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The mayfly Ephemera lota Navás, 1934 was described based on subimagines, and the imagines and nymphs have not been known so far. For the first time, we provide descriptions of adults and nymphs using recently collected material. Based on their morphology, the species diagnostic characters are imaginal abdomen without transverse line, penis with finger-like apex, hindwing without any dot; nymphal frons with deep anterior emargination, two mandibular tusks subequal in length. Significantly, forewings of this species have variable MP2 base: from independent to fusing with CuA in different specimens through the other characters and barcoding data confirm all specimens belong to the same species. Due to the holotype lost, a neotype of the species is designated and subimagines are re-described. [ABSTRACT FROM AUTHOR]

The landscape of oncology drug development has witnessed remarkable advancements over the last few decades, significantly improving clinical outcomes and quality of life for patients with cancer. Project Optimus, introduced by the U.S. Food and Drug Administration, stands as a groundbreaking endeavor to reform dose selection of oncology drugs, presenting both opportunities and challenges for the field. To address complex dose optimization challenges, an Oncology Dose Optimization IQ Working Group was created to characterize current practices, provide recommendations for improvement, develop a clinical toolkit, and engage Health Authorities. Historically, dose selection for cytotoxic chemotherapeutics has focused on the maximum tolerated dose, a paradigm that is less relevant for targeted therapies and new treatment modalities. A survey conducted by this group gathered insights from member companies regarding industry practices in oncology dose optimization. Given oncology drug development is a complex effort with multidimensional optimization and high failure rates due to lack of clinically relevant efficacy, this Working Group advocates for a case‐by‐case approach to inform the timing, specific quantitative targets, and strategies for dose optimization, depending on factors such as disease characteristics, patient population, mechanism of action, including associated resistance mechanisms, and therapeutic index. This white paper highlights the evolving nature of oncology dose optimization, the impact of Project Optimus, and the need for a tailored and evidence‐based approach to optimize oncology drug dosing regimens effectively. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is suffering from a substantial decline in terrestrial water storage (TWS) in exorheic basins, threatening water resources that are critical for ∼2 billion people downstream. TWS changes are commonly estimated using gravity satellites through observations of the total terrestrial mass storage (TMS) change, with an implicit assumption of a negligible contribution from sediment transport. Through long‐term (2002–2017) sediment flux observations in seven headwater basins on the TP, we reveal that the gravity satellite‐derived TMS has decreased at a rate of 3.85 ± 0.23 Gt yr−1 in the seven basins, of which 0.35 ± 0.04 Gt yr−1 is contributed by sediment transport. Neglecting this contribution leads to an overestimation of the TWS loss by 10.1 ± 1.3%, equivalent to the annual water demand of an additional 0.62 million people in the surrounding nations. Regionally, the overestimation is surprisingly high in the Indus River and Yarkant River basins, reaching up to 50.8%–77.6%. Plain Language Summary: Accurate quantification of the change in the terrestrial water storage (TWS) on the Tibetan Plateau (TP) is imperative to improve the assessment of water availability that are critical for ∼2 billion people downstream. Through long‐term sediment flux observations, here we find that sediment transport makes a substantial contribution to gravity satellite‐derived TWS change in regions with a high erosion rate such as the TP, which has never been taken into consideration in previous studies. Neglecting this contribution leads to an overestimation of the TWS loss by about 10% on average for the seven headwater basins on the TP. The contribution is especially high in the Indus River and Yarkant River basins. Our findings improve the regional estimation of water availability and thus support climate adaptation and sustainable water resource management. Key Points: For the first time, we quantify the contribution of sediment transport to gravity satellite‐based estimation of TWS change on the TPNeglecting the contribution of sediment transport leads to an overestimation of the TWS loss by 10.1% on averageThe overestimated TWS loss is equivalent to the annual water demand of an additional 0.62 million people in surrounding nations [ABSTRACT FROM AUTHOR]

The polymer of sodium lignosulfonate and acrylic acid was prepared by grafting copolymerization, and lignin hydrogel was obtained by the polymer intercalated with montmorillonite, and the adsorption performance of Zn (II) by lignin hydrogel was investigated. The results showed that the prepared hydrogels have good adsorbability of Zn (II) and pH response. The adsorption capacity reached 285.39 mg/g, under the initial solution concentration of 600 mg/L, pH =4.5, adsorption temperature of 45 °C and adsorption time of 140 min, respectively. Modeling of adsorption kinetics indicated good agreement of experimental data with the quasi-second-order kinetic model. Langmuir equilibrium isotherm fitted the experimental data reasonable well, the adsorption is monolayer adsorption. [ABSTRACT FROM AUTHOR]

Background: Chemotactic cytokines play a crucial role in the development of acute myeloid leukemia (AML). Thus, investigating the mechanisms of chemotactic cytokine-related genes (CCRGs) in AML is of paramount importance. Methods: Using the TCGA-AML, GSE114868 , and GSE12417 datasets, differential expression analysis identified differentially expressed CCRGs (DE-CCRGs). These genes were screened by overlapping differentially expressed genes (DEGs) between AML and control groups with CCRGs. Subsequently, functional enrichment analysis and the construction of a protein-protein interaction (PPI) network were conducted to explore the functions of the DE-CCRGs. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses identified relevant prognostic genes and developed a prognostic model. Survival analysis of the prognostic gene was performed, followed by functional similarity analysis, immune analysis, enrichment analysis, and drug prediction analysis. Results: Differential expression analysis revealed 6,743 DEGs, of which 29 DE-CCRGs were selected for this study. Functional enrichment analysis indicated that DE-CCRGs were primarily involved in chemotactic cytokine-related functions and pathways. Six prognostic genes (CXCR3, CXCR2, CXCR6, CCL20, CCL4, and CCR2) were identified and incorporated into the risk model. The model's performance was validated using the GSE12417 dataset. Survival analysis showed significant differences in AML overall survival (OS) between prognostic gene high and low expression groups, indicating that prognostic gene might be significantly associated with patient survival. Additionally, nine different immune cells were identified between the two risk groups. Correlation analysis revealed that CCR2 had the most significant positive correlation with monocytes and the most significant negative correlation with resting mast cells. The tumor immune dysfunction and exclusion score was lower in the high-risk group. Conclusion: CXCR3, CXCR2, CXCR6, CCL20, CCL4, and CCR2 were identified as prognostic genes correlated to AML and the tumor immune microenvironment. These findings offerred novel insights into the prevention and treatment of AML. [ABSTRACT FROM AUTHOR]

Anomaly detection for multivariate time series is an essential task in the modern industrial field. Although several methods have been developed for anomaly detection, they usually fail to effectively exploit the metrical-temporal correlation and the other dependencies among multiple variables. To address this problem, we propose a stacked attention autoencoder for anomaly detection in multivariate time series (SA2E-AD); it focuses on fully utilizing the metrical and temporal relationships among multivariate time series. We design a multiattention block, alternately containing the temporal attention and metrical attention components in a hierarchical structure to better reconstruct normal time series, which is helpful in distinguishing the anomalies from the normal time series. Meanwhile, a two-stage training strategy is designed to further separate the anomalies from the normal data. Experiments on three publicly available datasets show that SA2E-AD outperforms the advanced baseline methods in detection performance and demonstrate the effectiveness of each part of the process in our method. [ABSTRACT FROM AUTHOR]

Piezocatalysis is attracting extensive attention in recent years because it can directly convert mechanical energy from the ambient environment (such as tiny vibrations and noise) into piezopotential for catalytic activities. Dyes are widely used in diverse industries, including paper, printing, and textiles, which cause serious environmental problems due to their persistence and toxicity. Unlike traditional catalysts that rely on chemical reactions to drive dye degradation, piezocatalysts offer a sustainable and cost‐effective alternative to breaking down complex molecules through creating highly reactive species, which have shown a significant promise in the treatment of organic pollutants in wastewater. In this review, the basic principles of piezocatalysis are first outlined, specifically describing two ubiquitous forms of driving force in nature. Following the catalytic mechanism, the current mainstream piezocatalytic materials are classified into two categories: organic and inorganic materials with detailed discussions. Moreover, after investigating and analyzing previous literature, effective strategies for improving piezocatalytic efficiency for dye degradation are systematically compared and summarized. In the end, current issues that need to be addressed in the future as well as potential research directions related to piezocatalysis are prospected. This work provides an insight into solving current issues to advance the piezocatalysts. [ABSTRACT FROM AUTHOR]

In March 2021, Serbia made the unprecedented announcement to offer free Covid‐19 vaccination to citizens of Bosnia and Herzegovina, and notably to Bosniaks, against whom three decades earlier Serbia had waged a bloody war. How was this policy appraised and, most importantly, did the policy appraisal impact reconciliation? We report here the results of a longitudinal investigation amid a representative sample of Bosniak youth (N = 450). Results suggest that a positive appraisal of this actual, state‐level policy, predicted improvement on a series of intergroup reconciliation indicators (e.g., trust in the out‐group, forgiveness for past violence, hope for future relationship), particularly so amid those who are strongly attached to their Bosniak in‐group. [ABSTRACT FROM AUTHOR]

An accurate gas utilization model is essential for precisely detecting plant photosynthetic capacity. Existing equipment for measuring the plant photosynthetic rate typically considers the key parameters of mesophyll cell conductance and a photosynthetic model based on the carbon reaction process under direct light conditions. However, the light environment signals received by the plant canopy not only vary significantly in incidence angles, but the effective light intensity also differs greatly from the measured values under vertical incidence conditions. To reduce the deviation between existing photosynthetic models and the actual photosynthetic efficiency of leaves, this study employs the gas diffusion method from engineering, using the finite element approach. Based on elastic mechanics and seepage mechanics, the internal stress field control equation of tomato leaves and the two-phase flow equation under a CO2 porous medium were derived. A mathematical model of porous gas–liquid two-phase fluid-solid coupling was established, solved, and analyzed. Preliminary verification was conducted through tests. The results show that in the initial stage of CO2 entering the leaf, the gas flow velocity is higher because of the larger pressure gradient between the pore and the leaf. In this stage, the gas diffusion rate is higher. As the intake time increases, the pressure gradient gradually decreases, and the inlet velocity slows down. Consequently, the diffusion rate gradually reduces. Because of the coupling of light quantity and light direction, the gas diffusion rate significantly increases compared with the uncoupled model. Additionally, a diffusion model that does not consider fluid–solid coupling will overestimate the gas flow rate as the depth of gas entry increases. Therefore, the internal gas diffusion model must account for the effect of coupling on the diffusion rate. [ABSTRACT FROM AUTHOR]