Search Results (22,364)

Concurrent/interleaved transcranial magnetic stimulation combined with functional MRI (TMS–fMRI) enables causal perturbation of targeted cortical regions while measuring whole-brain MR-based responses during stimulation. This perspective argues that the main translational value of concurrent/interleaved TMS–fMRI lies in operationalizing target engagement and network-level propagation as measurable endpoints, bridging stimulation “dose” to clinically meaningful effects. Rather than proposing a validated gold-standard protocol, we frame concurrent/interleaved TMS–fMRI as a measurement-driven translational approach in which MRI-informed targeting and MR-based readouts can be integrated to quantify target engagement under clearly specified methodological and quality-control conditions. This perspective specifically aims to make explicit an intermediate verification step that remains only partially formalized in current clinical neuromodulation workflows. We propose that MRI-based neuronavigation should move beyond template coordinates toward individualized anatomical and network-informed targeting, with the aim of improving precision, reproducibility, and safety. Building on the field’s evolution from technical feasibility to emerging clinical applications, we outline a staged framework from feasibility to biomarker potential, summarize representative protocol archetypes, and provide pragmatic recommendations for reporting and study design to improve comparability. This framework is intended to guide future concurrent/interleaved TMS–fMRI studies toward biomarker-ready designs and more clinically informative network neuromodulation. We further distinguish offline MRI-informed targeting from potential future real-time or closed-loop implementations, and we emphasize that current biomarker claims should remain proportional to the still heterogeneous evidence base. Full article

Thyroid cancer is the most common malignancy of the endocrine system and represents a biologically heterogeneous disease driven by the interplay between endocrine regulation, oncogenic signaling pathways, and tumor microenvironment dynamics. Although most follicular cell-derived thyroid cancers follow an indolent clinical course, a subset progresses toward aggressive, therapy-refractory phenotypes, underscoring the need for refined molecular understanding and improved biomarkers. This review comprehensively examines the molecular determinants of thyroid cancer progression, with particular emphasis on Thyroid Hormone (TH) signaling, the Mitogen-Activated Protein Kinase (MAPK) and Phosphoinositide 3-Kinase (PI3K)/AKT pathways, and the emerging role of microRNAs (miRNAs). We discuss how oncogenic alterations, most notably the ^V600EBRAF mutation, act as central drivers of tumor initiation and aggressiveness by sustaining MAPK/ERK signaling, promoting dedifferentiation, metabolic reprogramming, immune evasion, and resistance to targeted therapies. The cooperative role of PI3K/AKT signaling in reinforcing survival, invasion, and treatment resistance is highlighted, emphasizing the network-level integration of oncogenic pathways rather than linear dependency on single drivers. In parallel, thyroid hormones exert context-dependent effects on tumor biology through both genomic actions mediated by nuclear thyroid hormone receptors and non-genomic mechanisms initiated at the integrin αvβ3 receptor, linking endocrine status to cancer progression and therapeutic response. Finally, we review the expanding evidence supporting miRNAs as critical regulators of thyroid carcinogenesis and as promising diagnostic, prognostic, and predictive biomarkers. The clinical validation of miRNA-based panels and circulating miRNAs offers new opportunities to improve preoperative risk stratification, reduce overtreatment, and guide personalized therapeutic strategies. Collectively, these insights support a multidimensional framework for understanding thyroid cancer progression and highlight future directions for precision oncology. Full article

The COVID-19 pandemic intensified communication challenges for community college leaders navigating prolonged uncertainty and organizational disruption. This qualitative study examines how community college administrators described and interpreted their communication practices during the pandemic. Guided by the Elaboration Likelihood Model (ELM), this study explores how leaders made sense of message design, audience responsiveness, and trust under conditions of information overload and emotional strain. Semi-structured interviews were conducted with twelve administrators from community colleges across the United States, including presidents, vice presidents, and senior-level directors. Data were analyzed using reflexive thematic analysis. Five themes emerged: communication breakdowns between employee groups; tailored messaging for specific constituencies; preferences for in-person and interactive communication; trust-building through transparency; and reliance on collaborative communication structures. Participants described communication as an ongoing relational and organizational practice rather than a one-time transmission of information. Administrators reported adapting strategies by combining repetition, audience-specific framing, interactive formats, and structural supports to manage uncertainty and sustain institutional trust. Findings are not intended to be generalizable but provide contextually grounded insight into leadership communication during an extended crisis. This study contributes to scholarship on higher education leadership and crisis communication by illustrating how persuasion, sensemaking, and relational cues intersected in administrators’ communication practices. Full article

Leaks in pipe systems result in significant economic losses, environmental hazards, and public health risks. Transient-based leak detection methods, which exploit the dynamics of pressure waves in response to system anomalies, have emerged as efficient techniques for identifying and characterizing leaks in pressurized pipelines. These methods offer distinct advantages, including minimal data requirements, high sensitivity to low-pressure anomalies, and resilience to the ill-posed conditions often affecting steady-state models. This paper reviews transient-based leak detection, synthesizing findings from over 139 peer-reviewed publications spanning the past three decades. The review categorizes transient-based methods into transient damping, transient reflection, system response, and inverse transient methods, analyzing the prevalence, evolution, and research rate of each category over time. By structuring the review around key aspects such as simulation domain type, analysis approach, system response, solver strategies, adaptability to noise, viscoelasticity, and network complexity, this paper identifies significant trends and shifts in research focus. A comprehensive tabular dataset of 139 studies captures how research activity in various areas has accelerated, slowed, or reached stability, offering insights into the evolving priorities within the field. This review highlights areas for further development, particularly in addressing AI-enhanced applications, transient excitation and measurement sites design, noise resilience, comprehensive leak characterization, validation approaches, and scalability for complex network applications, providing a resource to guide future research in transient-based leak detection. Full article

Metabolic reprogramming is a core hallmark of malignancy, enabling tumor cells to sustain rapid proliferation, evade immune elimination, and develop resistance to therapy. Although a wide range of plant-derived phytochemicals exhibit anticancer activity with comparatively low toxicity, their capacity to disrupt specific metabolic dependencies exploited by tumors has not been comprehensively synthesized. This review brings together current mechanistic evidence showing how major phytochemical classes, including polyphenols, terpenes and terpenoids, glucosinolates, and alkaloids, interfere with pathways central to tumor metabolic fitness, such as aerobic glycolysis, pentose phosphate pathway flux, mitochondrial substrate oxidation, glutamine dependence, and redox homeostasis. It further introduces a pathway-focused framework that links phytochemical mechanisms to quantifiable metabolic outcomes and highlights their potential to remodel the tumor microenvironment by altering nutrient competition, oxidative stress responses, and hypoxia-driven signaling. Key barriers such as poor systemic bioavailability, rapid metabolic degradation, and limited tissue penetration are assessed alongside emerging formulation and delivery strategies designed to enhance therapeutic exposure while preserving low-toxicity profiles. Mapping these mechanistic insights onto clinical development needs allows prioritization of specific phytochemical-metabolic pathway pairs with the strongest potential for translation. This positions plant-derived metabolic disruptors as promising candidates for next-generation, low-toxicity anticancer therapies that strategically exploit defined metabolic vulnerabilities. Full article

Extreme hydrological events fundamentally alter sediment transport dynamics across grain, reach, and watershed scales, rendering classical equilibrium-based transport formulations inadequate. This review synthesizes recent advances in multiscale sediment transport modeling under highly unsteady and high-magnitude forcing conditions. At the grain scale, particle-resolved simulations demonstrate that sediment entrainment is governed by turbulence intermittency and transient force exceedance rather than mean bed shear stress thresholds, particularly when the hydrograph rise timescale (T_h) becomes comparable to particle response times (T_p). At the reach scale, non-equilibrium transport emerges when the unsteadiness ratio T_h/T_a∼O(1), where T_a is the sediment adaptation timescale representing the time required for sediment flux to adjust toward transport capacity. Under these conditions, pronounced hysteresis between discharge and sediment flux is observed, requiring relaxation-based transport formulations instead of instantaneous equilibrium laws. At the watershed scale, the sediment delivery ratio (SDR), defined as the ratio of sediment yield at the basin outlet to total hillslope erosion, becomes highly time-dependent. Extreme precipitation events can activate hillslope-channel connectivity, increasing SDR by orders of magnitude relative to baseline conditions. A unified dimensionless scaling framework is presented based on mobility intensity (θ/θ_c, where θ is the Shields parameter and θ_c is its critical value for incipient motion), unsteadiness ratio (T_h/T_a), and morphodynamic coupling (T_f/T_m, where T_f is the hydraulic advection timescale and T_m is the morphodynamic adjustment timescale). This framework enables classification of sediment transport regimes ranging from quasi-equilibrium to cascade-dominated states. The synthesis demonstrates that predictive uncertainty increases nonlinearly across scales due to timescale compression, threshold activation, and feedback between flow hydraulics and evolving morphology. Recent developments in hybrid physics-AI approaches show promise in improving predictive capability by enabling dynamic transport closures, surrogate modeling of computationally expensive microscale processes, and data assimilation for real-time forecasting. However, these approaches remain limited by extrapolation uncertainty and the need to enforce physical constraints. Overall, this review concludes that regime-aware multiscale coupling, combined with uncertainty quantification and adaptive modeling strategies, is essential for robust sediment hazard prediction and climate-resilient infrastructure design under intensifying hydrological extremes. Full article

This study adopts a systemic perspective to investigate how China’s carbon emissions trading pilot (CCTPP) influences the internal configuration of the firm as a complex socio-technical system. We focus on the emergent property of digital–green synergy, which captures the integration between a firm’s digital and green transformation subsystems. Employing a panel dataset of Chinese A-share listed companies from 2010 to 2024 and an event-study difference-in-differences methodology, we analyze the response of this system-level property to carbon market signals. The results demonstrate that policy intervention significantly enhances systemic synergy, with an effect equivalent to 4.4 percent of the standard deviation of the synergy index. The response follows a dynamic pattern, persisting for four years before gradually diminishing, thereby revealing the system’s adaptation process. Critically, the internal structure of the firm-system moderates this response, as financing constraints, executive compensation, and firm size represent key components of governance and resource-allocation subsystems and each exerts a significant negative moderating effect. Furthermore, environmental context matters, with the policy effect concentrating on firms located in central and southern regions and within non-manufacturing and non-high-tech sectors. These findings offer a system-based understanding of how carbon pricing interacts with corporate governance to facilitate integrated socio-technical transitions. Full article

Background/Objectives: The COVID-19 pandemic imposed logistical challenges on health systems, particularly for mass vaccination campaigns under emergency conditions. In decentralized health systems, the absence of a structured preparedness phase may compromise coordination, allocation, and operational performance. This study analyzes the vaccination campaign in a municipality in southern Brazil, examining how the overlap of the preparedness and response phases affected outcomes and how alternative logistical scenarios could have altered campaign performance. Methods: An empirical analysis was conducted using scenario-based simulation with stock and flow structures. The model represents vaccine procurement, distribution across national, state, regional, and municipal levels, and municipal vaccination capacity. Real data from the 2021 vaccination campaign in the municipality were used to build a Business-as-Usual scenario, compared with alternative scenarios involving changes in procurement predictability, allocation rules, and operational capacity. Results: Vaccination outcomes were strongly conditioned by upstream allocation decisions, particularly at the national state level. Isolated adjustments at intermediate supply chain levels produced limited improvements when upstream constraints persisted. Scenarios combining improved alignment between forecasted and acquired doses with operational capacity showed higher vaccination potential, revealing a gap between observed performance and system capacity. Conclusions: The findings reinforce that preparedness is a critical determinant of vaccination performance and must precede response in emergency contexts. Supply predictability alone is insufficient without coordinated allocation mechanisms and operational readiness across governance levels. This study provides empirical evidence on how preparation-related decisions shape vaccination outcomes in decentralized health systems and inform logistical coordination in future emergencies. Full article

Type 2 diabetes mellitus (T2DM) affects approximately 10–25% of patients undergoing orthopedic procedures and is associated with impaired tissue healing, increased complication rates, and reduced responsiveness to orthobiologic therapies, including platelet-rich plasma (PRP), bone marrow aspirate concentrate (BMAC), and mesenchymal stem cell (MSC) preparations. The underlying mechanisms include advanced glycation end-product accumulation, NF-κB-driven chronic inflammation, Nrf2 pathway impairment, mitochondrial dysfunction, and epigenetic diabetic memory, collectively compromising both orthobiologic product quality and the tissue microenvironment. Emerging, predominantly mechanistic evidence suggests that targeted nutritional interventions, including bioactive compounds targeting mitochondrial biogenesis pathways, anti-inflammatory dietary patterns, and specific micronutrients, may modulate these pathological processes and potentially improve orthobiologic outcomes. This narrative review synthesizes evidence from diabetic pathophysiology, orthobiologic outcomes research, and nutritional science to propose a conceptual clinical framework for regenerative medicine optimization in T2DM patients. Critical knowledge gaps are identified, and a research agenda is proposed. The proposed framework, based primarily on mechanistic and preclinical evidence, should be interpreted as a foundation for research prioritization and hypothesis generation rather than as a clinical protocol. Rigorous randomized trials directly evaluating nutritional optimization in orthobiologic therapy for diabetic patients are required before evidence-based recommendations can be established. Full article

Graft-versus-host disease (GVHD) remains the most severe complications following allogeneic hematopoietic cell transplantation (allo-HCT). Mesenchymal stromal cells (MSCs) have shown therapeutic potential in GVHD due to their immunomodulatory properties. However, their clinical application is constrained by safety concerns, including ectopic engraftment, microvascular obstruction, rejected by host, and potential tumor-supportive effects. Increasing evidence suggests that MSC-derived exosomes (MSC-Exos), as cell-free mediators, retain many of the beneficial effects of MSCs while exhibiting improved safety and stability profiles. MSC-Exos carry diverse bioactive cargo, including nucleic acids, lipids, and proteins, and can modulate immune responses, promote tissue repair, and restore barrier integrity. In this review, we place particular emphasis on both immunoregulation and tissue barrier protection as dual mechanisms underlying MSC-Exos efficacy in GVHD. We further discuss emerging preclinical and clinical evidence, as well as key challenges in translation. Full article

Enhancing the ESG performance of manufacturing enterprises represents a critical pathway for promoting high-quality economic development and achieving sustainable development goals. Leveraging the establishment of National New-Generation Artificial Intelligence Innovation and Development Pilot Zones as a quasi-natural experiment, this study examined A-share listed manufacturing enterprises on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2023, employing a multi-period difference-in-differences model to systematically evaluate the policy’s impact on enterprise ESG performance and its underlying mechanisms. The empirical results demonstrate that the Artificial Intelligence Innovation and Development Pilot Zone policy exerts a significant positive effect on manufacturing enterprises’ ESG performance, with the robustness of this conclusion validated through parallel trends tests, placebo tests, and multiple robustness checks. A mechanism analysis revealed that the policy primarily enhances manufacturing enterprises’ ESG performance through two transmission channels: intensifying the R&D expenditure intensity and strengthening environmental compliance pressures. Furthermore, the enterprise resource allocation and operational efficiencies significantly moderate the policy effect, amplifying the enabling effect of the policy on ESG performance. A heterogeneity analysis indicates that, from the perspectives of enterprise ownership and responsibility orientation, the policy demonstrates more pronounced enabling effects on non-state-owned enterprises and non-high-pollution enterprises; from the perspectives of technological endowment and factor structure, the policy effects are more evident among high-tech enterprises, non-capital-intensive enterprises, and non-labor-intensive enterprises. This study elucidates the multi-dimensional transmission mechanisms through which the Artificial Intelligence Innovation and Development Pilot Zone policy empowers ESG development in manufacturing enterprises, providing theoretical foundations and practical guidance for refining artificial intelligence policy frameworks and promoting manufacturing enterprise sustainable development. The research findings also contribute empirical evidence from emerging economies to comparative research on global AI governance. Full article

Treatment-resistant schizophrenia (TRS) remains a significant clinical challenge due to limited therapeutic options and a poor understanding of its underlying biology. Recent findings suggest that immune system dysregulation may play a critical role in the pathophysiology of TRS. This systematic review aimed to synthesize current evidence on immunological abnormalities associated with TRS, with a focus on inflammatory markers, immune cell profiles, and the role of autoantibodies, and to explore their potential utility in diagnosis and treatment. A systematic review of the literature was conducted in accordance with PRISMA guidelines, incorporating clinical, molecular, and translational studies on immunological markers in patients with TRS. Included studies assessed cytokine levels, immune cell phenotypes, autoantibodies, genetic factors, and the effects of immunomodulatory therapies. Emphasis was placed on findings differentiating TRS from treatment-responsive schizophrenia. TRS is associated with distinct immune profiles, including elevated IL-6, IL-8, TNF-α, and sCD25 levels, overexpression of CD33 on monocytes and expansion of CD123+ plasmacytoid dendritic cells. Autoantibodies, particularly those targeting glutamatergic receptors, are more prevalent in TRS and decrease with clozapine treatment. Predictive models using IgM autoantibodies and genetic variants show promise for early identification of at-risk individuals. Emerging immunomodulatory treatments such as rituximab, levamisole, and senolytics are under investigation, offering potential for personalized strategies. Immunological dysfunction represents a reproducible and biologically relevant feature of TRS. Integration of immune biomarkers into clinical practice may enhance diagnostic precision and inform personalized therapeutic approaches. Future research should prioritize standardized biomarker protocols and longitudinal studies to validate causal associations and optimize treatment algorithms. Full article

Galectin-3 (Gal-3) is a multifunctional molecule that exerts pleiotropic effects in inflammatory responses and contributes to the pathogenesis of numerous immune-mediated diseases. Although Gal-3 has been known for more than five decades, it remains a lectin with intriguing and not yet fully elucidated properties. The existing body of evidence underscores the importance of Gal-3 in the regulation of homeostatic and inflammatory processes. Neurotrophins are traditionally recognized as key regulators of neuronal development, survival, and synaptic plasticity; nevertheless, accumulating evidence indicates that they also play important roles in immune regulation and neuroimmune communication. Importantly, neurotrophins are also produced by immune cells, including monocytes, macrophages, lymphocytes, and basophils, which express functional neurotrophin receptors including tropomyosin receptor kinase A (TrkA), tropomyosin receptor kinase A (TrkB), and p75 neurotrophin receptor (p75NTR). In this narrative review, we synthesize current evidence on neuroinflammation, neurotrophins, and Gal-3, with a particular focus on the molecular mechanisms involved in the crosstalk between neurotrophins and Gal-3 or immune cells. We further examine how this neuroimmune–neurotrophic crosstalk contributes to the pathogenesis of psychiatric and neurodegenerative disorders, as well as other neurological conditions. Finally, we discuss the emerging therapeutic potential of targeting neurotrophins and Gal-3 as modulators of neuroinflammation. Full article

This study investigates emotional patterns in state government disaster guideline documents using keyword-level emotion analysis and TF–IDF based topic modeling, framing disaster policy communication as an emotional–cognitive dual structure, drawing from Situational Crisis Communication Theory. The findings demonstrate a strong negative relationship between fear and neutrality, indicating a functional separation between risk awareness and administrative clarity. Nine topics were identified and organized into clusters centered on operational support, administrative structures, and policy frameworks, while content related to hazards and recovery emerged as a distinct semantic category based on cosine similarity analysis. In the integrated analysis of sentiment and topics, neutral language predominates, reflecting the cognitive dimension of government guidelines, with fear and sadness appearing as secondary but systematically patterned emotions. Fear concentrates in topics addressing hazardous conditions and risk-related content. Emotionally neutral language has traditionally been privileged in public administration, but the findings highlight disaster policy communication shaped by governance objectives that privilege specific emotional orientations aligned with coordination, participation, and risk management. State disaster guidelines function not only as technical instructions but also as structured communicative instruments that operate along a dual cognitive–emotional model, shaping public attention and response. Full article

Trained immunity refers to the enduring functional reprogramming of innate immune cells after particular stimuli, driven by epigenetic and metabolic alterations that augment non-specific responses upon subsequent exposure. Neutrophils and monocytes/macrophages, as essential innate effectors, are crucial for the induction and control of trained immunity, which is the primary emphasis of this review. Neutrophils, the predominant circulating leukocytes, were historically considered incapable of memory owing to their brief lifespan. Emerging evidence indicates that trained immunity functions at the bone marrow progenitor level, influencing granulopoiesis to produce neutrophils with lasting functional modifications. This research offers new insights into neutrophil functions in infection, cancer, and inflammation. Monocytes and macrophages, characterized by phenotypic plasticity and tissue residence, function as conventional models of trained immunity. They experience direct peripheral reprogramming or emerge as primed descendants of trained bone marrow precursors, performing pro-inflammatory or reparative roles in malignancies, infections, and ischemia lesions. This study comprehensively outlines the regulatory mechanisms of trained immunity in these cells, clarifies their functions in various clinical situations, and examines therapeutic applications. Comprehending these pathways is crucial for elucidating the cellular foundation of innate immunological memory, uncovering its multiple functions in disease, and guiding innovative therapeutics aimed at granulopoiesis and monocyte-macrophage polarization. Full article