Long noncoding RNAs (lncRNAs) are involved in the pathology of colorectal cancer (CRC). Current efforts to eradicate CRC predominantly focused on targeting the proliferation of rapidly growing cancer ...epithelial cells. This is largely ineffective with resistance arising in most tumors after exposure to chemotherapy. Despite the long‐standing recognition of the crosstalk between carcinoma‐associated fibroblasts (CAFs) and cancer cells in the tumor microenvironment, how CAFs may contribute to drug resistance in neighboring cancer cells is not well characterized. Here, we show that lncRNA CCAL (colorectal cancer‐associated lncRNA) promotes oxaliplatin (Oxa) resistance of CRC cells. RNA‐ISH shows higher CCAL expressed in the tumor stroma compared to cancer nests of CRC tissues. Functional studies reveal that CCAL is transferred from CAFs to the cancer cells via exosomes, where it suppresses CRC cell apoptosis, confers chemoresistance and activates β‐catenin pathway in vitro and in vivo. Mechanistically, CCAL interacts directly with mRNA stabilizing protein HuR (human antigen R) to increase β‐catenin mRNA and protein levels. Our findings indicate that CCAL expressed by CAFs of the colorectal tumor stroma contributes to tumor chemoresistance and CCAL may serve as a potential therapeutic target for Oxa resistance.
What's new?
Long noncoding RNA signatures of tumor‐derived exosomes have been identified in multiple tumor types, including colorectal cancer. The expression pattern of the lncRNA CCAL in CRC and its role in exosome‐derived chemoresistance remain to be elucidated, however. Here, the authors report that CCAL is located in the tumor stroma rather than cancer nests and can be delivered from cancer‐associated fibroblasts to cancer cells via exosomes, to promote oxaliplatin resistance in vitro and in vivo. The findings highlight the crucial role of CCAL in the interaction of cancer cells with the tumor microenvironment and offer potential targets for overcoming drug resistance.
Abstract
Mitigating agricultural ammonia (NH
3
) emissions in China is urgently needed to avoid further damage to human and ecosystem health. Effective and feasible mitigation strategies hinge on ...integrated knowledge of the mitigation potential of NH
3
emissions and the associated economic costs and societal benefits. Here we present a comprehensive analysis of marginal abatement costs and societal benefits for NH
3
mitigation in China. The technical mitigation potential of agricultural NH
3
emissions is 38–67% (4.0–7.1 Tg N) with implementation costs estimated at US$ 6–11 billion. These costs are much lower than estimates of the overall societal benefits at US$ 18–42 billion. Avoiding unnecessary fertilizer use and protein-rich animal feed could provide 30% of this mitigation potential without additional abatement costs or decreases in agricultural productivity. Optimizing human diets with less animal-derived products offers further potential for NH
3
reduction of 12% by 2050.
Urban air quality in China has been declining substantially in recent years due to severe haze episodes. The reduction of sulfur dioxide (SO2) and nitrogen oxide (NOx) emissions since 2013 does not ...yet appear to yield substantial benefits for haze mitigation. As the reductions of those key precursors to secondary aerosol formation appears not to sufficient, other crucial factors need to be considered for the design of effective air pollution control strategies. Here we argue that ammonia (NH3) plays a - so far - underestimated role in the formation of secondary inorganic aerosols, a main component of urban fine particulate matter (PM2.5) concentrations in China. By analyzing in situ concentration data observed in major cities alongside gridded emission data obtained from remote sensing and inventories, we find that emissions of NH3 have a more robust association with the spatiotemporal variation of PM2.5 levels than emissions of SO2 and NOx. As a consequence, we argue that urban PM2.5 pollution in China in many locations is substantially affected by NH3 emissions. We highlight that more efforts should be directed to the reduction of NH3 emissions that help mitigate PM2.5 pollution more efficiently than other PM2.5 precursors. Such efforts will yield substantial co-benefits by improving nitrogen use efficiency in farming systems. As a consequence, such integrated strategies would not only improve urban air quality, but also contribute to China's food-security goals, prevent further biodiversity loss, reduce greenhouse gas emissions and lead to economic savings.
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•NH3 plays an underestimated role in the formation of PM2.5 in China.•More efforts should be directed to reducing NH3 emissions to mitigate PM2.5 pollution.•Reducing NH3 emissions also contributes to China's food-security goals.•Results of panel model analysis on in situ PM2.5 data agree well with global observation.
PM2.5 pollution in China is substantially affected by NH3 emissions and more efforts should be directed to reducing NH3 emissions to mitigate PM2.5 pollution more efficiently.
For realizing scalable solar hydrogen synthesis, the development of visible-light-absorbing photocatalysts capable of overall water splitting is essential. Metal sulfides can capture visible light ...efficiently; however, their utilization in water splitting has long been plagued by the poor resilience against hole oxidation. Herein, we report that the ZnIn2S4 monolayers with dual defects (Ag dopants and nanoholes) accessed via cation exchange display stoichiometric H2 and O2 evolution in pure water under visible light irradiation. In-depth characterization and modeling disclose that the dual-defect structure endows the ZnIn2S4 monolayers with optimized light absorption and carrier dynamics. More significantly, the dual defects cooperatively function as active sites for water oxidation (Ag dopants) and reduction (nanoholes), thus leading to steady performance in photocatalytic overall water splitting without the assistance of cocatalysts. This work demonstrates a feasible way for fulfilling “all-in-one” photocatalyst design and manifests its great potential in addressing the stability issues associated with sulfide-based photocatalysts.
Cropland is a main source of global nitrogen pollution
. Mitigating nitrogen pollution from global croplands is a grand challenge because of the nature of non-point-source pollution from millions of ...farms and the constraints to implementing pollution-reduction measures, such as lack of financial resources and limited nitrogen-management knowledge of farmers
. Here we synthesize 1,521 field observations worldwide and identify 11 key measures that can reduce nitrogen losses from croplands to air and water by 30-70%, while increasing crop yield and nitrogen use efficiency (NUE) by 10-30% and 10-80%, respectively. Overall, adoption of this package of measures on global croplands would allow the production of 17 ± 3 Tg (10
g) more crop nitrogen (20% increase) with 22 ± 4 Tg less nitrogen fertilizer used (21% reduction) and 26 ± 5 Tg less nitrogen pollution (32% reduction) to the environment for the considered base year of 2015. These changes could gain a global societal benefit of 476 ± 123 billion US dollars (USD) for food supply, human health, ecosystems and climate, with net mitigation costs of only 19 ± 5 billion USD, of which 15 ± 4 billion USD fertilizer saving offsets 44% of the gross mitigation cost. To mitigate nitrogen pollution from croplands in the future, innovative policies such as a nitrogen credit system (NCS) could be implemented to select, incentivize and, where necessary, subsidize the adoption of these measures.
Summary
The pandemic coronavirus SARS‐CoV‐2 in the world has caused a large infected population suffering from COVID‐19. To curb the spreading of the virus, WHO urgently demanded an extension of ...screening and testing; thus, a rapid and simple diagnostic method is needed. We applied a reverse transcription‐loop‐mediated isothermal amplification (RT‐LAMP) to achieve the detection of SARS‐CoV‐2 in 30 min. We designed four sets of LAMP primers (6 primers in each set), targeting the viral RNA of SARS‐CoV‐2 in the regions of orf1ab, S gene and N gene. A colorimetric change was used to report the results, which enables the outcome of viral RNA amplification to be read by the naked eye without the need of expensive or dedicated instrument. The sensitivity can be 80 copies of viral RNA per ml in a sample. We validated the RT‐LAMP method in a hospital in China, employing 16 clinic samples with 8 positives and 8 negatives. The testing results are consistent with the conventional RT‐qPCR. In addition, we also show that one‐step process without RNA extraction is feasible to achieve RNA amplification directly from a sample. This rapid, simple and sensitive RT‐LAMP method paves a way for a large screening at public domain and hospitals, particularly regional hospitals and medical centres in rural areas.
A rapid method for the detection of SARS‐CoV‐2 RNA virus.
Casually-taken portrait photographs often suffer from unflattering lighting and shadowing because of suboptimal conditions in the environment. Aesthetic qualities such as the position and softness of ...shadows and the lighting ratio between the bright and dark parts of the face are frequently determined by the constraints of the environment rather than by the photographer. Professionals address this issue by adding light shaping tools such as scrims, bounce cards, and flashes. In this paper, we present a computational approach that gives casual photographers some of this control, thereby allowing poorly-lit portraits to be relit post-capture in a realistic and easily-controllable way. Our approach relies on a pair of neural networks---one to remove foreign shadows cast by external objects, and another to soften facial shadows cast by the features of the subject and to add a synthetic fill light to improve the lighting ratio. To train our first network we construct a dataset of real-world portraits wherein synthetic foreign shadows are rendered onto the face, and we show that our network learns to remove those unwanted shadows. To train our second network we use a dataset of Light Stage scans of human subjects to construct input/output pairs of input images harshly lit by a small light source, and variably softened and fill-lit output images of each face. We propose a way to explicitly encode facial symmetry and show that our dataset and training procedure enable the model to generalize to images taken in the wild. Together, these networks enable the realistic and aesthetically pleasing enhancement of shadows and lights in real-world portrait images.1
The recent outbreak of betacoronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is responsible for the Coronavirus Disease 2019 (COVID-19) global pandemic, has created ...great challenges in viral diagnosis. The existing methods for nucleic acid detection are of high sensitivity and specificity, but the need for complex sample manipulation and expensive machinery slow down the disease detection. Thus, there is an urgent demand to develop a rapid, inexpensive, and sensitive diagnostic test to aid point-of-care viral detection for disease monitoring. In this study, we developed a clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated proteins (Cas) 12a-based diagnostic method that allows the results to be visualized by the naked eye. We also introduced a rapid sample processing method, and when combined with recombinase polymerase amplification (RPA), the sample to result can be achieved in 50 minutes with high sensitivity (1-10 copies per reaction). This accurate and portable detection method holds a great potential for COVID-19 control, especially in areas where specialized equipment is not available.
Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping ...(categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach.
A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as “factors.” Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2–57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics.
Analyses yielded three factors with dissociable whole-brain hypo- and hyper–RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper–RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion.
There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper–RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms—a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.
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