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.

What are they considering when they face a fetus with birth defects? A qualitative study on ethical attitudes of health professionals in China.

BACKGROUND: Birth defects are the leading cause of mortality in newborn babies and children under five years old. In response, the Chinese government has implemented a three-tiered prevention strategy, which has brought ethical concerns about fetuses with birth defects. This study aims to explore the attitudes toward fetuses with birth defects among health professionals engaged in maternal and child health services. METHODS: A qualitative study was conducted among 13 health professionals engaged in maternal and child health services in Hunan Province, China. The questions were designed to elicit the participants' work experience and attitudes toward fetuses with birth defects. The data were collected through in-depth semi-structured interviews, and NVivo 12 was used for data coding and analysis. A thematic analysis approach was employed following the SRQR checklist. RESULTS: Five themes and 13 attributes were generated regarding health professionals' perspectives on fetuses with birth defects. The five themes included: (1) severity and curability of diseases (two attributes), (2) family relations (four attributes), (3) medical assessments (two attributes), (4) social situations (three attributes), (5) self-value orientations (three attributes). The findings showed that the majority of health professionals held the view that a fetus with a curable disease could be born, whereas a fetus with severe disability and teratogenesis should be terminated. Twelve out of the 13 health professionals believed that parents should be the decision-makers, while only one thought that the family should make a decision together. CONCLUSIONS: Attitudes toward birth defects were influenced by various factors, indicating the complexity of real-world cases identified in this study. The findings highlight the dilemmas faced by both families and health professionals regarding birth defects. Adequate medical knowledge and support from society are crucial to inform decision-making among family members. Additionally, standardized norms and policies for birth defects are needed. Establishing an ethics committee for prenatal diagnosis is necessary to address current ethical issues in this field.

Impact of must clarification treatments on chemical and sensory profiles of kiwifruit wine.

This study examined the effect of various clarification treatments on the physicochemical properties, volatile compounds, and sensory attributes of kiwi wines produced from five different kiwifruit (Actinidia deliciosa) varieties. The degree of clarification had a minimal impact on physicochemical parameters, including the content of residual sugar, ethanol, volatile acid, titratable acidity (except for the kiwifruit variety 'Qinmei'), and the pH value. However, wines made from unclarified juices (muddy juice and pulp) displayed a higher glycerol content than those made from clarified juices. The cluster heat map and principal component analyses (PCA) demonstrated that kiwi wines produced from clarified kiwi juices possessed a higher ester content, whereas muddy juice and pulp wines contained elevated levels of higher alcohols. Quantitative descriptive analysis (QDA) indicated that clarified juice wines outperformed muddy juice and pulp wines in terms of purity, typicality, harmony, intensity, and freshness, with negligible differences in terms of palate acidity. Moreover, the clarified juice wines featured more characteristic kiwi wine aromas (kiwifruit, passionfruit, and pineapple) compared with that of the muddy juice and pulp wines, which exhibited an increased grassy flavour. Although the 100-NTU kiwifruit juice-fermented wine did not show an advantage in the cluster heat map and PCA, it presented better freshness, typicality, and intensity in the QDA, as well as a more passionfruit aroma. Based on the orthogonal partial least-squares discriminant analysis, A. deliciosa 'Xuxiang' was deemed to be the most suitable variety for vinification. This study provides crucial insights for enhancing the production of high-quality kiwi wine.

Malleable, Ultrastrong Antibacterial Thermosets Enabled by Guanidine Urea Structure.

Dynamic covalent polymers (DCPs) that strike a balance between high performance and rapid reconfiguration have been a challenging task. For this purpose, a solution is proposed in the form of a new dynamic covalent supramolecular motif-guanidine urea structure (GUAs). GUAs contain complex and diverse chemical structures as well as unique bonding characteristics, allowing guanidine urea supramolecular polymers to demonstrate advanced physical properties. Noncovalent interaction aggregates (NIAs) have been confirmed to form in GUA-DCPs through multistage H-bonding and π-π stacking, resulting in an extremely high Young's modulus of 14 GPa, suggesting remarkable mechanical strength. Additionally, guanamine urea linkages in GUAs, a new type of dynamic covalent bond, provide resins with excellent malleability and reprocessability. Guanamine urea metathesis is validated using small molecule model compounds, and the temperature dependent infrared and rheological behavior of GUA-DCPs following the dissociative exchange mechanism. Moreover, the inherent photodynamic antibacterial properties are extensively verified by antibacterial experiments. Even after undergoing three reprocessing cycles, the antibacterial rate of GUA-DCPs remains above 99% after 24 h, highlighting their long-lasting antibacterial effectiveness. GUA-DCPs with dynamic nature, tuneable composition, and unique combination of properties make them promising candidates for various technological advancements.

Integration of transcriptomics, metabolomics, and hormone analysis revealed the formation of lesion spots inhibited by GA and CTK was related to cell death and disease resistance in bread wheat (Triticum aestivum L.).

BACKGROUND: Wheat is one of the important grain crops in the world. The formation of lesion spots related to cell death is involved in disease resistance, whereas the regulatory pathway of lesion spot production and resistance mechanism to pathogens in wheat is largely unknown. RESULTS: In this study, a pair of NILs (NIL-Lm5W and NIL-Lm5M) was constructed from the BC1F4 population by the wheat lesion mimic mutant MC21 and its wild genotype Chuannong 16. The formation of lesion spots in NIL-Lm5M significantly increased its resistance to stripe rust, and NIL-Lm5M showed superiour agronomic traits than NIL-Lm5W under stripe rust infection.Whereafter, the NILs were subjected to transcriptomic (stage N: no spots; stage S, only a few spots; and stage M, numerous spots), metabolomic (stage N and S), and hormone analysis (stage S), with samples taken from normal plants in the field. Transcriptomic analysis showed that the differentially expressed genes were enriched in plant-pathogen interaction, and defense-related genes were significantly upregulated following the formation of lesion spots. Metabolomic analysis showed that the differentially accumulated metabolites were enriched in energy metabolism, including amino acid metabolism, carbohydrate metabolism, and lipid metabolism. Correlation network diagrams of transcriptomic and metabolomic showed that they were both enriched in energy metabolism. Additionally, the contents of gibberellin A7, cis-Zeatin, and abscisic acid were decreased in leaves upon lesion spot formation, whereas the lesion spots in NIL-Lm5M leaves were restrained by spaying GA and cytokinin (CTK, trans-zeatin) in the field. CONCLUSION: The formation of lesion spots can result in cell death and enhance strip rust resistance by protein degradation pathway and defense-related genes overexpression in wheat. Besides, the formation of lesion spots was significantly affected by GA and CTK. Altogether, these results may contribute to the understanding of lesion spot formation in wheat and laid a foundation for regulating the resistance mechanism to stripe rust.

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.

[Retracted] LINC01094 promotes the invasion of ovarian cancer cells and regulates the Wnt/ß­catenin signaling pathway by targeting miR­532­3p.

[This retracts the article DOI: 10.3892/etm.2021.10662.].

The effect of ancillary ligands on hydrocarbon C-H bond functionalization by uranyl photocatalysts.

The aqueous uranyl dication has long been known to facilitate the UV light-induced decomposition of aqueous VOCs (volatile organic compounds), via the long-lived highly efficient, uranyl excited state. The lower-energy visible light excited uranyl ion is also able to cleave unactivated hydrocarbon C-H bonds, yet the development of this reactivity into controlled and catalytic C-H bond functionalization is still in its infancy, with almost all studies still focused on uranyl nitrate as the precatalyst. Here, hydrocarbon-soluble uranyl nitrate and chloride complexes supported by substituted phenanthroline (Ph2phen) ligands are compared to each other, and to the parent salts, as photocatalysts for the functionalization of cyclooctane by H atom abstraction. Analysis of the absorption and emission spectra, and emission lifetimes of Ph2phen-coordinated uranyl complexes demonstrate the utility of the ligand in light absorption in the photocatalysis, which is related to the energy and kinetic decay profile of the uranyl photoexcited state. Density functional theory computational analysis of the C-H activation steps in the reaction show how a set of dispersion forces between the hydrocarbon substrate and the Ph2phen ligand provide control over the H atom abstraction, and provide predictions of selectivity of H atom abstraction by the uranyl oxo of the ring C-H over the ethyl C-H in an ethylcyclohexane substrate.

The impact of technological innovation on the green digital economy and development strategies.

To investigate the interplay among technological innovation, industrial structure, production methodologies, economic growth, and environmental consequences within the paradigm of a green economy and to put forth strategies for sustainable development, this study scrutinizes the limitations inherent in conventional deep learning networks. Firstly, this study analyzes the limitations and optimization strategies of multi-layer perceptron (MLP) networks under the background of the green economy. Secondly, the MLP network model is optimized, and the dynamic analysis of the impact of technological innovation on the digital economy is discussed. Finally, the effectiveness of the optimization model is verified by experiments. Moreover, a sustainable development strategy based on dynamic analysis is also proposed. The experimental results reveal that, in comparison to traditional Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) models, the optimized model in this study demonstrates improved performance across various metrics. With a sample size of 500, the optimized model achieves a prediction accuracy of 97.2% for forecasting future trends, representing an average increase of 14.6%. Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. In the examination of changes in industrial structure using 2020 data to forecast the output value of traditional and green industries in 2030, it is observed that the output value of traditional industries is anticipated to decrease, with an average decline of 11.4 billion yuan. Conversely, propelled by the development of the digital economy, the output value of green industries is expected to increase, with an average growth of 23.4 billion yuan. This shift in industrial structure aligns with the principles and trends of the green economy, further promoting sustainable development. In the study of innovative production methods, the green industry has achieved an increase in output and significantly enhanced production efficiency, showing an average growth of 2.135 million tons compared to the average in 2020. Consequently, this study highlights the dynamic impact of technological innovation on the digital economy and its crucial role within the context of a green economy. It holds certain reference significance for research on the dynamic effects of the digital economy under technological innovation.

Foodomics uncovers functional and volatile metabolite dynamics in red raspberry chewable tablet optimized processing.

Raspberries are known to contain valuable metabolites and possess a robust antioxidant capacity. However, the impact of different tablet processing stages on the nutritional content and flavor profile of raspberries remains unclear. The dynamic profile of functional and volatile metabolites was investigated through foodomics combined with UPLC-MS/MS-based widely targeted metabolomics and HS-SPME-GC-MS, and antioxidant capacities were assessed during tablet processing. 1336 functional metabolites and 645 volatile metabolites were identified. Results indicated tablets retained 34% âˆ¼ 61% of the total volatile contents. In addition, the conversion intensity of functional metabolites was consistent with the order of "Tableting > Freeze-drying > Crushing". Compared to raspberry, tablets showed higher antioxidant activity, which was positively correlated with vitamin contents. This study elucidated that tablet formation demonstrated advantages in antioxidation and aroma retention, which may provide insights for enhancing quality during the tableting process.

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.

Microbiological impact of long-term wine grape cultivation on soil organic carbon in desert ecosystems: a study on rhizosphere and bulk sandy soils.

The improvement of nutrients in soil is essential for using deserts and decertified ecosystems and promoting sustainable agriculture. Grapevines are suitable crops for desert soils as they can adapt to harsh environments and effectively impact soil nutrients; however, the mechanisms underlying this remain unclear. This study explored the impact of the different duration(3, 6, and 10 years) of grape cultivation on soil organic carbon, physicochemical properties, enzyme activities, microbial communities, and carbon cycle pathways in both rhizosphere and bulk soils. Partial least squares path modeling was used to further reveal how these factors contributed to soil nutrient improvement. Our findings indicate that after long-term grape cultivation six years, soil organic carbon, total nitrogen, total phosphorus, microbial biomass carbon and nitrogen, and enzyme activities has significantly increased in both rhizosphere and bulk soils but microbial diversity decreased in bulk soil. According to the microbial community assembly analysis, we found that stochastic processes, particularly homogenizing dispersal, were dominant in both soils. Bacteria are more sensitive to environmental changes than fungi. In the bulk soil, long-term grape cultivation leads to a reduction in ecological niches and an increase in salinity, resulting in a decrease in soil microbial diversity. Soil enzymes play an important role in increasing soil organic matter in bulk soil by decomposing plant litters, while fungi play an important role in increasing soil organic matter in the rhizosphere, possibly by decomposing fine roots and producing mycelia. Our findings enhance understanding of the mechanisms of soil organic carbon improvement under long-term grape cultivation and suggest that grapes are suitable crops for restoring desert ecosystems.

Ion-imprinted macroporous polyethyleneimine incorporated chitosan/layered hydrotalcite foams for the selective biosorption of U(VI) ions.

In order to prevent uranium pollution and recovery uranium resources, it was necessary to find a highly efficient adsorbent for radioactive wastewater treatment. Herein, U(VI) imprinted polyethyleneimine (PEI) incorporated chitosan/layered hydrotalcite composite foam (IPCL) was synthesized by combining ion-imprinting and freeze-drying techniques. IPCL has a high amino/imino content and an ultralight macroporous structure, making it capable of efficiently adsorbing U(VI) and easy to separate; Especially after ion-imprinting, vacancies matching the size of uranyl ions were formed, significantly improving U(VI) selectivity. The adsorption isotherms and adsorption kinetics were in accordance with the Freundlich model and PSO model respectively, indicating that heterogeneous adsorption of U(VI) by the adsorbents. The adsorption capacity of IPCL-2 for U(VI) reached 278.8. mg/g (under the conditions of optimal pH 5.0, temperature of 298 K, contact time of 2 h, and adsorbent dosage of 0.2 g/L), which is almost double of that for the non-imprinted foam (PCL-2, 138.2 mg/g), indicating that IPCL-2 can intelligently recognize U(VI). The heterogeneous adsorption mechanism of U(VI) by IPCL-2 involves complexation, ion-exchange and isomorphic substitution. The adsorption of U(VI) by IPCL-2 is spontaneous and endothermic. IPCL-2 has excellent adsorption performance for U(VI), and is a promising adsorbent for radioactive pollution control.

Root microbiota of tea plants regulate nitrogen homeostasis and theanine synthesis to influence tea quality.

The flavor profile of tea is influenced not only by different tea varieties but also by the surrounding soil environment. Recent studies have indicated the regulatory role of soil microbes residing in plant roots in nutrient uptake and metabolism. However, the impact of this regulatory mechanism on tea quality remains unclear. In this study, we showed that a consortium of microbes isolated from tea roots enhanced ammonia uptake and facilitated the synthesis of theanine, a key determinant of tea taste. Variations were observed in the composition of microbial populations colonizing tea roots and the rhizosphere across different seasons and tea varieties. By comparing the root microorganisms of the high-theanine tea variety Rougui with the low-theanine variety Maoxie, we identified a specific group of microbes that potentially modulate nitrogen metabolism, subsequently influencing the theanine levels in tea. Furthermore, we constructed a synthetic microbial community (SynCom) mirroring the microbe population composition found in Rougui roots. Remarkably, applying SynCom resulted in a significant increase in the theanine content of tea plants and imparted greater tolerance to nitrogen deficiency in Arabidopsis. Our study provides compelling evidence supporting the use of root microorganisms as functional microbial fertilizers to enhance tea quality.

A co-located QTL for seven spike architecture-related traits shows promising breeding use potential in common wheat (Triticum aestivum L.).

KEY MESSAGE: A co-located novel QTL for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs with potential of improving wheat yield was identified and validated. Spike-related traits, including fertile florets per spike (FFS), kernel weight per spike (KWS), total florets per spike (TFS), florets per spikelet (FPs), florets in the middle spikelet (FMs), fertile florets per spikelet (FFPs), and kernel weight per spikelet (KWPs), are key traits in improving wheat yield. In the present study, quantitative trait loci (QTL) for these traits evaluated under various environments were detected in a recombinant inbred line population (msf/Chuannong 16) mainly genotyped using the 16 K SNP array. Ultimately, we identified 60 QTL, but only QFFS.sau-MC-1A for FFS was a major and stably expressed QTL. It was located on chromosome arm 1AS, where loci for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs were also simultaneously co-mapped. The effect of QFFS.sau-MC-1A was further validated in three independent segregating populations using a Kompetitive Allele-Specific PCR marker. For the co-located QTL, QFFS.sau-MC-1A, the presence of a positive allele from msf was associate with increases for all traits: + 12.29% TFS, + 10.15% FPs, + 13.97% FMs, + 17.12% FFS, + 14.75% FFPs, + 22.17% KWS, and + 19.42% KWPs. Furthermore, pleiotropy analysis showed that the positive allele at QFFS.sau-MC-1A simultaneously increased the spike length, spikelet number per spike, and thousand-kernel weight. QFFS.sau-MC-1A represents a novel QTL for marker-assisted selection with the potential for improving wheat yield. Four genes, TraesCS1A03G0012700, TraesCS1A03G0015700, TraesCS1A03G0016000, and TraesCS1A03G0016300, which may affect spike development, were predicted in the physical interval harboring QFFS.sau-MC-1A. Our results will help in further fine mapping QFFS.sau-MC-1A and be useful for improving wheat yield.

CropGS-Hub: a comprehensive database of genotype and phenotype resources for genomic prediction in major crops.

The explosive amount of multi-omics data has brought a paradigm shift both in academic research and further application in life science. However, managing and reusing the growing resources of genomic and phenotype data points presents considerable challenges for the research community. There is an urgent need for an integrated database that combines genome-wide association studies (GWAS) with genomic selection (GS). Here, we present CropGS-Hub, a comprehensive database comprising genotype, phenotype, and GWAS signals, as well as a one-stop platform with built-in algorithms for genomic prediction and crossing design. This database encompasses a comprehensive collection of over 224 billion genotype data and 434 thousand phenotype data generated from >30 000 individuals in 14 representative populations belonging to 7 major crop species. Moreover, the platform implemented three complete functional genomic selection related modules including phenotype prediction, user model training and crossing design, as well as a fast SNP genotyper plugin-in called SNPGT specifically built for CropGS-Hub, aiming to assist crop scientists and breeders without necessitating coding skills. CropGS-Hub can be accessed at https://iagr.genomics.cn/CropGS/.

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.

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).

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.

Daily mood and cognitive performance of women with and without bipolar disorder: role of menopausal status.

We examined the role of menopausal status in daily mood and cognitive performance among women with bipolar disorder (BD) compared to healthy comparison women. We analyzed the association of menopausal status, bipolar diagnosis, and their interaction on daily mood assessed by mobile surveys and attentional performance measured multiple times over 2 weeks. Menopausal status was associated with more daily negative affect in women with BD, but not related to attentional performance.