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BackgroundMillions of people across the globe are affected by conditions like Amyotrophic Lateral Sclerosis (ALS), Parkinson’s Disease (PD), Multiple Sclerosis (MS), Spinal Cord Injury (SCI), and Traumatic Brain Injury (TBI), although most occurrences are common in the elderly population. This systematic review aims to highlight the safety of the procedures, their tolerability, and efficacy of the available therapies conducted over the years using mesenchymal stem cells (MSCs) in treating the neurological conditions mentioned above.MethodsPubMed was used to search for published data from clinical trials performed using mesenchymal stem cells. Studies that provided the necessary information that mentioned the efficacy and adverse effects of the treatment in patients were considered for this review.ResultsIn total, 43 manuscripts were selected after a strategic search, and these studies have been included in this systematic review. Most included studies reported the safety of the procedures used and the treatment’s good tolerability, with mild adverse events such as fever, headache, mild pain at the injection site, or nausea being common. A few studies also reported death of some patients, attributed to the progression of the disease to severe stages before the treatment. Other severe events, such as respiratory or urinary infections reported in some studies, were not related to the treatment. Different parameters were used to evaluate the efficacy of the treatment based on the clinical condition of the patient.ConclusionMesenchymal stem cells transplantation has so far proven to be safe and tolerable in select studies and patient types. This systematic review includes the results from the 43 selected studies in terms of safety and tolerability of the procedures, and several adverse events and therapeutic benefits during the follow-up period after administration of MSCs.

Abstract Background Flowering is a critical physiological change that interferes with not only biomass yield but also secondary metabolism, such as the biosynthesis of flavonoids, in rhizome/root plants. The continuous inflorescence removal (CIR) treatment is frequently conducted to weaken this effect. Fagopyrum dibotrys (D.Don) H.Hara (Golden buckwheat) is a kind of rhizome medicinal plant rich in flavonoids and is widely used for the treatment of lung diseases. The CIR treatment is usually conducted in F. dibotrys because of its excessive reproductive growth. To uncover the molecular mechanisms, comprehensive analysis was performed using metabolome and transcriptome data obtained from normally bloomed and the CIR treated plants. Results Metabolome results demonstrated that in the rhizomes of F. dibotrys, its bioactive compound called epicatechin has higher amount than most of the detected precursors. Compared with the normally bloomed plants, the level of epicatechin in the rhizomes of the CIR group increased by 25% at the withering stage. Based on 96 samples of the control and the CIR groups at 4 flowering stages for 4 tissues, RNA-Seq results revealed a 3 ~ 5 times upregulations of all the key enzyme genes involved in the biosynthesis of epicatechin in both time (from the bud stage to the withering stage) and spatial dimensions (from the top of branch to rhizome) under the CIR treatment compared to normal flowering. Integrated analysis of LC–MS/MS and transcriptome revealed the key roles of several key enzyme genes besides anthocyanidin reductase (ANR). A total of 93 transcription factors were identified to co-expressed with the genes in epicatechin biosynthetic pathway. The flowering activator SQUAMOSA promoter-binding protein like (SPLs) exhibited opposite spatiotemporal expression patterns to that of the epicatechin pathway genes; SPL3 could significantly co-express with all the key enzyme genes rather than the flowering repressor DELLA. Weighted gene co-expression network analysis (WGCNA) further confirmed the correlations among chalcone synthases (CHSs), chalcone isomerases (CHIs), ANRs, SPLs and other transcription factors. Conclusions SPL3 might dominantly mediate the effect of normal flowering and the CIR treatment on the biosynthesis of epicatechin in rhizomes mainly through the negative regulations of its key enzyme genes including CHS, CHI and ANR.

In the adult skeleton, cells of the immune system interact with those of the skeleton during all phases of bone repair to influence the outcome. Mast cells are immune cells best known for their pathologic role in allergy, and may be involved in chronic inflammatory and fibrotic disorders. Potential roles for mast cells in tissue homeostasis, vascularization and repair remain enigmatic. Previous studies in combined mast cell- and Kit-deficient KitW-sh/W-sh mice (KitW-sh) implicated mast cells in bone repair but KitW-sh mice suffer from additional Kit-dependent hematopoietic and non- hematopoietic deficiencies that could have confounded the outcome. The goal of the current study was to compare bone repair in normal wild type (WT) and Cpa3Cre/+ mice, which lack mast cells in the absence of any other hematopoietic or non- hematopoietic deficiencies. Repair of a femoral window defect was characterized using micro CT imaging and histological analyses from the early inflammatory phase, through soft and hard callus formation, and finally the remodeling phase. The data indicate 1) mast cells appear in healing bone of WT mice but not Cpa3Cre/+ mice, beginning 14 days after surgery; 2) re-vascularization of repair tissue and deposition of mineralized bone was delayed and dis-organised in Cpa3Cre/+ mice compared with WT mice; 3) the defects in Cpa3Cre/+ mice were associated with little change in anabolic activity and biphasic alterations in osteoclast and macrophage activity. The outcome at 56 days postoperative was complete bridging of the defect in most WT mice and fibrous mal-union in most Cpa3Cre/+ mice. The results indicate that mast cells promote bone healing, possibly by recruiting vascular endothelial cells during the inflammatory phase and coordinating anabolic and catabolic activity during tissue remodeling. Taken together the data indicate that mast cells have a positive impact on bone repair.

The Src substrate associated in mitosis of 68 kDa (Sam68) is a KH-type RNA binding protein that has been shown to regulate several aspects of RNA metabolism; however, its physiologic role has remained elusive. Herein we report the generation of Sam68-null mice by homologous recombination. Aged Sam68-/- mice preserved their bone mass, in sharp contrast with 12-month-old wild-type littermates in which bone mass was decreased up to approximately 75%. In fact, the bone volume of the 12-month-old Sam68-/- mice was virtually indistinguishable from that of 4-month-old wild-type or Sam68-/- mice. Sam68-/- bone marrow stromal cells had a differentiation advantage for the osteogenic pathway. Moreover, the knockdown of Sam68 using short hairpin RNA in the embryonic mesenchymal multipotential progenitor C3H10T1/2 cells resulted in more pronounced expression of the mature osteoblast marker osteocalcin when differentiation was induced with bone morphogenetic protein-2. Cultures of mouse embryo fibroblasts generated from Sam68+/+ and Sam68-/- littermates were induced to differentiate into adipocytes with culture medium containing pioglitazone and the Sam68-/- mouse embryo fibroblasts shown to have impaired adipocyte differentiation. Furthermore, in vivo it was shown that sections of bone from 12-month-old Sam68-/- mice had few marrow adipocytes compared with their age-matched wild-type littermate controls, which exhibited fatty bone marrow. Our findings identify endogenous Sam68 as a positive regulator of adipocyte differentiation and a negative regulator of osteoblast differentiation, which is consistent with Sam68 being a modulator of bone marrow mesenchymal cell differentiation, and hence bone metabolism, in aged mice.

PurposeTo explore the value of quantitative imaging parameters by enhanced T2* weighted angiography (ESWAN) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for evaluating the expression of Hypoxia-inducible factor-1α (HIF-1α) in endometrial carcinoma (EC).MethodsData from 122 patients with EC confirmed by clinical pathology were retrospectively analyzed. According to the number of positive cells stained with HIF-1α by immunohistochemistry, patients were divided into two groups: 65 cases with high expression of HIF-1α and 57 cases with low expression of HIF-1α. Clinical data included age, FIGO stage, menopausal status, abnormal uterine bleeding, and pathological type. All patients underwent preoperative 1.5T MRI scans, including ESWAN and DCE-MRI. The amplitude, phase, and R2* values derived from ESWAN and the volume transfer constant (Ktrans), rate constant (Kep), and extravascular volume fraction (Ve) values derived from DCE-MRI were measured by two observers, respectively. The intra-class correlation coefficient (ICC) was used to assess the measurement of reproducibility across observers, and the differences in imaging parameters between the two groups were compared using the independent sample t-test or Mann-Whitney U-test. Binary logistic regression analysis was used to find independent risk factors for HIF-1α expression. The efficacy of selected imaging parameters for predicting HIF-1α expression was assessed using receiver operating characteristic (ROC) curves, and the Delong test was used to compare the area under ROC curves (AUC).ResultsThe consistency between the two observers was good (ICC>0.75). The R2*, Ktrans, and Kep values of the HIF-1α high expression group were higher than those of the HIF-1α low expression group (14.59 ± 4.06 vs. 11.99 ± 2.84 Hz, 0.45 ± 0.18 vs. 0.36 ± 0.14/min, and 2.17 ± 1.10 vs. 1.54 ± 0.80/min) (P< 0.001, P = 0.011, and P =0.001). Binary logistic regression analysis revealed that R2* and Kep values were independent risk factors for HIF-1α expression. The AUC values of R2*, Kep, and their combination for prediction of HIF-1α expression were 0.697, 0.677, and 0.781, respectively. The diagnostic efficacy was significantly improved with combination of R2* and Kep.ConclusionsQuantitative parameters by ESWAN and DCE-MRI showed significant differences between EC patients with low and high expression of HIF-1α, and the combination of ESWAN and DCE-MRI improves the efficacy in prediction of HIF-1α expression in EC, which has an excellent clinical application prospect.

PurposeTo explore the role of deep learning (DL) and radiomics-based integrated approach based on contrast enhanced magnetic resonance imaging (CEMRI) for predicting early recurrence (ER) in hepatocellular carcinoma (HCC) patients after curative resection.MethodsTotal 165 HCC patients (ER, n = 96 vs. non-early recurrence (NER), n = 69) were retrospectively collected and divided into a training cohort (n = 132) and a validation cohort (n = 33). From pretreatment CEMR images, a total of 3111 radiomics features were extracted, and radiomics models were constructed using five machine learning classifiers (logistic regression, support vector machine, k-nearest neighbor, extreme gradient Boosting, and multilayer perceptron). DL models were established via three variations of ResNet architecture. The clinical-radiological (CR), radiomics combined with clinical-radiological (RCR), and deep learning combined with RCR (DLRCR) models were constructed. Model discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. The best-performing model was compared with the widely used staging systems and preoperative prognostic indexes.ResultsThe RCR model (area under the curve (AUC): 0.841 and 0.811) and the optimal radiomics model (AUC: 0.839 and 0.804) achieved better performance than the CR model (AUC: 0.662 and 0.752) in the training and validation cohorts, respectively. The optimal DL model (AUC: 0.870 and 0.826) outperformed the radiomics model in the both cohorts. The DL, radiomics, and CR predictors (aspartate aminotransferase (AST) and tumor diameter) were combined to construct the DLRCR model. The DLRCR model presented the best performance over any model, yielding an AUC, an accuracy, a sensitivity, a specificity of 0.917, 0.886, 0.889, and 0.882 in the training cohort and of 0.844, 0.818, 0.800, and 0.846 in the validation cohort, respectively. The DLRCR model achieved better clinical utility compared to the clinical staging systems and prognostic indexes.ConclusionBoth radiomics and DL models derived from CEMRI can predict HCC recurrence, and DL and radiomics-based integrated approach can provide a more effective tool for the precise prediction of ER for HCC patients undergoing resection.

ObjectiveTo investigate the value of the combined application of intravoxel incoherent motion (IVIM) and enhanced T2*-weighted angiography (ESWAN) for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).Materials and methods76 patients with pathologically confirmed HCC were retrospectively enrolled and divided into the MVI-positive group (n=26) and MVI-negative group (n=50). Conventional MRI, IVIM, and ESWAN sequences were performed. Three region of interests (ROIs) were placed on the maximum axial slice of the lesion on D, D*, and f maps derived from IVIM sequence, and R2* map derived from ESWAN sequence, and intratumoral susceptibility signal (ITSS) from the phase map derived from ESWAN sequence was also automatically measured. Receiver operating characteristic (ROC) curves were drawn to evaluate the ability for predicting MVI. Univariate and multivariate logistic regression were used to screen independent risk predictors in clinical and imaging information. The Delong’s test was used to compare the differences between the area under curves (AUCs).ResultsThe D and D* values of MVI-negative group were significantly higher than those of MVI-positive group (P=0.038, and P=0.023), which in MVI-negative group were 0.892×10-3 (0.760×10-3, 1.303×10-3) mm2/s and 0.055 (0.025, 0.100) mm2/s, and in MVI-positive group were 0.591×10-3 (0.372×10-3, 0.824×10-3) mm2/s and 0.028 (0.006, 0.050)mm2/s, respectively. The R2* and ITSS values of MVI-negative group were significantly lower than those of MVI-positive group (P=0.034, and P=0.005), which in MVI-negative group were 29.290 (23.117, 35.228) Hz and 0.146 (0.086, 0.236), and in MVI-positive group were 43.696 (34.914, 58.083) Hz and 0.199 (0.155, 0.245), respectively. After univariate and multivariate analyses, only AFP (odds ratio, 0.183; 95% CI, 0.041–0.823; P = 0.027) was the independent risk factor for predicting the status of MVI. The AUCs of AFP, D, D*, R2*, and ITSS for prediction of MVI were 0.652, 0.739, 0.707, 0.798, and 0.657, respectively. The AUCs of IVIM (D+D*), ESWAN (R2*+ITSS), and combination (D+D*+R2*+ITSS) for predicting MVI were 0.772, 0.800, and, 0.855, respectively. When IVIM combined with ESWAN, the performance was improved with a sensitivity of 73.1% and a specificity of 92.0% (cut-off value: 0.502) and the AUC was significantly higher than AFP (P=0.001), D (P=0.038), D* (P=0.023), R2* (P=0.034), and ITSS (P=0.005).ConclusionThe IVIM and ESWAN parameters showed good efficacy in prediction of MVI in patients with HCC. The combination of IVIM and ESWAN may be useful for noninvasive prediction of MVI before clinical operation.

PurposeTo explore the consistency of FRACTURE (Fast-field-echo Resembling A CT Using Restricted Echo-spacing) MRI and X-Ray/computerized tomography (CT) in the evaluation of bone injuries in knee and ankle joints.MethodsFrom Nov. 2020 to Jul. 2023, 42 patients with knee joint or ankle joint injuries who underwent FRACTURE MRI examinations were retrospectively collected. 11 patients were examined by both X-Ray and FRACTURE examinations. 31 patients were examined by both CT and FRACTURE examinations. The fracture, osteophyte, and bone destruction of the joints were evaluated by two radiologists using X-Ray/CT and FRACTURE images, respectively. Kappa test was used for consistency analysis.ResultsThe evaluation consistency of fracture, osteophyte and bone destruction via X-Ray and FRACTURE images by radiologist 1 were 0.879, 0.867 and 0.847 respectively, and for radiologist 2 were 0.899, 0.930, and 0.879, respectively. The evaluation consistency of fracture, osteophyte and bone destruction via CT and FRACTURE images by radiologist 1 were 0.938, 0.937 and 0.868 respectively, and for radiologist 2 were 0.961, 0.930, and 0.818, respectively.ConclusionFor fracture, osteophyte, and bone destruction of knee and ankle joints. FRACTURE MRI showed a high consistency with X-Ray/CT examinations.

PurposeTo develop and validate a nomogram based on extracellular volume (ECV) fraction derived from dual-energy CT (DECT) for preoperatively predicting microsatellite instability (MSI) status in gastric cancer (GC).Materials and methodsA total of 123 patients with GCs who underwent contrast-enhanced abdominal DECT scans were retrospectively enrolled. Patients were divided into MSI (n=41) and microsatellite stability (MSS, n=82) groups according to postoperative immunohistochemistry staining, then randomly assigned to the training (n=86) and validation cohorts (n=37). We extracted clinicopathological characteristics, CT imaging features, iodine concentrations (ICs), and normalized IC values against the aorta (nICs) in three enhanced phases. The ECV fraction derived from the iodine density map at the equilibrium phase was calculated. Univariate and multivariable logistic regression analyses were used to identify independent risk predictors for MSI status. Then, a nomogram was established, and its performance was evaluated by ROC analysis and Delong test. Its calibration performance and clinical utility were assessed by calibration curve and decision curve analysis, respectively.ResultsThe ECV fraction, tumor location, and Borrmann type were independent predictors of MSI status (all P < 0.05) and were used to establish the nomogram. The nomogram yielded higher AUCs of 0.826 (0.729–0.899) and 0.833 (0.675–0.935) in training and validation cohorts than single variables (P

To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommodating the complex anatomy and significant variations, optimizing surgical approaches, reducing postoperative complications, and preserving liver function.This research presents a novel approach to automating liver segmentation by identifying seven key anatomical landmarks using portal venous phase images from contrast-enhanced magnetic resonance imaging (CE-MRI). By employing a multi-task learning framework, we synchronized the detection of these landmarks with the segmentation process, resulting in accurate and robust delineation of the Couinaud segments.To comprehensively validate our model, we included multiple patient types in our test set—those with normal livers, diffuse liver diseases, and localized liver lesions—under varied imaging conditions, including two field strengths, two devices, and two contrast agents. Our model achieved an average Dice Similarity Coefficient (DSC) of 85.29%, surpassing the next best-performing models by 3.12%.Our research presents a pioneering automated approach for segmenting Couinaud segments using CE-MRI. By correlating landmark detection with segmentation, we enhance surgical planning precision. This method promises improved clinical outcomes by accurately adapting to anatomical variability and reducing potential postoperative complications.Clinical impact: The application of this technique in clinical settings is poised to enhance the precision of liver surgical planning. This could lead to more tailored surgical interventions, minimization of operative risks, and preservation of healthy liver tissue, culminating in improved patient outcomes and potentially lowering the incidence of postoperative complications.Clinical and Translational Impact Statement: This research offers a novel automated liver segmentation technique, enhancing preoperative planning and potentially reducing complications, which may translate into better postoperative outcomes in hepatic surgery.

Abstract Background Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. Methods A total of 138 patients with HCC who received TACE were retrospectively included and randomly divided into training and validation cohorts at a ratio of 7:3. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. The inter- and intraclass correlation coefficients, the spearman’s rank correlation test, and the gradient boosting decision tree algorithm were used for radiomics feature selection. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. Results The T-PTR radiomics models performed better than the TR and PTR models, and the T-PTR (3 mm) radiomics model demonstrated preferable performance with the AUCs of 0.884 (95%CI, 0.821–0.936) and 0.911 (95%CI, 0.825–0.975) in both training and validation cohorts. The T-PTR (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were fused to construct a combined nomogram. The combined nomogram [AUC: 0.910 (95%CI, 0.854–0.958) and 0.918 (95%CI, 0.831–0.986)] outperformed the clinical-radiological model [AUC: 0.789 (95%CI, 0.709–0.863) and 0.782 (95%CI, 0.660–0.902)] in the both cohorts and achieved good calibration capability and clinical utility. Conclusions CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE.

Objective: To evaluate and compare the image quality of T2-weighted abdominal scans using a respiratory belt trigger (RBT) and frequency-modulated continuous wave (FMCW)-trigger (FT) techniques and to explore the feasibility of FT in abdominal magnetic resonance imaging (MRI).Methods: The study prospectively included 28 subjects, each undergoing abdominal scans with both RBT and FT. The analysis focused on 64 inconsistent trigger segments from the respiratory curves triggered by RBT and FMCW. Parameters such as inconsistent trigger type (ITT), number of inconsistent trigger points (ITPs), ratio of ITP (ITR), and single-segment ITR (SITR) were derived from these curves. Image quality was evaluated by two observers using subjective scoring, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The assessments classified image quality as either “good” or “poor.” Consistency in image quality assessment between observers was determined using the kappa test and intraclass correlation coefficient (ICC). The chi-square test, Student’s t-test, and the Mann–Whitney U test were employed to compare the categorical and continuous variables between the RBT and FT groups.Results: The observers showed a high level of agreement in image quality assessment. There were no significant differences in ITR, SITR, acquisition time, SNR, and CNR between the RBT and FT groups (all p > 0.05). Both subjective and objective evaluations indicated no notable difference in image quality between the two groups (p > 0.05).Conclusion: The FMCW trigger technique is a viable alternative to the traditional respiratory belt trigger in scenarios of relatively stable breathing. It offers potential benefits, such as reducing operational demands on technicians and improving MRI workflow efficiency.

ObjectiveTo examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer.MaterialsIn this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups.ResultsAPT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax).ConclusionAPTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment.

PurposeTo develop and validate multi-parametric MRI (MP-MRI)-based radiomics models for the prediction of biological characteristics in endometrial cancer (EC).MethodsA total of 292 patients with EC were divided into LVSI (n = 208), DMI (n = 292), MSI (n = 95), and Her-2 (n = 198) subsets. Total 2316 radiomics features were extracted from MP-MRI (T2WI, DWI, and ADC) images, and clinical factors (age, FIGO stage, differentiation degree, pathological type, menopausal state, and irregular vaginal bleeding) were included. Intra-class correlation coefficient (ICC), spearman’s rank correlation test, univariate logistic regression, and least absolute shrinkage and selection operator (LASSO) were used to select radiomics features; univariate and multivariate logistic regression were used to identify clinical independent risk factors. Five classifiers were applied (logistic regression, random forest, decision tree, K-nearest neighbor, and Bayes) to construct radiomics models for predicting biological characteristics. The clinical model was built based on the clinical independent risk factors. The combined model incorporating the radiomics score (radscore) and the clinical independent risk factors was constructed. The model was evaluated by ROC curve, calibration curve (H-L test), and decision curve analysis (DCA).ResultsIn the training cohort, the RF radiomics model performed best among the five classifiers for the three subsets (MSI, LVSI, and DMI) according to AUC values (AUCMSI: 0.844; AUCLVSI: 0.952; AUCDMI: 0.840) except for Her-2 subset (Decision tree: AUC=0.714), and the combined model had higher AUC than the clinical model in each subset (MSI: AUCcombined =0.907, AUCclinical =0.755; LVSI: AUCcombined =0.959, AUCclinical =0.835; DMI: AUCcombined = 0.883, AUCclinical =0.796; Her-2: AUCcombined =0.812, AUCclinical =0.717; all P

PurposeTo assess the usefulness of amide proton transfer-weighted (APTw) imaging in the differentiation of parotid gland tumors.Materials and methodsPatients with parotid gland tumors who underwent APTw imaging were retrospectively enrolled and divided into groups according to pathology. Two radiologists evaluated the APTw image quality independently, and APTw images with quality score ≥3 were enrolled. The maximum and average values of APTw imaging for tumor lesions (APTmax and APTmean) were measured. The differences in APTmax and APTmean were compared between malignant tumors (MTs) and benign tumors (BTs), as well as between MTs and pleomorphic adenomas (PAs) and between MTs and Warthin tumors (WTs). Independent-samples t-test, Kruskal–Wallis H test, and receiver operating characteristic (ROC) curve analyses were used for statistical analysis.ResultsSeventy-three patients were included for image quality evaluation. In this study, 32/73 and 29/73 parotid tumors were scored as 4 and 3, respectively. After excluding lesions with quality score ≤2 (12/73), the APTmean and APTmax of MTs were 4.15% ± 1.33% and 7.43% ± 1.61%, higher than those of BTs 2.74% ± 1.04% and 5.25% ± 1.54%, respectively (p < 0.05). The areas under the ROC curve (AUCs) of the APTmean and APTmax for differentiation between MTs and BTs were 0.819 and 0.821, respectively. MTs indicated significantly higher APTmean and APTmax values than those of PAs (p < 0.05) and WTs (p < 0.05). The AUCs of the APTmean and APTmax for differentiation between MTs and PAs were 0.830 and 0.815 and between MTs and WTs were 0.847 and 0.920, respectively.ConclusionMost APTw images for parotid tumors had acceptable image quality for APTw value evaluation. Both APTmax and APTmean can be used to differentiate MTs from BTs and to differentiate MTs from subtype parotid gland tumors.

Abstract Background Lactic acid bacteria (LAB) participating in milk fermentation naturally release and enrich the fermented dairy product with a broad range of bioactive metabolites, which has numerous roles in the intestinal health-promoting of the consumer. However, information is lacking regarding the application prospect of LAB fermented milk in the animal industry. This study investigated the effects of lactic acid bacteria-fermented formula milk (LFM) on the growth performance, intestinal immunity, microbiota composition, and transcriptomic responses in weaned piglets. A total of 24 male weaned piglets were randomly divided into the control (CON) and LFM groups. Each group consisted of 6 replicates (cages) with 2 piglets per cage. Each piglet in the LFM group were supplemented with 80 mL LFM three times a day, while the CON group was treated with the same amount of drinking water. Results LFM significantly increased the average daily gain of piglets over the entire 14 d (P

As an important part of the power system, it is necessary to ensure the safe and stable operation of transmission lines. Due to long-term exposure to the outdoors, the lines face many insecurity factors, and foreign object intrusion is one of them. Traditional foreign object (bird’s nest, kite, balloon, trash bag) detection algorithms suffer from low efficiency, poor accuracy, and small coverage, etc. To address the above problems, this paper introduces the RCDAM-Net. In order to prevent feature loss or useful feature compression, the RevCol (Reversible Column Networks) is used as the backbone network to ensure that the total information remains unchanged during feature decoupling. DySnakeConv (Dynamic Snake Convolution) is adopted and embedded into the C2f structure, which is named C2D and integrates low-level features and high-level features. Compared to the original BottleNeck structure of C2f, the DySnakeConv enhances the feature extraction ability for elongated and weak targets. In addition, MPDIoU (Maximum Performance Diagonal Intersection over Union) is used to improve the regression performance of model bounding boxes, solving the problem of predicted bounding boxes having the same aspect ratio as true bounding boxes, but with different values. Further, we adopt Decoupled Head for detection and add additional auxiliary training heads to improve the detection accuracy of the model. The experimental results show that the model achieves mAP50, Precision, and Recall of 97.98%, 98.15%, and 95.16% on the transmission tower line foreign object dataset, which is better to existing multi-target detection algorithms.

Purpose: To assess the value of multimodal MRI, including amide proton transfer-weighted imaging (APT), diffusion kurtosis imaging (DKI), and T2 mapping sequences for estimating human epidermal growth factor receptor-2 (Her-2) expression in patients with endometrial cancer (EC). Methods: A total of 54 patients with EC who underwent multimodal pelvic MRI followed by biopsy were retrospectively selected and divided into the Her-2 positive (n = 24) and Her-2 negative (n = 30) groups. Her-2 expression was confirmed by immunohistochemistry (IHC). Two observers measured APT, mean kurtosis (MK), mean diffusivity (MD), and T2 values for EC lesions. Results: The Her-2 (+) group showed higher APT values and lower MD and T2 values than the Her-2 (−) group (all p < 0.05); there was no significant difference in MK values (p > 0.05). The area under the receiver operating characteristic curve (AUC) of APT, MD, T2, APT + T2, APT + MD, T2 + MD, and APT + MD + T2 models to identify the two groups of cases were 0.824, 0.695, 0.721, 0.824, 0.858, 0.782, and 0.860, respectively, and the diagnostic efficacy after combined APT + MD + T2 value was significantly higher than those of MD and T2 values individually (p = 0.018, 0.028); the diagnostic efficacy of the combination of APT + T2 values was significantly higher than that of T2 values separately (p = 0.028). Weak negative correlations were observed between APT and T2 values (r = −0.365, p = 0.007), moderate negative correlations between APT and MD values (r = −0.560, p < 0.001), and weak positive correlations between MD and T2 values (r = 0.336, p = 0.013). The APT values were independent predictors for assessing Her-2 expression in EC patients. Conclusion: The APT, DKI, and T2 mapping sequences can be used to preoperatively assess the Her-2 expression in EC, which can contribute to more precise treatment for clinical preoperative.

Abstract Background Biliary adenofibroma (BAF) is a rare primary hepatic tumor with the potential risk of malignant transformation. Given the extreme rarity of the disease, the imaging features of BAF are unclear. We presented a case of malignant BAF and conducted a systematic literature review. We highlighted the key imaging features in the diagnosis and aggressiveness assessment of BAF, as well as the role of various imaging modalities in evaluating BAF. Case presentation We reported a 64-year-old woman with a 5-months history of pain in the right upper quadrant abdomen. US of the liver showed a hypoechoic subcapsular nodule. CT scan revealed a subcapsular solid-cystic mass in segment V of the liver. The mass showed a marked enhancement in the arterial phase followed by wash-out in the venous phase. The patient underwent partial resection of liver’s right lobe. The mass was diagnosed as BAF with malignant transformation by postoperative pathology. Conclusions CT and MRI are helpful in recognizing and characterizing BAF. The imaging features of BAF include a solitary, large solid-cystic mass with a well-defined margin, lobulated shape, and internal septa; subcapsular location; no intrahepatic bile duct communication; the presence of von Meyenberg complexes in background liver. The enhancement patterns may have the potential to assess the aggressiveness of BAF, and that marked enhancement in the arterial phase followed by wash-out in the venous phase is suggestive of malignant BAF.