The maize gene maternal derepression of r1 encodes a DNA glycosylase that demethylates DNA and reduces siRNA expression in the endosperm.

Demethylation of transposons can activate the expression of nearby genes and cause imprinted gene expression in the endosperm; this demethylation is hypothesized to lead to expression of transposon small interfering RNAs (siRNAs) that reinforce silencing in the next generation through transfer either into egg or embryo. Here we describe maize (Zea mays) maternal derepression of r1 (mdr1), which encodes a DNA glycosylase with homology to Arabidopsis thaliana DEMETER and which is partially responsible for demethylation of thousands of regions in endosperm. Instead of promoting siRNA expression in endosperm, MDR1 activity inhibits it. Methylation of most repetitive DNA elements in endosperm is not significantly affected by MDR1, with an exception of Helitrons. While maternally-expressed imprinted genes preferentially overlap with MDR1 demethylated regions, the majority of genes that overlap demethylated regions are not imprinted. Double mutant megagametophytes lacking both MDR1 and its close homolog DNG102 result in early seed failure, and double mutant microgametophytes fail pre-fertilization. These data establish DNA demethylation by glycosylases as essential in maize endosperm and pollen and suggest that neither transposon repression nor genomic imprinting is its main function in endosperm.

Tri-Compartmental Restriction Spectrum Imaging Based on 18F-FDG PET/MR for Identification of Primary Benign and Malignant Lung Lesions.

BACKGROUND: Restriction spectrum imaging (RSI), as an advanced quantitative diffusion-weighted magnetic resonance imaging technique, has the potential to distinguish primary benign and malignant lung lesions. OBJECTIVE: To explore how well the tri-compartmental RSI performs in distinguishing primary benign from malignant lung lesions compared with diffusion-weighted imaging (DWI), and to further explore whether positron emission tomography/magnetic resonance imaging (PET/MRI) can improve diagnostic efficacy. STUDY TYPE: Prospective. POPULATION: 137 patients, including 108 malignant and 29 benign lesions (85 males, 52 females; average age = 60.0 ± 10.0 years). FIELD STRENGTH/SEQUENCE: T2WI, T1WI, multi-b value DWI, MR-based attenuation correction, and PET imaging on a 3.0 T whole-body PET/MR system. ASSESSMENT: The apparent diffusion coefficient (ADC), RSI-derived parameters (restricted diffusion f 1 $$ {f}_1 $$ , hindered diffusion f 2 $$ {f}_2 $$ , and free diffusion f 3 $$ {f}_3 $$ ) and the maximum standardized uptake value (SUVmax) were calculated and analyzed for diagnostic efficacy individually or in combination. STATISTICAL TESTS: Student's t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curves, Delong test, Spearman's correlation analysis. P < 0.05 was considered statistically significant. RESULTS: The f 1 $$ {f}_1 $$ , SUVmax were significantly higher, and f 3 $$ {f}_3 $$ , ADC were significantly lower in the malignant group [0.717 ± 0.131, 9.125 (5.753, 13.058), 0.194 ± 0.099, 1.240 (0.972, 1.407)] compared to the benign group [0.504 ± 0.236, 3.390 (1.673, 6.030), 0.398 ± 0.195, 1.485 ± 0.382]. The area under the ROC curve (AUC) values ranked from highest to lowest as follows: AUC (SUVmax) > AUC ( f 3 $$ {f}_3 $$ ) > AUC ( f 1 $$ {f}_1 $$ ) > AUC (ADC) > AUC ( f 2 $$ {f}_2 $$ ) (AUC = 0.819, 0.811, 0.770, 0.745, 0549). The AUC (AUC = 0.900) of the combined model of RSI with PET was significantly higher than that of either single-modality imaging. CONCLUSION: RSI-derived parameters ( f 1 $$ {f}_1 $$ , f 3 $$ {f}_3 $$ ) might help to distinguish primary benign and malignant lung lesions and the discriminatory utility of f 2 $$ {f}_2 $$ was not observed. The RSI exhibits comparable or potentially enhanced performance compared with DWI, and the combined RSI and PET model might improve diagnostic efficacy. TECHNICAL EFFICACY: Stage 2.

An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer.

OBJECTIVES: To develop an [18F]FDG PET/3D-UTE model based on clinical factors, three-dimensional ultrashort echo time (3D-UTE), and PET radiomics features via machine learning for the assessment of lymph node (LN) status in non-small cell lung cancer (NSCLC). METHODS: A total of 145 NSCLC patients (training, 101 cases; test, 44 cases) underwent whole-body [18F]FDG PET/CT and chest [18F]FDG PET/MRI were enrolled. Preoperative clinical factors and 3D-UTE, CT, and PET radiomics features were analyzed. The Mann-Whitney U test, LASSO regression, and SelectKBest were used for feature extraction. Five machine learning algorithms were used to establish prediction models, which were evaluated by the area under receiver-operator characteristic (ROC), DeLong test, calibration curves, and decision curve analysis (DCA). RESULTS: A prediction model based on random forest, consisting of four clinical factors, six 3D-UTE, and six PET radiomics features, was used as the final model for PET/3D-UTE. The AUCs of this model were 0.912 and 0.791 in the training and test sets, respectively, which not only showed different degrees of improvement over individual models such as clinical, 3D-UTE, and PET (AUC-training = 0.838, 0.834, and 0.828, AUC-test = 0.756, 0.745, and 0.768, respectively) but also achieved the similar diagnostic efficacy as the optimal PET/CT model (AUC-training = 0.890, AUC-test = 0.793). The calibration curves and DCA indicated good consistency (C-index, 0.912) and clinical utility of this model, respectively. CONCLUSION: The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using machine learning methods could noninvasively assess the LN status of NSCLC. CLINICAL RELEVANCE STATEMENT: A machine learning model of 18F-fluorodeoxyglucose positron emission tomography/ three-dimensional ultrashort echo time could noninvasively assess the lymph node status of non-small cell lung cancer, which provides a novel method with less radiation burden for clinical practice. KEY POINTS: • The 3D-UTE radiomics model using the PLS-DA classifier was significantly associated with LN status in NSCLC and has similar diagnostic performance as the clinical, CT, and PET models. • The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using the RF classifier could noninvasively assess the LN status of NSCLC and showed improved diagnostic performance compared to the clinical, 3D-UTE, and PET models. • In the assessment of LN status in NSCLC, the [18F]FDG PET/3D-UTE model has similar diagnostic efficacy as the [18F]FDG PET/CT model that incorporates clinical factors and CT and PET radiomics features.

Genome-wide redistribution of 24-nt siRNAs in rice gametes.

Gametes constitute a critical stage of the plant life cycle during which the genome undergoes reprogramming in preparation for embryogenesis. Here, we examined genome-wide distributions of small RNAs in the sperm and egg cells of rice. We found that 24-nt siRNAs, which are a hallmark of RNA-directed DNA methylation (RdDM) in plants, were depleted from heterochromatin boundaries in both gametes relative to vegetative tissues, reminiscent of siRNA patterns in DDM1-type nucleosome remodeler mutants. In sperm cells, 24-nt siRNAs were spread across heterochromatic regions, while in egg cells, 24-nt siRNAs were concentrated at a smaller number of heterochromatic loci throughout the genome, especially at loci which also produced siRNAs in other tissues. In both gametes, patterns of CHH methylation, typically a strong indicator of RdDM, were similar to vegetative tissues, although lower in magnitude. These findings indicate that the small RNA transcriptome undergoes large-scale redistribution in both male and female gametes, which is not correlated with recruitment of DNA methyltransferases in gametes and suggestive of unexplored regulatory activities of gamete small RNAs.

Semaphorin 4C regulates ovarian steroidogenesis through RHOA/ROCK1-mediated actin cytoskeleton rearrangement.

Semaphorins are a family of evolutionarily conserved morphogenetic molecules that were initially found to be associated with axonal guidance. Semaphorin 4C (Sema4C), a member of the fourth subfamily of semaphorins, has been demonstrated to play multifaceted and important roles in organ development, immune regulation, tumor growth, and metastasis. However, it is completely unknown whether Sema4C is involved in the regulation of ovarian function. We found that Sema4C was widely expressed in the stroma, follicles, and corpus luteum of mouse ovaries, and its expression was decreased at distinct foci in ovaries of mice of mid-to-advanced reproductive age. Inhibition of Sema4C by the ovarian intrabursal administration of recombinant adeno-associated virus-shRNA significantly reduced oestradiol, progesterone, and testosterone levels in vivo. Transcriptome sequencing analysis showed changes in pathways related to ovarian steroidogenesis and the actin cytoskeleton. Similarly, knockdown of Sema4C by siRNA interference in mouse primary ovarian granulosa cells or thecal interstitial cells significantly suppressed ovarian steroidogenesis and led to actin cytoskeleton disorganization. Importantly, the cytoskeleton-related pathway RHOA/ROCK1 was simultaneously inhibited after the downregulation of Sema4C. Furthermore, treatment with a ROCK1 agonist after siRNA interference stabilized the actin cytoskeleton and reversed the inhibitory effect on steroid hormones described above. In conclusion, Sema4C may play an important role in ovarian steroidogenesis through regulation of the actin cytoskeleton via the RHOA/ROCK1 signaling pathway. These findings shed new light on the identification of dominant factors involved in the endocrine physiology of female reproduction.

Inhibition of checkpoint kinase prevents human oocyte apoptosis induced by chemotherapy and allows enhanced tumour chemotherapeutic efficacy.

STUDY QUESTION: Could inhibition of the checkpoint kinase (CHEK) pathway protect human oocytes and even enhance the anti-tumour effects, during chemotherapy? SUMMARY ANSWER: CHEK inhibitors prevented apoptosis of human oocytes induced by chemotherapy and even enhanced the anti-tumour effects. WHAT IS KNOWN ALREADY: CHEK inhibitors showed ovarian protective effects in mice during chemotherapy, while their role in human oocytes is unclear. STUDY DESIGN, SIZE, DURATION: This experimental study evaluated the ovarian reserve of young patients (120 patients) with cancer, exposed or not exposed to taxane and platinum (TP)-combined chemotherapy. Single RNA-sequencing analysis of human primordial oocytes from 10 patients was performed to explore the mechanism of oocyte apoptosis induced by TP chemotherapy. The damaging effects of paclitaxel (PTX) and cisplatin on human oocytes were also evaluated by culturing human ovaries in vitro. A new mouse model that combines human ovarian xenotransplantation and patient-derived tumour xenografts was developed to explore adjuvant therapies for ovarian protection. The mice were randomly allocated to four groups (10 mice for each group): control, cisplatin, cisplatin + CK1 (CHEK1 inhibitor, SCH 900776), and cisplatin + CK2 (CHEK2 inhibitor, BML277). PARTICIPANTS/MATERIALS, SETTING, METHODS: In the prospective cohort study, human ovarian follicles were counted and serum AMH levels were evaluated. RNA-sequencing analysis was conducted, and staining for follicular damage (phosphorylated H2AX histone; γH2AX), terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labelling (TUNEL) assays and assessments of apoptotic biomarkers (western blot and immunofluorescence) were conducted in human ovaries. After the treatments, histological analysis was performed on human ovarian samples to investigate follicular populations, and oocyte damage was measured by γH2AX staining, BAX staining, and TUNEL assays. At the same time, the tumours were evaluated for volume, weight, and apoptosis levels. MAIN RESULTS AND THE ROLE OF CHANCE: Patients who received TP chemotherapy showed decreased ovarian reserves. Single RNA-sequencing analysis of human primordial oocytes indicated that TP chemotherapy induced apoptosis of human primordial oocytes by causing CHEK-mediated TAp63α phosphorylation. In vitro culture of human ovaries showed greater damaging effects on oocytes after cisplatin treatment compared with that after PTX treatment. Using the new animal model, CHEK1/2 inhibitors prevented the apoptosis of human oocytes induced by cisplatin and even enhanced its anti-tumour effects. This protective effect appeared to be mediated by inhibiting DNA damage via the CHEK-TAp63α pathway and by generation of anti-apoptotic signals in the oocytes. LARGE SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: This was a preclinical study performed with human ovarian samples, and clinical research is required for validation. WIDER IMPLICATIONS OF THE FINDINGS: These findings highlight the therapeutic potential of CHEK1/2 inhibitors as a complementary strategy for preserving fertility in female cancer patients. STUDY FUNDING/COMPETING INTEREST(S): This work was financially supported by the National Natural Science Foundation of China (nos. 82001514 and 81902669) and the Fundamental Research Funds for the Central Universities (2021yjsCXCY087). The authors declare no conflict of interest.

Fibroadipose vascular anomaly: a clinicopathological study of 75 cases.

AIMS: Fibroadipose vascular anomaly (FAVA) is a complex vascular malformation that is likely to be under-recognised. In this study we aimed to report the pathological features and somatic PIK3CA mutations associated with the most common clinicopathological features. METHODS AND RESULTS: Cases were identified by reviewing the lesions resected from patients with FAVA registered at our Haemangioma Surgery Centre and unusual intramuscular vascular anomalies in our pathology database. There were 23 males and 52 females, who ranged in age from 1 to 51 years. Most cases occurred in the lower extremities (n = 62). The majority of the lesions were intramuscular, with a few disrupting the overlying fascia and involving subcutaneous fat (19 of 75), and a minority of the cases had cutaneous vascular stains (13 of 75). Histopathologically, the lesion was composed of anomalous vascular components that were intertwined with mature adipocytic and dense fibrous tissues and vascular components with: (a) clusters of thin-walled channels, some with blood-filled nodules and others with thin walls resembling pulmonary alveoli; (b) numerous small vessels (arteries, veins and indeterminate channels) - proliferative small blood vessels were often mixed with adipose tissue; (c) larger abnormal venous channels usually irregularly and sometimes excessively muscularised; (d) lymphoid aggregates or lymphoplasmacytic aggregates were usually observed; and (e) lymphatic malformations were sometimes seen as minor elements. All patients had their lessons subjected to PCR, and 53 patients had somatic PIK3CA mutations (53 of 75). CONCLUSIONS: FAVA is a slow-flow vascular malformation with specific clinicopathological and molecular characteristics. Its recognition is fundamental for its clinical/prognostic implications and for targeted therapy.

Amide Proton Transfer-Weighted Imaging and Multiple Models Intravoxel Incoherent Motion-Based 18 F-FDG PET/MRI for Predicting Progression-Free Survival in Non-Small Cell Lung Cancer.

BACKGROUND: Amide proton transfer-weighted imaging (APTWI) and multiple models intravoxel incoherent motion (IVIM) based 18 F-FDG PET/MR could reflect the microscopic information of the tumor from multiple perspectives. However, its value in the prognostic assessment of non-small cell lung cancer (NSCLC) still needs to be further explored. PURPOSE: To determine whether pretreatment APTWI, mono-, bi-, and stretched-exponential model IVIM, and 18 F-FDG PET-derived parameters of the primary lesion may be associated with progression-free survival (PFS) in NSCLC. STUDY TYPE: Prospective. POPULATION: Seventy-seven patients (mean age, 62 years, range, 20-81 years) with 37 men and 40 women were included. FIELD STRENGTH/SEQUENCE: 3.0 T 18 F-FDG PET/MRI, single shot echo planar imaging sequences for IVIM and fast spin-echo sequences with magnetization transfer pulses for APTWI. ASSESSMENT: Patient clinical characteristics (age, sex, smoke, subtype, TNM stage, and surgery), PFS (chest CT every 3 months, median follow-up was 18 months, range, 4-27 months), and APTWI (MTRasym(3.5 ppm)), IVIM (ADCstand , D, D*, f, DDC, and α), and 18 F-FDG PET (SUVmax , MTV, and TLG) parameters were recorded. STATISTICAL TESTS: Proportional hazards model, concordance index, calibration curve, decision curve analysis (DCA), and Log-rank test. A P value <0.05 was considered statistically significant. RESULTS: Histological subtype, TNM stage, MTV, D*, and MTRasym(3.5 ppm) were all independent predictors of PFS. A prediction model based on these predictors was developed with a C-index of 0.895 (95% CI: 0.839-0.951), which was significantly superior to each of the above predictors alone (C-index = 0.629, 0.707, 0.692, 0.678, and 0.558, respectively). The calibration curve and DCA indicated good consistency and clinical utility of the prediction model, respectively. Log-rank test results showed a significant difference in PFS between the high- and low-risk groups. DATA CONCLUSION: APTWI and multiple models IVIM based 18 F-FDG PET/MRI can be used for PFS assessment in NSCLC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Development and validation of the OSASH score to predict overall survival of hepatocellular carcinoma after surgical resection: a dual-institutional study.

OBJECTIVE: To develop and validate a risk score based on preoperative clinical-radiological parameters for predicting overall survival (OS) in patients undergoing surgical resection for hepatocellular carcinoma (HCC). METHODS: From July 2010 to December 2021, consecutive patients with surgically-proven HCC who underwent preoperative contrast-enhanced MRI were retrospectively enrolled. A preoperative OS risk score was constructed in the training cohort using a Cox regression model and validated in a propensity score-matched internal validation cohort and an external validation cohort. RESULTS: A total of 520 patients were enrolled, among whom 210, 210, and 100 patients were from the training, internal validation, and external validation cohorts, respectively. Independent predictors for OS included incomplete tumor "capsule," mosaic architecture, tumor multiplicity, and serum alpha-fetoprotein, which were incorporated into the "OSASH score." The C-index the OSASH score was 0.85, 0.81, and 0.62 in the training, internal, and external validation cohorts, respectively. Using 32 as the cutoff point, the OSASH score stratified patients into prognostically distinct low- and high-risk groups among all study cohorts and six subgroups (all p < 0.05). Furthermore, patients with BCLC stage B-C HCC and OSASH-low risk achieved comparable OS to that of patients with BCLC stage 0-A HCC and OSASH-high risk in the internal validation cohort (5-year OS rates, 74.7 vs. 77.8%; p = 0.964). CONCLUSION: The OSASH score may help predict OS in HCC patients undergoing hepatectomy and identify potential surgical candidates among those with BCLC stage B-C HCC. CLINICAL RELEVANCE STATEMENT: By incorporating three preoperative MRI features and serum AFP, the OSASH score may help predict postsurgical overall survival in patients with hepatocellular carcinoma and identify potential surgical candidates among those with BCLC stage B and C HCC. KEY POINTS: • The OSASH score incorporating three MRI features and serum AFP can be used to predict OS in HCC patients who received curative-intent hepatectomy. • The score stratified patients into prognostically distinct low- and high-risk strata in all study cohorts and six subgroups. • Among patients with BCLC stage B and C HCC, the score identified a subgroup of low-risk patients who achieved favorable outcomes after surgery.

Deep learning-based dynamic PET parametric Ki image generation from lung static PET.

OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric Ki provides better quantification and improve specificity for cancer detection. However, parametric imaging is difficult to implement clinically due to the long acquisition time (~ 1 h). We propose a dynamic parametric imaging method based on conventional static PET using deep learning. METHODS: Based on the imaging data of 203 participants, an improved cycle generative adversarial network incorporated with squeeze-and-excitation attention block was introduced to learn the potential mapping relationship between static PET and Ki parametric images. The image quality of the synthesized images was qualitatively and quantitatively evaluated by using several physical and clinical metrics. Statistical analysis of correlation and consistency was also performed on the synthetic images. RESULTS: Compared with those of other networks, the images synthesized by our proposed network exhibited superior performance in both qualitative and quantitative evaluation, statistical analysis, and clinical scoring. Our synthesized Ki images had significant correlation (Pearson correlation coefficient, 0.93), consistency, and excellent quantitative evaluation results with the Ki images obtained in standard dynamic PET practice. CONCLUSIONS: Our proposed deep learning method can be used to synthesize highly correlated and consistent dynamic parametric images obtained from static lung PET. KEY POINTS: • Compared with conventional static PET, dynamic PET parametric Ki imaging has been shown to provide better quantification and improved specificity for cancer detection. • The purpose of this work was to develop a dynamic parametric imaging method based on static PET images using deep learning. • Our proposed network can synthesize highly correlated and consistent dynamic parametric images, providing an additional quantitative diagnostic reference for clinicians.

Characterizing worker compensation claims in long-term care and examining the association between facility characteristics and severe injury: a repeated cross-sectional study from Alberta, Canada.

BACKGROUND: Despite the physical demands and risks inherent to working in long-term care (LTC), little is known about workplace injuries and worker compensation claims in this setting. The purpose of this study was to characterize workplace injuries in LTC and to estimate the association between worker and organizational factors on severe injury. METHODS: We used a repeated cross-sectional design to examine worker compensation claims between September 1, 2014 and September 30, 2018 from 25 LTC homes. Worker compensation claim data came from The Workers Compensation Board of Alberta. LTC facility data came from the Translating Research in Elder Care program. We used descriptive statistics to characterize the sample and multivariable logistic regression to estimate the association between staff, organizational, and resident characteristics and severe injury, measured as 31+ days of disability. RESULTS: We examined 3337 compensation claims from 25 LTC facilities. Less than 10% of claims (5.1%, n = 170) resulted in severe injury and most claims did not result in any days of disability (70.9%, n = 2367). Most of the sample were women and over 40 years of age. Care aides were the largest occupational group (62.1%, n = 2072). The highest proportion of claims were made from staff working in voluntary not for profit facilities (41.9%, n = 1398) followed by public not for profit (32.9%, n = 1098), and private for profit (n = 25.2%, n = 841). Most claims identified the nature of injury as traumatic injuries to muscles, tendons, ligaments, or joints. In the multivariable logistic regression, higher staff age (50-59, aOR: 2.26, 95% CI 1.06-4.83; 60+, aOR: 2.70, 95% CI 1.20-6.08) was associated with more severe injury, controlling for resident acuity and other organizational staffing factors. CONCLUSIONS: Most claims were made by care aides and were due to musculoskeletal injuries. In LTC, few worker compensation claims were due to severe injury. More research is needed to delve into the specific features of the LTC setting that are related to worker injury.

MiR-145 regulates steroidogenesis in mouse primary granulosa cells by targeting Arpc5 and subsequent cytoskeleton remodeling.

MicroRNA (miR)-145 is enriched in the follicular granulosa cells (GCs) of 3-week-old mice. Downregulating miR-145 inhibits the proliferation and differentiation of GCs and induces evident changes in their cytoskeleton. In this study, we examined how miR-145 induces cytoskeletal changes in mouse GCs and its potential mechanism in regulating GC steroidogenesis. We found that actin related protein 2/3 complex subunit 5 (Arpc5) is a target of miR-145. The miR-145 antagomir increased ARPC5 expression but not ß-ACTIN, ß-TUBULIN, and PAXILLIN expression. Arpc5 overexpression inhibited GC proliferation, differentiation, and progesterone synthesis. Furthermore, the expression of progesterone synthesis-associated enzymes was downregulated in the Arpc5 overexpression group, and the GC cytoskeleton exhibited evident changes. We conclude that Arpc5, a new target of miR-145, regulates primary GC proliferation and progesterone production by regulating the cytoskeleton remodeling.

Radiomics-based machine learning approach in differentiating fibro-adipose vascular anomaly from venous malformation.

BACKGROUND: As a complex vascular malformation, fibro-adipose vascular anomaly was first proposed in 2014. Its overlap with other vascular malformations regarding imaging and clinical features often leads to misdiagnosis and improper management. OBJECTIVE: To construct a radiomics-based machine learning model to help radiologists differentiate fibro-adipose vascular anomaly from common venous malformations. MATERIALS AND METHODS: We retrospectively analyzed 178 children, adolescents and young adults with vascular malformations (41 fibro-adipose vascular anomaly and 137 common vascular malformation cases) who underwent MRI before surgery between May 2012 to January 2021. We extracted radiomics features from T1-weighted images and fat-saturated (FS) T2-weighted images and further selected features through least absolute shrinkage and selection operator (LASSO) and Boruta methods. We established eight weighted logistic regression classification models based on various combinations of feature-selection strategies (LASSO or Boruta) and sequence types (single- or multi-sequence). Finally, we evaluated the performance of each model by the mean area under the receiver operating characteristics curve (ROC-AUC), sensitivity and specificity in 10 runs of repeated k-fold (k = 10) cross-validation. RESULTS: Two multi-sequence models based on axial FS T2-W, coronal FS T2-W and axial T1-W images showed promising performance. The LASSO-based multi-sequence model achieved an AUC of 97%±3.8, a sensitivity of 94%±12.4 and a specificity of 89%±9.0. The Boruta-based multi-sequence model achieved an AUC of 97%±3.7, a sensitivity of 95%±10.5 and a specificity of 87%±9.0. CONCLUSION: The radiomics-based machine learning model can provide a promising tool to help distinguish fibro-adipose vascular anomaly from common venous malformations.

Inferring the Regulatory Network of miRNAs on Terpene Trilactone Biosynthesis Affected by Environmental Conditions.

As a medicinal tree species, ginkgo (Ginkgo biloba L.) and terpene trilactones (TTLs) extracted from its leaves are the main pharmacologic activity constituents and important economic indicators of its value. The accumulation of TTLs is known to be affected by environmental stress, while the regulatory mechanism of environmental response mediated by microRNAs (miRNAs) at the post-transcriptional levels remains unclear. Here, we focused on grafted ginkgo grown in northwestern, southwestern, and eastern-central China and integrally analyzed RNA-seq and small RNA-seq high-throughput sequencing data as well as metabolomics data from leaf samples of ginkgo clones grown in natural environments. The content of bilobalide was highest among detected TTLs, and there was more than a twofold variation in the accumulation of bilobalide between growth conditions. Meanwhile, transcriptome analysis found significant differences in the expression of 19 TTL-related genes among ginkgo leaves from different environments. Small RNA sequencing and analysis showed that 62 of the 521 miRNAs identified were differentially expressed among different samples, especially the expression of miRN50, miR169h/i, and miR169e was susceptible to environmental changes. Further, we found that transcription factors (ERF, MYB, C3H, HD-ZIP, HSF, and NAC) and miRNAs (miR319e/f, miRN2, miRN54, miR157, miR185, and miRN188) could activate or inhibit the expression of TTL-related genes to participate in the regulation of terpene trilactones biosynthesis in ginkgo leaves by weighted gene co-regulatory network analysis. Our findings provide new insights into the understanding of the regulatory mechanism of TTL biosynthesis but also lay the foundation for ginkgo leaves' medicinal value improvement under global change.

Genome-Scale Sequence Disruption Following Biolistic Transformation in Rice and Maize.

Biolistic transformation delivers nucleic acids into plant cells by bombarding the cells with microprojectiles, which are micron-scale, typically gold particles. Despite the wide use of this technique, little is known about its effect on the cell's genome. We biolistically transformed linear 48-kb phage lambda and two different circular plasmids into rice (Oryza sativa) and maize (Zea mays) and analyzed the results by whole genome sequencing and optical mapping. Although some transgenic events showed simple insertions, others showed extreme genome damage in the form of chromosome truncations, large deletions, partial trisomy, and evidence of chromothripsis and breakage-fusion bridge cycling. Several transgenic events contained megabase-scale arrays of introduced DNA mixed with genomic fragments assembled by nonhomologous or microhomology-mediated joining. Damaged regions of the genome, assayed by the presence of small fragments displaced elsewhere, were often repaired without a trace, presumably by homology-dependent repair (HDR). The results suggest a model whereby successful biolistic transformation relies on a combination of end joining to insert foreign DNA and HDR to repair collateral damage caused by the microprojectiles. The differing levels of genome damage observed among transgenic events may reflect the stage of the cell cycle and the availability of templates for HDR.

Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.

PURPOSE: Total-body dynamic positron emission tomography/computed tomography (PET/CT) provides much sensitivity for clinical imaging and research, bringing new opportunities and challenges regarding the generation of total-body parametric images. This study investigated parametric [Formula: see text] images directly generated from static PET images without an image-derived input function on a 2-m total-body PET/CT scanner (uEXPLORER) using a deep learning model to significantly reduce the dynamic scanning time and improve patient comfort. METHODS: [Formula: see text]F-Fluorodeoxyglucose ([Formula: see text]F-FDG) 2-m total-body PET/CT image pairs were acquired for 200 patients (scanned once) with two protocols: one parametric PET image (60 min, 0[Formula: see text]60 min) and one static PET image (10 min, range of 50[Formula: see text]60 min). A deep learning model was implemented to predict parametric [Formula: see text] images from the static PET images. Evaluation metrics, including the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and normalized mean square error (NMSE), were calculated for a 10-fold cross-validation assessment. Moreover, image quality was assessed by two nuclear medicine physicians in terms of clinical readings. RESULTS: The synthetic parametric PET images were qualitatively and quantitatively consistent with the reference images. In particular, the global mean SSIM between the synthetic and reference parametric [Formula: see text] images exceeded 0.9 across all test patients. On the other hand, the overall subjective quality of the synthetic parametric PET images was 4.00 ± 0.45 (the highest possible rating is 5) according to the two expert nuclear medicine physicians. CONCLUSION: The findings illustrated the feasibility of the proposed technique and its potential to reduce the required scanning duration for 2-m total-body dynamic PET/CT systems. Moreover, this study explored the potential of direct parametric image generation with uEXPLORER. Deep learning technologies may output high-quality synthetic parametric images, and the validation of clinical applications and the interpretability of network models still need further research in future works.

A Comparative Study of Amide Proton Transfer Weighted Imaging and Intravoxel Incoherent Motion MRI Techniques Versus (18) F-FDG PET to Distinguish Solitary Pulmonary Lesions and Their Subtypes.

BACKGROUND: Amide proton transfer weighted imaging (APTw), intravoxel incoherent motion (IVIM), and positron emission tomography (PET) imaging all have the potential to characterize solitary pulmonary lesions (SPLs). PURPOSE: To compare APTw and IVIM with PET imaging for distinguishing between benign and malignant SPLs and their subtypes. STUDY TYPE: Prospective. POPULATION: Ninety-five patients, 78 with malignant SPLs (including 48 with adenocarcinoma [AC] and 17 with squamous cell carcinoma [SCC]), and 17 with benign SPLs. FIELD STRENGTH/SEQUENCE: Fast spin-echo (FSE) T2WI, FSE APTw and echo-planar imaging IVIM, MR-base attenuation correction (MRAC), and PET imaging on a 3-T whole-body PET/MR system. ASSESSMENT: The magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and the maximum standardized uptake value (SUVmax) were analyzed. STATISTICAL TESTS: Individual sample t-test, Delong test, Pearson's correlation analysis, and area under the receiver operating characteristic curve (AUC). P < 0.05 indicated statistical significance. RESULTS: The MTRasym and SUVmax were significantly higher, and D was significantly lower in the malignant group (3.3 ± 2.6 [%], 7.8 ± 5, and 1.2 ± 0.3 [×10-3 mm2 /second]) compared to the benign group (-0.3 ± 1.6 [%], 3.1 ± 3.8, and 1.6 ± 0.3 [×10-3 mm2 /second]). The MTRasym and D were significantly lower, and SUVmax was significantly higher in the SCC group (0.8 ± 1.0 [%], 1.0 ± 0.2 [×10-3 mm2 /second] than in the AC group (4.1 ± 2.6 [%], 1.3 ± 0.3 [×10-3 mm2 /second], 6.7 ± 4.6). Besides, the combination (AUC = 0.964) of these three methods showed higher diagnostic efficacy than any individual method (AUC = 0.917, 0.851, 0.82, respectively) in identifying malignant and benign SPLs. However, APTw showed better diagnostic efficacy than the combination of three methods or PET imaging alone in distinguishing SCC and AC groups (AUC = 0.934, 0.781, 0.725, respectively). DATA CONCLUSION: APTw, IVIM, and PET imaging are all effective methods to distinguish benign and malignant SPLs and their subtypes. APTw is potentially more capable than PET imaging of distinguishing lung SCC from AC. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Evaluation of Amide Proton Transfer-Weighted Imaging for Lung Cancer Subtype and Epidermal Growth Factor Receptor: A Comparative Study With Diffusion and Metabolic Parameters.

BACKGROUND: Lung cancer is one of the most devastating diseases worldwide, and it is meaningful to assess the subtype and epidermal growth factor receptor (EGFR) status in lung cancer noninvasively by imaging methods. PURPOSE: To differentiate noninvasively small cell lung cancer (SCLC) from nonsmall cell lung cancer (NSCLC), and EGFR mutation-type from wild-type NSCLC by comparing amide proton transfer-weighted imaging (APTWI), diffusion-weighted imaging (DWI), and 2-[18 F]-fluoro-2-deoxy-d-glucose positron emission tomography (18 F-FDG PET). STUDY TYPE: Prospective. POPULATION: A total of 99 patients with lung cancer. FIELD STRENGTH/SEQUENCE: APTWI and DWI at 18 F-FDG PET/MRI 3.0 T. ASSESSMENT: The apparent diffusion coefficient (ADC), magnetization transfer ratio asymmetry (MTRasym [3.5 ppm]), maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated and compared. STATISTICAL TESTS: Individual sample t-test, Mann-Whitney U test, Logistic regression, and P < 0.05 were considered statistically significant. RESULTS: In NSCLC, MTRasym (3.5 ppm), MTV, and TLG were significantly lower and ADC was significantly higher than in SCLC; MTRasym (3.5 ppm) was significantly higher and SUVmax , MTV, and TLG were significantly lower in EGFR mutation-type NSCLC than in EGFR wild-type NSCLC. In the identification of SCLC and NSCLC, MTRasym (3.5 ppm), ADC, and MTV were independent predictors, the AUCs of the combination of independent predictors, MTV, TLG, MTRasym (3.5 ppm), and ADC were 0.942, 0.875, 0.843, 0.814, and 0.687, respectively. In the identification of EGFR mutation-type and wild-type NSCLC, MTRasym (3.5 ppm) and MTV were independent predictors, the AUCs of the combination of independent predictors, TLG, MTV, MTRasym (3.5 ppm), and SUVmax were 0.919, 0.834, 0.813, 0.795, and 0.771, respectively. DATA CONCLUSION: In the noninvasive assessment of lung cancer subtype and EGFR status, APTWI has similar utility to diffusion and metabolic parameters. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma.

BACKGROUND: Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma. PURPOSE: To explore the value of simultaneous 18 F-fluorodeoxyglucose (18 F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters. STUDY TYPE: Prospective. POPULATION: Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI. FIELD STRENGTH/SEQUENCE: 3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and 18 F-FDG PET. ASSESSMENT: DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed. STATISTICAL TESTS: Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant. RESULTS: The SUVmax , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N = 35) and low Ki-67 PI groups (N = 43). D, SUVmax , and MTV independently predicted the Ki-67 PI status. The combination of D, SUVmax , and MTV had the largest area under the ROC curve (AUC = 0.900), which was significantly larger than the AUC alone of DDC (AUC = 0.725), SUVmax (AUC = 0.815), MTV (AUC = 0.774), or TLG (AUC = 0.783). The perfusion fraction did not correlate with SUVmax , MTV, or TLG (r = -0.03, -0.11, and -0.04, respectively; P = 0.786, 0.348, and 0.733). DATA CONCLUSION: The combination of D, SUVmax , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Predicting microvascular invasion in hepatocellular carcinoma: A dual-institution study on gadoxetate disodium-enhanced MRI.

BACKGROUND & AIMS: Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but its diagnosis mandates postoperative histopathologic analysis. We aimed to develop and externally validate a predictive scoring system for MVI. METHODS: From July 2015 to November 2020, consecutive patients underwent surgery for HCC with preoperative gadoxetate disodium (EOB)-enhanced MRI was retrospectively enrolled. All MR images were reviewed independently by two radiologists who were blinded to the outcomes. In the training centre, a radio-clinical MVI score was developed via logistic regression analysis against pathology. In the testing centre, areas under the receiver operating curve (AUCs) of the MVI score and other previous MVI schemes were compared. Overall survival (OS) and recurrence-free survival (RFS) were analysed by the Kaplan-Meier method with the log-rank test. RESULTS: A total of 417 patients were included, 195 (47%) with pathologically-confirmed MVI. The MVI score included: non-smooth tumour margin (odds ratio [OR] = 4.4), marked diffusion restriction (OR = 3.0), internal artery (OR = 3.0), hepatobiliary phase peritumoral hypointensity (OR = 2.5), tumour multifocality (OR = 1.6), and serum alpha-fetoprotein >400 ng/mL (OR = 2.5). AUCs for the MVI score were 0.879 (training) and 0.800 (testing), significantly higher than those for other MVI schemes (testing AUCs: 0.648-0.684). Patients with model-predicted MVI had significantly shorter OS (median 61.0 months vs not reached, P < .001) and RFS (median 13.0 months vs. 42.0 months, P < .001) than those without. CONCLUSIONS: A preoperative MVI score integrating five EOB-MRI features and serum alpha-fetoprotein level could accurately predict MVI and postoperative survival in HCC. Therefore, this score may aid in individualized treatment decision making.