Leveraging cfDNA fragmentomic features in a stacked ensemble model for early detection of esophageal squamous cell carcinoma.

In this study, we develop a stacked ensemble model that utilizes cell-free DNA (cfDNA) fragmentomics for the early detection of esophageal squamous cell carcinoma (ESCC). This model incorporates four distinct fragmentomics features derived from whole-genome sequencing (WGS) and advanced machine learning algorithms for robust analysis. It is validated across both an independent validation cohort and an external cohort to ensure its generalizability and effectiveness. Notably, the model maintains its robustness in low-coverage sequencing environments, demonstrating its potentials in clinical settings with limited sequencing resources. With its remarkable sensitivity and specificity, this approach promises to significantly improve the early diagnosis and management of ESCC. This study represents a substantial step forward in the application of cfDNA fragmentomics in cancer diagnostics, emphasizing the need for further research to fully establish its clinical efficacy.

Quantification of urinary podocyte-derived migrasomes for the diagnosis of kidney disease.

Migrasomes represent a recently uncovered category of extracellular microvesicles, spanning a diameter range of 500 to 3000 nm. They are emitted by migrating cells and harbour a diverse array of RNAs and proteins. Migrasomes can be readily identified in bodily fluids like serum and urine, rendering them a valuable non-invasive source for disease diagnosis through liquid biopsy. In this investigation, we introduce a streamlined and effective approach for the capture and quantitative assessment of migrasomes, employing wheat germ agglutinin (WGA)-coated magnetic beads and flow cytometry (referred to as WBFC). Subsequently, we examined the levels of migrasomes in the urine of kidney disease (KD) patients with podocyte injury and healthy volunteers using WBFC. The outcomes unveiled a substantial increase in urinary podocyte-derived migrasome concentrations among individuals with KD with podocyte injury compared to the healthy counterparts. Notably, the urinary podocyte-derived migrasomes were found to express an abundant quantity of phospholipase A2 receptor (PLA2R) proteins. The presence of PLA2R proteins in these migrasomes holds promise for serving as a natural antigen for the quantification of autoantibodies against PLA2R in the serum of patients afflicted by membranous nephropathy. Consequently, our study not only pioneers a novel technique for the isolation and quantification of migrasomes but also underscores the potential of urinary migrasomes as a promising biomarker for the early diagnosis of KD with podocyte injury.

An integrative platform for detection of RNA 2'-O-methylation reveals its broad distribution on mRNA.

Ribose 2'-O-methylation is involved in critical biological processes, but its biological functions and significance in mRNAs remain underexplored. We have developed NJU-seq, a sensitive method for unbiased 2'-O-methylation (Nm) profiling, and Nm-VAQ, a site-specific quantification tool. Using these tools in tandem, we identified thousands of Nm sites on mRNAs of human and mouse cell lines, of which 68 of 84 selected sites were further validated to be more than 1% 2'-O-methylated. Unlike rRNA, most mRNA Nm sites were from 1% to 30% methylated. In addition, mRNA Nm was dynamic, changing according to the circumstance. Furthermore, we show that fibrillarin is involved as a methyltransferase. By mimicking the detected Nm sites and the context sequence, the RNA fragments could be 2'-O-methylated and demonstrated higher stability but lower translation efficiency. Last, profiling of Nm sites in lung surgery samples revealed common signatures of lung cancer pathogenesis, providing potential new diagnostic markers.

Automatic artery/vein classification methods for retinal blood vessel: A review.

Automatic retinal arteriovenous classification can assist ophthalmologists in disease early diagnosis. Deep learning-based methods and topological graph-based methods have become the main solutions for retinal arteriovenous classification in recent years. This paper reviews the automatic retinal arteriovenous classification methods from 2003 to 2022. Firstly, we compare different methods and provide comparison tables of the summary results. Secondly, we complete the classification of the public arteriovenous classification datasets and provide the annotation development tables of different datasets. Finally, we sort out the challenges of evaluation methods and provide a comprehensive evaluation system. Quantitative and qualitative analysis shows the changes in research hotspots over time, Quantitative and qualitative analyses reveal the evolution of research hotspots over time, highlighting the significance of exploring the integration of deep learning with topological information in future research.

Rapid Identification of Pathogens in Severe Pneumonia by Species-specific Bacterial Detector (SSBD).

Fast and accurate detection of pathogenic bacterial infection in patients with severe pneumonia is significant to its treatment. The traditional culture method currently used by most medical institutions relies on a time-consuming culture process (over two days) that is unable to meet clinical needs. Rapid, accurate, and convenient species-specific bacterial detector (SSBD) has been developed to provide timely information on pathogenic bacteria. The SSBD was designed based on the fact that Cas12a indiscriminately cleaves any DNA following the binding of the crRNA-Cas12a complex to the target DNA molecule. SSBD involves two processes, starting with PCR of the target DNA using primers specific for the pathogen, followed by detection of the existence of pathogen target DNA in the PCR product using the corresponding crRNA and Cas12a protein. Compared to the culture test, the SSBD can obtain accurate pathogenic information in only a few hours, dramatically shortening the detection time and allowing more patients to benefit from timely clinical treatment.

Biochemical characterization of RNase R 2'-O-methylation sensitivity.

RNase R is a member of the RNA exonuclease family that digests RNA in the 3'-5' direction. Previous studies have identified RNase R from Mycoplasma genitalium (MgR) as the only RNA exonuclease that is sensitive to 2'-O-methylation (Nm) modification. However, the mechanism underlying this characteristic is not well understood. In this study, we aimed to explore the molecular mechanism of RNase R Nm sensitivity using an improved assay that can better evaluate Nm sensitivity. By comparing the sequences of five wild-type RNase R variants from Mycoplasma, we identified the importance of loop 18 in Nm sensitivity. Furthermore, we demonstrated the critical roles of L283, T278, and T279 within loop18. Our findings deepen the understanding of the molecular mechanism of why MgR is sensitive to Nm and provide a potential direction of protein engineering for applications.

Mature Red Blood Cells Contain Long DNA Fragments and Could Acquire DNA from Lung Cancer Tissue.

Red blood cells (RBC) are commonly known as cells with no nucleus or mitochondria and are assumed to be a transportation vehicle. This study confirms that RBC contain long DNA fragments inside with stain by both microscope and flow cytometry, which covers most nuclear and mitochondrial genome regions by next-generation sequencing (NGS). Such characteristics demonstrate a significant difference compared with A549 cell line or paired peripheral blood mononuclear cell as nucleated cells. To further explore the characteristics of RNA DNA, DNA from 20 RBC samples is sequenced by NGS. Interestingly, several gaps and multiple regions with copy number variation are observed significantly different between different samples, which could be used to distinguish samples with different health status accurately. Using an in vitro co-culture system, it is shown that RBC could absorb DNA-bearing tumorigenic mutations from cancer cell lines but requires cell-to-cell contact. Finally, based on a small scale clinical trial, it is confirmed that common genetic mutations of cancer tissues could be detected in RBC from patients with early-stage non-small-cell lung cancer. This study highlights a new biological phenomenon involving RBC and its translational potential as a novel liquid biopsy technology platform for early cancer screening and diagnosis of malignancy.

Novel fast pathogen diagnosis method for severe pneumonia patients in the intensive care unit: randomized clinical trial.

Background: Severe pneumonia is one of the common acute diseases caused by pathogenic microorganism infection, especially by pathogenic bacteria, leading to sepsis with a high morbidity and mortality rate. However, the existing bacteria cultivation method cannot satisfy current clinical needs requiring rapid identification of bacteria strain for antibiotic selection. Therefore, developing a sensitive liquid biopsy system demonstrates the enormous value of detecting pathogenic bacterium species in pneumonia patients. Methods: In this study, we developed a tool named Species-Specific Bacterial Detector (SSBD, pronounce as 'speed') for detecting selected bacterium. Newly designed diagnostic tools combining specific DNA-tag screened by our algorithm and CRISPR/Cas12a, which were first tested in the lab to confirm the accuracy, followed by validating its specificity and sensitivity via applying on bronchoalveolar lavage fluid (BALF) from pneumonia patients. In the validation I stage, we compared the SSBD results with traditional cultivation results. In the validation II stage, a randomized and controlled clinical trial was completed at the ICU of Nanjing Drum Tower Hospital to evaluate the benefit SSBD brought to the treatment. Results: In the validation stage I, 77 BALF samples were tested, and SSBD could identify designated organisms in 4 hr with almost 100% sensitivity and over 87% specific rate. In validation stage II, the SSBD results were obtained in 4 hr, leading to better APACHE II scores (p=0.0035, ANOVA test). Based on the results acquired by SSBD, cultivation results could deviate from the real pathogenic situation with polymicrobial infections. In addition, nosocomial infections were found widely in ICU, which should deserve more attention. Conclusions: SSBD was confirmed to be a powerful tool for severe pneumonia diagnosis in ICU with high accuracy. Funding: National Natural Science Foundation of China. The National Key Scientific Instrument and Equipment Development Project. Project number: 81927808. Clinical trial number: This study was registered at https://clinicaltrials.gov/ (NCT04178382).

The molecular mechanism of constructive remodeling of a mechanically-loaded polymer.

Large or repeated mechanical loads usually degrade polymers by accelerating fragmentation of their backbones but rarely, they can cause new backbone bonds to form. When these new bonds form faster than the original bonds break, mechanical degradation may be arrested or reversed in real time. Exploiting such constructive remodeling has proven challenging because we lack an understanding of the competition between bond-forming and bond-breaking reactions in mechanically-stressed polymers. Here we report the molecular mechanism and analysis of constructive remodeling driven by the macroradical products of mechanochemical fragmentation of a hydrocarbon backbone. By studying the changing compositions of a random copolymer of styrene and butadiene sheared at 10 °C in the presence of different additives we developed an approach to characterizing this growth/fracture competition, which is generalizable to other underlying chemistries. Our results demonstrate that constructive remodeling is achievable under practically relevant conditions, requires neither complex chemistries, elaborate macromolecular architectures or free monomers, and is amenable to detailed mechanistic interrogation and simulation. These findings constitute a quantitative framework for systematic studies of polymers capable of autonomously counteracting mechanical degradation at the molecular level.

Construction and Validation of a Glioma Prognostic Model Based on Immune Microenvironment.

OBJECTIVE: This study aims to construct a prognostic model based on the different immune infiltration statuses of the glioma samples. METHODS: Glioma-associated dataset was assessed from The Cancer Genome Atlas database. Hierarchical cluster analysis was performed to classify the glioma samples. Single-sample gene set enrichment analysis was introduced to the glioma samples for immune infiltration analysis. Kaplan-Meier survival analysis was applied to evaluate patients' prognoses. The differentially expressed genes (DEGs) between different sample groups were screened using limma package. Univariate Cox, LASSO Cox, and multivariate Cox regression analyses were employed to construct the prognostic model. The prediction performance of the model was examined by plotting a receiver-operating characteristic (ROC) curve, and GSEA was introduced to screen the differently activated pathways between high- and low-risk groups. RESULTS: The glioma samples were classified into 3 clusters where the different immune infiltration and survival statuses were presented among the clusters. 123 immune-related DEGs were screened from the differential expression analyses, and based on these DEGs, an 8-gene prognostic model was constructed. The ROC curve exhibited an optimal performance of the prognostic model, and GSEA showed that ECM-receptor interaction, complement and coagulation cascades, cytokine receptor pathways, and viral protein interaction with cytokine were differently activated between the two risk groups. CONCLUSION: The current study screened an immune-associated gene set by classifying and differential analysis, followed by constructing an 8-gene prognostic model based on the screened genes.

Prolonged siRNA expression in mammalian cells using an Epstein-Barr virus-based plasmid expression system.

RNA interference (RNAi) is a powerful tool in gene function analysis and disease treatment, especially diseases that are 'undruggable' by classical small molecules. However, the RNAi applications are limited due to some defects, such as short duration and toxic side effects. New strategies are still needed to improve RNAi applications. Previous studies have illustrated that Epstein-Barr virus nuclear antigen 1 (EBNA-1) and the origin of plasmid replication (oriP) are critical factors for EBV latent gene expression, which can keep the replication of the EBV genome as an extrachromosomal element for a relatively long time. Here we report a plasmid expression system on the base of oriP and EBNA-1, which could produce protein as well as short interfering RNAs(siRNAs) for a long time in mammalian cells. siRNA expression mediated by this system causes efficient and specific down-regulation of gene expression. Except for analyzing gene function, this study also provided a new optional and practical way for protein and/or RNAi-based therapies that require enduring effect.

A four-DNA methylation biomarker is a superior predictor of survival of patients with cutaneous melanoma.

Cutaneous melanoma (CM) is a life-threatening form of skin cancer. Prognostic biomarkers can reliably stratify patients at initial melanoma diagnosis according to risk, and may inform clinical decisions. Here, we performed a retrospective, cohort-based study analyzing genome-wide DNA methylation of 461 patients with CM from the TCGA database. Cox regression analyses were conducted to establish a four-DNA methylation signature that was significantly associated with the overall survival (OS) of patients with CM, and that was validated in an independent cohort. Corresponding Kaplan-Meier analysis displayed a distinct separation in OS. The ROC analysis confirmed that the predictive signature performed well. Notably, this signature exhibited much higher predictive accuracy in comparison with known biomarkers. This signature was significantly correlated with immune checkpoint blockade (ICB) immunotherapy-related signatures, and may have potential as a guide for measures of responsiveness to ICB immunotherapy.

A five-DNA methylation signature act as a novel prognostic biomarker in patients with ovarian serous cystadenocarcinoma.

BACKGROUND: Ovarian cancer is the most fatal tumor of the female reproductive system and the fifth leading cause of cancer death among women in the USA. The prognosis is poor due to the lack of biomarkers for treatment options. RESULTS: The methylation array data of 551 patients with ovarian serous cystadenocarcinoma (OSC) in The Cancer Genome Atlas (TCGA) database were assessed in this study to explore the methylation biomarkers associated with prognosis and improve the prognosis of patients. These patients were divided into training (first two thirds) and validation datasets (remaining one third). A five-DNA methylation signature was found to be significantly associated with the overall survival of patients with OSC using the Cox regression analysis in the training dataset. The Kaplan-Meier analysis showed that the five-DNA methylation signature could significantly distinguish the high- and low-risk patients in both training and validation sets. The receiver operating characteristic (ROC) analysis further confirmed that the five-DNA methylation signature exhibited high sensitivity and specificity to predict the prognostic survival of patients. Also, the five-DNA methylation signature was not only applicable in patients of different ages, stages, histologic grade, and size of residual tumor after surgery but also more accurate in predicting OSC prognosis compared with known biomarkers. CONCLUSIONS: This five-DNA methylation signature demonstrated the potential of being a novel independent prognostic indicator and served as an important tool for guiding the clinical treatment of OSC to improve outcome prediction and management for patients. Hence, the findings of this study might have potential clinical significance.

Biochemical Characterization of APOBEC3H Variants: Implications for Their HIV-1 Restriction Activity and mC Modification.

APOBEC3H (A3H) is the most polymorphic member of the APOBEC3 family. Seven haplotypes (hap I-VII) and four mRNA splicing variants (SV) of A3H have been identified. The various haplotypes differ in anti-HIV activity, which is attributed to differences in protein stability, subcellular distribution, and/or RNA binding and virion packaging. Here, we report the first comparative biochemical studies of all the A3H variants using highly purified proteins. We show that all haplotypes were stably expressed and could be purified to homogeneity by Escherichia coli expression. Surprisingly, four out of the seven haplotypes showed high cytosine (C) deaminase activity, with hap V displaying extremely high activity that was comparable to the highly active A3A. Furthermore, all four haplotypes that were active in C deamination were also highly active on methylated C (mC), with hap II displaying almost equal deamination efficiency on both. The deamination activity of these A3H variants correlates well with their reported anti-HIV activity for the different haplotypes, suggesting that deaminase activity may be an important factor in determining their respective anti-HIV activities. Moreover, mC deamination of A3H displayed a strong preference for the sequence motif of T-mCpG-C/G, which may suggest a potential role in genomic mC modification at the characteristic "CpG" island motif.

The in vitro Biochemical Characterization of an HIV-1 Restriction Factor APOBEC3F: Importance of Loop 7 on Both CD1 and CD2 for DNA Binding and Deamination.

APOBEC3F (A3F) is a member of the apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) family of proteins that can deaminate cytosine (C) to uracil (U) on nucleic acids. A3F is one of the four APOBEC members with two Zn-coordinated homologous cytosine deaminase (CD) domains, with the others being A3G, A3D, and A3B. Here we report the in vitro characterization of DNA binding and deaminase activities using purified wild-type and various mutant proteins of A3F from an Escherichia coli expression system. We show that even though CD1 is catalytically inactive and CD2 is the active deaminase domain, presence of CD1 on the N-terminus of CD2 enhances the deaminase activity by over an order of magnitude. This enhancement of CD2 catalytic activity is mainly through the increase of substrate single-stranded (ss) DNA binding by the N-terminal CD1 domain. We further show that the loop 7 of both CD1 and CD2 of A3F plays an important role for ssDNA binding for each individual domain, as well as for the deaminase activity of CD2 domain in the full-length A3F.

Role of signal peptide-Cub-Egf domain-containing protein-1 in serum as a predictive biomarker of outcome after severe traumatic brain injury.

BACKGROUND: Signal peptide-Cub-Epidermal growth factor domain-containing protein 1 (SCUBE1), a marker for coagulation, is secreted under hypoxia and inflammatory conditions from platelet α granules. This study was designed to determine the associations of serum SCUBE1 concentrations with trauma severity and prognosis after severe traumatic brain injury. METHODS: Serum SCUBE1 concentrations of 113 patients and 113 controls were measured. An unfavorable outcome was defined as Glasgow Outcome Scale score of 1-3. RESULTS: Serum SCUBE1 concentrations were significantly higher in patients than in controls (15.5 ± 6.0 vs. 1.1 ± 0.3 ng/ml, P < 0.001) and were associated with Glasgow coma scale scores (r = -0.439, P < 0.001) and blood platelet count (r = 0.420, P < 0.001). SCUBE1 was identified as an independent prognostic marker of 6-month unfavorable outcome (odds ratio, 1.357; 95% confidence interval, 1.159-1.589; P < 0.001), and had high predictive value according to receiver operating characteristic curve (area under curve, 0.830; 95% confidence interval, 0.748-0.890; P < 0.001). CONCLUSIONS: Increased serum SCUBE1 concentrations are associated highly with trauma severity, platelet activation and poor outcome, suggesting that SCUBE1 might be a novel prognostic biomarker after traumatic brain injury.

Strong positive selection drives rapid diversification of R-genes in Arabidopsis relatives.

Although plant resistance (R) genes are extremely diverse and evolve rapidly, little is known about the mechanisms that generate this sequence divergence. To investigate these forces, we compared all nucleotide binding sites and leucine-rich repeat R-genes between two closely related species, Arabidopsis thaliana and Arabidopsis lyrata. Our analyses revealed two distinct evolutionary patterns driven by either positive or stabilizing selection. Most R-genes (>50%) were evolving under strong positive selection characterized by high Ka/Ks ratios (>1), frequent recombination, copy number variation, and extremely high sequence divergence between the two species. The stably selected R-genes (<30%) have exactly the opposite four characters as the positively selected genes. The remaining R-genes (about 20%) are present in only one genome and absent from the other. A higher proportion of such genes were found to be part of TNL class (23.5%) compared to the non-TNL class (5.6%), suggesting different evolutionary patterns between these two groups. A significant correlation between Ka and divergence was revealed, indicating that the rapid evolution and diversification of R-genes were initiated by selectively generated, frequently shuffled and selectively maintained non-synonymous substitutions. Our genome-wide analyses confirmed an amazing mechanism by which plants to selectively accumulate and efficiently exploit these non-synonymous substitutions for their resistance to various pathogens.