Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.

BACKGROUND: Accurate determination of human epidermal growth factor receptor 2 (HER2) is important for choosing optimal HER2 targeting treatment strategies. HER2-low is currently considered HER2-negative, but patients may be eligible to receive new anti-HER2 drug conjugates. PURPOSE: To use breast MRI BI-RADS features for classifying three HER2 levels, first to distinguish HER2-zero from HER2-low/positive (Task-1), and then to distinguish HER2-low from HER2-positive (Task-2). STUDY TYPE: Retrospective. POPULATION: 621 invasive ductal cancer, 245 HER2-zero, 191 HER2-low, and 185 HER2-positive. For Task-1, 488 cases for training and 133 for testing. For Task-2, 294 cases for training and 82 for testing. FIELD STRENGTH/SEQUENCE: 3.0 T; 3D T1-weighted DCE, short time inversion recovery T2, and single-shot EPI DWI. ASSESSMENT: Pathological information and BI-RADS features were compared. Random Forest was used to select MRI features, and then four machine learning (ML) algorithms: decision tree (DT), support vector machine (SVM), k-nearest neighbors (k-NN), and artificial neural nets (ANN), were applied to build models. STATISTICAL TESTS: Chi-square test, one-way analysis of variance, and Kruskal-Wallis test were performed. The P values <0.05 were considered statistically significant. For ML models, the generated probability was used to construct the ROC curves. RESULTS: Peritumoral edema, the presence of multiple lesions and non-mass enhancement (NME) showed significant differences. For distinguishing HER2-zero from non-zero (low + positive), multiple lesions, edema, margin, and tumor size were selected, and the k-NN model achieved the highest AUC of 0.86 in the training set and 0.79 in the testing set. For differentiating HER2-low from HER2-positive, multiple lesions, edema, and margin were selected, and the DT model achieved the highest AUC of 0.79 in the training set and 0.69 in the testing set. DATA CONCLUSION: BI-RADS features read by radiologists from preoperative MRI can be analyzed using more sophisticated feature selection and ML algorithms to build models for the classification of HER2 status and identify HER2-low. TECHNICAL EFFICACY: Stage 2.

Breast lesions on MRI in mass and non-mass enhancement: Kaiser score and modified Kaiser score + for readers of variable experience.

OBJECTIVES: To compare the diagnostic performance of three readers using BI-RADS and Kaiser score (KS) based on mass and non-mass enhancement (NME) lesions. METHODS: A total of 630 lesions, 393 malignant and 237 benign, 458 mass and 172 NME, were analyzed. Three radiologists with 3 years, 6 years, and 13 years of experience made diagnoses. 596 cases had diffusion-weighted imaging, and the apparent diffusion coefficient (ADC) was measured. For lesions with ADC > 1.4 × 10-3 mm2/s, the KS was reduced by 4 as the modified KS +, and the benefit was assessed. RESULTS: When using BI-RADS, AUC was 0.878, 0.915, and 0.941 for mass, and 0.771, 0.838, 0.902 for NME for Reader-1, 2, and 3, respectively, better for mass than for NME. The diagnostic accuracy of KS was improved compared to BI-RADS for less experienced readers. For Reader-1, AUC was increased from 0.878 to 0.916 for mass (p = 0.005) and from 0.771 to 0.822 for NME (p = 0.124). Based on the cut-off value of BI-RADS ≥ 4B and KS ≥ 5 as malignant, the sensitivity of KS by Readers-1 and -2 was significantly higher for both Mass and NME. When ADC was considered to change to modified KS +, the AUC and the accuracy for all three readers were improved, showing higher specificity with slightly degraded sensitivity. CONCLUSION: The benefit of KS compared to BI-RADS was most noticeable for the less experienced readers in improving sensitivity. Compared to KS, KS + can improve specificity for all three readers. For NME, the KS and KS + criteria need to be further improved. CLINICAL RELEVANCE STATEMENT: KS provides an intuitive method for diagnosing lesions on breast MRI. BI-RADS and KS face greater difficulties in evaluating NME compared to mass lesions. Adding ADC to the KS can improve specificity with slightly degraded sensitivity. KEY POINTS: KS provides an intuitive method for interpreting breast lesions on MRI, most helpful for novice readers. KS, compared to BI-RADS, improved sensitivity in both mass and NME groups for less experienced readers. NME lesions were considered during the development of the KS flowchart, but may need to be better defined.

Indoxyl sulphate-TNFα axis mediates uremic encephalopathy in rodent acute kidney injury.

Acute kidney injury (AKI) is often accompanied by uremic encephalopathy resulting from accumulation of uremic toxins in brain possibly due to impaired blood-brain barrier (BBB) function. Anionic uremic toxins are substrates or inhibitors of organic anionic transporters (OATs). In this study we investigated the CNS behaviors and expression/function of BBB OAT3 in AKI rats and mice, which received intraperitoneal injection of cisplatin 8 and 20 mg/kg, respectively. We showed that cisplatin treatment significantly inhibited the expressions of OAT3, synaptophysin and microtubule-associated protein 2 (MAP2), impaired locomotor and exploration activities, and increased accumulation of uremic toxins in the brain of AKI rats and mice. In vitro studies showed that uremic toxins neither alter OAT3 expression in human cerebral microvascular endothelial cells, nor synaptophysin and MAP2 expressions in human neuroblastoma (SH-SY5Y) cells. In contrast, tumour necrosis factor alpha (TNFα) and the conditioned medium (CM) from RAW264.7 cells treated with indoxyl sulfate (IS) significantly impaired OAT3 expression. TNFα and CM from IS-treated BV-2 cells also inhibited synaptophysin and MAP2 expressions in SH-SY5Y cells. The alterations caused by TNFα and CMs in vitro, and by AKI and TNFα in vivo were abolished by infliximab, a monoclonal antibody designed to intercept and neutralize TNFα, suggesting that AKI impaired the expressions of OAT3, synaptophysin and MAP2 in the brain via IS-induced TNFα release from macrophages or microglia (termed as IS-TNFα axis). Treatment of mice with TNFα (0.5 mg·kg-1·d-1, i.p. for 3 days) significantly increased p-p65 expression and reduced the expressions of Nrf2 and HO-1. Inhibiting NF-κB pathway, silencing p65, or activating Nrf2 and HO-1 obviously attenuated TNFα-induced downregulation of OAT3, synaptophysin and MAP2 expressions. Significantly increased p-p65 and decreased Nrf2 and HO-1 protein levels were also detected in brain of AKI mice and rats. We conclude that AKI inhibits the expressions of OAT3, synaptophysin and MAP2 due to IS-induced TNFα release from macrophages or microglia. TNFα impairs the expressions of OAT3, synaptophysin and MAP2 partly via activating NF-κB pathway and inhibiting Nrf2-HO-1 pathway.

Radiomics analysis for the prediction of locoregional recurrence of locally advanced oropharyngeal cancer and hypopharyngeal cancer.

PURPOSE: By radiomic analysis of the postcontrast CT images, this study aimed to predict locoregional recurrence (LR) of locally advanced oropharyngeal cancer (OPC) and hypopharyngeal cancer (HPC). METHODS: A total of 192 patients with stage III-IV OPC or HPC from two independent cohort were randomly split into a training cohort with 153 cases and a testing cohort with 39 cases. Only primary tumor mass was manually segmented. Radiomic features were extracted using PyRadiomics, and then the support vector machine was used to build the radiomic model with fivefold cross-validation process in the training data set. For each case, a radiomics score was generated to indicate the probability of LR. RESULTS: There were 94 patients with LR assigned in the progression group and 98 patients without LR assigned in the stable group. There was no significant difference of TNM staging, treatment strategies and common risk factors between these two groups. For the training data set, the radiomics model to predict LR showed 83.7% accuracy and 0.832 (95% CI 0.72, 0.87) area under the ROC curve (AUC). For the test data set, the accuracy and AUC slightly declined to 79.5% and 0.770 (95% CI 0.64, 0.80), respectively. The sensitivity/specificity of training and test data set for LR prediction were 77.6%/89.6%, and 66.7%/90.5%, respectively. CONCLUSIONS: The image-based radiomic approach could provide a reliable LR prediction model in locally advanced OPC and HPC. Early identification of those prone to post-treatment recurrence would be helpful for appropriate adjustments to treatment strategies and post-treatment surveillance.

Prediction of poor outcome in stroke patients using radiomics analysis of intraparenchymal and intraventricular hemorrhage and clinical factors.

PURPOSE: To build three prognostic models using radiomics analysis of the hemorrhagic lesions, clinical variables, and their combination, to predict the outcome of stroke patients with spontaneous intracerebral hemorrhage (sICH). MATERIALS AND METHODS: Eighty-three sICH patients were included. Among them, 40 patients (48.2%) had poor prognosis with modified Rankin scale (mRS) of 5 and 6 at discharge, and the prognostic model was built to differentiate mRS ≤ 4 vs. 5 + 6. The region of interest (ROI) of intraparenchymal hemorrhage (IPH) and intraventricular hemorrhage (IVH) were separately segmented. Features were extracted using PyRadiomics, and the support vector machine was applied to select features and build radiomics models based on IPH and IPH + IVH. The clinical models were built using multivariate logistic regression, and then the radiomics scores were combined with clinical variables to build the combined model. RESULTS: When using IPH, the AUC for radiomics, clinical, and combined model was 0.78, 0.82, and 0.87, respectively. When using IPH + IVH, the AUC was increased to 0.80, 0.84, and 0.90, respectively. The combined model had a significantly improved AUC compared to the radiomics by DeLong test. A clinical prognostic model based on the ICH score of 0-1 only achieved AUC of 0.71. CONCLUSIONS: The combined model using the radiomics score derived from IPH + IVH and the clinical factors could achieve a high accuracy in prediction of sICH patients with poor outcome, which may be used to assist in making the decision about the optimal care.

Endometrial microstimulation effects on endometrial receptivity assessed by transvaginal color Doppler sonography.

OBJECTIVE: This study investigated the effect of endometrial microstimulation (EM) on endometrial receptivity using transvaginal color Doppler sonography (TVCDS). METHOD: Women of childbearing age who were preparing to conceive (n = 90) were randomly divided into the EM group (n = 30), who were examined by EM on days 3-5 of the menstrual cycle, and the control group (n = 60). TVCDS was conducted during the implantation window phase, and endometrial thickness, endometrial pattern, endometrial movement, blood flow type, and uterine and spiral arterial hemodynamic parameter measurements were made. The groups were compared to identify differences. RESULTS: Endometrial thickness (0.97 ± 0.18 cm and 0.95 ± 0.17 cm), endometrial movement (type 1: 46.7% and 51.7%; type 2: 30.0% and 28.3%; type 3: 6.7% and 5.0%; type 5: 16.7% and 15.0%), and hemodynamic parameters of the uterine (pulsatility index [PI]: 2.46 ± 0.50 and 2.41 ± 0.48; resistance index [RI]: 0.85 ± 0.05 and 0.84 ± 0.05) and spiral (PI: 1.11 ± 0.32 and 1.19 ± 0.33; RI: 0.48 ± 0.11 and 0.51 ± 0.08) arteries did not differ significantly between groups (P > 0.05). However, the endometrial pattern (a trilaminar pattern: 80.0% and 58.3%; P = 0.041) and blood flow type (type I: 16.7% and 43.3%; type II: 63.3% and 40.0%; type III 20.0% and 16.7%; P = 0.038) differed significantly between groups. CONCLUSION: Endometrial microstimulation did not alter endometrial pathological staging, endometrial thickness, or movement, nor did it affect uterine and spiral arterial blood flow parameters. However, it may be able to abrade abnormal endometrial tissue, optimizing the endometrial pattern. Endometrial microstimulation may support local spiral artery regeneration and increase endometrial blood supply in new cycles.

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system. METHODS: A total of 190 patients, 50 with malignant and 140 with benign fractures, were studied. The visual diagnosis was made by one senior MSK radiologist, one fourth-year resident, and one first-year resident. The MSK radiologist also gave the binary score for 15 qualitative imaging features. Deep learning was implemented using ResNet50, using one abnormal spinal segment selected from each patient as input. The T1W and T2W images of the lesion slice and its two neighboring slices were considered. The diagnostic performance was evaluated using tenfold cross-validation. RESULTS: The overall reading accuracy was 98, 96, and 66% for the senior MSK radiologist, fourth-year resident, and first-year resident, respectively. Of the 15 imaging features, 10 showed a significant difference between benign and malignant groups with p < = 0.001. The accuracy achieved by using the ResNet50 deep learning model for the identified abnormal vertebral segment was 92%. Compared to the first-year resident's reading, the model improved the sensitivity from 78 to 94% (p < 0.001) and the specificity from 61 to 91% (p < 0.001). CONCLUSION: Our deep learning-based model may provide information to assist less experienced clinicians in the diagnosis of spinal fractures on MRI. Other findings away from the vertebral body need to be considered to improve the model, and further investigation is required to generalize our findings to real-world settings.

The role of microglia mediated pyroptosis in neonatal hypoxic-ischemic brain damage.

Neonatal hypoxic-ischemic encephalopathy (HIE) often leads to neonatal death or severe, irreversible neurological deficits. Pathologically, the occurrence of massive cell death and subsequent inflammation suggested that pyroptosis, an inflammation associated programed cell death, might play a role in HIE. Here, by measuring changes of key molecules in pyroptosis pathway in HIE patients, we discovered that their elevation levels tightly correlate with the severity of HIE. Next, we demonstrated that application of MCC950, a small molecule to inhibit NLRP3 inflammasome and thus pyroptosis, substantially alleviated pyroptosis and the injury severity in rats with neonatal hypoxic-ischemic brain damage (HIBD). Mechanistically, we showed that NLRP-3/caspase-1/GSDMD axis is required for microglia pyroptosis and activation. Our data demonstrated that microglia mediated pyroptosis played a crucial role in neonatal HIE, which shed lights into the development of intervention avenues targeting pyroptosis to treat HIE and traumatic brain injuries.

Renewed classification within Goniurosaurus (Squamata: Eublepharidae) uncovers the dual roles of a continental island (Hainan) in species evolution.

Continental islands are often dynamic in regard to the origin and evolution of their biota. Although colonizations from mainland Southeast Asia to Hainan Island have been reported, the role of Hainan Island as a source for continental biota has not been considered. Goniurosaurus is a genus comprised of nocturnal ground geckos. We reexamined the evolutionary history of Goniurosaurus using both molecular phylogenetics and morphological comparisons. All phylogenetic trees recovered G. zhoui as sister to G. hainanensis + G. lichtenfelderi, which together are the sister lineage of G. bawanglingensis. The recovery of this "Hainan clade" contradicts previous classifications that placed G. bawanglingensis within the G. luii group. Moreover, ancestral trait reconstruction revealed that body band number might have decreased two or three times independently within Goniurosaurus from four to three. The divergence between the continental G. luii group and the Hainan clade was estimated at ∼34.7 Mya (CI = 22.3-48.6), possibly correlating with the vicariance event between Hainan Island and the mainland. G. lichtenfelderi diverged from G. hainanensis very recently, which might be associated with a historical dispersal event from Hainan Island to Vietnam during glacial periods. Our study improves the understanding of Goniurosaurus systematics and reveals the important role of Hainan Island in bidirectional colonizations.

In vivo phosphoproteome characterization reveals key starch granule-binding phosphoproteins involved in wheat water-deficit response.

BACKGROUND: Drought stress during grain development causes significant yield loss in cereal production. The phosphorylated modification of starch granule-binding proteins (SGBPs) is an important mechanism regulating wheat starch biosynthesis. In this study, we performed the first proteomics and phosphoproteomics analyses of SGBPs in elite Chinese bread wheat (Triticum aestivum L.) cultivar Jingdong 17 under well-watered and water-stress conditions. RESULTS: Water stress treatment caused significant reductions in spike grain numbers and weight, total starch and amylopectin content, and grain yield. Two-dimensional gel electrophoresis revealed that the quantity of SGBPs was reduced significantly by water-deficit treatment. Phosphoproteome characterization of SGBPs under water-deficit treatment demonstrated a reduced level of phosphorylation of main starch synthesis enzymes, particularly for granule-bound starch synthase (GBSS I), starch synthase II-a (SS II-a), and starch synthase III (SS III). Specifically, the Ser34 site of the GBSSI protein, the Tyr358 site of SS II-a, and the Ser837 site of SS III-a exhibited significant less phosphorylation under water-deficit treatment than well-watered treatment. Furthermore, the expression levels of several key genes related with starch biosynthesis detected by qRT-PCR were decreased significantly at 15 days post-anthesis under water-deficit treatment. Immunolocalization showed a clear movement of GBSS I from the periphery to the interior of starch granules during grain development, under both water-deficit and well-watered conditions. CONCLUSIONS: Our results demonstrated that the reduction in gene expression or transcription level, protein expression and phosphorylation levels of starch biosynthesis related enzymes under water-deficit conditions is responsible for the significant decrease in total starch content and grain yield.

Real-Time Intracellular Measurements of ROS and RNS in Living Cells with Single Core-Shell Nanowire Electrodes.

Nanoelectrodes allow precise and quantitative measurements of important biological processes at the single living-cell level in real time. Cylindrical nanowire electrodes (NWEs) required for intracellular measurements create a great challenge for achieving excellent electrochemical and mechanical performances. Herein, we present a facile and robust solution to this problem based on a unique SiC-core-shell design to produce cylindrical NWEs with superior mechanical toughness provided by the SiC nano-core and an excellent electrochemical performance provided by the ultrathin carbon shell that can be used as such or platinized. The use of such NWEs for biological applications is illustrated by the first quantitative measurements of ROS/RNS in individual phagolysosomes of living macrophages. As the shell material can be varied to meet any specific detection purpose, this work opens up new opportunities to monitor quantitatively biological functions occurring inside cells and their organelles.

Trends in prevalence and risk factors of childhood asthma in Fuzhou, a city in Southeastern China.

UNLABELLED: Abstract Objective: The prevalence of asthma in children age 0-14 years in Fuzhou, a city in Southeast China, was 1.57% in 1990 and 3.28% in 2000. The aim of this study was to investigate the asthma prevalence and risk factors in children in the same city in 2010. METHODS: This was a cross-sectional study with a two-stage, clustered, stratified random sample design. Parents of 12235 children 0-14 years of age in Fuzhou were surveyed using a questionnaire. Children with history and/or symptoms of asthma were then interviewed by pediatricians in a nearby clinic to confirm the diagnosis of asthma, and a second questionnaire listing reported risk factors of asthma was completed by the parents in the clinic. RESULTS: About 11738 questionnaires were completed with a response rate of 95.9%. Among the responders, 648 children had history and/or symptoms of asthma but only 485 (4.13%) were confirmed with asthma. The prevalence was 1.83%, 7.64% and 6.27% in the age groups of 0-1 years, 3-4 years and 13-14 years, respectively. The most significant (binary logistic regression test) factors associated with asthma were presence of atopic or allergic diseases (OR=21.5, 95% CI: 12-38.5), family history of allergy or asthma (OR=29.4, 95% CI: 12.6-68.6), use of at least one course of antibiotics in the first year of life (OR=7.61, 95% CI: 3.4-17.06), supplementary protein feedings before 6 months (OR=1.90, 95% CI: 1.23-2.95). Natural ventilation at home (versus frequent use of air-conditioning) appeared to be a protective factor (OR = 0.5, 95% CI: 0.3-0.8). CONCLUSION: The prevalence of asthma in childhood has increased significantly during the past 20 years in Fuzhou.

MRI-Based Machine Learning for Prediction of Clinical Outcomes in Primary Central Nervous System Lymphoma.

A portion of individuals diagnosed with primary central nervous system lymphomas (PCNSL) may experience early relapse or refractory (R/R) disease following treatment. This research explored the potential of MRI-based radiomics in forecasting R/R cases in PCNSL. Forty-six patients with pathologically confirmed PCNSL diagnosed between January 2008 and December 2020 were included in this study. Only patients who underwent pretreatment brain MRIs and complete postoperative follow-up MRIs were included. Pretreatment contrast-enhanced T1WI, T2WI, and T2 FLAIR imaging were analyzed. A total of 107 radiomic features, including 14 shape-based, 18 first-order statistical, and 75 texture features, were extracted from each sequence. Predictive models were then built using five different machine learning algorithms to predict R/R in PCNSL. Of the included 46 PCNSL patients, 20 (20/46, 43.5%) patients were found to have R/R. In the R/R group, the median scores in predictive models such as support vector machine, k-nearest neighbors, linear discriminant analysis, naïve Bayes, and decision trees were significantly higher, while the apparent diffusion coefficient values were notably lower compared to those without R/R (p < 0.05). The support vector machine model exhibited the highest performance, achieving an overall prediction accuracy of 83%, a precision rate of 80%, and an AUC of 0.78. Additionally, when analyzing tumor progression, patients with elevated support vector machine and naïve Bayes scores demonstrated a significantly reduced progression-free survival (p < 0.05). These findings suggest that preoperative MRI-based radiomics may provide critical insights for treatment strategies in PCNSL.

Early oral-motor management on feeding performance in premature neonates.

BACKGROUND/PURPOSE: Poor oral-motor developments in premature infants are common. From the viewpoint of developmental care, most of the infants required individualized therapy. The specific aim of our study was to evaluate the effectiveness and impact of early intervention of oral-motor management on feeding pattern and the neonatal outcomes in premature neonates. METHODS: The study enrolled 68 preterm infants with birth weight less than 1500 g or gestational age less than 32 weeks. We tried to strengthen the sucking ability of infants with poor oral-motor coordination. RESULTS: There were significant differences in the body weight (g) while feeding up to 45 mL (1916 ± 156 vs. 2003 ± 191 g, p = 0.002) and hospital stay (46.3 ± 25.3 vs. 54.7 ± 23.5 days, p = 0.003) between the study and control groups. CONCLUSION: Abnormal brain sonography [odds ratio (OR): 2.222, p = 0.047) and necrotizing enterocolitis (NEC) (OR: 2.857, p = 0.017) did affect the first trial in the study group. Early intervention of oral-motor management in very-low-birth-weight premature infants improved feeding performance and neonatal outcome in terms of shorter hospital days. Abnormal brain image and NEC could interfere with the success rate of initial challenge of transitioning from tube to oral feeding in the study group.

Microbial diversity on grape epidermis and wine volatile aroma in spontaneous fermentation comprehensively driven by geography, subregion, and variety.

On their journey from the wine grape to the resulting wine, microbiota from grape surfaces controlled by multiple factors is transferred to wine spontaneous fermentation process with indisputable consequences for wine quality parameters. The associated microbiota was regionally distinct (defined to microbial terroir) but how these microbial patterns with significantly regional distinctiveness quantitatively drive the wine regional characteristics are not definite within a complete grape ecosystem at different geographical (> 300 km), subregional (< 10 km), and varietal scales. Here, we collected 24 samples (containing two grape varieties) from four subregions of two regions in Xinjiang wine production area to investigate fungal distribution patterns and the association with wine chemical composition at different evaluation scales. Meanwhile, the relationships were established between geographical, subregional, varietal community of fungi, and wine volatile aroma using partial least squares regression (PLSR) and structural equation modeling (SEM). Results show that microbial and volatile samples present the significantly regional difference inside the complete ecosystem. Microbiota showed a stronger heterogeneity at geography scales, which drove the distributions of subregional and varietal microbiota thereby influencing the volatile composition of finished wines. Moreover, geographical microbiota seems to weaken the effects of varietal community on wine aroma compounds. Microbial communities respond to environmental changes within a completely set grape-related ecosystem at different scales, and these responses resulted in the wine regional distinctiveness based on the volatile profiles. Our findings further confirmed the important role of microbial terroir in shaping wine styles and provided the new cerebration for the terroir drivers of microbiota.

Efficacy and safety of low-dose sacubitril/valsartan in heart failure patients: A systematic review and meta-analysis.

BACKGROUND: Controversy has persisted over the clinical benefits of low-dose sacubitril/valsartan in patients with heart failure (HF). HYPOTHESIS: Low-dose sacubitril/valsartan might also be effective and safe in HF patients. METHODS: Electronic databases including PubMed, Ovid, and Cochrane Library were systematically retrieved from inception to August 5, 2021. Review manager 5.4 and Stata 15.1 were employed in this systematic review and meta-analysis. Key efficacy outcomes of interest included HF hospitalization, all-cause mortality, left ventricular ejection fraction (LVEF), N-terminal pro-B-type natriuretic peptide (NT-proBNP), together with New York Heart Association (NYHA) functional class. The safety outcome was systolic blood pressure (SBP). The grading of recommendations assessment, development, and evaluation approach was conducted to evaluate the quality of evidence for each outcome. RESULTS: A total of 1269 studies were screened and 9 real-world studies met the inclusion criteria were included in the meta-analysis, with 1697 participants. Compared with low-dose sacubitril/valsartan, high-dose sacubitril/valsartan significantly reduced the risk of HF hospitalization (odds ratio [OR]: 0.4, 95% confidence interval [CI]: 0.27-0.61, p < .0001) and the risk of all-cause mortality (OR: 0.23, 95% CI: 0.11-0.47, p < .0001). However, there were no appreciable differences in improvements of NYHA (OR: 0.59, 95% CI: 0.15-2.35, p = .45), changes of LVEF (mean difference [MD]: 2.73%, 95% CI: -2.24% to 7.7%, p = .28), changes of NT-proBNP (MD: 43.09, 95% CI: -28.41 to 114.59, p = .24) and changes of SBP (MD: 3.01, 95% CI: -4.62 to 10.64, p = .44) between groups with low-dose and high-dose sacubitril/valsartan. CONCLUSIONS: Compared with high-dose sacubitril/valsartan, low-dose sacubitril/valsartan was associated with increased risks of HF hospitalization and all-cause mortality. However, no distinct between-group differences in improvements of NYHA, changes of LVEF, changes of NT-proBNP and changes of SBP were observed.

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics.

Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted in radiologists' visual evaluation. More sophisticated computer algorithms are needed to extract the higher-order information. The purpose of this study was to apply a new deep learning algorithm, the bi-directional convolutional long short-term memory (CLSTM) network, and the radiomics analysis for differential diagnosis of PCa and benign prostatic hyperplasia (BPH). To systematically investigate the optimal amount of peritumoral tissue for improving diagnosis, a total of 9 ROIs were delineated by using 3 different methods. The results showed that bi-directional CLSTM with ± 20% region growing peritumoral ROI achieved the mean AUC of 0.89, better than the mean AUC of 0.84 by using the tumor alone without any peritumoral tissue (p = 0.25, not significant). For all 9 ROIs, deep learning had higher AUC than radiomics, but only reaching the significant difference for ± 20% region growing peritumoral ROI (0.89 vs. 0.79, p = 0.04). In conclusion, the kinetic information extracted from DCE-MRI using bi-directional CLSTM may provide helpful supplementary information for diagnosis of PCa.

Fungal dynamic during apricot wine spontaneous fermentation and aromatic characteristics of Pichia kudriavzevii for potential as starter.

Microbial activity during spontaneous fermentation in alcoholic beverages have driven in developing the chemical and aromatic characteristic of products but not clear in apricot wines. We have characterised the composition of fungal communities and volatile metabolites in apricot wine spontaneous fermentation among two Shaanxi regions. Results showed that Aureobasidium, Alternaria, Pichia and Saccharomyces, were the dominant fungi in apricot wine fermentation. A total of 80 volatiles including esters, alcohols, acids and terpenes were detected from two apricot wines. Their correlations suggested that apricot wine aroma was mainly affected by Pichia kudriavzevii, rather than Saccharomyces cerevisiae we commonly considered. Furthermore, reinforced inoculation of P. kudriavzevii LQD20 has exhibited the commendable potential in enhancing sensory qualities. The results of this study provide fundamental information of the indigenous microbiota in microbial dynamic during apricot wine fermentation, which would be helpful in exploiting the strains with potential for industrial use as starter cultures.

Deep Learning-based Automatic Diagnosis of Breast Cancer on MRI Using Mask R-CNN for Detection Followed by ResNet50 for Classification.

RATIONALE AND OBJECTIVES: Diagnosis of breast cancer on MRI requires, first, the identification of suspicious lesions; second, the characterization to give a diagnostic impression. We implemented Mask Reginal-Convolutional Neural Network (R-CNN) to detect abnormal lesions, followed by ResNet50 to estimate the malignancy probability. MATERIALS AND METHODS: Two datasets were used. The first set had 176 cases, 103 cancer, and 73 benign. The second set had 84 cases, 53 cancer, and 31 benign. For detection, the pre-contrast image and the subtraction images of left and right breasts were used as inputs, so the symmetry could be considered. The detected suspicious area was characterized by ResNet50, using three DCE parametric maps as inputs. The results obtained using slice-based analyses were combined to give a lesion-based diagnosis. RESULTS: In the first dataset, 101 of 103 cancers were detected by Mask R-CNN as suspicious, and 99 of 101 were correctly classified by ResNet50 as cancer, with a sensitivity of 99/103 = 96%. 48 of 73 benign lesions and 131 normal areas were identified as suspicious. Following classification by ResNet50, only 16 benign and 16 normal areas remained as malignant. The second dataset was used for independent testing. The sensitivity was 43/53 = 81%. Of the total of 121 identified non-cancerous lesions, only 6 of 31 benign lesions and 22 normal tissues were classified as malignant. CONCLUSION: ResNet50 could eliminate approximately 80% of false positives detected by Mask R-CNN. Combining Mask R-CNN and ResNet50 has the potential to develop a fully-automatic computer-aided diagnostic system for breast cancer on MRI.

Magnetic Resonance Imaging Features Associated with a High and Low Expression of Tumor-Infiltrating Lymphocytes: A Stratified Analysis According to Molecular Subtypes.

A total of 457 patients, including 241 HR+/HER2- patients, 134 HER2+ patients, and 82 TN patients, were studied. The percentage of TILs in the stroma adjacent to the tumor cells was assessed using a 10% cutoff. The low TIL percentages were 82% in the HR+ patients, 63% in the HER2+ patients, and 56% in the TN patients (p < 0.001). MRI features such as morphology as mass or non-mass enhancement (NME), shape, margin, internal enhancement, presence of peritumoral edema, and the DCE kinetic pattern were assessed. Tumor sizes were smaller in the HR+/HER2- group (p < 0.001); HER2+ was more likely to present as NME (p = 0.031); homogeneous enhancement was mostly seen in HR+ (p < 0.001); and the peritumoral edema was present in 45% HR+, 71% HER2+, and 80% TN (p < 0.001). In each subtype, the MR features between the high- vs. low-TIL groups were compared. In HR+/HER2-, peritumoral edema was more likely to be present in those with high TILs (70%) than in those with low TILs (40%, p < 0.001). In TN, those with high TILs were more likely to present a regular shape (33%) than those with low TILs (13%, p = 0.029) and more likely to present the circumscribed margin (19%) than those with low TILs (2%, p = 0.009).