Browse Articles

Combination of ultrasonography and MRI for preoperative prediction of lymph node metastasis in tongue squamous cell carcinoma: An exploratory study

Preoperative depth of invasion (DOI) is a critical predictor of cervical lymph node metastasis (CLNM) in tongue squamous cell carcinoma (TSCC). Ultrasonography (US) offers high accuracy for shallow tumors, whereas magnetic resonance imaging (MRI) provides superior visualization of deeper structures. However, each modality has limitations. This retrospective, exploratory study aimed to investigate a combined strategy leveraging the complementary strengths of both modalities to improve preoperative CLNM prediction. The study included 46 patients with TSCC who underwent radical surgery between September 2014 and August 2019. Correlations between US-derived DOI (usDOI), MRI-derived DOI (mrDOI), and pathological DOI (pDOI) were assessed using Pearson’s product-moment correlation. Agreement was evaluated by Bland–Altman analysis. A grid search approach identified the optimal usDOI threshold for switching to mrDOI, and predictive performance for CLNM was evaluated using receiver operating characteristic (ROC) analysis with the area under the curve (AUC). Both usDOI and mrDOI showed strong correlations with pDOI (r = 0.956 and r = 0.958, respectively). However, usDOI demonstrated smaller measurement bias (mean difference: 0.88 mm) compared to mrDOI (2.43 mm). Bland–Altman plots revealed that usDOI tended to underestimate pDOI when the mean DOI exceeded 10 mm. Grid search analysis determined an optimal threshold of 7 mm for switching from US to MRI measurements. The combined DOI strategy —using usDOI for DOI ≤ 7 mm and mrDOI for DOI > 7 mm— yielded a numerically higher AUC (0.694) compared to either modality alone (usDOI: AUC = 0.682; mrDOI: AUC = 0.673). This study demonstrates the potential value of a conditional imaging strategy that applies US for shallow lesions and MRI for deeper ones. By capitalizing on the strengths of each modality, this approach offers a logical framework for improving the accuracy of preoperative CLNM prediction in TSCC. Larger, prospective studies are warranted to validate these findings.

Chlorinated bis-4-hydroxycoumarins suppress flavivirus replication by inhibiting dengue virus type 2 translation and replication

Abstract Dengue virus (DENV) remains a major global health threat, and no clinically approved antiviral therapy is currently available. Halogenated biscoumarins have been reported as versatile antimicrobial and antiviral agents. Here, we screened eleven halogenated biscoumarin derivatives against DENV and identified compounds 3 and 4—bearing chlorine substitutions at the 3- or 4-position of the phenyl moiety—as the most potent inhibitors of DENV2, with EC 50 values of 3.62–9.72 µM and 4.62–10.88 µM, respectively, and selectivity indices (SI) up to 20.97. Both compounds also inhibited all four DENV serotypes and Zika virus (ZIKV) with comparable efficacy. Mechanistic analyses demonstrated that compounds 3 and 4 significantly suppressed viral translation and RNA replication in infectious and replicon models. Long-term passaging generated mutations in NS4B, although these substitutions did not confer resistance, was involved in self-dimerization to curvature formation of ER-derived spherules, which may reflect adaptive changes linked to host interaction. In vitro enzymatic assays further indicated that the viral NS5 methyltransferase is a potential target, with IC 50 values of 4.60 ± 0.83 µM and 3.17 ± 0.25 µM for compounds 3 and 4, respectively, and both compounds inhibited NS3 protease activity by > 89% at 50 µM. Collectively, these results identify chlorinated biscoumarins as promising antiviral scaffolds that impair flaviviral translation and replication, supporting their further optimization and in vivo evaluation.

Oxygen Vacancy‐Driven Asymmetrical Charge Distribution on Bi‐O‐Sn Sites in Sn‐Doped Bi ₂ MoO ₆ for Efficient Photocatalytic CO ₂ ‐to‐CH ₄ Conversion

Abstract Efficient proton‐coupled electron transfer (PCET) at tailored active sites is beneficial for photocatalytic CO 2 reduction, yet the relationship between catalytic sites and performance remains unclear. Herein, p ‐block Sn is introduced into the Bi 2 MoO 6 lattice (Sn‐BMO) via Bi site substitution to construct a novel oxygen vacancy (Ov)‐Bi‐O‐Sn structure, where high‐valence Sn induces Ov formation by lowering the Bi valence state, thereby creating a charge‐asymmetrical region. This unique configuration promotes PCET: Sn acts as H 2 O oxidation site, enabling proton transfer to proximal Bi site connected to Ov that preferentially traps electrons to convert CO 2 . Furthermore, the electronic structure of Bi is modified to optimize Bi 6 p ‐C 2 p hybridization for formation of the key intermediate *CHO with low energy barrier. Consequently, Sn‐BMO exhibits a remarkable CH 4 evolution rate of 207.3 µmol g −1 h −1 with 95.7% CH 4 selectivity in pure water, achieving a record apparent quantum efficiency of 9.4% at 420 nm. This work provides a novel approach to design charge‐asymmetrical active site in multisite catalysts, elucidating how p ‐block elements influence catalytic performance in CO 2 photoreduction.

Blockchain adoption in remanufacturing under carbon tax policies: A game theory analysis of industry dynamics and consumer impact

Within the context of China’s “dual carbon” goals, remanufacturing of waste products has garnered significant government interest due to its potential to reduce carbon emissions during production and alleviate environmental pollution. This study analyzed the impact of carbon tax policies (carbon tax and carbon tax reduction) and consumer demand on the blockchain introduction strategies of manufacturers and remanufacturers by constructing a two-party evolutionary game model of “manufacturers-remanufacturers”. The key findings are as follows: (1) Under carbon tax policies, manufacturers and remanufacturers in different industries exhibit divergent strategies regarding blockchain adoption. Specifically, manufacturers in industries lacking carbon emission advantages are more inclined to introduce blockchain technology. Conversely, remanufacturers in industries possessing carbon emission advantages demonstrate a stronger preference for adopting blockchain technology. (2) Government strategies involving tax reductions and exemptions can effectively incentivize manufacturers and remanufacturers to adopt blockchain, thereby boosting the sales of remanufactured products and the recycling of waste products. (3) Consumers’ environmental awareness and acceptance of remanufactured products significantly influence manufacturers’ and remanufacturers’ blockchain adoption decisions, although the nature of this impact varies across industries. Based on these insights, this paper proposes targeted strategies to facilitate the low-carbon development of the manufacturing industry. Different from previous studies, this study considers the external factors of “blockchain applications” to further enrich the research on remanufacturing decisions considering different external factors under carbon tax policies. Based on the application of blockchain technology, the impact of carbon tax policies on remanufacturing decisions in different industries is further compared and analyzed.

Visual perception based deep learning transformers for classifying paintings and photographs through feature extraction

In their own words: A qualitative examination of student experiences with high-impact practices during the second-year transition

Researchers and practitioners have called for the use of high-impact practices to support student engagement and development in higher education institutions in the United States. Many studies have used quantitative methods to validate the importance of these practices in supporting broad academic and social outcomes, but fewer have used qualitative approaches to understand the range of outcomes that students perceive they are obtaining from these experiences. The development and evaluation of high-impact practices cannot be fully realized without leveraging student voices to understand the range of potential benefits that students acquire. Identifying practices that students perceive as valuable to their learning is essential for cultivating meaningful experiences that support student development and improve affective dispositions toward educational experiences. Second-year students are a particularly understudied population in higher education, facing unique challenges such as the “sophomore slump” that warrant increased access to high-impact practices. To complement existing literature on high-impact practices and second-year student development, this study applied a phenomenographic approach to analyze students’ experiences in a summer-bridge program that supported students (n = 133) through the second-year transition. Using weekly written reflections as a primary data source, student experiences and outcomes were examined across four dimensions of student development: academic, social, professional, and personal. Students reported a variety of positive outcomes from their consistent participation in these practices, with a range of benefits observed primarily in their academic, personal, and social enrichment experiences. Perceptions of professional development outcomes were notably less salient and less detailed compared to the other three dimensions, suggesting that the types of activities students chose in this category may have offered fewer immediate benefits. Implications for cultivating meaningful experiences in higher education that can support second-year students’ transition and development are discussed.

Enhanced diagnostic tools for visceral leishmaniasis using kinase based antigens in Brazilian human and canine samples

Self-esteem in crisis: Psychosocial adaptation and masculine identity among Chinese men with azoospermia

Background Azoospermia affects 1% of men and 10–20% of infertile males, yet the psychosocial mechanisms underlying self-esteem impairment remain poorly characterized. Guided by Connell’s Masculinity Theory and Bury’s Biographical Disruption Framework, this mixed methods study examined self-esteem experiences among Chinese men with azoospermia. Methods An explanatory sequential design was employed. Phase 1 surveyed 216 men using Rosenberg’s Self-Esteem Scale, with multiple regression identifying predictors. Phase 2 involved semi-structured interviews with 16 purposively sampled participants, analyzed through thematic analysis. Integration of quantitative and qualitative findings provided comprehensive interpretation. Results Quantitative analysis revealed moderate self-esteem overall (mean = 30.18 ± 3.99), with 10.19% exhibiting low self-esteem. Significant predictors included monthly income ( β  = 0.210, p  < 0.001), family harmony ( β  = 0.141, p  = 0.028), and attitudes toward childbearing discussions ( β  = 0.159, p  = 0.014). Qualitative findings identified five themes, including economic burden, family dynamics, social stigma, treatment uncertainty, and cumulative psychological impacts. Integration demonstrated financial capacity’s dual role as both practical enabler and symbolic compensation for perceived masculine failure. Conclusions Self-esteem in azoospermic men is shaped by interconnected economic, familial, and social factors. Clinical interventions should integrate financial counseling, family-based emotional support, and culturally tailored stigma reduction, highlighting the value of mixed methods in understanding male infertility psychosocial dimensions.

Porous media grouting diffusion mechanism based on tailings slurry phase change characteristics

Hyalucidin A: A Bacterial RiPP Featuring a Benzofuranoindoline Motif Biosynthesized by Tandem P450 Catalysis

Abstract Despite the emergence of P450‐modified ribosomally synthesized and post‐translationally modified peptides (RiPPs) as a distinct and rapidly expanding class of natural products, their structural diversity has been limited to scaffolds catalyzed solely by single P450 enzymes. To access greater structural complexity, we targeted unexplored biosynthetic gene clusters encoding two P450s. This effort led to the discovery of hyalucidin A, which features the most intricate polycyclic cross‐linked architecture among reported P450‐RiPPs and represents the first bacterial RiPP containing a benzofuranoindoline motif. Through stepwise enzymatic analysis, combinatorial biosynthesis, and precursor peptide engineering, we deciphered the cooperative function and substrate tolerance of both P450s. Our work expands the biosynthetic logic of P450‐driven cyclization and provides a platform for engineering complex macrocyclic peptides.

Bacterial community associated with the surface and inside of centipede forcipules: Identification and characterization

Background In tropical to subtropical regions, centipede bites may prompt medical attention, with manifestations largely reflecting venom-related discomfort, although infections, including rare fatal necrotizing soft tissue infection (NSTI), have been reported. However, no reports are available on the commensal bacteria on centipede forcipules. Objectives This study aimed to investigate bacterial species residing on and in centipede forcipules and their potential role in post-bite infections. Methods Nine Scolopendra mutilans , three Scolopendra japonica , and two Bothropolys rugosus were collected from three regions in Japan. The bacterial composition of their forcipules was analyzed using 16S ribosomal ribonucleic acid gene sequencing and microbiome analysis. Findings A diverse bacterial community was observed on the centipede forcipules. Among the NSTI-associated genera examined ( Escherichia, Staphylococcus, and Streptococcus ), only Staphylococcus was identified as a minor population. Conclusion This study provides the first evidence that some bacteria found on centipede forcipules have been previously isolated from centipede bite infections. The risk of infection from bacteria on centipede forcipules during a centipede bite appears low. However, the presence of diverse bacterial species emphasizes the importance of thoroughly cleaning centipede bite wounds to prevent secondary infection.

Automated detection of giant cell arteritis from temporal artery biopsy specimens using deep learning approaches

Adaptive and migration-enhanced tree seed algorithm for multi-threshold CT image segmentation and lung cancer recognition

The Tree-Seed Algorithm (TSA) is a swarm intelligence algorithm inspired by the propagation relationship between trees and seeds. However, the original TSA is prone to premature convergence and becomes trapped in local optima when addressing high-dimensional, complex optimization problems, limiting its practical efficacy. To overcome these limitations, this paper proposes an Adaptive and Migration-enhanced Tree Seed Algorithm (AMTSA), which integrates three key mechanisms to significantly enhance performance in solving complex optimization tasks. First, to effectively evade local optima, an adaptive tree migration mechanism is designed to dynamically adjust the search step-size and direction based on individual fitness, thereby improving global exploration. Second, to enhance the algorithm’s adaptability and efficiency across different search stages, an adaptive seed generation strategy based on the dynamic Weibull distribution is introduced. This strategy enables flexible control over the number of seeds and promotes a balanced search throughout the solution space. Third, to mitigate convergence oscillations during the global search, a nonlinear step-size adjustment function inspired by the GBO algorithm is incorporated, which effectively improves convergence stability by responding to the iteration progress. Rigorous testing on the IEEE CEC 2014 benchmark functions demonstrates that AMTSA’s overall performance surpasses not only state-of-the-art optimizers like JADE and LSHADE but also recent TSA variants, including STSA, fb-TSA, and MTSA. To further validate its robustness in high-dimensional spaces, AMTSA was tested on 30 benchmark functions at 30, 50, and 100 dimensions. Results show that AMTSA ranked first in the number of functions optimized best and exhibited the fastest convergence speed among all compared algorithms. In a real-world application, AMTSA was employed to optimize multi-threshold segmentation for lung cancer CT images. The resulting AMTSA-SVM classification model achieved an accuracy of 89.5%, significantly outperforming models such as standard SVM (76.22%), DE-SVM (82%), GA-SVM (79.33%), TSA-SVM (84.44%), and JADE-SVM (89.12%). In conclusion, the proposed AMTSA, by integrating adaptive migration, dynamic seed generation, and nonlinear step-size control, successfully addresses the inherent deficiencies of the native TSA, offering a more efficient and robust tool for solving high-dimensional, complex optimization problems. The AMTSA source code will be available at www.jianhuajiang.com .

Cultural ecology perspective on mechanisms influencing the spatial morphology of traditional villages in Suichang County, China

Predicting grain growth kinetic in steels using machine learning and XAI for mechanical properties

Understanding and controlling grain growth kinetics in steels is crucial for optimizing mechanical properties during thermomechanical processing. However, traditional empirical models often fail to account for the complex, nonlinear interactions between alloying elements and processing parameters. In this study, we introduce a novel machine learning (ML) based framework that predicts austenitic grain growth behaviour directly from chemical composition and process conditions, utilizing a comprehensive dataset of 1039 experimentally validated samples. Among various algorithms tested, the XGBoost model demonstrated exceptional predictive capability, achieving an R 2 value of 0.9728 after hyperparameter optimization. Feature selection methods (Pearson correlation, CfsSubset, ReliefF) and SHAP-based explainable AI analyses were employed to identify the most influential parameters, revealing temperature, initial grain size, and holding time as dominant factors. Experimental validation was conducted on 316L stainless steel samples annealed at 1100 °C. The predicted grain sizes showed strong agreement with experimental measurements, and the observed hardness variations followed the expected Hall–Petch behaviour. This study demonstrates the first integrated ML and experimental approach for predicting grain growth kinetics in steels, offering a powerful tool for alloy design and process optimization. Future work will extend this framework to additional process variables and alloy systems.

Prolonged exposure to polyvinylpyrrolidone heightens DNA breaks in human sperm

An immunofluorescence microscopy assay to discriminate distinct expression patterns of HIV-1 Gag and Nef proteins in HIV-1 provirus-harboring cells

Over 95% of HIV-1 proviruses are defective and were once considered clinically irrelevant. However, growing evidence shows that these defective proviruses can still be transcribed and translated into viral proteins. Here, we developed an improved immunofluorescence protocol that combines two anti-Nef antibodies with one anti-Gag antibody, along with membrane and nuclear staining, enabling direct visualization of protein expression and localization. This method allows detailed characterization of the expression patterns and subcellular distribution of Gag and Nef proteins derived from defective proviruses. The protocol provides a practical tool for investigating the potential functions of proteins expressed from defective HIV-1 proviruses and for facilitating the ability to determine the biologic activity of cells harboring defective HIV-1 proviruses in patients living with HIV.

Association between fetal eye movement density and developmental problems at age 3 years

Abstract In this longitudinal study of 77 pregnant women, we examined how eye movement density (EMD) measured at 34 to 36 weeks’ gestation related to child development at age 3 years, using two developmental assessment tools. Fetal eye movements were recorded for 60 min. Data from 41 children with complete follow-up at age 3 years were analyzed. EMD was calculated as the number of eye movements per minute during periods with eye movement activity, which reflects the active behavioral state considered a precursor to rapid eye movement (REM) sleep. At 3 years, development was assessed using the Kinder Infant Development Scale and autism-related traits using the Social Responsiveness Scale-2. Sleep was evaluated with caregiver-completed questionnaires and sleep logs at 6 months, 1 year, and 3 years. Higher fetal EMD was associated with greater receptive and expressive language development, whereas lower EMD was linked to higher restricted and repetitive behavior (RRB) scores and an increased likelihood of clinically significant RRB. Moreover, lower EMD predicted later bedtimes at age 1 year. These findings suggest that fetal EMD reflects early maturation of neural circuits and may serve as a noninvasive early biomarker for identifying children at risk of developmental and behavioral difficulties.

DC-STAMP activates the PI3K/AKT/mTOR signaling pathway to regulate PANoptosis in acute myeloid leukemia

Background PANoptosis is a newly defined form of programmed cell death that integrates features of apoptosis, pyroptosis and necroptosis, playing a critical role in immune regulation and tumor biology. Clinically, Acute Myeloid Leukemia (AML) patients with high DC‑STAMP expression exhibited notably poorer cytogenetic risk profiles and shorter overall survival. Gene set enrichment analysis of primary AML samples from public databases revealed significant enrichment of the mTORC1 signaling pathway, a core signaling axis regulating the apoptotic process, in AML samples with high DC-STAMP expression. Methods DC-STAMP knockdown and overexpression models were established in the AML cell line THP-1 using small interfering RNA (siRNA) and lentiviral plasmids, respectively. Western blotting and RT-PCR were used to assess changes in PI3K/AKT/mTOR pathway activity in response to altered DC-STAMP expression. Flow cytometry and other cellular phenotypic assays were employed to evaluate the impact of DC-STAMP on PANoptosis in AML cells. Finally, PI3K inhibitors were introduced to assess the functional reversal of DC-STAMP–driven malignant phenotypes through downstream PI3K pathway inhibition. Results High DC-STAMP expression in AML activated the PI3K/AKT/mTOR signaling pathway and suppressed the PANoptosis process, thereby enhancing leukemic cell survival and chemoresistance. In contrast, genetic silencing of DC-STAMP or pharmacological inhibition of downstream PI3K restored normal apoptotic processes and significantly attenuated the malignant phenotypes driven by mTOR hyperactivation. Conclusions Activation of DC-STAMP is an essential mechanism that suppresses PANoptosis and promotes chemoresistance in AML cells. Targeting the downstream PI3K/mTOR signaling pathway may offer a promising therapeutic strategy for this high-risk AML subtype.

Smart irrigation-based internet of things and cloud computing technologies for sustainable farming