Magnetic resonance elastography （MRE） has become an important tool for the diagnosis and staging of fibrosis in metabolic dysfunction-associated fatty liver disease （MAFLD）， and its high diagnostic accuracy can help to effectively evaluate the dynamic changes and long-term prognosis of fibrosis in patients with MAFLD. In addition， MRE also shows wide potential in patient screening and outcome assessment in new drug development for metabolic-associated steatohepatitis. This article comprehensively analyzes the potential value of MRE in evaluating liver fibrosis in MAFLD patients， as well as its advantages in clinical practice and future development directions.

To address the constrains imposed by insufficient hydrogen peroxide (H2O2) and high glutathione (GSH) expression in tumor cells on the efficacy of chemodynamic therapy (CDT), zeolitic imidazolate framework-8 (ZIF-8) loaded with disulfiram (DSF) and 3-amino-1,2,4-triazole (3-AT) was synthesized via a one-pot approach. Subsequently, hyaluronic acid (HA)-modified cupric peroxide (CuO2) was in-situ grown on its surface through biomineralization to construct a multifunctional copper-based nanozyme ADZCH (3-AT/DSF@ZIF-8@CuO2-HA). This nanoplatform disrupts the intratumoral H2O2 homeostasis, depletes GSH, and synchronously delivers DSF and Cu2+ via cascade catalysis, thereby enhancing CDT and sensitizing tumors to DSF-based chemotherapy. The results of physicochemical characterization indicated that ADZCH presented a uniform core-shell structure with favorable dispersibility. Its particle size and Zeta potential were 196.5 nm and −19.5 mV, respectively. It possessed a microporous structure with a specific surface area of 81.8600 m2/g, and demonstrated efficient loading capacity for DSF and 3-AT, achieving drug loading efficiencies of 5.91% and 45.07%, respectively. Moreover, ADZCH can continuously and slowly release drugs in an acidic environment and maintain good stability under diverse physiological conditions. In vitro functional assays verified that ADZCH catalytically generated H2O2 and hydroxyl radicals while concurrently depleting GSH in a concentration- and incubation time-dependent manner. Cellular uptake experiments showed that HA modification significantly improved the uptake of nanoparticles by 4T1 cells. Cytotoxicity tests showed that 80 μg/mL ADZCH had a significant cytotoxic effect on 4T1 cells but no significant toxicity on L929 cells. DCFH-DA probe detection indicated that ADZCH could significantly induce intracellular reactive oxygen species (ROS) generation, thereby enhancing CDT efficacy. Live/dead staining experiments showed that ADZCH efficiently induced apoptosis, with the proportion of dead cells reaching 94.74%, demonstrating its promising potential for anti-tumor applications.This study provides new research ideas and experimental basis for overcoming the tumor microenvironment barrier and enhancing the anti-tumor effect of CDT combined with chemotherapy.

Objective: To compare the transcriptomic profiles between three distinct metabolic dysfunction⁃associat⁃mal murine model that more closely resembles human MASH progression . Methods: Forty 8 ⁃week⁃old male C57BL/6J mice were randomly assigned to either a control group fed normal chow diet ( NCD) or one of three MASH model groups receiving high⁃fat high⁃cholesterol diet (HFHCD) , choline⁃deficient high⁃fat diet (CDHFD) ,from three randomly selected mice per group were collected for mRNA sequencing ( mRNA⁃seq) analysis . Mean⁃bases . Overlap of functional profiles was analyzed by gene set enrichment analysis (GSEA) profiles to compare the mouse transcriptome with that of human patients at different stages of the disease . Additionally , Pearson ′s correla⁃tion analysis was used to explore the correlation between gene expression of murine models and human MASH . Results: Seven commonly up⁃regulated genes (Col1a1 , Smoc2 , Col6a1 , Gpx3 , Col16a1 , Spp1 and Crtap) were de⁃ways involving steatosis , hepatocellular injury and fibrosis were detected in the three MASH models at the pathway level . HFHCD and MCD might share more common traits . In comparing gene expression and pathway profiles be⁃tween different murine models and patients with different stages of MASH , all three murine MASH models showed a closer resemblance to the human progressive stages of MASH . Notably , the transcriptomic features of the CDHFD model were more consistent with those of human MASH . Conclusion There are certain similarities and differences among the transcriptional profiles of the three MASH models . The MASH models are more similar to the advanced stage of MASH in human patients . Compared to the other two models , the CDHFD model ′ s transcriptome profile more closely resembles human MASH .

In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.

The study explores the traditional Chinese medicine （TCM） diagnostic and treatment approach to coronary microvascular disease （CMVD） from the perspective of "disharmony of blood collaterals and dysfunction of qi transformation". It is proposed that the core pathogenesis of CMVD lies in these two mechanisms. From an integrative medicine perspective， different CMVD types are analyzed based on their specific pathogenesis. Through clinical practice， four targeted treatment methods， i.e. warming， unblocking， tonifying， and activating， are formulated. CMVD caused by atherosclerosis is primarily associated with myocardial ischemia， myocardial infarction， and coronary revascularization， with corresponding pathological mechanisms of latent pathogenic obstruction， toxic accumulation in the collaterals， and deficiency with collateral stasis. The disease progression exhibits characteristics of correlation， staging， and transformation. Accordingly， treatment principles include warming to assist qi transformation， unblocking obstruction and dispelling turbidity， activating to disperse toxic stasis and invigorate collaterals， and tonifying to eliminate stasis and nourish collaterals. For CMVD unrelated to atherosclerosis， attention should be paid to the underlying disease， analyzing the main syndromes of blood and collateral disharmony. An approach combining disease-syndrome differentiation with blood and collateral regulation is emphasized for precise treatment.

Objective:To dynamically assess liver fibrosis using magnetic resonance elastography (MRE) and explore factors associated with fibrosis reversal in patients with metabolic dysfunction-associated steatohepatitis (MASH).Methods:This study included data from patients diagnosed with MASH by liver biopsy who underwent at least two MRE examinations. Patients were divided into a fibrosis reversal group and a non-reversal group according to whether MRE values decreased by 20% during follow-up. Differences in clinical data between the groups were compared using analysis of variance, the Kruskal-Wallis test, and the chi-square test. Univariate and multivariate logistic regression analyses were used to explore independent risk factors for fibrosis reversal in MASH.Results:A total of 46 cases were included in this study (mean age 50.1±12.3 years, BMI 26.1±3.1 kg/m2). Among them, the reversal group accounted for 26.1%. The rate of decrease in MRI proton density fat fraction (PDFF) was significantly higher in the reversal group (-50.0% vs. -8.1%, P=0.001) than in the non-reversal group between the two MRE examinations. The reversal group showed a more significant change rate of decreases in fasting insulin (-37.3% vs. -3.6%, P=0.011), insulin resistance index (-38.6% vs. -6.5%, P=0.044), and ALP (-24.9% vs. 0, P=0.004). Multivariate logistic regression analysis indicated that the rate of change in MRI PDFF was an independent predictor of fibrosis reversal ( OR=0.96, 95% CI: 0.92-1.00, P=0.046). Conclusion:A decrease in MRI proton density fat fraction levels is independently associated with liver fibrosis reversal in MASH, suggesting that intervention targeting liver fat content may be an effective treatment strategy.

Objective:To dynamically assess liver fibrosis using magnetic resonance elastography (MRE) and explore factors associated with fibrosis reversal in patients with metabolic dysfunction-associated steatohepatitis (MASH).Methods:This study included data from patients diagnosed with MASH by liver biopsy who underwent at least two MRE examinations. Patients were divided into a fibrosis reversal group and a non-reversal group according to whether MRE values decreased by 20% during follow-up. Differences in clinical data between the groups were compared using analysis of variance, the Kruskal-Wallis test, and the chi-square test. Univariate and multivariate logistic regression analyses were used to explore independent risk factors for fibrosis reversal in MASH.Results:A total of 46 cases were included in this study (mean age 50.1±12.3 years, BMI 26.1±3.1 kg/m2). Among them, the reversal group accounted for 26.1%. The rate of decrease in MRI proton density fat fraction (PDFF) was significantly higher in the reversal group (-50.0% vs. -8.1%, P=0.001) than in the non-reversal group between the two MRE examinations. The reversal group showed a more significant change rate of decreases in fasting insulin (-37.3% vs. -3.6%, P=0.011), insulin resistance index (-38.6% vs. -6.5%, P=0.044), and ALP (-24.9% vs. 0, P=0.004). Multivariate logistic regression analysis indicated that the rate of change in MRI PDFF was an independent predictor of fibrosis reversal ( OR=0.96, 95% CI: 0.92-1.00, P=0.046). Conclusion:A decrease in MRI proton density fat fraction levels is independently associated with liver fibrosis reversal in MASH, suggesting that intervention targeting liver fat content may be an effective treatment strategy.

Objective To observe the impact of ultrasonic image quality on the consistency of artificial intelligence(Al)assisted diagnosis system and manual measurements of biological indicators of developmental dysplasia of hip(DDH).Methods Hip ultrasonic data of 75 DDH and 345 non-DDH children were retrospectively analyzed,and the quality of ultrasonic images were subjectively scored.An evaluation model of ultrasonic image quality was constructed based on 140 ultrasonic images acquired from 140 cases(group A,containing 25 DDH and 115 non-DDH)using entropy weighting method,the weight of anatomic structures and impact factors related to DDH were obtained.The comprehensive image quality scores of other ultrasonic images acquired from 280 cases(group B,including 50 DDH and 230 non-DDH)were calculated,and the images in group B were classified into grade A,B and C in descending order.The consistency of AI and manual measurements of DDH biological indicators in group B was assessed.Results The weight of each anatomic structure and impact factors of DDH obtained with the model were as follows:The lower edge of iliac branch＞ilium＞glenoid labrum＞bony margin＞femoral head＞motion artifacts.In group B,grade A was observed in 67(9 DDH and 58 non-DDH),grade B was found in 160(26 DDH and 134 non-DDH),while grade C was noticed in 53(15 DDH and 38 non DDH)images.Except for β,femoral head coverage(FHC)and femoral head length diameter,the consistencies between AI and manual measurements of other indicators of DDH were grade A＞B＞C.In group B,AI and manual measurements were more consistent in DDH than in non-DDH cases.Conclusion Ultrasonic image quality affected the consistency between AI and manual measurements of biological indicators of DDH.When image quality was not good enough,further attention should be paid to measurement of FHC and sizes of femoral head.

Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development.However,the single-cell or low-input proteomic research in this field is rela-tively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology.In this study,a comprehensive solution of ultrasensitive proteome technology(CS-UPT)was developed for single-cell or low-input mouse oocyte/embryo samples.The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands.Using the deep coverage route,we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition,including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample.Moreover,significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.

BRAF is a serine/threonine kinase that harbors activating mutations in ∼7% of human malignancies and ∼60% of melanomas. Despite initial clinical responses to BRAF inhibitors, patients frequently develop drug resistance. To identify candidate therapeutic targets for BRAF inhibitor resistant melanoma, we conduct CRISPR screens in melanoma cells harboring an activating BRAF mutation that had also acquired resistance to BRAF inhibitors. To investigate the mechanisms and pathways enabling resistance to BRAF inhibitors in melanomas, we integrate expression, ATAC-seq, and CRISPR screen data. We identify the JUN family transcription factors and the ETS family transcription factor ETV5 as key regulators of CDK6, which together enable resistance to BRAF inhibitors in melanoma cells. Our findings reveal genes contributing to resistance to a selective BRAF inhibitor PLX4720, providing new insights into gene regulation in BRAF inhibitor resistant melanoma cells.