Browse Articles

Characterization and stability of plasmid DNA calcium nanoparticles using a simple formulation for gene therapy

Impact of excessive environmental information disclosure on stock price crash risk

With the deepening of carbon peak and carbon neutrality (“dual carbon”) initiatives, corporate responsibility for environmental information disclosure has become imperative. However, due to imperfect laws and regulations, companies may have incentives to over-disclose environmental information, which could trigger stock price crashes. This study investigates the behavior of excessive environmental information disclosure among A-share listed companies in China. Using a sample of A-share firms that published social responsibility reports from 2015 to 2023, we employ threshold effect and quantile regression models to verify the presence of “greenwashing” components in environmental textual disclosures. A panel fixed-effects model is further adopted to examine the potential impact of excessive environmental information disclosure on stock price crash risk. The findings reveal that corporate environmental disclosures contain non-substantive, embellished content-indicative of greenwashing-and that such behavior significantly exacerbates stock price crash risk, particularly in manufacturing industries. The mechanism lies in the fact that excessive textual disclosure reduces information quality and transparency, thereby amplifying irrational investment behaviors. Conversely, effective environmental disclosure practices are shown to mitigate crash risk. Further analysis demonstrates that reducing ownership concentration, increasing managerial shareholding, and enhancing the role of independent directors in corporate governance can improve the quality of environmental disclosure and curb over-disclosure. This study provides a novel analytical perspective on environmental textual disclosure and offers practical insights for guiding rational investor decision-making.

Nanotextured light modulation for flexible OLEDs with 370% enhanced EQE and angular color stability

Correction: Early warning of regime switching in a financial time series: A heteroskedastic network model

SLC11A1 can activate TGF-β1 signaling pathway to resist ferroptosis in colorectal cancer

Brand public opinion data analysis method based on deep learning

With the rapid development of Internet information technology and digital technology, various network platforms and media are showing a vigorous growth momentum. The powerful power of online public opinion has an immeasurable impact on brand awareness, consumption attitude, and decision-making of consumer groups. For brand owners, responding to sudden online public opinion has become an important issue and a new challenge in the current era. This article mainly focuses on Weibo comments, selects specific brand A, and tracks topic data related to public opinion events of brand A within a certain time range. The emotion dictionary is crucial in analyzing public opinion events using the Latent Dirichlet Allocation (LDA) topic model. This study aims to enhance the emotion dictionary by employing algorithms that leverage topic words and benchmark words, specifically in the context of Dalian University of Technology. The effectiveness of the improved emotion dictionary will be demonstrated through its integration with pre-trained word vectors, utilizing a Bidirectional Encoder Representations from Transformers (BERT) linear sentiment classification model. By combining these methods, the study seeks to provide more accurate sentiment analysis and deeper insights into public opinion. Finally, sentiment orientation analysis is conducted.

Advancing skin cancer diagnosis with deep learning and attention mechanisms

The use of carbogen for interruption of febrile seizures - the randomized controlled CARDIF trial

Febrile seizures are the most common seizure disorders in children. Fever-induced hyperventilation and subsequent hypocapnia may precipitate febrile seizures. In preclinical studies and in individual children, increasing CO 2 partial pressure has shown potential to terminate febrile seizures. We hypothesized that the use of carbogen (5% CO 2 plus 95% O 2 ) in the home environment would be an effective and safe treatment for recurrent febrile seizures. The CARDIF (CARbon DIoxide against Febrile seizures) trial is a randomized, monocentric, prospective, double-blind, placebo-controlled, crossover study to determine whether short-term inhalation of carbogen in the home environment can stop febrile seizures. 100% oxygen was used as a placebo control. We included children aged 0.5 to 5.0 years who presented after a first febrile seizure in the absence of severe organ or neurological disease, pathological EEG changes, or a history afebrile seizures. We noted parent-reported seizure duration, benzodiazepine use, and any serious adverse events. We enrolled n = 92 patients. In n = 20 children, at least one recurrent febrile seizure was treated with either carbogen or oxygen . Six of these children received both carbogen and oxygen in a planned crossover design. The febrile seizure was terminated in 5/15 episodes on carbogen and in 8/11 episodes on oxygen (Fischer’s exact test; p = 0.11). Children with ≥2 recurrent febrile seizures completed the crossover arm. In these children, febrile seizures stopped during carbogen administration in 3/6 cases and during oxygen administration in 5/6 cases. In conclusion, carbogen did not interrupt acute febrile seizures more often than placebo . Home caregivers had difficulty determining when a seizure had stopped. Trial registration ClinicalTrials.gov NCT01370044

Confocal Raman microspectroscopy imaging reveals structural protein reorganization in human intracranial aneurysm tissue

Testing oral nicotine pouches versus nicotine replacement therapy for cigarette harm reduction in Appalachia: The ARISE study protocol

Background With the highest cancer incidence and mortality rates in the country, rural Appalachia has experienced a decades-long health decline, due in part to high smoking rates. Cigarette smoking prevalence exceeds 30% in much of the region. Oral nicotine pouches (ONPs), which contain nicotine but no tobacco, present an unexplored opportunity to reduce cigarette smoking and cancer incidence. Objectives We outline the protocol for the Appalachian Research to Impact Smoking’s Effects (ARISE) study, a randomized controlled trial to determine whether ONPs affect cigarette smoking patterns short- and long-term, and to evaluate their abuse liability versus nicotine replacement therapy (NRT) in a large sample of Appalachian smokers (clinicaltrials.gov: NCT06763536). Methods Between 2025 and 2029, we will recruit 1,000 adult smokers living in rural Appalachian counties across 11 states. Participants will be identified via media outreach, mobile cancer screening, community events, and respondent-driven sampling, then randomized to ONP or NRT and complete four study phases: Baseline, Sampling, Switch, and Observation. In the Sampling phase, participants will receive varied flavors and nicotine strengths of their assigned product and select preferred options for use. During the Switch Phase, they will attempt to quit smoking and switch completely to their assigned product. The Observation phase will monitor tobacco use after discontinuation of study products. Study procedures will be conducted online and by mail, including surveys, expired carbon monoxide verification, and product delivery. The primary outcome is 7-day biochemically verified cigarette abstinence at the end of the Switch Phase. Secondary outcomes include switching rates, product appeal, craving, withdrawal, dependence, and purchases during the Observation phase. An intention-to-treat log-binomial regression model will estimate the effect of intervention assignment on cigarette abstinence. Conclusions Results will inform whether and how ONPs should be regulated, approached clinically, and used in public health interventions to reduce the burdens of cigarette smoking in Appalachia.

Impact of land use land cover on microplastic accumulation in high-altitude freshwater lakes of the central Himalayas

Effectiveness of vestibular incision subperiosteal tunnel access (VISTA) technique with or without A-PRF in treatment of multiple adjacent gingival recession defects (MAGRD): A 12 months CBCT study

Objectives In order to treat MAGRD in the maxillary anterior region, the VISTA approach was evaluated and compared with and without A-PRF. Materials and methods A split mouth RCT was designed with 216 MAGRD that were assigned to VISTA alone and VISTA with A-PRF. The complete root coverage (CRC) and gingival thickness (GT) were measured using CBCT at baseline and 12 months post-operatively, while the clinical parameters of probing depth (PD), clinical attachment level (CAL), width of keratinized gingival (WKG), gingival recession depth (GRD), and gingival recession width (GRW) were recorded at baseline, 6 months, and 12 months. Results From baseline to 12 months, there was a significant decrease in the mean values of GRD and GRW with an increase in WKG. CBCT scans showed a significant increase in GT mean values. According to these results, the Test group’s CRC was higher (95.92%) than the Control groups (85.02%). Conclusions In contrast to the Control group, the Test group demonstrated superior MAGRD resolution in achieving a decrease in GRD and GRW as well as a higher increase in WKG and GT. These findings resulted into a substantially more CRC for the Test group. Trial registration Registration no. CTRI/2022/09/045845. Registered on: 26/09/2022

In tendons, differing physiological requirements lead to distinct patterns of MMP-1 degradation

Abstract Collagen fibrils from high-stress, energy-storing tendons critical to locomotion are smaller in diameter with increased intermolecular crosslinking compared to fibrils from low-stress, positional tendons. This results in distinct loading mechanics thought to limit fatigue damage in energy-storing tendons. However, there appears to be a functional trade-off with energy-storing tendons also having reduced remodeling ability. Energy-storing tendons have lower collagen turnover and increased injury rates compared to positional tendons. In a recent study, a causative factor for this lower collagen turnover was suggested: resistance to degradation by MMP-1. To validate the prior study’s results obtained from single fibrils, the current study undertook population level assessment of fibril degradation by MMP-1. Predictive degradation models were created to assess fibril diameter distribution changes. Positional and energy-storing tendon sections were incubated for 24 h with buffer or MMP-1, imaged with scanning electron microscopy, and analysed with a custom pipeline for piece-wise fibril measurement. Enzyme treated sections showed evidence of degradation with reduced fibril diameter, decreased alignment, increased curvature, and decreased D-band length. Energy-storing tendon fibrils were more resistant to enzymolysis, with only the large diameter fibril subpopulation affected by MMP-1 (15% diameter reduction compared to control), while the entire population of positional tendon fibrils decreased in diameter (41%). Comparison to model predictions confirmed a linear relationship of degradation with fibril size. Larger fibrils experienced greater diameter decreases combined with increased longitudinal diameter variation and D-band decreases. Crosslinking is thought to be responsible for both fibril type and size findings, the latter suggesting higher density crosslinking in the fibril core.

Investigating adaptation to environmental variability in forest trees through molecular phylogenetic analysis

We conducted a molecular phylogenetic analysis of the abiotic stress response in 13 key European forest species ( Fagus sylvatica L., Quercus robur L., Quercus ilex L., Quercus pubescens Willd., Quercus suber L., Quercus lobata L., Juglans regia L., Populus trichocarpa L., Pinus taeda L., Pinus nigra J.F. Arnold, Pinus pinea L., Pinus pinaster Aiton and Abies alba Mill.) to clarify how different abiotic stressors have influenced their adaptation. The study on the evolution of abiotic stress responses in these species, seeks to uncover the factors driving their distinct evolutionary pathways of adaptation. We created the dataset by collecting data from genomic dataset on genes relevant to the response to abiotic stress in the target species dataset. Then, we used the data in the dataset to search for possible orthologs in the studied species dataset. A matrix was created with sequences of each identified ortho-group, closely related to the analyzed genes, and phylogenetic relationships were reconstructed using the maximum likelihood (ML) method. Pairwise estimates of synonymous and nonsynonymous substitutions per site (Ks and Ka, respectively) were calculated using the ML method. Analysis of 616 genes associated with abiotic stress response revealed 347 genes in angiosperms species, with F. sylvatica having the highest count, and 269 genes in conifers, where A. alba contributing the most. Drought stress exhibited the highest number of shared genes, while freezing stress showed the least. Substitution rate analysis indicated higher average values in angiosperms species, with a stronger signature of adaptive evolution in conifers, as suggested by the higher Ka/Ks ratio. The study unveils distinctive patterns in the evolutionary dynamics of molecular responses to abiotic stresses between the 13 key forest tree species. Lower substitution rates in conifers suggest unique constraints, likely influenced by larger genomes and ancient lineage divergence. The prevalence of Ka/Ks values below unity emphasizes strong selective constraints, highlighting the conservation of abiotic stress response mechanisms across diverse lineages.

Correction: Gradient vortex dynamics in 3D-weak turbulence

Identification and classification of oil and gas pipeline intru-sion events based on 1-D CNN network

Oil and gas pipeline security is critical to national infrastructure, yet existing monitoring systems often lack the sensitivity and real-time responsiveness required to detect subtle intrusion events. This study presents a novel multimodal sensing and interaction frame-work that integrates phase-sensitive optical time-domain reflectometry (φ-OTDR)–based distributed acoustic sensing (DAS) with an optimized one-dimensional convolutional neural network (1-D CNN) architecture. The approach leverages both raw fiber optic vi-bration signals and carefully selected handcrafted features, enabling robust automatic in-trusion classification across multiple event types including manual tapping, mechanical excavation, and human footsteps. By incorporating transfer learning from publicly avail-able human activity datasets, the model achieves enhanced feature generalization, result-ing in a classification accuracy exceeding 95%. This work demonstrates the potential of combining advanced multimodal sensing technologies with deep learning-based interac-tive analytics for real-time pipeline security monitoring, paving the way for intelligent in-frastructure protection systems. Future efforts will focus on expanding dataset diversity, integrating multi-sensor fusion, and enhancing adaptive interaction capabilities for field deployment.

Targeting biological age with bioactive, microbiota-accessible nutritional complexes: a pilot study on healthspan extension in medically healthy adults

Promoting or pressurising participation? A discourse analysis of online patient information resources about prehabilitation before cancer treatment

Prehabilitation aims to improve outcomes by optimising health before treatment. Interventions typically target diet, physical activity and/or mental health. Communicating the benefits of prehabilitation may influence patients’ engagement in interventions. However, the evidence for prehabilitation prior to cancer treatment is replete with uncertainties. Synthesising and communicating the efficacy of prehabilitation is challenging. This study aims to understand how evidence, motivation and accessibility are balanced in online patient-facing resources about prehabilitation. Databases, search engines and websites (identified by prehabilitation researchers) were systematically searched for patient-facing resources from UK organisations about prehabilitation before cancer treatment. Search strategies were built from non-technical synonyms for three terms: prehabilitation, cancer, and patient information. Results were screened against predefined eligibility criteria. The Quality Evaluation Scoring Tool assessment informed purposive sampling. Included resources were interrogated using discourse analysis. Screening of 3394 search results identified 68 resources from which a sample of 25 was analysed. Two themes summarised how resources presented prehabilitation to patients. Resources influenced rather than informed patients about participation in prehabilitation. Benefits were presented with emphasis, certainty and authority whereas limitations or alternatives were rarely discussed. The information focused on individual motivation rather than acknowledging patients’ resources or systemic barriers. Overall, it functioned to convince patients to participate in prehabilitation. Promoting prehabilitation in patient-facing literature may be beneficial. However, this relies upon two assumptions: firstly, that this communication approach is effective at increasing participation in practice, and secondly, that prehabilitation itself is ‘beneficial’. When outcomes prioritised by patients are not established, and evidence remains uncertain, this is not guaranteed. Overpromoting the benefits of prehabilitation risks giving patients unrealistic expectations. Allocating responsibility to individuals may risk introducing patient blame and guilt in the event of treatment complications. Further research is required to understand how patients experience information resources and to define the patient-centred outcomes of prehabilitation.

African swine fever vaccine ASFV-G-ΔI177L induces solid protection in four-week-old piglets

Abstract African swine fever (ASF) is an important disease of swine currently affecting pig production worldwide. Vietnam is, currently, the only country where commercial live attenuated vaccines are being freely used in the field. One of these vaccines is based in the use of the ASFV-G-ΔI177L strain, a recombinant virus developed by a partial deletion in the I177L gene from the highly virulent parental strain Georgia 2010. The commercial version of the vaccine was originally limited to use in pigs between 8 and 10 weeks of age, which significantly restricts its use. In this report, we demonstrate that pigs can be vaccinated as early as the fourth week of age, producing an efficacious immune response that fully protects the animals against the challenge with the virulent Vietnamese field strain TTKN/ASFV/DN/2019 and thus increasing the vaccine’s usage to pigs 4–10 weeks of age. Several groups of four-week-old pigs were intramuscularly (IM) vaccinated with a single dose of a commercial vaccine containing 10 2.6 HAD 50 of ASFV-G-ΔI177L and IM challenged 28 days later with 10 2 HAD 50 of TTKN/ASFV/DN/2019. All the vaccinated animals remained clinically normal after vaccination, demonstrating no presence of residual virulence of ASFV-G-ΔI177L in animals of this age. In addition, all vaccinated animals remained protected after the challenge, showing no clinical signs associated with ASF during the observational period. These results corroborate the safety and efficacy of the ASFV-G-ΔI177L vaccine strain when used in pigs as early as four week of age.

Enhancing mathematical modeling competencies through AI-powered VR

Background Improving students’ problem-solving skills is one of the primary objectives of mathematics education. Problem-solving skills are closely related to the mathematical modeling process and the competencies required in this process, which are essential in various aspects of daily life. Method The study was designed as a mixed design. A quasi-experimental design to examine the impact of an instructional model based on an artificial intelligence-supported virtual reality (VR) application on students’ modeling competencies for quantitative data and opinion and observation forms were used for qualitative data. These competencies included inductive, deductive, pragmatic, planned, and problem-solving thinking. The study involved 30 students from two 6th-grade classes at a Science and Art Center located in the western part of Turkey. One class served as the experimental group (f = 15) and engaged with the AI-pVR approach, while the other class served as the control group (f = 15) and followed the traditional teaching model. In the study, independent samples t-tests and ANCOVA were performed for quantitative analysis, and to check ANCOVA assumptions, normality, homogeneity of variances, linearity, and homogeneity of regression slopes were examined. Descriptive analysis was also performed for qualitative analysis. Results The findings of this study revealed that the intervention had a significant large effect (η² = 0.37) on students’ mathematical modeling competencies. Among the components of modeling competence, understanding and simplifying the problem, mathematizing, working mathematically, interpreting, and verifying all exhibited significant large effects (η² = 0.33, 0.19, 0.32, 0.39, respectively), while defining the problem showed a moderate effect (η² = 0.15). The variability observed in some measurements may be attributed to limitations in the number of practice trials and the small sample size. However, the educational process carried out within the scope of this study has shown that students have made significant progress in their mathematical modeling skills. Students have stated that they have meaningfully grasped the basic steps of the modeling process, such as analyzing real-life problems, relating these problems to mathematical structures, creating models, solving the model they have created step by step, interpreting and verifying the results. In addition, students have developed a significant awareness in sharing their models with their friends and teachers, receiving meaningful feedback, developing new models for different life situations, and establishing connections between real life and mathematics. Conclusion The results indicated that the integration of the AI-pVR instructional approach significantly improved students’ modeling competencies and related sub-dimensions. These sub-dimensions were problem understanding and simplification, mathematizing, working mathematically, interpreting, and verifying. Based on these findings, it is recommended that artificial intelligence applications, which can positively influence various areas such as competencies, should be incorporated into teachers’ lessons and even included in curriculum programs.