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Triangle completion is a task widely used to study human path integration, an important navigation method relying on idiothetic cues. Systematic biases (compression patterns in the inbound responses) have been well documented in human triangle completion. However, the sources of systematic biases remain controversial. We used cross-validation modeling to compare three plausible theoretical models that assume that systematic errors occur in the encoding outbound path solely (encoding-error model), executing the inbound responses solely (execution-error model), and both (bicomponent model), respectively. The data for cross-validation modeling are from a previous study (Qi et al., 2021), in which participants learned three objects' locations (one at the path origin, that is, home) very well before walking each outbound path and then pointed to the objects' original locations after walking the outbound path. The modeling algorithm used one inbound response (i.e., response to the home) or multiple inbound responses (i.e., responses to two nonhome locations and the home) for each outbound path. The algorithm of using multiple inbound responses demonstrated that the bicomponent model outperformed the other models in accounting for the systematic errors. This finding suggests that both encoding the outbound path and executing the inbound responses contribute to the systematic biases in human path integration. In addition, the results showed that the algorithm using only the home response could not distinguish among these 3 models, suggesting that the typical triangle-completion task with only the home response for each outbound path cannot determine the sources of the systematic biases. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Pancreatic adenocarcinoma (PDAC) is one of the deadliest cancers, and it is resistant to most conventional antineoplastic therapies. To address this challenge, gemcitabine (Gem)-loaded carbonaceous nanoparticles (MFC-Gem) as nanozymes and a theranostic platform were fabricated and used for MR-guided ferroptosis-chemo synergetic therapy of PDAC. As a biocompatible carrier, MFC-Gem nanoparticles are regarded as peroxidase-like and glutathione peroxidase-like nanozymes that promote ferroptosis therapy by effectively generating ROS and consuming GSH. Meanwhile, the combination of MnFe

Thylakoid membrane protein quality control (PQC), which requires the coordination of membrane protein translocation and degradation of unassembled proteins, determines chloroplast development during de-etiolation. Despite numerous efforts, the regulation of this process in land plants is largely unknown. Here, we report the isolation and characterization of pale green Arabidopsis4 (pga4) mutants in Arabidopsis (Arabidopsis thaliana) with defects in chloroplast development during de-etiolation. Map-based cloning and complementation assays confirmed that PGA4 encodes the chloroplast Signal Recognition Particle 54 kDa (cpSRP54) protein. A heterogeneous Light-Harvesting Chlorophyll a/b Binding-Green Fluorescent Protein (LhcB2-GFP) fusion protein was generated as an indicative reporter for cpSRP54-mediated thylakoid translocation. LhcB2-GFP was dysfunctional and degraded to a short-form dLhcB2-GFP during de-etiolation through an N-terminal degradation initiated on thylakoid membranes. Further biochemical and genetic evidence demonstrated that the degradation of LhcB2-GFP to dLhcB2-GFP was disrupted in pga4 and yellow variegated2 (var2) mutants caused by mutations in the Filamentous Temperature-Sensitive H2 (VAR2/AtFtsH2) subunit of thylakoid FtsH. The yeast two-hybrid assay showed that the N-terminus of LhcB2-GFP interacts with the protease domain of VAR2/AtFtsH2. Moreover, the over-accumulated LhcB2-GFP in pga4 and var2 formed protein aggregates, which were insoluble in mild nonionic detergents. Genetically, cpSRP54 is a suppressor locus for the leaf variegation phenotype of var2. Together, these results demonstrate the coordination of cpSRP54 and thylakoid FtsH in maintaining thylakoid membrane PQC during the assembly of photosynthetic complexes and provide a trackable substrate and product for monitoring cpSRP54-dependent protein translocation and FtsH-dependent protein degradation.

The metastatic or recurrent potential of localized human papillomavirus-associated endocervical adenocarcinoma (HPVA EAC) is difficult to predict, especially based upon biopsy alone. Recent analyses of small cohorts indicate that high tumor nuclear grade (TNG) and the presence of necrotic tumor debris (NTD) from HPVA EACs in cervical biopsy specimens are highly predictive of nodal metastasis (NM). In the present study, we aimed to investigate how reliably tumoral morphologic features from cervical biopsy specimens predict NM or tumor recurrence (TR) and patient outcomes in a large cohort of endocervical adenocarcinoma patients. A cohort comprised of 397 patients with HPVA EAC treated at 18 institutions was identified, and cervical biopsies were paired with their associated complete tumor resections for a total of 794 specimens. A variety of tumoral histologic features were examined for each paired specimen, including TNG (assessed on a 3-tiered scale of increasing abnormalities-TNG1, TNG2, TNG3) and NTD (defined by the presence of necrotic and apoptotic tumor cells within tumor glandular lumens admixed with granular and eosinophilic amorphous material and inflammatory cells), which were correlated with outcomes. The distribution of TNG in biopsies was as follows: 86 (21.7%) TNG1, 223 (56.2%) TNG2, and 88 (22.2%) TNG3. NTD was identified in 176 (44%) of the biopsy specimens. The sensitivity, specificity, positive predictive value, and negative predictive value of a TNG1 assignment in the biopsy being predictive of the same assignment in the full resection were 0.82 (95% confidence interval [CI]: 0.7-0.9), 0.895 (0.86-0.93), 0.593 (0.48-0.696), and 0.96 (0.94-0.98), respectively. Respective values for an NTD-negative status were 0.89 (95% CI: 0.83-0.92), 0.715 (0.64-0.77), 0.72 (0.65-0.77), and 0.89 (0.83-0.93), respectively. Compared with the other cases in each category, both TNG1 and an NTD-negative status were each significantly associated with lower rates of NM (odds ratio for TNG1=0.245, 95% CI: 0.070-0.857, P=0.0277; for NTD=0.199, 95% CI: 0.094-0.421, P

Background The value of measuring mechanical properties to categorize various pathophysiologic states of the liver is as yet undetermined in chronic hepatitis B (CHB) or C (CHC). Purpose To evaluate multiparametric three-dimensional (3D) MR elastography as a means of detecting early necroinflammation, distinguishing necroinflammation from fibrosis, and gauging the severity of portal hypertension (PH) in CHB or CHC. Materials and Methods From January 2015 to September 2019, participants with CHB or CHC were prospectively enrolled from a single institution and were divided into two groups: those with liver biopsy and no evidence of PH (group 1) and those with PH and a hepatic venous pressure gradient (HVPG) measurement (group 2). For group 3, healthy volunteers were separately recruited from a nearby community. Multiple viscoelastic parameters (shear stiffness [SS], storage modulus, loss modulus, and damping ratio [DR]) were determined at 3D MR elastography at 60 Hz, and multivariable logistic or linear regression analysis was used to assess associations of mechanical parameters with histologic scores and HVPG. Results A total of 155 participants (median age, 41 years [interquartile range, 32-48 years]; 85 women) were in group 1 (training set: n = 78, validation set: n = 77), 85 participants (median age, 57 years [interquartile range, 43-61 years]; 51 women) in group 2, and 60 healthy volunteers (median age, 49 years [interquartile range, 27-64 years]; 38 men) in group 3. The liver DR was higher in participants with necroinflammation (DR, 0.13 ± 0.03) versus those without (at liver fibrosis stage F0) (DR, 0.10 ± 0.02; P < .001). Liver DR and SS together performed well in the diagnosis of necroinflammation (area under the receiver operating characteristic curve [AUC], 0.88 [95% CI: 0.79, 0.96]) and the scoring of moderate to severe activity (AUC, 0.88 [95% CI: 0.81, 0.95]) in the validation data set. Liver DR (regression coefficient [β] = -30.3 [95% CI: -58.0, -2.5]; P = .03) and splenic SS (β = 2.3 [95% CI: 1.7, 2.9]; P < .001) were independently associated with HVPG. Conclusion Three-dimensional MR elastography may detect early necroinflammation, distinguish necroinflammation from liver fibrosis, and correlate with hepatic venous pressure gradient in chronic hepatitis B and C. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Reeder in this issue.

Immune checkpoint blockade has become a paradigm-shifting treatment modality to combat cancer, while conventional administration of immune checkpoint inhibitors, such as anti-PD-L1 antibody (α-PD-L1), often shows unsatisfactory immune responses and lead to severe immune-related adverse effects (irAEs). Herein, we develop a PD-L1 aptamer-based spherical nucleic acids (SNAs), which consists of oxaliplatin (OXA) encapsulated in a metal-organic framework nanoparticle core and a dense shell of aptPD-L1 (denoted as M@O-A). Upon light irradiation, this nanosystem enables concurrent photodynamic therapy (PDT), chemotherapy, and enhanced immunotherapy in one shot to inhibit both primary colorectal tumors and untreated distant tumors in mice. Notably, M@O-A shows scarcely any systemic immunotoxicity in a clinical irAEs-mimic transgenic mouse model. Collectively, this study presents a novel strategy for priming robust photo-immunotherapy against cancer with enhanced safety.

The endometrium undergoes morphological and functional changes during menstrual cycles, regulated by female hormones. MRI T2 weighted imaging (T2WI) plays an essential role in endometrial disease evaluation. This study aims to define the cyclic course of endometrial T2 values and thickness and explore their relationship with basal female sex hormones. We prospectively recruited 38 healthy volunteers (20–30 years:22; 30–40 years:16), 3.0 T MR were performed during the menstrual phase (MP), follicular phase (FP), peri-ovulation phase (OP), and luteal phase (LP). Basal serum oestradiol (E), progesterone (P), luteinizing hormone (LH) and follicle stimulating hormone (FSH) hormone was tested. Endometrium thicknesses, T2 values were obtained in each phase. Pearson correlation test, Fisher's least significant difference (LSD) test, the analysis of variance (ANOVA) test, and the paired sample t test were applied. The endometrium thickness was significantly thinner in the younger age group (p

To develop an imaging-derived biomarker for prediction of overall survival (OS) of pancreatic cancer by analyzing preoperative multiphase contrast-enhanced computed topography (CECT) using deep learning.Exploiting prognostic biomarkers for guiding neoadjuvant and adjuvant treatment decisions may potentially improve outcomes in patients with resectable pancreatic cancer.This multicenter, retrospective study included 1516 patients with resected pancreatic ductal adenocarcinoma (PDAC) from 3 centers located in China. The discovery cohort (n=763), which included preoperative multiphase CECT scans and OS data from 2 centers, was used to construct a fully automated imaging-derived prognostic biomarker-DeepCT-PDAC-by training scalable deep segmentation and prognostic models (via self-learning) to comprehensively model the tumor-anatomy spatial relations and their appearance dynamics in multiphase CECT for OS prediction. The marker was independently tested using internal (n=574) and external validation cohorts (n=179, 3 centers) to evaluate its performance, robustness, and clinical usefulness.Preoperatively, DeepCT-PDAC was the strongest predictor of OS in both internal and external validation cohorts [hazard ratio (HR) for high versus low risk 2.03, 95% confidence interval (CI): 1.50-2.75; HR: 2.47, CI: 1.35-4.53] in a multivariable analysis. Postoperatively, DeepCT-PDAC remained significant in both cohorts (HR: 2.49, CI: 1.89-3.28; HR: 2.15, CI: 1.14-4.05) after adjustment for potential confounders. For margin-negative patients, adjuvant chemoradiotherapy was associated with improved OS in the subgroup with DeepCT-PDAC low risk (HR: 0.35, CI: 0.19-0.64), but did not affect OS in the subgroup with high risk.Deep learning-based CT imaging-derived biomarker enabled the objective and unbiased OS prediction for patients with resectable PDAC. This marker is applicable across hospitals, imaging protocols, and treatments, and has the potential to tailor neoadjuvant and adjuvant treatments at the individual level.

Hepatocellular carcinoma (HCC) is a common and highly malignant tumor that is prone to recurrence and metastasis and has no effective treatment. Unsurprisingly, its prognosis is quite poor; early detection methods and effective low-toxicity treatments are urgently needed. To achieve these goals, we designed a multifunctional, U.S. Food and Drug Administration-approved Prussian blue (PB) nanoparticle (NP) with a porous metal organic frame loaded with sorafenib (SF), conjugated with HCC-specific targeting peptide SP94 and the near-infrared dye cyanine (Cy)5.5. These NPs are amenable to multimodal imaging for dynamic monitoring of their biodistribution and tumor-targeting effects. The SP94-PB-SF-Cy5.5 NPs achieved targeted delivery and controlled SF release and exhibited good photothermal effects. In this strategy, photothermal therapy and SF treatment complement each other, reducing the side effects of SF and achieving a therapeutic effect without local tumor recurrence. In addition, the catalase-like ability of the NPs alleviates tumor hypoxia, and their photothermal effects induce immunogenic cell death, leading to the release of tumor-associated antigens. These effects combine to trigger an antitumor immune response; the NPs also displayed promising inhibitory effects on tumor metastasis and recurrence and produced an abscopal effect and long-term immunological memory when combined with antiprogrammed death-ligand 1 (PD-L1) immunotherapy. These safe, multifunctional NPs represent a valuable treatment option for HCC. In addition, this next-generation treatment model may provide some ideas for the management of HCC and other cancers.

Poster: "ECR 2017 / C-2942 / Morphological description of uterine scar one year after cesarean section by T2 3D SPACE 3.0T MR" by: "N. Ding, Y. Qi, Y. He, H. D. Xue, Z. Jin; Beijing/CN"

To identify quantitative imaging features of contrast-enhanced computed tomography (CE-CT) that may be prognostically favorable after resection of smaller (≤ 30 mm) pancreatic ductal adenocarcinomas (PDACs) located at head. This retrospective study included two independent cohorts (discovery cohort, n = 212; test cohort, n = 100) of patients who underwent resection of head PDACs ≤ 30 mm and preoperative CE-CT. We examined tumor and surrounding parenchymal attenuation differences (deltas), and tumor attenuation changes across phases (ratios). Semantic features of PDACs were evaluated by two radiologists. Clinicopathologic and imaging features for predicting disease-free survival (DFS) and overall survival (OS) were analyzed via multivariate Lasso-penalized Cox proportional-hazards models. Survival rates were derived by Kaplan-Meier method. Imaging features achieved C-indices of 0.766 (discovery cohort) and 0.739 (test cohort) for DFS, and 0.790 (discovery cohort) and 0.772 (test cohort) for OS estimates through incorporation of clinicopathologic features. The most decisive imaging feature was delta 3, denoting attenuation differences between tumor and surrounding pancreas at pancreatic phase (DFS: HR = 2.122; OS: HR = 2.375; both p

Background Biopsy Gleason score (GS) is crucial for prostate cancer (PCa) treatment decision-making. Upgrading in GS from biopsy to radical prostatectomy (RP) puts a proportion of patients at risk of undertreatment. Purpose To develop and validate a radiomics model based on multiparametric magnetic resonance imaging (mp-MRI) to predict PCa upgrading. Study type Retrospective, radiomics. Population A total of 166 RP-confirmed PCa patients (training cohort, n = 116; validation cohort, n = 50) were included. Field strength/sequence 3.0T/T2 -weighted (T2 W), apparent diffusion coefficient (ADC), and dynamic contrast enhancement (DCE) sequences. Assessment PI-RADSv2 score for each tumor was recorded. Radiomic features were extracted from T2 W, ADC, and DCE sequences and Mutual Information Maximization criterion was used to identify the optimal features on each sequence. Multivariate logistic regression analysis was used to develop predictive models and a radiomics nomogram and their performance was evaluated. Statistical tests Student's t or chi-square were used to assess the differences in clinicopathologic data between the training and validation cohorts. Receiver operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated. Results In PI-RADSv2 assessment, 67 lesions scored 5, 70 lesions scored 4, and 29 lesions scored 3. For each sequence, 4404 features were extracted and the top 20 best features were selected. The radiomics model incorporating signatures from the three sequences achieved better performance than any single sequence (AUC: radiomics model 0.868, T2 W 0.700, ADC 0.759, DCE 0.726). The combined mode incorporating radiomics signature, clinical stage, and time from biopsy to RP outperformed the clinical model and radiomics model (AUC: combined model 0.910, clinical model 0.646, radiomics model 0.868). The nomogram showed good performance (AUC 0.910) and calibration (P-values: training cohort 0.624, validation cohort 0.294). Data conclusion Radiomics based on mp-MRI has potential to predict upgrading of PCa from biopsy to RP. Level of evidence 3 TECHNICAL EFFICACY: Stage 5 J. Magn. Reson. Imaging 2020;52:1239-1248.

The establishment of photosynthetic protein complexes during chloroplast development requires the influx of a large number of chloroplast proteins that are encoded by the nuclear genome, which is critical for cytosol and chloroplast protein homeostasis and chloroplast development. However, the mechanisms regulating this process are still not well understood in higher plants. Here, we report the isolation and characterization of the pale green Arabidopsis pga1-1 mutant, which is defective in chloroplast development and chloroplast protein accumulation. Using genetic and biochemical evidence, we reveal that PGA1 encodes AtFtsH12, a chloroplast envelope-localized protein of the FtsH family proteins. We determined a G703R mutation in the GAD motif of the conserved ATPase domain renders the pga1-1 a viable hypomorphic allele of the essential gene AtFtsH12. In de-etiolation assays, we showed that the accumulation of photosynthetic proteins and the expression of photosynthetic genes were impaired in pga1-1. Using the FNR

Thylakoid FtsH complex participates in PSII repair cycle during high light-induced photoinhibition. The Arabidopsis yellow variegated2 (var2) mutants are defective in the VAR2/AtFtsH2 subunit of thylakoid FtsH complex. Taking advantage of the var2 leaf variegation phenotype, dissections of genetic enhancer loci have yielded novel paradigms in understanding functions of thylakoid FtsH complex. Here, we report the isolation of a new var2 enhancer, enhancer of variegation2-1 (evr2-1). We confirmed that EVR2 encodes a chloroplast protein that was known as BALANCE OF CHLOROPHYLL METABOLISM 1 (BCM1), or CHLOROPHYLL BIOSYNTHETIC DEFECT 1 (CBD1). We showed that EVR2/BCM1/CBD1 was involved in the oligomerization of photosystem I complexes. Genetic assays indicated that general defects in chlorophyll biosynthesis and the accumulation of photosynthetic complexes do not necessarily enhance var2 leaf variegation. In addition, we found that VAR2/AtFtsH2 is required for the accumulation of photosynthetic proteins during de-etiolation. Moreover, we identified PSII core proteins D1 and PsbC as potential EVR2-associated proteins using Co-IP/MS. Furthermore, the accumulation of D1 protein was greatly compromised in the var2-5 evr2-1 double mutant during de-etiolation. Together, our findings reveal a functional link between VAR2/AtFtsH2 and EVR2/BCM1/CBD1 in regulating chloroplast development and the accumulation of PSII reaction centre D1 protein during de-etiolation.

Objective To investigate the value of CT radiomics in the differentiation of mycoplasma pneumoniae pneumonia (MPP) from streptococcus pneumoniae pneumonia (SPP) with similar CT manifestations in children. Methods 63 children with MPP (n=30) or SPP (n=33) with similar consolidation and surrounding halo on CT images in Qilu Hospital and Qilu Children's Hospital between January 2017 and July 2019 were enrolled in the retrospective study. Radiomic features of the both lesions on plain CT images were extracted including the consolidation part of the pneumonia or both consolidation and surrounding halo area which were respectively delineated at region of interest (ROI) areas on the maximum axial image. The training set (n=43) and the validation set (n=20) were established by stratified random sampling at a ratio of 7:3. By means of variance threshold, the effective radiomics features, Select Best and least absolute shrinkage and selection operator (LASSO) regression method were employed for feature selection. Six classifiers, including k-nearest neighbor(KNN), support vector machine (SVM),extreme gradient boosting(XGBoost), random forest(RF), logistic regression(LR), and decision tree(DT) were used to construct the models based on radiomic features. The diagnostic performance of these models was estimated and compared using the area under the receiver operating characteristic (ROC) curve (AUC), and the accuracy (score) matrix was established to compare and evaluate the results of different radiomics models. Results XGBoost outperformed other classifiers and was selected as the backbone in the classifier with the consolidation + the surrounding halo was taken as ROI to differentiate MPP from SPP in validation set. The AUC value of MPP in validation set was 0.889, the sensitivity and specificity were 0.89 and 0.82, respectively; and the AUC value of SPP validation set was 0.889, the sensitivity and specificity were 0.82 and 0.89, respectively. Conclusion The XGBoost model has the best classification efficiency in the identification of MPP from SPP in children, and the ROI with both consolidation and surrounding halo is most suitable for the delineation.

Chloroplast development and photosynthesis require the proper assembly and turnover of photosynthetic protein complexes. Chloroplasts harbor a repertoire of proteases to facilitate proteostasis and development. We have previously used an Arabidopsis leaf variegation mutant, yellow variegated2 (var2), defective in thylakoid FtsH protease complexes, as a tool to dissect the genetic regulation of chloroplast development. Here, we report a new genetic enhancer mutant of var2, enhancer of variegation3–1 (evr3–1). We confirm that EVR3 encodes a chloroplast metalloprotease, reported previously as ethylene-dependent gravitropism-deficient and yellow-green1 (EGY1)/ammonium overly sensitive1 (AMOS1). We observed that mutations in EVR3/EGY1/AMOS1 cause more severe leaf variegation in var2–5 and synthetic lethality in var2–4. Using a modified blue-native PAGE system, we reveal abnormal accumulations of photosystem I, photosystem II, and light-harvesting antenna complexes in EVR3/EGY1/AMOS1 mutants. Moreover, we discover distinct roles of VAR2 and EVR3/EGY1/AMOS1 in the turnover of photosystem II reaction center under high light stress. In summary, our findings indicate that two chloroplast metalloproteases, VAR2/AtFtsH2 and EVR3/EGY1/AMOS1, function coordinately to regulate chloroplast development and reveal new roles of EVR3/EGY1/AMOS1 in regulating chloroplast proteostasis in Arabidopsis.

Molecular medicine requires a more precise treatment directed at molecular aberrations detected in tumors on an individual patient level. Immunotherapies empower the body's own immune system to confront tumor cells; however, their efficacy is often affected by tumor heterogeneity. Numerous noninvasive imaging techniques are available to monitor changes in tumor function reflecting therapeutic response, including immunotherapy, and to realize personalized response evaluation. For immunotherapy, strategies for using noninvasive imaging as a prognostic biomarker to identify patients who could benefit from targeted immunotherapy and predict early responders/nonresponders may ultimately lead to improved clinical management, individualized therapy regimens, and better prediction of patient outcomes. Herein, we summarize the recent progress in noninvasive imaging of immunotherapeutic targets such as immune cells, immune checkpoint inhibitors, immune vaccines, and T-cell therapy with chimeric antigen receptor, and review the clinical application of noninvasive imaging in immunotherapy. Finally, we describe the application of multimodal/multispectral imaging and radiomics, which may offer future direction for precision imaging in immunotherapy. With further progress of noninvasive imaging, guiding cancer immunotherapy into the era of precision medicine would be a promising option.

To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer. This retrospective study included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surgically proven gastric cancer. Dedicated radiomics prototype software was used to segment lesions on preoperative arterial phase (AP) CT images and extract features. A radiomics model was constructed to predict the LN metastasis by using a random forest (RF) algorithm. Finally, a nomogram was built incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were used to validate the capability of the radiomics model and nomogram on both the training and test cohorts. The radiomics model showed a favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.844 (95% CI, 0.759 to 0.909), which was confirmed in the test cohort with an AUC of 0.837 (95% CI, 0.705 to 0.926). The nomogram consisted of radiomics scores and the CT-reported LN status showed excellent discrimination in the training and test cohorts with AUCs of 0.886 (95% CI, 0.808 to 0.941) and 0.881 (95% CI, 0.759 to 0.956), respectively. The CT-based radiomics nomogram holds promise for use as a noninvasive tool in the individual prediction of LN metastasis in gastric cancer. • CT radiomics showed a favorable performance for the prediction of LN metastasis in gastric cancer. • Radiomics model outperformed the routine CT in predicting LN metastasis in gastric cancer. • The radiomics nomogram holds potential in the individualized prediction of LN metastasis in gastric cancer.

Background Although aberrant DNA methyltransferase 3a (DNMT3a) expression is important to the tumorigenesis of pancreatic ductal adenocarcinoma (PDAC), the role of DNMT3a in PDAC prognosis is not clarified yet due to the limited studies and lacking of underlying molecular mechanism. Methods The expression of DNMT3a was examined by immunohistochemistry in PDAC tissues. Gene expression profiles assays were conducted to explore the impact of DNMT3a on biological processes and signal pathways. Cell cycle and apoptosis were measured by flow cytometry. Western blotting and real-time qPCR assays were used to explore the impact of DNMT3a on expression of protein and mRNA related to cell cycle, STAT3 signaling pathway and apoptosis. Results DNMT3a was overexpressed and closely associated with poor outcomes of PDAC. DNMT3a knockdown restrained PDAC cell proliferation, induced cell cycle arrest and promoted apoptosis in vitro. Affymetrix GeneChip Human Transcriptome Array identified that the cell cycle-related process was most significantly associated with DNMT3a. DNMT3a knockdown induced G1-S phase transition arrest by decreasing the expression of cyclin D1, which was mediated by the reduction of IL8 and the subsequent inactivation of STAT3 signaling pathway. Furthermore, exogenous apoptosis was also promoted after DNMT3a knockdown, probably via up-regulation of DNA transcription and expression in CASP8. Conclusion These findings indicate that DNMT3a plays an important role in PDAC progression. DNMT3a may serve as a prognostic biomarker and a therapeutic strategy candidate in PDAC.

BACKGROUND Amide proton transfer-weighted (APTw) imaging has shown great potential in the diagnosis of cancer, but has yet not been well studied in cervical cancer. PURPOSE To evaluate the image quality and clinical feasibility of APTw MRI for cervical cancer. STUDY TYPE Prospective. POPULATION In all, 75 patients with cervical lesions and 49 healthy volunteers. FIELD STRENGTH/SEQUENCE 3.0 T, 3D turbo spin echo (TSE) APTw sequence. ASSESSMENT Three radiologists, blinded to the clinical data, independently evaluated APTw image quality with a 5-point Likert scale on 64 patients with pathologically confirmed cervical cancer. APT values, calculated based on asymmetry of acquired Z-spectrum with respect to water frequency, using 3D turbo spin echo volume acquisition with B0 correction, were independently measured by two radiologists, twice for each observer, on 52 cervical cancer lesions and 49 normal cervical stroma with a mean region of interest area of 638.6 mm2 and 557.5 mm2 , respectively. STATISTICAL TESTS Interobserver agreement was evaluated by Kendall's W test. Intra- and interobserver interclass correlation coefficients (ICC) were computed. Student's t-test was used to compare the differences of APT values between cervical cancer and normal cervix; receiver operating characteristic analysis was performed. RESULTS Most cases revealed good APTw image quality with excellent agreement (Kendall's W = 0.850, P