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CCNE2 promotes cisplatin resistance and affects prognosis of head and neck squamous cell carcinoma by targeting MNAT1
The role of university entrepreneurship support and student diversity in student entrepreneurial intention: a social identity theory perspective
One of the most significant shortcomings of the extant literature is the dearth of conceptualizations and empirical testing pertaining to entrepreneurial diversity and the underlying social identities. Accordingly, this research aims to empirically investigate the influence of entrepreneurial support at the university level on students’ entrepreneurial intention from a diversity and social identity perspective. The research utilizes fsQCA (fuzzy set Qualitative Content Analysis) and a set of observable and underlying diversity factors (gender, age, previous academic performance, and parental educational attainment) to elucidate the causal structures that influence the formation of entrepreneurial intention among university students. The findings illustrate the multifaceted nature of the entrepreneurial intention formation, with first-generation status being a necessary condition for low entrepreneurial intention. The findings underscore the importance of university entrepreneurial support in the formation of entrepreneurial intention especially for younger students and first-generation students. The study contributes to the literature on entrepreneurial diversity and social identities in entrepreneurship by identifying the underlying factors that contribute to high and low entrepreneurial intention among university students.
Selection and validation of stable reference genes in potato infected by Pectobacterium atrosepticum using real-time quantitative PCR
Optimizing China’s carbon quota allocation for peak emissions: A novel AMLC framework tailored to regional dynamics
As China advances its carbon reduction efforts, the equitable and efficient allocation of initial carbon quotas among provinces has become increasingly critical. This study proposes a novel two-stage Adjusting Measures to Local Conditions (AMLC) framework that integrates regional development disparities and marginal abatement costs into the quota allocation process. Employing a PSO-LSSVM model for carbon emission estimation and a hierarchical clustering algorithm, this study categorizes 30 Chinese provinces into six distinct types, facilitating a regionally adaptive allocation strategy. Key findings include: (1) Between 2003 and 2022, carbon emissions exhibited a structural shift from energy-abundant, carbon-exporting provinces with inefficient industrial structures to energy-deficient, carbon-importing provinces, intensifying regional disparities. (2) Equity-based allocation schemes tend to favor regions with abundant carbon sinks, yet all provinces in the sixth category experience quota deficits; conversely, efficiency-based allocation disproportionately benefits initially efficient regions, exacerbating interprovincial disparities. (3) The AMLC framework enables 17 provinces across all clusters to achieve quota surpluses while significantly enhancing national green productivity, demonstrating its superiority in promoting high-quality economic development. These findings provide valuable insights for policymakers in designing macroeconomic strategies that balance equity and efficiency in carbon quota distribution, thereby supporting China’s transition toward peak emissions and sustainable growth.
Artery segmentation and atherosclerotic plaque quantification using AI for murine whole slide images stained with oil red O
Abstract Atherosclerosis is the leading cause of death in Western industrial nations. To study the etiology of plaque progression, atherosclerotic mouse models are widely used. Traditionally, analyzing the obtained histological whole slide images of Oil Red O-stained aortic roots required manual segmentation. To accelerate this process, an artificial intelligence-driven solution is proposed that comprises three stages: (1) defining the region of interest (ROI) of the aortic root using a YOLOv8l object detector, (2) applying supervised machine learning with ensembles of U-Net++ networks for artery segmentation using ROI masks, and (3) performing plaque segmentation within arterial walls with the unsupervised W-Net method. To establish a robust segmentation pipeline, we benchmark our methods using manually created masks ( $$\text {n}=6085$$ for artery segmentation, $$\text {n}=1089$$ for plaque segmentation). A key finding is that an ensemble of U-Net++ networks applied on ROI masks outperformed single network architectures. Through a novel combination strategy, the ensemble output can be easily modified, paving the way for a quick and robust application in the lab. Finally, a case study utilizing published mouse data ( $$\text {n}=373$$ slices) underscored the ability of our optimized pipeline to replicate human-made plaque predictions with a high correlation (Pearson’s $$\text {r}=0.91$$ ) and reproduce biological insights derived from manual analysis.
Repeatability of wildlife surveys for estimating abundance: A method to assess the consistency of detection probability and animal availability
A primary consideration of abundance studies that use unmarked animals is whether survey counts accurately reflect the population size or if unknown variation in animal movement or detection probability biases counts irrespective of population size. We posited that high repeatability in counts among temporally replicated surveys would indicate that counts are a good index of abundance. We temporally replicated 49 nocturnal spotlight surveys of white-tailed deer (Odocoileus virginianus) up to three times each (n = 128 total samples) to test the repeatability of this commonly used wildlife monitoring technique. Repeatability was high (R = 0.86), suggesting spring spotlight surveys provide a reliable index of deer population size in Iowa, USA. Fourteen percent of the variation among replicated counts was explained by day of year and, to a lesser degree, a vegetation green-up index. Detection probability was high (~0.70) early in the sampling season and declined considerably during the following 6 weeks. Deer abundance was greater at sites with higher percent landcovers of forest and hay/pasture and was lower at sites with higher landcover in crops. Our findings suggest deer managers should sample prior to green-up in the spring to maximize the proportion of the population that is detectable, and that accounting for seasonality on detection estimation is important for reliable abundance estimates if sampling occurs over a range of phenological progression. Finally, we show that temporal replication of surveys is a logistically feasible method to assess the reliability of abundance estimates from study designs that are normally conducted with single visits.
Simultaneous production of fatty acids and amino polysaccharides from Norway spruce hydrolysates using oleaginous Mucor circinelloides
Abstract Lignocellulose is an abundant raw material and renewable carbon source for the production of single cell oils which can replace plant-derived oils in food, feed, fuels, and oleochemicals. Mucor circinelloides produces both fatty acids and amino polysaccharides, such as chitin and chitosan. This study evaluates hydrolysates of Norway spruce (Picea abies) as a carbon source for their simultaneous production. Cultivation in spruce hydrolysate media yielded 15.8 g/L of biomass, with fatty acids comprising ~ 50% of the cell dry weight and amino polysaccharides up to 8.5%. The fatty acid methyl ester (FAME) content and fatty acid profile were comparable to glucose fermentation. Optimal harvesting times ranged from 72 to 120 h, depending on desired yields. These findings demonstrate that Norway spruce hydrolysates are a viable and sustainable substrate for microbial lipid and polysaccharide production, supporting their potential use in biotechnology and industrial applications.
Vibration control of a class of flexible mechanical systems with output constraints based on partial differential equations
Vibration suppression in flexible mechanical systems (FMSs) significantly enhances the precision and stability of equipment, extending its operational life. This technology is extensively applied across various sectors, including aerospace, robotics, and precision manufacturing. This paper introduces a robust control scheme leveraging a Partial Differential Equations (PDEs) model and Barrier Lyapunov Function (BLF), applied through backstepping technology to manage a flexible mechanical system modeled as an Euler-Bernoulli beam with a centrally attached rigid body. The control laws we have formulated are designed to effectively dampen vibrations and rotations, thereby ensuring system stability despite the presence of environmental disturbances. Throughout the control process, the system output consistently stays within the predefined safety limits. Comparative simulations further validate the effectiveness of the proposed control strategy, showing that it can effectively counteract unforeseen disturbances while ensuring that the output remains within the specified constraints.
Effect of processing on microstructure, mechanical properties, corrosion and biocompatibility of additive manufacturing Ti-6Al-4V orthopaedic implants
Retraction: Design and interactive performance of human resource management system based on artificial intelligence
Ecosystem services scenario simulation in Guangzhou based on the FLUS-InVEST model
Abstract The sustainable development of the region cannot be separated from the support of ecosystem services. By investigating the effects of potential land use and land cover change (LUCC) on these services in different scenarios, we can work towards protecting the ecological environment of urban areas, thus promoting the sustainable development of the region. This paper simulates the natural, ecological and development scenarios of Guangzhou in 2035 using the FLUS model based on LUCC of Guangzhou from 2015 to 2020; on top of the three scenarios, calculates the physical quantities of three ecosystem services—annual water yield, habitat quality, and carbon storage, through the InVEST model; and uses the GeoDetector model to identify the influencing Drivers. (1) Compared to 2020, the different land use types will change differently under the three scenarios in 2035; (2) The spatial distribution of ecosystem services in Guangzhou for the years 2020 and 2035 show similar patterns across three scenarios; (3) Based on the analysis of the driving factors behind Land Use and Land Cover Change (LUCC) in Guangzhou, it has been observed that population density has the most significant impact on LUCC.
Pan-cancer analysis and validation show GTF2E2’s diagnostic, prognostic, and immunological roles in regulating ferroptosis in endometrial cancer
Background Transcription initiation factor IIE subunit beta (GTF2E2) is a crucial component of the RNA polymerase II transcription initiation complex. There is a lack of more detailed research on the biological function of GTF2E2 in pan-cancer. Methods We conducted a comprehensive pan-cancer analysis using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) project. Employing a multi-pronged approach with tools including R, Cytoscape, TISIDB, cBioPortal, STRING, GSCALite, and CancerSEA, we investigated GTF2E2’s expression patterns, prognostic value, mutational landscape, functional enrichment, and immunological associations across 33 cancer types. Besides, we further validated the bioinformatic results through in vitro experiments in Uterine corpus endometrial carcinoma (UCEC), including western blotting (WB), cell proliferation assays and transwell. DCFH-DA, C11-BODIPY 581/591 and FeRhoNox-1 probes were performed to identify ferroptosis levels in vitro. Results GTF2E2 expression was significantly elevated in most cancers compared to normal tissues, with notable diagnostic potential (AUC > 0.7) in 20 cancer types. GTF2E2 expression varied across molecular and immune subtypes and correlated with tumor stage and patient age in several cancers. Functional enrichment analyses highlighted GTF2E2’s involvement in key cancer-related and immunological pathways. Notably, GTF2E2 promoted UCEC progression in vitro, and knockdown of GTF2E2 significantly inhibited the proliferation, migration and invasion of UCEC cells. Compared with the control group, GPX4 expression was down-regulated and ACSL4 expression was up-regulated in the GTF2E2-knockdown group. Knockdown of GTF2E2 also increased the intracellular levels of Fe2+, lipid peroxides (LPOs) and reactive oxygen species (ROS). Conclusions Our findings underscore GTF2E2’s multifaceted roles in cancer biology, highlighting its potential as a diagnostic biomarker, prognostic indicator, and immunotherapeutic target across various malignancies. This investigation has the potential to contribute significantly to a deeper understanding of the substantial involvement of GTF2E2 in human malignancies, particularly UCEC.
Effect of polystyrene nanoplastics on its toxicity and reproduction in Philodina roseola
Abstract Micro-nano plastics have emerged as a major ecological concern. The nanoplastics (NPs) pose a huge threat to microscopic animals. Our study aims to decipher the effect of polystyrene nanoplastics (PSNPs) of 50 and 100 nm sizes on a bdelloid rotifer (Philodina roseola). Both sizes of PSNPs were analyzed using field emission Scanning electron microscopy, Fourier transform Infrared spectroscopy, and Dynamic light scattering analyses. The LC50 values for 50 and 100 nm PSNPs at 48 h upon interaction with the rotifers were 16.36 and 22.94 mg/L respectively. The total protein and superoxide dismutase levels decreased with an increase in concentration in both PSNPs upon interaction at various concentrations (4, 8, 12, and 16 mg/L). Whereas the lipid peroxidase and reactive oxygen species levels increased with an increase in concentration for both PSNPs at similar concentrations. Further, both PSNPs were found to cause internal organ damage in rotifers. A delay in the hatching rate was observed when the rotifers interacted with both PSNPs in addition to the decrease in the hatching rate of F1 generation. Therefore, PSNPs pose a threat to the natural life cycle in the rotifers.
The impact of physical activity on subjective well-being: The mediating role of exercise identity and the moderating role of health consciousness
This study investigates the relationship between physical exercise and subjective well-being through a moderated mediation model. It examines how physical exercise influences subjective well-being, focusing on the mediating role of exercise identity and the moderating role of health awareness. The results show that physical exercise significantly enhances subjective well-being, with exercise identity fully mediating this relationship. Additionally, health awareness positively moderates both the relationship between physical exercise and exercise identity and the mediating effect of exercise identity on the link between physical exercise and subjective well-being. This research reveals the mechanisms through which physical exercise promotes well-being and provides theoretical support for advancing national fitness initiatives and improving public health.
Author Correction: A new cancer/testis long noncoding RNA, the OTP-AS1 RNA
Developing a multivariable prediction model to support personalized selection among five major empirically-supported treatments for adult depression. Study protocol of a systematic review and individual participant data network meta-analysis
Background Various treatments are recommended as first-line options in practice guidelines for depression, but it is unclear which is most efficacious for a given person. Accurate individualized predictions of relative treatment effects are needed to optimize treatment recommendations for depression and reduce this disorder’s vast personal and societal costs. Aims We describe the protocol for a systematic review and individual participant data (IPD) network meta-analysis (NMA) to inform personalized treatment selection among five major empirically-supported depression treatments. Method We will use the METASPY database to identify randomized clinical trials that compare two or more of five treatments for adult depression: antidepressant medication, cognitive therapy, behavioral activation, interpersonal psychotherapy, and psychodynamic therapy. We will request IPD from identified studies. We will conduct an IPD-NMA and develop a multivariable prediction model that estimates individualized relative treatment effects from demographic, clinical, and psychological participant characteristics. Depressive symptom level at treatment completion will constitute the primary outcome. We will evaluate this model using a range of measures for discrimination and calibration, and examine its potential generalizability using internal-external cross-validation. Conclusions We describe a state-of-the-art method to predict personalized treatment effects based on IPD from multiple trials. The resulting prediction model will need prospective evaluation in mental health care for its potential to inform shared decision-making. This study will result in a unique database of IPD from randomized clinical trials around the world covering five widely used depression treatments, available for future research.
Interactions among Cupressaceae pollen, air pollutants and meteorology in the urban and suburban areas of Beijing, China
Identification of novel compound heterozygous variants in the PEX10 gene in a Han-Chinese family with PEX10-related peroxisome biogenesis disorders
The peroxisome biogenesis disorders (PBDs) are a group of rare inherited autosomal recessive diseases characterized by motor and cognitive neurological dysfunction, hypotonia, seizures, feeding difficulties, retinopathy, sensorineural hearing loss, hepatic and renal abnormalities, and chondrodysplasia punctata of long bones, and the clinical expression is variable. Exome sequencing and Sanger sequencing were used to identify the genetic defect for PBDs in a two-generation non-consanguineous Han-Chinese pedigree. Compound heterozygous variants, a novel splicing variant c.113-2A>G and a reported substitution c.890T>C (p.Leu297Pro), in the peroxisomal biogenesis factor 10 gene (PEX10) were detected. The splicing variant c.113-2A>G led to a canonical splice acceptor site inactivation, exon 2 skipping, and in-frame deletions (p.Ala39_Gly65del). The three patients had similar phenotypes of milder PBDs, which were further genetically determined as PBD6B. The findings extend the PEX10 variant spectrum and may provide new insights into PBDs causation and diagnosis, with implications for genetic counseling and clinical management.