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ENSO-driven rainfall patterns are set to change as the climate warms. A moisture budget decomposition of simulations from 18 climate models reveals the mechanisms driving the shift in rainfall variability from western to central Pacific. El Niño/Southern Oscillation (ENSO) is a mode of natural variability that has considerable impacts on global climate and ecosystems 1 , 2 , 3 , 4 , through rainfall variability in the tropical Pacific and atmospheric teleconnections 5 . In response to global warming, ENSO-driven rainfall variability is projected to intensify over the central-eastern Pacific but weaken over the western Pacific, whereas ENSO-related sea surface temperature variability is projected to decrease 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 . Here, we explore the mechanisms that lead to changes in ENSO-driven rainfall variability in the tropical Pacific in response to global warming, with the help of a moisture budget decomposition for simulations from eighteen state-of-the-art climate models 15 . We identify two opposing mechanisms that approximately offset each other: the increase in mean-state moisture content associated with surface warming strengthens ENSO-related rainfall anomalies 7 , whereas the projected reduction in ENSO-related variability of sea surface temperatures suppresses rainfall. Two additional effects—spatially non-uniform changes in background sea surface temperatures and structural changes in sea surface temperature related to ENSO—both enhance central-eastern Pacific rainfall variability while dampening variability in the western Pacific, in nearly equal amounts. Our decomposition method may be generalized to investigate how rainfall variability would change owing to nonlinear interactions between background sea surface temperatures and their variability.

Taxol®, an antitumor drug with significant activity, is the first microtubule stabilizing agent described in the literature. This short review of the mechanism of action of Taxol® emphasizes the research done in the Horwitz’ laboratory. It discusses the contribution of photoaffinity labeled analogues of Taxol® toward our understanding of the binding site of the drug on the microtubule. The importance of hydrogen/deuterium exchange experiments to further our insights into the stabilization of microtubules by Taxol® is addressed. The development of drug resistance, a major problem that arises in the clinic, is discussed. Studies describing differential drug binding to distinct β-tubulin isotypes are presented. Looking forward, it is suggested that the β-tubulin isotype content of a tumor may influence its responses to Taxol®.

The El Niño/Southern Oscillation (ENSO) has a profound influence on global climate and ecosystems. Determining how the ENSO responds to greenhouse warming is a crucial issue in climate science. Despite recent progress in understanding, the responses of important ENSO characteristics, such as air temperature and atmospheric circulation, are still unknown. Here, we use a suite of global climate model projections to show that greenhouse warming drives a robust intensification of ENSO-driven variability in boreal winter tropical upper tropospheric temperature and geopotential height, tropical humidity, subtropical jets and tropical Pacific rainfall. These robust changes are primarily due to the Clausius–Clapeyron relationship, whereby saturation vapour pressure increases nearly exponentially with increasing temperature. Therefore, the vapour response to temperature variability is larger under a warmer climate. As a result, under global warming, even if the ENSO’s sea surface temperature remains unchanged, the response of tropical lower tropospheric humidity to the ENSO amplifies, which in turn results in major reorganization of atmospheric temperature, circulation and rainfall. These findings provide a novel theoretical constraint for ENSO changes and reduce uncertainty in the ENSO response to greenhouse warming. Greenhouse gas-induced warming intensifies atmospheric variability associated with the El Niño/Southern Oscillation, according to an analysis of global climate model projections.

An excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSO SST variability among the models. The ENSO SST bias lowers the models’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension of ENSO SST in 25 CMIP5 and 25 CMIP6 models. Based on the intermodel spread of ENSO SST variability simulated in the 50 models, we reveal that this ENSO SST bias among the models largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue from CMIP5 to CMIP6, the excessive westward extension bias of ENSO SST in CMIP6 models is also reduced relative to those in CMIP5 models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which improves ENSO simulation.

The response of tropical precipitation to global warming varies spatially and the factors controlling the spatial patterns of precipitation changes are unclear. An analysis of climate model simulations shows that warm regions are projected to become wetter in annual mean, whereas seasonally high rainfall anomalies are expected in regions that are currently wet. Tropical convection is an important factor in regional climate variability and change around the globe 1 , 2 . The response of regional precipitation to global warming is spatially variable, and state-of-the-art model projections suffer large uncertainties in the geographic distribution of precipitation changes 3 , 4 , 5 . Two views exist regarding tropical rainfall change: one predicts increased rainfall in presently rainy regions (wet-get-wetter) 6 , 7 , 8 , and the other suggests increased rainfall where the rise in sea surface temperature exceeds the mean surface warming in the tropics (warmer-get-wetter) 9 , 10 , 11 , 12 . Here we analyse simulations with 18 models from the Coupled Model Intercomparison Project (CMIP5), and present a unifying view for seasonal rainfall change. We find that the pattern of ocean warming induces ascending atmospheric flow at the Equator and subsidence on the flanks, anchoring a band of annual mean rainfall increase near the Equator that reflects the warmer-get-wetter view. However, this climatological ascending motion marches back and forth across the Equator with the Sun, pumping moisture upwards from the boundary layer and causing seasonal rainfall anomalies to follow a wet-get-wetter pattern. The seasonal mean rainfall, which is the sum of the annual mean and seasonal anomalies, thus combines the wet-get-wetter and warmer-get-wetter trends. Given that precipitation climatology is well observed whereas the pattern of ocean surface warming is poorly constrained 13 , 14 , our results suggest that projections of tropical seasonal mean rainfall are more reliable than the annual mean.

Data factors have become an essential factor of production in today’s digital era, and provided renewed energy for China’s green and high-quality development. This study analyses the impact of data factor-driven industries on green total factor productivity (GTFP) and the underlying mechanisms using panel data of 277 Chinese cities from 2008 to 2020. The results show that: First, the urban data factor-driven industry can enhance GTFP. Second, the data factor-driven industry can increase the input–output ratio and enhance GTFP by promoting AI technological innovation and AI technological entrepreneurship. Third, the heterogeneity analysis show that in regions with high levels of digital technological innovation, the market size of data factor-driven industries is larger and the effect of data factor-driven industries in enhancing GTFP is more significant. And in regions with low levels of savings, the data factor-driven industry has limited capital availability and is more efficient in using capital, which has a stronger effect on GTFP enhancement. This study provides valuable empirical evidence on the relationship between data factor-driven industries and urban GTFP, and important policy implications for fully leveraging the green economic effects of data factors, and promoting green and high-quality urban development.

• Some medicinal plants of the Solanaceae produce pharmaceutical tropane alkaloids (TAs), such as hyoscyamine and scopolamine. Littorine is a key biosynthetic intermediate in the hyoscyamine and scopolamine biosynthetic pathways. However, the mechanism underlying littorine formation from the precursors phenyllactate and tropine is not completely understood. • Here, we report the elucidation of littorine biosynthesis through a functional genomics approach and functional identification of two novel biosynthesis genes that encode phenyllactate UDP-glycosyltransferase (UGT1) and littorine synthase (LS). • UGT1 and LS are highly and specifically expressed in Atropa belladonna secondary roots. Suppression of either UGT1 or LS disrupted the biosynthesis of littorine and its TA derivatives (hyoscyamine and scopolamine). Purified His-tagged UGT1 catalysed phenyllactate glycosylation to form phenyllactylglucose. UGT1 and LS co-expression in tobacco leaves led to littorine synthesis if tropine and phenyllactate were added. • This identification ofUGT1and LS provides the missing link in littorine biosynthesis. The results pave the way for producing hyoscyamine and scopolamine for medical use by metabolic engineering or synthetic biology.

We conducted a systematic literature review to obtain risk population-based fungal disease incidence or prevalence data from China. Data were categorized by risk factors and extrapolated by using most recent demographic figures. A total of 71,316,101 cases (5.0% of the population) were attributed to 12 risk factors and 17 fungal diseases. Excluding recurrent Candida vaginitis (4,057/100,000 women) and onychomycosis (2,600/100,000 persons), aspergillosis (317/100,000 persons) was the most common problem; prevalence exceeded that in most other countries. Cryptococcal meningitis, an opportunistic infection, occurs in immunocompetent persons almost twice as often as AIDS. The pattern of fungal infections also varies geographically; Talaromyces marneffei is distributed mainly in the Pearl River Basin, and the Yangtze River bears the greatest histoplasmosis burden. New host populations, new endemic patterns, and high fungal burdens in China, which caused a huge impact on public health, underscore the urgent need for building diagnostic and therapeutic capacity.

Selective detection of signal over noise is essential to measurement and signal processing. Time-frequency filtering has been the standard approach for the optimal detection of non-stationary signals. However, there is a fundamental tradeoff between the signal detection efficiency and the amount of undesirable noise detected simultaneously, which restricts its uses under weak signal yet strong noise conditions. Here, we demonstrate quantum parametric mode sorting based on nonlinear optics at the edge of phase matching to improve the tradeoff. By tailoring the nonlinear process in a commercial lithium-niobate waveguide through optical arbitrary waveform generation, we demonstrate highly selective detection of picosecond signals overlapping temporally and spectrally but in orthogonal time-frequency modes as well as against broadband noise, with performance well exceeding the theoretical limit of the optimized time-frequency filtering. We also verify that our device does not introduce any significant quantum noise to the detected signal and demonstrate faithful detection of pico-second single photons. Together, these results point to unexplored opportunities in measurement and signal processing under challenging conditions, such as photon-starving quantum applications.

Fires in South America have profound effects on climate change and air quality. Although anthropogenic forcing has exacerbated drought and fire risks, the fire emissions and aerosol pollution in the southern Amazon and the Pantanal region showed a consistent long-term decrease during the dry season (August–October) between 2003 and 2019. Here, we find that the decreasing trend in fire emissions, mainly located in the non-deforested region, was associated with climatic conditions unfavorable for intensifying and spreading fires, including increased humidity and slower surface wind speed. These climatic trends can be attributed to weakening of the positive phase of the Atlantic Multidecadal Oscillation, which has strengthened the northeast trade winds within the region (3°S–13°N) and the northwest winds east of the Andes that transport more moisture into the southern Amazon and the Pantanal region. Our findings show the mitigating effects of weakening of the positive Atlantic Multidecadal Oscillation phase on human-induced intensification of fire risks in South America and warn of potentially increased risks of fires and aerosol pollution under intensified anthropogenic forcing in the future. Fire emissions in South America consistently decreased in 2003–2019, although anthropogenic forcing could exacerbate drought and fire risks. Here the authors find that the decreasing fires were associated with climatic conditions unfavorable for intensifying and spreading fires, led by the phase transition of the Atlantic Multidecadal Oscillation.