Search Results (94,200)

This paper advances a Lie-group approach to measurement by identifying symmetry conditions that determine when effect sizes from different instruments can be meaningfully compared. Measurement transformations are modeled as elements of a two-parameter affine Lie group, and the associated Lie algebra describes the infinitesimal flow linking true scores and measurement-error variability across instruments. Within this framework, it is shown that the population standardized mean difference (SMD) is invariant across measures if and only if the transformation between them consists of a uniform affine transformation of true scores together with a uniform scaling of measurement-error standard deviations by the same factor. These symmetry conditions arise directly from the Lie algebra and ensure that the SMD remains constant along the exponential transformation flow; even slight departures from this symmetry produce a non-zero derivative of the SMD, marking a precise breakdown of invariance. A simulation study demonstrates how small nonlinear perturbations of the affine symmetry generate systematic distortions in the population true-score SMD. The results provide a mathematically grounded characterization of effect-size comparability and illustrate how continuous symmetries, Lie algebras, and transformation flows can clarify fundamental issues in measurement equivalence, meta-analysis, and longitudinal or cross-cultural research. Full article

This paper proposes a Bayesian estimation method for spatial lagged panel quantile models. The proposed model simultaneously considers spatial lag effects of the dependent variable and the quantile regression framework, enabling effective capture of spatial dependence and conditional distribution heterogeneity. The research constructs a Bayesian estimation framework based on the asymmetric Laplace distribution by decomposing the random disturbance term into a combination of normal and exponential distributions, successfully developing a probabilistic model with both thick tail robustness and computational efficiency. On this basis, the study derives the full conditional posterior probability distributions of model parameters and designs a hybrid Markov Chain Monte Carlo (MCMC) sampling algorithm integrating Gibbs sampling and Metropolis–Hastings algorithm for parameter estimation. Numerical simulation experiments demonstrate that, compared with traditional estimation methods, the proposed Bayesian estimation approach exhibits superior estimation accuracy and robustness across different quantiles, with particularly pronounced advantages in small sample and heavy-tailed distribution scenarios. This methodology provides a more reliable theoretical tool for analyzing panel data with spatial dependencies. This method can not only accurately quantify the spatial spillover effect, but also identify the different effects of the same influencing factor at different emission levels, which provides a strong methodological support for formulating differentiated and precise emission reduction policies. Full article

This study addresses the common challenges of complex soil behavior and the difficulties in achieving precise control during the construction of large open caissons. A centrifugal model test was conducted to investigate open caisson–fine sandy soil interaction, and the findings were further verified through field testing. Results indicated that during the sinking process, the open caisson–soil interface exhibited slip failure characteristics, while the soil at the cutting edge of the open caisson showed a tendency for inward shear slippage. The horizontal earth pressure along the open caisson sidewall was found to correspond to static earth pressure in the upper section and gradually approached active earth pressure in the lower section. The maximum earth pressure occurred at approximately three-quarters of the embedded depth of the open caisson wall. Furthermore, the friction angle at the soil-open caisson interface was approximately 0.63 times that of the soil friction angle. Based on the observed distribution patterns of earth pressure and skin friction, theoretical calculation formulas were developed. Their accuracy was confirmed through field tests, providing valuable references for the design and construction of large open caisson projects. Full article

RNA editing is a way to diversify, regulate expression, and expand the cell transcriptome. The most common RNA editing is the reversible conversion of adenosine (A) to inosine (I) driven by double-stranded RNA-binding adenosine deaminases (ADARs). As inosine is recognized as guanosine (G) during translation, the RNA editing may result in non-synonymous codon changes. For this reason, ADARs have gained attention as promising enzymes to rewrite mRNA. Many efforts were undertaken to engineer a precise, effective, and controllable ADAR-based system to target certain Adenines on RNA to repair pathological mutations. This review summarizes the advances in ADAR-mediated RNA editing, evolving from systems using antisense oligonucleotides as guide RNA to recruit endogenous or overexpressed ADARs, through more complex setups additionally expressing other RNA-binding proteins, to rational designs harnessing ADARs to convert other nucleotides and amplify the low initial signal. Increasing the specificity and yield of RNA editing, expanding the number of targetable sites, and reducing off-target and bystander activity remain key challenges for these technologies. Improving delivery efficiency across a broad range of cell types, as well as optimizing delivery routes in in vivo studies are also critical to harness them as advantageous tools for both research and therapy. Full article

This study employs the Atangana–Baleanu–Caputo fractional derivative within the Moore–Gibson–Thompson heat conduction model to analytically investigate the thermoelastic vibrations in solid medium-containing voids. The ABC–MGT formulation incorporates a non-singular Mittag–Leffler memory kernel, facilitating the modeling of tempered hereditary relaxation in voided thermoelastic media, thereby producing more realistic attenuation and phase lag characteristics in transient responses than conventional integer-order models. Specifically, our novelty lies in developing a coupled thermoelastic–void formulation within an ABC–MGT heat conduction framework, deriving the full governing system and boundary-value solution in the Laplace domain, and providing a systematic parametric analysis showing how the ABC order changes attenuation, phase lag, and stress/void interactions. This approach enables a precise analytical resolution of the problem. The analysis indicates that the presence and size of voids substantially impact the system response variables, with smaller apertures yielding reduced magnitudes. Thus, this analytical investigation introduces a novel methodology for addressing the complex challenges associated with advanced functional materials and high-performance engineering structures. Full article

Multiple myeloma (MM) is an oncohematological neoplasm characterized by the abnormal proliferation of neoplastic plasma cells in the bone marrow and the excessive secretion of monoclonal antibodies into the bloodstream. Approximately 3 to 5% of patients present with a variant form of the disease where there is no secretion of monoclonal proteins, characterizing the non-secretory MM picture. It exhibits a highly complex and heterogeneous genetic signature, allowing the disease to be classified into premalignant entities and symptomatic forms. In this context, an integrative narrative review was conducted, encompassing genomic, epigenomic, proteomic, metabolomic, and radiomic biomarkers described in the literature between 2018 and 2025. Emphasis was placed on their translational potential, current limitations in clinical practice, and gaps within recent recommendations. Several categories of biomarkers, particularly ctDNA methylome, single-cell multiomics, proteomics of surface antigens, functional ex vivo assays, and PET/CT radiomics, demonstrate strong potential for enhancing risk stratification, detecting early progression, guiding therapy selection, and identifying novel therapeutic targets. These applications extend beyond existing guideline frameworks. Thus, integrating advanced biomarker platforms can overcome limitations of current diagnostic and therapeutic models and enhance precision strategies across plasma cell disorders. Full article

Objectives: Anticipated telehealth use is an important determinant of whether telehealth can function as a durable component of hybrid care models. However, there are limited practical tools to identify patients at risk of discontinuing telehealth. We aim to (1) identify factors associated with anticipated telehealth use; (2) develop a risk stratification tool (CONTEST); (3) compare its performance with machine learning (ML) models; and (4) evaluate model fairness across sex and race/ethnicity. Methods: We conducted a retrospective cross-sectional analysis of the 2024 Health Information National Trends Survey 7 (HINTS 7), including U.S. adults with ≥1 telehealth visit in the prior 12 months. The primary outcome was anticipated telehealth use. Survey-weighted multivariable logistic regression informed a Framingham-style point score (CONTEST). ML models (XGBoost, random forest, logistic regression) were trained and evaluated using the area under the receiver operating characteristic curve (AUROC), precision, and recall. Global interpretation used SHAP values. Fairness was assessed using group metrics (Disparate Impact, Equal Opportunity) and individual counterfactual-flip rates (CFR). Results: Approximately one-third of adults reported at least one telehealth visit in the prior year. Among these users, nearly one in ten expressed an unwillingness to continue using telehealth in the future. Four telehealth experience factors were independently associated with unwillingness to continue: lower perceived convenience, technical problems, lower perceived quality compared to in-person care, and unwillingness to recommend telehealth. CONTEST demonstrated strong discrimination for identifying individuals with lower anticipated telehealth use (AUROC 0.876; 95% CI, 0.843–0.908). XGBoost performed best among the ML models (AUROC 0.902 with all features). With the same four top features, an ML-informed point score achieved an AUROC of 0.872 (95% CI, 0.839–0.904), and a four-feature XGBoost model yielded an AUROC of 0.893 (95% CI, 0.821–0.948, p > 0.05). Group fairness metrics revealed disparities across sex and race/ethnicity, whereas individual counterfactual analyses indicated low flip rates (sex CFR: 0.024; race/ethnicity CFR: 0.013). Conclusions: A parsimonious, interpretable score (CONTEST) and feature-matched ML models provide comparable discrimination for stratifying risk of lower anticipated telehealth use. Sustained engagement hinges on convenience, technical reliability, perceived quality, and patient advocacy. Implementation should pair prediction with operational support and routine fairness monitoring to mitigate subgroup disparities. Full article

Anterior cruciate ligament (ACL) reconstruction is a common orthopedic procedure, but graft failure remains a significant complication, particularly in young and active individuals. Understanding the multifactorial etiology of failure and optimizing revision strategies are crucial for improving outcomes. A structured narrative review of the literature was conducted, including studies published from January 2000 to May 2024. Databases searched included PubMed/MEDLINE, Embase, and Google Scholar. Eligible studies addressed definitions, etiology, classification, and surgical management of ACL reconstruction failure. Data were synthesized qualitatively, integrating evidence on technical, biological, and traumatic causes, as well as neuromuscular and psychosocial factors influencing functional outcomes. ACL reconstruction failure is primarily caused by technical errors, particularly tunnel malposition (60–70% of cases), followed by traumatic (15–25%) and biological (10–15%) mechanisms. Failure timing provides diagnostic clues: early (<3 months) failures often relate to fixation or infection, mid-term (3–12 months) to technical errors, and late (>12 months) to trauma or degeneration. Revision strategies include individualized graft selection, anatomical tunnel placement, repair of associated lesions, and consideration of biomechanical abnormalities. Overall success rates of revision procedures average 70–75%, with lower outcomes in adolescents and high-demand athletes. Emerging techniques, including lateral extra-articular tenodesis and biologic augmentation, may enhance revision outcomes, although long-term evidence remains limited. ACL reconstruction failure is a multifactorial event requiring thorough preoperative assessment, precise surgical planning, and individualized management. Addressing technical, biological, and neuromuscular factors, alongside patient-specific considerations, is essential to optimize functional outcomes and reduce failure rates. Future research should focus on standardized reporting, multicenter prospective studies, and advanced surgical planning tools to further improve revision success. Full article

High-altitude grazing animals are continuously exposed to strong wind and low temperature, which challenge physiological homeostasis and energy metabolism. Improving living conditions and nutritional supplementation are two commonly used strategies. In this study, sixty 7-month-old Gangba sheep (initial body weight (BW) 21.00 ± 1.90 kg) were allocated to a 42-day trial with four groups (open-air sheepfold, mobile sheepfold, open-air sheepfold + supplementary feeding, mobile sheepfold + supplementary feeding) to investigate their effects on growth performance, serum parameters and gut microbiota in naturally grazing Gangba sheep. Mobile sheepfolds increased the temperature–humidity index (THI) and reducing the wind chill index (WCI) (p < 0.05). The sheep with mobile sheepfold showed higher serum total antioxidant capacity and lower levels of heat shock proteins HSP70 and HSP90 (p < 0.05), indicating alleviated stress. Supplementary feeding markedly increased final BW and average daily gain (p < 0.05). The interaction between sheepfold type and feeding supplementation showed increasing IgA levels in the open-air sheepfold with supplementary feeding group and increasing IL-4 levels in the mobile sheepfold with supplementary feeding group, while TNF-α concentrations were reduced in all three treatment groups (p < 0.05). Meanwhile, KB and FFAs were increased in the open-air sheepfold with supplementary feeding group but decreased in the mobile sheepfold with supplementary feeding group (p < 0.05). The mobile sheepfold also increased the Bacillota-to-Bacteroidota ratio, suggesting improved microbial community structure. Functional predictions showed enrichment of reductive acetogenesis and reduction in aerobic chemoheterotrophy and sulfur-related respiration pathways (p < 0.05). Moreover, key microbial genera were significantly correlated with THI and WCI (p < 0.05). Collectively, these results demonstrated that mobile sheepfold together with feeding supplementation improve stress responses, serum immune and lipid metabolic indicators, and potentially altered gut microbial composition and function, providing insights into host–microbiota interaction in extreme high-altitude environments. Full article

Mutants with a bright green appearance due to wax synthesis or deposition defects have been reported in various plants such as Arabidopsis thaliana, corn, and rice, but they are relatively rare in broccoli (a brassicaceae crop). Here, we describe SY03, a natural mutant of broccoli with a glossy green phenotype owing to epidermal wax deficiency. Genetic analysis indicated that the leaf luster trait of SY03 was controlled by a single recessive gene. By using the F₂ generation and combining bulked segregant analysis and molecular marker techniques, the candidate gene BoFAR3a, homologous to the Arabidopsis FAR gene, was identified within a 96.678 kb interval of chromosome C01. The A→G point mutation in exon 1 of the BoFAR3a coding sequence substitutes the canonical ATG start codon with GTG, which is predicted to abrogate or severely reduce translation initiation. RT-qPCR indicated that the expression levels of BoFAR3a were significantly decreased in the leaves of the glossy green phenotype mutant. Heterologous expression of BoFAR3a in A. thaliana restored the phenotype of A. thaliana mutant FAR3. The discovery of BoFAR3a is of great significance for breeding lustrous and commercially appealing broccoli varieties. This study systematically analyzed the molecular basis of the lustrous green phenotype in broccoli, providing new insights into the epidermal waxy regulatory network of cruciferous crops. In the future, the wax synthesis pathway can be precisely improved through gene editing technology, achieving a coordinated enhancement of the appearance quality and stress resistance of broccoli. Full article

Distinguishing mood from emotion has long posed challenges for psychology, with persistent definitional ambiguity limiting both theoretical precision and applied effectiveness. Our early work, identified duration and cause attribution as the most reliable markers differentiating short-lived, event-linked emotions from more diffuse, enduring moods. Researchers further advanced understanding by conceptualising emotions as feedback signals that support learning and adaptation, while the 4Rs model translated these insights into applied practice by embedding cause attribution within affect regulation. This paper integrates these conceptual, functional, and applied perspectives to demonstrate why accurate classification of affective states is a functional necessity in high-performance contexts. I propose that misclassifying moods and emotions may contribute to inefficient deployment of self-regulatory resources, whereas distinguishing states based on cause attribution may support more targeted and efficient regulation. Drawing on examples from sport, healthcare, performing arts, military operations, and corporate leadership, this paper synthesizes existing work to highlight the practical implications of the mood–emotion distinction for applied psychology. Full article

Thyroid hormones profoundly modulate hepatic fatty acid and cholesterol synthesis and turnover. Although nonalcoholic fatty liver disease (NAFLD) shows epidemiological links to hypothyroidism, the genetic substrates of this relationship remain unresolved. Integrating large-scale genome-wide association studies with single-cell transcriptomics, spatial transcriptomics, and single-cell chromatin accessibility via state-of-the-art computational approaches, we interrogated the association between NAFLD and hypothyroidism across organ systems, cellular expression landscapes, and molecular–genetic strata. We uncovered pronounced spatial specificity in genetic risk within the liver, prioritized hepatocytes as the principal shared cell type affected, and, leveraging spatial transcriptomics, advanced a dynamic spatiotemporal two-hit model. We further nominated MAGI3, RRNAD1, and PRCC as high-confidence candidate genes and pinpointed a key risk locus, rs926103. These findings deliver a dynamic, testable framework for the full pathophysiological continuum linking NAFLD and hypothyroidism and yield new targets and leads for precision intervention. Full article

The exploration of natural redox-modulating agents to mitigate/reduce oxidative damage triggered by toxins is a major area of interest in nutritional and pharmacological fields. Aspalathus linearis (rooibos), traditionally consumed in South Africa for health benefits, was assessed for hepatoprotective effects against fumonisin B1 (FB1)-induced damage. This study involved 24 male rats (n = 6/group) that received FB1 (50 mg/kg diet equivalent, i.p. for 5 days) with or without oral exposure to unfermented (GR) or fermented (FR) rooibos extracts. Alongside somatic records, we assessed blood biochemicals, as well as liver histology, antioxidative stress markers (GSH, GPx, MDA, and carbonylation), regulatory proteins (Nrf2, Sirt3, PGC-α, TRX1, HSP70, and LONp1), inflammation (cytokines), and phospholipid fatty acid profile. Based on results, FB1 suppressed growth, compromised liver function, altered redox status, and elevated stress markers. Both rooibos extracts decreased oxidative damage (↓MDA, ↓carbonylation) and modulated stress regulators (↑Nrf2, ↓HSP70). FR uniquely increased GPx and TRX1 while decreasing IL-1β and PGC-α concentrations, whereas GR strongly increased Nrf2 and Sirt3, reflecting distinct bioactivities linked to their differing polyphenolic profiles. Neither extract compensated for FB1-induced alterations in the liver total phospholipid fatty acid profile or serum cholesterol. In conclusion, GR and FR improved redox potential and inflammatory/stress response; however, this effect was selective, as it did not translate into comprehensive hepatoprotection. These findings support the potential role of rooibos as a dietary modulator of endogenous antioxidant defenses, although clinical translational trials are needed. Full article

In the post-pandemic era, student mental health challenges have emerged as a critical issue in higher education. However, conventional assessment approaches often treat at-risk populations as a monolithic entity, thereby limiting intervention effectiveness. This study proposes a novel computational framework that integrates explainable artificial intelligence (XAI) with unsupervised learning to decode the latent heterogeneity of psychological risk mechanisms. We developed a “predict-explain-discover” pipeline leveraging TreeSHAP and Gaussian Mixture Models to identify distinct risk subtypes based on a 2556-dimensional feature space encompassing lexical, linguistic, and affective indicators. Our approach identified three theoretically-grounded subtypes: academically-driven (28.46%), socio-emotional (43.85%), and internal regulatory (27.69%) risks. Sensitivity analysis using top-20 core features further validated the structural stability of these mechanisms, proving that the subtypes are anchored in the model’s primary decision drivers rather than high-dimensional noise. The framework demonstrates how black-box classifiers can be transformed into diagnostic tools, bridging the gap between predictive accuracy and mechanistic understanding. Our findings align with the Research Domain Criteria (RDoC) and establish a foundation for precision interventions targeting specific risk drivers. This work advances computational mental health research through methodological innovations in mechanism-based subtyping and practical strategies for personalized student support. Full article

Diabetic retinopathy (DR) stands as a classic microvascular complication of diabetes mellitus. DR is characterized by multidimensional pathological changes in retinal neurons, microvasculature and supportive cells, leading to an intricate damage network. It is predominantly marked by neuropathy, encompassing retinal neuronal dysfunction, aberrant activation of glial cells, and degeneration of synaptic structures. In severe instances, it can result in visual impairment and, in the worst-case scenario, blindness. As diabetes progresses, retinal nerve tissue frequently sustains damage owing to oxidative stress, inflammatory responses, and compromised mitochondrial function. Although the precise neuroprotective mechanisms remain elusive, exercise has the ability to bolster mitochondrial function in retinal cells, diminish oxidative stress, and curb inflammatory reactions, thereby safeguarding the neurophysiological function of the retina. Irisin is a myokine primarily secreted by skeletal muscles in response to exercise stimulation. Moreover, being produced in trace amounts across a variety of tissues, it has the capacity to regulate the physiological processes of multiple organs. Recent studies have indicated that irisin can exert powerful neuroprotective effects by enhancing cellular glucose uptake, improving mitochondrial function, inhibiting the expression of pro-inflammatory factors, and resisting ferroptosis. In this review, we systematically collated and synthesized existing evidence on irisin-related signaling pathways and comprehensively assessed its regulatory potential in alleviating neuroinflammation and promoting neural repair in diabetic retinopathy and offer insights into future research directions in this field. Full article