Thermal expansion, lattice vibration, and isotope effect on hydrogen diffusion in BCC Fe, Cr, and W from first-principles calculations.

Fe, Cr, and W are important elements in the alloys of in-reactor materials and operate in high-temperature environments with thermal expansion. Their tritium-impeding abilities are crucial to the radiation safety of various nuclear reactors. In this study, first-principles density functional theory is combined with quasi-harmonic approximation to evaluate factors that can affect the interstitial formation energy and diffusion coefficient of hydrogen isotopes in body-centered cubic (BCC) Fe, Cr, and W, including thermal expansion, metal host lattice vibrations, phonon density-of-states (pDOS) coupling diffusing atoms, and isotope effects. Calculation results indicate that the interstitial formation energy decreases as lattice expansion increases, whereas the jump barriers remain almost constant. Thermal expansion, host lattice vibration, and pDOS coupling minimally affect the diffusion coefficients of hydrogen isotopes in Fe, Cr, and W. The diffusion coefficient ratios between hydrogen isotopes are higher than the inverse ratio of the square root of the isotope mass at low temperatures. However, they decrease to the inverse ratio of the square root of the isotope mass at temperatures exceeding 800 K. This study comprehensively investigates factors that affect the diffusion coefficients of hydrogen isotopes in BCC Fe, Cr, and W, thus providing a firm theoretical foundation for predicting the diffusion coefficients of tritium at different temperatures using protium/deuterium diffusion coefficients.

Novel Iridoid Derivatives Isolated from the Roots of Patrinia scabra with Potential Anti-Renal Fibrosis Activity In Vitro.

Scabrol B and Scabrol C, two newly identified iridoid derivatives (1 and 2) and six known compounds (3-8), were extracted from the roots of Patrinia scabra. The structures of these derivatives, including their absolute configurations, were elucidated via comprehensive NMR analysis, chemical derivatization, and quantum chemical ECD calculations. All isolated compounds were evaluated for their anti-renal fibrosis activity. The results demonstrate that compounds 1 and 2 showed dose-dependent protective effects against renal fibrosis in vitro by reducing the expression of fibronectin, collagen I, and alpha-smooth muscle actin (α-SMA) in NRK-49f cells mediated by TGF-ß1.

Volumetric visceral fat machine learning phenotype on CT for differential diagnosis of inflammatory bowel disease.

OBJECTIVES: To investigate whether volumetric visceral adipose tissue (VAT) features extracted using radiomics and three-dimensional convolutional neural network (3D-CNN) approach are effective in differentiating Crohn's disease (CD) and ulcerative colitis (UC). METHODS: This retrospective study enrolled 316 patients (mean age, 36.25 ± 13.58 [standard deviation]; 219 men) with confirmed diagnosis of CD and UC who underwent CT enterography between 2012 and 2021. Volumetric VAT was semi-automatically segmented on the arterial phase images. Radiomics analysis was performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm. We developed a 3D-CNN model using VAT imaging data from the training cohort. Clinical covariates including age, sex, modified body mass index, and disease duration that impact VAT were added to the machine learning model for adjustment. The model's performance was evaluated on the testing cohort separating from the model's development process by its discrimination and clinical utility. RESULTS: Volumetric VAT radiomics analysis with LASSO had the highest AUC value of 0.717 (95% CI, 0.614-0.820), though difference of diagnostic performance among the 3D-CNN model (AUC = 0.693; 95% CI, 0.587-0.798) and radiomics analysis with PCA (AUC = 0.662; 95% CI, 0.548-0.776) and LASSO have not reached statistical significance (all p > 0.05). The radiomics score was higher in UC than in CD on the testing cohort (mean ± SD, UC 0.29 ± 1.05 versus CD -0.60 ± 1.25; p < 0.001). The LASSO model with adjustment of clinical covariates reached an AUC of 0.775 (95%CI, 0.683-0.868). CONCLUSION: The developed volumetric VAT-based radiomics and 3D-CNN models provided comparable and effective performance for the characterization of CD from UC. KEY POINTS: • High-output feature data extracted from volumetric visceral adipose tissue on CT enterography had an effective diagnostic performance for differentiating Crohn's disease from ulcerative colitis. • With adjustment of clinical covariates that cause difference in volumetric visceral adipose tissue, adjusted clinical machine learning model reached stronger performance when distinguishing Crohn's disease patients from ulcerative colitis patients.

Design, synthesis and biological evaluation of novel modified dual-target shikonin derivatives for colorectal cancer treatment.

Warburg effect provides energy and material essential for tumor proliferation, the reverse of Warburg effect provides insights into the development of a novel anti-cancer strategy. Pyruvate kinase 2 (PKM2) and pyruvate dehydrogenase kinase 1 (PDK1) are two key enzymes in tumor glucose metabolism pathway that not only contribute to the Warburg effect through accelerating aerobic glycolysis, but also serve as druggable target for colorectal cancer (CRC). Considering that targeting PKM2 or PDK1 alone does not seem to be sufficient to remodel abnormal glucose metabolism and achieve significant antitumor activity, a series of novel benzenesulfonyl shikonin derivatives were designed to regulate PKM2 and PDK1 simultaneously. By means of molecular docking and antiproliferative screen, we found that compound Z10 could act as the combination of PKM2 activator and PDK1 inhibitor, thereby significantly inhibited glycolysis that reshaping tumor metabolism. Moreover, Z10 could inhibit proliferation, migration and induce apoptosis in CRC cell HCT-8. Finally, the in vivo anti-tumor activity of Z10 was evaluated in a colorectal cancer cell xenograft model in nude mice and the results demonstrated that Z10 induced tumor cell apoptosis and inhibited tumor cell proliferation with lower toxicity than shikonin. Our findings indicated that it is feasible to alter tumor energy metabolism through multi-target synergies, and the dual-target benzenesulfonyl shikonin derivative Z10 could be a potential anti-CRC agent.

Clinical application of a digital semi-rigid bridge space maintainer fabricated from polyetheretherketone for premature loss of primary molars.

BACKGROUND: Premature loss of primary molars can be treated with a band loop space maintainer (SM). However, fabricating a conventional band loop SM requires multiple clinical and laboratory procedures, which can potentially affect the accuracy of the SM. Moreover, the conventional SM is unable to fully restore masticatory function and maintain the vertical dimension of the edentulous space. In this current study, a fully digital workflow to fabricate a semi-rigid bridge SM made from polyetheretherketone (PEEK) has been described and evaluated for its clinical effectiveness. METHODS: A total of 15 children (eight males and seven females) between the ages of 4-8 years, who experienced the premature loss of a single primary molar, were included in this study. Digital impressions were taken using the CEREC CAD/CAM chair system and imported into CAD software to design the semi-rigid bridge SM, which was fabricated using PEEK block as the maintainer material. The digital SM was tried-in and bonded to the abutment with resin cement. The edentulous space was measured immediately after bonding (T0) and 1 month (T1), 3 months (T2), and 6 months (T3) after treatment. The periodontal condition and mobility of the SM and abutment were also examined. RESULTS: The use of digital impressions resulted in a decreased occurrence of the pharyngeal reflex. The digital semi-rigid bridge SM, fabricated with PEEK, was both convenient and aesthetically pleasing, and successfully restored the anatomy and masticatory function of the missing primary molar. None of the 15 semi-rigid bridge SMs or abutments became loose or fell off during the study, and only one child presented with gingivitis. Furthermore, the difference in the edentulous space at T0, T1, T2, and T3 was not statistically significant (all P > 0.05). CONCLUSIONS: The digital semi-rigid bridge SM fabricated with PEEK was clinically effective in maintaining the missing space and had advantages over the traditional band/crown loop SM.

Ureteral calculi lithotripsy for single ureteral calculi: can DNN-assisted model help preoperatively predict risk factors for sepsis?

OBJECTIVES: To explore the utility of radiomics and deep learning model in assessing the risk factors for sepsis after flexible ureteroscopy lithotripsy (FURL) or percutaneous nephrolithotomy (PCNL) in patients with ureteral calculi. METHODS: This retrospective analysis included 847 patients with treatment-naive proximal ureteral calculi who received FURL or PCNL. All participants were preoperatively conducted non-contrast computed tomography scans, and relevant clinical information was meanwhile collected. After propensity score matching, the radiomics model was established to predict the onset of sepsis. A deep learning model was also adapted to further improve the prediction accuracy. Performance of these trained models was verified in another independent external validation set including 40 cases of ureteral calculi patients. RESULTS: The overall incidence of sepsis after FURL or PCNL was 5.9%. The least absolute shrinkage and selection operator (LASSO) regression analysis revealed 26 predictive variables, with an overall AUC of 0.881 (95% CI, 0.813-0.931) and an AUC of 0.783 (95% CI, 0.766-0.801) in external validation cohort. Judicious adaption of a deep neural network (DNN) model to our dataset improved the AUC to 0.920 (95% CI, 0.906-0.933) in the internal validation. To eliminate the overfitting, external validation was carried out for DNN model (AUC = 0.874 (95% CI, 0.858-0.891)). CONCLUSIONS: The DNN was more effective than the LASSO model in revealing risk factors for sepsis after FURL or PCNL in single ureteral calculi patients, and females are more susceptible to sepsis than males. Deep learning models have the potential to act as gatekeepers to facilitate patient stratification. KEY POINTS: • Both the least absolute shrinkage and selection operator (LASSO) and deep neural network (DNN) models were shown to be effective in sepsis prediction. • The DNN model achieved superior prediction capability, with an AUC of 0.920 (95% CI, 0.906-0.933). • DNN-assisted model has potential to serve as a gatekeeper to facilitate patient stratification.

Progress on biosynthesis and function of the natural products of Zi Cao as a traditional Chinese medicinal herb.

Zi Cao is an important traditional medicinal plant resource in China. Shikonin and its derivatives, as the purple-red naphthoquinones among natural products of its roots, are commonly used clinically in the treatment of sores and skin inflammations. Over the past few decades, due to their highly effective multiple biological activities, pharmacological effects, good clinical efficacy and high utilization value, shikonin and its derivatives have attracted increasing attention of domestic and foreign researchers. For this reason, the wild plant germplasm resources have been suffering a grievous exploitation, leading to a serious threat to the habitat. With the development of the biosynthesis, molecular metabolism and biotechnology, as well as the continuous innovation of research methods on the biological activities and pharmacological effects of plant natural products, significant progress has been made in the research on the biosynthetic pathways and related regulatory genes of shikonin. The pharmacological action and its mechanism of shikonin have also been deeply elucidated, which greatly promoted the basic research and clinical application development of shikonin. In this review, we briefly introduce and analyze the classification of Zi Cao, structure and composition of natural shikonin and its biosynthesis pathway, functional genes related to the regulation of shikonin biosynthesis, and biological activities and pharmacological functions of shikonin. Finally, we address possible prospective for the trend on the future research and development of natural shikonin and its derivatives, hoping to provide a useful reference for the deep mining and development of medicinal natural products from important Chinese medicinal materials, and to promote the modern development of traditional Chinese medicine.

A Bidirectional Quasi-Endfire Patch Antenna with Low Elevation Angle.

A bidirectional quasi-endfire patch antenna with a low elevation angle has promising applications for wireless communication systems that are vehicle-based, airborne, and shipborne. In this paper, the shortened patch resonators and open patch resonator are integrated to form a bidirectional quasi-endfire patch antenna with low elevation angle. The open patch resonator operates with a TM20 mode to realize bidirectional radiation. The two shortened patch resonators operate with a TM01 mode coupled with a TM20 mode to control the phase difference between them at a suitable angle, so that the shortened patch resonators act as directors to tilt the dual beams toward the endfire direction and achieve low elevation angle. Compared with reported patch antennas with dual beams, the proposed antenna has the lowest elevation angle and a compact structure. For demonstration purposes, an antenna prototype operating at 3.5 GHz is fabricated and measured, exhibiting a low elevation angle of ±28°, a -10 dB impedance matching bandwidth from 3.44 GHz to 3.61 GHz, and a size of 1.36 λ0 × 0.57 λ0 with a profile of 0.036 λ0. A prototype with two pair of shortened patch directors further reduces the elevation angle to ±19° with the size of 2.3 λ0 × 0.57 λ0.

Incremental value of automatically segmented perirenal adipose tissue for pathological grading of clear cell renal cell carcinoma: a multicenter cohort study.

OBJECTIVES: Accurate preoperative prediction of the pathological grade of clear cell renal cell carcinoma (ccRCC) is crucial for optimal treatment planning and patient outcomes. This study aims to develop and validate a deep-learning (DL) algorithm to automatically segment renal tumours, kidneys, and perirenal adipose tissue (PRAT) from computed tomography (CT) images and extract radiomics features to predict the pathological grade of ccRCC. METHODS: In this cross-ethnic retrospective study, a total of 614 patients were divided into a training set (383 patients from the local hospital), an internal validation set (88 patients from the local hospital), and an external validation set (143 patients from the public dataset). A two-dimensional TransUNet-based DL model combined with the train-while-annotation method was trained for automatic volumetric segmentation of renal tumours, kidneys, and visceral adipose tissue (VAT) on images from two groups of datasets. PRAT was extracted using a dilation algorithm by calculating voxels of VAT surrounding the kidneys. Radiomics features were subsequently extracted from three regions of interest of CT images, adopting multiple filtering strategies. The least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, and the support vector machine (SVM) for developing the pathological grading model. Ensemble learning was used for imbalanced data classification. Performance evaluation included the Dice coefficient for segmentation and metrics such as accuracy and area under curve (AUC) for classification. The WHO/International Society of Urological Pathology (ISUP) grading models were finally interpreted and visualized using the SHapley Additive exPlanations (SHAP) method. RESULTS: For automatic segmentation, the mean Dice coefficient achieved 0.836 for renal tumours and 0.967 for VAT on the internal validation dataset. For WHO/ISUP grading, a model built with features of PRAT achieved a moderate AUC of 0.711 (95% CI, 0.604-0.802) in the internal validation set, coupled with a sensitivity of 0.400 and a specificity of 0.781. While model built with combination features of the renal tumour, kidney, and PRAT showed an AUC of 0.814 (95% CI, 0.717-0.889) in the internal validation set, with a sensitivity of 0.800 and a specificity of 0.753, significantly higher than the model built with features solely from tumour lesion (0.760; 95% CI, 0.657-0.845), with a sensitivity of 0.533 and a specificity of 0.767. CONCLUSION: Automated segmentation of kidneys and visceral adipose tissue (VAT) through TransUNet combined with a conventional image morphology processing algorithm offers a standardized approach to extract PRAT with high reproducibility. The radiomics features of PRAT and tumour lesions, along with machine learning, accurately predict the pathological grade of ccRCC and reveal the incremental significance of PRAT in this prediction.

ATP-dependent remodeling of chromatin condensates uncovers distinct mesoscale effects of two remodelers.

ATP-dependent chromatin remodeling enzymes mobilize nucleosomes, but how such mobilization affects chromatin condensation is unclear. Here, we investigate effects of two major remodelers, ACF and RSC using chromatin condensates and single-molecule footprinting. We find that both remodelers inhibit the formation of condensed chromatin. However, the remodelers have distinct effects on pre-formed chromatin condensates. ACF spaces nucleosomes without de-condensing the chromatin, explaining how ACF maintains nucleosome organization in transcriptionally repressed genomic regions. In contrast, RSC catalyzes ATP-dependent de-condensation of chromatin. Surprisingly, RSC also drives micron-scale movements of entire condensates. These newly uncovered activities of RSC explain its central role in transcriptional activation. The biological importance of remodelers may thus reflect both their effects on nucleosome mobilization and the corresponding consequences on chromatin dynamics at the mesoscale.

Identification of Calculous Pyonephrosis by CT-Based Radiomics and Deep Learning.

Urgent detection of calculous pyonephrosis is crucial for surgical planning and preventing severe outcomes. This study aims to evaluate the performance of computed tomography (CT)-based radiomics and a three-dimensional convolutional neural network (3D-CNN) model, integrated with independent clinical factors, to identify patients with calculous pyonephrosis. We recruited 182 patients receiving either percutaneous nephrostomy tube placement or percutaneous nephrolithotomy for calculous hydronephrosis or pyonephrosis. The regions of interest were manually delineated on plain CT images and the CT attenuation value (HU) was measured. Radiomics analysis was performed using least absolute shrinkage and selection operator (LASSO). A 3D-CNN model was also developed. The better-performing machine-learning model was combined with independent clinical factors to build a comprehensive clinical machine-learning model. The performance of these models was assessed using receiver operating characteristic analysis and decision curve analysis. Fever, blood neutrophils, and urine leukocytes were independent risk factors for pyonephrosis. The radiomics model showed higher area under the curve (AUC) than the 3D-CNN model and HU (0.876 vs. 0.599, 0.578; p = 0.003, 0.002) in the testing cohort. The clinical machine-learning model surpassed the clinical model in both the training (0.975 vs. 0.904, p = 0.019) and testing (0.967 vs. 0.889, p = 0.045) cohorts.

Effects of hesperidin on the histological structure, oxidative stress, and apoptosis in the liver and kidney induced by NiCl2.

The aim of this study was to investigate the effect of hesperidin on the liver and kidney dysfunctions induced by nickel. The mice were divided into six groups: nickel treatment with 80 mg/kg, 160 mg/kg, 320 mg/kg hesperidin groups, 0.5% CMC-Na group, nickel group, and blank control group. Histopathological techniques, biochemistry, immunohistochemistry, and the TUNEL method were used to study the changes in structure, functions, oxidative injuries, and apoptosis of the liver and kidney. The results showed that hesperidin could alleviate the weight loss and histological injuries of the liver and kidney induced by nickel, and increase the levels of lactate dehydrogenase (LDH), alanine aminotransferase (GPT), glutamic oxaloacetic transaminase (GOT) in liver and blood urea nitrogen (BUN), creatinine (Cr) and N-acetylglucosidase (NAG) in kidney. In addition, hesperidin could increase the activities of superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), and glutathione peroxidase (GSH-Px) in the liver and kidney, decrease the content of malondialdehyde (MDA) and inhibit cell apoptosis. It is suggested that hesperidin could help inhibit the toxic effect of nickel on the liver and kidney.

Understanding how genetically encoded tags affect phase separation by Heterochromatin Protein HP1α.

Liquid-liquid phase separation (LLPS) is driven by weak multi-valent interactions. Such interactions can result in the formation of puncta in cells and droplets in vitro . The heterochromatin protein HP1α forms droplets with chromatin in vitro and is found in puncta in cells. A common approach to visualize the dynamics of HP1α in cells is to genetically encode fluorescent tags on the protein. HP1α modified with tags such as GFP has been shown to localize to dynamic puncta in vivo . However, whether tagged HP1α retains its intrinsic phase separation properties has not been systematically studied. Here, using different C-terminal tags (AID-sfGFP, mEGFP, and UnaG), we assessed how tag size and linker length affected the phase separation ability of HP1α with DNA in vitro . We found that the AID-sfGFP tag (52 kDa) promoted HP1α phase-separation, possibly driven by the highly disordered AID degron. The mEGFP tag (27 kDa) inhibited phase-separation by HP1α, whereas an UnaG tag (13 kDa) with a 16 amino acid linker showed minimal perturbation. The UnaG tag can thus be used in cellular studies of HP1α to better correlate in vitro and in vivo studies. To test if cellular crowding overcomes the negative effects of large tags in vivo , we used polyethylene glycol (PEG) to mimic crowding in vitro . We found that addition of 10% PEG8000 or PEG4000 enables phase separation by GFP-tagged HP1α at comparable concentrations as untagged HP1α. However, these crowding agents also substantially dampened the differences in phase-separation between wild-type and mutant HP1α proteins. PEG further drove phase-separation of Maltose Binding Protein (MBP), a tag often used to solubilize other proteins. These results suggest that phase-separation of biological macromolecules with PEG should be interpreted with caution as PEG-based crowding agents may change the types of interactions made within the phases.

A contrast-enhanced CT-based whole-spleen radiomics signature for early prediction of oxaliplatin-related thrombocytopenia in patients with gastrointestinal malignancies: a retrospective study.

Background: Thrombocytopenia is a common adverse event of oxaliplatin-based chemotherapy. Grade 2 or higher oxaliplatin-related thrombocytopenia may result in dose reduction, discontinuation or delay initiation of chemotherapy and may adversely affect the therapeutic efficacy and even overall survival of patients. Early recognition of patients at risk of developing grade 2 or higher thrombocytopenia is critical. However, to date there is no well-established method to early identify patients at high risk. The aims of this study were to develop and validate a contrast-enhanced CT-based whole-spleen radiomics signature for early prediction of grade 2 or higher thrombocytopenia in patients with gastrointestinal malignancies treated with oxaliplatin-based chemotherapy and to explore the incremental value of combining the radiomics signature and conventional clinical factors for risk prediction. Methods: A total of 119 patients with gastrointestinal malignancies receiving oxaliplatin-based chemotherapy from March 2017 to December 2020 were retrospectively included and randomly divided into a training cohort (n = 85) and a validation cohort (n = 34). Grade 2 or higher thrombocytopenia occurred in 26.1% of patients (22 and nine patients in the training and validation cohort, respectively) with a median time interval of 101 days from the start of chemotherapy. The whole-spleen radiomics features were extracted on the portal venous phase of the first follow-up CT images. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to select radiomics features and to build the radiomics signature for the prediction of grade 2 or higher thrombocytopenia. A clinical model that included clinical factors only and a clinical-radiomics model that incorporated clinical factors and radiomics signature were constructed. The performances of both models were evaluated and compared in the training, validation and the whole cohorts. Results: The radiomics signature yielded favorable performance in predicting grade 2 or higher thrombocytopenia, with the area under the curve (AUC), sensitivity and specificity being 0.865, 81.8% and 84.1% in the training cohort and 0.747, 77.8% and 80.0% in the validation cohort. The AUCs of the clinical-radiomics model in the training and validation cohorts reached 0.913 (95% CI [0.720-0.935]) and 0.867 (95% CI [0.727-1.000]), greater than the AUCs of the clinical model. Integrated discrimination improvement (IDI) index showed that incorporating radiomic signature into conventional clinical factors significantly improved the predictive accuracy by 17.0% (95% CI [4.9%-29.1%], p = 0.006) in the whole cohort. Conclusions: Contrast-enhanced CT-based whole-spleen radiomics signature might serve as an early predictor for grade 2 or higher thrombocytopenia during oxaliplatin-based chemotherapy in patients with gastrointestinal malignancies and provide incremental value over conventional clinical factors.

Advances in Self-Assembled Peptides as Drug Carriers.

In recent years, self-assembled peptide nanotechnology has attracted a great deal of attention for its ability to form various regular and ordered structures with diverse and practical functions. Self-assembled peptides can exist in different environments and are a kind of medical bio-regenerative material with unique structures. These materials have good biocompatibility and controllability and can form nanoparticles, nanofibers and hydrogels to perform specific morphological functions, which are widely used in biomedical and material science fields. In this paper, the properties of self-assembled peptides, their influencing factors and the nanostructures that they form are reviewed, and the applications of self-assembled peptides as drug carriers are highlighted. Finally, the prospects and challenges for developing self-assembled peptide nanomaterials are briefly discussed.

Is the radiomics-clinical combined model helpful in distinguishing between pancreatic cancer and mass-forming pancreatitis?

PURPOSE: To develop CT-based radiomics models for distinguishing between resectable PDAC and mass-forming pancreatitis (MFP) and to provide a non-invasive tool for cases of equivocal imaging findings with EUS-FNA needed. METHODS: A total of 201 patients with resectable PDAC and 54 patients with MFP were included. Development cohort: patients without preoperative EUS-FNA (175 PDAC cases, 38 MFP cases); validation cohort: patients with EUS-FNA (26 PDAC cases, 16 MFP cases). Two radiomic signatures (LASSOscore, PCAscore) were developed based on the LASSO model and principal component analysis. LASSOCli and PCACli prediction models were established by combining clinical features with CT radiomic features. ROC analysis and decision curve analysis (DCA) were performed to evaluate the utility of the model versus EUS-FNA in the validation cohort. RESULTS: In the validation cohort, the radiomic signatures (LASSOscore, PCAscore) were both effective in distinguishing between resectable PDAC and MFP (AUCLASSO = 0.743, 95% CI: 0.590-0.896; AUCPCA = 0.788, 95% CI: 0.639-0.938) and improved the diagnostic accuracy of the baseline onlyCli model (AUConlyCli = 0.760, 95% CI: 0.614-0.960) after combination with variables including age, CA19-9, and the double-duct sign (AUCPCACli = 0.880, 95% CI: 0.776-0.983; AUCLASSOCli = 0.825, 95% CI: 0.694-0.955). The PCACli model showed comparable performance to FNA (AUCFNA = 0.810, 95% CI: 0.685-0.935). In DCA, the net benefit of the PCACli model was superior to that of EUS-FNA, avoiding biopsies in 70 per 1000 patients at a risk threshold of 35%. CONCLUSIONS: The PCACli model showed comparable performance with EUS-FNA in discriminating resectable PDAC from MFP.

Nucleosome density shapes kilobase-scale regulation by a mammalian chromatin remodeler.

Nearly all essential nuclear processes act on DNA packaged into arrays of nucleosomes. However, our understanding of how these processes (for example, DNA replication, RNA transcription, chromatin extrusion and nucleosome remodeling) occur on individual chromatin arrays remains unresolved. Here, to address this deficit, we present SAMOSA-ChAAT: a massively multiplex single-molecule footprinting approach to map the primary structure of individual, reconstituted chromatin templates subject to virtually any chromatin-associated reaction. We apply this method to distinguish between competing models for chromatin remodeling by the essential imitation switch (ISWI) ATPase SNF2h: nucleosome-density-dependent spacing versus fixed-linker-length nucleosome clamping. First, we perform in vivo single-molecule nucleosome footprinting in murine embryonic stem cells, to discover that ISWI-catalyzed nucleosome spacing correlates with the underlying nucleosome density of specific epigenomic domains. To establish causality, we apply SAMOSA-ChAAT to quantify the activities of ISWI ATPase SNF2h and its parent complex ACF on reconstituted nucleosomal arrays of varying nucleosome density, at single-molecule resolution. We demonstrate that ISWI remodelers operate as density-dependent, length-sensing nucleosome sliders, whose ability to program DNA accessibility is dictated by single-molecule nucleosome density. We propose that the long-observed, context-specific regulatory effects of ISWI complexes can be explained in part by the sensing of nucleosome density within epigenomic domains. More generally, our approach promises molecule-precise views of the essential processes that shape nuclear physiology.

Radiomics Nomogram Based on High-b-Value Diffusion-Weighted Imaging for Distinguishing the Grade of Bladder Cancer.

BACKGROUND: The aim was to evaluate the feasibility of radiomics features based on diffusion-weighted imaging (DWI) at high b-values for grading bladder cancer and to compare the possible advantages of high-b-value DWI over the standard b-value DWI. METHODS: Seventy-four participants with bladder cancer were included in this study. DWI sequences using a 3 T MRI with b-values of 1000, 1700, and 3000 s/mm2 were acquired, and the corresponding ADC maps were generated, followed with feature extraction. Patients were randomly divided into training and testing cohorts with a ratio of 8:2. The radiomics features acquired from the ADC1000, ADC1700, and ADC3000 maps were compared between low- and high-grade bladder cancers by using the Wilcox analysis, and only the radiomics features with significant differences were selected. The least absolute shrinkage and selection operator method and a logistic regression were performed for the feature selection and establishing the radiomics model. A receiver operating characteristic (ROC) analysis was conducted to assess the diagnostic performance of the radiomics models. RESULTS: In the training cohorts, the AUCs of the ADC1000, ADC1700, and ADC3000 model for discriminating between low- from high-grade bladder cancer were 0.901, 0.920, and 0.901, respectively. In the testing cohorts, the AUCs of ADC1000, ADC1700, and ADC3000 were 0.582, 0.745, and 0.745, respectively. CONCLUSIONS: The radiomics features extracted from the ADC1700 maps could improve the diagnostic accuracy over those extracted from the conventional ADC1000 maps.

Spontaneous healing of complicated crown-root fractures in children: Two case reports.

BACKGROUND: Complicated crown-root fracture is considered a severe dental trauma and is unlikely to heal without treatment. Usually, dentists have to remove the loose coronal fragment of the fractured tooth and treat the remaining part with multidisciplinary approaches. However, we observed spontaneous healing of fracture in two pediatric cases with a history of complicated crown-root fractures over 4 years ago. CASE SUMMARY: In case 1, a 12-year-old boy complained of pain at tooth 11 following an accidental fall 1 d ago. Clinical examination showed a crack line on the crown of tooth 11. Cone beam computed tomography (CBCT) images of tooth 11 showed signs of hard tissue deposition between the fractured fragments. The patient recalled that tooth 11 had struck the floor 1 year ago without seeking any other treatment. In case 2, a 10-year-old girl fell down 1 d ago and wanted to have her teeth examined. Clinical examination showed a fracture line on the crown of tooth 21. CBCT images of tooth 21 also showed signs of hard tissue deposition between the fractured fragments. She also had a history of dental trauma 1 year ago and her tooth 11 received dental treatment by another dentist. According to her periapical radiograph at that time, tooth 21 was fractured 1 year ago and the fracture was overlooked by her dentist. Both of these two cases showed spontaneous healing of complicated crown-root fractures. After over 4 years of follow-up, both fractured teeth showed no signs of abnormality. CONCLUSION: These findings may provide new insights and perspectives on the management and treatment of crown-root fractures in children.

The relationship between perianal fistula activity and abdominal adipose tissue in Crohn's disease: an observational study.

OBJECTIVE: The aim of this study was to analyze the relationship between abdominal adipose tissue and perianal fistula activity in patients with Crohn's disease (CD) using cross-sectional imaging. METHODS: Patients with perianal fistulizing CD who underwent pelvic magnetic resonance imaging (MRI) and abdominal computed tomography (CT) were retrospectively enrolled. We scored the fistulas in each patient's MRI images based on Van Assche's classification. The area and density of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) (at the third, fourth, and fifth lumbar (L3, L4, and L5) levels were measured by averaging five slices of measurements at each vertebral level in CT images, and areas were further standardized by the lumbar height2 (heightL1-5). The VAT/SAT ratio (VSR) and VAT/Total adipose tissue (VA/TA) index were calculated. Based on MRI scores, patients were divided into two groups with low and high activity, and their clinical, MRI features, and CT parameters were compared. We evaluated patients with follow-up MRI and compared the differences in clinical and radiological indicators among patients with different outcomes. RESULTS: Overall, 136 patients were included, 77 in the low-activity group and 59 in the high-activity group. Patients in the high activity group had lower subcutaneous adipose index (all levels, p < 0.05) and visceral adipose index (L3 level, p < 0.01), but higher SAT and VAT density (all levels, p < 0.01), VSR (L5 level, p = 0.07) and VA/TA index (L5 level, p < 0.05). CONCLUSION: There were differences in adipose tissue composition among CD patients with different active perianal fistulas.