Simultaneous multislice echo-planar diffusion-weighted imaging (DWI) in patients with focal liver lesions: a comparative study with conventional DWI.

Background: Simultaneous multislice (SMS) technology improves acquisition efficiency of diffusion-weighted imaging (DWI). This study aimed to evaluate the performance of SMS-DWI in image quality and apparent diffusion coefficient (ADC) measurements for focal liver lesions (FLLs) as compared with that of conventional DWI (CON-DWI). Methods: The institutional ethics committee of West China Hospital, Sichuan University approved this single-center, prospective study conducted from February 2021 to March 2022. Free-breathing SMS-DWI and CON-DWI examinations were acquired on a 3-T scanner with b-values of 50, 400, and 800 s/mm2. Qualitative image quality and quantitative measurements of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC were compared between SMS-DWI and CON-DWI. The ADC values for FLLs were further compared between SMS-DWI and CON-DWI in different patient subgroups. The intra- and interreader agreements were assessed. Significance was set at P<0.05. Results: This study included 116 patients (96 males, 20 females; mean age 52.0±10.7 years) with 119 FLLs. No significant differences were observed between SMS-DWI and CON-DWI regarding overall image quality in any b-value DWIs, and there were also no differences observed between SMS-DWI and CON-DWI (b=800 s/mm2) for either SNR or CNR (both P values >0.05). ADC values obtained from CON-DWI were higher than those from SMS-DWI in all FLLs [(1.31±0.47)×10-3 vs. (1.26±0.46)×10-3 mm2/s; P=0.004], and similar findings were observed across the different patient subgroups. The consistency analysis showed intrareader intraclass correlation coefficient (ICC) values of 0.792-0.944 and interreader ICC values of 0.758-0.861 for quantitative measurements (SNR, CNR, and ADC) and kappa values of 0.609-0.878 for qualitative image quality. Conclusions: SMS-DWI achieved a 37% reduction in scan time compared to CON-DWI while maintaining comparable overall image quality. Notably, the ADC values for FLLs were observed to be quantitatively lower with SMS-DWI.

The Chemo-Immunotherapeutic Roles of Tumor-Derived Extracellular Vesicle-Based Paclitaxel Delivery System in Hepatocarcinoma.

As a first-line chemotherapeutic agent, albumin-bound paclitaxel (PA) has a considerable effect on the treatment of various cancers. However, in chemotherapy for hepatocarcinoma, the sensitivity to PA is low owing to the innate resistance of hepatocarcinoma cells; the toxicity and side effects are severe, and the clinical treatment impact is poor. In this study, we present a unique nanodrug delivery system. The ultraviolet (UV)-induced tumor-cell-derived extracellular vesicles (EVs) were isolated and purified by differential centrifugation. Then, PA was loaded by coextrusion to create a vesicle drug delivery system (EVPA). By employing the EV-dependent enhanced retention effect and specific homing effect, EVPA would passively and actively target tumor tissues, activate the immune response to release PA, and achieve the combination therapeutic effect of chemo-immunotherapy on hepatocarcinoma. We demonstrated that the tumor-killing effect of EVPA is superior to that of PA, both in vivo and in vitro and that EVPA can be effectively taken up by hepatocarcinoma and dendritic cells, activate the body's specific immune response, promote the infiltration of CD4+ and CD8+ T cells in tumor tissues, and exert a precise killing effect on hepatocarcinoma cells via chemo-immunotherapy.

MRI-based prediction of the need for wide resection margins in patients with single hepatocellular carcinoma.

OBJECTIVES: To develop an MRI-based score that enables individualized predictions of the survival benefit of wide over narrow resection margins. MATERIALS AND METHODS: This single-center retrospective study (December 2011 to May 2022) included consecutive patients who underwent curative-intent resection for single Barcelona Clinic Liver Cancer (BCLC) 0/A HCC and preoperative contrast-enhanced MRI. In patients with narrow resection margins, preoperative demographic, laboratory, and MRI variables independently associated with early recurrence-free survival (RFS) were identified using Cox regression analyses, which were employed to develop a predictive score (named "MARGIN"). Survival outcomes were compared between wide and narrow resection margins in a propensity-score matched cohort for the score-stratified low- and high-risk groups, respectively. RESULTS: Four hundred nineteen patients (median age, 54 years; 361 men) were included, 282 (67.3%) undergoing narrow resection margins. In patients with narrow resection margins, age, alpha-fetoprotein (AFP) > 400 ng/mL, protein induced by vitamin K absence or antagonist-II (PIVKA-II) > 200 mAU/mL, radiological involvement of liver capsule, and infiltrative appearance were associated with early RFS (p values, 0.002-0.04) and formed the MARGIN score with a testing dataset C-index of 0.75 (95% CI: 0.65-0.84). In the matched cohort, wide resection margin was associated with improved early RFS rate for the high-risk group (MARGIN score ≥ - 1.3; 71.1% vs 41.0%; p = 0.02), but not for the low-risk group (MARGIN score < - 1.3; 79.7% vs 76.1%; p = 0.36). CONCLUSION: In patients with single BCLC 0/A HCC, the MARGIN score may serve as promising decision-making to indicate the need for wide resection margins. CLINICAL RELEVANCE STATEMENT: The MARGIN score has the potential to identify patients who would benefit more from wide resection margins than narrow resection margins, improving the postoperative survival of patients with single BCLC 0/A hepatocellular carcinoma (HCC). KEY POINTS: Age, AFP, PIVKA-II, radiological involvement of liver capsule, and infiltrative appearance were associated with early RFS and formed the MARGIN score. The MARGIN score achieved a testing dataset C-index of 0.75. Wide resection margins were associated with improved early RFS for the high-risk group, but not for the low-risk group.

Single-cell RNA-Seq analysis of molecular changes during radiation-induced skin injury: the involvement of Nur77.

Introduction: Ionizing radiation has been widely used in industry, medicine, military and agriculture. Radiation-induced skin injury is a significant concern in the context of radiotherapy and accidental exposure to radiation. The molecular changes at the single-cell level and intercellular communications during radiation-induced skin injury are not well understood. Methods: This study aims to illustrate this information in a murine model and human skin samples from a radiation accident using single-cell RNA sequencing (scRNA-Seq). We further characterize the functional significance of key molecule, which may provide a potential therapeutic target. ScRNA-Seq was performed on skin samples from a nuclear accident patient and rats exposed to ionizing radiation. Bioinformatic tools were used to analyze the cellular heterogeneity and preferential mRNAs. Comparative analysis was performed to identify dysregulated pathways, regulators, and ligand-receptor interactions in fibroblasts. The function of key molecule was validated in skin cells and in three mouse models of radiation-induced skin injury. Results: 11 clusters in human skin and 13 clusters of cells in rat skin were depicted respectively. Exposure to ionizing radiation caused changes in the cellular population (upregulation of fibroblasts and endothelial cells, downregulation of keratinocytes). Fibroblasts and keratinocytes possessed the most interaction pairs with other cell lineages. Among the five DEGs common to human and rat skins, Nur77 was highly expressed in fibroblasts, which mediated radiosensitivity by cell apoptosis and modulated crosstalk between macrophages, keratinocytes and endothelial cells in radiation-induced skin injury. In animal models, Nur77 knock-out mice (Nur77 -/-) showed more severe injury after radiation exposure than wild-type counterparts in three models of radiation-induced skin injury with complex mechanisms. Conclusion: The study reveals a single-cell transcriptional framework during radiation-induced skin injury, which provides a useful resource to uncover key events in its progression. Nur77 is a novel target in radiation-induced skin injury, which provides a potential therapeutic strategy against this disease.

Incomplete Histologic Healing and Diminished Biomechanical Strength of Meniscus-Bone Interface After Medial Meniscus Posterior Root Transosseous Repair in a Goat Model.

PURPOSE: To enhance the understanding of histologic healing after repairing medial meniscal posterior root tears (MMPRTs) at an early stage, utilizing a goat model. METHODS: Eighteen adult goats, totaling 36 knee joints, were allocated into 3 groups (n = 12): sham group (Sham), root tear group (RT), and root tear with transosseous suture group (RTS). At 12- and 24-week intervals postsurgery, all the knees were harvested for imaging, macroscopic, histologic, and biomechanical assessments. RESULTS: The intact root served as a meniscus-bone interface that connected the tibial and circular fibers of the meniscus with a bony insertion and a root-meniscus transition. A direct fibrous connection was displayed at the bony insertion proximal to the synovium in the RTS group, while the remaining regions of the root displayed indirect fibrous healing. The healing in the RT group was disjointed and reminiscent of scar tissue. The RTS group exhibited a more pronounced coronal extrusion compared to the Sham group (0.42 ± 0.09 vs 0.19 ± 0.02, P = .0012) but was improved relative to that of the RT group (0.49 ± 0.02, P = .0028). The failure load and stiffness of the RTS group were notably higher than those of the RT group, with a strength of 42.67% and a stiffness of 83.75% of the intact root. All the samples ruptured at the root-meniscus transitions. CONCLUSIONS: The incomplete healing may be attributed to the histologic factors underlying the low healing rate and persistent medial meniscal extrusion. Notably, the region attached to the posterior cruciate ligament exhibited superior healing compared to other regions of the bony insertion in the repaired group. Conversely, the root-meniscus transition displayed discontinuity, representing a mechanical weakness in the healing process. CLINICAL RELEVANCE: Modifications of bone tunnel positioning and suture placement could be undertaken in subsequent studies to enhance the healing of the root-meniscus transition.

The accuracy and quality of image-based artificial intelligence for muscle-invasive bladder cancer prediction.

PURPOSE: To evaluate the diagnostic performance of image-based artificial intelligence (AI) studies in predicting muscle-invasive bladder cancer (MIBC). (2) To assess the reporting quality and methodological quality of these studies by Checklist for Artificial Intelligence in Medical Imaging (CLAIM), Radiomics Quality Score (RQS), and Prediction model Risk of Bias Assessment Tool (PROBAST). MATERIALS AND METHODS: We searched Medline, Embase, Web of Science, and The Cochrane Library databases up to October 30, 2023. The eligible studies were evaluated using CLAIM, RQS, and PROBAST. Pooled sensitivity, specificity, and the diagnostic performances of these models for MIBC were also calculated. RESULTS: Twenty-one studies containing 4256 patients were included, of which 17 studies were employed for the quantitative statistical analysis. The CLAIM study adherence rate ranged from 52.5% to 75%, with a median of 64.1%. The RQS points of each study ranged from 2.78% to 50% points, with a median of 30.56% points. All models were rated as high overall ROB. The pooled area under the curve was 0.85 (95% confidence interval (CI) 0.81-0.88) for computed tomography, 0.92 (95% CI 0.89-0.94) for MRI, 0.89 (95% CI 0.86-0.92) for radiomics and 0.91 (95% CI 0.88-0.93) for deep learning, respectively. CONCLUSION: Although AI-powered muscle-invasive bladder cancer-predictive models showed promising performance in the meta-analysis, the reporting quality and the methodological quality were generally low, with a high risk of bias. CRITICAL RELEVANCE STATEMENT: Artificial intelligence might improve the management of patients with bladder cancer. Multiple models for muscle-invasive bladder cancer prediction were developed. Quality assessment is needed to promote clinical application. KEY POINTS: Image-based artificial intelligence models could aid in the identification of muscle-invasive bladder cancer. Current studies had low reporting quality, low methodological quality, and a high risk of bias. Future studies could focus on larger sample sizes and more transparent reporting of pathological evaluation, model explanation, and failure and sensitivity analyses.

Enzyme-Responsive DNA Origami-Antibody Conjugates for Targeted and Combined Therapy of Choroidal Neovascularization.

Monotherapy, especially the use of antibodies targeting vascular endothelial growth factor (VEGF), has shown limitations in treating choroidal neovascularization (CNV) since reactive oxygen species (ROS) also exacerbate CNV formation. Herein, we developed a combination therapy based on a DNA origami platform targeting multiple components of ocular neovascularization. Our study demonstrated that ocular neovascularization was markedly suppressed by intravitreal injection of a rectangular DNA origami sheet modified with VEGF aptamers (Ap) conjugated to an anti-VEGF antibody (aV) via matrix metalloproteinase (MMP)-cleavable peptide linkers in a mouse model of CNV. Typically, the DNA origami-based therapeutic platform selectively accumulates in neovascularization lesions owing to the dual-targeting ability of the aV and Ap, followed by the cleavage of the peptide linker by MMPs to release the antibody. Together, the released antibody and Ap inhibited VEGF activity. Moreover, the residual bare DNA origami could effectively scavenge ROS, reducing oxidative stress at CNV sites and thus maximizing the synergistic effects of inhibiting neovascularization.

Focal liver lesion diagnosis with deep learning and multistage CT imaging.

Diagnosing liver lesions is crucial for treatment choices and patient outcomes. This study develops an automatic diagnosis system for liver lesions using multiphase enhanced computed tomography (CT). A total of 4039 patients from six data centers are enrolled to develop Liver Lesion Network (LiLNet). LiLNet identifies focal liver lesions, including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), metastatic tumors (MET), focal nodular hyperplasia (FNH), hemangioma (HEM), and cysts (CYST). Validated in four external centers and clinically verified in two hospitals, LiLNet achieves an accuracy (ACC) of 94.7% and an area under the curve (AUC) of 97.2% for benign and malignant tumors. For HCC, ICC, and MET, the ACC is 88.7% with an AUC of 95.6%. For FNH, HEM, and CYST, the ACC is 88.6% with an AUC of 95.9%. LiLNet can aid in clinical diagnosis, especially in regions with a shortage of radiologists.

Fully automated hybrid approach on conventional MRI for triaging clinically significant liver fibrosis: A multi-center cohort study.

Establishing reliable noninvasive tools to precisely diagnose clinically significant liver fibrosis (SF, ≥F2) remains an unmet need. We aimed to build a combined radiomics-clinic (CoRC) model for triaging SF and explore the additive value of the CoRC model to transient elastography-based liver stiffness measurement (FibroScan, TE-LSM). This retrospective study recruited 595 patients with biopsy-proven liver fibrosis at two centers between January 2015 and December 2021. At Center 1, the patients before December 2018 were randomly split into training (276) and internal test (118) sets, the remaining were time-independent as a temporal test set (96). Another data set (105) from Center 2 was collected for external testing. Radiomics scores were built with selected features from Deep learning-based (ResUNet) automated whole liver segmentations on MRI (T2FS and delayed enhanced-T1WI). The CoRC model incorporated radiomics scores and relevant clinical variables with logistic regression, comparing routine approaches. Diagnostic performance was evaluated by the area under the receiver operating characteristic curve (AUC). The additive value of the CoRC model to TE-LSM was investigated, considering necroinflammation. The CoRC model achieved AUCs of 0.79 (0.70, 0.86), 0.82 (0.73, 0.89), and 0.81 (0.72-0.91), outperformed FIB-4, APRI (all p < 0.05) in the internal, temporal, and external test sets and maintained the discriminatory power in G0-1 subgroups (AUCs range, 0.85-0.86; all p < 0.05). The AUCs of joint CoRC-LSM model were 0.86 (0.79-0.94), and 0.81 (0.72-0.90) in the internal and temporal sets (p = 0.01). The CoRC model was useful for triaging SF, and may add value to TE-LSM.

Corrigendum to "Hypoxia-triggered degradable porphyrinic covalent organic framework for synergetic photodynamic and photothermal therapy of cancer" [Mater. Today Bio 25, 2024, 100981].

[This corrects the article DOI: 10.1016/j.mtbio.2024.100981.].

Deep learning-based 3D quantitative total tumor burden predicts early recurrence of BCLC A and B HCC after resection.

OBJECTIVES: This study aimed to evaluate the potential of deep learning (DL)-assisted automated three-dimensional quantitative tumor burden at MRI to predict postoperative early recurrence (ER) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This was a single-center retrospective study enrolling patients who underwent resection for BCLC A and B HCC and preoperative contrast-enhanced MRI. Quantitative total tumor volume (cm3) and total tumor burden (TTB, %) were obtained using a DL automated segmentation tool. Radiologists' visual assessment was used to ensure the quality control of automated segmentation. The prognostic value of clinicopathological variables and tumor burden-related parameters for ER was determined by Cox regression analyses. RESULTS: A total of 592 patients were included, with 525 and 67 patients assigned to BCLC A and B, respectively (2-year ER rate: 30.0% vs. 45.3%; hazard ratio (HR) = 1.8; p = 0.007). TTB was the most important predictor of ER (HR = 2.2; p < 0.001). Using 6.84% as the threshold of TTB, two ER risk strata were obtained in overall (p < 0.001), BCLC A (p < 0.001), and BCLC B (p = 0.027) patients, respectively. The BCLC B low-TTB patients had a similar risk for ER to BCLC A patients and thus were reassigned to a BCLC An stage; whilst the BCLC B high-TTB patients remained in a BCLC Bn stage. The 2-year ER rate was 30.5% for BCLC An patients vs. 58.1% for BCLC Bn patients (HR = 2.8; p < 0.001). CONCLUSIONS: TTB determined by DL-based automated segmentation at MRI was a predictive biomarker for postoperative ER and facilitated refined subcategorization of patients within BCLC stages A and B. CLINICAL RELEVANCE STATEMENT: Total tumor burden derived by deep learning-based automated segmentation at MRI may serve as an imaging biomarker for predicting early recurrence, thereby improving subclassification of Barcelona Clinic Liver Cancer A and B hepatocellular carcinoma patients after hepatectomy. KEY POINTS: Total tumor burden (TTB) is important for Barcelona Clinic Liver Cancer (BCLC) staging, but is heterogenous. TTB derived by deep learning-based automated segmentation was predictive of postoperative early recurrence. Incorporating TTB into the BCLC algorithm resulted in successful subcategorization of BCLC A and B patients.

Chaperone- and PTM-mediated activation of IRF1 tames radiation-induced cell death and the inflammatory response.

The key role of structural cells in immune modulation has been revealed with the advent of single-cell multiomics, but the underlying mechanism remains poorly understood. Here, we revealed that the transcriptional activation of interferon regulatory factor 1 (IRF1) in response to ionizing radiation, cytotoxic chemicals and SARS-CoV-2 viral infection determines the fate of structural cells and regulates communication between structural and immune cells. Radiation-induced leakage of mtDNA initiates the nuclear translocation of IRF1, enabling it to regulate the transcription of inflammation- and cell death-related genes. Novel posttranslational modification (PTM) sites in the nuclear localization sequence (NLS) of IRF1 were identified. Functional analysis revealed that mutation of the acetylation site and the phosphorylation sites in the NLS blocked the transcriptional activation of IRF1 and reduced cell death in response to ionizing radiation. Mechanistically, reciprocal regulation between the single-stranded DNA sensors SSBP1 and IRF1, which restrains radiation-induced and STING/p300-mediated PTMs of IRF1, was revealed. In addition, genetic deletion or pharmacological inhibition of IRF1 tempered radiation-induced inflammatory cell death, and radiation mitigators also suppressed SARS-CoV-2 NSP-10-mediated activation of IRF1. Thus, we revealed a novel cytoplasm-oriented mechanism of IRF1 activation in structural cells that promotes inflammation and highlighted the potential effectiveness of IRF1 inhibitors against immune disorders.

Characterization and noncovalent inhibition of the K63-deubiquitinase activity of SARS-cov-2 PLpro.

SARS-CoV-2 papain-like protease (PLpro) could facilitate viral replication and host immune evasion by respectively hydrolyzing viral polyprotein and host ubiquitin conjugates, thereby rendering itself as an important antiviral target. Yet few noncovalent PLpro inhibitors of SARS-CoV-2 have been reported with improved directed towards pathogenic deubiquitinating activities inhibition. Herein, we report that coronavirus PLpro proteases have distinctive substrate bias and are conserved to deubiquitylate K63-linked polyubiquitination, thereby attenuating host type I interferon response. We identify a noncovalent compound specifically optimized towards halting the K63-deubiquitinase activity of SARS-CoV-2 PLpro, but not other coronavirus (CoV) counterparts or host deubiquitinase. Contrasting with GRL-0617, a SARS-CoV-1 PLpro inhibitor, SIMM-036 is 50-fold and 7-fold (half maximal inhibitory concentration (IC50)) more potent to inhibit viral replication during SARS-CoV-2 infection and restore the host interferon-ß (IFN-ß) response in human angiotensin-converting enzyme 2 (hACE2)-HeLa cells, respectively. Structure-activity relationship (SAR) analysis further reveals the importance of BL2 groove of PLpro, which could determine the selectivity of K63-deubiquitinase activity of the enzyme.

Photoactivated Gas-Generating Nanocontrast Agents for Long-Term Ultrasonic Imaging-Guided Combined Therapy of Tumors.

To date, long-term and continuous ultrasonic imaging for guiding the puncture biopsy remains a challenge. In order to address this issue, a multimodality imaging and therapeutic method was developed in the present study to facilitate long-term ultrasonic and fluorescence imaging-guided precision diagnosis and combined therapy of tumors. In this regard, certain types of photoactivated gas-generating nanocontrast agents (PGNAs), capable of exhibiting both ultrasonic and fluorescence imaging ability along with photothermal and sonodynamic function, were designed and fabricated. The advantages of these fabricated PGNAs were then utilized against tumors in vivo, and high therapeutic efficacy was achieved through long-term ultrasonic imaging-guided treatment. In particular, the as-prepared multifunctional PGNAs were applied successfully for the fluorescence-based determination of patient tumor samples collected through puncture biopsy in clinics, and superior performance was observed compared to the clinically used SonoVue contrast agents that are incapable of specifically distinguishing the tumor in ex vivo tissues.

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate.

BACKGROUND: To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules. METHODS: A retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions. RESULTS: Among the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2-87.5, P < 0.001; OR = 38.0, 95% CI = 20.4-70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861-0.909), 0.945 (95% CI: 0.926-0.961), 0.947 (95% CI: 0.928-0.962), 0.945 (95% CI: 0.926-0.961) and 0.951 (95% CI: 0.932-0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%. CONCLUSIONS: MRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.

Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI.

The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups. Employing univariate and multivariate logistic regression, we identified independent predictors of FTN and MFTN, and subsequently develop a nomogram for FTN and a risk score system (RSS) for MFTN prediction. We assessed performance of nomogram through its discrimination, calibration, and clinical utility. The diagnostic performance of the RSS for MFTN was further compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS). The nomogram, integrating independent predictors, demonstrated robust discrimination and calibration in differentiating FTN from non-FTN in both training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Key risk factors for differentiating MFTN from BFTN included tumor size, restricted diffusion, and cystic degeneration. The AUC of the RSS for MFTN prediction was 0.902 (95% CI 0.798-0.971), outperforming five TIRADS with a sensitivity of 73.3%, specificity of 95.1%, accuracy of 92.4%, and positive and negative predictive values of 68.8% and 96.1%, respectively, at the optimal cutoff. MRI-based models demonstrate excellent diagnostic performance for preoperative predicting of FTN and MFTN, potentially guiding clinicians in optimizing therapeutic decision-making.

Defect-Rich Metastable MoS2 Promotes Macrophage Reprogramming in Breast Cancer: A Clinical Perspective.

Tumor-associated macrophages (TAMs) play a crucial function in solid tumor antigen clearance and immune suppression. Notably, 2D transitional metal dichalcogenides (i.e., molybdenum disulfide (MoS2) nanozymes) with enzyme-like activity are demonstrated in animal models for cancer immunotherapy. However, in situ engineering of TAMs polarization through sufficient accumulation of free radical reactive oxygen species for immunotherapy in clinical samples remains a significant challenge. In this study, defect-rich metastable MoS2 nanozymes, i.e., 1T2H-MoS2, are designed via reduction and phase transformation in molten sodium as a guided treatment for human breast cancer. The as-prepared 1T2H-MoS2 exhibited enhanced peroxidase-like activity (≈12-fold enhancement) than that of commercial MoS2, which is attributed to the charge redistribution and electronic state induced by the abundance of S vacancies. The 1T2H-MoS2 nanozyme can function as an extracellular hydroxyl radical generator, efficiently repolarizing TAMs into the M1-like phenotype and directly killing cancer cells. Moreover, the clinical feasibility of 1T2H-MoS2 is demonstrated via ex vivo therapeutic responses in human breast cancer samples. The apoptosis rate of cancer cells is 3.4 times greater than that of cells treated with chemotherapeutic drugs (i.e., doxorubicin).

UV radiation-induced peptides in frog skin confer protection against cutaneous photodamage through suppressing MAPK signaling.

Overexposure to ultraviolet light (UV) has become a major dermatological problem since the intensity of ultraviolet radiation is increasing. As an adaption to outside environments, amphibians gained an excellent peptide-based defense system in their naked skin from secular evolution. Here, we first determined the adaptation and resistance of the dark-spotted frogs (Pelophylax nigromaculatus) to constant ultraviolet B (UVB) exposure. Subsequently, peptidomics of frog skin identified a series of novel peptides in response to UVB. These UV-induced frog skin peptides (UIFSPs) conferred significant protection against UVB-induced death and senescence in skin cells. Moreover, the protective effects of UIFSPs were boosted by coupling with the transcription trans-activating (TAT) protein transduction domain. In vivo, TAT-conjugated UIFSPs mitigated skin photodamage and accelerated wound healing. Transcriptomic profiling revealed that multiple pathways were modulated by TAT-conjugated UIFSPs, including small GTPase/Ras signaling and MAPK signaling. Importantly, pharmacological activation of MAPK kinases counteracted UIFSP-induced decrease in cell death after UVB exposure. Taken together, our findings provide evidence for the potential preventive and therapeutic significance of UIFSPs in UV-induced skin damage by antagonizing MAPK signaling pathways. In addition, these results suggest a practicable alternative in which potential therapeutic agents can be mined from organisms with a fascinating ability to adapt.

Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma.

OBJECTIVES: To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC). METHODS: Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors. RESULTS: Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = -0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = -0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02). CONCLUSIONS: Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment. CLINICAL RELEVANCE STATEMENT: Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy. KEY POINTS: Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.

Porphyrin-Based Self-Assembled Nanoparticles for PET/MR Imaging of Sentinel Lymph Node Metastasis.

Diagnosing of lymph node metastasis is challenging sometimes, and multimodal imaging offers a promising method to improve the accuracy. This work developed porphyrin-based nanoparticles (68Ga-F127-TAPP/TCPP(Mn) NPs) as PET/MR dual-modal probes for lymph node metastasis imaging by a simple self-assembly method. Compared with F127-TCPP(Mn) NPs, F127-TAPP/TCPP(Mn) NPs synthesized by amino-porphyrins (TAPP) doping can not only construct PET/MR bimodal probes but also improve the T1 relaxivity (up to 456%). Moreover, T1 relaxivity can be adjusted by altering the molar ratio of TAPP/TCPP(Mn) and the concentration of F127. However, a similar increase in T1 relaxivity was not observed in the F127-TCPP/TCPP(Mn) NPs, which were synthesized using carboxy-porphyrins (TCPP) doping. In a breast cancer lymph node metastasis mice model, subcutaneous injection of 68Ga-F127-TAPP/TCPP(Mn) NPs through the hind foot pad, the normal lymph nodes and metastatic lymph nodes were successfully distinguished based on the difference of PET standard uptake values and MR signal intensities. Furthermore, the dark brown F127-TAPP/TCPP(Mn) NPs demonstrated the potential for staining and mapping lymph nodes. This study provides valuable insights into developing and applying PET/MR probes for lymph node metastasis imaging.