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Commercial scale decarbonization through carbon capture and storage may likely involve many CO2 storage projects located in close proximity. The close proximity could raise concerns over caprock integrity associated with reservoir pressure buildup and interference among adjacent projects. Commercial-scale injection will also require large prospective CO2 storage resource and high injectivity in the targeted storage formations. To accommodate the need for both large resource and high injectivity, project operators could consider injecting CO2 into a stacked sequence of formations. This analysis investigates the benefits of injecting CO2 into a vertically stacked sequence of saline formations, over injecting the same amount of CO2 into a single saline formation, in addressing these challenges. Our analysis shows that injecting into the stacked sequence mitigates the extent of pressure buildup among the stacked formations, while still achieving the same or greater target CO2 storage volumes. Among cases modeled, the resulting pressure buildup front is most reduced when each storage site distributes injection volumes over several wells, each of which injects a portion of the total CO2 mass across the stacked sequence. This favorable case not only results in the smallest CO2 aerial footprint, but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 46% compared to the single-formation storage), the result of which is crucial to maintain caprock integrity. This analysis provides insights into required decision-making when considering multi-project deployment in a shared basin. [ABSTRACT FROM AUTHOR]

Epilithic green algae play crucial roles in aquatic ecosystems. While traditional morphological approaches have provided valuable insights into these algae, their limitations in resolving cryptic species and fully capturing the extent of diversity have impeded a comprehensive understanding. The diversity and phylogenetic relationships of these algae largely remain unexplored. In the present study, single molecular real-time (SMRT) sequencing of the full-length 18S rDNA was employed to investigate the molecular diversity and phylogenetic relationships of epilithic green algae in biodiversity conservation hotspots. A total of 79 709 algal reads were generated, yielding 169 amplicon sequence variants (ASVs) from 21 epilithic riverine green algal assemblages classified in the Ulvophyceae, Chlorophyceae and Trebouxiophyceae. The 10 families in which the greatest number of unique ASVs (diversity) were observed were the Ulvellaceae, Protosiphonaceae, Chlorococcaceae, Watanabeaceae, Chlorellaceae, Neochloridaceae, Chaetophoraceae, Hazeniaceae, Tupiellaceae and Scenedesmaceae. Unique clades formed by a substantial number of sequences of green algae were detected within the Ulvales/Ulotrichales (Ulvophyceae) and the Chlorococcaceae/Protosiphonaceae (Chlorophyceae). This study has unveiled hidden diversity within epilithic green algae, expanding our knowledge of their evolutionary relationships and providing fundamental data for taxonomic investigations within this group, as well as contributing to the assessment of algal diversity in biodiversity conservation hotspots. This study suggests that these epilithic green algal assemblages may be significantly more diverse than previously recognized, but we acknowledge the limited ecological and temporal scope of our sampling effort and the resulting effects on which taxa are identified, warranting further research. Molecular analysis shows high hidden diversity of epilithic green algae The families Ulvellaceae and Protosiphonaceae had the greatest number of unique ASVs Many unique clades within the Ulvales/Ulotrichales and Chlorococcaceae/Protosiphonaceae [ABSTRACT FROM AUTHOR]

Cephaleuros species are well-known as plant pathogens that cause red rust or algae spot diseases in many economically cultivated plants that grow in shady and humid environments. Despite their prevalence, the adaptive evolution of these pathogens remains poorly understood. We sequenced and characterized three Cephaleuros (Cephaleuros lagerheimii, Cephaleuros diffusus, and Cephaleuros virescens) chloroplast genomes, and compared them with seven previously reported chloroplast genomes. The chloroplast sequences of C. lagerheimii, C. diffusus, and C. virescens were 480,613 bp, 383,846 bp, and 472,444 bp in length, respectively. These chloroplast genomes encoded 94 genes, including 27 tRNA genes, 3 rRNA genes, and 64 protein-coding genes. Comparative analysis uncovered that the variation in genome size was principally due to the length of intergenic spacer sequences, followed by introns. Furthermore, several highly variable regions (trnY-GTA, trnL-TAG, petA, psbT, trnD-GTC, trnL-TAA, ccsA, petG, psaA, psaB, rps11, rps2, and rps14) were identified. Codon bias analysis revealed that the codon usage pattern of Cephaleuros is predominantly shaped by natural selection. Additionally, six chloroplast protein-coding genes (atpF, chlN, psaA, psaB, psbA, and rbcL) were determined to be under positive selection, suggesting they may play a vital roles in the adaptation of Cephaleuros to low-light intensity habitats. [ABSTRACT FROM AUTHOR]

Cellular senescence significantly affects the proliferative and differentiation capacities of mesenchymal stem cells (MSCs). Identifying key regulators of senescence and exploring potential intervention strategies, including drug-based approaches, are active areas of research. In this context, S -adenosyl- l -methionine (SAM), a critical intermediate in sulfur amino acid metabolism, emerges as a promising candidate for mitigating MSC senescence. In a hydrogen peroxide-induced MSC aging model (100 μM for 2 hours), SAM (50 and 100 μM) was revealed to alleviate the senescence of MSCs, and also attenuated the level of reactive oxygen species and enhanced the adipogenic and osteogenic differentiation in senescent MSCs. In a premature aging mouse model (subcutaneously injected with 150 mg/kg/day d -galactose in the neck and back for 7 weeks), SAM (30 mg/kg/day by gavage for 5 weeks) was shown to delay the overall aging process while increasing the number and thickness of bone trabeculae in the distal femur. Mechanistically, activation of PI3K/AKT signaling and increased phosphorylation of forkhead box O3 (FOXO3a) was proved to be associated with the antisenescence role of SAM. These findings highlight that the PI3K/AKT/FOXO3a axis in MSCs could play a crucial role in MSCs senescence and suggest that SAM may be a potential therapeutic drug for MSCs senescence and related diseases. [ABSTRACT FROM AUTHOR]

Background: Some patients with COVID-19 rapidly develop respiratory failure or mortality, underscoring the necessity for early identification of those prone to severe illness. Numerous studies focus on clinical and lab traits, but only few attend to chest computed tomography. The current study seeks to numerically quantify pulmonary lesions using early-phase CT scans calculated through artificial intelligence algorithms in conjunction with clinical and laboratory helps clinicians to early identify the development of severe illness and death in a group of COVID-19 patients. Methods: From December 15, 2022, to January 30, 2023, 191 confirmed COVID-19 patients admitted to Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine were consecutively enrolled. All patients underwent chest CT scans and serum tests within 48 hours prior to admission. Variables significantly linked to critical illness or mortality in univariate analysis were subjected to multivariate logistic regression models post collinearity assessment. Adjusted odds ratio, 95% confidence intervals, sensitivity, specificity, Youden index, receiver-operator-characteristics (ROC) curves, and area under the curve (AUC) were computed for predicting severity and in-hospital mortality. Results: Multivariate logistic analysis revealed that myoglobin (OR = 1.003, 95% CI 1.001– 1.005), APACHE II score (OR = 1.387, 95% CI 1.216– 1.583), and the infected CT region percentage (OR = 113.897, 95% CI 4.939– 2626.496) independently correlated with in-hospital COVID-19 mortality. Prealbumin stood as an independent safeguarding factor (OR = 0.965, 95% CI 0.947– 0.984). Neutrophil counts (OR = 1.529, 95% CI 1.131– 2.068), urea nitrogen (OR = 1.587, 95% CI 1.222– 2.062), SOFA score(OR = 3.333, 95% CI 1.476– 7.522), qSOFA score(OR = 15.197, 95% CI 3.281– 70.384), PSI score(OR = 1.053, 95% CI 1.018– 1.090), and the infected CT region percentage (OR = 548.221, 95% CI 2.615– 114,953.586) independently linked to COVID-19 patient severity. [ABSTRACT FROM AUTHOR]

Featured Application: The methodology developed in this study provides a robust way of tracking down specific events in hydraulic fracturing. The innovative workflow produced an effective diagnostics tool. Ultimately, the featured event detection and diagnostics can make it possible to find optimal solutions for oil/gas well completion design, spacing and infill, production management, and wellbore protection. The primary objective of the study was development of a machine learning (ML)-based workflow for fracture hit ("frac hit") detection and monitoring using shale oil-field data such as drilling surveys, production history (oil and produced water), pressure, and fracking start time and duration records. The ML method takes advantage of long short-term memory (LSTM) and multilayer perceptron (MLP) neural networks to identify the frac hits due to hydraulic communication between the fracking child well(s) and the producing parent well(s) within the same pad (intra-pad interaction) and/or on different pads (inter-pad interaction). It utilizes time series of pressure and production data from within a pad and from adjacent pads. The workflow can capture time variable features of frac hits when the model architecture is deep and wide enough, with enough trainable parameters for deep learning and feature extraction, as demonstrated in this paper by using training and testing subsets of the field data from selected neighboring pads with over a couple of hundred wells. The study was focused on frac-hit interaction among paired wells and demonstrated that the ML model, once trained, can predict the frac-hit probability. [ABSTRACT FROM AUTHOR]

Stigeoclonium is a genus of green algae that is widely distributed in freshwater habitats around the world. The genus comprises species with variously developed prostrates and erect systems of uniseriate branched filaments and grows attached to a wide range of different surfaces. It holds significant promise for applications in water quality indicators, sewage treatment, and the development of high-value-added products. Nevertheless, our comprehension of Stigeoclonium remains unclear and perplexing, particularly regarding its fundamental systematic taxonomy. Recent molecular analyses have revealed that the morphologically well-defined genus Stigeoclonium is polyphyletic and requires taxonomic revision. Phylogenetic analysis based on a single molecular marker and limited samples is insufficient to address the polyphyletic nature of Stigeoclonium. In the present study, 34 out of 45 strains of Stigeoclonium were newly acquired from China. Alongside the morphological data, a concatenated dataset of three markers (18S rDNA + ITS2 + tufA) was utilized to determine their molecular phylogeny. The phylogenetic analysis successfully resolved the broadly defined Stigeoclonium into three robustly supported clades (Stigeoclonim tenue clade, S. farctum clade, and S. helveticum clade). The morphological characteristics assessment results showed that the cell type of the main axis-producing branch, considered a crucial morphological characteristic of the Stigeoclonium taxonomy, did not accurately reflect the real phylogeny of the genus. A new taxonomical classification of the genus Stigeoclonium was proposed based on zoospores' germination types, which aligned well with the phylogenetic topologies. Species where zoospores showed erect germination (S. helveticum clade) formed a distinct monophyletic clade, clearly separated from the other two clades, with zoospores showing prostrate germination or pseudo-erect germination. Consequently, a new genus, Pseudostigeoclonium gen. nov., is suggested to include all species in the broadly defined Stigeoclonium with zoospores with erect germination. The taxonomic diversity is supported by distinctive morphological differences and phylogenetic divergence within the broadly defined Stigeoclonium identified in this study. Further evaluation of the genus Stigeoclonium is necessary, especially via examining additional specimens and re-evaluating morphological characters under precisely defined laboratory conditions. [ABSTRACT FROM AUTHOR]