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As the second most predominant greenhouse gas, methane-targeted emission mitigation holds the potential to decelerate the pace of global warming. Satellite remote sensing is an important monitoring tool, and we review developments in the satellite detection of methane. This paper provides an overview of the various types of satellites, including the various instrument parameters, and describes the different types of satellite retrieval algorithms. In addition, the currently popular methane point source quantification method is presented. Based on existing research, we delineate the classification of methane remote sensing satellites into two overarching categories: area flux mappers and point source imagers. Area flux mappers primarily concentrate on the assessment of global or large-scale methane concentrations, with a further subclassification into active remote sensing satellites (e.g., MERLIN) and passive remote sensing satellites (e.g., TROPOMI, GOSAT), contingent upon the remote sensing methodology employed. Such satellites are mainly based on physical models and the carbon dioxide proxy method for the retrieval of methane. Point source imagers, in contrast, can detect methane point source plumes using their ultra-high spatial resolution. Subcategories within this classification include multispectral imagers (e.g., Sentinel-2, Landsat-8) and hyperspectral imagers (e.g., PRISMA, GF-5), contingent upon their spectral resolution disparities. Area flux mappers are mostly distinguished by their use of physical algorithms, while point source imagers are dominated by data-driven methods. Furthermore, methane plume emissions can be accurately quantified through the utilization of an integrated mass enhancement model. Finally, a prediction of the future trajectory of methane remote sensing satellites is presented, in consideration of the current landscape. This paper aims to provide basic theoretical support for subsequent scientific research.

Atmospheric Infrared Ultraspectral Sounder (AIUS) aboard the Chinese GaoFen-5 satellite was launched on 9 May 2018. It is the first hyperspectral occultation spectrometer in China. The spectral quality assessment of AIUS measurements at the full and representative spectral bands was presented by comparing the transmittance spectra of measurements with that of simulations. AIUS measurements agree well with simulations. Statistics show that more than 73% of the transmittance differences are within ±0.05 and more than 91% of the transmittance differences are within ±0.1. The spectral windows for O3, H2O, temperature, CO, CH4, and HCl were also analyzed. The comparison experiments indicate that AIUS data can provide reliable data for O3, H2O, temperature, CO, CH4, and HCl detection and dynamic monitoring. The H2O profiles were then retrieved from AIUS measurements, and the precision, resolution, and accuracy of the H2O profiles are discussed. The estimated precision is less than 1.3 ppmv (21%) below 57 km and about 0.9–2.4 ppmv (20–31%) at 60–90 km. The vertical resolution of H2O profiles is better than 5 km below 32 km and about 5–8 km at 35–85 km. Comparisons with MLS Level 2 products indicate that the mean H2O profiles of AIUS have a good agreement with those of MLS. The relative differences are mostly within ±10% at 16–75 km and about 10–15% at 16–20 km in 60∘–80∘ S. For 60∘–65 ∘ S in December, the relative differences are within ±5% between 22 km and 80 km. The H2O profiles retrieved from AIUS measurements are credible for scientific research.

The effective monitoring of methane (CH4) point sources is important for climate change research. Satellite-based observations have demonstrated significant potential for emission estimation. In this study, the methane plumes with different emission rates are modelled and pseudo-observations with diverse spatial resolution, spectral resolution, and signal-to-noise ratios (SNR) are simulated by the radiative transfer model. The iterative maximum a posteriori–differential optical absorption spectroscopy (IMAP-DOAS) algorithm is applied to retrieve the column-averaged methane dry air mole fraction (XCH4), a three-dimensional matrix of estimated plume emission rates is then constructed. The results indicate that an optimal plume estimation requires high spatial and spectral resolution alongside an adequate SNR. While a spatial resolution degradation within 120 m has little impact on quantification, a high spatial resolution is important for detecting low-emission plumes. Additionally, a fine spectral resolution (<5 nm) is more beneficial than a higher SNR for precise plume retrieval. Scientific SNR settings can also help to accurately quantify methane plumes, but there is no need to pursue an overly extreme SNR. Finally, miniaturized spectroscopic systems, such as dispersive spectrometers or Fabry–Pérot interferometers, meet current detection needs, offering a faster and resource-efficient deployment pathway. The results can provide a reference for the development of current detection instruments for methane plumes.

Atmospheric carbon dioxide (CO2) is recognized as the most important component of the greenhouse gases, the concentration of which has increased rapidly since the pre-industrial era due to anthropogenic emissions of greenhouse gases (GHG). The accurate monitoring of carbon dioxide is essential to study the global carbon cycle and radiation budget on Earth. The Aerosol and Carbon Detection Lidar (ACDL) instrument onboard the Atmospheric Environmental Monitoring Satellite (AEMS) was successfully launched in April 2022, which allows a new perspective to quantify the global spatial distribution of atmospheric CO2 with high accuracy. In this work, the impact of the Doppler shift on CO2 measurements for an integrated-path differential absorption (IPDA) light detection and ranging (lidar) system was evaluated to meet the weighted column-averaged mixing ratio of carbon dioxide (XCO2) measurement requirements of less than one part per million (ppm). The measurement uncertainties due to the Doppler shift were first evaluated in airborne IPDA observations. The result shows that most of the Doppler shift is in the range of 6–8 MHz, resulting in 0.26-0.39 ppm deviations in the XCO2 results. The deviations between the XCO2 retrievals and in situ measurements decreased to 0.16 ppm after the correction of the Doppler shift from 11:28:29 to 11:28:49 in the flight campaign. In addition, the online Doppler shift accounts for 98% of the deviations between XCO2 retrievals and in situ measurements. Furthermore, the impact of the Doppler shift on ACDL measurements is also assessed. The differences between the XCO2 retrievals with and without Doppler shift are used to quantify measurement uncertainties due to the Doppler effect. The simulations reveal that a pointing misalignment of 0.067 mrad can lead to a mean bias of about 0.30 ppm (0.072%) in the CO2 column. In addition, CO2 measurements are more sensitive to the Doppler shift at high altitudes for IPDA lidar, so the largest differences in the CO2 columns are found on the Qinghai–Tibet Plateau in China.

Prokaryotic Argonautes (pAgos) provide bacteria and archaea with immunity against plasmids and viruses. Catalytically active pAgos utilize short oligonucleotides as guides to directly cleave foreign nucleic acids, while inactive pAgos lacking catalytic residues employ auxiliary effectors, such as nonspecific nucleases, to trigger abortive infection upon detection of foreign nucleic acids. Here, we report a unique group of catalytically active pAgo proteins that frequently associate with a phospholipase D (PLD) family protein. We demonstrate that this particular system employs the catalytic center of the associated PLD protein rather than that of pAgo to restrict plasmid DNA, while interestingly, its immunity against a single‐stranded DNA virus relies on the pAgo catalytic center and is enhanced by the PLD protein. We also find that this system selectively suppresses viral DNA propagation without inducing noticeable abortive infection outcomes. Moreover, the pAgo protein alone enhances gene editing, which is unexpectedly inhibited by the PLD protein. Our data highlight the ability of catalytically active pAgo proteins to employ auxiliary proteins to strengthen the targeted eradication of different genetic invaders and underline the trend of PLD nucleases to participate in host immunity. Impact statement Mesophilic prokaryotic Argonautes (pAgos) have the potential to be developed into genome editing tools. We report a mesophilic archaeal Ago that is catalytically active and utilizes an associated phospholipase D (PLD) family nuclease to restrict foreign DNA. The partnership with the PLD nuclease significantly enhances the pAgo‐based immunity against single‐stranded viruses and is essential for resisting double‐stranded plasmids. Furthermore, it shows that introducing only the pAgo protein into bacterial cells can enhance editing efficiency, suggesting its potential for genome editing applications.

The Fourier Transform Spectrometer (FTS) at the Beijing Satellite Meteorological Ground Station observed XCO2 (the dry carbon dioxide column) from 2 March 2016 to 4 December 2018. The validation results of ground-based XCO2, as well as GOSAT, OCO-2, and TanSat XCO2, show that the best temporal matching setting for ground-based XCO2 and satellite XCO2 is ±1 h, and the best spatial matching setting for GOSAT is 0.5° × 0.5°. Consistent with OCO-2, the best spatial matching setting of TanSat is 5° × 5° or 6° × 6°. Among GOSAT, OCO-2, and TanSat, the satellite observation validation characteristics near 5° × 5° from the ground-based station are obviously different from other spatial matching grids, which may be due to the different observation characteristics of satellites near 5° × 5°. To study the influence of local CO2 sources on the characteristics of satellite observation validation, we classified the daily XCO2 observation sequence into concentrated, dispersive, increasing, and decreasing types, respectively, and then validated the satellite observations. The results showed that the concentrated and decreasing sub-datasets have better validation performance. Our results suggest that it is best to use concentrated and decreasing sub-datasets when using the Beijing Satellite Meteorological Ground Station XCO2 for satellite validation. The temporal matching setting should be ±1 h, and the spatial matching setting should consider the satellites observation characteristics of 5° × 5° distance from the ground-based station.

A variety of bacterial anti-phage systems have recently been discovered1-3, but how these systems synergize to defend against diverse phages remains poorly understood. Here, we report that the adaptive immune system CRISPR-Cas supervises the expression of diverse immune systems by exploiting the regulatory CRISPR RNA-like RNAs (crlRNAs). The crlRNAs target and inhibit the promoters of various immune systems, including the newly characterized Nezha and Gabija, as well as eight previously unrecognized systems that feature distinct defensive domains. Notably, CRISPR regulation balances the expression level of these systems to ensure effective anti-phage activity while avoiding their autoimmunity risks. In return, the supervised immune systems trigger abortive infections when CRISPR-Cas is inhibited by viral anti-CRISPR proteins, thereby offering an anti-anti-CRISPR protection at the population level. Moreover, these systems complement CRISPR immunity with a differing anti-phage profile. These findings highlight the pivotal role of CRISPR-Cas in orchestrating a diverse range of immune systems and showcase the delicate synergy among the multilayered defense strategies in prokaryotes.Competing Interest StatementM. L., X. S., and R. W. filed a related patent.

Cancers are composed of populations of cells with distinct molecular and phenotypic features, a phenomenon termed intratumor heterogeneity (ITH). ITH in lung cancers has not been well studied. We applied multiregion whole-exome sequencing (WES) on 11 localized lung adenocarcinomas. All tumors showed clear evidence of ITH. On average, 76% of all mutations and 20 out of 21 known cancer gene mutations were identified in all regions of individual tumors, which suggested that single-region sequencing may be adequate to identify the majority of known cancer gene mutations in localized lung adenocarcinomas. With a median follow-up of 21 months after surgery, three patients have relapsed, and all three patients had significantly larger fractions of subclonal mutations in their primary tumors than patients without relapse. These data indicate that a larger subclonal mutation fraction may be associated with increased likelihood of postsurgical relapse in patients with localized lung adenocarcinomas.

The diffuser is a critical component in a heat storage tank, and its structure has an important influence on the thermal performance of the heat storage tank. At present, research on the structure of diffusers often focuses on the change of one single parameter, which results in the need for a comprehensive structure analysis of diffusers in heat storage tanks. This paper comprehensively considers the inlet diameter, hole distance, and hole diameter of the diffuser and the inlet conditions of the heat storage tank. Then, a new evaluation index, namely the non-uniformity coefficient of the diffuser, is proposed. The experiments verify the accuracy of numerical calculation, and the related empirical formula is summarized finally. The results show that the diffuser with a small non-uniformity coefficient can achieve thin temperature stratification and higher exergy efficiency. In other words, the non-uniformity coefficient is in good agreement with temperature stratification and the exergy efficiency of the heat storage tank. When the flow rate of the inlet device is 0.5 m/s, the exergy efficiency increases by nearly 30 percentage points and the non-uniformity coefficient of the No. 4 diffuser is 3.39%. In contrast, that of the No. 8 diffuser is 75.17%. This evaluation index is suitable for different diffuser types with high accuracy. It provides the theoretical and experimental basis for the structural design and selection of diffusers for heat storage tanks.

Due to low success rates and long cycles of traditional drug development, the clinical tendency is to apply omics techniques to reveal patient-level disease characteristics and individualized responses to treatment. However, the heterogeneous form of data and uneven distribution of targets make drug discovery and precision medicine a non-trivial task. This study takes pyroptosis therapy for triple-negative breast cancer (TNBC) as a paradigm and uses data mining of a large TNBC cohort and drug databases to establish a biofactor-regulated neural network for rapidly screening and optimizing compound pyroptosis drug pairs. Subsequently, biomimetic nanococrystals are prepared using the preferred combination of mitoxantrone and gambogic acid for rational drug delivery. The unique mechanism of obtained nanococrystals regulating pyroptosis genes through ribosomal stress and triggering pyroptosis cascade immune effects are revealed in TNBC models. In this work, a target omics-based intelligent compound drug discovery framework explores an innovative drug development paradigm, which repurposes existing drugs and enables precise treatment of refractory diseases. Cancer-targeted drug discovery can be achieved by transcriptomics screening on patients. Here this group reports a drug target screening model built upon triple-negative breast cancer (TNBC) cohort and drug database with the selected drug pair exhibiting effective pyroptosis induction and TNBC tumor growth inhibition.