Intratumoral and Peritumoral Radiomics Based on Preoperative MRI for Evaluation of Programmed Cell Death Ligand-1 Expression in Breast Cancer.

BACKGROUND: Programmed cell death ligand-1 (PD-L1) is a promising target for immune checkpoint blockade therapy in breast cancer. However, the preoperative evaluation of PD-L1 expression in breast cancer is rarely explored. PURPOSE: To determine the ability of radiomics signatures based on preoperative dynamic contrast-enhanced (DCE) MRI to evaluate PD-L1 expression in breast cancer. STUDY TYPE: Retrospective. POPULATION: 196 primary breast cancer patients with preoperative MRI and postoperative pathological evaluation of PD-L1 expression, divided into training (n = 137, 28 PD-L1-positive) and test cohorts (n = 59, 12 PD-L1-positive). FIELD STRENGTH/SEQUENCE: 3.0T; volume imaging for breast assessment DCE sequence. ASSESSMENT: Radiomics features were extracted from the first phase of DCE-MRI by using the minimum redundancy maximum relevance method and least absolute shrinkage and selection operator algorithm. Three radiomics signatures were constructed based on the intratumoral, peritumoral, and combined intra- and peritumoral regions. The performance of the signatures was assessed using area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, and accuracy. STATISTICAL TESTS: Univariable and multivariable logistic regression analysis, t-tests, chi-square tests, Fisher exact test or Yates correction, ROC analysis, and one-way analysis of variance. P < 0.05 was considered significant. RESULTS: In the test cohort, the combined radiomics signature (AUC, 0.853) exhibited superior performance compared to the intratumoral (AUC, 0.816; P = 0.528) and peritumoral radiomics signatures (AUC, 0.846; P = 0.905) in PD-L1 status evaluation, although the differences did not reach statistical significance. DATA CONCLUSION: Intratumoral and peritumoral radiomics signatures based on preoperative breast MRI showed some potential accuracy for the non-invasive evaluation of PD-L1 status in breast cancer. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Lumbar MR-based radiomics nomogram for detecting minimal residual disease in patients with multiple myeloma.

OBJECTIVES: Minimal residual disease (MRD) is a standard for assessing treatment response in multiple myeloma (MM). MRD negativity is considered to be the most powerful predictor of long-term good outcomes. This study aimed to develop and validate a radiomics nomogram based on magnetic resonance imaging (MRI) of the lumbar spine to detect MRD after MM treatment. METHODS: A total of 130 MM patients (55 MRD negative and 75 MRD positive) who had undergone MRD testing through next-generation flow cytometry were divided into a training set (n = 90) and a test set (n = 40). Radiomics features were extracted from lumbar spinal MRI (T1-weighted images and fat-suppressed T2-weighted images) by means of the minimum redundancy maximum relevance method and the least absolute shrinkage and selection operator algorithm. A radiomics signature model was constructed. A clinical model was established using demographic features. A radiomics nomogram incorporating the radiomics signature and independent clinical factor was developed using multivariate logistic regression analysis. RESULTS: Sixteen features were used to establish the radiomics signature. The radiomics nomogram included the radiomics signature and the independent clinical factor (free light chain ratio) and showed good performance in detecting the MRD status (area under the curve: 0.980 in the training set and 0.903 in the test set). CONCLUSIONS: The lumbar MRI-based radiomics nomogram showed good performance in detecting MRD status in MM patients after treatment, and it is helpful for clinical decision-making. KEY POINTS: • The presence or absence of minimal residual disease status has a strong predictive significance for the prognosis of patients with multiple myeloma. • A radiomics nomogram based on lumbar MRI is a potential and reliable tool for evaluating minimal residual disease status in MM.

Evaluating Tumor-Infiltrating Lymphocytes in Breast Cancer Using Preoperative MRI-Based Radiomics.

BACKGROUND: Evaluating tumor-infiltrating lymphocytes (TILs) in patients with breast cancer using radiomics has been rarely explored. PURPOSE: To establish a radiomics nomogram based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for preoperatively evaluating TIL level. STUDY TYPE: Retrospective. POPULATION: A total of 154 patients with breast cancer were divided into a training cohort (N = 87) and a test cohort (N = 67), who were further divided into low TIL (<50%) and high TIL (≥50%) subgroups according to the histopathological results. FIELD STRENGTH/SEQUENCE: 3.0 T; axial T2-weighted imaging (fast spin echo), diffusion-weighted imaging (spin echo-echo planar imaging), and the volume imaging for breast assessment DCE sequence (gradient recalled echo). ASSESSMENT: A radiomics signature was developed from the training dataset and independent risk factors were selected by multivariate logistic regression to build a clinical model. A nomogram model was built by combining radiomics score and risk factors. The performance of the nomogram was assessed using calibration curves and decision curves. The area under the receiver operating characteristic (ROC) curve, accuracy, sensitivity, and specificity were calculated. STATISTICAL TESTS: The least absolute shrinkage and selection operator, univariate and multivariate logistic regression analysis, t-tests and chi-squared tests or Fisher's exact test, Hosmer-Lemeshow test, ROC analysis, and decision curve analysis were conducted. P < 0.05 was considered statistically significant. RESULTS: The radiomics signature and nomogram model exhibited better calibration and validation performance in the training (radiomics: area under the curve [AUC] 0.86; nomogram: AUC 0.88) and test (radiomics: AUC 0.83; nomogram: AUC 0.84) datasets compared with clinical model (training: AUC 0.76; test: AUC 0.72). The decision curve demonstrated that the nomogram model exhibited better performance than the clinical model, with a threshold probability between 0.15 and 0.9. DATA CONCLUSION: The nomogram model based on preoperative MRI exhibited an excellent ability for the noninvasive evaluation of TILs in breast cancer. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Spinal MRI-Based Radiomics Analysis to Predict Treatment Response in Multiple Myeloma.

OBJECTIVE: The aim of this study was to explore the clinical utility of spinal magnetic resonance imaging-based radiomics to predict treatment response (TR) in patients with multiple myeloma (MM). METHODS: A total of 123 MM patients (85 in the training cohort and 38 in the test cohort) with complete response (CR) (n = 40) or non-CR (n = 83) were retrospectively enrolled in the study. Key feature selection and data dimension reduction were performed using the least absolute shrinkage and selection operator regression. A nomogram was built by combining radiomic signatures and independent clinical risk factors. The prediction performance of the nomogram was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Treatment response was assessed by determining the serum and urinary levels of M-proteins, serum-free light chain ratio, and the percentage of bone marrow plasma cells. RESULTS: Thirteen features were selected to build a radiomic signature. The International Staging System (ISS) stage was selected as an independent clinical factor. The radiomic signature and nomogram showed better calibration and higher discriminatory capacity (AUC of 0.929 and 0.917 for the radiomics and nomogram in the training cohort, respectively, and 0.862 and 0.874 for the radiomics and nomogram in the test cohort, respectively) than the clinical model (AUC of 0.661 and 0.674 in the training and test cohort, respectively). Decision curve analysis confirmed the clinical utility of the radiomics model. CONCLUSIONS: Nomograms incorporating a magnetic resonance imaging-based radiomic signature and ISS stage help predict the response to chemotherapy for MM and can be useful in clinical decision-making.

Comparative study on the gastrointestinal- and immune- regulation functions of Hedysari Radix Paeparata Cum Melle and Astragali Radix Praeparata cum Melle in rats with spleen-qi deficiency, based on fuzzy matter-element analysis.

CONTEXT: Hedysari Radix Praeparata Cum Melle (HRPCM) and Astragali Radix Praeparata Cum Melle (ARPCM) are used interchangeably in clinics to treat spleen-qi deficiency (SQD) symptom mainly including gastrointestinal dysfunction and decreased immunity, which has unknown differences in efficacy. OBJECTIVE: To investigate the differences between HRPCM and ARPCM on intervening gastrointestinal- and immune-function with SQD syndrome. MATERIALS AND METHODS: After the SQD model was established, the Sprague-Dawley (SD) rats were randomly divided into nine groups (n = 10): normal; model; Bu-Zhong-Yi-Qi Pills; 18.9, 12.6 and 6.3 g/kg dose groups of HRPCM and ARPCM. Gastrointestinal function including d-xylose, gastrin, amylase vasoactive intestinal peptide, motilin, pepsin, H+/K+-ATPase, Na+/K+-ATPase, sodium-glucose cotransporter 1 (SGLT1), glucose transporter 2 (GLUT2) and immune function including spleen and thymus index, blood routine, interleukin (IL)-2, IL-6, interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α), immunoglobulin (Ig) M, IgA, IgG and delayed-type hypersensitivity (DTH) were detected. Finally, the efficacy differences were analysed comprehensively by the fuzzy matter-element method. RESULTS: In regulating immune, the doses differences in efficacy between HRPCM and ARPCM showed in the high-dose (18.9 g/kg), but there were no differences in the middle- and low- dose (12.6 and 6.37 g/kg); the efficacy differences were primarily reflected in levels of IL-6, IFN-γ, TNF-α and IgM in serum, and the mRNA expression of IL-6 and IFN-γ in the spleen. In regulating gastrointestinal, the efficacy differences were primarily reflected in the levels of D-xylose, MTL, and GAS in serum, and the mRNA and protein expression of SGLT1 and GLUT2 in jejunum and ileum. DISCUSSION AND CONCLUSIONS: HRPCM is more effective than ARPCM on regulating gastrointestinal function and immune function with SQD syndrome. Therefore, we propose that HRPCM should be mainly used to treat SQD syndrome in the future.

[Comparative study of Astragali Radix Praeparata cum Melle and Hedysari Radix Praeparata cum Melle on spleen Qi deficiency rats].

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The role of CD28 in the prognosis of young lung adenocarcinoma patients.

BACKGROUND: The prognosis of lung cancer was found to be associated with a series of biomarkers related to the tumor immune microenvironment (TIME), which can modulate the biological behaviors and consequent outcomes of lung cancer. Therefore, establishing a prognostic model based on the TIME for lung cancer patients, especially young patients with lung adenocarcinoma (LUAD), is urgently needed. METHODS: In all, 809 lung cancer patients from the TCGA database and 71 young patients with LUAD in our center were involved in this study. Univariate and multivariate analysis based on clinical characteristics and TIME-related expression patterns (as evaluated by IHC) were performed to estimate prognosis and were verified by prognostic nomograms. RESULTS: Both LUAD and lung cancer patients with high CD28 expression had shorter disease-free survival (DFS) (P = 0.0011; P = 0.0001) but longer overall survival (OS) (P = 0.0001; P = 0.0282). TIME-related molecules combined with clinical information and genomic signatures could predict the prognosis of young patients with LUAD with robust efficiency and could be verified by the established nomogram based on the Cox regression model. In addition, CD28 expression was correlated with an abundance of lymphocytes and could modulate the TIME. Higher CD28 levels were observed in primary tumors than in metastatic tissues. CONCLUSION: TIME-related molecules were identified as compelling biomarkers for predicting the prognosis of lung cancer, especially in a cohort of young patients. Furthermore, CD28, which is associated with poor DFS but long OS, might participate in the modulation of the TIME and has a different role in the prognosis of young patients with LUAD.

Root Abscisic Acid Contributes to Defending Photoinibition in Jerusalem Artichoke (Helianthus tuberosus L.) under Salt Stress.

The aim of the study was to examine the role of root abscisic acid (ABA) in protecting photosystems and photosynthesis in Jerusalem artichoke against salt stress. Potted plants were pretreated by a specific ABA synthesis inhibitor sodium tungstate and then subjected to salt stress (150 mM NaCl). Tungstate did not directly affect root ABA content and photosynthetic parameters, whereas it inhibited root ABA accumulation and induced a greater decrease in photosynthetic rate under salt stress. The maximal photochemical efficiency of PSII (Fv/Fm) significantly declined in tungstate-pretreated plants under salt stress, suggesting photosystem II (PSII) photoinhibition appeared. PSII photoinhibition did not prevent PSI photoinhibition by restricting electron donation, as the maximal photochemical efficiency of PSI (ΔMR/MR0) was lowered. In line with photoinhibition, elevated H2O2 concentration and lipid peroxidation corroborated salt-induced oxidative stress in tungstate-pretreated plants. Less decrease in ΔMR/MR0 and Fv/Fm indicated that PSII and PSI in non-pretreated plants could maintain better performance than tungstate-pretreated plants under salt stress. Consistently, greater reduction in PSII and PSI reaction center protein abundance confirmed the elevated vulnerability of photosystems to salt stress in tungstate-pretreated plants. Overall, the root ABA signal participated in defending the photosystem's photoinhibition and protecting photosynthesis in Jerusalem artichoke under salt stress.

Digital Breast Tomosynthesis: A New Diagnostic Method for Mass-Like Lesions in Dense Breasts.

To compare the rates and accuracy of digital breast tomosynthesis (DBT) and 2D digital mammography (DM) for detecting and diagnosing mass-like lesions in dense breasts. Mediolateral and craniocaudal images taken with DBT (affected breast) and DM (both breasts) of the dense breasts of 631 women were assessed independently using Breast Imaging Reporting and Data System (BI-RADS) scores. Images were compared for detection and diagnostic accuracy for masses; sensitivity and specificity of diagnosis; false-negative and recall rates; and clarity of display, particularly of margins and spicules. Histopathology was conducted via surgical biopsies of all patients. The detection and diagnostic accuracy rates of DBT images (84.3% and 82.3%, respectively) were significantly higher than that of DM (77.3% and 73.4%; p < 0.01, both). The sensitivity and specificity of DBT (68.1% and 95.2%) were higher than that of DM (58.8% and 86.7%), whereas the recall rate of DBT was lower (3.6% cf. 9.8%). The number of cases of benign circumscribed masses and malignant spiculated masses detected by DBT (172 and 182) was significantly higher than the number detected through DM (75 and 115; p < 0.01, both). Radiologists assigned higher BI-RADS scores for probability of malignancy to DBT images than DM, to lesions proved malignant (p = 0.025); for benign cases, the methods were comparable (p = 0.065). Compared with DM, DBT yielded significantly higher rates of detection and diagnostic accuracy for benign and malignant masses, with greater sensitivity and specificity and lower recall rates. In addition, DBT images facilitated analysis of margins, and the rate of accuracy for judgments of malignancy probability was higher, as proved on biopsy.

Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.

RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary response after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. MATERIALS AND METHODS: We enrolled 327 BC patients with axillary lymph node (ALN) metastases receiving axillary operations after NAC. The deep learning features were extracted by ResNet34, which was pretrained by a large, well-annotated dataset from ImageNet. Then we identified deep learning radiomics on magnetic resonance imaging with dynamic contrast enhancement (DCE-MRI) in predicting axillary response after NAC in BC patients. RESULTS: The extraction of 128 deep learning radiomics (DLR) features relied on the DCE-MRI for each patient. After the least absolute shrinkage and selection operator regression analysis, 13, 8, and 21 features remained from the pre-treatment, post-treatment, and combined DCE-MRI, respectively. The DLR signature established based on the combined DCE-MRI achieved good capacity in ALN response after NAC. The support vector machine achieved the best performance with an 0.99 area under the curve (AUC) of (95% confidence interval (CI), 0.98-1.00) and 0.83 (95% CI, 0.73-0.92) in the training and test sets, respectively. The LR model established with clinical parameters represented the best performance with 0.73 AUC (95% CI, 0.62-0.84), 0.73 sensitivity, 0.73 specificity, 0.63 PPV, and 0.81 NPV in the test set, respectively. Finally, the integration of radiomic signature and clinical signature resulted in establishing a predictive radiomic nomogram, with an AUC of 0.99 (95%CI, 0.99-1.00). CONCLUSION: In conclusion, our current study constructed a predictive nomogram through the deep learning method, demonstrating favorable performance in the training and test cohort. The present prognostic model furnishes a precise and objective foundation for directing the surgical strategy toward ALN management in BC patients receiving NAC.

Network pharmacology and experimental verification reveal the mechanism of Hedysari Radix and Curcumae Rhizoma with the optimal compatibility ratio against colitis-associated colorectal cancer.

ETHNOPHARMACOLOGICAL RELEVANCE: The herb pair Astragali Radix (AR) and Curcumae Rhizoma (vinegar-processed, VPCR), derived from the traditional Chinese medicine (TCM) text 'Yixuezhongzhongcanxilu', have long been used to treat gastrointestinal diseases, notably colitis-associated colorectal cancer (CAC). Hedysari Radix (HR), belonging to the same Leguminosae family as AR but from a different genus, is traditionally used as a substitute for AR when paired with VPCR in the treatment of CAC. However, the optimal compatibility ratio for HR-VPCR against CAC and the underlying mechanisms remain unclear. AIM OF THE STUDY: To investigate the optimal compatibility ratio and underlying mechanisms of HR-VPCR against CAC using a combination of comparative pharmacodynamics, network pharmacology, and experimental verification. MATERIALS AND METHODS: The efficacy of different compatibility ratios of HR-VPCR against CAC was evaluated using various indicators, including the body weight, colon length, tumor count, survival rate, disease activity index (DAI) score, Haemotoxylin and Eosin (H&E) pathological sections, inflammation cytokines (IL-1ß, IL-6, IL-10, TNF-α), tumor markers (K-Ras, p53), and intestinal permeability proteins (claudin-1, E-cadherin, mucin-2). Then, the optimal compatibility ratio of HR-VPCR against CAC was determined based on the fuzzy matter-element analysis by integrating the above indicators. After high-performance liquid chromatography (HPLC) analysis for the optimal compatibility ratio of HR-VPCR, potential active components of HR-VPCR were identified by TCMSP and the previous bibliographies. Swiss Targets and GeneCards were adopted to predict the targets of the active components and the targets of CAC, respectively. Then, the common targets of HR-VPCR against CAC were obtained by Venn analysis. PPI networks were constructed in STRING. GO and KEGG enrichments were visualized by the David database. Finally, the predicted pathway was experimentally validated via Western blot. RESULTS: Various compatibility ratios of HR-VPCR demonstrated notable therapeutic effects to some extent, evidenced by improvements in body weight, colon length, tumor count, pathological symptoms (DAI score), colon and organ indexes, survival rate, and modulation of inflammation factors (IL-1ß, IL-6, IL-10, TNF-α), as well as tumor markers (K-Ras, p53), and down-regulation of intestinal permeability proteins (claudin-1, E-cadherin, mucin-2) in CAC mice. Among these ratios, the ratio 4:1 represents the optimal compatibility ratio by the fuzzy matter-element analysis. Thirty active components of HR-VPCR were carefully selected, targeting 553 specific genes. Simultaneously, 2022 targets associated with CAC were identified. 88 common targets were identified after generating a Venn plot. Following PPI network analysis, 29 core targets were established, with AKT1 ranking highest among them. Further analysis via GO and KEGG enrichment identified the PI3K-AKT signaling pathway as a potential mechanism. Experimental validation confirmed that HR-VPCR intervention effectively reversed the activated PI3K-AKT signaling pathway. CONCLUSIONS: The optimal compatibility ratio for the HR-VPCR herb pair in alleviating CAC is 4:1. HR-VPCR exerts its effects by alleviating intestinal inflammation, improving intestinal permeability, and regulating the PI3K-AKT signaling pathway.

An MRI-Based Radiomics Nomogram to Distinguish Ductal Carcinoma In Situ with Microinvasion From Ductal Carcinoma In Situ of Breast Cancer.

RATIONALE AND OBJECTIVES: Accurate preoperative differentiation between ductal carcinoma in situ with microinvasion (DCISM) and ductal carcinoma in situ (DCIS) could facilitate treatment optimization and individualized risk assessment. The present study aims to build and validate a radiomics nomogram based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) that could distinguish DCISM from pure DCIS breast cancer. MATERIALS AND METHODS: MR images of 140 patients obtained between March 2019 and November 2022 at our institution were included. Patients were randomly divided into a training (n = 97) and a test set (n = 43). Patients in both sets were further split into DCIS and DCISM subgroups. The independent clinical risk factors were selected by multivariate logistic regression to establish the clinical model. The optimal radiomics features were chosen by the least absolute shrinkage and selection operator, and a radiomics signature was built. The nomogram model was constructed by integrating the radiomics signature and independent risk factors. The discrimination efficacy of our nomogram was assessed by using calibration and decision curves. RESULTS: Six features were selected to construct the radiomics signature for distinguishing DCISM from DCIS. The radiomics signature and nomogram model exhibited better calibration and validation performance in the training (AUC 0.815, 0.911, 95% confidence interval [CI], 0.703-0.926, 0.848-0.974) and test (AUC 0.830, 0.882, 95% CI, 0.672-0.989, 0.764-0.999) sets than in the clinical factor model (AUC 0.672, 0.717, 95% CI, 0.544-0.801, 0.527-0.907). The decision curve also demonstrated that the nomogram model exhibited good clinical utility. CONCLUSION: The proposed noninvasive MRI-based radiomics nomogram model showed good performance in distinguishing DCISM from DCIS.

Identifications of metabolic differences between Hedysari Radix Praeparata Cum Melle and Astragali Radix Praeparata Cum Melle for spleen-qi deficiency rats: A comparative study.

Hedysari Radix Praeparata Cum Melle (HRPCM) and Astragali Radix Praeparata Cum Melle (ARPCM) are capable of improving spleen-qi deficiency (SQD) syndrome especially in the gastrointestinal dysfunction and decreased immunity in traditional Chinese medicine clinically. This study aims to compare and reveal the metabolic differences between HRPCM and ARPCM for SQD rats. Firstly, HRPCM (12.6 g/kg) and ARPCM (12.6 g/kg) were used to intervene SQD rats to further evaluate the effect. The results showed that HRPCM and ARPCM were able to improve the spleen pathology, increase the body weight, the rectal temperature, the spleen index, the thymus index, the levels of GAS and D-xylose in serum, and decrease the levels of IL-2, IL-6 and TNF-α in serum for SQD rats. Then, the studies of metabolic differences in serum and spleen were carried out using UPLC-Q-TOF-MS. The findings emphasized that HRPCM and ARPCM not only regulated metabolic profiling of serum and spleen in SQD rats, but also existed differences. HRPCM and ARPCM regulated metabolic pathways mainly including lipid metabolism, energy metabolism, amino acid metabolism, nucleotide metabolism, sugar metabolism and other types of metabolism for SQD rats. However, the metabolite profiles in SQD rats changed significantly, mainly involving abnormal glycine synthesis occurred in SQD rats. The expression trends of metabolites in HRPCM and ARPCM intervention for SQD rats were partly the same. Interestingly, there are similarities and differences in metabolic profiling between HRPCM and ARPCM for SQD rats. The differences were mainly in the synthesis of L-glutamine in amino acid metabolism.

Evaluation of Lymphatic Vessel Invasion Determined by D2-40 Using Preoperative MRI-Based Radiomics for Invasive Breast Cancer.

RATIONALE AND OBJECTIVES: Preoperative prediction of LVI status can facilitate personalized therapeutic planning. This study aims to investigate the efficacy of preoperative MRI-based radiomics for predicting lymphatic vessel invasion (LVI) determined by D2-40 in patients with invasive breast cancer. MATERIALS AND METHODS: A total of 203 patients with pathologically confirmed invasive breast cancer, who underwent preoperative breast MRI, were retrospectively enrolled and randomly assigned to the following cohorts: training cohort (n=141) and test cohort (n=62). Then, univariate and multivariate logistic regression were performed to select independent risk factors and build a clinical model. Afterwards, least absolute shrinkage and selection operator (LASSO) logistic regression was performed to select predictive features extracted from the early and delay enhancement dynamic contrast-enhanced (DCE)-MRI images, and a radiomics signature was established. Subsequently, a nomogram model was constructed by incorporating the radiomics score and risk factors. Receiver operating characteristic curves were performed to determine the performance of various models. The efficacy of the various models was evaluated using calibration and decision curves. RESULTS: Fourteen radiomics features were selected to construct the radiomics model. The size of the lymph node was identified as an independent risk factor of the clinical model. The nomogram model demonstrated the best calibration and discrimination performance in both the training and test cohorts, with an area under the curve of 0.873 (95% confidence interval [CI]: 0.807-0.923) and 0.902 (95% CI: 0.800-0.963), respectively. The decision curve illustrated that the nomogram model added more net benefits, when compared to the radiomics signature and clinical model. CONCLUSION: The nomogram model based on preoperative DCE-MRI images exhibits satisfactory efficacy for the noninvasive prediction of LVI determined by D2-40 in invasive breast cancer.

Loss of ARID1A expression promotes lung adenocarcinoma metastasis and predicts a poor prognosis.

BACKGROUND: ARID1A is an essential subunit of SWI/SNF chromatin remodeling complexes. ARID1A gene mutations and loss of ARID1A expression have been observed in a variety of cancers, and to be correlated with invasion, immune escape and synthetic lethality. As yet, however, the biological effect of ARID1A expression and its role in the prognosis of lung adenocarcinoma (LUAD) patients have remained unclear. In this study we aimed to further elucidate the role of ARID1A expression in LUAD in vitro and in vivo and to assess its effect on the clinical prognosis of LUAD patients. METHODS: ARID1A expression was detected by IHC in tissue samples from LUAD patients. After regular culturing of LUAD cell lines and constructing stable ARID1A knockdown lines, wound healing and Transwell assays were used to assess the role of ARID1A in cell migration and invasion. The effect of ARID1A knockdown on metastasis was verified in vivo. Western blotting was used to examine the expression of target proteins. Univariate and multivariate analyses were performed to assess survival and to provide variables for nomogram construction. In addition, we used the "rms" package to construct a prognostic nomogram based on a Cox regression model. RESULTS: We found that ARID1A expression serves as an effective prognostic marker for LUAD patients. Loss of ARID1A expression correlated with a poor prognosis, as verified with a nomogram based on a Cox regression model. In addition, we found that ARID1A knockdown promoted LUAD cell proliferation, migration and invasion in vitro and enhanced LUAD metastasis in vivo by activating the Akt signaling pathway. CONCLUSIONS: Our data indicate that loss of ARID1A expression promotes LUAD metastasis and predicts a poor prognosis in LUAD patients.

Actin-Binding Proteins as Potential Biomarkers for Chronic Inflammation-Induced Cancer Diagnosis and Therapy.

Actin-binding proteins (ABPs), by interacting with actin, regulate the polymerization, depolymerization, bundling, and cross-linking of actin filaments, directly or indirectly, thereby mediating the maintenance of cell morphology, cell movement, and many other biological functions. Consequently, these functions of ABPs help regulate cancer cell invasion and metastasis when cancer occurs. In recent years, a variety of ABPs have been found to be abnormally expressed in various cancers, indicating that the detection and interventions of unusual ABP expression to alter this are available for the treatment of cancer. The early stages of most cancer development involve long-term chronic inflammation or repeated stimulation. This is the case for breast cancer, gastric cancer, lung cancer, prostate cancer, liver cancer, esophageal cancer, pancreatic cancer, melanoma, and colorectal cancer. This article discusses the relationship between chronic inflammation and the above-mentioned cancers, emphatically introduces relevant research on the abnormal expression of ABPs in chronic inflammatory diseases, and reviews research on the expression of different ABPs in the above-mentioned cancers. Furthermore, there is a close relationship between ABP-induced inflammation and cancer. In simple terms, abnormal expression of ABPs contributes to the chronic inflammation developing into cancer. Finally, we provide our viewpoint regarding these unusual ABPs serving as potential biomarkers for chronic inflammation-induced cancer diagnosis and therapy, and interventions to reverse the abnormal expression of ABPs represent a potential approach to preventing or treating the corresponding cancers.

[Effects of root abscisic acid on Na+ transport and photosystem 2 in Helianthus tuberosus under salt stress]. / ç›èƒè¿«ä¸‹èŠèŠ‹æ ¹ç³»è„±è½é ¸å¯¹é’ ç¦»å­è½¬è¿å’Œå ‰ç³»ç»Ÿâ ¡çš„å½±å“.

The effects of root abscisic acid (ABA) signal on Na+ transport and photosystem 2 (PS2) in Jerusalem artichoke (Helianthus tuberosus) under salt stress (150 mmol·L-1 NaCl) were examined by applying ABA synthesis inhibitor sodium tungstate to roots. Sodium tungstate inhibited ABA synthesis in roots, reduced root Na+ efflux, and increased the efficiency of Na+ transport from roots to leaves under salt stress. Salt stress increased leaf Na+ content and did not affect leaf membrane lipid peroxidation, PS2 reaction center protein and PS2 maximum photochemical efficiency (Fv/Fm ). The inhibition on root ABA synthesis significantly increased leaf Na+ accumulation, aggravated leaf membrane lipid peroxidation, impaired PS2 reaction center protein, decreased Fv/Fm, and induced PS2 photoinhibition. In conclusion, root ABA signal was beneficial to reducing leaf Na+ accumulation and preventing PS2 oxidative damage by inducing root Na+ efflux and inhibiting Na+ transport to the aerial part in H. tuberosus under salt stress.

Computed tomography, magnetic resonance imaging, and F-deoxyglucose positron emission computed tomography/computed tomography findings of alveolar soft part sarcoma with calcification in the thigh: A case report.

BACKGROUND: Alveolar soft part sarcoma (ASPS) is an extremely rare malignant sarcoma, accounting for less than 1% of all soft-tissue sarcomas. However, limited information is available on multimodal imaging [computed tomography (CT), magnetic resonance imaging (MRI), and positron emission computed tomography/computed tomography (PET/CT)] of ASPS. CASE SUMMARY: This study reports a case of a 35-year-old female patient with ASPS of the left thigh with lung metastasis. The patient presented with a 1-year history of a palpable mass in the lower extremity, which exhibited rapid growth for 3 wk. CT, MRI, and F-deoxyglucose PET/CT examinations were performed. CT showed a slightly hypodense or isodense mass with patchy calcifications. On MRI examination, the mass manifested hyperintensity on T1-weighted, T2-weighted, and diffusion-weighted images with some signal voids. PET/CT images demonstrated an intensely hypermetabolic mass in the left thigh and hypermetabolic nodules in lungs. CONCLUSION: ASPS should be considered as a possible diagnosis when a slow-growing mass is detected in the soft tissue of the extremities, with hyperintensity and numerous signal voids on T1-weighted, T2-weighted, and diffusion-weighted images and intense F-deoxyglucose uptake on PET/CT. ASPS can have calcifications on CT.

Material Basis of the Difference between Hedysari Radix and Honey-Processed Hedysari Radix in Buzhong Yiqi.

OBJECTIVE: To compare the changes of chemical components of Hedysari Radix (HR) before and after honey-processing, and to explore the material basis of the difference between HR and honey-processed Hedysari Radix (HPHR) in Buzhong Yiqi. METHODS: Different compounds in aqueous extracts of HR and HPHR were analysed by UPLC-MS. A rat model of spleen qi deficiency was established. The rats were treated with different doses of water extracts of HR or HPHR, and pathological differences in spleen tissue, serum levels of D-xylose, gastrin (GAS) and amylase (AMS) interleukin-2 (IL)-2 and tumour necrosis factor-α (TNF-α), as well as spleen and thymus indices, were used as indicators. Differences in the efficacy of HR and HPHR in Buzhong Yiqi were studied. RESULTS: The research showed that compared with the blank group, the spleen tissue of rats in the model group showed spleen tissue damage, which mainly manifested as unclear boundaries between red pulp and white pulp, irregular spleen morphology and irregular arrangement, and the structure of white pulp destruction, less lymphocytes, the number of germinal centers decreased or atrophied. Compared with the model group, the middle and high dose groups of HR and HPHR had protective effects on spleen tissue of spleen-qi deficiency rats, and HPHR had a stronger effect; compared with those in the model group, rats in each treatment group showed remarkably higher serum D-xylose, GAS and AMS levels and thymus and spleen indices, and remarkably lower serum IL-2 and TNF-α levels, among which HPHR group showed better regulation effect than HR group. A total of 16 differential compounds were found in the aqueous extracts of HR and HPHR, of which 10 compounds in HPHR were up regulated, while 6 compounds were down regulated compare to HR. CONCLUSION: The results indicated that both HR and HPHR can improve spleen qi deficiency syndrome of rats, the pharmacodynamic effect of the latter was better than the former. Differences in components of HR and HPHR potentially leading to variations in efficacy.

Radiomic signatures derived from multiparametric MRI for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer.

OBJECTIVES: To investigate the ability of radiomic signatures based on MRI to evaluate the response and efficiency of neoadjuvant chemotherapy (NAC) for treating breast cancers. METHODS: 152 patients were included in this study at our institution between March 2017 and September 2019. All patients with breast cancer underwent a preoperative breast MRI and the Miller-Payne grading system was applied to evaluate response to NAC. Quantitative parameters were compared between patients with sensitive and insensitive responses to NAC and between those with pathological complete responses (pCR) and non-pCR. Four radiomic signatures were built based on T2W imaging, diffusion-weighted imaging, dynamic contrast-enhanced imaging and their combination, and radiomics scores (Rad-score) were calculated. The combination of the clinical factors and Rad-scores created a nomogram model. Multivariate logistic regression was performed to assess the association between MRI features and independent clinical risk factors. RESULTS: 20 features and 18 features were selected to build the radiomic signature for evaluating sensitivity and the possibility of pCR, respectively. The combined radiomic signature and nomogram model showed a similar discrimination in the training (AUC 0.91, 0.92, 95% confidence interval [CI], 0.85-0.96, 0.86-0.98) and validation (AUC 0.93, 0.91, 95% CI, 0.86-1.00, 0.82-1.00) sets. The clinical factor model exhibited reduced performance (AUC 0.74, 0.64, 95% CI, 0.64-0.84, 0.46-0.82) in terms of NAC sensitivity and pCR. CONCLUSIONS: The combined radiomic signature and nomogram model exhibited potential predictive power for predicting effective NAC treatment which can aid in the prognosis and guidance of treatment regimens. ADVANCES IN KNOWLEDGE: Identifying a means of assessing the efficacy of NAC before surgery can guide follow-up treatment and avoid chemotherapy-induced toxicity.