Characterization of extrachromosomal circular DNAs in plasma of patients with clear cell renal cell carcinoma.

BACKGROUND AND PURPOSE: Extrachromosomal circular DNAs (eccDNAs) have been recognized for their significant involvement in numerous biological processes. Nonetheless, the existence and molecular characteristics of eccDNA in the peripheral blood of patients diagnosed with clear cell renal cell carcinoma (ccRCC) have not yet been reported. Our aim was to identify potentially marked plasma eccDNAs in ccRCC patients. METHODS AND MATERIALS: The detection of plasma eccDNA in ccRCC patients and healthy controls was performed using the Tn5-tagmentation and next-generation sequencing (NGS) method. Comparisons were made between ccRCC patients and healthy controls regarding the distribution of length, gene annotation, pattern of junctional nucleotide motif, and expression pattern of plasma eccDNA. RESULTS: We found 8,568 and 8,150 plasma eccDNAs in ccRCC patients and healthy controls, respectively. There were no statistical differences in the length distribution, gene annotation, and motif signature of plasma eccDNAs between the two groups. A total of 701 differentially expressed plasma eccDNAs were identified, and 25 plasma eccDNAs with potential diagnostic value for ccRCC have been successfully screened. These up-regulated plasma eccDNAs also be indicated to originate from the genomic region of the tumor-associated genes. CONCLUSION: This work demonstrates the characterization of plasma eccDNAs in ccRCC and suggests that the up-regulated plasma eccDNAs could be considered as a promising non-invasive biomarker in ccRCC.

An exploratory study of whether axillary lymph node dissection can be avoided in breast cancer patients with positive lymph nodes.

Background: Breast cancer patients with positive axillary lymph nodes usually require axillary lymph node dissection (ALND), with many postoperative complications, such as lymphedema. For these patients, whether sentinel lymph node biopsy (SLNB) can replace ALND has been a research hotspot in the field of breast cancer. This study developed two risk stratification models for predicting the clinical outcomes of breast cancer patients with positive axillary lymph nodes receiving SLNB alone or ALND to determine which patients could potentially avoid ALND. Methods: A total of 21,942 breast cancer patients, including a training set (n=15,362) and a testing set (n=6,580), were enrolled in this study from Surveillance, Epidemiology, and End Results (SEER) between 2000 and 2017. The risk factors associated with breast cancer-specific survival (BCSS) and overall survival (OS) were evaluated using multivariate Cox regression analysis and then integrated into nomograms and risk stratification models examined by receiver operating characteristic (ROC) curves and calibration curves. The survival discrepancies were compared between the SLNB and ALND subgroups with different risk scores with Kaplan-Meier plots. Results: In multivariate Cox regression analyses, grade, marital status, T stage, radiotherapy and lymph node metastasis (GMTRL) were independent risk factors in breast cancer patients with both OS and BCSS status in the ALND cohort from the training set. Nomograms have been developed based on these factors to predict 3- and 5-year OS and BCSS in patients with ALND. Calibration curves and ROC curves in both the training and testing sets confirmed the excellent overall predictive performance of the nomograms. Furthermore, we developed two risk stratification models based on OS and BCSS status, revealing that patients with low GMTRL scores might avoid ALND in both OS and BCSS status [OS: hazard ratio (HR) =0.929, 95% confidence interval (CI): 0.841-1.027, P=0.150; BCSS: HR =0.953, 95% CI: 0.831-1.094, P=0.495], but patients with moderate (OS: HR =0.756, 95% CI: 0.666-0.859, P<0.001; BCSS: HR =0.643, 95% CI: 0.537-0.768, P<0.001) and high GMTRL scores could not (OS: HR =0.719, 95% CI: 0.549-0.940, P=0.014; BCSS: HR =0.731, 95% CI: 0.549-0.974, P=0.031). Conclusions: Breast cancer patients with positive nodes could be treated with SLNB alone rather than ALND without affecting prognosis based on GMTRL scores. Patients with high or moderate GMTRL scores benefited greatly from ALND, but not for patients with low GMTRL scores. This study may assist clinicians in tailoring treatments.

Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.

PARP1 is one of six enzymes required for the highly error-prone DNA repair pathway microhomology-mediated end joining (MMEJ) and needs to be inhibited when over-expressed. In order to study the PARP1 inhibitory effect of fused tetracyclic or pentacyclic dihydrodiazepinoindolone derivatives (FTPDDs) by quantitative structure-activity relationship technique, six models were established by four kinds of methods, heuristic method, gene expression programming, random forester, and support vector regression with single, double, and triple kernel function respectively. The single, double, and triple kernel functions were RBF kernel function, the integration of RBF and polynomial kernel functions, and the integration of RBF, polynomial, and linear kernel functions respectively. The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. Among the models, the model established by support vector regression with triple kernel function, in which the optimal R 2 and RMSE of training set and test set were 0.9353, 0.9348 and 0.0157, 0.0288, and R2 cv of training set and test set were 0.9090 and 0.8971, shows the strongest prediction ability and robustness. The method of support vector regression with triple kernel function is a great promotion in the field of quantitative structure-activity relationship, which will contribute a lot to designing and screening new drug molecules. The information contained in the model can provide important factors that guide drug design. Based on these factors, six new FTPDDs have been designed. Using molecular docking experiments to determine the properties of new derivatives, the new drug was ultimately successfully designed.

Applications of photodynamic therapy in extramammary Paget's disease.

Extramammary Paget's disease (EMPD) is a rare form of adenocarcinoma usually found in apocrine gland-containing cutaneous regions. EMPD affects the vulvar area most commonly, followed by the perianal area, scrotum, penis, and axillary region. In its initial form, EMPD presents as an erythematous plaque with well-defined edges, fine scaling, excoriations, exulcerations, and lichenification. Generally, a definitive diagnosis can be made through histopathological analysis. Importantly, associated malignancies should be investigated prior to treatment initiation. Photodynamic therapy (PDT) is a modern, noninvasive treatment strategy for non-oncological diseases as well as various cancers. In recent years, PDT has been widely used to treat EMPD. This present article presents a discussion of the diagnosis and treatment of EMPD as well as the usefulness of PDT in its management.

A rapid genome-wide analysis of isolated giant viruses using MinION sequencing.

Following the discovery of Acanthamoeba polyphaga mimivirus, diverse giant viruses have been isolated. However, only a small fraction of these isolates have been completely sequenced, limiting our understanding of the genomic diversity of giant viruses. MinION is a portable and low-cost long-read sequencer that can be readily used in a laboratory. Although MinION provides highly error-prone reads that require correction through additional short-read sequencing, recent studies assembled high-quality microbial genomes only using MinION sequencing. Here, we evaluated the accuracy of MinION-only genome assemblies for giant viruses by re-sequencing a prototype marseillevirus. Assembled genomes presented over 99.98% identity to the reference genome with a few gaps, demonstrating a high accuracy of the MinION-only assembly. As a proof of concept, we de novo assembled five newly isolated viruses. Average nucleotide identities to their closest known relatives suggest that the isolates represent new species of marseillevirus, pithovirus and mimivirus. The assembly of subsampled reads demonstrated that their taxonomy and genomic composition could be analysed at the 50× sequencing coverage. We also identified a pithovirus gene whose homologues were detected only in metagenome-derived relatives. Collectively, we propose that MinION-only assembly is an effective approach to rapidly perform a genome-wide analysis of isolated giant viruses.

An exploration of the correlations between seven psychiatric disorders and the risks of breast cancer, breast benign tumors and breast inflammatory diseases: Mendelian randomization analyses.

Background: Previous observational studies have showed that certain psychiatric disorders may be linked to breast cancer risk, there is, however, little understanding of relationships between mental disorders and a variety of breast diseases. This study aims to investigate if mental disorders influence the risks of overall breast cancer, the two subtypes of breast cancer (ER+ and ER-), breast benign tumors and breast inflammatory diseases. Methods: During our research, genome-wide association study (GWAS) data for seven psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, post-traumatic stress disorder, panic disorder, obsessive-compulsive disorder and anorexia nervosa) from the Psychiatric Genomics Consortium (PGC) and the UK Biobank were selected, and single-nucleotide polymorphisms (SNPs) significantly linked to these mental disorders were identified as instrumental variables. GWAS data for breast diseases came from the Breast Cancer Association Consortium (BCAC) as well as the FinnGen consortium. We performed two-sample Mendelian randomization (MR) analyses and multivariable MR analyses to assess these SNPs' effects on various breast diseases. Both heterogeneity and pleiotropy were evaluated by sensitivity analyses. Results: When the GWAS data of psychiatric disorders were derived from the PGC, our research found that schizophrenia significantly increased the risks of overall breast cancer (two-sample MR: OR 1.05, 95%CI [1.03-1.07], p = 3.84 × 10-6; multivariable MR: OR 1.06, 95%CI [1.04-1.09], p = 2.34 × 10-6), ER+ (OR 1.05, 95%CI [1.02-1.07], p = 5.94 × 10-5) and ER- (two-sample MR: OR 1.04, 95%CI [1.01-1.07], p = 0.006; multivariable MR: OR 1.06, 95%CI [1.02-1.10], p = 0.001) breast cancer. Nevertheless, major depressive disorder only showed significant positive association with overall breast cancer (OR 1.12, 95%CI [1.04-1.20], p = 0.003) according to the two-sample MR analysis, but not in the multivariable MR analysis. In regards to the remainder of the mental illnesses and breast diseases, there were no significant correlations. While as for the data from the UK Biobank, schizophrenia did not significantly increase the risk of breast cancer. Conclusions: The correlation between schizophrenia and breast cancer found in this study may be false positive results caused by underlying horizontal pleiotropy, rather than a true cause-and-effect relationship. More prospective studies are still needed to be carried out to determine the definitive links between mental illnesses and breast diseases.

Infiltrating myeloid cell diversity determines oncological characteristics and clinical outcomes in breast cancer.

BACKGROUND: Breast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown. METHODS: Myeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner. RESULTS: We dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients. CONCLUSIONS: Our study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification.

Accumulation of microplastics in greenhouse soil after long-term plastic film mulching in Beijing, China.

Intensive use of plastic film and organic fertilizer in the greenhouse has resulted in microplastic contamination of soil. However, microplastic pollution in different types of greenhouses has not been reported so far. The contamination of microplastics in three different types of greenhouses (abandoned greenhouse, normal greenhouse, and simple greenhouse) were investigated. The abundance of microplastics in abandoned greenhouse reached as high as 2215.56 ± 1549.86 items kg-1, followed by normal greenhouse (891.11 ± 316.71 items kg-1), and simple greenhouse (632.50 ± 566.93 items kg-1). The mean abundance of microplastic organic fertilizer, and irrigation water were 1486.67 ± 140.48 items kg-1, and 4.2 items L-1, respectively. The abundance of microplastics in the shallow soils of abandoned greenhouse (826.67 ± 261.02) and normal greenhouse (560.00 ± 52.92 items kg-1) were lower than those in the deep soils (1073.33 ± 306.16 and 720.00 ± 111.36 items kg-1), while the simple greenhouse showed the opposite result. Microplastic was found to be primarily fragment-shaped, white in color, and 0-1 mm in size, and the polymers of microplastics were polypropylene (PP) and polyethylene (PE). White was the most frequently observed color in the abandoned greenhouse (46.1%) and normal greenhouse (32.2%), while the dominant color in the simple greenhouse was yellow (23.1%). This study provides first-hand data for the pollution characteristics of microplastics in different greenhouse soils and explores the primary sources of microplastics in the greenhouse soil.

Triple signal amplification strategy for the ultrasensitive electrochemical detection of human papillomavirus 16 E6/E7 mRNA.

Human papilloma virus (HPV) is the primary causative agent of cervical, vaginal, and vulvar cancers. HPV E6/E7 mRNA detection has been proven to improve the specificity and positive predictive value compared with HPV DNA testing in screening, whereby, it may possess higher diagnostic potential. Herein, to establish the ultrasensitive and specific detection of HPV E6/E7 mRNA, we developed a novel triple signal amplification strategy, combined with gold nanoparticles (AuNPs), reverse transcription loop-mediated isothermal amplification (RT-LAMP) and high affinity biotin-avidin system. This novel proposed signal amplification strategy exhibits the desired detection limit of 0.08 fM (approximately 100 copies) and a wide linear range from 0.1 pmol/mL to 100 nmol/mL for HPV16 E6/E7 mRNA detection. Importantly, the present novel biosensor is 10-100 times more sensitive than conventional RT-PCR in detecting HPV16 E6/E7 mRNA positive clinical samples. Conclusively, this biosensor shows good stability, selectivity, and reproducibility, which demonstrates its potential in future clinical diagnosis with desirable sensitivity and specificity.

Uncoupling of macrophage inflammation from self-renewal modulates host recovery from respiratory viral infection.

Tissue macrophages self-renew during homeostasis and produce inflammatory mediators upon microbial infection. We examined the relationship between proliferative and inflammatory properties of tissue macrophages by defining the impact of the Wnt/ß-catenin pathway, a central regulator of self-renewal, in alveolar macrophages (AMs). Activation of ß-catenin by Wnt ligand inhibited AM proliferation and stemness, but promoted inflammatory activity. In a murine influenza viral pneumonia model, ß-catenin-mediated AM inflammatory activity promoted acute host morbidity; in contrast, AM proliferation enabled repopulation of reparative AMs and tissue recovery following viral clearance. Mechanistically, Wnt treatment promoted ß-catenin-HIF-1α interaction and glycolysis-dependent inflammation while suppressing mitochondrial metabolism and thereby, AM proliferation. Differential HIF-1α activities distinguished proliferative and inflammatory AMs in vivo. This ß-catenin-HIF-1α axis was conserved in human AMs and enhanced HIF-1α expression associated with macrophage inflammation in COVID-19 patients. Thus, inflammatory and reparative activities of lung macrophages are regulated by ß-catenin-HIF-1α signaling, with implications for the treatment of severe respiratory diseases.

Cascade marker removal algorithm for thyroid ultrasound images.

During thyroid ultrasound diagnosis, radiologists add markers such as pluses or crosses near a nodule's edge to indicate the location of a nodule. For computer-aided detection, deep learning models achieve classification, segmentation, and detection by learning the thyroid's texture in ultrasound images. Experiments show that manual markers are strong prior knowledge for data-driven deep learning models, which interferes with the judgment mechanism of computer-aided detection systems. Aiming at this problem, this paper proposes cascade marker removal algorithm for thyroid ultrasound images to eliminate the interference of manual markers. The algorithm consists of three parts. First, in order to highlight marked features, the algorithm extracts salient features in thyroid ultrasound images through feature extraction module. Secondly, mask correction module eliminates the interference of other features besides markers' features. Finally, the marker removal module removes markers without destroying the semantic information in thyroid ultrasound images. Experiments show that our algorithm enables classification, segmentation, and object detection models to focus on the learning of pathological tissue features. At the same time, compared with mainstream image inpainting algorithms, our algorithm shows better performance on thyroid ultrasound images. In summary, our algorithm is of great significance for improving the stability and performance of computer-aided detection systems. Graphical Abstract During thyroid ultrasound diagnosis, doctors add markers such as pluses or crosses near nodule's edge to indicate the location of nodule. Manual markers are strong prior knowledge for data-driven deep learning models, which interferes the judgment mechanism of computer-aided diagnosis system based on deep learning. Markers make models overfit the specific labeling forms easily, and performs poorly on unmarked thyroid ultrasound images. Aiming at this problem, this paper proposes a cascade marker removal algorithm to eliminate the interference of manual markers. Our algorithm make deep learning models pay attention on nodules' features of thyroid ultrasound images, which make computer-aided diagnosis system performs good in both marked imaging and unmarked imaging.

BCL6 modulates tissue neutrophil survival and exacerbates pulmonary inflammation following influenza virus infection.

Neutrophils are vital for antimicrobial defense; however, their role during viral infection is less clear. Furthermore, the molecular regulation of neutrophil fate and function at the viral infected sites is largely elusive. Here we report that BCL6 deficiency in myeloid cells exhibited drastically enhanced host resistance to severe influenza A virus (IAV) infection. In contrast to the notion that BCL6 functions to suppress innate inflammation, we find that myeloid BCL6 deficiency diminished lung inflammation without affecting viral loads. Using a series of Cre-transgenic, reporter, and knockout mouse lines, we demonstrate that BCL6 deficiency in neutrophils, but not in monocytes or lung macrophages, attenuated host inflammation and morbidity following IAV infection. Mechanistically, BCL6 bound to the neutrophil gene loci involved in cellular apoptosis in cells specifically at the site of infection. As such, BCL6 disruption resulted in increased expression of apoptotic genes in neutrophils in the respiratory tract, but not in the circulation or bone marrow. Consequently, BCL6 deficiency promoted tissue neutrophil apoptosis. Partial neutrophil depletion led to diminished pulmonary inflammation and decreased host morbidity. Our results reveal a previously unappreciated role of BCL6 in modulating neutrophil apoptosis at the site of infection for the regulation of host disease development following viral infection. Furthermore, our studies indicate that tissue-specific regulation of neutrophil survival modulates host inflammation and tissue immunopathology during acute respiratory viral infection.

An ultrasensitive electrochemical immunosensor for procalcitonin detection based on the gold nanoparticles-enhanced tyramide signal amplification strategy.

In this study, we established an ultrasensitive electrochemical immunosensor based on the gold nanoparticles-enhanced tyramide signal amplification (AuNPs-TSA) for the detection of procalcitonin (PCT, for discriminating bacterial infections from nonbacterial infections). Firstly, a facilely prepared, well-conducting reduced graphene oxide nanosheets/GNP (rGO-AuNPs) nanocomposite was synthesized and immobilized on the electrode surface to absorb more capture antibodies (Ab1). Next another nanocomposite, acting as a signal tool, was modified with detection antibody (Ab2) and horseradish peroxidase (HRP), and then backfilled by bovine serum albumin (BSA). Because a single AuNP is able to load multiple HRPs and BSAs, a number of tyramine labeled biotins (T-B) could be deposited on the proteins adhering to the surface of AuNPs. Moreover, the high affinity between streptavidin (SA) and biotins significantly increases the loading of streptavidin labeled horseradish peroxidase (SA-HRP). The amplification system which was based on the two nanocomposites mentioned above, effectively amplified the electric current signals. This immunosensor exhibits a wide dynamic detection range from 0.05 ng mL-1 to 100 ng mL-1 and with an ultralow detection limit of 0.1 pg mL-1. We have successfully utilized this immunosensor to quantify the concentration of PCT in human serum samples, and the results suggest its potential use in clinical application.

Purification of GFRα1+ and GFRα1- Spermatogonial Stem Cells Reveals a Niche-Dependent Mechanism for Fate Determination.

Undifferentiated spermatogonia comprise a pool of stem cells and progenitor cells that show heterogeneous expression of markers, including the cell surface receptor GFRα1. Technical challenges in isolation of GFRα1+ versus GFRα1- undifferentiated spermatogonia have precluded the comparative molecular characterization of these subpopulations and their functional evaluation as stem cells. Here, we develop a method to purify these subpopulations by fluorescence-activated cell sorting and show that GFRα1+ and GFRα1- undifferentiated spermatogonia both demonstrate elevated transplantation activity, while differing principally in receptor tyrosine kinase signaling and cell cycle. We identify the cell surface molecule melanocyte cell adhesion molecule (MCAM) as differentially expressed in these populations and show that antibodies to MCAM allow isolation of highly enriched populations of GFRα1+ and GFRα1- spermatogonia from adult, wild-type mice. In germ cell culture, GFRα1- cells upregulate MCAM expression in response to glial cell line-derived neurotrophic factor (GDNF)/fibroblast growth factor (FGF) stimulation. In transplanted hosts, GFRα1- spermatogonia yield GFRα1+ spermatogonia and restore spermatogenesis, albeit at lower rates than their GFRα1+ counterparts. Together, these data provide support for a model of a stem cell pool in which the GFRα1+ and GFRα1- cells are closely related but show key cell-intrinsic differences and can interconvert between the two states based, in part, on access to niche factors.

High telomerase is a hallmark of undifferentiated spermatogonia and is required for maintenance of male germline stem cells.

Telomerase inactivation causes loss of the male germline in worms, fish, and mice, indicating a conserved dependence on telomere maintenance in this cell lineage. Here, using telomerase reverse transcriptase (Tert) reporter mice, we found that very high telomerase expression is a hallmark of undifferentiated spermatogonia, the mitotic population where germline stem cells reside. We exploited these high telomerase levels as a basis for purifying undifferentiated spermatogonia using fluorescence-activated cell sorting. Telomerase levels in undifferentiated spermatogonia and embryonic stem cells are comparable and much greater than in somatic progenitor compartments. Within the germline, we uncovered an unanticipated gradient of telomerase activity that also enables isolation of more mature populations. Transcriptomic comparisons of Tert(High) undifferentiated spermatogonia and Tert(Low) differentiated spermatogonia by RNA sequencing reveals marked differences in cell cycle and key molecular features of each compartment. Transplantation studies show that germline stem cell activity is confined to the Tert(High) cKit(-) population. Telomere shortening in telomerase knockout strains causes depletion of undifferentiated spermatogonia and eventual loss of all germ cells after undifferentiated spermatogonia drop below a critical threshold. These data reveal that high telomerase expression is a fundamental characteristic of germline stem cells, thus explaining the broad dependence on telomerase for germline immortality in metazoans.