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"Chen, Yu"
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Srategy and performance of knowledge flow : university-industry collaborative innovation in China
This book constructs a model of the knowledge value chain in the university and analyzes the university knowledge value-added mechanism in the process of Industry-University Collaborative Innovation. The efficiency of university knowledge value-added of Provinces in China is measured. The book illustrates the operating mechanism between enterprise subsystems and college subsystems in the collaborative innovation system, and establishes a Data Envelopment Analysis (DEA) model with parallel decision making units to assess the performance of Industry-University Collaboration Innovation in China by considering the complex internal structure of the collaborative innovation system. The book also addresses various behaviors of knowledge agents in the knowledge sharing process.
Book
Mechanical stretch induces hair regeneration through the alternative activation of macrophages
Tissues and cells in organism are continuously exposed to complex mechanical cues from the environment. Mechanical stimulations affect cell proliferation, differentiation, and migration, as well as determining tissue homeostasis and repair. By using a specially designed skin-stretching device, we discover that hair stem cells proliferate in response to stretch and hair regeneration occurs only when applying proper strain for an appropriate duration. A counterbalance between WNT and BMP-2 and the subsequent two-step mechanism are identified through molecular and genetic analyses. Macrophages are first recruited by chemokines produced by stretch and polarized to M2 phenotype. Growth factors such as HGF and IGF-1, released by M2 macrophages, then activate stem cells and facilitate hair regeneration. A hierarchical control system is revealed, from mechanical and chemical signals to cell behaviors and tissue responses, elucidating avenues of regenerative medicine and disease control by demonstrating the potential to manipulate cellular processes through simple mechanical stimulation.
Mechanical stimulation is known to affect cell proliferation, differentiation, and regeneration. Here, the authors demonstrate that stretching mouse skin recruits macrophages and polarizes them into M2 cells that facilitate hair regeneration through the release of growth factors, including HGF and IGF-1
Journal Article
Lee Kuan Yew through the eyes of Chinese scholars
\"A compilation of essays by highly-respected Chinese scholars in which they evaluate the life, work and philosophy of Lee Kuan Yew, founding Prime Minister of Singapore. Presenting a range of views from a uniquely Chinese/Asian perspective, this book provides valuable insights for those who wish to gain a fuller and deeper understanding of Lee Kuan Yew, the man, as well as Singapore, his nation\"-- Provided by publisher.
Book
Combined Single‐Cell and Spatial Transcriptomics Reveal the Metabolic Evolvement of Breast Cancer during Early Dissemination
Breast cancer is now the most frequently diagnosed malignancy, and metastasis remains the leading cause of death in breast cancer. However, little is known about the dynamic changes during the evolvement of dissemination. In this study, 65 968 cells from four patients with breast cancer and paired metastatic axillary lymph nodes are profiled using single‐cell RNA sequencing (scRNA‐seq) and spatial transcriptomics. A disseminated cancer cell cluster with high levels of oxidative phosphorylation (OXPHOS), including the upregulation of cytochrome C oxidase subunit 6C and dehydrogenase/reductase 2, is identified. The transition between glycolysis and OXPHOS when dissemination initiates is noticed. Furthermore, this distinct cell cluster is distributed along the tumor's leading edge. The findings here are verified in three different cohorts of breast cancer patients and an external scRNA‐seq dataset, which includes eight patients with breast cancer and paired metastatic axillary lymph nodes. This work describes the dynamic metabolic evolvement of early disseminated breast cancer and reveals a switch between glycolysis and OXPHOS in breast cancer cells as the early event during lymph node metastasis. By single‐cell RNA sequencing and spatial transcriptomics, the early early‐disseminated breast cancer cells are found to travel from the border of primary tumor to axillary lymph nodes. During this metastasis, a switch between glycolysis and oxidative phosphorylation occurs in early disseminated breast cancer cells, indicating an interesting dynamic metabolic evolvement.
Journal Article
Weight Gain Associated with COVID-19 Lockdown in Children and Adolescents: A Systematic Review and Meta-Analysis
Background: Lockdown is an effective nonpharmaceutical intervention to reduce coronavirus disease 2019 (COVID-19) transmission, but it restricts daily activity. We aimed to investigate the impact of lockdown on pediatric body weight and body mass index (BMI). Methods: The systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement. Four online databases (EMBASE, Medline, the Cochrane Library and CINAHL) were searched. Results: The pooled results showed that lockdown was associated with significant body weight gain (MD 2.67, 95% CI 2.12–3.23; p < 0.00001). The BMI of children with comorbidities or obesity did not change significantly. The BMI of general population was significantly higher during lockdown than before the pandemic (MD 0.94, 95% CI 0.32–1.56; p = 0.003). However, heterogeneity was high (I2 = 84%). Among changes in weight classification, increases in the rates of obesity (OR 1.23, 95% CI 1.10–1.37; p = 0.0002) and overweight (OR 1.17, 95% CI 1.06–1.29; p = 0.001) were reported. Conclusions: Our meta-analysis showed significant increases in body weight and BMI during lockdown among school-age children and adolescents. The prevalence of obesity and overweight also increased. The COVID-19 pandemic worsened the burden of childhood obesity.
Journal Article
Ancient city walls in China : a heritage rediscovered
\"In numerous civilizations throughout world history city walls were an indispensable part of every city. In China they can be traced back to the 21th century BC as fortified symbols of power and manifestation of the Middle Kingdom. In the course of the country's long history several thousand have been erected, varying enormously in form, length, construction technology, functionality and significance. These city walls represent a unique heritage and a central identification factor from which to gain access to the self-image of Chinese culture. After years of decay and ignorance, it was only a few decades ago that they were discovered as cultural monuments and the securing and restoration work began. The city walls recorded in the statistics today, of which a selection is presented in this book by new and historic photos, range from wall ruins in the ground via about 150 with a length of more than one kilometer to the famous fortification of Nanjing, which still has more than 20 kilometers standing.\" -- amazon
Book
An experimental model for ovarian cancer: propagation of ovarian cancer initiating cells and generation of ovarian cancer organoids
Background
Ovarian cancer (OC) is the most lethal gynecological cancer due to the recurrence of drug-resistance. Cancer initiating cells (CICs) are proposed to be responsible for the aggressiveness of OC. The rarity and difficulty of in vitro long-term cultivation of CICs challenge the development of CIC-targeting therapeutics. Reprogramming cancer cells into induced cancer initiating cell (iCICs) could be an approach to solve these. Several inducible CICs have been acquired by activating the expression of stemness genes in different cancer cells. However, few reports have demonstrated the feasibility in OC.
Methods
Patients with primary OC receiving surgery were enrolled. Tumor tissue were collected, and OCT4, SOX2, and NANOG expressions were assessed by immunohistochemistry (IHC) staining to investigate the association of stemness markers with overall survival (OS). An high-grade serous ovarian cancer (HGSOC) cell line, OVCAR-3 was reprogrammed by transducing Yamanaka four factors
OCT4, SOX2, KLF4
and
MYC
(
OSKM
) to establish an iOCIC model, iOVCAR-3-OSKM. CIC characteristics of iOVCAR-3-OSKM were evaluated by RT-PCR, sphere formation assay and animal experiments. Drug-resistance and migration ability were accessed by dye-efflux activity assay, MTT assay and migration assay. Gene profile was presented through RNA-sequencing. Lineage differentiation ability and organoid culture were determined by in vitro differentiation assays.
Results
In OC patients, the co-expression of multiple stem-related transcription factors (
OCT4, SOX2
, and
NANOG
) was associated with worse OS. iOVCAR-3-OSKM cells generated by reprogramming successfully exhibited stemness characteristics with strong sphere-forming and tumorigenesis ability. iOVCAR-3-OSKM cells also showed malignant potential with higher drug resistance to chemodrug, Paclitaxel (PTX) and migration ability. iOVCAR-3-OSKM was maintainable and expandable on feeder-dependent culture condition, it also preserved ovarian lineage differentiation abilities, which could well differentiate into OC cells with CK-7 and CA125 expressions and develop into an organoid mimic poor prognostic OC histological feature.
Conclusions
The establishment of iOVCAR-3-OSKM not only allows us to fill the gap in the information on induced CICs in OC but also provides a potential strategy to develop personalized CICs and organoid models for treating OC in the near future.
Journal Article
An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning
Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole-slide images (WSIs). Most studies have employed patch-based methods, which often require detailed annotation of image patches. This typically involves laborious free-hand contouring on WSIs. To alleviate the burden of such contouring and obtain benefits from scaling up training with numerous WSIs, we develop a method for training neural networks on entire WSIs using only slide-level diagnoses. Our method leverages the unified memory mechanism to overcome the memory constraint of compute accelerators. Experiments conducted on a data set of 9662 lung cancer WSIs reveal that the proposed method achieves areas under the receiver operating characteristic curve of 0.9594 and 0.9414 for adenocarcinoma and squamous cell carcinoma classification on the testing set, respectively. Furthermore, the method demonstrates higher classification performance than multiple-instance learning as well as strong localization results for small lesions through class activation mapping.
Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole slide images (WSIs), which requires researchers to adopt patch-based methods and laborious free-hand contouring. Here, the authors develop a whole-slide training method to classify types of lung cancers using slide-level diagnoses with deep learning.
Journal Article