Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

Turning foes to friends: targeting cancer-associated fibroblasts

Abstract: Current paradigms of cancer-centric therapeutics are usually not sufficient to eradicate the malignancy, as the cancer stroma may prompt tumour relapse and therapeutic resistance. Among all the stromal cells that populate the tumour microenvironment, cancer-associated fibroblasts (CAFs) are the most abundant and are critically involved in cancer progression. CAFs regulate the biology of tumour cells and other stromal cells via cell–cell contact, releasing numerous regulatory factors and synthesizing and remodelling the extracellular matrix, and thus these cells affect cancer initiation and development. The recent characterization of CAFs based on specific cell surface markers not only deepens our insight into their phenotypic heterogeneity and functional diversity but also brings CAF-targeting therapies for cancer treatment onto the agenda. In this Review, we discuss the current knowledge of biological hallmarks, cellular origins, phenotypical plasticity and functional heterogeneity of CAFs and underscore their contribution to cancer progression. Moreover, we highlight relevant translational advances and potential therapeutic strategies that target CAFs for cancer treatment. Cancer-associated fibroblasts (CAFs) are often the most abundant cell type in the tumour microenvironment. Here, Song and colleagues discuss how to target or harness these cells for cancer therapy. They highlight the progress made to date and the remaining challenges in bringing CAF-targeted therapies to the clinic.

Planck 2018 results. I. Overview and the cosmological legacy of Planck

Abstract: The European Space Agency’s Planck satellite, which was dedicated to studying the early Universe and its subsequent evolution, was launched on 14 May 2009. It scanned the microwave and submillimetre sky continuously between 12 August 2009 and 23 October 2013, producing deep, high-resolution, all-sky maps in nine frequency bands from 30 to 857 GHz. This paper presents the cosmological legacy of Planck, which currently provides our strongest constraints on the parameters of the standard cosmological model and some of the tightest limits available on deviations from that model. The 6-parameter ΛCDM model continues to provide an excellent fit to the cosmic microwave background data at high and low redshift, describing the cosmological information in over a billion map pixels with just six parameters. With 18 peaks in the temperature and polarization angular power spectra constrained well, Planck measures five of the six parameters to better than 1% (simultaneously), with the best-determined parameter (θ*) now known to 0.03%. We describe the multi-component sky as seen by Planck, the success of the ΛCDM model, and the connection to lower-redshift probes of structure formation. We also give a comprehensive summary of the major changes introduced in this 2018 release. The Planck data, alone and in combination with other probes, provide stringent constraints on our models of the early Universe and the large-scale structure within which all astrophysical objects form and evolve. We discuss some lessons learned from the Planck mission, and highlight areas ripe for further experimental advances.

Effect of non-pharmaceutical interventions to contain COVID-19 in China.

Abstract: On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings3. Here, using epidemiological data on COVID-19 and anonymized data on human movement4,5, we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimate that there were a total of 114,325 cases of COVID-19 (interquartile range 76,776–164,576) in mainland China as of 29 February 2020. Without non-pharmaceutical interventions, we predict that the number of cases would have been 67-fold higher (interquartile range 44–94-fold) by 29 February 2020, and we find that the effectiveness of different interventions varied. We estimate that early detection and isolation of cases prevented more infections than did travel restrictions and contact reductions, but that a combination of non-pharmaceutical interventions achieved the strongest and most rapid effect. According to our model, the lifting of travel restrictions from 17 February 2020 does not lead to an increase in cases across China if social distancing interventions can be maintained, even at a limited level of an on average 25% reduction in contact between individuals that continues until late April. These findings improve our understanding of the effects of non-pharmaceutical interventions on COVID-19, and will inform response efforts across the world. A model of the effects of different non-pharmaceutical interventions on the spread of COVID-19 in China suggests that a strategy involving the rapid implementation of a combination of interventions is most effective.

Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus

Abstract: We performed a genome-wide association study (GWAS) of systemic lupus erythematosus (SLE) in a Chinese Han population by genotyping 1,047 cases and 1,205 controls using Illumina Human610-Quad BeadChips and replicating 78 SNPs in two additional cohorts (3,152 cases and 7,050 controls). We identified nine new susceptibility loci (ETS1, IKZF1, RASGRP3, SLC15A4, TNIP1, 7q11.23, 10q11.22, 11q23.3 and 16p11.2; 1.77 x 10(-25) < or = P(combined) < or = 2.77 x 10(-8)) and confirmed seven previously reported loci (BLK, IRF5, STAT4, TNFAIP3, TNFSF4, 6q21 and 22q11.21; 5.17 x 10(-42) < or = P(combined) < or = 5.18 x 10(-12)). Comparison with previous GWAS findings highlighted the genetic heterogeneity of SLE susceptibility between Chinese Han and European populations. This study not only advances our understanding of the genetic basis of SLE but also highlights the value of performing GWAS in diverse ancestral populations.