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Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge—the largest histopathology competition to date, joined by 1,290 developers—to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted κ, 95% confidence interval (CI), 0.840–0.884) and 0.868 (95% CI, 0.835–0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials. Through a community-driven competition, the PANDA challenge provides a curated diverse dataset and a catalog of models for prostate cancer pathology, and represents a blueprint for evaluating AI algorithms in digital pathology.

The precise segmentation of retinal vasculature is crucial for the early screening of various eye diseases, such as diabetic retinopathy and hypertensive retinopathy. Given the complex and variable overall structure of retinal vessels and their delicate, minute local features, the accurate extraction of fine vessels and edge pixels remains a technical challenge in the current research. To enhance the ability to extract thin vessels, this paper incorporates a pyramid channel attention module into a U-shaped network. This allows for more effective capture of information at different levels and increased attention to vessel-related channels, thereby improving model performance. Simultaneously, to prevent overfitting, this paper optimizes the standard convolutional block in the U-Net with the pre-activated residual discard convolution block, thus improving the model’s generalization ability. The model is evaluated on three benchmark retinal datasets: DRIVE, CHASE_DB1, and STARE. Experimental results demonstrate that, compared to the baseline model, the proposed model achieves improvements in sensitivity (Sen) scores of 7.12%, 9.65%, and 5.36% on these three datasets, respectively, proving its strong ability to extract fine vessels.

The Budyko models (BM) have been extended in previous studies by incorporating water storage change (ΔS) (subtracting ΔS from precipitation) to estimate evapotranspiration (ET) under non‐steady state conditions at scales finer than the climatological mean scale. However, a systematic assessment of the interannual ET predictability of the extended BM is still lacking, hence its validity and controlling factors of improvement (over the original BM) under globally diverse climates is not yet well understood. Based on a long‐term (1984–2008) gridded water budget data set, we present a comparative analysis of annual ET predictability between the original BM (ET1) and the extended BM considering ΔS (ET2) in 32 global river basins to explore the sensitivity of climate factors and catchment hydrologic responses in determining ET predictability. Results show that the difference between ET1 and ET2 increases linearly with ΔS, with ET2 < ET1 (ET2 > ET1) when ΔS > 0 (ΔS < 0). When both ET1 and ET2 overestimate (underestimate) observed ET, the error in ET2 is smaller than ET1 when ΔS > 0 (ΔS < 0) for all 32 basins considered. When the error signs of ET2 and ET1 differ, however, the difference in the absolute magnitude of ET2 and ET1 errors (REdiff) under extremely humid climates is determined by the difference between potential ET and ET, leading to comparable accuracy between ET2 and ET1. In contrast, under extremely arid climates, REdiff is controlled by the combined influences of ΔS and R, resulting in more accurate ET2 than ET1 under the condition of the in‐phase, positive‐correlated relationship between ΔS and R. Key Points The difference in evaporation (ET) estimated from original (ET1) and extended Budyko model (ET2) is linearly with water storage change (ΔS) When both ET1 and ET2 overestimate (underestimate) observed ET, ET2 is more accurate than ET1 if ΔS > 0 (ΔS < 0) If the error signs of ET2 and ET1 differ, their similar accuracy in humid climates is caused by similar ET and potential ET variability

This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.

Background & aims Intestinal fibrosis is a common and severe complication of inflammatory bowel disease without clear pathogenesis. Abnormal expression of host genes and metabolic perturbations might associate with the onset of intestinal fibrosis. In this study, we aimed to investigate the relationship between the development of intestinal fibrosis and the dynamic alterations in both fecal metabolites and host gene expression. Methods We induced intestinal fibrosis in a murine model using 2,4,6-trinitrobenzene sulfonic acid (TNBS). TNBS-treated or control mice were sacrificed after 4 and 6 weeks of intervention; alterations in colonic genes and fecal metabolites were determined by transcriptomics and metabolomics, respectively. Differential, tendency, enrichment, and correlation analyses were performed to assess the relationship between host genes and fecal metabolites. Results RNA-sequencing analysis revealed that 679 differential genes with enduring changes were mainly enriched in immune response-related signaling pathways and metabolism-related biological processes. Among them, 15 lipid metabolism-related genes were closely related to the development of intestinal fibrosis. Moreover, the fecal metabolic profile was significantly altered during intestinal fibrosis development, especially the lipid metabolites. Particularly, dynamic perturbations in lipids were strongly associated with alterations in lipid metabolism-related genes expression. Additionally, six dynamically altered metabolites might serve as biomarkers to identify colitis-related intestinal fibrosis in the murine model. Conclusions Intestinal fibrosis in colitis mice might be related to dynamic changes in gene expression and metabolites. These findings could provide new insights into the pathogenesis of intestinal fibrosis.

The digital reform of tax administration occupies a pivotal role due in enhancing governmental governance capabilities in the digital era. We consider China’s “Golden Tax Phase III” project (GTP3P) as a representative digital reform of tax administration. Utilizing a multi-phase DID model, we analyze the impact of GTP3P on the stock market, with a particular focus on corporate stock price crash risk (SPCR). Our findings reveal a significant reduction in SPCR subsequent to the GTP3P implementation. After performing parallel trend test, dealing with endogeneity concerns, and estimating the double machine learning model, we confirm baseline findings again. Heterogeneity analysis indicates that the influences of GTP3P on SPCR is asymmetrical. In the mechanism analysis, we verified that tax administration reform significantly enhances information disclosure, which guarantees a reduction of SPCR. Finally, we perform a further analysis examining investors’ holding preferences. Contrary to expectations, we observed a decrease in stock liquidity and the shareholding of long-term and fund investors, attributed to the escalated tax burden and diminishing business benefits post-reform. This study presents an innovative perspective on the corporate implications of digitization.

Black-box quantum state preparation is a fundamental building block for many higher-level quantum algorithms. The basic task of black-box state preparation is to transduce the data encoded as computational basis of quantum state into the amplitude. In the present work, we address the problem of transducing the reciprocal of the data, not the data itself into the amplitude, which is called the inverse-coefficient problem. This algorithm can be used directly as a subroutine in the matrix inversion algorithms. Furthermore, we extend this approach to address the more general nonlinear-coefficient problem in black-box state preparation. Our algorithm is based on the technique of inequality test. It can greatly relieve the need to do quantum arithmetic and the error is only resulted from the truncated error of binary string. The present algorithms enrich the algorithm library of black-box quantum state preparation and will be useful ingredients of quantum algorithm to implement non-linear quantum state transformations.

Our understanding of the molecular mechanisms underlying sleep homeostasis is limited. We have taken a systematic approach to study neural signaling by the transmitter 5-hydroxytryptamine (5-HT) in drosophila. We have generated knockout and knockin lines for Trh, the 5-HT synthesizing enzyme and all five 5-HT receptors, making it possible for us to determine their expression patterns and to investigate their functional roles. Loss of the Trh, 5HT1a or 5HT2b gene decreased sleep time whereas loss of the Trh or 5HT2b gene diminished sleep rebound after sleep deprivation. 5HT2b expression in a small subset of, probably a single pair of, neurons in the dorsal fan-shaped body (dFB) is functionally essential: elimination of the 5HT2b gene from these neurons led to loss of sleep homeostasis. Genetic ablation of 5HT2b neurons in the dFB decreased sleep and impaired sleep homeostasis. Our results have shown that serotonergic signaling in specific neurons is required for the regulation of sleep homeostasis.

Accurate quantification of the absorption properties of brown carbon (BrC) aerosols is crucial to assess the Earth‐atmosphere radiative impacts of BrC. However, the BrC absorption properties were often misestimated in field observations, due to neglecting the contribution of dust absorption. This study solved this problem by coupling a method for calculating the dust concentration into the traditional model for quantifying BrC absorption. The results show that dust absorption was up to 16.8% of the sum of BrC and dust absorption in northwestern China. The potential contribution of dust to the sum of BrC and dust absorption was significantly higher in the Asia‐located studies (0.4%–16.8%) than in the Americas‐located (<1.2%) and Europe‐located (<2.3%) studies. This work underscores the necessity of eliminating the negative effect of dust in BrC quantitative model. It prompts us to revisit the BrC absorption properties resolved by previous studies, especially in dust‐influenced areas such as Asia. Plain Language Summary Organic components in aerosols that can absorb light are collectively referred to as brown carbon (BrC), and dust aerosols can also absorb light. Their ability to change weather and climate by absorbing solar radiation has received a lot of attention from the academic community. Previous studies have often misestimated the BrC absorption properties because of the difficulty in separating BrC and dust absorption. To solve this difficulty, we proposed a new method to separate the BrC and dust absorption properties, which was successfully applied at a northwestern Chinese site. Subsequently, we found that the contribution of dust to absorption was generally high in the Asia‐located studies, not only in this study, emphasizing the necessity of applying the new method proposed in this study in dust‐affected regions such as Asia. Key Points A method was developed to remove dust effect when quantifying light absorption properties of brown carbon (BrC) Dust absorption was up to 16.8% of the sum of BrC and dust absorption at a typical site in northwest China Absorption properties of BrC in dust‐affected areas such as Asia need to be reassessed due to high dust absorption contribution

Background WD40 proteins represent a major conserved eukaryotic family, participating broadly in regulating diverse biological processes and secondary metabolite biosynthesis, including anthocyanin production. While peanut ( Arachis hypogaea ) ranks among the world’s most significant oilseed crops, the AhWD40 family remains uncharacterized, with unknown regulatory roles in anthocyanin accumulation. Results Our genome-wide analysis identified 367 AhWD40 members. Bioinformatics characterization revealed both conserved features and subgroup-specific attributes among family members. Evolutionary analysis further indicated segmental duplications as principal drivers of AhWD40 family expansion. Ka/Ks calculations demonstrated dominant purifying selection during AhWD40 evolution. Notably, six members exhibit high sequence similarity to Arabidopsis TRANSPARENT TESTA GLABRA1 ( TTG1 ). Transcriptomic and qRT-PCR analyses established strong correlations between AhWD40-170 and AhWD40-171 expression and anthocyanin accumulation. Transient overexpression of either gene in apple skin significantly enhanced anthocyanin biosynthesis. Conclusion This study provides a comprehensive understanding of the structure, classification, evolution, and anthocyanin accumulation of WD40 genes in peanut. These findings establish a functional framework for AhWD40s in anthocyanin regulation and propose novel genetic targets for enhancing plant anthocyanin production.