Multiparametric magnetic resonance imaging-based assessment of the effect of adenomyosis on determining the depth of myometrial invasion in endometrial cancer.

Background: Accurate preoperative diagnosis of endometrial cancer (EC) with deep myometrial invasion (DMI) is critical to deciding whether to perform lymphadenectomy. However, the presence of adenomyosis makes distinguishing DMI from superficial myometrial invasion (SMI) on magnetic resonance imaging (MRI) challenging. We aimed to evaluate the accuracy of multiparametric MRI (mpMRI) in diagnosing DMI in EC coexisting with adenomyosis (EC-A) compared with EC without coexisting adenomyosis and to evaluate the effect of different adenomyosis subtypes on myometrial invasion (MI) depth in EC. Methods: Patients with histologically confirmed International Federation of Gynecology and Obstetrics (FIGO) stage I EC who underwent preoperative MRI were consecutively included in this 2-center retrospective study. Institution 1 was searched from January 2017 to November 2022 and institution 2 was searched from June 2017 to March 2021. Patients were divided into 2 groups: group A, patients with EC-A; group B, EC patients without coexisting adenomyosis, matched 1:2 according to age ±5 years and tumor grade. A senior radiologist assessed the MRI adenomyosis classification in group A. Then, 2 radiologists (R1/R2) independently interpreted T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), T1-weighted contrast-enhanced (T1CE), and a combination of all images (mpMRI) respectively, and then assessed MI depth. Accuracy, sensitivity, specificity, and the areas under the receiver operating curve (AUC) were calculated. The chi-square test was used to compare the accuracy of diagnosing DMI. Interobserver agreement was evaluated using the Kappa test. Results: A total of 70 cases in group A and 140 cases in group B were included. The accuracy, sensitivity, and specificity of consensus were 94.3% [95% confidence interval (CI): 88.9-99.7%] vs. 92.1% (95% CI: 87.7-96.6%), 60.0% (95% CI: 17-92.7%) vs. 86.7% (95% CI: 68.4-95.6%), and 96.9% (95% CI: 88.4-95.5%) vs. 93.6% (95% CI: 86.8-97.2%) (group A vs. group B, respectively). There was no significant difference in the diagnostic accuracy of DMI on each sequence between the groups (Reviewer 1/Reviewer 2): PT2WI=0.14/0.17, PDWI=0.50/0.33, PT1CE=0.90/0.18, PmpMRI=0.50/0.37. The AUC for T2WI, DWI, T1CE, and mpMRI (Reviewer 1/Reviewer 2), respectively, were 0.54 (95% CI: 0.42-0.66)/0.78 (95% CI: 0.67-0.87), 0.63 (95% CI: 0.50-0.74)/0.77 (95% CI: 0.65-0.86), 0.69 (95% CI: 0.57-0.80)/0.79 (95% CI: 0.68-0.88), and 0.91 (95% CI: 0.82-0.97)/0.89 (95% CI: 0.79-0.95) (group A) and 0.83 (95% CI: 0.76-0.89)/0.85 (95% CI: 0.78-0.90), 0.83 (95% CI: 0.76-0.89)/0.86 (95% CI: 0.79-0.91), 0.88 (95% CI: 0.82-0.93)/0.86 (95% CI: 0.80-0.92), and 0.91 (95% CI: 0.85-0.95)/0.87 (95% CI: 0.80-0.92) (group B). Interobserver agreement was highest with mpMRI [κ=0.387/0.695 (case/control)]. The consensus results of MRI categorization of adenomyosis revealed no significant difference in the accuracy of diagnosing DMI by adenomyosis subtype (Pspatial relationship>0.99, Paffected area=0.52, Paffected pattern=0.58, Paffected size>0.99). Conclusions: The presence of adenomyosis or adenomyosis subtype had no significant effect on the interpretation of the depth of MI. T1CE can increase the contrast between adenomyosis and cancer foci; therefore, the information provided by T1CE should be valued.

Diagnostic Value of Clear Cell Likelihood Score v1.0 and v2.0 for Common Subtypes of Small Renal Masses: A Multicenter Comparative Study.

BACKGROUND: Clear cell likelihood score (ccLS) is reliable for diagnosing small renal masses (SRMs). However, the diagnostic value of Clear cell likelihood score version 1.0 (ccLS v1.0) and v2.0 for common subtypes of SRMs might be a potential score extension. PURPOSE: To compare the diagnostic performance and interobserver agreement of ccLS v1.0 and v2.0 for characterizing five common subtypes of SRMs. STUDY TYPE: Retrospective. POPULATION: 797 patients (563 males, 234 females; mean age, 53 ± 12 years) with 867 histologically proven renal masses. FIELD STRENGTH/SEQUENCES: 3.0 and 1.5 T/T2 weighted imaging, T1 weighted imaging, diffusion-weighted imaging, a dual-echo chemical shift (in- and opposed-phase) T1 weighted imaging, multiphase dynamic contrast-enhanced imaging. ASSESSMENT: Six abdominal radiologists were trained in the ccLS algorithm and independently scored each SRM using ccLS v1.0 and v2.0, respectively. All SRMs had definite pathological results. The pooled area under curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the diagnostic performance of ccLS v1.0 and v2.0 for characterizing common subtypes of SRMs. The average κ values were calculated to evaluate the interobserver agreement of the two scoring versions. STATISTICAL TESTS: Random-effects logistic regression; Receiver operating characteristic analysis; DeLong test; Weighted Kappa test; Z test. The statistical significance level was P < 0.05. RESULTS: The pooled AUCs of clear cell likelihood score version 2.0 (ccLS v2.0) were statistically superior to those of ccLS v1.0 for diagnosing clear cell renal cell carcinoma (ccRCC) (0.907 vs. 0.851), papillary renal cell carcinoma (pRCC) (0.926 vs. 0.888), renal oncocytoma (RO) (0.745 vs. 0.679), and angiomyolipoma without visible fat (AMLwvf) (0.826 vs. 0.766). Interobserver agreement for SRMs between ccLS v1.0 and v2.0 is comparable and was not statistically significant (P = 0.993). CONCLUSION: The diagnostic performance of ccLS v2.0 surpasses that of ccLS v1.0 for characterizing ccRCC, pRCC, RO, and AMLwvf. Especially, the standardized algorithm has optimal performance for ccRCC and pRCC. ccLS has potential as a supportive clinical tool. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Design and Screening of Fluorescent Probes Based upon Hemicyanine Dyes for Monitoring Mitochondrial Viscosity in Living Cells.

Viscosity, at the subcellular level, plays a crucial role as a physicochemical factor affecting microenvironment homeostasis. Abnormal changes in mitochondrial viscosity often lead to various diseases in the organism. Based on the twisted intramolecular charge transfer mechanism, four hemicyanine dye fluorescent probes (HT-SA, HT-SA-S, HT-Bzh, and HT-NA) were designed and synthesized for viscosity response. The single bond between the nitrogen-containing heterocycle and the carbon-carbon double in the structure of the probe bond served as the viscosity response site. Finally, the probe HT-Bzh was screened as the optimal mitochondrial viscosity probe according to its responsiveness, targeting, and interference resistance. The fluorescence intensity of the probe HT-Bzh increased 22-fold when the viscosity was increased from 13.75 to 811.2 cP. In summary, all four viscosity probes we have developed can be used in different applications depending on the external environment, providing a valuable reference for the design of potential tools to address viscosity monitoring in biological systems.

Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.

PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm. METHODS: Patients diagnosed with HCC who underwent locoregional therapy were retrospectively collected. We constructed a deep learning-based subtraction model and automatically generated arterial subtraction images. Two radiologists evaluated LR-TR category on ordinary images and then evaluated again on ordinary images plus arterial subtraction images after a 2-month washout period. The reference standard for viability was tumor stain on the digital subtraction hepatic angiography within 1 month after MRI. RESULTS: 286 observations of 105 patients were ultimately enrolled. 157 observations were viable and 129 observations were nonviable according to the reference standard. The sensitivity and accuracy of LR-TR algorithm for detecting viable HCC significantly increased with the application of arterial subtraction images (87.9% vs. 67.5%, p < 0.001; 86.4% vs. 75.9%, p < 0.001). And the specificity slightly decreased without significant difference when the arterial subtraction images were added (84.5% vs. 86.0%, p = 0.687). The AUC of LR-TR algorithm significantly increased with the addition of arterial subtraction images (0.862 vs. 0.768, p < 0.001). The arterial subtraction images also improved inter-reader agreement (0.857 vs. 0.727). CONCLUSION: Extended application of deep learning-based arterial subtraction images on extracellular agents-enhanced MRI can increase the sensitivity of LR-TR algorithm for detecting viable HCC without significant change in specificity.

Clinical research progress of ridaforolimus (AP23573, MK8668) over the past decade: a systemic review.

Rapamycin, an established mTOR inhibitor in clinical practice, is widely recognized for its therapeutic efficacy. Ridaforolimus, a non-prodrug rapalog, offers improved aqueous solubility, stability, and affinity compared to rapamycin. In recent years, there has been a surge in clinical trials involving ridaforolimus. We searched PubMed for ridaforolimus over the past decade and selected clinical trials of ridaforolimus to make a summary of the research progress of ridaforolimus in clinical trials. The majority of these trials explored the application of ridaforolimus in treating various tumors, including endometrial cancer, ovarian cancer, prostate cancer, breast cancer, renal cell carcinoma, and other solid tumors. These trials employed diverse drug combinations, incorporating agents such as ponatinib, bicalutamide, dalotuzumab, MK-2206, MK-0752, and taxanes. The outcomes of these trials unveiled the diverse potential applications of ridaforolimus in disease treatment. Our review encompassed analyses of signaling pathways, ridaforolimus as a single therapeutic agent, its compatibility in combination with other drugs, and an assessment of adverse events (AEs). We conclude by recommending further research to advance our understanding of ridaforolimus's clinical applications.

Identification and utility exploration of a highly potent and long-acting bullfrog GLP-1 analogue in GLP-1 and amylin combination therapy.

This study assesses the efficacy of an innovative therapeutic approach that combines GLP-1 and amylin analogues for weight reduction. Focusing on GLP-1 analogues from bullfrog (Rana catesbeiana), we designed ten bGLP-1 analogues with various modifications. Among them, bGLP-10 showed high potency in binding and activating GLP-1 receptors, with superior albumin affinity. In diet-induced obesity (DIO) mice fed a high-fat diet, bGLP-10 demonstrated significant superiority over semaglutide in reducing blood sugar and food intake at a dose of 10 nmol/kg (P < 0.001). Notably, in a chronic study involving DIO mice, the combination of bGLP-10 with the amylin analogue cagrilintide led to a more substantial weight loss (-38.4%, P < 0.001) compared to either the semaglutide-cagrilintide combination (-23.0%) or cagrilintide (-5.7%), bGLP-10 (-16.1%), and semaglutide (-10.9%) alone. Furthermore, the bGLP-10 and cagrilintide combination exhibited superior glucose control and liver lipid management compared to the semaglutide-cagrilintide combination (P < 0.001). These results highlight bGLP-10's potential in GLP-1 and amylin-based therapies and suggest exploring more GLP-1 analogues from natural sources for anti-obesity and anti-diabetic treatments.

DRAC 2022: A public benchmark for diabetic retinopathy analysis on ultra-wide optical coherence tomography angiography images.

We described a challenge named "DRAC - Diabetic Retinopathy Analysis Challenge" in conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022). Within this challenge, we provided the DRAC datset, an ultra-wide optical coherence tomography angiography (UW-OCTA) dataset (1,103 images), addressing three primary clinical tasks: diabetic retinopathy (DR) lesion segmentation, image quality assessment, and DR grading. The scientific community responded positively to the challenge, with 11, 12, and 13 teams submitting different solutions for these three tasks, respectively. This paper presents a concise summary and analysis of the top-performing solutions and results across all challenge tasks. These solutions could provide practical guidance for developing accurate classification and segmentation models for image quality assessment and DR diagnosis using UW-OCTA images, potentially improving the diagnostic capabilities of healthcare professionals. The dataset has been released to support the development of computer-aided diagnostic systems for DR evaluation.

Association between deep learning measured retinal vessel calibre and incident myocardial infarction in a retrospective cohort from the UK Biobank.

BACKGROUND: Cardiovascular disease is a leading cause of global death. Prospective population-based studies have found that changes in retinal microvasculature are associated with the development of coronary artery disease. Recently, artificial intelligence deep learning (DL) algorithms have been developed for the fully automated assessment of retinal vessel calibres. METHODS: In this study, we validate the association between retinal vessel calibres measured by a DL system (Singapore I Vessel Assessment) and incident myocardial infarction (MI) and assess its incremental performance in discriminating patients with and without MI when added to risk prediction models, using a large UK Biobank cohort. RESULTS: Retinal arteriolar narrowing was significantly associated with incident MI in both the age, gender and fellow calibre-adjusted (HR=1.67 (95% CI: 1.19 to 2.36)) and multivariable models (HR=1.64 (95% CI: 1.16 to 2.32)) adjusted for age, gender and other cardiovascular risk factors such as blood pressure, diabetes mellitus (DM) and cholesterol status. The area under the receiver operating characteristic curve increased from 0.738 to 0.745 (p=0.018) in the age-gender-adjusted model and from 0.782 to 0.787 (p=0.010) in the multivariable model. The continuous net reclassification improvements (NRIs) were significant in the age and gender-adjusted (NRI=21.56 (95% CI: 3.33 to 33.42)) and the multivariable models (NRI=18.35 (95% CI: 6.27 to 32.61)). In the subgroup analysis, similar associations between retinal arteriolar narrowing and incident MI were observed, particularly for men (HR=1.62 (95% CI: 1.07 to 2.46)), non-smokers (HR=1.65 (95% CI: 1.13 to 2.42)), patients without DM (HR=1.73 (95% CI: 1.19 to 2.51)) and hypertensive patients (HR=1.95 (95% CI: 1.30 to 2.93)) in the multivariable models. CONCLUSION: Our results support DL-based retinal vessel measurements as markers of incident MI in a predominantly Caucasian population.

Intravoxel incoherent motion assessment of liver fibrosis staging in MASLD.

PURPOSE: Partial correlation analysis was performed to account for the interference of steatosis changes and inflammatory factors, to determine the true correlation between fibrosis and IVIM parameters (Dfast, Dslow, and F), and to evaluate the diagnostic efficacy of IVIM for liver fibrosis. METHODS: A total of 106 patients with metabolic dysfunction-associated steatotic liver disease (MASLD) examined by IVIM from November 2016 to November 2023 at our hospital were retrospectively included. Preliminary analysis of each IVIM parameter and correlations with pathological findings were performed using Spearman correlation analysis, and partial correlation analysis was used to exclude the interference of other pathological factors, thus yielding the true correlations between IVIM parameters (Dfast, Dslow, and F) and pathology. The diagnostic efficacy of IVIM parameters for diagnosing MASLD was assessed via receiver operating characteristic (ROC) curve analysis. RESULTS: Spearman correlation analysis of all the IVIM parameters revealed correlations with steatosis, lobular inflammation, and ballooning. Partial correlation analysis indicated that Dfast was correlated with the pathological fibrosis stage (r = - 0.593, P < 0.001), Dslow was correlated with the pathological steatosis score (r = - 0.313, P < 0.05), and F was correlated with the pathological fibrosis stage and steatosis score (r = - 0.456 and 0.255, P < 0.001 and P < 0.05). In the diagnosis of hepatic fibrosis, significant hepatic fibrosis, advanced liver fibrosis and cirrhosis, Dfast achieved areas under the ROC curve of 0.763, 0.801, 0.853, and 0.897, respectively. The threshold values for diagnosing different fibrosis stages using Dfast (10-3 mm2/s) were 57.613, 54.587, 52.714, and 51.978, respectively. CONCLUSION: According to our partial correlation analysis, there was a moderate correlation between Dfast and F according to fibrosis stage, and Dfast was not influenced by inflammation or steatosis when diagnosing fibrosis in MASLD patients. A relatively close Dfast threshold is insufficient for accurately and noninvasively assessing various stages of MASLD fibrosis. In clinical practice, this approach can be considered an alternative method for the preliminary assessment of fibrosis in MASLD patients.

Quantitative Comparison of Liver Volume, Proton Density Fat Fraction, and Time Burden between Automatic Whole Liver Segmentation and Manual Sampling MRI Strategies for Diagnosing Metabolic Dysfunction-associated Steatotic Liver Disease in Obese Patients.

BACKGROUND: The performance of automatic liver segmentation and manual sampling MRI strategies needs be compared to determine interchangeability. OBJECTIVE: To compare automatic liver segmentation and manual sampling strategies (manual whole liver segmentation and standardized manual region of interest) for performance in quantifying liver volume and MRI-proton density fat fraction (MRI-PDFF), identifying steatosis grade, and time burden. METHODS: Fifty patients with obesity who underwent liver biopsy and MRI between December 2017 and November 2018 were included. Sampling strategies included automatic and manual whole liver segmentation and 4 and 9 large regions of interest. Intraclass correlation coefficient (ICC), Bland-Altman, linear regression, receiver operating characteristic curve, and Pearson correlation analyses were performed. RESULTS: Automatic whole liver segmentation liver volume and manual whole liver segmentation liver volume showed excellent agreement (ICC=0.97), high correlation (R2=0.96), and low bias (3.7%, 95% limits of agreement, -4.8%, 12.2%) in liver volume. There was the best agreement (ICC=0.99), highest correlation (R2=1.00), and minimum bias (0.84%, 95% limits of agreement, -0.20%, 1.89%) between automated whole liver segmentation MRI-PDFF and manual whole liver segmentation MRI-PDFF. There was no difference of each paired comparison of receiver operating characteristic curves for detecting steatosis (P=0.07-1.00). The minimum time burden for automatic whole liver segmentation was 0.32 s (0.32-0.33 s). CONCLUSION: Automatic measurement has similar effects to manual measurement in quantifying liver volume, MRI-PDFF, and detecting steatosis. Time burden of automatic whole liver segmentation is minimal among all sampling strategies. Manual measurement can be replaced by automatic measurement to improve quantitative efficiency.

Mitochondrial dysfunction in type 2 diabetes: A neglected path to skeletal muscle atrophy.

Over the course of several decades, robust research has firmly established the significance of mitochondrial pathology as a central contributor to the onset of skeletal muscle atrophy in individuals with diabetes. However, the specific intricacies governing this process remain elusive. Extensive evidence highlights that individuals with diabetes regularly confront the severe consequences of skeletal muscle degradation. Deciphering the sophisticated mechanisms at the core of this pathology requires a thorough and meticulous exploration into the nuanced factors intricately associated with mitochondrial dysfunction.

Clinical findings of hyperechoic substantia nigra in patients with Parkinson's disease.

This study aims to analyse hyperechoic substantia nigra (HSN) characteristics and the correlation of HSN with clinical features and blood biomarkers in patients with Parkinson's disease (PD). Transcranial sonography (TCS) evaluations of the substantia nigra (SN) were performed in 40 healthy controls and 71 patients with PD, including patients with SN hyperechogenicity (SN+) and those with normal SN echogenicity (SN-). Evaluation of motor and non-motor symptoms was assessed by a series of rating scales. The uricase method was used to determine serum uric acid (UA) levels, and enzyme-linked immunosorbent assay (ELISA) was used to measure plasma interleukin (IL)-1ß levels. TCS showed 92.50% specificity and 61.97% sensitivity in differentiating PD patients from controls. The area of SN+ contralateral to the side of initial motor symptoms (SNcontra ) was larger than that ipsilateral to the side of initial motor symptoms (SNipsi ). The PDSN+ group had lower Argentine Hyposmia Rating Scale (AHRS) scores and UA levels than the PDSN- group. Binary logistic regression analysis revealed that AHRS scores and UA levels could be independent predictors for HSN. The larger SN echogenic area (SNL ) sizes positively correlated with plasma IL-1ß levels in PD patients with SN+. The present study provides further evidence of the potential of SN echogenicity as an imaging biomarker for PD diagnosis. PD patients with HSN have more severe non-motor symptoms of hyposmia. HSN in PD patients is related to the mechanism of abnormal iron metabolism and microglial activation.

Spatial transcriptomics reveals heterogeneity of histological subtypes between lepidic and acinar lung adenocarcinoma.

BACKGROUND: Patients who possess various histological subtypes of early-stage lung adenocarcinoma (LUAD) have considerably diverse prognoses. The simultaneous existence of several histological subtypes reduces the clinical accuracy of the diagnosis and prognosis of early-stage LUAD due to intratumour intricacy. METHODS: We included 11 postoperative LUAD patients pathologically confirmed to be stage IA. Single-cell RNA sequencing (scRNA-seq) was carried out on matched tumour and normal tissue. Three formalin-fixed and paraffin-embedded cases were randomly selected for 10× Genomics Visium analysis, one of which was analysed by digital spatial profiler (DSP). RESULTS: Using DSP and 10× Genomics Visium analysis, signature gene profiles for lepidic and acinar histological subtypes were acquired. The percentage of histological subtypes predicted for the patients from samples of 11 LUAD fresh tissues by scRNA-seq showed a degree of concordance with the clinicopathologic findings assessed by visual examination. DSP proteomics and 10× Genomics Visium transcriptomics analyses revealed that a negative correlation (Spearman correlation analysis: r = -.886; p = .033) between the expression levels of CD8 and the expression trend of programmed cell death 1(PD-L1) on tumour endothelial cells. The percentage of CD8+ T cells in the acinar region was lower than in the lepidic region. CONCLUSIONS: These findings illustrate that assessing patient histological subtypes at the single-cell level is feasible. Additionally, tumour endothelial cells that express PD-L1 in stage IA LUAD suppress immune-responsive CD8+ T cells.

Rapid automated extracellular vesicle isolation and miRNA preparation on a cost-effective digital microfluidic platform.

As a prerequisite for extracellular vesicle (EV) -based studies and diagnosis, effective isolation, enrichment and retrieval of EV biomarkers are crucial to subsequent analyses, such as miRNA-based liquid biopsy for non-small-cell lung cancer (NSCLC). However, most conventional approaches for EV isolation suffer from lengthy procedure, high cost, and intense labor. Herein, we introduce the digital microfluidic (DMF) technology to EV pretreatment protocols and demonstrate a rapid and fully automated sample preparation platform for clinical tumor liquid biopsy. Combining a reusable DMF chip technique with a low-cost EV isolation and miRNA preparation protocol, the platform completes automated sample processing in 20-30 min, supporting immediate RT-qPCR analyses on EV-derived miRNAs (EV-miRNAs). The utility and reliability of the platform was validated via clinical sample processing for EV-miRNA detection. With 23 tumor and 20 non-tumor clinical plasma samples, we concluded that EV-miR-486-5p and miR-21-5p are effective biomarkers for NSCLC with a small sample volumn (20-40 µL). The result was consistent to that of a commercial exosome miRNA extraction kit. These results demonstrate the effectiveness of DMF in EV pretreatment for miRNA detection, providing a facile solution to EV isolation for liquid biopsy.

Superiority of spleen stiffness on two-dimensional magnetic resonance elastography over liver stiffness and serum tests in assessing portal hypertension in chronic liver disease.

Background: The value of magnetic resonance elastography (MRE) in portal hypertension (PH) has yet to be determined in the context of chronic liver disease (CLD). This study examined the value of MRE for the prediction of hepatic venous pressure gradient (HVPG) and high-risk esophageal varices (EVs) in a CLD cohort with a generally high HVPG. Methods: Patients with CLD who underwent both HVPG measurement and two-dimensional MRE examination at Beijing Friendship Hospital between April 2018 and March 2022 were prospectively included. Two-dimensional MRE was performed within the liver and spleen. Endoscopy results and laboratory parameters were collected. Some selected published serum markers were calculated, including fibrosis 4, aspartate aminotransferase-to-platelet ratio index, and King's score. The efficacy of the parameters for assessing PH was analyzed by using the Pearson correlation coefficient, linear and logistic regression, and receiver operating characteristic curve analyses. Results: A total of 48 patients were included. The mean HVPG was 16.8±5.8 mmHg. Among these patients, 47 patients had PH (HVPG >5 mmHg), and 43 patients had clinically significant PH (HVPG ≥10 mmHg). Among the parameters associated with HVPG, the strongest correlation was found for spleen stiffness (SS) (R=0.638; P<0.001). In multiple regression analyses, SS was independently associated with an elevated HVPG and high-risk EVs. The areas under the receiver operating characteristic curve of SS for identifying patients with an HVPG ≥16 mmHg, HVPG ≥20 mmHg, and high-risk EVs were 0.790, 0.822, and 0.886, respectively, which were higher than those of liver stiffness (LS) and serum markers but slightly inferior to that of fibrosis 4 (area under the receiver operating characteristic curve =0.844) in identifying an HVPG ≥16 mmHg. SS cutoff values of 9.5, 10.05, and 9.9 kPa were selected to rule out the presence of an HVPG ≥16 mmHg, HVPG ≥20 mmHg, and high-risk EVs (sensitivity: 100%, 100%, and 100%, respectively; specificity: 45.5%, 50%, and 60%, respectively). Conclusions: In patients with generally high HVPG, SS measured by two-dimensional MRE may be a better predictor of HVPG values and high-risk EVs than LS and serum markers.

The staging of nonalcoholic fatty liver disease fibrosis: A comparative study of MR elastography and the quantitative DCE-MRI exchange model.

Objectives: To evaluate the efficacy and image processing time of the dynamic contrast-enhanced MRI (DCE-MRI) exchange model in liver fibrosis staging and compare it to the efficacy of magnetic resonance elastography (MRE). Methods: The subjects were 45 patients with nonalcoholic fatty liver disease (NAFLD) who underwent MRE and DCE-MRI in our hospital. Liver biopsy results were available for all patients. Spearman rank correlation coefficients were used to compare the correlations among MRE, DCE-MRI and liver fibrosis parameters. Quantitative DCE-MRI parameters, MRE-derived liver stiffness measurement (LSM), and the results of a combined DCE-MRI + MRE logistic regression model were compared in terms of the area under the receiver operating characteristic curve (AUC). We also compared the scanning and postprocessing times of the MRE and DCE-MRI techniques. Results: The correlation coefficients between the following parameters of interest and liver fibrosis were as follows: capillary permeability-surface area product (PS; DCE-MRI parameter), -0.761; portal blood flow (Fp; DCE-MRI parameter), -0.754; MRE-LSM, 0.835. Some DCE-MRI parameters (PS, Fp) had slightly greater AUC values than MRE-LSM for diagnosing the presence or absence of liver fibrosis, and the combined model had the highest AUC value for all stages except F4, but there was no significant difference in the diagnostic efficacy of the DCE-MRI, MRE, and combined models for any stage of fibrosis. The average scanning times for MRE and DCE-MRI were 17 s and 330 s, respectively, and the average postprocessing times were 45.5 s and 342.7 s, respectively. Conclusions: In the absence of MRE equipment, DCE-MRI represents an alternative technique. However, MRE is a quicker and simpler method for assessing fibrosis than DCE-MRI in the clinic.

Increased plasma lipocalin-2 levels are associated with nonmotor symptoms and neuroimaging features in patients with Parkinson's disease.

Lipocalin-2 (LCN2) is essential for the regulation of neuroinflammation and cellular uptake of iron. This study aimed to evaluate plasma LCN2 levels and explore their correlation with clinical and neuroimaging features in Parkinson's disease (PD) patients. Enzyme-linked immunosorbent assay (ELISA) was used to measure plasma LCN2 levels in 120 subjects. Evaluation of motor symptoms and nonmotor symptoms in PD patients was assessed by the associated scales. Voxel-based morphometry (VBM) was used to evaluate brain volume alterations, and quantitative susceptibility mapping (QSM) was used to quantitatively analyze brain iron deposition in 46 PD patients. Plasma LCN2 levels were significantly higher in PD patients than those in healthy controls. LCN2 levels were negatively correlated with Montreal Cognitive Assessment (MoCA) scores, total brain gray matter volume (GMV), and GMV/total intracranial volume (TIV) ratio, but positively correlated with Hamilton Anxiety Rating Scale (HAMD) scores and mean QSM values of the bilateral substantial nigra (SN). Receiver operating characteristic (ROC) curves confirmed that plasma LCN2 levels had good predictive accuracy for PD. The results suggest that plasma LCN2 levels have potential as a biomarker for the diagnosis of PD. LCN2 may be a therapeutic target for neuroinflammation and brain iron deposition.

Multi-DNA-Modified Double-Network Hydrogel with Customized Microstructure: A Novel System for Living Circulating Tumor Cells Capture and Real-Time Detection.

The precise and effective isolation of living circulating tumor cells (CTCs) from peripheral blood, followed by their real-time monitoring, is crucial for diagnosing cancer patients. In this study, a cell-imprinted double-network (DN) hydrogel modified with circular multi-DNA (CMD), coined the CMD-imprinted hydrogel with fixed cells as templates (CMD-CIDH), was developed. The hydrogel featured a customized surface for proficient capture of viable CTCs and in situ real-time fluorescent detection without subsequent release. The customized surface, constructed using polyacrylamide/chitosan DN hydrogel as the matrix on the cell template, had a dense network structure, thereby ensuring excellent stability and a low degradation rate. Optimal capture efficiencies, recorded at 93 ± 3% for MCF-7 cells and 90 ± 2% for Hela cells, were achieved by grafting the CMD and adjusting the nodule size on the customized surface. The capture efficiency remained significantly high at 67 ± 11% in simulated breast cancer patient experiments even at a minimal concentration of 5 cells mL-1. Furthermore, CMD grafted onto the surface produced a potent fluorescence signature, enabling in situ real-time fluorescent detection of the target cell's growth state even in complex environments. The customized surface is highly efficient for screening CTCs in peripheral blood and has promising potential for setting up the CTCs culture.

Microbes translocation from oral cavity to nasopharyngeal carcinoma in patients.

The presence of oral microbes in extra-oral sites is linked to gastrointestinal cancers. However, their potential ectopically colonization in the nasopharynx and impact on local cancer development remains uncertain. Our study involving paired nasopharyngeal-oral microbial samples from nasopharyngeal carcinoma (NPC) patients and controls unveils an aberrant oral-to-nasopharyngeal microbial translocation associated with increased NPC risk (OR = 4.51, P = 0.012). Thirteen species are classified as oral-translocated and enriched in NPC patients. Among these, Fusobacterium nucleatum and Prevotella intermedia are validated through culturomics and clonal strain identification. Nasopharyngeal biopsy meta-transcriptomes confirm these microbes within tumors, influencing local microenvironment and cytokine response. These microbes correlate significantly with the Epstein-Barr virus (EBV) loads in the nasopharynx, exhibiting an increased dose-response relationship. Collectively, our study identifies oral microbes migrating to the nasopharynx, infiltrating tumors, impacting microenvironments and linking with EBV infection. These results enhance our understanding of abnormal microbial communication and their roles in carcinogenesis.

The timing phase affected the inconsistency of APHE subtypes of liver observations in patients at risk for HCC on the multi-hepatic arterial phase imaging.

OBJECTIVE: To investigate whether liver observations in patients at risk for hepatocellular carcinoma (HCC) display inconsistent arterial phase hyperenhancement (APHE) subtypes on the multi-hepatic arterial phase imaging (mHAP) and to further investigate factors affecting inconsistent APHE subtype of observations on mHAP imaging. METHODS: From April 2018 to June 2021, a total of 141 patients at high risk of HCC with 238 liver observations who underwent mHAP MRI acquisitions were consecutively included in this retrospective study. Two experienced radiologists reviewed individual arterial phase imaging independently and assessed the enhancement pattern of each liver observation according to LI-RADS. Another two experienced radiologists identified and recorded the genuine timing phase of each phase independently. When a disagreement appeared between the two radiologists, another expert participated in the discussion to get a final decision. A separate descriptive analysis was used for all observations scored APHE by the radiologists. The Kappa coefficient was used to determine the agreement between the two radiologists. Univariate analysis was performed to investigate the factors affecting inconsistent APHE subtype of liver observations on mHAP imaging. RESULTS: The interobserver agreement was substantial to almost perfect agreement on the assessment of timing phase (κ = 0.712-0.887) and evaluation of APHE subtype (κ = 0.795-0.901). A total of 87.8% (209/238) of the observations showed consistent nonrim APHE and 10.2% (24/238) of the observations showed consistent rim APHE on mHAP imaging. A total of 2.1% (5/238) of the liver observations were considered inconsistent APHE subtypes, and all progressed nonrim to rim on mHAP imaging. 87.9% (124/141) of the mHAP acquisitions were all arterial phases and 12.1% (17/141) of the mHAP acquisitions obtained both the arterial phase and portal venous phase. Univariate analysis was performed and found that the timing phase of mHAP imaging affected the consistency of APHE subtype of liver observations. When considering the timing phase and excluding the portal venous phase acquired by mHAP imaging, none of the liver observations showed inconsistent APHE subtypes on mHAP imaging. CONCLUSION: The timing phase which mHAP acquisition contained portal venous phase affected the inconsistency of APHE subtype of liver observations on mHAP imaging. When evaluating the APHE subtype of liver observations, it's necessary to assess the timing of each phase acquired by the mHAP technique at first.