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Cloud changes and their attribution under global warming still remains a challenge in climatic change studies, especially in decomposing the fast and slow cloud responses to anthropogenic forcing. In this study, the responses of global cloud cover to the quadrupled CO2 forcing are investigated quantitatively by decomposing the total response into fast and slow ones using the multi-model data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). During the quasi-equilibrium period after the quadrupling of CO2 forcing, the global mean changes of simulated total cloud cover (TCC) in the total, fast, and slow responses are −2.42%, −0.64%, and −1.78%, respectively. Overall, the slow response dominates the total response in most regions over the globe with similar spatial patterns. TCC decreases at middle and low latitudes but increases at high latitudes in the total and slow responses. Whereas, it mainly decreases in the middle and low latitudes of the southern hemisphere as well as in the middle and high latitudes of the northern hemisphere in the fast response. A change in vertical motion is the major contributor to the cloud cover change at middle and low latitudes, while the decrease in upper atmospheric temperature leads to an increase in high cloud cover at high latitudes. In addition, the anomaly in water vapor convergence/diffusion also contributes to the cloud cover increase/decrease at low latitudes. [ABSTRACT FROM AUTHOR]

The annual mean surface solar radiation (SSR) trends under all-sky, clear-sky, all-sky-no-aerosol, and clear-sky-no-aerosol conditions as well as their possible causes are analyzed during 2005–2018 across China based on different satellite-retrieved datasets to determine the major drivers of the trends. The results confirm clouds and aerosols as the major contributors to such all-sky SSR trends over China but play differing roles over sub-regions. Aerosol variations during this period result in a widespread brightening, while cloud effects show opposite trends from south to north. Moreover, aerosols contribute more to the increasing all-sky SSR trends over northern China, while clouds dominate the SSR decline over southern China. A radiative transfer model is used to explore the relative contributions of cloud cover from different cloud types to the all-types-of-cloud-cover-induced (ACC-induced) SSR trends during this period in four typical sub-regions over China. The simulations point out that the decreases in low-cloud-cover (LCC) over the North China Plain are the largest positive contributor of all cloud types to the marked annual and seasonal ACC-induced SSR increases, and the positive contributions from both high-cloud-cover (HCC) and LCC declines in summer and winter greatly contribute to the ACC-induced SSR increases over East China. The contributions from medium-low-cloud-cover (mid-LCC) and LCC variations dominate the ACC-caused SSR trends over southwestern and South China all year round, except for the larger HCC contribution in summer. [ABSTRACT FROM AUTHOR]

Simple Summary: Bladder cancer (BLCA) stands as the predominant malignancy within the global urinary system. Small Cajal body-specific RNAs (scaRNAs), constituting a distinct subset of small nucleolar RNAs (snoRNAs), have recently recognized as crucial players in various physiological and pathological processes. The aim of our retrospective study was to elucidate the potential role and mechanism of SCARNA12 in BLCA, offering a foundational understanding the functionalities of scaRNAs. Employing integrated transcriptomic and single-cell proteomic analyses, we comprehensively investigate the impact of SCARNA12 on extracellular matrix (ECM) signaling pathways. Biological experiments provide additional insights into the oncogenic nature of SCARNA12, highlighting its interaction with the transcription factor H2AFZ as a pivotal factor in contributing to the carcinogenesis and progression of BLCA. This study suggests SCARNA12 as a promising diagnostic biomarker and therapeutic target, unveiling its involvement in BLCA through modulation of ECM signaling and interaction with H2AFZ. Background: Small Cajal body-specific RNAs (scaRNAs) are a specific subset of small nucleolar RNAs (snoRNAs) that have recently emerged as pivotal contributors in diverse physiological and pathological processes. However, their defined roles in carcinogenesis remain largely elusive. This study aims to explore the potential function and mechanism of SCARNA12 in bladder cancer (BLCA) and to provide a theoretical basis for further investigations into the biological functionalities of scaRNAs. Materials and Methods: TCGA, GEO and GTEx data sets were used to analyze the expression of SCARNA12 and its clinicopathological significance in BLCA. Quantitative real-time PCR (qPCR) and in situ hybridization were applied to validate the expression of SCARNA12 in both BLCA cell lines and tissues. RNA sequencing (RNA-seq) combined with bioinformatics analyses were conducted to reveal the changes in gene expression patterns and functional pathways in BLCA patients with different expressions of SCARNA12 and T24 cell lines upon SCARNA12 knockdown. Single-cell mass cytometry (CyTOF) was then used to evaluate the tumor-related cell cluster affected by SCARNA12. Moreover, SCARNA12 was stably knocked down in T24 and UMUC3 cell lines by lentivirus-mediated CRISPR/Cas9 approach. The biological effects of SCARNA12 on the proliferation, clonogenic, migration, invasion, cell apoptosis, cell cycle, and tumor growth were assessed by in vitro MTT, colony formation, wound healing, transwell, flow cytometry assays, and in vivo nude mice xenograft models, respectively. Finally, a chromatin isolation by RNA purification (ChIRP) experiment was further conducted to delineate the potential mechanisms of SCARNA12 in BLCA. Results: The expression of SCARNA12 was significantly up-regulated in both BLCA tissues and cell lines. RNA-seq data elucidated that SCARAN12 may play a potential role in cell adhesion and extracellular matrix (ECM) related signaling pathways. CyTOF results further showed that an ECM-related cell cluster with vimentin+, CD13+, CD44+, and CD47+ was enriched in BLCA patients with high SCARNA12 expression. Additionally, SCARNA12 knockdown significantly inhibited the proliferation, colony formation, migration, and invasion abilities in T24 and UMUC3 cell lines. SCARNA12 knockdown prompted cell arrest in the G0/G1 and G2/M phase and promoted apoptosis in T24 and UMUC3 cell lines. Furthermore, SCARNA12 knockdown could suppress the in vivo tumor growth in nude mice. A ChIRP experiment further suggested that SCARNA12 may combine transcription factors H2AFZ to modulate the transcription program and then affect BLCA progression. Conclusions: Our study is the first to propose aberrant alteration of SCARNA12 and elucidate its potential oncogenic roles in BLCA via the modulation of ECM signaling. The interaction of SCARNA12 with the transcriptional factor H2AFZ emerges as a key contributor to the carcinogenesis and progression of BLCA. These findings suggest SCARNA12 may serve as a diagnostic biomarker and potential therapeutic target for the treatment of BLCA. [ABSTRACT FROM AUTHOR]

Estimating individual tree diameters at breast height (DBH) from delineated crowns and tree heights on the basis of airborne light detection and ranging (LiDAR) data provides a good opportunity for large-scale forest inventory. Generally, ground-based measurements are more accurate, but LiDAR data and derived DBH values can be obtained over larger areas for a relatively smaller cost if a right procedure is developed. A nonlinear least squares (NLS) regression is not an appropriate approach to predict the aboveground biomass (AGB) of individual trees from the estimated DBH because both the response variable and the regressor are subject to measurement errors. In this study, a system of compatible individual tree DBH and AGB error-in-variable models was developed using error-in-variable regression techniques based on both airborne LiDAR and field-measured datasets of individual Picea crassifolia Kom. trees, collected in northwestern China. Two parameter estimation algorithms, i.e., the two-stage error-in-variable model (TSEM) and the nonlinear seemingly unrelated regression (NSUR), were proposed for estimating the parameters in the developed system of compatible individual tree DBH and AGB error-in-variable models. Moreover, two model structures were applied to estimate AGB for comparison purposes: NLS with AGB estimation depending on DBH (NLS&DD) and NLS with AGB estimation not depending on DBH (NLS&NDD). The results showed that both TSEM and NSUR led to almost the same parameter estimates for the developed system. Moreover, the developed system effectively accounted for the inherent correlation between DBH and AGB as well as for the effects of measurement errors in the DBH on the predictions of AGB, whereas NLS&DD and NLS&NDD did not. A leave-one-out cross-validation indicated that the prediction accuracy of the developed system of compatible individual tree DBH and AGB error-in-variable models with NSUR was the highest among those estimated by the four methods evaluated, but, statistically, the accuracy improvement was not significantly different from zero. The main reason might be that, except for the measurement errors, other source errors were ignored in the modeling. This study implies that, overall, the proposed method provides the potential to expand the estimations of both DBH and AGB from individual trees to stands by combining the error-in-variable modeling and LiDAR data and improve their estimation accuracies, but its application needs to be further validated by conducting a systematical uncertainty analysis of various source errors in a future study. [ABSTRACT FROM AUTHOR]

Simple Summary: The tumor microenvironment (TME) is considered to play a key role in the development of many types of tumors. Muscle invasive bladder cancer (MIBC), which is well known for its heterogeneity, has a highly complex TME. Herein, we integrated mass cytometry and imaging mass cytometry to systematically investigate the complexity of the MIBC TME. Our investigation revealed tumor and immune cells with diverse phenotypes. We identified a specific cancer stem-like cell cluster (ALDH+PD-L1+ER-β−), which is associated with poor prognosis and highlighted the importance of the spatial distribution patterns of MIBC TME components. The present study comprehensively elucidated the complexity of the MIBC TME and provides potentially valuable information for future research. Muscle invasive bladder cancer (MIBC) is a malignancy with considerable heterogeneity. The MIBC tumor microenvironment (TME) is highly complex, comprising diverse phenotypes and spatial architectures. The complexity of the MIBC TME must be characterized to provide potential targets for precision therapy. Herein, an integrated combination of mass cytometry and imaging mass cytometry was used to analyze tumor cells, immune cells, and TME spatial characteristics of 44 MIBC patients. We detected tumor and immune cell clusters with abnormal phenotypes. In particular, we identified a previously overlooked cancer stem-like cell cluster (ALDH+PD-L1+ER-β−) that was strongly associated with poor prognosis. We elucidated the different spatial architectures of immune cells (excluded, infiltrated, and deserted) and tumor-associated collagens (curved, stretched, directionally distributed, and chaotic) in the MIBC TME. The present study is the first to provide in-depth insight into the complexity of the MIBC TME at the single-cell level. Our results will improve the general understanding of the heterogeneous characteristics of MIBC, potentially facilitating patient stratification and personalized therapy. [ABSTRACT FROM AUTHOR]