Evaluation of preoperative magnetic resonance imaging features and diagnostic effectiveness of grades II and III intracranial solitary fibroma.

OBJECTIVES: To explore the value of preoperative magnetic resonance imaging (MRI) characterization of intracranial solitary fibrous tumors (ISFT) and to evaluate the effectiveness of preoperative MRI features in predicting pathological grading. MATERIALS AND METHODS: This retrospective analysis comprised the clinical and preoperative MRI characterization of 55 patients with ISFT in our hospital, including 27 grade II cases and 28 grade III cases confirmed by postoperative pathology. Variables included age, sex, tumor location, cross-midline status, signal characteristics of T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), T2-fluid-attenuated inversion recovery (T2-FLAIR), and diffusion­weighted imaging (DWI), peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel, maximum tumor diameter, maximum, minimum, and average values of apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumors enhancement mode, meningeal tail sign, skull invasion, cerebral parenchymal invasion, and venous sinus involvement. The independent samples t test or Mann-Whitney U test was performed to compare continuous data between the two groups, and the Pearson chi-squared test or Fisher's exact test was used to compare categorical data. In addition, bivariate logistic regression was performed to construct a comprehensive model, and receiver operating characteristic (ROC) curves were generated to calculate the areas under the curve (AUCs), thereby determining the value of each parameter in the differential diagnosis of grades II and III ISFT. RESULTS: The mean age at onset was similar between patients with grades II and III ISFT (46.77 ± 14.66 years and 45.82 ± 12.07 years, respectively). The proportions of men among patients with grades II and III ISFT were slightly higher than those of female patients (male/female: 1.25 [15/12] and 1.33 [16/12], respectively). There were significant differences between grades II and III ISFT in the T2-FLAIR and DWI signal characteristics, maximum, minimum, and average values of the apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumor location, and skull invasion (P = 0.001, P = 0.018, P = 0.000, P = 0.000, P = 0.000, P = 0.010, and P = 0.032, respectively). However, no significant differences were noted between grades II and III ISFT in age, sex, cross-midline status, T1WI and T2WI signal characteristics, peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel shadow, enhancement mode, meningeal tail sign, maximum tumor diameter, brain parenchyma invasion, or venous sinus involvement (all P > 0.05). Moreover, binary logistic regression analysis showed that the model accuracy was 89.1% when ADCmin was included in the regression equation. Moreover, ROC curve analysis showed that the AUC of ADCmin was 0.805 (0.688, 0.922), sensitivity was 74.1%, specificity was 75.0%, and the cutoff value was 672 mm2/s. CONCLUSIONS: Grade III ISFT patients displayed more mixed T2-FLAIR signal characteristics and DWI signal characteristics than grade II patients, as shown by higher skull invasion and tumor mass collapse midline distribution and lower ADCmax, ADCmean, and ADCmin values. The ADCmin value was significant in the preoperative assignment of grades II and III ISFT, thereby contributing to enhanced accuracy in the imaging grading diagnosis of the disease.

Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy.

BACKGROUND: To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS: This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method. RESULTS: Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance. CONCLUSIONS: Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.

Extraocular muscle volume on time-of-flight magnetic resonance angiography in patients with myasthenia gravis.

INTRODUCTION/AIMS: Despite being a prominent feature of myasthenia gravis (MG), extraocular muscle (EOM) has received little attention in clinical research. The aim of this study was to examine EOM volume in patients with MG and controls using time-of-flight magnetic resonance angiography (TOF-MRA). METHODS: EOM volumes (overall and individual rectus muscles) were calculated using TOF-MRA images and compared between MG patients (including subgroups) and controls. The correlation between EOM volume and disease duration was examined. Predictive equations for the selected parameters were developed using multiple linear regression analysis. RESULTS: EOM volume was lower in MG patients than controls, especially in MG patients with ophthalmoparesis (MG-O). MG-O exhibited a moderate negative correlation between EOM volume and disease duration. Multiple linear regression showed that disease duration and EOM status (ophthalmoparesis or not) account for 48.4% of EOM volume. DISCUSSION: Patients with MG show atrophy of the EOMs, especially those with ophthalmoparesis and long disease duration.

Whole-tumor histogram analysis of multiple non-Gaussian diffusion models at high b values for assessing cervical cancer.

PURPOSE: To assess the diagnostic potential of whole-tumor histogram analysis of multiple non-Gaussian diffusion models for differentiating cervical cancer (CC) aggressive status regarding of pathological types, differentiation degree, stage, and p16 expression. METHODS: Patients were enrolled in this prospective single-center study from March 2022 to July 2023. Diffusion-weighted images (DWI) were obtained including 15 b-values (0 ~ 4000 s/mm2). Diffusion parameters derived from four non-Gaussian diffusion models including continuous-time random-walk (CTRW), diffusion-kurtosis imaging (DKI), fractional order calculus (FROC), and intravoxel incoherent motion (IVIM) were calculated, and their histogram features were analyzed. To select the most significant features and establish predictive models, univariate analysis and multivariate logistic regression were performed. Finally, we evaluated the diagnostic performance of our models by using receiver operating characteristic (ROC) analyses. RESULTS: 89 women (mean age, 55 ± 11 years) with CC were enrolled in our study. The combined model, which incorporated the CTRW, DKI, FROC, and IVIM diffusion models, offered a significantly higher AUC than that from any individual models (0.836 vs. 0.664, 0.642, 0.651, 0.649, respectively; p < 0.05) in distinguishing cervical squamous cell cancer from cervical adenocarcinoma. To distinguish tumor differentiation degree, except the combined model showed a better predictive performance compared to the DKI model (AUC, 0.839 vs. 0.697, respectively; p < 0.05), no significant differences in AUCs were found among other individual models and combined model. To predict the International Federation of Gynecology and Obstetrics (FIGO) stage, only DKI and FROC model were established and there was no significant difference in predictive performance among different models. In terms of predicting p16 expression, the predictive ability of DKI model is significantly lower than that of FROC and combined model (AUC, 0.693 vs. 0.850, 0.859, respectively; p < 0.05). CONCLUSION: Multiple non-Gaussian diffusion models with whole-tumor histogram analysis show great promise to assess the aggressive status of CC.

Mean Apparent Propagator MRI: Quantitative Assessment of Tumor-Stroma Ratio in Invasive Ductal Breast Carcinoma.

Purpose To determine whether metrics from mean apparent propagator (MAP) MRI perform better than apparent diffusion coefficient (ADC) value in assessing the tumor-stroma ratio (TSR) status in breast carcinoma. Materials and Methods From August 2021 to October 2022, 271 participants were prospectively enrolled (ClinicalTrials.gov identifier: NCT05159323) and underwent breast diffusion spectral imaging and diffusion-weighted imaging. MAP MRI metrics and ADC were derived from the diffusion MRI data. All participants were divided into high-TSR (stromal component < 50%) and low-TSR (stromal component ≥ 50%) groups based on pathologic examination. Clinicopathologic characteristics were collected, and MRI findings were assessed. Logistic regression was used to determine the independent variables for distinguishing TSR status. The area under the receiver operating characteristic curve (AUC) and sensitivity, specificity, and accuracy were compared between the MAP MRI metrics, either alone or combined with clinicopathologic characteristics, and ADC, using the DeLong and McNemar test. Results A total of 181 female participants (mean age, 49 years ± 10 [SD]) were included. All diffusion MRI metrics differed between the high-TSR and low-TSR groups (P < .001 to P = .01). Radial non-Gaussianity from MAP MRI and lymphovascular invasion were significant independent variables for discriminating the two groups, with a higher AUC (0.81 [95% CI: 0.74, 0.87] vs 0.61 [95% CI: 0.53, 0.68], P < .001) and accuracy (138 of 181 [76%] vs 106 of 181 [59%], P < .001) than that of the ADC. Conclusion MAP MRI may serve as a better approach than conventional diffusion-weighted imaging in evaluating the TSR of breast carcinoma. Keywords: MR Diffusion-weighted Imaging, MR Imaging, Breast, Oncology ClinicalTrials.gov Identifier: NCT05159323 Supplemental material is available for this article. © RSNA, 2024.

Differentiation of confluent hepatic fibrosis and infiltrative hepatocellular carcinoma on MR imaging.

BACKGROUND: To identify reliable magnetic resonance imaging (MRI) features that can differentiate confluent fibrosis (CF) from infiltrative hepatocellular carcinoma (HCC). METHODS: A retrospective analysis was conducted on Twenty CF patients and 28 infiltrative HCC patients who underwent upper abdomen MRI scans. The imaging features of lesions were analyzed, and the apparent diffusion coefficient (ADC) of lesions were measured. Accuracy, sensitivity and specificity for the diagnosis of CF were calculated for each category individually and combined. RESULTS: Compared to infiltrative HCC, hepatic capsular retraction at the site of lesion, hepatic volume loss at the site of lesion and "nodular surround sign" were more common in patients with CF (all P < 0.001). Hepatic volume loss at the site of lesion, no or mild enhancement in arterial phase, and hyper-enhancing in delayed phase to the background parenchyma showed superior diagnostic accuracy (83.3%, 85.4%, 97.9%, respectively). When the lesion exhibited hepatic volume loss at the site of lesion or no or mild enhancement in arterial phase or hyper-enhancing in delayed phase, a sensitivity of 100.0% for the diagnosis of CF was achieved. When the lesion was positive for any two of three categories, or positive for all three categories, a specificity of 100.0% was achieved. The ADC values of CF were higher than those of infiltrative HCC (P < 0.001). CONCLUSION: The combination of the hepatic volume loss at the site of lesion, no or mild enhancement in arterial phase, and hyper-enhancing in delayed phase to the background parenchyma can be considered reliable MR features for the diagnosis of CF, as they allow differentiation from infiltrative HCC.

Stabilization of all-natural water-in-oil high internal phase pickering emulsion by using diosgenin/soybean phosphatidylethanolamine complex: Characterization and application in 3D printing.

This study aimed to prepare an all-natural water-in-oil high internal phase Pickering emulsion (W/O-HIPPE) using diosgenin/soybean phosphatidylethanolamine complex (DGSP) and investigate the 3D printing performance. Results suggested that the self-assembly of diosgenin crystal was modified by SP in DGSP (diosgenin-SP ratios at 3:1 and 1:1), revealing a variation from large-size outward radiating needle-like to small-size granular-like shape, which facilitated closely packing at the interface. Hydrophilicity of DGSP was also increased (contact angle varying from 133.3 o to 106.4 o), ensuring more adequate interfacial adsorption to reduce interfacial tension more largely (6.5 mN/m). Thus, the W/O-HIPPE made by DGSP with diosgenin-SP = 1:1, exhibited smaller droplets and better freeze/thawing stability. The W/O-HIPPE was also measured improved rheological properties for 3D printing: satisfied shear-thinning behavior, higher recovery and self-supporting (viscoelasticity and deformation resistance). Consequently, the W/O-HIPPE allowed for printing more delicate patterns. This work provided guidance to prepare W/O-HIPPE for 3D printing.

Iron Oxide Nanoparticles Engineered Macrophage-Derived Exosomes for Targeted Pathological Angiogenesis Therapy.

Engineering exosomes with nanomaterials usually leads to the damage of exosomal membrane and bioactive molecules. Here, pathological angiogenesis targeting exosomes with magnetic imaging, ferroptosis inducing, and immunotherapeutic properties is fabricated using a simple coincubation method with macrophages being the bioreactor. Extremely small iron oxide nanoparticle (ESIONPs) incorporated exosomes (ESIONPs@EXO) are acquired by sorting the secreted exosomes from M1-polarized macrophages induced by ESIONPs. ESIONPs@EXO suppress pathological angiogenesis in vitro and in vivo without toxicity. Furthermore, ESIONPs@EXO target pathological angiogenesis and exhibit an excellent T1-weighted contrast property for magnetic resonance imaging. Mechanistically, ESIONPs@EXO induce ferroptosis and exhibit immunotherapeutic ability toward pathological angiogenesis. These findings demonstrate that a pure biological method engineered ESIONPs@EXO using macrophages shows potential for targeted pathological angiogenesis therapy.

Copper oxide nanoparticles suppress retinal angiogenesis via inducing endothelial cell cuproptosis.

Background: Copper oxide nanoparticles (CuO NPs) exhibit antitumor activity; however, their potential as an antiangiogenesis agent is unknown. Materials & methods: The antiangiogenesis properties of CuO NPs were evaluated in vitro and in vivo and the underlying mechanism was examined using RNA sequencing and metabolomic analyses. Results: CuO NPs inhibited endothelial cell function in vitro. They also mitigated retinal vasculature development and alleviated pathological retinal angiogenesis in vivo. RNA sequencing and metabolomic analyses revealed that CuO NPs disrupt the tricarboxylic acid cycle and induce cuproptosis, which was further supported by evaluating cuproptosis-related metabolites and proteins. Conclusion: CuO NPs may be an effective antiangiogenic agent for the treatment of retinal angiogenesis.

A novel MRI-based diagnostic model for predicting placenta accreta spectrum.

Objective To develop and evaluate a diagnostic model based on MRI signs for predicting placenta accreta spectrum. Materials and Methods A total of 155 pregnant women were included in this study, randomly divided into 104 cases in the training set and 51 cases in the validation set. There were 93 Non-PAS cases, and 62 cases in the PAS group. The training set included 62 Non-PAS cases and 42 PAS cases. Clinical factors and MRI signs were collected for univariate analysis. Then, binary logistic regression analysis was used to develop independent diagnostic models with clinical relevant risk factors or MRI signs, as well as those combining clinical risk factors and MRI signs. The ROC curve analysis was used to evaluate the diagnostic performance of each diagnostic model. Finally, the validation was performed with the validation set. Results In the training set, four clinical factors (gestity, parity, uterine surgery history, placental position) and 11 MRI features (T2-dark bands, placental bulge, T2 hypointense interface loss, myometrial thinning, bladder wall interruption, focal exophytic mass, abnormal placental bed vascularization, placental heterogeneity, asymmetric placental thickening/shape, placental ischemic infarction, abnormal intraplacental vascularity) were considered as risk factors for PAS. The AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.779, 0.854, and 0.874, respectively. In the validation set, the AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.655, 0.728, and 0.735, respectively. Conclusion Diagnosis model based on MRI features in this study can well predict placenta accreta spectrum.

Discrimination between human epidermal growth factor receptor 2 (HER2)-low-expressing and HER2-overexpressing breast cancers: a comparative study of four MRI diffusion models.

OBJECTIVES: To determine the value of conventional DWI, continuous-time random walk (CTRW), fractional order calculus (FROC), and stretched exponential model (SEM) in discriminating human epidermal growth factor receptor 2 (HER2) status of breast cancer (BC). METHODS: This prospective study included 158 women who underwent DWI, CTRW, FROC, and SEM and were pathologically categorized into the HER2-zero-expressing group (n = 10), HER2-low-expressing group (n = 86), and HER2-overexpressing group (n = 62). Nine diffusion parameters, namely ADC, αCTRW, ßCTRW, DCTRW, ßFROC, DFROC, µFROC, αSEM, and DDCSEM of the primary tumor, were derived from four diffusion models. These diffusion metrics and clinicopathologic features were compared between groups. Logistic regression was used to determine the optimal diffusion metrics and clinicopathologic variables for classifying the HER2-expressing statuses. Receiver operating characteristic (ROC) curves were used to evaluate their discriminative ability. RESULTS: The estrogen receptor (ER) status, progesterone receptor (PR) status, and tumor size differed between HER2-low-expressing and HER2-overexpressing groups (p < 0.001 to p = 0.009). The αCTRW, DCTRW, ßFROC, DFROC, µFROC, αSEM, and DDCSEM were significantly lower in HER2-low-expressing BCs than those in HER2-overexpressing BCs (p < 0.001 to p = 0.01). Further multivariable logistic regression analysis showed that the αCTRW was the single best discriminative metric, with an area under the curve (AUC) being higher than that of ADC (0.802 vs. 0.610, p < 0.05); the addition of ER status, PR status, and tumor size to the αCTRW improved the AUC to 0.877. CONCLUSIONS: The αCTRW could help discriminate the HER2-low-expressing and HER2-overexpressing BCs. CLINICAL RELEVANCE STATEMENT: Human epidermal growth factor receptor 2 (HER2)-low-expressing breast cancer (BC) might also benefit from the HER2-targeted therapy. Prediction of HER2-low-expressing BC or HER2-overexpressing BC is crucial for appropriate management. Advanced continuous-time random walk diffusion MRI offers a solution to this clinical issue. KEY POINTS: • Human epidermal receptor 2 (HER2)-low-expressing BC had lower αCTRW, DCTRW, ßFROC, DFROC, µFROC, αSEM, and DDCSEM values compared with HER2-overexpressing breast cancer. • The αCTRW was the single best diffusion metric (AUC = 0.802) for discrimination between the HER2-low-expressing and HER2-overexpressing breast cancers. • The addition of αCTRW to the clinicopathologic features (estrogen receptor status, progesterone receptor status, and tumor size) further improved the discriminative ability.

Targeting progranulin alleviated silica particles-induced pulmonary inflammation and fibrosis via decreasing Il-6 and Tgf-ß1/Smad.

Long term exposure to silica particles leads to various diseases, among which silicosis is of great concern. Silicosis is an interstitial lung disease caused by inhalation of silica particles in production environments. However, the mechanisms underlying silicosis remains unclear. Our previous studies revealed that progranulin (Pgrn) promoted the expression of pro-inflammatory factors in alveolar macrophages treated with silica particles and the secretion of extracellular matrix of pulmonary fibroblasts. Nevertheless, the role of Pgrn in silica particles-induced silicosis in vivo was unknown. This study found that silica particles increased Pgrn expression in silicosis patients. Pgrn deficiency reduced lung inflammation and fibrosis in silica particles-induced silicosis mouse models. Subsequently, based on transcriptional sequencing and interleukin (Il) -6 knockout mouse models, results demonstrated that Pgrn deficiency might decrease silicosis inflammation by reducing the production of Il-6, thereby modulating pulmonary fibrosis in the early stage of silicosis mouse models. Furthermore, another mechanism through which Pgrn deficiency reduced fibrosis in silicosis mouse models was the regulation of the transforming growth factor (Tgf) -ß1/Smad signaling pathway. Conclusively, Pgrn contributed to silicosis inflammation and fibrosis induced by silica particles, indicating that Pgrn could be a promising therapeutic target.

Interfacial adsorption of soybean phosphatidylethanolamine in different oil phase and the stability of water-in-oil emulsion.

Water-in-oil (W/O) emulsion holds great potential in designing fat-reduced foods. However, due to the lack of W/O-type surfactant, formation of all-natural W/O emulsion is challenged. This study aimed to investigate the effect of oil phase on interfacial adsorption of soybean phosphatidylethanolamine (SP) and stability of W/O emulsion. Five oils, including medium chain triglycerides oil (MO), coconut oil (CO), palm kernel oil (PKO), sunflower oil (SO) and rapeseed oil (RO), were selected. Results showed that diffusion rate of SP to the interface ranked as MO > CO > PKO > SO ≈ RO, increasing interfacial adsorption from 50.2 % to 85.3 %. Higher interfacial adsorption improved the deformation resistance of interfacial layer, causing more significant decrease in interfacial tension (3.54 mN/m). So, the largest water fraction (65 %) was stabilized by SP with MO and CO, and exhibited smaller droplet sizes and better stability. Consequently, shorter-chain oil was more suitable for preparing W/O emulsions.

Tumor Multiregional Mean Apparent Propagator (MAP) Features in Evaluating Gliomas-A Comparative Study With Diffusion Kurtosis Imaging (DKI).

BACKGROUND: Glioma classification affects treatment and prognosis. Reliable imaging methods for preoperatively evaluating gliomas are essential. PURPOSE: To evaluate tumor multiregional mean apparent propagator (MAP) features in glioma diagnosis and to compare those with diffusion-kurtosis imaging (DKI). STUDY TYPE: Retrospective study. SUBJECTS: 70 untreated glioma patients (31 LGGs (low-grade gliomas), 34 women; mean age, 47 ± 12 years, training (60%, n = 42) and testing cohorts (40%, n = 28)). FIELD STRENGTH/SEQUENCE: 3-T, diffusion-MRI using q-space Cartesian grid sampling with 11 different b-values. ASSESSMENT: Tumor multiregional MAP (mean squared displacement (MSD); q-space inverse variance (QIV); non-Gaussianity (NG); axial/radial non-Gaussianity (NGAx, NGRad); return-to-origin/axis/plane probability (RTOP, RTAP, and RTPP)); and DKI metrics (axial/mean/radial kurtosis (AK, MK, and RK)) on tumor parenchyma (TP) and peritumoral areas (PT) in histopathologically gliomas grading and genotyping were assessed. STATISTICAL TESTS: Mann-Whitney U; Kruskal-Wallis; Benjamini-Hochberg; Bonferroni-correction; receiver operating curve (ROC) and area under curve (AUC); DeLong's test; Random Forest (RF). P value<0.05 was considered statistically significant after multiple comparisons correction. RESULTS: Compared with LGGs, MSD, and QIV were significantly lower in TP, whereas NG, NGAx, NGRad, RTOP, RTAP, RTPP, and DKI metrics were significantly higher in HGGs (high-grade gliomas) (P ≤ 0.007), as well as in isocitrate-dehydrogenase (IDH)-mutated than IDH-wildtype gliomas (P ≤ 0.039). These trends were reversed for PT (tumor grades, P ≤ 0.011; IDH-mutation status, P ≤ 0.012). ROC analysis showed that, in TP, DKI metrics performed best in TP (AUC 0.83), whereas in PT, RTPP performed best (AUC 0.77) in glioma grading. AK performed best in TP (AUC 0.77), whereas MSD and RTPP performed best in PT (AUC 0.73) in IDH genotyping. Further RF analysis with DKI and MAP demonstrated good performance in grading (AUC 0.91, Accuracy 82%) and IDH genotyping (AUC 0.87, Accuracy 79%). DATA CONCLUSION: Tumor multiregional MAP features could effectively evaluate gliomas. The performance of MAP may be similar to DKI in TP, while in PT, MAP may outperform DKI. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

The guiding value of the cinematic volume rendering technique in the preoperative diagnosis of brachial plexus schwannoma.

This study aimed to explore and compare the guiding value of Maximum Intensity Projection (MIP) and Cinematic Volume Rendering Technique (cVRT) in the preoperative diagnosis of brachial plexus schwannomas. We retrospectively analyzed the clinical and imaging data of 45 patients diagnosed with brachial plexus schwannomas at the First Affiliated Hospital of Zhengzhou University between January 2020 and December 2022. The enhanced three-dimensional short recovery time inversion-recovery fast spin-echo imaging (3D-STIR-SPACE) sequence served as source data for the reconstruction of MIP and cVRT. Two independent observers scored the image quality and evaluated the location of the tumor and the relationship between the tumor and the brachial plexus. The image quality scores of the two reconstruction methods were compared using the nonparametric Wilcoxon signed-rank test, and the consistency between the image and surgical results was assessed using the weighted kappa. Compared to MIP images, cVRT images had a better performance of overall image quality (p < 0.001), nerve and lump visualization (p < 0.001), spatial positional relationship conspicuity (p < 0.001), and diagnostic confidence (p < 0.001). Additionally, the consistency between the cVRT image results and surgical results (kappa =0.913, P<0.001) was higher than that of the MIP images (kappa =0.829, P<0.001). cVRT provides a high guiding value in the preoperative diagnosis of brachial plexus schwannomas and is an important basis for formulating surgical plans.

[The role of natural killer cells in anti-infection and tumor therapy].

Natural killer (NK) cells are an important part of the body's innate immune system. As the first line of defense against pathogens, they need to be transformed into a mature state under the control of various cell signaling molecules and transcription factors to play cytotoxic and immune regulatory roles. Under the interaction of activated receptors and inhibitory receptors, NK cells are activated to perform a direct cell killing effect by secreting perforin and granzyme, or indirectly eliminate pathogenic microorganisms in the body by secreting various cytokines, such as type I and type II interferons. These functions of NK cells play a very important role in antiviral and anti-autoimmune diseases, especially in anti-tumor.

Design and synthesis of 1H-benzo[d]imidazole selective HDAC6 inhibitors with potential therapy for multiple myeloma.

Pan-HDAC inhibitors exhibit significant inhibitory activity against multiple myeloma, however, their clinical applications have been hampered by substantial toxic side effects. In contrast, selective HDAC6 inhibitors have demonstrated effectiveness in treating multiple myeloma. Compounds belonging to the class of 1H-benzo[d]imidazole hydroxamic acids have been identified as novel HDAC6 inhibitors, with the benzimidazole group serving as a specific linker for these inhibitors. Notably, compound 30 has exhibited outstanding HDAC6 inhibitory activity (IC50 = 4.63 nM) and superior antiproliferative effects against human multiple myeloma cells, specifically RPMI-8226. Moreover, it has been shown to induce cell cycle arrest in the G2 phase and promote apoptosis through the mitochondrial pathway. In a myeloma RPMI-8226 xenograft model, compound 30 has demonstrated significant in vivo antitumor efficacy (T/C = 34.8%) when administered as a standalone drug, with no observable cytotoxicity. These findings underscore the immense potential of compound 30 as a promising therapeutic agent for the treatment of multiple myeloma.

Colon-targeted delivery of polyphenols: construction principles, targeting mechanisms and evaluation methods.

Polyphenols have received considerable attention for their promotive effects on colonic health. However, polyphenols are mostly sensitive to harsh gastrointestinal environments, thus, must be protected. It is necessary to design and develop a colon-targeted delivery system to improve the stability, colon-targeting and bioavailability of polyphenols. This paper mainly introduces research on colon-targeted controlled release of polyphenols. The physiological features affecting the dissolution, release and absorption of polyphenol-loaded delivery systems in the colon are first discussed. Simultaneously, the types of colon-targeted carriers with different release mechanisms are described, and colon-targeting assessment models that have been studied so far and their advantages and limitations are summarized. Based on the current research on polyphenols colon-targeting, outlook and reflections are proposed, with the goal of inspiring strategic development of new colon-targeted therapeutics to ensure that the polyphenols reach the colon with complete bioactivity.

Fabrication of fat-reduced water-in-oil emulsion and the application in 3D printing.

Water-in-oil (W/O) emulsion is promising to design fat-reduced foods for 3D printing. In this study, oleogel-based W/O emulsion containing 65% water fraction was prepared by sunflower wax (SW, 1.0 wt%) and soybean phosphatidylethanolamine (SP, 0.5 wt%) with stability exceeding 30 days. Besides reducing interfacial tension, from X-ray diffraction and rheological results, SP was considered co-oleogelator to change the crystal habit of SW to enhance the external SW-based oleogel structure. The strong external oleogel structure was not only good for reducing droplets movements to improve physical stability, but facilitating the molding and supporting abilities of the emulsion gel in 3D printing. Based on rheological measurements, the emulsion gels were shown improved printing performance with SP increasing: extrusion (shear-thinning behavior), recovery (excellent thixotropy), and self-supporting (sufficient storage modulus and deformation resistance). In 3D printing, the emulsion gels with growing SP were displayed better shape retention and allowed printing the designs with more delicate and vivid features. This study provided new insight for W/O emulsion formation using natural ingredients for 3D printing to create fat-reduced foods.

Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features.

BACKGROUND: Axillary lymph node (ALN) metastasis is used to select treatment strategies and define the prognosis in breast cancer (BC) patients and is typically assessed using an invasive procedure. Noninvasive, simple, and reliable tools to accurately predict ALN status are desirable. We aimed to develop and validate a point-based scoring system (PSS) for stratifying the ALN metastasis risk of BC based on clinicopathological and quantitative MRI features and to explore its prognostic significance. METHODS: A total of 219 BC patients were evaluated. The clinicopathological and quantitative MRI features of the tumors were collected. A multivariate logistic regression analysis was used to create the PSS. The performance of the models was evaluated using receiver operating characteristic curves, and the area under the curve (AUC) of the models was calculated. Kaplan-Meier curves were used to analyze the survival outcomes. RESULTS: Clinical features, including the American Joint Committee on Cancer (AJCC) stage, T stage, human epidermal growth factor receptor-2, estrogen receptor, and quantitative MRI features, including maximum tumor diameter, Kep, Ve, and TTP, were identified as risk factors for ALN metastasis and were assigned scores for the PSS. The PSS achieved an AUC of 0.799 in the primary cohort and 0.713 in the validation cohort. The recurrence-free survival (RFS) and overall survival (OS) of the high-risk (> 19.5 points) groups were significantly shorter than those of the low-risk (≤ 19.5 points) groups in the PSS. CONCLUSION: PSS could predict the ALN metastasis risk of BC. A PSS greater than 19.5 was demonstrated to be a predictor of short RFS and OS.