The transcriptional repressors VAL1 and VAL2 mediate genome-wide recruitment of the CHD3 chromatin remodeler PICKLE in Arabidopsis.

PICKLE (PKL) is a chromodomain helicase DNA-binding domain 3 (CHD3) chromatin remodeler that plays essential roles in controlling the gene expression patterns that determine developmental identity in plants, but the molecular mechanisms through which PKL is recruited to its target genes remain elusive. Here, we define a cis-motif and trans-acting factors mechanism that governs the genomic occupancy profile of PKL in Arabidopsis thaliana. We show that two homologous trans-factors VIVIPAROUS1/ABI3-LIKE1 (VAL1) and VAL2 physically interact with PKL in vivo, localize extensively to PKL-occupied regions in the genome, and promote efficient PKL recruitment at thousands of target genes, including those involved in seed maturation. Transcriptome analysis and genetic interaction studies reveal a close cooperation of VAL1/VAL2 and PKL in regulating gene expression and developmental fate. We demonstrate that this recruitment operates at two master regulatory genes, ABSCISIC ACID INSENSITIVE3 and AGAMOUS-LIKE 15, to repress the seed maturation program and ensure the seed-to-seedling transition. Together, our work unveils a general rule through which the CHD3 chromatin remodeler PKL binds to its target chromatin in plants.

A cytosine base editor toolkit with varying activity windows and target scopes for versatile gene manipulation in plants.

CRISPR/Cas-derived base editing tools empower efficient alteration of genomic cytosines or adenines associated with essential genetic traits in plants and animals. Diversified target sequences and customized editing products call for base editors with distinct features regarding the editing window and target scope. Here we developed a toolkit of plant base editors containing AID10, an engineered human AID cytosine deaminase. When fused to the N-terminus or C-terminus of the conventional Cas9 nickase (nSpCas9), AID10 exhibited a broad or narrow activity window at the protospacer adjacent motif (PAM)-distal and -proximal protospacer, respectively, while AID10 fused to both termini conferred an additive activity window. We further replaced nSpCas9 with orthogonal or PAM-relaxed Cas9 variants to widen target scopes. Moreover, we devised dual base editors with AID10 located adjacently or distally to the adenine deaminase ABE8e, leading to juxtaposed or spaced cytosine and adenine co-editing at the same target sequence in plant cells. Furthermore, we expanded the application of this toolkit in plants for tunable knockdown of protein-coding genes via creating upstream open reading frame and for loss-of-function analysis of non-coding genes, such as microRNA sponges. Collectively, this toolkit increases the functional diversity and versatility of base editors in basic and applied plant research.

Photoactivated Organic Nanomachines for Programmable Enhancement of Antitumor Efficacy.

Limited permeability in solid tumors significantly restricts the anticancer efficacy of nanomedicines. Light-driven nanomotors powered by photothermal converting engines are appealing carriers for directional drug delivery and simultaneous phototherapy. Nowadays, it is still a great challenge to construct metal-free photothermal nanomotors for a programmable anticancer treatment. Herein, one kind of photoactivated organic nanomachines is reported with asymmetric geometry assembled by light-to-heat converting semiconducting polymer engine and macromolecular anticancer payload through a straightforward nanoprecipitation process. The NIR-fueled polymer engine can be remotely controlled to power the nanomachines for light-driven thermophoresis in the liquid media and simultaneously thermal ablating the cancer cells. The great manipulability of the nanomachines allows for programming of their self-propulsion in the tumor microenvironment for effectively improving cellular uptake and tumor penetration of the anticancer payload. Taking the benefit from this behavior, a programmed treatment process is established at a low drug dose and a low photothermal temperature for significantly enhancing the antitumor efficacy.

Multiplex and optimization of dCas9-TV-mediated gene activation in plants.

Synthetic gene activators consisting of nuclease-dead Cas9 (dCas9) for single-guide RNA (sgRNA)-directed promoter binding and a transcriptional activation domain (TAD) represent new tools for gene activation from endogenous genomic locus in basic and applied plant research. However, multiplex gene coactivation by dCas9-TADs has not been demonstrated in whole plants. There is also room to optimize the performance of these tools. Here, we report that our previously developed gene activator, dCas9-TV, could simultaneously upregulate OsGW7 and OsER1 in rice by up to 3,738 fold, with one sgRNA targeting to each promoter. The gene coactivation could persist to at least the fourth generation. Astonishingly, the polycistronic tRNA-sgRNA expression under the maize ubiquitin promoter, a Pol II promoter, could cause enormous activation of these genes by up to >40,000-fold in rice. Moreover, the yeast GCN4 coiled coil-mediated dCas9-TV dimerization appeared to be promising for enhancing gene activation. Finally, we successfully introduced a self-amplification loop for dCas9-TV expression in Arabidopsis to promote the transcriptional upregulation of AtFLS2, a previously characterized dCas9-TV-refractory gene with considerable basal expression. Collectively, this work illustrates the robustness of dCas9-TV in multigene coactivation and provides broadly useful strategies for boosting transcriptional activation efficacy of dCas9-TADs in plants.

Silencing of lncRNA PVT1 by miR-214 inhibits the oncogenic GDF15 signaling and suppresses hepatocarcinogenesis.

The prognosis for hepatocellular carcinoma (HCC) is dismal. Long noncoding RNA PVT1 has been linked to malignancies and might be a deleterious therapy target. However, the key events controlling its expression in HCC remain undetermined. Here, we address how PVT1 is fine-regulated and its downstream signaling in hepatoma cells. Interestingly, we found that c-Myc and P53 could divergently regulate PVT1 transcription. Oncoprotein c-Myc enhances PVT1 expression, whereas P53 suppresses its expression. We also identified miR-214 as a crucial, negative regulator of PVT1. Consistently, high miR-214 levels were significantly correlated with diminished PVT1 expression in HCC specimens. Silencing of PVT1 by ectopic miR-214 or siRNAs markedly inhibited viability and invasion of HCC cells. In opposition, inhibition of endogenous miR-214 promoted PVT1 expression and enhanced cell proliferation. Notably, oncogenic GDF15 is a potential downstream target of the miR-214-PVT1 signaling. Collectively, our results show that the c-Myc/P53/miR-214-PVT1-GDF15 axis is implicated in HCC development, shedding light on the mechanistic actions of PVT1 and representing potential targets for HCC clinical intervention.

LncRNA MALAT1 Promotes STAT3-Mediated Endothelial Inflammation by Counteracting the Function of miR-590.

The excessive production of inflammatory mediators by vascular endothelial cells (ECs) greatly contributes to the development of atherosclerosis. In this study, we explored the potential effect of lncRNA MALAT1 on endothelial inflammation. First, the EC inflammation model was constructed by treating human umbilical vein ECs (HUVECs) and human coronary artery ECs (HCAECs) with oxidized low-density lipoprotein (ox-LDL), which confirmed the role of MALAT1 in the inflammatory activity. Then MALAT1 was overexpressed in HUVECs and HCAECs, and the levels of inflammatory mediators and nitric oxide (NO) were examined by Western blotting, ELISA, and NO detection assay. The migration ability was confirmed by wound healing assay. The interactions among MALAT1, miR-590, and STAT3 were predicted by bioinformatics analysis and verified by qRT-PCR, Western blotting, or dual-luciferase reporter assay. MALAT1 was upregulated in ECs treated with ox-LDL, and knockdown of MALAT1 significantly inhibited ox-LDL-induced inflammation. MALAT1 overexpression potentiated the inflammatory activities of ECs, including enhanced production of inflammatory cytokines (IL-6, IL-8, and TNF-α) and adhesion molecules (VCAM1 and ICAM1), and decreased NO level and cell migratory ability. Mechanistically, MALAT1 could directly downregulate miR-590, and miR-590 could bind to the 3'-UTR of STAT3 to repress its expression. Additionally, overexpression of MALAT1-mediated inflammation was largely abrogated by the concomitant overexpression of miR-590. miR-590 knockdown activated the inflammatory response, which was reversed by STAT3 inhibition. Thus, MALAT1 serves as a proinflammatory lncRNA in ECs through regulating the miR-590/STAT3 axis, suggesting that MALAT1 may be a promising therapeutic target during the treatment of atherosclerosis.

Gene disruption through base editing-induced messenger RNA missplicing in plants.

Gene knockout tools are highly desirable for basic and applied plant research. Here, we leverage the Cas9-derived cytosine base editor to introduce precise C-to-T mutations to disrupt the highly conserved intron donor site GT or acceptor site AG, thereby inducing messenger RNA (mRNA) missplicing and gene disruption. As proof of concept, we successfully obtained Arabidopsis null mutant of MTA gene in the T2 generation and rice double null mutant of GL1-1 and NAL1 genes in the T0 generation by this strategy. Elimination of the original intron donor site or acceptor site could trigger aberrant splicing at a new specific exonic site, but not at the closest GT or AG site, suggesting cryptic rules governing splice site recognition. The strategy presented expands the applications of base editing technologies in plants by providing a new means for gene inactivation without generating DNA double-strand breaks, and it can potentially serve as a useful tool for studying the biology of mRNA splicing.

Whole exome sequencing identifies lncRNA GAS8-AS1 and LPAR4 as novel papillary thyroid carcinoma driver alternations.

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. However, we know little of mutational spectrum in the Chinese population. Thus, here we report the identification of somatic mutations for Chinese PTC using 402 tumor-normal pairs (Discovery: 91 pairs via exome sequencing; validation: 311 pairs via Sanger sequencing). We observed three distinct mutational signatures, evidently different from the two mutational signatures among Caucasian PTCs. Ten significantly mutated genes were identified, most previously uncharacterized. Notably, we found that long non-coding RNA (lncRNA) GAS8-AS1 is the secondary most frequently altered gene and acts as a novel tumor suppressor in PTC. As a mutation hotspot, the c.713A>G/714T>C dinucleotide substitution was found among 89.1% patients with GAS8-AS1 mutations and associated with advanced PTC disease (P = 0.009). Interestingly, the wild-type lncRNA GAS8-AS1 (A713T714) showed consistently higher capability to inhibit cancer cell growth compared to the mutated lncRNA (G713C714). Further studies also elucidated the oncogene nature of the G protein-coupled receptor LPAR4 and its c.872T>G (p.Ile291Ser) mutation in PTC malignant transformation. The BRAF c.1799T>A (p.Val600Glu) substitution was present in 59.0% Chinese PTCs, more frequently observed in patients with lymph node metastasis (P = 1.6 × 10(-4)). Together our study defines a exome mutational spectrum of PTC in the Chinese population and highlights lncRNA GAS8-AS1 and LPAR4 as potential diagnostics and therapeutic targets.

Association of the functional BCL-2 rs2279115 genetic variant and small cell lung cancer.

As a well-known oncogene, B cell lymphoma-2 (BCL-2) can promote cancer cell survival through preventing their apoptosis. Several functional BCL-2 single nucleotide polymorphisms (SNPs), such as rs2279115, rs1801018, and rs1564483, have been identified and might contribute to cancer susceptibility. However, the involvement of these SNPs in small cell lung cancer (SCLC) was still unclear. As a result, we investigated associations between these three genetic variants and SCLC risk in a case-control design. Genotypes were determined in two independent case-control sets consisted of 520 SCLC patients and 1040 controls from two medical centers. Odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated utilizing unconditional logistic regression. We found that only BCL-2 rs2279115 genetic variant significantly contributed to decreased SCLC risk in Chinese Han populations, with the rs2279115 A allele as the protective allele. Stratified analyses of association between BCL2 rs2279115 SNP and SCLC risk indicated that the functional polymorphism was only significantly associated with decreased risk of the limited stage SCLC but not the extensive stage disease. Our results indicate that the BCL-2 rs2279115 genetic variant was associated with SCLC risk in Chinese populations and support the hypothesis that SNPs in regulatory regions of oncogenes might contribute to cancer susceptibility.

Prognostic value of serum IGF-1, Gal-3, and PTX-3 levels in elderly patients with chronic heart failure.

OBJECTIVES: To evaluate the diagnostic and prognostic value of insulin-like growth factor-1 (IGF-1), galactoagglutinin-3 (GAL-3), and pentamerin-3 (PTX-3) levels in elderly patients with chronic heart failure (CHF). METHODS: In this retrospective study, 107 elderly CHF patients treated in Xiangyang Central Hospital were designated as the observation group, and 60 healthy individuals were selected as the control group. The cardiac function indexes and serum IGF-1, Gal-3, and PTX-3 levels were compared between the two groups. Furthermore, the serum IGF-1, Gal-3, and PTX-3 levels in patients across different cardiac function grades were compared, as well as in patients with poor or favorable prognosis. Additionally, receiver operating characteristic (ROC) curve was adopted to explore the diagnostic value of serum IGF-1, Gal-3, and PTX-3 levels for senile CHF; and multivariate logistic regression analysis was used to screen the independent factors affecting patients' prognosis. RESULTS: The serum IGF-1 level was significantly lower, while the levels of Gal-3 and PTX-3 were significantly higher in the observation group than those of the control group (all P<0.05). The serum IGF-1 level in patients with cardiac function grade IV was lower than that of the patients with cardiac function grade II and III, while the levels of Gal-3 and PTX-3 were higher than those with cardiac function grade II and III (all P<0.05). The serum IGF-1 level in the patients with cardiac function grade III was lower than those with cardiac function grade II, while the levels of Gal-3 and PTX-3 were higher in patients with grade III than those with grade II (all P<0.05). The serum IGF-1 level was lower, while the levels of Gal-3 and PTX-3 were higher in the patients with poor prognosis than those with favorable prognosis (all P<0.05). CONCLUSION: In elderly CHF patients, IGF-1 level were decreases, while the levels of Gal-3 and PTX-3 were increase. These biomarkers show high sensitivity in diagnosing CHF and are closely linked to the prognosis, indicating their value for clinical assessment and management of CHF.

Identification and application of an exocarp-preferential promoter for genetic engineering of tomato fruit.

Tomato (Solanum lycopersicum) is a globally cultivated crop with great economic value. The exocarp determines the appearance of tomato fruit and protects it from various biotic and abiotic challenges at both pre-harvest and post-harvest stages. However, no tomato exocarp-specific promoter is currently available, which hinders exocarp-based genetic engineering. Here, we identified by RNA sequencing and reverse transcription-quantitative PCR analyses that the tomato gene SlPR10 (PATHOGENESIS RELATED 10) was abundantly and predominantly expressed in the exocarp. A fluorescent reporter expressed by a 2087-bp SlPR10 promoter (pSlPR10) was mainly detected in the exocarp of transgenic tomato plants of both Ailsa Craig and Micro-Tom cultivars. This promoter was further utilized for transgenic expression of SlANT1 and SlMYB31 in tomato, which are master regulators of anthocyanin and cuticular wax biosynthesis, respectively. pSlPR10-driven SlANT1 expression resulted in anthocyanin accumulation in the exocarp, conferring gray mold resistance and extended shelf life to the fruit, while SlMYB31 expression led to waxy thickening in the fruit skin, delaying water loss and also extending fruit shelf life. Intriguingly, pSlPR10 and two other weaker tomato exocarp-preferential promoters exhibited coincided expression specificities in the gynophore of transgenic Arabidopsis (Arabidopsis thaliana) plants, providing not only an inkling of evolutionary homology between tomato exocarp and Arabidopsis gynophore but also useful promoters for studying gynophore biology in Arabidopsis. Collectively, this work reports a desirable promoter enabling targeted gene expression in tomato exocarp and Arabidopsis gynophore and demonstrates its usefulness in genetic improvement of tomato fruit quality.

A multi-task generative model for simultaneous post-contrast MR image synthesis and brainstem glioma segmentation.

OBJECTIVES: This study aims to generate post-contrast MR images reducing the exposure of gadolinium-based contrast agents (GBCAs) for brainstem glioma (BSG) detection, simultaneously delineating the BSG lesion, and providing high-resolution contrast information. METHODS: A retrospective cohort of 30 patients diagnosed with brainstem glioma was included. Multi-contrast images, including pre-contrast T1 weighted (pre-T1w), T2 weighted (T2w), arterial spin labeling (ASL) and post-contrast T1w images, were collected. A multi-task generative model was developed to synthesize post-contrast T1w images and simultaneously segment BSG masks from the multi-contrast inputs. Performance evaluation was conducted using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean absolute error (MAE) metrics. A perceptual study was also undertaken to assess diagnostic quality. RESULTS: The proposed model achieved SSIM of 0.86 ± 0.04, PSNR of 26.33 ± 0.05 and MAE of 57.20 ± 20.50 for post-contrast T1w image synthesis. Automated delineation of the BSG lesions achieved Dice similarity coefficient (DSC) score of 0.88 ± 0.27. CONCLUSIONS: The proposed model can synthesize high-quality post-contrast T1w images and accurately segment the BSG region, yielding satisfactory DSC scores. CLINICAL RELEVANCE STATEMENT: The synthesized post-contrast MR image presented in this study has the potential to reduce the usage of gadolinium-based contrast agents, which may pose risks to patients. Moreover, the automated segmentation method proposed in this paper aids radiologists in accurately identifying the brainstem glioma lesion, facilitating the diagnostic process.

A dual-function selection system enables positive selection of multigene CRISPR mutants and negative selection of Cas9-free progeny in Arabidopsis.

The CRISPR/Cas9 technology revolutionizes targeted gene knockout in diverse organisms including plants. However, screening edited alleles, particularly those with multiplex editing, from herbicide- or antibiotic-resistant transgenic plants and segregating out the Cas9 transgene represent two laborious processes. Current solutions to facilitate these processes rely on different selection markers. Here, by taking advantage of the opposite functions of a d-amino acid oxidase (DAO) in detoxifying d-serine and in metabolizing non-toxic d-valine to a cytotoxic product, we develop a DAO-based selection system that simultaneously enables the enrichment of multigene edited alleles and elimination of Cas9-containing progeny in Arabidopsis thaliana. Among five DAOs tested in Escherichia coli, the one encoded by Trigonopsis variabilis (TvDAO) could confer slightly stronger d-serine resistance than other homologs. Transgenic expression of TvDAO in Arabidopsis allowed a clear distinction between transgenic and non-transgenic plants in both d-serine-conditioned positive selection and d-valine-conditioned negative selection. As a proof of concept, we combined CRISPR-induced single-strand annealing repair of a dead TvDAO with d-serine-based positive selection to help identify transgenic plants with multiplex editing, where d-serine-resistant plants exhibited considerably higher co-editing frequencies at three endogenous target genes than those selected by hygromycin. Subsequently, d-valine-based negative selection successfully removed Cas9 and TvDAO transgenes from the survival offspring carrying inherited mutations. Collectively, this work provides a novel strategy to ease CRISPR mutant identification and Cas9 transgene elimination using a single selection marker, which promises more efficient and simplified multiplex CRISPR editing in plants. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-023-00132-6.

Detection of chronic obstructive pulmonary disease with deep learning using inspiratory and expiratory chest computed tomography and clinical information.

Background: In recent years, more and more patients with chronic obstructive pulmonary disease (COPD) have remained undiagnosed despite having undergone medical examination. This study aimed to develop a convolutional neural network (CNN) model for automatically detecting COPD using double-phase (inspiratory and expiratory) chest computed tomography (CT) images and clinical information. Methods: A total of 2,047 participants, including never-smokers, ex-smokers, and current smokers, were prospectively recruited from three hospitals. The double-phase CT images and clinical information of each participant were collected for training the proposed CNN model which integrated a sequence of residual feature extracting blocks network (RFEBNet) for extracting CT image features and a fully connected feed-forward network (FCNet) for extracting clinical features. In addition, the RFEBNet utilizing double- or single-phase CT images and the FCNet using clinical information were conducted for comparison. Results: The proposed CNN model, which utilized double-phase CT images and clinical information, outperformed other models in detecting COPD with an area under the receiver operating characteristic curve (AUC) of 0.930 [95% confidence interval (CI): 0.913-0.951] on an internal test set (n=307). The AUC was higher than the RFEBNet using double-phase CT images (AUC =0.912, 95% CI: 0.891-0.932), single inspiratory CT images (AUC =0.888, 95% CI: 0.863-0.915), single expiratory CT images (AUC =0.897, 95% CI: 0.874-0.925), and FCNet using clinical information (AUC =0.805, 95% CI: 0.777-0.841). The proposed model also achieved the best performance on an external test (n=516) with an AUC of 0.896 (95% CI: 0.871-0.931). Conclusions: The proposed CNN model using double-phase CT images and clinical information can automatically detect COPD with high accuracy.

Distance guided generative adversarial network for explainable medical image classifications.

Despite the potential benefits of data augmentation for mitigating data insufficiency, traditional augmentation methods primarily rely on prior intra-domain knowledge. On the other hand, advanced generative adversarial networks (GANs) generate inter-domain samples with limited variety. These previous methods make limited contributions to describing the decision boundaries for binary classification. In this paper, we propose a distance-guided GAN (DisGAN) that controls the variation degrees of generated samples in the hyperplane space. Specifically, we instantiate the idea of DisGAN by combining two ways. The first way is vertical distance GAN (VerDisGAN) where the inter-domain generation is conditioned on the vertical distances. The second way is horizontal distance GAN (HorDisGAN) where the intra-domain generation is conditioned on the horizontal distances. Furthermore, VerDisGAN can produce the class-specific regions by mapping the source images to the hyperplane. Experimental results show that DisGAN consistently outperforms the GAN-based augmentation methods with explainable binary classification. The proposed method can apply to different classification architectures and has the potential to extend to multi-class classification. We provide the code in https://github.com/yXiangXiong/DisGAN.

SUV39H1 epigenetically modulates the MCPIP1-AURKA signaling axis to enhance neuroblastoma tumorigenesis.

Epigenetic regulation is a pivotal factor during neuroblastoma (NB) pathogenesis and investigations into cancer epigenetics are actively underway to identify novel therapeutic strategies for NB patients. SUV39H1, a member of the H3K9 methyltransferase family, contributing to tumorigenesis across multiple malignancies. However, its specific role in NB remains unexplored. In this study, we conducted a high-throughput screen utilizing a compound library containing 288 epigenetic drugs, leading to the identification of chaetocin as the most potent NB inhibitor by targeting SUV39H1. Genetic manipulation and therapeutic inhibition of SUV39H1 significantly impacted proliferation, migration, cell cycle phases, and apoptosis in NB cells. Concurrently, chaetocin demonstrated robust anti-tumor efficacy in vivo with tolerable toxicity. RNA-seq unveiled that SUV39H1 knockdown and inhibition down-regulated cell cycle pathways, impacting vital genes such as AURKA. Besides, MCPIP1 emerged as a novel tumor suppressor following SUV39H1 inhibition, which decreased AURKA expression in NB. In detail, SUV39H1 mediated the enrichment of H3K9me3 at the promoter region of MCPIP1, repressing the MCPIP1-mediated degradation of AURKA and facilitating the subsequent accumulation of AURKA, which revealed the oncogenic role of SUV39H1 via the SUV39H1-MCPIP1-AURKA signaling axis in NB. Therapeutic inhibition of SUV39H1 using chaetocin emerges as an effective and safe strategy for NB patients. Illustration of the oncogenic pathway regulated by SUV39H1 in NB.

A Clinical Study of Girls With Idiopathic Central Precocious Puberty and Psychological Behavior Problems.

To understand the psychological effects on behavior of girls with idiopathic central precocious puberty (ICPP) and to explore the role of gonadotropin-releasing hormone analog (GnRHa) in the reversal or blocking of the negative psychological effects on behaviors of girls with ICPP. A total of 100 girls with ICPP diagnosed at the Department of Endocrinology of Jiangxi Children's Hospital were divided into the treatment group and observation group with 50 cases in each group. The control group consisted of 50 healthy girls examined at our hospital during the same period. The Achenbach Child Behavior Check List ([CBCL] for parents) was used to evaluate the psychological effects on behavior of the girls diagnosed with ICPP and the girls in the control group, and the scores of related behavioral factors were calculated. At the same time, the psychological effects on behaviors of the girls with ICPP treated with GnRHa were followed up. (1) There were 100 girls with ICPP and 30 with behavioral problems. There were 50 normal healthy girls (control group) with 3 cases of behavior problems. Of the 50 girls with ICPP, after treatment, 8 had behavioral issues. The rate of abnormal psychological effects on behavior in the group of girls with ICPP before treatment was significantly higher than in the control group (P < .01), and after treatment, the rate was lower than before treatment (P < .05). (2) The scores of depression, social withdrawal, poor communication, and school discipline violation in the ICPP group were higher than those in the control group, with a statistical significance (P < .01). (3) After 24 months of GnRHa treatment for girls in the ICPP group, the scores of 4 factors, including depression, social withdrawal, poor communication, and violation of discipline in the Achenbach CBCL, were significantly different before and after treatment (P < .05). (1) Girls with ICPP have low self-esteem, low self-confidence, high incidences of psychological effects on behavior problems, manifested in depression, withdrawal, poor communication, discipline violations, and other aspects; (2) GnRHa treatment can reverse the low self-esteem and low self-confidence of girls with ICPP to varying degrees.

Split complementation of base editors to minimize off-target edits.

Base editors (BEs) empower the efficient installation of beneficial or corrective point mutations in crop and human genomes. However, conventional BEs can induce unpredictable guide RNA (gRNA)-independent off-target edits in the genome and transcriptome due to spurious activities of BE-enclosing deaminases, and current improvements mostly rely on deaminase-specific mutagenesis or exogenous regulators. Here we developed a split deaminase for safe editing (SAFE) system applicable to BEs containing distinct cytidine or adenosine deaminases, with no need of external regulators. In SAFE, a BE was properly split at a deaminase domain embedded inside a Cas9 nickase, simultaneously fragmenting and deactivating both the deaminase and the Cas9 nickase. The gRNA-conditioned BE reassembly conferred robust on-target editing in plant, human and yeast cells, while minimizing both gRNA-independent and gRNA-dependent off-target DNA/RNA edits. SAFE also substantially increased product purity by eliminating indels. Altogether, SAFE provides a generalizable solution for BEs to suppress off-target editing and improve on-target performance.

A Cascaded Multi-Task Generative Framework for Detecting Aortic Dissection on 3-D Non-Contrast-Enhanced Computed Tomography.

Contrast-enhanced computed tomography (CE-CT) is the gold standard for diagnosing aortic dissection (AD). However, contrast agents can cause allergic reactions or renal failure in some patients. Moreover, AD diagnosis by radiologists using non-contrast-enhanced CT (NCE-CT) images has poor sensitivity. To address this issue, we propose a novel cascaded multi-task generative framework for AD detection using NCE-CT volumes. The framework includes a 3D nnU-Net and a 3D multi-task generative architecture (3D MTGA). Specifically, the 3D nnU-Net was employed to segment aortas from NCE-CT volumes. The 3D MTGA was then employed to simultaneously synthesize CE-CT volumes, segment true & false lumen, and classify the patient as AD or non-AD. A theoretical formulation demonstrated that the 3D MTGA could increase the Jensen-Shannon Divergence (JSD) between AD and non-AD for each NCE-CT volume, thus indirectly improving the AD detection performance. Experiments also showed that the proposed framework could achieve an average accuracy of 0.831, a sensitivity of 0.938, and an F1-score of 0.847 in comparison with seven state-of-the-art classification models used by three radiologists with junior, intermediate, and senior experiences, respectively. The experimental results indicate that the proposed framework obtains superior performance to state-of-the-art models in AD detection. Thus, it has great potential to reduce the misdiagnosis of AD using NCE-CT in clinical practice. The source codes and supplementary materials for our framework are available at https://github.com/yXiangXiong/CMTGF.

Deep Learning for Accurate Segmentation of Venous Thrombus from Black-Blood Magnetic Resonance Images: A Multicenter Study.

OBJECTIVE: Deep vein thrombosis (DVT) is the third-largest cardiovascular disease, and accurate segmentation of venous thrombus from the black-blood magnetic resonance (MR) images can provide additional information for personalized DVT treatment planning. Therefore, a deep learning network is proposed to automatically segment venous thrombus with high accuracy and reliability. METHODS: In order to train, test, and external test the developed network, total images of 110 subjects are obtained from three different centers with two different black-blood MR techniques (i.e., DANTE-SPACE and DANTE-FLASH). Two experienced radiologists manually contoured each venous thrombus, followed by reediting, to create the ground truth. 5-fold cross-validation strategy is applied for training and testing. The segmentation performance is measured on pixel and vessel segment levels. For the pixel level, the dice similarity coefficient (DSC), average Hausdorff distance (AHD), and absolute volume difference (AVD) of segmented thrombus are calculated. For the vessel segment level, the sensitivity (SE), specificity (SP), accuracy (ACC), and positive and negative predictive values (PPV and NPV) are used. RESULTS: The proposed network generates segmentation results in good agreement with the ground truth. Based on the pixel level, the proposed network achieves excellent results on testing and the other two external testing sets, DSC are 0.76, 0.76, and 0.73, AHD (mm) are 4.11, 6.45, and 6.49, and AVD are 0.16, 0.18, and 0.22. On the vessel segment level, SE are 0.95, 0.93, and 0.81, SP are 0.97, 0.92, and 0.97, ACC are 0.96, 0.94, and 0.95, PPV are 0.97, 0.82, and 0.96, and NPV are 0.97, 0.96, and 0.94. CONCLUSIONS: The proposed deep learning network is effective and stable for fully automatic segmentation of venous thrombus on black blood MR images.