparse signals. In this paper, we proposed a fast and robust non-sparse signal recovery algorithm for wearable ECG telemonitoring. In the proposed algorithm, the alternating direction method of multipliers (ADMM) is used to accelerate the speed of block sparse Bayesian learning (BSBL) framework. We used the famous MIT-BIH Arrhythmia Database, MIT-BIH Long-Term ECG Database and ECG datasets collected in our practical wearable ECG telemonitoring system to verify the performance of the proposed algorithm. The experimental results show that the proposed algorithm can directly recover ECG signals with a satisfactory accuracy in a time domain without a dictionary matrix. Due to acceleration by ADMM, the proposed algorithm has a fast speed, and also it is robust for different ECG datasets. These results suggest that the proposed algorithm is very promising for wearable ECG telemonitoring.

Hepatocellular carcinoma stem cell-like cells are enriched following low-dose 5-fluorouracil chemotherapy.

It has been proposed that cancer stem cells (CSCs) are involved in tumor resistance to chemotherapy and tumor relapse. The goal of the present study was to determine the effect of low-dose 5-fluorouracil (5-Fu) on enriched hepatocellular CSC-like cells. Increased cell motility and epithelial-mesenchymal transition were observed by migration assay in human hepatoblastoma PLC/RAF/5 cells following 5-Fu treatment, as well as a significant enhancement in their sphere-forming abilities. CSC-like cells were identified by side population cell analysis. The percentage of CSC-like cells in the surviving cells was greatly increased in response to 5-Fu. These findings indicate that low-dose 5-Fu treatment may efficiently enrich the CSC-like cell population in PLC/RAF/5 cells.

Cytochrome c modulates the mitochondrial signaling pathway and polymorphonuclear neutrophil apoptosis in bile duct-ligated rats.

It has been observed that polymorphonuclear neutrophils (PMN) increase in number and function during obstructive jaundice (OJ). However, the precise mechanisms underlying PMN apoptosis during OJ remain poorly understood. The aim of the present study was to investigate the modulation of cytochrome c (Cytc) on the mitochondrial signaling pathway in bile duct-ligated (BDL) rats and the effect on PMN apoptosis following the intravenous administration of Cytc. Rats were randomly divided into four groups: A control group, a sham group, a BDL group and a BDL + Cytc group (rats with common bile duct ligation as well as Cytc intravenous injection). Blood samples were collected from the inferior vein cava for biochemical analysis and separation of the PMN. PMN apoptosis was evaluated using flow cytometry. The mitochondrial membrane potential (ΔΨm) of PMN was detected by rhodamine-123 staining. The Cytc protein expression levels were examined using western blotting. PMN mitochondria were observed using transmission electron microscopy. The results of the present study revealed that the PMN apoptosis rate in rats decreased gradually from 12 to 72 h following BDL to levels that were significantly lower than those of the control group and the sham group. Compared with the corresponding time point of the BDL group, the BDL + Cytc group showed a significantly increased PMN apoptosis rate. The mean fluorescence intensity (MFI) of ΔΨm decreased from 12 to 72 h following BDL, and was significantly increased compared with the control and sham groups. MFI in the BDL + Cytc group was higher compared with that in the BDL group. Cytc expression levels increased in the mitochondria and decreased in the cytoplasm from the 12 to 72 h in the BDL group, which was significantly different from that in the control and sham groups at the corresponding time points. Compared with the BDL group, Cytc expression levels in the cytoplasm for the BDL + Cytc group tended to gradually and significantly increase. Morphological changes in PMN mitochondria were marginal in BDL rats and marked in the BDL + Cytc group. In the BDL rats, PMN apoptosis was inhibited, a process induced by the mitochondrial apoptotic signaling pathway in which Cytc has an important role. High ΔΨm in the mitochondria and decreased Cytc expression levels in the cytoplasm result in PMN apoptosis inhibition. Intravenous injection of Cytc may help compensate for the lack of Cytc proteins in the cytoplasm, inducing PMN apoptosis following BDL.

Preparation of (103)Pd brachytherapy seeds by electroless plating of (103)Pd onto carbon bars.

A method for preparing (103)Pd brachytherapy seeds is reported. The key of the method was to deposit (103)Pd onto carbon bars by electroless plating so as to prepare source cores. After each carbon bar with (103)Pd was sealed in a titanium capsule, the (103)Pd seeds were fabricated. This paper provides valuable experiences and data for the preparation of (103)Pd brachytherapy seeds.