scispace - formally typeset
Search or ask a question
Institution

Tongji University

EducationShanghai, China
About: Tongji University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Population & Adsorption. The organization has 76116 authors who have published 81176 publications receiving 1248911 citations. The organization is also known as: Tongji & Tóngjì Dàxué.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, a comprehensive review is presented on the researches and developments related to electrospun polymer nanofibers including processing, structure and property characterization, applications, and modeling and simulations.

6,987 citations

Journal ArticleDOI
Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (695)
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

5,187 citations

Journal ArticleDOI
TL;DR: It is suggested that erlotinib is important for first-line treatment of patients with advanced EGFR mutation-positive NSCLC, and was associated with more favourable tolerability than standard chemotherapy.
Abstract: Summary Background Activating mutations in EGFR are important markers of response to tyrosine kinase inhibitor (TKI) therapy in non-small-cell lung cancer (NSCLC). The OPTIMAL study compared efficacy and tolerability of the TKI erlotinib versus standard chemotherapy in the first-line treatment of patients with advanced EGFR mutation-positive NSCLC. Methods We undertook an open-label, randomised, phase 3 trial at 22 centres in China. Patients older than 18 years with histologically confirmed stage IIIB or IV NSCLC and a confirmed activating mutation of EGFR (exon 19 deletion or exon 21 L858R point mutation) received either oral erlotinib (150 mg/day) until disease progression or unacceptable toxic effects, or up to four cycles of gemcitabine plus carboplatin. Patients were randomly assigned (1:1) with a minimisation procedure and were stratified according to EGFR mutation type, histological subtype (adenocarcinoma vs non-adenocarcinoma), and smoking status. The primary outcome was progression-free survival, analysed in patients with confirmed disease who received at least one dose of study treatment. The trial is registered at ClinicalTrials.gov, number NCT00874419, and has completed enrolment; patients are still in follow-up. Findings 83 patients were randomly assigned to receive erlotinib and 82 to receive gemcitabine plus carboplatin; 82 in the erlotinib group and 72 in the chemotherapy group were included in analysis of the primary endpoint. Median progression-free survival was significantly longer in erlotinib-treated patients than in those on chemotherapy (13.1 [95% CI 10.58–16.53] vs 4.6 [4.21–5.42] months; hazard ratio 0.16, 95% CI 0.10–0.26; p vs no patients with either event on erlotinib); the most common grade 3 or 4 toxic effects with erlotinib were increased alanine aminotransferase concentrations (three [4%] of 83 patients) and skin rash (two [2%] patients). Chemotherapy was also associated with increased treatment-related serious adverse events (ten [14%] of 72 patients [decreased platelet count, n=8; decreased neutrophil count, n=1; hepatic dysfunction, n=1] vs two [2%] of 83 patients [both hepatic dysfunction]). Interpretation Compared with standard chemotherapy, erlotinib conferred a significant progression-free survival benefit in patients with advanced EGFR mutation-positive NSCLC and was associated with more favourable tolerability. These findings suggest that erlotinib is important for first-line treatment of patients with advanced EGFR mutation-positive NSCLC. Funding F Hoffmann-La Roche Ltd (China); Science and Technology Commission of Shanghai Municipality.

3,657 citations

Journal ArticleDOI
TL;DR: Tumor Immune Estimation Resource (TIMER) is presented to comprehensively investigate molecular characterization of tumor-immune interactions and provides a user-friendly web interface for dynamic analysis and visualization of these associations, which will be of broad utilities to cancer researchers.
Abstract: Recent clinical successes of cancer immunotherapy necessitate the investigation of the interaction between malignant cells and the host immune system. However, elucidation of complex tumor-immune interactions presents major computational and experimental challenges. Here, we present Tumor Immune Estimation Resource (TIMER; cistrome.shinyapps.io/timer) to comprehensively investigate molecular characterization of tumor-immune interactions. Levels of six tumor-infiltrating immune subsets are precalculated for 10,897 tumors from 32 cancer types. TIMER provides 6 major analytic modules that allow users to interactively explore the associations between immune infiltrates and a wide spectrum of factors, including gene expression, clinical outcomes, somatic mutations, and somatic copy number alterations. TIMER provides a user-friendly web interface for dynamic analysis and visualization of these associations, which will be of broad utilities to cancer researchers. Cancer Res; 77(21); e108-10. ©2017 AACR.

3,236 citations

Journal ArticleDOI
TL;DR: Osimertinib showed efficacy superior to that of standard EGFR‐TKIs in the first‐line treatment of EGFR mutation–positive advanced NSCLC, with a similar safety profile and lower rates of serious adverse events.
Abstract: BackgroundOsimertinib is an oral, third-generation, irreversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) that selectively inhibits both EGFR-TKI–sensitizing and EGFR T790M resistance mutations. We compared osimertinib with standard EGFR-TKIs in patients with previously untreated, EGFR mutation–positive advanced non–small-cell lung cancer (NSCLC). MethodsIn this double-blind, phase 3 trial, we randomly assigned 556 patients with previously untreated, EGFR mutation–positive (exon 19 deletion or L858R) advanced NSCLC in a 1:1 ratio to receive either osimertinib (at a dose of 80 mg once daily) or a standard EGFR-TKI (gefitinib at a dose of 250 mg once daily or erlotinib at a dose of 150 mg once daily). The primary end point was investigator-assessed progression-free survival. ResultsThe median progression-free survival was significantly longer with osimertinib than with standard EGFR-TKIs (18.9 months vs. 10.2 months; hazard ratio for disease progression or death, 0.46; 95% confi...

3,074 citations


Authors

Showing all 76610 results

NameH-indexPapersCitations
Gang Chen1673372149819
Yang Yang1642704144071
Georgios B. Giannakis137132173517
Jian Li133286387131
Jianlin Shi12785954862
Zhenyu Zhang118116764887
Ju Li10962346004
Peng Wang108167254529
Qian Wang108214865557
Yan Zhang107241057758
Richard B. Kaner10655766862
Han-Qing Yu10571839735
Wei Zhang104291164923
Fabio Marchesoni10460774687
Feng Li10499560692
Network Information
Related Institutions (5)
Shanghai Jiao Tong University
184.6K papers, 3.4M citations

95% related

Zhejiang University
183.2K papers, 3.4M citations

94% related

Nanjing University
105.5K papers, 2.2M citations

93% related

Peking University
181K papers, 4.1M citations

92% related

Fudan University
117.9K papers, 2.6M citations

92% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023238
20221,051
20219,713
20208,502
20197,517
20186,352