Search Results (546)

Climate regulation ecosystem services (CRESs) play a crucial role in maintaining ecological balance and promoting regional sustainability. Previous studies have primarily focused on the total volume or per-unit-area quantity of CRESs, with limited attention given to their underlying driving mechanisms. This neglect overlooks their multidimensional attributes and dynamic complexity. Such simplifications often overlook the multidimensional attributes and dynamic complexity inherent in these services. Therefore, this study introduces a multidimensional evaluation framework to reveal the characteristic of the spatiotemporal evolution of CRESs. By integrating a multiscale geographically weighted regression (MGWR) model, the intensity and effective distance of theireffects are quantitatively identified, thereby providing a scientific and refined cognitive foundation for regional sustainable development. The results showed the following: (1) Between 2002 and 2022, CRESs in Guizhou Province showed an upward trend, with 64% of counties experiencing positive trends, whereas 51% of counties remained below average in terms of output and efficiency. (2) The spatial pattern of CRESs varied significantly, with stabilization in hotspots, improvement in coldspots, and the highest proportion of “A progress zones” in the east (45%). (3) Vegetation cover and annual precipitation were the two mainpositive factors that most strongly influenced the intensity of the CRESs, with values of 1.494 and 1.196, respectively; GDP had the most significant negative effect, with a value of −0.189; and population density had the largest range of effects, with a bandwidth of 1629. (4) Except for annual rainfall and aspect, the remaining eight influencingfactors, including population density, GDP, altitude, NPP, vegetation cover, annual temperature, and annual humidity, had positive and negative bidirectional effects on CRESs. Overall, this study emphasizes the need for differentiated, sustainability-oriented management strategies to better integrate ecosystem service evaluations into regional planning and sustainable policy development. Full article

Advances in neuroimaging and intraoperative mapping have transformed brain tumour surgery from anatomy-based resection to function-guided intervention. This review synthesises current evidence on multimodal strategies for maximising tumour removal while preserving cognitive and neurological function. Integrating task-based and resting-state functional MRI (fMRI), diffusion tensor imaging (DTI), tractography, and connectomic analysis enables personalised mapping of eloquent and cognitive networks. Intraoperatively, awake craniotomy with direct electrical stimulation (DES) remains the gold standard for real-time functional validation, while adjuncts such as intraoperative MRI (iMRI), 5-aminolevulinic acid (5-ALA) fluorescence, and ultrasound-based extended resection accuracy. However, these technologies present unique limitations, including neurovascular uncoupling in fMRI, tract distortion in DTI, and resource constraints in low-income settings. Our review differentiates their application across low-grade and high-grade gliomas, emphasising that tumour biology determines the balance between neuroplasticity-driven mapping and imaging-guided radicality. Key future priorities include validation of multimodal imaging protocols, integration of longitudinal neuropsychological outcomes, and development of interpretable connectomic models. Addressing the technological and ethical challenges of high-field MRI, data standardisation, and cost-effective implementation will be essential for equitable global adoption. Ultimately, the evolution of functional neurosurgery depends not only on new technologies but on integrating multimodal evidence and patient-centred outcome measures to achieve reproducible, safe, and personalised brain tumour surgery. Full article

Introduction: Huntington’s disease is a genetic disorder, also known as an autosomal dominant neurodegenerative disease, that has typical manifestations such as motor disturbances, cognitive decline, and psychiatric symptoms. Neurologists initially classified it as a movement disorder because the diagnosis is primarily based on the presence of extrapyramidal motor symptoms. However, after careful examination of several cases, it was revealed that chorea was only one type of motor dysfunction and that tics and myoclonus were also present. Regarding psychiatric symptoms, studies have shown that patients presenting psychosis-related symptoms have a worse evolution with poor prognosis, and it was concluded that they present distinct clinical, imaging, and biological characteristics. Case presentation: The present case report aims to describe the onset of a particular case of Huntington’s disease, taking into consideration the fact that early psychotic symptoms, very similar to those identified in schizophrenia, could represent indicators of Huntington’s disease onset. An interesting aspect of this case was that our patient had no family history of neurological conditions but had a clinical picture characterized by delusions and hallucinations. These symptoms were considered criteria for schizophrenia. Moreover, chorea motor movements appeared several years after the onset of psychosis, determining the need for the diagnosis to be changed from schizophrenia to Huntington’s disease. Conclusion: We need to point out that psychiatric symptoms could represent the only initial visible change in the clinical picture, being also considered as indicators of Huntington’s disease onset. These features could help patients be easily and faster identified, allowing for proper medical interventions to be provided. Full article

Heavy metals (HMs) were originally formed in the universe long before human evolution and are now ubiquitous in the environment, where some HMs are good as essential elements for human health while others are not. The purpose of this analytical review is to provide an updated clinical overview on health risks attributable to drinking water containing specific HMs and to discuss new aspects of molecular steps leading to disrupted diseases. This approach was favored because the study cohorts were homogeneous, since exposed individuals lived in households where all members had access to the same drinking water of constant quality. Among the HMs under consideration, aluminum, arsenic, cadmium, chromium, copper, iron, lead, manganese, and mercury were detected in drinking water and represented a health risk if levels were above thresholds recommended by national and international regulatory authorities. For example, (1) aluminum increased the risk of dementia and Alzheimer’s disease; (2) arsenic was associated with the development of bladder cancer; (3) cadmium increased the no-carcinogenic, as well as the carcinogenic, health risk; (4) chromium was considered as a risk factor for liver and kidney injury, as well cancer development; (5) copper contributed to cognitive impairment in the aging population and Alzheimer’s disease; (6) iron increased the non-carcinogenic health risk; (7) lead impaired neurodevelopmental functions in children; (8) manganese increased the risk of attention-deficit hyperactivity disorder (ADHD); and (9) mercury was causally related to chronic kidney disease. In contrast, for nickel and zinc, no overt health risks have been reported, likely due to low levels in the drinking water, attributable to their low water solubility. Of note is the good news that some HMs represent essential elements for human health. In essence, many HMs were detected in drinking water and exerted non-carcinogenic or carcinogenetic health risks, requiring proactive management of national and international regulatory authorities. Full article

Blue Finance has rapidly emerged as a strategic frontier for channeling capital toward sustainable and resilient ocean economies, connecting financial innovation with environmental governance and climate responsibility. However, its conceptual foundations remain fragmented, hindering theoretical integration and policy application. This study conducts a comprehensive bibliometric and science-mapping analysis of 217 Scopus-indexed publications (2007–2025), using Biblioshiny (Bibliometrix v4.2.2), VOSviewer v1.6.20, and Gephi v0.10.1 to trace the intellectual evolution, thematic configuration, and research agenda of Blue Finance. The analysis reveals a rapidly consolidating field that has evolved through three distinct phases, anchored in sustainability science but constrained by limited financial integration. The field’s cognitive structure is organized around three interlinked pillars: the climate–environmental interface, sustainability integration and governance, and innovative financial mechanisms enhancing economic resilience. Emerging research hotspots in blue bonds, sustainable finance, and blue justice signal a paradigm shift from normative ecological awareness to actionable, market-aligned resilience. The findings outline a forward-looking research agenda that strengthens theoretical consolidation, governance accountability, and sustainable investment frameworks. This study offers strategic guidance for researchers, investors, and policymakers, positioning Blue Finance as a transformative catalyst that unites innovation, resilience, and equity in shaping the future of sustainable finance. Full article

Docosahexaenoic acid (DHA), the dominant polyunsaturated fatty acid in photoreceptors, neurons, and synapses, is usually described as a passive structural membrane constituent. We propose a different view: DHA is a quantum-electronically active molecule whose conjugated double-bond system creates an electron-rich matrix that couples with proteins to form quantum “clouds” and high-speed signaling central to recognition, recall, and cognition. Integrating evidence from molecular evolution, biophysics, and neuroscience, we argue that, as the original chromophore, DHA’s unique properties enabled the emergence of the nervous system and continue to provide the electronic substrate for cognition. By suggesting that cognition depends not only on protein-based mechanisms but on DHA-mediated electron dynamics at the membrane–protein interface, this perspective reframes DHA as an active, conserved determinant of brain evolution and function. Full article

Small cell lung cancer (SCLC) is an aggressive malignancy with a high incidence of brain metastases. Prophylactic cranial irradiation (PCI) was developed to reduce central nervous system (CNS) relapses and has been shown to improve survival, particularly in limited-stage disease. The pivotal Auperin meta-analysis and subsequent studies confirmed its role in patients achieving a complete response to initial therapy. In extensive-stage SCLC, earlier trials demonstrated reduced brain metastases and modest survival gains, but more recent studies incorporating routine magnetic resonance imaging (MRI) surveillance failed to show overall survival benefits, supporting MRI monitoring with salvage therapy as an alternative. Neurocognitive toxicity remains the major limitation of PCI, especially in older adults. Common effects include memory impairment, cognitive changes, and a reduced quality of life. Advances such as hippocampal avoidance PCI and neuroprotective strategies like memantine have shown the ability to mitigate long-term decline. Modern radiotherapy techniques, including intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), enable the precise sparing of critical structures while maintaining intracranial control. The integration of immunotherapy has shifted treatment paradigms in SCLC. While checkpoint inhibitors have improved systemic outcomes, their impact on brain relapses and interactions with PCI remain uncertain. This review provides an overview of the evolution of PCI in SCLC, while emphasizing current challenges and future directions. Full article

This review traces the historical evolution, conceptual foundations, and contemporary applications of the term homeodynamics across biological, ecological, cognitive, and social systems. Initially coined in the 19th century but largely forgotten, the term re-emerged in the second half of the 20th century as scholars sought to describe dynamic stability in open, self-organizing systems. From Yates’s theoretical formalization in biology to Rattan’s work in biogerontology and recent applications in psychology and organizational theory, homeodynamics has progressively evolved from a synonym of homeostasis to a distinct systems concept. It now denotes the capacity of complex systems to sustain coherence through transitions between multiple temporary equilibria, integrating feedbacks, bifurcations, and adaptive reconfigurations. By revisiting the term’s lineage, this review clarifies its epistemological scope and proposes its use as a heuristic and modeling framework for understanding dynamic stability and regime shifts in living and social systems. Full article

Rural collective entrepreneurship poverty alleviation within the university participation context is regarded as a “socio-technical-economic” hybrid system, which aims to generate long-term economic benefits and social well-being for rural collectives through the knowledge of universities and realize the effect of poverty alleviation. However, the existing research has largely overlooked the dynamic mechanisms involved, especially how rural collectives transition from a passive response to a proactive creation in the context of university participation. Thus, we employ Complex Adaptive Systems (CAS) theory’s “detectors-IF/THEN rules-effectors” framework through a longitudinal case study. These findings demonstrate that (1) detectors have transitioned from “specialized knowledge embedding” to “diverse knowledge embedding,” which enables broader information scanning; (2) IF/THEN rules undergo cognitive destructuring to cognitive restructuring, fostering adaptive knowledge orchestration strategies; and (3) effectors shift from exploiting vertically related opportunities to horizontally related opportunities. (4) Cross-phase evolution: The knowledge flow mechanism of “knowledge spillover-organizational learning-knowledge absorption” propels “detectors, IF/THEN rules, and effectors” from the passive response phase to the proactive creation phase. This study advances theoretical understanding of CAS and research on entrepreneurship for poverty alleviation. Full article

Background: Tremor-dominant Parkinson’s disease (TDPD) is the most common subtype of PD. Tremor is difficult to treat and less than 50% of patients respond to dopaminergic medications. Magnetic resonance guided focused ultrasound (MRgFUS) thalamotomy is an incisionless noninvasive method for treating pharmacoresistant tremor in PD patients, but its effect on progression of PD is unknown. In this study, we investigate the efficacy of MRgFUS thalamotomy on progression of motor and non-motor symptoms, using a levodopa equivalent daily dose (LEDD) requirement. Methods: A total of 21 PD patients with ineffective tremor correction by medical therapy underwent MRgFUS thalamotomy. Assessments of motor and non-motor symptoms, adverse events (AE), changes in LEDD, and evolution of FUS (focused ultrasound) lesion were performed on the day before surgery, and then 2 days, as well as 3, 6, and 12 months, after the procedure. Results: On the 2nd day after FUS thalamotomy, 11 patients were tremor-free and, in 10 patients, tremor decreased by 80–90% with a concomitant reduction in hypokinesia and rigidity. By the end of the 12th month, 5 patients remained tremor-free; in 11 patients, mild/moderate tremor re-emerged; and in 5 patients, there was a relapse of severe tremor. Quality of life (QoL) and activities of daily living (ADL) improved significantly at 3 months and remained stable thereafter. Cognitive function improved in patients with baseline MoCA score < 26 points at 3 months after FUS. Anxiety progressed between baseline and end of follow-up. By the end of the follow-up period, LEDD was lowered or stable in 9 patients. Four patients had persistent mild AE. Conclusions: This open label study suggests a beneficial effect of MRgFUS in reducing tremor, hypokinesia, and rigidity and improving QoL, ADL, and cognitive function in TDPD patients in the short term, although long-term data needs to be collected in further studies. Full article

We investigate why the remarkable diversity of human identity, including gender fluidity, non-binary roles, and varied sexual orientations, is fundamentally rooted in the evolutionary and neurocognitive complexity of the human brain. Drawing upon interdisciplinary evidence from comparative biology, neuroimaging, anthropology, and social neuroscience, this paper explores how increased neural complexity across evolutionary trajectories supports behavioral plasticity and identity diversification. The concept of neural degeneracy, wherein different neural structures produce functionally similar outcomes, is central to understanding how individual and cultural diversity naturally emerges from the brain’s highly adaptable networks. By reviewing historical, prehistoric, and cross-species data, the paper demonstrates that identity diversity is neither recent nor culturally limited but has longstanding evolutionary and social foundations. Despite substantial scientific consensus on this inherent complexity, societal resistance persists, often driven by oversimplified and biologically reductionist interpretations of neuroscience. To counter these misunderstandings, the article introduces Complexity Neuroethics, a framework advocating the acknowledgment of diversity of identity expressions as an evolutionarily expected outcome of neurocognitive evolution. Ultimately, the review calls for a transformative dialogue between neuroscience and society, promoting policies, healthcare practices, and educational initiatives aligned with neuroscientific realities to foster more inclusive societies that embrace self-identity as an evolutionary and cognitive achievement. Full article

Third-wave cognitive-behavioral therapies (CBT3) have progressively shifted the focus of psychotherapy from symptom reduction to process-based and transdiagnostic mechanisms of change, emphasizing self-identification as a core dimension. Within this evolution, the Self-Identification Program (SIP) represents a conceptual and clinical advancement particularly relevant to mood disorders, where maladaptive self-identification, rumination, and self-judgment play central roles. SIP directly targets dysfunctional self-identification—the reification of transient and maladaptive mental contents as defining features of a self—through a framework integrating the three levels of CBT3: mindfulness (CBT3.1), loving/kindness and compassion (CBT3.2), and deconstructive insight into the nature of a self (CBT3.3). Theoretically, SIP aligns with dimensional psychiatry (AMPD, HiTOP, RDoC) and recent advances in behavioral linguistics (Relational Frame Theory) and psychotherapy (Process-Based Behavioral Therapy). By integrating linguistic, affective, and neuroscientific perspectives, SIP bridges contextual behavioral science and contemplative practice, offering a unified, process-based model of identity transformation. Clinically, SIP extends CBT3 beyond mindfulness and loving/kindness and/or compassion training to specifically address the mechanism by which self-identification becomes a source of suffering—namely, the mistaken identification with an independent and permanent self. In doing so, SIP provides a novel, mechanistically grounded pathway toward enduring change in depressive and bipolar spectrum disorders. Full article

The rapid integration of artificial intelligence (AI) into professional, educational, and everyday cognitive processes has created a dual dynamic of cognitive growth and cognitive atrophy. This study introduces a unified theoretical and quantitative framework to analyze these opposing tendencies and their equilibrium, conceptualized as the cognitive co-evolution model. The model interprets human–AI interaction as a nonlinear process in which reflective engagement enhances metacognitive skills, while over-delegation to automation reduces analytical autonomy. To quantify this balance, the paper proposes the cognitive sustainability index (CSI) as a composite measure integrating five behavioral parameters representing autonomy, reflection, creativity, delegation, and reliance. Simulation examples and domain-specific illustrations, including the case of software developers, demonstrate how CSI values can reveal distinct cognitive zones ranging from atrophy to synergy. Building upon these findings, the paper develops the framework of applied cognitive management, which links cognitive monitoring with adaptive interventions across individual, educational, professional, and institutional levels. The results highlight the need for organizations and policymakers to monitor cognitive sustainability as a strategic indicator of digital transformation. Maintaining CSI above the sustainability threshold ensures that automation enhances rather than replaces human reasoning, creativity, and ethical responsibility. The study concludes by outlining methodological challenges and future research directions toward a quantitative science of cognitive sustainability and co-evolutionary human–AI ecosystems. Full article

This study comprehensively analyses how AI tools scaffold and share metacognitive processes, thereby facilitating students’ learning in STEM classrooms through a mixed-method research synthesis combining bibliometric analysis and systematic review. Using a convergent parallel mixed-methods design, the study draws on 135 peer-reviewed articles published between 2005 and 2025 to map publication trends, author and journal productivity, keyword patterns, and theoretical frameworks. Data were retrieved from Scopus and Web of Science using structured Boolean searches and analysed using Biblioshiny and VOSviewer. Guided by PRISMA 2020 protocols, 24 studies were selected for in-depth qualitative review. Findings show that while most research remains grounded in human-centred conceptualisations of metacognition, there are emerging indications of posthumanist framings, where AI systems are positioned as co-regulators of learning. Tools like learning analytics, intelligent tutoring systems, and generative AI platforms have shifted the discourse from individual reflection to system-level regulation and distributed cognition. The study is anchored in Flavell’s theory of metacognition, General Systems Theory, and posthumanist perspectives to interpret this evolution. Educational implications highlight the need to reconceptualise pedagogical roles, integrate AI literacy in teacher preparation, and prioritise ethical, reflective AI design. The review provides a structured synthesis of theoretical, empirical, and conceptual trends, offering insights into how human–machine collaboration is reshaping learning by scaffolding and co-regulating students’ metacognitive development in STEM education. Full article

Background: Stroke leads to lasting disability by disrupting the connectivity of functional brain networks. Although several rehabilitation methods are promising, our full understanding of how these strategies restore network function is still limited. Here, we map how non-invasive brain stimulation (NIBS), brain–computer interface (BCI)/neurofeedback, virtual reality (VR), and robot-assisted therapy restore connectivity within the sensorimotor network (SMN), default mode network (DMN), and salience network, and we contextualize these effects within the known temporal evolution of post-stroke motor network reorganization. Methods: This scoping review adhered to PRISMA guidelines and searched PubMed, Cochrane, and Medline from January 2015 to January 2025 for clinical trials focused on stroke rehabilitation with functional connectivity outcomes. Included studies used conventional therapy, neuromodulation, or feedback-based interventions. Results: Twenty-three studies fulfilled the inclusion criteria, covering interventions like robotic training, transcranial stimulation (tDCS/TMS), brain–computer interfaces, virtual reality, and cognitive training. Motor impairments were linked to disrupted interhemispheric sensorimotor connectivity, while cognitive issues reflected changes in frontoparietal and default mode networks. Combining neuromodulation with feedback-based methods showed better network recovery than standard therapy alone, with clinical improvements closely associated with connectivity alterations. Conclusions: Effective stroke rehabilitation depends on targeting specific disrupted networks through various modalities. Robotic interventions focus on restoring structural motor pathways, feedback-enhanced methods improve temporal synchronization, and cognitive training aims to enhance higher-order network integration. Future research should work toward standardizing connectivity assessment protocols and conducting multicenter trials. This will help develop evidence-based, network-focused rehabilitation guidelines that effectively translate mechanistic insights into personalized clinical treatments. Full article