Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
4,877
result(s) for
"Li, Lihua"
Sort by:
Structure of graphene and its disorders: a review
Monolayer graphene exhibits extraordinary properties owing to the unique, regular arrangement of atoms in it. However, graphene is usually modified for specific applications, which introduces disorder. This article presents details of graphene structure, including sp
2
hybridization, critical parameters of the unit cell, formation of σ and π bonds, electronic band structure, edge orientations, and the number and stacking order of graphene layers. We also discuss topics related to the creation and configuration of disorders in graphene, such as corrugations, topological defects, vacancies, adatoms and sp
3
-defects. The effects of these disorders on the electrical, thermal, chemical and mechanical properties of graphene are analyzed subsequently. Finally, we review previous work on the modulation of structural defects in graphene for specific applications.
Journal Article
Radiogenomic signatures reveal multiscale intratumour heterogeneity associated with biological functions and survival in breast cancer
Advanced tumours are often heterogeneous, consisting of subclones with various genetic alterations and functional roles. The precise molecular features that characterize the contributions of multiscale intratumour heterogeneity to malignant progression, metastasis, and poor survival are largely unknown. Here, we address these challenges in breast cancer by defining the landscape of heterogeneous tumour subclones and their biological functions using radiogenomic signatures. Molecular heterogeneity is identified by a fully unsupervised deconvolution of gene expression data. Relative prevalence of two subclones associated with cell cycle and primary immunodeficiency pathways identifies patients with significantly different survival outcomes. Radiogenomic signatures of imaging scale heterogeneity are extracted and used to classify patients into groups with distinct subclone compositions. Prognostic value is confirmed by survival analysis accounting for clinical variables. These findings provide insight into how a radiogenomic analysis can identify the biological activities of specific subclones that predict prognosis in a noninvasive and clinically relevant manner.
Tumours are made up of heterogeneous subclones. Here, the authors show using breast cancer imaging and gene expression datasets that these subclones can be inferred by the deconvolution of gene expression data, mapped to MRI derived radiogenomic signatures and used to estimate prognosis.
Journal Article
Clinical significance of PCT, CRP, IL-6, NLR, and TyG Index in early diagnosis and severity assessment of acute pancreatitis: A retrospective analysis
To evaluate the clinical utility of PCT, CRP, IL-6, NLR, and TyG index in improving the early diagnosis and severity assessment of acute pancreatitis (AP). This retrospective study included 137 AP patients and 30 healthy controls from Hunan Provincial People’s Hospital (January 2021–September 2023). Univariate and multivariate logistic regression analyses assessed the associations between biomarkers and severe acute pancreatitis (SAP). Receiver operating characteristic (ROC) curves, DeLong test, and Bonferroni correction were used to evaluate predictive performance. Model robustness was validated via 5-fold cross-validation. PCT, CRP, IL-6, NLR, and TyG index levels were significantly elevated in AP patients compared to controls (
P
< 0.001) and correlated with disease severity (
P
< 0.05). CRP and NLR levels differed significantly among mild, moderate, and severe AP (
P
< 0.01). Alcohol consumption and hyperlipidemia were significantly linked to AP severity (P for trend < 0.0001). Multivariate analysis identified hyperlipidemia (OR = 3.030,
P
= 0.040), CRP (OR = 1.011,
P
< 0.001), and NLR (OR = 1.078,
P
= 0.020) as independent SAP predictors. The combined model of CRP + NLR + TyG achieved the highest AUC (0.882, sensitivity = 77.2%, specificity = 88.5%), though it was not significantly better than CRP + NLR or CRP + TyG models (
P
> 0.05). 5-fold cross-validation confirmed consistent performance (mean AUC = 0.817 ± 0.118). PCT, CRP, IL-6, NLR, and TyG index are valuable in diagnosing and assessing AP prognosis. Hyperlipidemia, CRP, and NLR are reliable independent predictors of SAP. Combining multiple biomarkers enhances diagnostic precision and provides guidance for personalized treatment strategies in AP.
Journal Article
Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer
The purpose of this study was to investigate the role of features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical information to predict the molecular subtypes of breast cancer. In particular, 60 breast cancers with the following four molecular subtypes were analyzed: luminal A, luminal B, human epidermal growth factor receptor-2 (HER2)-over-expressing and basal-like. The breast region was segmented and the suspicious tumor was depicted on sequentially scanned MR images from each case. In total, 90 features were obtained, including 88 imaging features related to morphology and texture as well as dynamic features from tumor and background parenchymal enhancement (BPE) and 2 clinical information-based parameters, namely, age and menopausal status. An evolutionary algorithm was used to select an optimal subset of features for classification. Using these features, we trained a multi-class logistic regression classifier that calculated the area under the receiver operating characteristic curve (AUC). The results of a prediction model using 24 selected features showed high overall classification performance, with an AUC value of 0.869. The predictive model discriminated among the luminal A, luminal B, HER2 and basal-like subtypes, with AUC values of 0.867, 0.786, 0.888 and 0.923, respectively. An additional independent dataset with 36 patients was utilized to validate the results. A similar classification analysis of the validation dataset showed an AUC of 0.872 using 15 image features, 10 of which were identical to those from the first cohort. We identified clinical information and 3D imaging features from DCE-MRI as candidate biomarkers for discriminating among four molecular subtypes of breast cancer.
Journal Article
Morphological analysis of tumor microenvironment in HER2-positive breast cancer: predicting response to neoadjuvant chemotherapy on histopathological images
Background
HER2-positive breast cancer (HER2 + BC) is clinically distinct from other subtypes, such as triple-negative or hormone receptor–positive breast cancers, due to its unique tumor microenvironment (TME) and its heterogeneous response to neoadjuvant chemotherapy (NAC). Given the critical role of the TME in treatment outcomes, we investigated whether TME features extracted from histopathological images can predict pathological complete response (pCR) and guide personalized therapy.
Methods
We retrospectively analyzed 147 HER2 + BC patients treated with NAC, including 85 from the Yale Response dataset (training cohort) and 62 from the IMPRESS HER2+ dataset (external validation cohort). Hematoxylin and eosin-stained histopathology images were segmented using VGG-16 and Xception networks to generate tissue segmentation images (TS-images). Based on the TS-images, tumor and stroma regions were segmented. Intratumoral and stromal tumor-infiltrating lymphocytes (iTILs and sTILs, respectively) were extracted from these regions and then combined to form TILs. The morphological features of these regions were quantitatively characterized using connected component analysis. Feature selection was performed by integrating morphological and clinical data via the least absolute shrinkage and selection operator. The selected features were then used to train a multilayer perceptron model, which was validated on the IMPRESS HER2+ dataset.
Results
In external validation, the model based on sTILs achieved an AUC of 0.873 for pCR prediction, with an F1 score of 0.889, PPV of 0.821, recall of 0.970, and NPV of 0.933. This performance substantially outperformed models trained on stroma (AUC = 0.779), tumor (0.732), iTILs (0.594), and TILs (0.668). Notably, the sTILs-based model maintained high performance (AUC = 0.722) even when trained with 20% of the training cohort. Univariate analyses identified morphological predictors for pCR, including the filled area of significant regions (mean) in sTILs (
P
value = 0.015).
Conclusion
Morphological TME features from histopathological images can accurately predict pCR in HER2 + BC, supporting their use in guiding NAC decision-making.
Journal Article
Exploring the relationship between regional tourism development and land use efficiency: A case study of Guangxi Zhuang Autonomous Region, China
The utilization efficiency of land resources is an essential embodiment of economic development, social development, and ecological development and is a critical core to measure how to maximize the efficiency of land resources under limited conditions. The land is an important content and essential carrier of the research of tourism development level. This paper selects Panel Data from 2010 to 2019 to research the Guangxi regional tourism development. The entropy weight method and stochastic frontier production function (SFA) model were used to evaluate the development level of urban-rural tourism and the utilization efficiency of land resources in Guangxi. This paper uses the Panel Vector Autoregression (PVAR) model to analyze the internal relationship between urban-rural tourism development. The results show that: (1) Guangxi has a good level of tourism development and a high land use efficiency. (2) There is a reciprocal causation relationship between the regional tourism development level and land use efficiency in Guangxi, with significant levels of 0.005 and 0.034 respectively, indicating high credibility. This indicates that there is a mutual promotion and interaction between the two, which rely on and drive each other, promoting the joint sustainability of tourism development and land use efficiency. (3) . The tourism development level is greatly influenced by itself, with impact values all above 0.99. At the same time, land use also has a significant self-impact, with impact values all above 0.87. Their internal optimization system is solid and endogenous impetus is robust, which can drive their development. Establishing an effective strategy for developing and protecting land use is beneficial to promote the long-term effectiveness of sustainable tourism development, enhancing high-quality development of the tourism economy and improving people’s living standards and quality.
Journal Article
Association between minerals intake and childhood obesity: A cross-sectional study of the NHANES database in 2007–2014
The roles of minerals in obesity received increasing attention recently due to its oxidant or antioxidant functions and effects on insulin and glucose metabolism that may be associated with obesity. Herein, this study aims to explore the association between minerals and obesity and body mass index (BMI) in children with different ages, and hope to provide some references for prevention and management in children with high-risk of obesity.
Data of children aged 2-17 years old were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2007-2014 in this cross-sectional study. Weighted univariate and multivariate logistic regression and liner regression analyses were used to screen covariates, and explore the association between minerals [including calcium (Ca), phosphorus (P), magnesium (Mg), iron (Fe), zinc (Zn), copper (Cu), sodium (Na), potassium (K) and selenium (Se)] and childhood obesity and BMI. The evaluation indexes were β, odds ratios (ORs) and 95% confidence intervals (CIs). These relationships were also investigated in age subgroups.
Among 10,450 eligible children, 1,988 (19.02%) had obesity. After adjusting for covariates, we found the highest quartile of dietary Fe [OR = 0.74, 95%CI: (0.58, 0.95)] and Zn [OR = 0.70, 95%CI: (0.54, 0.92)] intakes were associated with low odds of childhood obesity, while that of dietary Na intake seemed to be positively linked to childhood obesity [OR = 1.35, 95%CI: (1.05, 1.74)]. High dietary intakes of Ca, Na and K were positively associated with children's BMI, on the contrary, dietary Fe and Zn consumptions had a negative one (all P<0.05). Additionally, these associations were also found in children with different age (all P<0.05).
Dietary Fe and Zn intakes played positive roles in reducing childhood obesity or BMI, while the intakes of Na should be controlled suitably.
Journal Article
Role of PI3K in the Progression and Regression of Atherosclerosis
Phosphatidylinositol 3 kinase (PI3K) is a key molecule in the initiation of signal transduction pathways after the binding of extracellular signals to cell surface receptors. An intracellular kinase, PI3K activates multiple intracellular signaling pathways that affect cell growth, proliferation, migration, secretion, differentiation, transcription and translation. Dysregulation of PI3K activity, and as aberrant PI3K signaling, lead to a broad range of human diseases, such as cancer, immune disorders, diabetes, and cardiovascular diseases. A growing number of studies have shown that PI3K and its signaling pathways play key roles in the pathophysiological process of atherosclerosis. Furthermore, drugs targeting PI3K and its related signaling pathways are promising treatments for atherosclerosis. Therefore, we have reviewed how PI3K, an important regulatory factor, mediates the development of atherosclerosis and how targeting PI3K can be used to prevent and treat atherosclerosis.
Journal Article
The Many Faces of Daoism: Modern Reception and Scholarly Perspectives
Over the last two centuries, “Daoism” has been discovered anew, interpreted in new ways, translated, and even reinvented in very different cultural and intellectual settings [...]
Journal Article