VADIS: A Visual Analytics Pipeline for Dynamic Document Representation and Information-Seeking.

In the biomedical domain, visualizing the document embeddings of an extensive corpus has been widely used in informationseeking tasks. However, three key challenges with existing visualizations make it difficult for clinicians to find information efficiently. First, the document embeddings used in these visualizations are generated statically by pretrained language models, which cannot adapt to the user's evolving interest. Second, existing document visualization techniques cannot effectively display how the documents are relevant to users' interest, making it difficult for users to identify the most pertinent information. Third, existing embedding generation and visualization processes suffer from a lack of interpretability, making it difficult to understand, trust and use the result for decision-making. In this paper, we present a novel visual analytics pipeline for user-driven document representation and iterative information seeking (VADIS). VADIS introduces a prompt-based attention model (PAM) that generates dynamic document embedding and document relevance adjusted to the user's query. To effectively visualize these two pieces of information, we design a new document map that leverages a circular grid layout to display documents based on both their relevance to the query and the semantic similarity. Additionally, to improve the interpretability, we introduce a corpus-level attention visualization method to improve the user's understanding of the model focus and to enable the users to identify potential oversight. This visualization, in turn, empowers users to refine, update and introduce new queries, thereby facilitating a dynamic and iterative information-seeking experience. We evaluated VADIS quantitatively and qualitatively on a real-world dataset of biomedical research papers to demonstrate its effectiveness.

Mogroside V and mogrol: unveiling the neuroprotective and metabolic regulatory roles of Siraitia grosvenorii in Parkinson's disease.

Introduction: Siraitia grosvenorii (Swingle) C. Jeffrey, is an edible and traditional medicine widely used in China. Mogroside V (MGV) and mogrol (MG) are its main active ingredients, which have been found to be effective in the treatment of neurodegenerative diseases recently. However, whether they can effectively treat Parkinson's disease (PD) and their underlying mechanisms have not been sufficiently explored. In this study, we investigated the neuroprotective and metabolic regulatory effects of MGV and MG on PD. Materials and methods: Using SH-SY5Y cell models and an MPTP-induced mouse model of PD, we evaluated the compounds' efficacy in mitigating MPP+-induced neurotoxicity and ameliorating motor deficits and dopaminergic neuron loss. Employing widely targeted metabolomics and bioinformatics analysis to investigate the Metabolic imbalance rectification caused by MGV and MG treatment. The vivo experimental protocol encompassed a 14-day drug administration regimen with mice randomly allocated into six groups (n = 9) receiving distinct compound dosages including a control group, a model group, MGV-H (30 mg/kg/day), MGV-L (10 mg/kg/day), MG-H (15 mg/kg/day), and MG-L (3 mg/kg/day). Results: Our findings revealed that pre-treatment with MGV and MG significantly enhanced cell viability in SH-SY5Y cells exposed to MPP+, demonstrating a potent protective effect against neurotoxicity. In the MPTP mouse model, MGV-H, MGV-L, and MG-H significantly enhanced motor coordination as assessed by the rotarod test (p < 0.05); MGV-L and MG-H evidently inhibited dopaminergic neuronal loss in the substantia nigra pars compacta (p < 0.05). Furthermore, metabolomic analysis of the substantia nigra highlighted the restoration of metabolic balance, with MGV-L and MG-H impacting 160 differential metabolites and modulating key pathways disrupted in PD, including sphingolipid metabolism, fatty acid metabolism, and amino acid metabolism. Notably, treatment with MGV-L and MG-H led to the regulation of 106 metabolites, showing a recovery trend towards normal levels, which constitutes approximately 17.5% of the identified metabolites. Key metabolites such as n-acetyl-l-glutamate, hexadecanoic acid, and 9-octadecenal were significantly altered (p < 0.05), underscoring their broad-spectrum metabolic regulatory capacity. Conclusion: This study underscores the potential of natural compounds in developing comprehensive treatment strategies for neurodegenerative diseases, paving the way for future clinical research to validate the therapeutic efficacy of mogrosides in PD.

Swarming caddisflies in the mid-cretaceous.

Swarming, as a special form of mating aggregation, is most noteworthy in insects of the orders Ephemeroptera, Diptera, and Trichoptera. Swarming in extant trichopterans is well understood in terms of sex composition, specific mating behaviors, and functional morphological specializations of adults, but an exploration of the evolution of such aggregative behaviors is hampered by the dearth of available examples from the fossil record as well as the ability to reliably distinguish the few gatherings as the result of swarming relative to other taphonomic or behavioral factors. Herein we describe five new fossil species of caddisflies preserved in mid-Cretaceous amber from Myanmar, all preserved as large aggregations. Monospecific aggregations of these five new species can be positively identified as swarms based on morphological traits of wing shape, as well as the presence of particular forms of sexual dimorphism. Results of a phylogenetic reconstruction of both molecular and morphological data as well as ancestral-trait reconstructions and tip-dating analyses indicate that swarming was likely present in the Triassic as a feature of the trichopteran groundplan. Since most Mesozoic insectivorous predators were diurnal based on morphological evidence, largely nocturnal caddisflies would have been freed from such pressures. The phylogeny also shows a correlation between the rise of nocturnal bat predators from the Paleocene or early Eocene and the repeated loss of swarming from various clades of caddisflies, revealing the potential impact of bat predation on reshaping the behavioral landscape of Trichoptera during the Cenozoic.

Individualized dose calculation for internal exposure on radionuclide intake: GPU acceleration approach.

Objective. The rapid and accurate assessment of internal exposure dose is a crucial safeguard for personnel health and safety. This study aims to investigate a precise and efficient GPU Monte Carlo simulation approach for internal exposure dose calculation. It directly calculates doses from common radioactive nuclides intake, like60Co for occupational exposure, allowing personalized assessments.Approach. This study developed a GPU-accelerated Monte Carlo program for internal exposure on radionuclide intake, successfully realizing photoelectronic coupled transport, nuclide simulation, and optimized acceleration. The generation of internal irradiation sources and sampling methods were achieved, along with the establishment of a personalized phantom construction process. Three irradiation scenarios were simulated to assess computational accuracy and efficiency, and to investigate the influence of posture variations on internal dose estimations.Main results. Using the International Commission on Radiological Protection (ICRP) voxel-type phantom, the internal dose of radionuclides in individual organs was calculated, exhibiting relative deviation of less than 3% in comparison to organ dose results interpolated by Specific Absorbed Fractions in ICRP Publication 133. Employing the Chinese reference phantom for calculating internal irradiation dose from the intake of various radionuclides, the use of GPU Monte Carlo program significantly shortened the simulation time compared to using CPU programs, by a factor of 150-500. Internal dose estimation utilizing a seated Chinese phantom revealed up to a 75% maximum difference in organ dose compared to the same phantom in a standing posture.Significance. This study presents a rapid GPU-based simulation method for internal irradiation doses, capable of directly simulating dose outcomes from nuclide intake and accommodating individualized phantoms for more realistic and expeditious calculations tailored to specific internal irradiation scenarios. It provides an effective and feasible tool for precisely calculating internal irradiation doses in real-world scenarios.

Mathematical analysis of FLASH effect models based on theoretical hypotheses.

OBJECTIVE: Clinical applications of FLASH radiotherapy require formulas to describe how the FLASH radiation features and other related factors determine the FLASH effect. Mathematical analysis of the models can connect the theoretical hypotheses with the radiobiological effect, which provides the foundation for establishing clinical application models. Moreover, experimental and clinical data can be used to explore the key factors through mathematical analysis. Approach: We abstract the complex models of the oxygen depletion hypothesis and radical recombination-antioxidants hypothesis into concise mathematical equations. The equations are solved to analyze how the radiation features and other factors influence the FLASH effect. Then we propose methodologies for determining the parameters in the models and utilizing the models to predict the FLASH effect. Main results: The formulas linking the physical, chemical and biological factors to the FLASH effect are obtained through mathematical derivation of the equation. The analysis indicates that the initial oxygen concentration, radiolytic oxygen consumption and oxygen recovery are key factors for the oxygen depletion hypothesis and that the level of antioxidants is the key factor for the radical recombination-antioxidants hypothesis. According to the model derivations and analysis, the methodologies for determining parameters and predicting the FLASH effect are proposed: the criteria for data filtration; the strategy of hybrid FLASH and conventional dose rate (CONV) irradiation to ensure the acquisition of effective experimental data across a wide dose range; pipelines of fitting parameters and predicting the FLASH effect. Significance: This study establishes the quantitative relationship between the FLASH effect and key factors. The derived formulas can be used to calculate the FLASH effect in future clinical FLASH radiotherapy. The proposed methodologies guide to obtain sufficient high-quality datasets and utilize them to predict FLASH effect. Furthermore, this study indicates the key factors of FLASH effect and offers clues to further explore the FLASH mechanism.

PIG: Prompt Images Guidance for Night-Time Scene Parsing.

Night-time scene parsing aims to extract pixel-level semantic information in night images, aiding downstream tasks in understanding scene object distribution. Due to limited labeled night image datasets, unsupervised domain adaptation (UDA) has become the predominant method for studying night scenes. UDA typically relies on paired day-night image pairs to guide adaptation, but this approach hampers dataset construction and restricts generalization across night scenes in different datasets. Moreover, UDA, focusing on network architecture and training strategies, faces difficulties in handling classes with few domain similarities. In this paper, we leverage Prompt Images Guidance (PIG) to enhance UDA with supplementary night knowledge. We propose a Night-Focused Network (NFNet) to learn night-specific features from both target domain images and prompt images. To generate high-quality pseudo-labels, we propose Pseudo-label Fusion via Domain Similarity Guidance (FDSG). Classes with fewer domain similarities are predicted by NFNet, which excels in parsing night features, while classes with more domain similarities are predicted by UDA, which has rich labeled semantics. Additionally, we propose two data augmentation strategies: the Prompt Mixture Strategy (PMS) and the Alternate Mask Strategy (AMS), aimed at mitigating the overfitting of the NFNet to a few prompt images. We conduct extensive experiments on four night-time datasets: NightCity, NightCity+, Dark Zurich, and ACDC. The results indicate that utilizing PIG can enhance the parsing accuracy of UDA. The code is available at https://github.com/qiurui4shu/PIG.

Hydrogen-Bonding Integrated Low-Dimensional Flexible Electronics Beyond the Limitations of van der Waals Contacts.

Van der Waals (vdW) integration enables clean contacts for low-dimensional electronic devices. The limitation remains; however, that an additional tunneling contact resistance occurs owing to the inherent vdW gap between the metal and the semiconductor. Here, it is demonstrated from theoretical calculations that stronger non-covalent hydrogen-bonding interactions facilitate electron tunneling and significantly reduce the contact resistance; thus, promising to break the limitations of the vdW contact. π-plane hydrogen-bonding contacts in surface-engineered MXene/carbon nanotube metal/semiconductor heterojunctions are realized, and an anomalous temperature-dependent tunneling resistance is observed. Low-dimensional flexible thin-film transistors integrated by hydrogen-bonding contacts exhibit both excellent flexibility and carrier mobility orders of magnitude higher than their counterparts with vdW contacts. This strategy demonstrates a scalable solution for realizing high-performance and low-power flexible electronics beyond vdW contacts.

Effects of the fermentation quality and microbial community of waxy maize mixed with fodder soybean silage.

Waxy maize (Zea mays L. sinensis Kulesh) is highly regarded for its high nutritional content and unique taste. Although the stalks and leaves contain high carbohydrate levels after ear harvesting, inadequate crude protein (CP) limits the utilization and promotion of waxy maize silage in animal husbandry. In this study, waxy maize and fodder soybeans were mixed for sowing in different proportions [1:0 (CK), 1:1 (A1), 1:2 (A2), 1:3 (A3), and 1:4 (A4)] to investigate the effects of different mixing ratios on the growth of the waxy maize, the chemical indices, fermentation quality, and the microbial community of the mixed silage after ear harvesting. The mixed planting of waxy maize and fodder soybeans in different proportions had no effect on the yield and quality of the waxy maize ears and increased the aboveground biomass after ear harvesting. After ear harvesting, the neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents significantly decreased, and the CP content and relative feeding value (RFV) gradually increased in the mixed silage. The pH of the treatments was lower than 4.2 except for A4, and the lowest ammonia nitrogen (AN) concentration was observed in A3. With increasing proportions of fodder soybeans, the abundance of beneficial bacteria increased and that of harmful bacteria decreased; Firmicutes and Lactobacillus were the dominant phylum and genus, respectively, and both increased gradually. Redundancy analysis (RDA) revealed that the fermentation indices affecting the microbial community composition in the silage were inconsistent among the different mixed sowing combinations. The Mantel test showed that the composition of the microbial communities in the treatments was significantly correlated with the ADF, water-soluble carbohydrate (WSC), and propionic acid (PA) contents. Comprehensive analysis revealed that the optimal mixed sowing ratio of waxy maize to fodder soybeans was 1:3, and waxy maize and fodder soybeans silage can increase the utilization of aboveground biomass and improve the fermentation quality and feeding quality of silage by changing the microbial community. These findings lay a certain theoretical foundation for improving the utilization of waxy maize.

Investigation on the relationship between hemoglobin concentration and stroke risk: a bidirectional Mendelian randomization study.

Background: The relationship between hemoglobin concentration and stroke has garnered significant interest in the research community. However, findings from published observational epidemiological studies on this relationship have been inconclusive. By using publicly available genome-wide association study (GWAS) aggregated statistics, a two-sample Mendelian randomization analysis is conducted to explore the causal relationship between hemoglobin concentration and stroke. Methods: Summary statistics data from UK Biobank for hemoglobin concentration and from the FinnGen R9 and MEGASTROKE consortium for stroke are used. A series of quality control steps are taken to select eligible instrumental SNPs closely related to exposure. In order to make the conclusion more robust and reliable, several robust analysis methods are employed including inverse variance weighted, weighted median, MR-Egger regression, which are based on different assumptions of two-sample MR Analysis. Meanwhile, sensitivity analyses such as pleiotropy test and MR-Egg regression, are performed to mitigate horizontal pleiotropy and heterogeneity. Results: The two-sample Mendelian randomized study indicates a negative association between hemoglobin concentration and stroke, suggesting that hemoglobin concentration acts as a protective factor against stroke. From the FinnGen database, there is a negative association between hemoglobin concentration and stroke, with an odds ratio (OR) of 0.82 and a 95% confidence interval (CI) of 0.73-0.92, p = 0.0006. Similarly, the MEGASTROKE database findings reinforce this observation. The negative association between hemoglobin concentration and stroke (OR: 0.91, 95%CI: 0.83-1.00, p = 0.040), ischemic stroke (OR: 0.87, 95%CI: 0.79-0.96, p = 0.004), and cardiogenic stroke (OR: 0.82, 95% CI: 0.69-0.99, p = 0.039) further suggests that higher hemoglobin levels might confer a protective effect against these conditions. Conclusion: Hemoglobin concentration serves as a protective factor against stroke, and managing abnormal hemoglobin levels can effectively reduce the incidence of stroke.

The association of impulsivity with depression and anxiety symptoms: A transdiagnostic network analysis and replication.

BACKGROUND: Impulsivity increases the risk for depression and anxiety. However, the granular pathways among them remain unknown. A network approach that moves from disorder-level analysis to symptom-level analysis can provide further understanding of psychopathological mechanisms. In this study, we examined the network structure of impulsivity and separate and comorbid symptoms of depression and anxiety. METHODS: Regularized partial-correlation networks were estimated using cross-sectional data from 1047 Chinese participants aged 18-26 years (main dataset, mean age = 21.45 ± 2.01 years) and 325 Chinese participants aged 18-36 years (an independent replication dataset, mean age = 21.49 ± 3.73 years), including impulsivity-depression, impulsivity-anxiety, and impulsivity-depression-anxiety networks. The datasets were collected from 1 June 2023 to 4 August 2023 and from 27 April 2022 to 16 May 2022, respectively. Impulsivity, depression, and anxiety were assessed using Barratt Impulsiveness Scale Version 11, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7, respectively. Bridge centrality was analyzed, and a network comparison test (NCT) was conducted to investigate the differences between the main dataset and replication dataset. RESULTS: The motor impulsivity dimension was revealed to be closely connected with individual symptoms of depression and anxiety regardless of whether they were in separate disorder forms or comorbid forms. In all the networks, motor impulsivity was the most important bridge node. The NCT showed comparable network connectivity and network structure between the main and replication datasets. LIMITATIONS: The use of cross-sectional data limited the inferences about the direction of causality between variables. CONCLUSIONS: These findings elucidate the psychopathological mechanisms underlying how impulsivity functions within depression, anxiety, and comorbidity and support that motor impulsivity is an important risk factor across different mental disorders and is responsible for comorbidity. The implications of these findings are discussed.

Preparation of novel Fe-containing zeolite-A for KN-R decolorization by Fenton-like reaction.

Herein, novel catalysts of Fe-containing zeolite-A (Fe/zeolite-A) were synthesized by exchanging iron ions into zeolite-A framework, and short-chain organic acids (SCOAs) were employed as chelating agents. Reactive Brilliant Blue KN-R (KN-R) was used as a model pollutant to evaluate the performance of these catalysts based on the heterogeneous Fenton reaction. The results showed that Fe-OA/3A, which applied zeolite-3A as the supporter and oxalic as the chelating agent, presented the most prominent KN-R decolorization efficiency. Under the initial pH of 2.5, 0.4 mM KN-R could be totally decolorized within 20 min. However, the mineralization efficiency of KN-R was only 58.2%. Therefore, anthraquinone dyes were introduced to modify zeolite-3A. As a result, the mineralization efficiency of KN-R was elevated to 92.7% when using Alizarin Violet (AV) as the modifier. Moreover, the modified catalysts exhibited excellent stability, the KN-R decolorization efficiency could be maintained above 95.0% within 20 min after operating for nine cycles. The mechanism revealed that the Fe(II)/Fe(III) cycle was accelerated by AV-modified catalyst thus prompting the KN-R decolorization in Fenton-like system. These findings provide new insights for preparing catalysts with excellent activity and stability for dye wastewater treatment.

Complete genome sequence of a novel dsRNA virus from the phytopathogenic fungus Fusarium oxysporum.

Fusarium oxysporum is a widespread plant pathogen that causes fusarium wilt and fusarium root rot in many economically significant crops. Here, a novel dsRNA virus tentatively named "Fusarium oxysporum virus 1" (FoV1) was identified in F. oxysporum strain 3S-18. The genome of FoV1 is 2,944 nucleotides (nt) in length and contains two non-overlapping open reading frames (ORF1 and 2). The larger of these, ORF2, encodes an RNA-dependent RNA polymerase (RdRp) of 590 amino acids with a molecular mass of 67.52 kDa. ORF1 encodes a putative nucleocapsid protein consisting of 134 amino acids with a molecular mass of 34.25 kDa. The RdRp domain of FoV1 shares 60.00% to 84.24% sequence identity with non-segmented dsRNA viruses. Phylogenetic analysis further suggested that FoV1 is a new member of the proposed genus "Unirnavirus" accommodating unclassified monopartite dsRNA viruses.

Characterization of Fusarium solani Associated with Tobacco (Nicotiana tabacum) Root Rot in Henan, China.

The aim of this study was to characterize the Fusarium solani species complex (FSSC) population obtained from tobacco roots with root rot symptoms by morphological characteristics, molecular tests, and assessment of pathogenicity. Cultures isolated from roots were white to cream with sparse mycelium on potato dextrose agar, with colony growth of 21.5 ± 0.5 to 29.5 ± 0.5 mm after 3 days. Sporodochia were cream on carnation leaf agar (CLA) and Spezieller Nährstoffarmer agar (SNA), and macroconidia formed in sporodochia were 3 to 6 septate and straight to slightly curved, with wide central cells, a slightly short blunt apical cell, and a straight to almost cylindrical basal cell with a distinct foot shape, ranging in size from 20.92 to 64.37 × 3.91 to 6.57 µm. Microconidia formed on CLA were reniform and fusiform, with 0 or 1 to occasionally 2 septa, that formed on long monophialidic conidiogenous cells, with a size range of 5.99 to 32.32 × 1.76 to 5.84 µm. Globose to oval chlamydospores were smooth- to rough-walled, 6.5 to 13.3 ± 0.37 µm in diameter, and terminal or intercalary and occurred singly, in pairs, or occasionally in short chains on SNA. Molecular tests consisted of sequencing and phylogenetic analysis of the translation elongation factor-1 alpha (EF-1α), RNA polymerase II largest subunit, and second largest subunit regions. All the obtained sequences revealed 98.14 to 100% identity to F. solani in both Fusarium ID and Fusarium MLST databases. Phylogenetic trees of the EF-1α gene and concatenated three-locus data showed that isolates from tobacco in Henan grouped in the proposed group 5, which is nested within FSSC clade 3 (FSSC 5). Twenty-seven of the 28 isolates caused root rot in artificially inoculated tobacco seedlings, with a disease severity index ranging from 15.00 ± 1.67 to 91.11 ± 2.22. Cross-pathogenicity tests showed that three representative isolates were virulent to six species of Solanaceae and two species of Poaceae, with disease severity indexes ranging from 6.12 ± 0.56 to 84.44 ± 0.00, indicating that these isolates have a wide host range. The results may inform the control of tobacco root rot through improved crop rotations.

Facilely Prepared Carbon Dots as Effective Anode Modifier for Enhanced Performance of Microbial Fuel Cells.

Microbial fuel cells (MFCs) are a promising technology for obtaining energy in wastewater. Effective extracellular electron transfer is one of the key factors for its practical application. In this work, carbon dots (CDs) enriched with oxygen-containing groups on the surface were synthesized as an efficient anode modifier using a simple hydrothermal method and common reactants. The experimental findings indicated that anodes modified with CDs exhibited increased electrical conductivity and greater hydrophilicity. These modifications facilitated increased microorganism loading and contributed to enhancing electrochemical processes within the anode biofilm. The CD-modified MFCs exhibited higher maximum power density (661.1 ± 42.6 mW·m-2) and open-circuit voltage (534.50 ± 6.4 mV), which were significantly better than those of the blank group MFCs (484.1 ± 14.1 mW·m-2 and 447.50 ± 12.1 mV). The use of simple carbon materials to improve the microbial loading on the MFCs anode and the electron transfer between the microbial-electrode may provide a new idea for the design of efficient MFCs.

THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry.

Objective. Establishing realistic phantoms of human anatomy is a continuing concern within virtual clinical trials of breast x-ray imaging. However, little attention has been paid to glandular distribution within these phantoms. The principal objective of this study was to develop breast phantoms considering the clinical glandular distribution.Approach. This research introduces an innovative method for integrating glandular distribution information into breast phantoms. We have developed an open-source software, THUBreast44http://github.com/true02Hydrogen/THUBreast/, which generates breast phantoms that accurately replicate both the structural texture and glandular distribution, two crucial elements in breast x-ray imaging and dosimetry. To validate the efficacy of THUBreast, we assembled three groups of breast phantoms (THUBreast, patient-based, homogeneous) for irradiation simulation and calculated the power-law exponents (ß) and mean glandular dose (Dg), indicators of texture realism and radiation risk, respectively, utilizing MC-GPU.Main results. Upon the computation of theDgfor the THUBreast phantoms, it was found to be in agreement with that absorbed by the phantoms based on patients, with an average deviation of 4%. The estimates of averageDgthus obtained were on average 23% less than those computed for the homogeneous phantoms. It was observed that the homogeneous phantoms did overestimate the averageDgby 30% when compared to the phantoms based on patients. The mean value ofßfor the images of THUBreast phantoms was found to be 2.92 ± 0.08, which shows a commendable agreement with the findings of prior investigations.Significance. It is evidently clear from the results that THUBreast phantoms have a preliminary good performance in both imaging and dosimetry in terms of indicators of texture realism and glandular dose. THUBreast represents a further step towards developing a powerful toolkit for comprehensive evaluation of image quality and radiation risk.

Computational model of radiation oxygen effect with Monte Carlo simulation: effects of antioxidants and peroxyl radicals.

PURPOSE: Oxygen plays a crucial role in radiation biology. Antioxidants and peroxyl radicals affect the oxygen effect greatly. This study aims to establish a computational model of the oxygen effect and explore the effect attributed to antioxidants and peroxyl radicals. MATERIALS AND METHODS: Oxygen-related reactions are added to our track-structure Monte Carlo code NASIC, including oxygen fixation, chemical repair by antioxidants and damage migration from base-derived peroxyl radicals. Then the code is used to simulate the DNA damage under various oxygen, antioxidant and damage migration rate conditions. The oxygen enhancement ratio(OER) is calculated quantifying by the number of double-strand breaks for each condition. The roles of antioxidants and peroxyl radicals are examined by manipulating the relevant parameters. RESULTS AND CONCLUSIONS: Our results indicate that antioxidants are capable of rapidly restoring DNA radicals through chemical reactions, which compete with natural and oxygen fixation processes. Additionally, antioxidants can react with peroxyl radicals derived from bases, thereby preventing the damage from migrating to DNA strands. By quantitatively accounting for the impact of peroxyl radicals and antioxidants on the OER curves, our study establishes a more precise and comprehensive model of the radiation oxygen effect.

Weak correlations among leaf thermal metrics, economic traits and damages under natural heatwaves.

The frequency and intensity of heatwaves are increasing around the world, causing severe damages to plants, but whether leaf thermal metrics is in line with leaf economic spectrum is still controversial. Here, we measured leaf damage ratio, leaf thermal metrics (tolerance and sensitivity) and economic traits of 131 woody species across five cities along the Yangtze River after a two-month natural extreme temperature event. We found that leaf thermal sensitivity but not thermal tolerance was correlated with leaf damage ratio, and the relationships between leaf thermal metrics and economic traits were weak, indicating that leaf thermal adaptation may be independent from leaf carbon construction. This study suggests a potential indicator for predicting plant survival under heatwaves, urging future research to explore more physiological traits to comprehensively understand plant heat responses and adaptations.

The Relationships between Effortful Control, Mind Wandering, and Mobile Phone Addiction Based on Network Analysis.

BACKGROUND: The prevailing mobile phone use brought the problem of addiction, which might cause negative consequences. Effortful control and mind wandering were associated with addictive behavior. The present study aimed to investigate the dimension-level relationships between effortful control, mind wandering, and mobile phone addiction. METHODS: A total of 1684 participants participated this study. The mobile phone addiction, effortful control, and mind wandering were measured through self-report scales, respectively. Dimension-level network of these psychological variables was estimated and bridge expected influence (BEI) values for each node was calculated. RESULTS: Dimensions of mobile phone addiction, effortful control, and mind wandering exhibited distinct and complex links to each other. The node "activation control" exhibited the highest negative BEI value (BEI = -0.32), whereas "spontaneous thinking" showed the highest positive BEI value (BEI = 0.20). CONCLUSIONS: Different dimensions of effortful control and mind wandering had varied yet significant connections with distinct dimensions of mobile phone addiction, facilitating understanding of the specific pathways underlying the three constructs. The identified dominant bridge nodes can provide potential targets for the intervention of mobile phone addiction.

Effects of Wood Content and Modification on Properties of Wood Flour/Polybutylene Adipate Terephthalate Biocomposites.

Biodegradable polymers have recently become attractive and have been increasingly used as matrix materials to replace fossil plastics due to concerns about the environmental issue. However, their application areas are limited due to their high costs and natural properties. In this study, we fabricated ecofriendly and economical polybutylene adipate terephthalate (PBAT) composites loaded with various concentrations of wood flour (WF) to investigate the effects on the PBAT and WF interfaces as well as the physical properties of the WF/PBAT biocomposites. Then, WF was acetylated with acetic anhydride, and the effect of WF acetylation on the mechanical and thermal properties of the biocomposites were investigated. The results showed that the tensile strength, tensile modulus, flexural strength and flexural modulus increased with WF loading in the composites, and acetylation could not only further increase these properties, but also increase the impact strength and elongation at break. The incorporation of WF would weaken the thermal stability of PBAT, but the thermal stability of the biocomposite could be improved after WF acetylation. The cold crystallization temperature and hydrophobicity of the WF/PBAT samples would be increased with the increasing load of the WF, while the melting enthalpy and the crystallinity of the samples reduced gradually. A morphological analysis of the modified composites revealed that the matrix exhibited greater interfacial interactions with the WF compared to the WF/PBAT. Considering the much lower cost of WF compared to PBAT, the improved properties of WF/PBAT biocomposites will make it economically competitive with other commercial polymers, and these biocomposites should have much wider application areas.