Albumin-seeking dyes with adjustable assemblies in situ enable programmable imaging windows and targeting tumor imaging.

Cyanine dyes are widely used organic probes for in vivo imaging due to their tunable fluorescence. They can form complexes with endogenous albumin, resulting in enhanced brightness and photostability. However, this binding is uncontrollable and irreversible, leading to considerable nonspecific background signals and unregulated circulation time. Methods: Here, we connect varying numbers of 4-(4-iodophenyl) butanoic acid (IP) as albumin-binding moieties (ABM) to the cyanine dye, enabling dynamic and controllable binding with albumin. Meanwhile, we provide a blocking method to completely release the dye from covalent capture with albumin, resulting in specific targeting fluorescence. Furthermore, we evaluate the pharmacokinetics and tumor targeting of the developed dyes. Results: The engineered dyes can dynamically and selectively bind with multiple albumins to change the in situ size of assemblies and circulation time, providing programmable regulation over the imaging time window. The nucleophilic substitution of meso-Cl with water-soluble amino acids or targeting peptides for IP-engineered dye further addresses the nonspecific signals caused by albumin, allowing for adjustable angiography time and efficient tumor targeting. Conclusion: This study rationalizes the binding modes of dyes and proteins, applicable to a wide range of near-infrared (NIR) dyes for improving their in vivo molecular imaging.

NIR-II Protein-Escaping Dyes Enable High-Contrast and Long-Term Prognosis Evaluation of Flap Transplantation.

Real-time vascular positioning, postoperative flap monitoring, and vascular reconstruction assessment are of great importance in flap transplantation. Cyanine dyes offer the advantage of high resolution in the Near-infrared-II (NIR-II) imaging window. However, the nonspecific binding of many cyanine dyes to endogenous albumin leads to high organ accumulation and skin absorption, resulting in low-quality imaging and poor reproducibility of contrast during long-term (e.g., 7 days) postoperative monitoring. Here, a novel strategy is proposed that can be widely applied to prevent protein binding for NIR-I/II Cl-containing cyanine dyes. This strategy produces protein-escaping dyes, ensuring high fluorescence enhancement in the blood with rapid clearance and no residual fluorescence, allowing for short-term repeatable injections for vascular imaging. This strategy in the perioperative monitoring of pedicle perforator flap models in mice and rats is successfully applied. Furthermore, leveraging the universality of this strategy, multiple nonoverlapping protein-escaping probes that achieve dual-excitation (808 and 1064 nm) interference-free imaging of nerve-vessel and tumor-vessel simultaneously are designed and synthesized. These protein-escaping dyes enable long-term repeatable dual-color imaging of tumor localization, resection, and tumor-vessel reconstruction at the wound site.

Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma.

BACKGROUND: Microvascular invasion (MVI) of small hepatocellular carcinoma (sHCC) (≤ 3.0 cm) is an independent prognostic factor for poor progression-free and overall survival. Radiomics can help extract imaging information associated with tumor pathophysiology. AIM: To develop and validate radiomics scores and a nomogram of gadolinium ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for preoperative prediction of MVI in sHCC. METHODS: In total, 415 patients were diagnosed with sHCC by postoperative pathology. A total of 221 patients were retrospectively included from our hospital. In addition, we recruited 94 and 100 participants as independent external validation sets from two other hospitals. Radiomics models of Gd-EOB-DTPA-enhanced MRI and diffusion-weighted imaging (DWI) were constructed and validated using machine learning. As presented in the radiomics nomogram, a prediction model was developed using multivariable logistic regression analysis, which included radiomics scores, radiologic features, and clinical features, such as the alpha-fetoprotein (AFP) level. The calibration, decision-making curve, and clinical usefulness of the radiomics nomogram were analyzed. The radiomic nomogram was validated using independent external cohort data. The areas under the receiver operating curve (AUC) were used to assess the predictive capability. RESULTS: Pathological examination confirmed MVI in 64 (28.9%), 22 (23.4%), and 16 (16.0%) of the 221, 94, and 100 patients, respectively. AFP, tumor size, non-smooth tumor margin, incomplete capsule, and peritumoral hypointensity in hepatobiliary phase (HBP) images had poor diagnostic value for MVI of sHCC. Quantitative radiomic features (1409) of MRI scans) were extracted. The classifier of logistic regression (LR) was the best machine learning method, and the radiomics scores of HBP and DWI had great diagnostic efficiency for the prediction of MVI in both the testing set (hospital A) and validation set (hospital B, C). The AUC of HBP was 0.979, 0.970, and 0.803, respectively, and the AUC of DWI was 0.971, 0.816, and 0.801 (P < 0.05), respectively. Good calibration and discrimination of the radiomics and clinical combined nomogram model were exhibited in the testing and two external validation cohorts (C-index of HBP and DWI were 0.971, 0.912, 0.808, and 0.970, 0.843, 0.869, respectively). The clinical usefulness of the nomogram was further confirmed using decision curve analysis. CONCLUSION: AFP and conventional Gd-EOB-DTPA-enhanced MRI features have poor diagnostic accuracies for MVI in patients with sHCC. Machine learning with an LR classifier yielded the best radiomics score for HBP and DWI. The radiomics nomogram developed as a noninvasive preoperative prediction method showed favorable predictive accuracy for evaluating MVI in sHCC.

Radiomics in Addition to Computed Tomography-Based Body Composition Nomogram May Improve the Prediction of Postoperative Complications in Gastric Cancer Patients.

OBJECTIVES: The study aimed to determine the impact of computed tomography (CT)-based body composition and radiomics nomogram on the prediction of postoperative complications in gastric cancer. METHODS: The clinical data of 457 individuals with surgically confirmed gastric cancer, 320 patients in the training cohort (TC) and 137 patients in the validation cohort (VC), were retrospectively analyzed. Body composition data were measured using CT. Postoperative complications were graded using the Clavien-Dindo system. Dedicated radiomics prototype software was used to segment lesions and extract characteristics from preoperative portal venous-phase CT images. Clinical, radiomics, and combined models were developed using logistic regression analysis. Model performance was evaluated using the area under the curve (AUC) of receiver operating characteristic curve, and the prediction ability of the optimal model was evaluated using calibration curves and decision curve analysis (DCA). RESULTS: Nutritional Risk Screening 2002 (NRS2002) score, sarcopenia, and blood loss were independent predictors of postoperative complications in gastric cancer. A radiomics signature was created using 19 conserved radiomics features. The nomogram based on both the clinical model and radiomics signature showed the greatest predictive performance, with AUCs of 0.763 (95% confidence interval [CI], 0.708-0.817) and 0.748 (95% CI: 0.667-0.818) in the TC and VC, respectively. The calibration curve and DCA revealed that the nomogram was beneficial in clinical practice for the preoperative prediction of postoperative complications. CONCLUSIONS: The combined model consisting of NRS2002 score, sarcopenia, blood loss, and a radiomics signature holds potential application value for the individualized prediction of postoperative complications in gastric cancer patients.

The value of multi-parameter diffusion and perfusion magnetic resonance imaging for evaluating epithelial-mesenchymal transition in rectal cancer.

PURPOSE: Epithelial-mesenchymal transition (EMT) is characterized by a decreased expression of E-cadherin and an increased expression of vimentin, which is associated with poor prognosis in rectal cancer. This study aimed to explore the feasibility of using multi-parameter diffusion and perfusion magnetic resonance imaging (MRI) to evaluate the expression of E-cadherin and vimentin. METHODS: One hundred and ten patients with rectal cancer, who underwent preoperative multi-parameter diffusion and perfusion MRI and subsequent radical resection of rectal carcinoma, were included in this prospective study. The expression of E-cadherin, vimentin, vascular endothelial growth factor (VEGF), and Ki67 was identified by immunohistochemical test and MRI morphology features; quantitative parameters were analyzed and combined diagnostic models were created by binary logistic regression. The receiver operating characteristics curve with area under the curve (AUC) was used to evaluated diagnostic performance. Interobserver agreement for MRI parameters was evaluated by intraclass correlation coefficient. RESULTS: In the low expression E-cadherin group, the VEGF expression was significantly higher than the high expression group (60.5% vs 37.3%, P < 0.05), and the Ki67 expression had no significant difference (P > 0.05). In the high expression vimentin group, the Ki67 expression was significantly higher than the low expression group (77.3% vs 56.1%, P < 0.05), and the VEGF expression was not significantly significant (P > 0.05). MRI morphological features had no significant diagnostic efficacy for E-cadherin and vimentin expression in rectal cancer (P > 0.05). There were positive and negative correlations between apparent diffusion coefficient (ADC) values with E-cadherin and vimentin expression (P < 0.05), the Ktrans and Kep values were negatively and positively correlated with the expression of E-cadherin and vimentin (P < 0.05). The ADC value (b = 3000 s/mm2) had mild significant diagnostic efficiencies for low E-cadherin expression and high vimentin expression (AUC = 0.63 and 0.644, P < 0.05), the Ktrans and Kep values had significant diagnostic efficiencies (AUC = 0.801 and 0.724, P < 0.05; AUC = 0.722 and 0.628, P < 0.05, respectively). The combined model of ADC, Ktrans, and Kep values had good diagnostic efficiencies for low E-cadherin expression and high vimentin expression (AUC = 0.814 and 0.728, P < 0.05). CONCLUSION: The quantitative parameters of diffusion (with ultra-high b-values) and perfusion MRI can assess the major biomarkers of EMT in rectal cancer, and the combined diagnostic model could further improve the evaluating efficiency for EMT, which possibly can provide valuable information for non-invasive and preoperative assessment of the tumor microenvironment.

Multi-parameter diffusion and perfusion magnetic resonance imaging and radiomics nomogram for preoperative evaluation of aquaporin-1 expression in rectal cancer.

PURPOSE: The overexpression of aquaporin-1 (AQP1) is associated with poor prognosis in rectal cancer. This study aimed to explore the value of multi-parameter diffusion and perfusion MRI and radiomics models in predicting AQP1 high expression. METHODS: This prospective study was performed from July 2019 to February 2021, which included rectal cancer participants after preoperative rectal MRI, with diffusion-weighted imaging, intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and dynamic contrast-enhanced (DCE) sequences. Radiomic features were extracted from MR images, and immunohistochemical tests assessed AQP1 expression. Selected quantitative MRI and radiomic features were analyzed. Receiver operating characteristic (ROC) curves evaluated the predictive performance. The nomogram performance was evaluated by its calibration, discrimen, and clinical utility. The intraclass correlation coefficient evaluated the interobserver agreement for the MRI features. RESULTS: 110 participants with the age of 60.7 ± 12.5 years been enrolled in this study. The apparent diffusion coefficient (ADC), IVIM_D, DKI_diffusivity, and DCE_Ktrans were significantly higher in participants with high AQP1 expression than in those with low expression (P < 0.05). ADC (b = 1000, 2000, and 3000 s/mm2), IVIM_D, DKI_diffusivity, and DCE_Ktrans were positively correlated (r = 0.205, 0.275, 0.37, 0.235, 0.229, and 0.227, respectively; P < 0.05), whereas DKI_Kurtosis was negatively correlated (r = - 0.22, P = 0.021) with AQP1 expression. ADC (b = 3000 s/mm2), IVIM_D, DKI_ diffusivity, DKI_Kurtosis, and DCE_Ktrans had moderate diagnostic efficiencies for high AQP1 expression (AUC = 0.715, 0.636, 0.627, 0.633, and 0.632, respectively; P < 0.05). The radiomic features had excellent predictive efficiency for high AQP1 expression (AUC = 0.967 and 0.917 for training and validation). The model-based nomogram had C-indexes of 0.932 and 0.851 for the training and validation cohorts, which indicated good fitting to the calibration curves (p > 0.05). CONCLUSION: Diffusion and perfusion MRI can indicate the aquaporin-1 expression in rectal cancer, and radiomic features can enhance the predictive efficiency for high AQP1 expression. A nomogram for high aquaporin-1 expression will improve clinical decision-making.

ARMC Subfamily: Structures, Functions, Evolutions, Interactions, and Diseases.

Armadillo repeat-containing proteins (ARMCs) are widely distributed in eukaryotes and have important influences on cell adhesion, signal transduction, mitochondrial function regulation, tumorigenesis, and other processes. These proteins share a similar domain consisting of tandem repeats approximately 42 amino acids in length, and this domain constitutes a substantial platform for the binding between ARMCs and other proteins. An ARMC subfamily, including ARMC1∼10, ARMC12, and ARMCX1∼6, has received increasing attention. These proteins may have many terminal regions and play a critical role in various diseases. On the one hand, based on their similar central domain of tandem repeats, this ARMC subfamily may function similarly to other ARMCs. On the other hand, the unique domains on their terminals may cause these proteins to have different functions. Here, we focus on the ARMC subfamily (ARMC1∼10, ARMC12, and ARMCX1∼6), which is relatively conserved in vertebrates and highly conserved in mammals, particularly primates. We review the structures, biological functions, evolutions, interactions, and related diseases of the ARMC subfamily, which involve more than 30 diseases and 40 bypasses, including interactions and relationships between more than 100 proteins and signaling molecules. We look forward to obtaining a clearer understanding of the ARMC subfamily to facilitate further in-depth research and treatment of related diseases.

Short-term outcomes after totally laparoscopic total gastrectomy with esophagojejunostomy constructed by π-shaped method versus overlap method.

BACKGROUND: Regarding the overlap anastomosis and recently introduced π-shaped anastomosis, there is no consensus on which intracorporeal esophagojejunostomy (EJS) methods are preferred using linear stapler in totally laparoscopic total gastrectomy (TLTG). This study aims to evaluate the short-term outcomes using two methods. METHODS: Patients with upper gastric cancer underwent TLTG with either π-shaped (n = 48) or the modified overlap method using knotless barbed sutures (MOBS) (n = 37) were included in our study. Intraoperative and perioperative outcomes were compared. RESULTS: All patients achieved R0 resection margin. The overall esophagojejunal (E-J)-related complications rate was 7.06%. There was no significant difference between the two groups in terms of postoperative complications, margin distance, numbers of lymph nodes (LNs), length of stay. In the π-shaped group, anastomosis time (19.61 ± 7.17 min vs. 27.09 ± 3.59 min, p < 0.001) was significantly lower. The consumable costs for surgery were similar (44 507.74¥ [42 933.03-46 937.29] vs. 43 718.36¥ [42 743.25-47 256.06], p = 0.825). The first defection time was significantly longer in π-shaped group (131.00 h [93.75-171.25] vs. 100.00 h [85.00-120.00], p = 0.026), whereas the other postoperative recovery parameters were similar. No mortality was observed. CONCLUSIONS: Both methods showed similar short-term postoperative outcomes. The π-shaped technique was faster than the MOBS method without significantly increasing the supplies costs. Large prospective studies are warranted.

Comparison of Conventional Gadoxetate Disodium-Enhanced MRI Features and Radiomics Signatures With Machine Learning for Diagnosing Microvascular Invasion.

OBJECTIVE. This study aimed to determine the best model for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using conventional gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (gadoxetate disodium)-enhanced MRI features and radiomics signatures with machine learning. MATERIALS AND METHODS. This retrospective study included 269 patients with a postoperative pathologic diagnosis of HCC. Gadoxetate disodium-enhanced MRI features were assessed, including T1 relaxation time, tumor margin, tumor size, peritumoral enhancement, peritumoral hypointensity, and ADC. Radiomics models were constructed and validated by machine learning. The least absolute shrinkage and selection operator (LASSO) was used for feature selection, and radiomics-based LASSO models were constructed with six classifiers. Predictive capability was assessed using the ROC AUC. RESULTS. Histologic examination confirmed MVI in 111 (41.3%) of the 269 patients. ADC value, nonsmooth tumor margin, and 20-minute T1 relaxation time showed diagnostic accuracy with AUC values of 0.850, 0.847, and 0.846, respectively (p < .05 for all). A total of 1395 quantitative imaging features were extracted. In the hepatobiliary phase (HBP) model, the support vector machine (SVM), extreme gradient boosting (XGBoost), and logistic regression (LR) classifiers showed greater diagnostic efficiency for predicting MVI, with AUCs of 0.942, 0.938, and 0.936, respectively (p < .05 for all). CONCLUSION. ADC value, nonsmooth tumor margin, and 20-minute T1 relaxation time show high diagnostic accuracy for predicting MVI. Radiomics signatures with machine learning can further improve the ability to predict MVI and are best modeled during HBP. The SVM, XGBoost, and LR classifiers may serve as potential biomarkers to evaluate MVI.

Low expression of tRF-Pro-CGG predicts poor prognosis in pancreatic ductal adenocarcinoma.

BACKGROUND & AIMS: tRFs (tRNA-derived RNA fragments) have been reported to facilitate cancer progression in multiple cancers. However, their role in pancreatic ductal adenocarcinoma (PDAC) remains to be determined. In this study, we mainly investigated the expression of tRF-Pro-CGG in pancreatic ductal adenocarcinoma and evaluated its relationship with the clinicopathology and survival time of patients. METHODS: 37 cases of pancreatic ductal adenocarcinoma, and 15 cases of normal pancreatic tissues were collected which were resected by surgery from January 2017 to June 2020 from the Department of Hepatobiliary and Pancreatic surgery of Changzhou second people's Hospital. The expression of tRF-Pro-CGG in paraffin-embedded tissues was detected by fluorescence in situ hybridization (FISH). The clinical data including age, sex, tumor location, tumor diameter, tumor clinical stage (TNM stage), depth of invasion, regional lymph node metastasis, serum CA199, and serum CEA were collected and analyzed retrospectively, whether the expression tRF-Pro-CGG was correlation with the pathological parameters and clinical outcomes of patients. RESULTS: The expression level of tRF-Pro-CGG was significantly downregulated in PDAC and associated with an advanced TNM stage (P=0.000) and the N stage (P=0.000) of patients. More importantly, low tRF-Pro-CGG expression predicted poor survival in PDAC patients (P=0.003). CONCLUSIONS: TRF-Pro-CGG is under-expressed in PDAC and is associated with short clinical survival and poor prognosis. tRF-Pro-CGG is an independent prognostic factor, which highlights its role as a potential biomarker for PDAC progression and therapy.

Conductivitylike Gilbert Damping due to Intraband Scattering in Epitaxial Iron.

Confirming the origin of Gilbert damping by experiment has remained a challenge for many decades, even for simple ferromagnetic metals. Here, we experimentally identify Gilbert damping that increases with decreasing electronic scattering in epitaxial thin films of pure Fe. This observation of conductivitylike damping, which cannot be accounted for by classical eddy-current loss, is in excellent quantitative agreement with theoretical predictions of Gilbert damping due to intraband scattering. Our results resolve the long-standing question about a fundamental damping mechanism and offer hints for engineering low-loss magnetic metals for cryogenic spintronics and quantum devices.

Diagnostic Value of Gd-EOB-DTPA-Enhanced MRI for the Expression of Ki67 and Microvascular Density in Hepatocellular Carcinoma.

CONTRACT GRANT SPONSOR: National Natural Science Foundation of China; Contract grant number: 81260214. BACKGROUND: Recent studies have highlighted the diagnostic value of Gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in small hepatocellular carcinoma (HCC). Ki67 and CD34 are histologic markers that reflect the proliferation of tumor cells and the microvascular density (MVD). PURPOSE: To explore the diagnostic value of Gd-EOB-DTPA-enhanced MRI for Ki67 expression and MVD in HCC. STUDY TYPE: Retrospective. SUBJECTS: In all, 180 patients with HCC. FIELD STRENGTH/SEQUENCE: 3.0T, Gd-EOB-DTPA-enhanced T1 WI volumetric interpolated breath-hold examination (VIBE) axial fat suppression plain, and enhanced scanning. ASSESSMENT: The T1 relaxation time (T1 rt) and signal intensity (SI) of the lesion were measured. The Ki67 expressions and MVD were evaluated by immunohistochemistry. STATISTICAL TEST: Receiver operating characteristic (ROC) curves were used to analyze the diagnostic efficacy of T1 rt for high Ki67 expression (≥50%) and high MVD (≥100). RESULTS: The T1 rt-20min, rrT1 rt-20min, and SI-hepatobiliary phase (SI-HBP) were strongly correlated with Ki67, the r values were 0.846, -0.765, and -0.760 (P < 0.05), respectively. There were moderate correlations with CD34, with r values -0.444, 0.336, and -0.463 (P < 0.05), respectively. The T1 rt-Pre, T1 rt-20min, SI-Pre, and SI-HBP were significantly different both between the high and low ki67 expression groups (P < 0.05) and between the high MVD and low MVD groups (P < 0.05). In the two groups the T1 rt-20min and SI-HBP was 800.06 ± 128.91 vs. 530.06 ± 139.29 (P < 0.05) and 122.29 ± 39.39 vs. 173.49 ± 46.15 (P < 0.05); T1 rt-20min was found to have high diagnostic efficiency for high ki67 expression (area under the curve [AUC], 0.937; P < 0.05) T1 rt-20min had moderate diagnostic value for high MVD (AUC, 0.716; P < 0.05). DATA CONCLUSION: The T1 rt and SI of Gd-EOB-DTPA-enhanced MRI were correlated with Ki67 expression and MVD. T1 rt-20min has a high diagnostic value for high ki67 expression and high MVD in HCC tissues. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1755-1763.

WITHDRAWN: A personal technical experience and results of a modified end-to-side technique of pancreatojejunostomy: A 350 patients retrospective cohort study.

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Analysis of codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) and its relation to evolution.

BACKGROUND: Analysis of codon usage bias is an extremely versatile method using in furthering understanding of the genetic and evolutionary paths of species. Codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) has remained largely unexplored at present. Hence, the codon usage bias of NPV envelope glycoprotein was analyzed here to reveal the genetic and evolutionary relationships between different viral species in baculovirus genus. RESULTS: A total of 9236 codons from 18 different species of NPV of the baculovirus genera were used to perform this analysis. Glycoprotein of NPV exhibits weaker codon usage bias. Neutrality plot analysis and correlation analysis of effective number of codons (ENC) values indicate that natural selection is the main factor influencing codon usage bias, and that the impact of mutation pressure is relatively smaller. Another cluster analysis shows that the kinship or evolutionary relationships of these viral species can be divided into two broad categories despite all of these 18 species are from the same baculovirus genus. CONCLUSIONS: There are many elements that can affect codon bias, such as the composition of amino acids, mutation pressure, natural selection, gene expression level, and etc. In the meantime, cluster analysis also illustrates that codon usage bias of virus envelope glycoprotein can serve as an effective means of evolutionary classification in baculovirus genus.