Activation-induced deaminase (AID) initiates U:G mismatches, causing point mutations or DNA double-stranded breaks at immunoglobulin (
Ig
) loci. How AID-initiated lesions are prevented from inducing ...genome-wide damage remains elusive. Differential DNA repair mechanism might protect certain non-Ig loci such as
c-myc
from AID attack. However, determinants regulating such protective mechanisms are largely unknown. To test whether target DNA sequences modulate protective mechanisms via altering the processing manner of AID-initiated lesions, we established a knock-in model by inserting an Sγ2b region, a
bona fide
AID target, into the first intron of
c-myc
. Unexpectedly, we found that the inserted S region did not mutate or enhance
c-myc
genomic instability, due to error-free repair of AID-initiated lesions, in antigen-stimulated germinal center (GC) B cells. In contrast,
in vitro
cytokine-activated B cells display a much higher level of
c-myc
genomic instability in an AID- and S region-dependent manner. Furthermore, we observe a comparable frequency of AID deamination events between the
c-myc
intronic sequence and inserted S region in different B cell populations, demonstrating a similar frequency of AID targeting. Thus, our study reveals a clear difference between GC and cytokine-activated B cells in their ability to develop genomic instability, attributable to a differential processing of AID-initiated lesions in distinct B cell populations. We propose that locus-specific regulatory mechanisms (e.g. transcription) appear to not only override the effects of S region sequence on AID targeting frequency but also influence the repair manner of AID-initiated lesions.
Myotonic dystrophy type 1 (DM1) is associated with expansion of (CTG)(n) · (CAG)(n) trinucleotide repeats (TNRs) in the 3' untranslated region (UTR) of the DMPK gene. Replication origins are ...cis-acting elements that potentiate TNR instability; therefore, we mapped replication initiation sites and prereplication complex protein binding within the ~10-kb DMPK/SIX5 locus in non-DM1 and DM1 cells. Two origins, IS(DMPK) and IS(SIX5), flanked the (CTG)(n) · (CAG)(n) TNRs in control cells and in DM1 cells. Orc2 and Mcm4 bound near each of the replication initiation sites, but a dramatic change in (CTG)(n) · (CAG)(n) replication polarity was not correlated with TNR expansion. To test whether (CTG)(n) · (CAG)(n) TNRs are cis-acting elements of instability in human cells, model cell lines were created by integration of cassettes containing the c-myc replication origin and (CTG)(n) · (CAG)(n) TNRs in HeLa cells. Replication forks were slowed by (CTG)(n) · (CAG)(n) TNRs in a length-dependent manner independent of replication polarity, implying that expanded (CTG)(n) · (CAG)(n) TNRs lead to replication stress. Consistent with this prediction, TNR instability increased in the HeLa model cells and DM1 cells upon small interfering RNA (siRNA) knockdown of the fork stabilization protein Claspin, Timeless, or Tipin. These results suggest that aberrant DNA replication and TNR instability are linked in DM1 cells.
Instability of (CTG) x (CAG) microsatellite trinucleotide repeat (TNR) sequences is responsible for more than a dozen neurological or neuromuscular diseases. TNR instability during DNA synthesis is ...thought to involve slipped-strand or hairpin structures in template or nascent DNA strands, although direct evidence for hairpin formation in human cells is lacking. We have used targeted recombination to create a series of isogenic HeLa cell lines in which (CTG) x (CAG) repeats are replicated from an ectopic copy of the Myc (also known as c-myc) replication origin. In this system, the tendency of chromosomal (CTG) x (CAG) tracts to expand or contract was affected by origin location and the leading or lagging strand replication orientation of the repeats, and instability was enhanced by prolonged cell culture, increased TNR length and replication inhibition. Hairpin cleavage by synthetic zinc finger nucleases in these cells has provided the first direct evidence for the formation of hairpin structures during replication in vivo.
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Growing evidences indicate that circular RNAs (circRNAs) play an important role in the regulation of biological behavior of tumor. We aim to explore the role of circRNA in glioma and elucidate how ...circRNA acts.
Real-time PCR was used to examine the expression of circPTN in glioma tissues and normal brain tissues (NBT). Assays of dual- luciferase reporter system, biotin label RNA pull-down and FISH were used to determine that circPTN could sponge miR-145-5p and miR-330-5p. Tumor sphere formation assay was performed to determine self- renewal of glioma stem cell (GSCs). Cell counting Kit-8 (CCK8), EdU assay and flow cytometry were used to investigate proliferation and cell cycle. Intracranial xenograft was established to determine how circPTN impacts in vivo. Tumor sphere formation assay was performed to determine self- renewal of glioma stem cell (GSCs).
We demonstrated circPTN was significantly higher expression in glioma tissues and glioma cell lines, compared with NBT and HEB (human astrocyte). In gain- and loss-of-function experiments, circPTN significantly promoted glioma growth in vitro and in vivo. Furthermore, we performed dual-luciferase reporter assays and RNA pull-down assays to verify that circPTN acts through sponging miR-145-5p and miR-330-5p. Increasing expression of circPTN rescued the inhibition of proliferation and downregulation of SOX9/ITGA5 in glioma cells by miR-145-5p/miR-330-5p. In addition, we found that circPTN promoted self-renewal and increased the expression of stemness markers (Nestin, CD133, SOX9, and SOX2) via sponging miR-145-5p. Moreover, this regulation was disappeared when circPTN binding sites in miR-145-5p were mutated.
Our results suggest that circPTN is an oncogenic factor that acts by sponging miR-145-5p/miR-330-5p in glioma.
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Machine learning (ML) classifiers have been widely used in the field of crop classification. However, having inputs that include a large number of complex features increases not only the difficulty ...of data collection but also reduces the accuracy of the classifiers. Feature selection (FS), which can availably reduce the number of features by selecting and reserving the most essential features for crop classification, is a good tool to solve this problem effectively. Different FS methods, however, have dissimilar effects on various classifiers, so how to achieve the optimal combination of FS methods and classifiers to meet the needs of high-precision recognition of multiple crops remains an open question. This paper intends to address this problem by coupling the analysis of three FS methods and six classifiers. Spectral, textual, and environmental features are firstly extracted as potential classification indexes from time-series remote sensing images from France. Then, three FS methods are used to obtain feature subsets and combined with six classifiers for coupling analysis. On this basis, 18 multi-crop classification models (FS–ML models) are constructed. Additionally, six classifiers without FS are constructed for comparison. The training set and the validation set for these models are constructed by using the Kennard-Stone algorithm with 70% and 30% of the samples, respectively. The performance of the classification model is evaluated by Kappa, F1-score, accuracy, and other indicators. The results show that different FS methods have dissimilar effects on various models. The best FS–ML model is RFAA+-RF, and its Kappa coefficient can reach 0.7968, which is 0.33–46.67% higher than that of other classification models. The classification results are highly dependent on the original classification index sets. Hence, the reasonability of combining spectral, textural, and environmental indexes is verified by comparing them with the single feature index set. The results also show that the classification strategy combining spectral, textual, and environmental indexes can effectively improve the ability of crop recognition, and the Kappa coefficient is 9.06–65.52% higher than that of the single unscreened feature set.
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The role of plants in alleviating aerosol pollution has drawn extensive attention. Most studies focus on compositions of aerosol particles on urban plants, while the leaf traits related to particle ...retention have not yet been intensively studied. This study selected five typical urban plants (Loropetalum chinense, Rhododendron simsii, Euonymus japonicus, Photinia × fraseri, Osmanthus fragrans), and employed scanning electron microscope (SEM) and ion chromatography, aiming to investigate the accumulation features of aerosol particles and the relationships between leaf traits and particle retention. Results show that aerosol particles were mainly retained on the adaxial leaf surface, the fine particles (Φ ≤ 2.5 μm) were the predominant components (77.8 % by number) on the leaves, and the dominant water-soluble ions of particles were Ca2+, SO42−, and NO3−. By comparison, E. japonicus and P. fraseri were efficient in the retention of fine and coarse particles (2.5 <Φ ≤ 10 μm), but L. chinense was capable to retain more large particles (Φ > 10 μm). The correlation analysis indicates that leaf traits are closely related to the accumulation of aerosol particles. The result shows that plant leaves with larger stomatal area, lower stomatal density, smaller specific leaf area and higher in epicuticular wax content can retain more aerosol particles. This result indicates that the leaves are capable of retaining aerosol particles via the synergy of multiple leaf traits, such as higher wax content and the fewer but larger stomata on their leaf surfaces. This study is helpful to understand the interactions between leaf traits and particle retention, and it further contributes to the selection of potential dust-retaining plants, which is of great significance for the alleviation of urban air pollution.
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•Fine particles were the predominant components of retained particles with diverse types and sources.•E. japonicus and P. fraseri were more efficient in particle accumulation than the other studied species.•The leaf traits (e.g., large stomatal area, low stomatal density, small specific leaf area and high epicuticular wax content) contributed to particle deposition.•This study gives insights into the relationship between leaf traits and particle accumulation, and provides a reference for the optimal selection of dust-retaining plants to alleviate aerosol pollutions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The combination of immune checkpoint inhibitors (ICIs) and anti-angiogenic agents has shown promising efficacy in unresectable hepatocellular carcinoma (HCC), but until now no clinical prognostic ...models or predictive biomarkers have been established.
From 2016 to 2021, a total of 258 HCCs treated with ICIs and tyrosine kinase inhibitors (TKIs) were retrospectively enrolled, as the study cohort. Patients' baseline data was extracted by least absolute and shrinkage selection operator (LASSO) and Cox regression. Finally, a prognostic model in the form of nomogram was developed. Model performance was assessed in terms of discrimination, calibration, and clinical utility. A 5-fold cross-validation was used to evaluate the internal repeatability of the model. In addition, the patient cohort was divided into three subgroups according to nomogram scores. Their survivals were estimated by Kaplan-Meier methods and the differences were analyzed using log-rank tests.
Seven clinical parameters were selected: Eastern Cooperative Oncology Group performance status (ECOG PS), combination of transarterial chemoembolization (TACE), extrahepatic metastasis (EHM), platelet to lymphocyte ratio (PLR), alanine aminotransferase (ALT), alpha-fetoprotein (AFP), and Child-Pugh score. The model had an area under the curve (AUC) of 0.777 at 1 year and 0.772 at 2 years. Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) showed that the discrimination, consistency and applicability of the model were good. In addition, cross-validation validated the discrimination of the model, and the C index value of the model is 0.7405. The median overall survival (OS) of the high-, medium- and low-risk subgroups was 7.58, 17.50 and 53.17 months, respectively, with a significant difference between the groups (P < 0.0001).
We developed a comprehensive and simple prognostic model for the combination of ICIs plus TKIs. And it may predict the efficacy of the combination regimen for unresectable HCC.
Objective To describe and analyze the predictive models of the prognosis of patients with hepatocellular carcinoma (HCC) undergoing systemic treatment. Design Systematic review. Data sources PubMed ...and Embase until December 2020 and manually searched references from eligible articles. Eligibility criteria for study selection The development, validation, or updating of prognostic models of patients with HCC after systemic treatment. Results The systematic search yielded 42 eligible articles: 28 articles described the development of 28 prognostic models of patients with HCC treated with systemic therapy, and 14 articles described the external validation of 32 existing prognostic models of patients with HCC undergoing systemic treatment. Among the 28 prognostic models, six were developed based on genes, of which five were expressed in full equations; the other 22 prognostic models were developed based on common clinical factors. Of the 28 prognostic models, 11 were validated both internally and externally, nine were validated only internally, two were validated only externally, and the remaining six models did not undergo any type of validation. Among the 28 prognostic models, the most common systemic treatment was sorafenib (n = 19); the most prevalent endpoint was overall survival (n = 28); and the most commonly used predictors were alpha-fetoprotein (n = 15), bilirubin (n = 8), albumin (n = 8), Child-Pugh score (n = 8), extrahepatic metastasis (n = 7), and tumor size (n = 7). Further, among 32 externally validated prognostic models, 12 were externally validated > 3 times. Conclusions This study describes and analyzes the prognostic models developed and validated for patients with HCC who have undergone systemic treatment. The results show that there are some methodological flaws in the model development process, and that external validation is rarely performed. Future research should focus on validating and updating existing models, and evaluating the effects of these models in clinical practice. Systematic review registration PROSPERO CRD42020200187. Keywords: Hepatocellular carcinoma, Systemic treatment, Prognostic models, Review and critical appraisal
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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