We conducted a meta-analysis to systematically assess the prevalence of hyperhomocysteinemia (HHcy) in China, its change over time, and its determinants. Literature searches were conducted using English databases (PubMed, Embase, and Web of Science) and Chinese databases (CNKI, CBM, VIP, and Wanfang). The time ranges were from Jan 2014 to Mar 2021 in China. We adopted the random effects model to estimate the pooled positive rates of HHcy and corresponding 95% confidence intervals (95% CI). To find the sources of heterogeneity, we performed subgroup analysis and meta-regression. A total of 29 related articles were identified involving 338,660 participants with 128,147 HHcy cases. The estimated prevalence of HHcy in China was 37.2% (95% CI: 32.6–41.8%, I² = 99.8%, p for heterogeneity < 0.001). The trend of HHcy prevalence was gradually upward over time, with increases during 2015–2016 (comparison to 2013–2014, p < 0.001), but steady between 2015–2016 and 2017–2018. Subgroup analysis showed that the prevalence was higher in the elderly over 55 years old, males, and residents in the north, inland, and rural China (for each comparison, p < 0.001). Meta-regression analysis revealed that age and area of study contributed to 42.3% of the heterogeneity between studies. The current meta-analysis provides strong evidence that the prevalence of HHcy is increasing in China, and varies substantially across different ages, genders, and geographic distribution. Accordingly, high-risk population groups should be focused on, and public health policies and strategies should be carried out to prevent and control HHcy in China.

Cervical cancer (CC) is the fourth most common malignant tumor among women worldwide. Constructing a high-accuracy deep convolutional neural network (DCNN) for cervical cancer screening and diagnosis is important for the successful prevention of cervical cancer. In this work, we proposed a robust DCNN for cervical cancer screening using whole-slide images (WSI) of ThinPrep cytologic test (TCT) slides from 211 cervical cancer and 189 normal patients. We used an active learning strategy to improve the efficiency and accuracy of image labeling. The sensitivity, specificity, and accuracy of the best model were 96.21%, 98.95%, and 97.5% for CC patient identification respectively. Our results also demonstrated that the active learning strategy was superior to the traditional supervised learning strategy in cost reduction and improvement of image labeling quality. The related data and source code are freely available at https://github.com/hqyone/cancer_rcnn.

Background: Whole genome bisulfite sequencing (WGBS) also known as BS-seq has been widely used to measure the methylation of whole genome at single-base resolution. One of the key steps in the assay is converting unmethylated cytosines into thymines (BS conversion). Incomplete conversion of unmethylated cytosines can introduce false positive methylation call. Developing a quick method to evaluate bisulfite conversion ratio (BCR) is benefit for both quality control and data analysis of WGBS. Results: Here we provide a computational method named “BCREval” to estimate the unconverted rate (UCR) by using telomeric repetitive DNA as native spike-in control. We tested the method by using public WGBS data and found that it is very stable and most of BS conversion assays can achieve> 99.5% efficiency. The non-CpG DNA methylation at telomere fits a binomial model and may result from a random process with very low possibility (the ratio < 0.4%). And the comparison between BCREval and Bismark (Krueger and Andrews, Bioinformatics 27:1571–1572, 2011), a widely used BCR evaluator, suggests that our algorithm is much faster and more efficient than the latter. Conclusion: Our method is a simple but robust method to QC and speculates BCR for WGBS experiments to make sure it achieves acceptable level. It is faster and more efficient than current tools and can be easily integrated into presented WGBS pipelines.

Alternative lengthening of telomeres (ALTs) mechanism is activated in some somatic, germ cells, and human cancer cells. However, the key regulators and mechanisms of the ALT pathway remain elusive. Here we demonstrated that ZBTB40 is a novel telomere-associated protein and binds to telomeric dsDNA through its N-terminal BTB (BR-C, ttk and bab) or POZ (Pox virus and Zinc finger) domain in ALT cells. Notably, the knockout or knockdown of ZBTB40 resulted in the telomere dysfunction-induced foci and telomere lengthening in the ALT cells. The results also show that ZBTB40 is associated with ALT-associated promyelocytic leukemia nuclear bodies, and the loss of ZBTB40 induces the accumulation of the ALT-associated promyelocytic leukemia nuclear bodies in U2OS cells. Taken together, our results implicate that ZBTB40 is a key player of telomere protection and telomere lengthening regulation in human ALT cells.

Extrachromosomal circular DNA (eccDNA) is a special class of circular DNA in eukaryotes. Recent studies have suggested that eccDNA is the product of genomic instability and has important biological functions to regulate many downstream biological processes. While NGS (Next-Generation Sequencing)-based eccDNA sequencing has led to the identification of many eccDNAs in both healthy and diseased tissues, the specific biological functions of individual eccDNAs have yet to be clearly elucidated. Synthesizing eccDNAs longer than 1 kb with specific sequences remains a major challenge in the field, which has hindered our ability to fully understand their functions. Current methods for synthesizing eccDNAs primarily rely on chemical oligo synthesis, ligation, or the use of a specific gene editing and recombination systems. Therefore, these methods are often limited by the length of eccDNAs and are complex, expensive, as well as time-consuming. In this study, we introduce a novel method named QuickLAMA (Ligase-Assisted Minicircle Accumulation) for rapidly synthesizing eccDNAs up to 2.6 kb using a simple PCR and ligation approach. To validate the efficacy of our method, we synthesized three eccDNAs of varying lengths from cancer tissue and PC3 cells and confirmed successful circularization through sequencing and restriction enzyme digestion. Additional analyses have demonstrated that this method is highly efficient, cost-effective, and time-efficient, with good reproducibility. Using the method, a well-trained molecular biologist can synthesize and purify multiple eccDNAs within a single day, and it can be easily standardized and processed in a high-throughput manner, indicating the potential of the method to produce a wide range of desired eccDNAs and promote the translation of eccDNA research into clinical applications.

Alternative lengthening of telomeres (ALT) is a homologous recombination-based telomere maintenance mechanism activated in 10–15% of human cancers. Although significant progress has been made, the key regulators of the ALT pathway and its role in cancer development remain elusive. Bioinformatics methods were used to predict novel telomere-associated proteins (TAPs) by analysis of large-scale ChIP-Seq data. Immunostaining and fluorescence in situ hybridization experiments were applied to detect the subcellular location of target genes and telomeres. Western blot and reverse transcription-polymerase chain reaction (RT-PCR) were used to examine the expression of targeting genes. Overall survival (OS) analyses were used to evaluate the relationship between gene expression and survival time; immunohistochemistry was used to detect the distribution of target genes in liver cancer tissues. We found that nuclear factor related to kappaB binding protein (NFRKB), a metazoan-specific subunit of the INO80 complex, can associate with telomeres in human ALT cells. Loss of NFRKB induces dysfunction of telomeres and less PML bodies in U2OS cells. In addition, NFRKB is low/moderately expressed in cytoplasm of normal hepatocytes but heavily accumulating in the nucleus of liver cancer cells. Finally, the high expression of NFRKB is associated with short OS time and poor prognosis. NFRKB is a TAP and protects telomeres from DNA damage in ALT cells. It is highly expressed in hepatocellular carcinoma (HCC) cells and predicts a poor prognosis. NFRKB may be a promising prognostic biomarker for the treatment of HCC in the future.