Search Results (25)

Prostate cancer, particularly metastatic castration-resistant prostate cancer (mCRPC), presents therapeutic challenges rooted in adaptive lineage plasticity and neuroendocrine transdifferentiation. Conventional genome-based models fail to account for the divergent clinical trajectories observed among tumors that share identical driver mutations. This limitation requires reconceptualizing cancer as a dynamic system in which tumor cells can execute context-dependent molecular programs governed by epigenetic and transcriptional network remodeling. This review critically evaluates three convergent technological pillars reshaping prostate cancer research and clinical care. First, conditional reprogramming (CR) enables the rapid generation of patient-derived models that preserve genomic fidelity, intratumoral heterogeneity, and reversible phenotypic plasticity without genetic manipulation. Second, single-cell and spatial multi-omics approaches have clarified the cellular trajectories underlying luminal-to-neuroendocrine transdifferentiation, identifying a therapeutically actionable intermediate state. They have revealed the hierarchical transcription factor network (FOXA2–NKX2-1–p300/CBP) which orchestrates chromatin remodeling during this lethal transition. Third, physics-informed machine learning and digital twin architectures aim to move beyond correlative risk prediction toward mechanistically sound forecasting of tumor evolution, treatment response, and resistance emergence. We address unresolved challenges in prospective clinical validation, spatial heterogeneity capture, regulatory pathways for functional diagnostics, and the imperative for causal, as opposed to associative, inference from perturbational datasets. The integration of these three domains through closed-loop experimental–computational feedback cycles represents a paradigm shift from reactive to anticipatory precision oncology. Full article

This paper presents an integrated multi-modal framework for detecting hyperthyroidism-associated abnormalities, namely exophthalmos and thyroid-related neck swelling, through the joint analysis of frontal facial and neck images using a deep learning-based approach. The objective of this research is to develop an integrated AI framework that improves hyperthyroid-related abnormality detection by simultaneously analyzing facial images of both the eye and neck based on pattern clinical knowledge. The multi-modal framework mimics a biological visual mechanism by using a dual-pathway architecture that concurrently processes foveal-like details of the eyes and neck. It integrates these high-resolution visual embeddings with quantitative morphological measurements to simulate a clinician’s ability to fuse observation with physical assessment. The proposed system employs a multi-faceted decision-making process derived from three distinct data components: two from frontal face analysis and one from neck region analysis. Specifically, eye regions extracted from facial images are preprocessed using the YOLOv11s model. The proposed system leverages a dual-pathway processing architecture to extract comprehensive diagnostic features. For the eye dataset, the framework utilizes a face mesh-based eye landmark (FMEL) to extract both eye regions and perform eyes unfold processing. These regions are subsequently analyzed by the proposed sclera map unwrapping engine (SMUE) to derive quantitative sclera metrics from both the left and right eyes. To optimize classification, a dual-branch architecture is employed by integrating CNN visual embeddings with SMUE-derived statistical features through a feature fusion layer. Simultaneously, the neck processing path executes the neck region of interest (ROI) prediction {upper, lower} to segment critical regions for goiter assessment via the proposed neck $\mu -\sigma$ ensemble thresholding (NSET) algorithm. The experimental results demonstrate that the proposed algorithm for eye analysis achieved a mean average precision (mAP50) of 96.4%, with a specific mAP50 of 98.6% for the hyperthyroid class. Regarding quantitative scleral measurement, the SMUE process revealed distinct morphological differences, with the experimental data group exhibiting consistently higher pixel distances across the reference points compared with the normal group. Furthermore, the proposed NSET algorithm yielded the highest performance for swollen neck classification with an mAP50 of 92.0%, significantly outperforming the baseline deep learning models while maintaining lower computational complexity. Full article

Epileptogenesis is commonly defined by the emergence of spontaneous seizures after an initial insult; however, convergent experimental and clinical evidence indicates that the underlying disease process begins well before seizures become clinically detectable. During this pre-seizure phase, persistent molecular cascades remodel synaptic plasticity, circuit architecture, and glial–immune signaling. These processes are associated with trait-like alterations in cognition, affect, and behavior. Despite their clinical relevance, these neurobehavioral signatures remain poorly integrated into molecular models of epileptogenesis and are rarely considered as translational biomarkers of disease progression. This review synthesizes evidence linking core epileptogenic molecular cascades—maladaptive synaptic plasticity, glial–immune signaling, oxidative–metabolic stress, and activity-dependent gene regulation—to reproducible alterations in executive control, cognitive flexibility, emotional regulation, and motivational–social behavior. We outline an integrative framework in which these phenotypes are conceptualized as system-level readouts of progressive network reconfiguration rather than nonspecific “comorbidities” or mere consequences of recurrent seizures. Within this perspective, neurobehavioral markers can complement electrophysiological and molecular measures by capturing disease-relevant changes during windows when anti-epileptogenic interventions would be most effective. To increase mechanistic specificity, we provide representative pathway and gene-level anchors across epileptogenesis stages, a structured molecular-to-neurobehavioral mapping, and an operational biomarker panel specifying confounders and minimal controls. These anchors are included to ground the framework in experimentally documented molecular nodes with stage-dependent relevance; examples are representative rather than exhaustive, and evidence strength is indicated as preclinical mechanistic versus associative human observations. Finally, we discuss methodological requirements for biomarker validity (specificity, temporal anchoring, and cross-model consistency) and outline how integrating molecular and neurobehavioral trajectories may refine target discovery and improve the translation of anti-epileptogenic strategies. Conceptualizing epileptogenesis as a progressive disease process with measurable pre-seizure neurobehavioral signatures may broaden biomarker strategies beyond seizure occurrence and support the development of disease-modifying interventions. Full article

Parkinson’s disease (PD) is a heterogeneous clinical syndrome representing the final stage of a complex and long-lasting neurodegenerative process that involves not only dysfunction of the dopaminergic system but also impairments in other neurotransmitter systems. The diversity of the clinical presentation of PD, together with the existence of Parkinsonian syndromes and atypical Parkinsonism—such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and dementia with Lewy bodies (DLB)—has important implications for rehabilitation outcomes and underscores the need for individualized, stage-dependent therapeutic approaches. Juggling is a complex motor activity that integrates cognitive, visuomotor, and balance processes, requiring a high level of concentration, precision, and motor adaptation. In recent years, there has been growing interest in this form of activity as a potential tool for supporting neuroplasticity, cognitive functions, and neurological rehabilitation. The aim of this review was to summarize current scientific evidence on the effects of juggling training on cognitive functions, visuomotor coordination, and balance, as well as to discuss the potential benefits of combining it with controlled hypoxia in patients with Parkinson’s disease (PD). This narrative review additionally considers how disease heterogeneity and stage of progression may influence the effectiveness of such multimodal interventions. This paper reviews the literature concerning the neurophysiological basis of learning to juggle and the mechanisms of brain plasticity, including increases in gray matter volume, improvements in white matter integrity, and reorganization of neuronal networks in motor and associative regions. Attention is drawn to the synergistic potential of combining juggling training with exposure to moderate, controlled hypoxia, which may induce an adaptive response involving the transcription factor HIF-1α, enhance the expression of brain-derived neurotrophic factor (BDNF), and promote angiogenesis and mitochondrial biogenesis. Although juggling and hypoxia are not directly related to training stimuli, both interventions activate overlapping and complementary neuroplastic pathways, providing a conceptual rationale for their parallel consideration and potential integration within future rehabilitation protocols. Juggling delivers task-specific motor–cognitive learning, whereas hypoxia may amplify molecular plasticity signaling, potentially enhancing responsiveness to motor interventions, particularly in patients at early stages of PD when compensatory mechanisms and neuroplastic capacity are relatively preserved. Findings from existing studies suggest that juggling under controlled hypoxic conditions may represent an innovative, safe, and multimodal form of training that supports both cognitive and motor components. Such effects may be particularly relevant in patients at early stages of PD, when compensatory mechanisms and neuroplastic potential are relatively preserved. Such an intervention may contribute to improvements in balance, attention, executive functions, and cognitive flexibility, which is particularly relevant in the context of rehabilitation for patients with neurodegenerative diseases. Importantly, to date, no randomized clinical trials have directly examined juggling performed under controlled hypoxic conditions in PD. Therefore, the present concept should be regarded as translational and exploratory, integrating evidence from juggling-induced neuroplasticity and hypoxia-related physiological adaptations. In this context, the proposed approach represents a proof-of-concept framework for future multimodal interventions rather than an established therapeutic strategy. Available evidence suggests that combining complex sensorimotor skill training with physiological modulation of the internal environment may constitute a novel direction in PD rehabilitation, extending beyond conventional exercise-based models. Despite promising reports, further well-designed clinical studies are needed to determine the optimal training parameters (frequency, intensity, duration, and degree of hypoxia), to evaluate the long-term sustainability of therapeutic effects, and to account for the heterogeneity of PD and related Parkinsonian disorders. Full article

Substance Use Disorder (SUD) constitutes a major and persistent global public health burden, accounting for approximately 600,000 deaths annually, largely driven by opioid use. Despite substantial advances in addiction neuroscience, currently approved therapeutic strategies remain limited in efficacy, as they predominantly target isolated neurobiological processes and fail to concurrently address core mechanisms such as glutamatergic hyperactivity, mesolimbic hypodopaminergic, and dysfunction of cortical and executive control networks. This mechanistic fragmentation contributes to persistently high relapse rates and underscores the need for integrative and multitarget therapeutic approaches. Within this context, ibogaine has re-emerged as a clinical candidate due to its distinctive multimodal neuropharmacological profile and its reported capacity to modulate multiple pathways implicated in addictive behaviours. However, the clinical translation of ibogaine remains substantially constrained by fragmented and heterogeneous evidence, the absence of regulatory frameworks in several jurisdictions, limited phytochemical validation and standardization of available formulations, and unresolved concerns regarding cardiac safety. This scoping review critically synthesizes the available preclinical and clinical literature on ibogaine in the treatment of SUD, with particular emphasis on reported effects on withdrawal symptoms and craving, dose–response relationships, and the occurrence of cardiac adverse events. By clarifying the current state of the evidence and delineating key translational constraints, this review defines the conditions under which ibogaine, an indole alkaloid isolated from Tabernanthe iboga Baill. (Apocynaceae), may warrant continued investigation. The hypothesis of a neurobiological “reset”, supported by emerging preclinical and clinical data, positions ibogaine as a compound of relevance in addiction research and highlights the need for rigorous pharmacological, toxicological, and regulatory evaluation to inform safer and more standardized clinical pathways. Full article

Background: Obsessive–compulsive disorder (OCD) is a heterogeneous psychiatric condition with substantial heritability. Early genetic studies were often underpowered and produced limited reproducibility, but recent large-scale genomic and multi-omic approaches are beginning to elucidate the genetic architecture of OCD. Objectives: This review aims to synthesise current evidence from recent genomic and epigenomic studies on OCD and their implications for molecular pathways of pathogenesis, including endophenotypes. Methods: We reviewed peer-reviewed literature and preprints published in recent years, focusing on multiple genetic approaches, including genome-wide association studies (GWAS), whole exome sequencing (WES), whole genome sequencing (WGS), and methylome-wide association studies (MWAS). We then integrated the results with endophenotypic evidence at the biochemical, physiological, structural, functional, and executive/cognitive levels. Results: Recent large-scale genomic studies provide strong evidence of a highly polygenic contribution from common variants, while rare coding and structural variants also contribute measurably, with enriched signals in pathways relevant to neurodevelopment and, in some cohorts, early-onset presentations. Epigenomic studies have moved from scattered findings to more replicable methylation patterns, including loci influenced by nearby genetic variation and indications of sex-dependent effects. Although convergence at the single-gene level remains limited, cross-study and cross-omics signals increasingly point to biological domains involving synaptic organisation and plasticity, neurological development and chromatin regulation, immune/stress pathways, and cellular homeostasis. Conclusions: The biology of OCD risk is best represented by an integrative model combining polygenic load, contributions from rare variants, and regulatory (epigenetic) mechanisms that influence intermediate phenotypes at the circuit and cognitive levels. The current findings are not yet clinically applicable for individual diagnosis; however, they may inform future multidisciplinary research frameworks and, in the longer term, contribute to the development of more personalised approaches in OCD. Full article

The intratumoral microbiota, comprising bacteria, fungi, and viruses within the tumor microenvironment, actively influences carcinogenesis. Key mechanisms include the induction of host DNA damage, modulation of critical oncogenic signaling pathways such as WNT-β-catenin, NF-κB, and PI3K, and the orchestration of inflammatory processes. The microbiome’s interaction with the host immune system is complex and bidirectional. On one hand, specific microbes can foster a pro-tumorigenic niche by suppressing the activity of cytotoxic T cells and natural killer (NK) cells or by promoting the accumulation of immunosuppressive cell types like tumor-associated macrophages (TAMs). On the other hand, microbial components can serve as neoantigens for T cell recognition or produce metabolites that reprogram the immune landscape to enhance anti-tumor responses. The composition of this microbiome is emerging as a crucial factor influencing the outcomes of immunotherapies. Prospective investigations in cancer immunotherapy ought to prioritize mechanistic inquiry employing integrative multi-omics methodologies. The execution of meticulously designed clinical trials for the validation of microbial biomarkers, and the systematic, evidence-based development of microbiome-targeted therapeutic interventions aimed at enhancing antitumor immune responses. Full article

Mild cognitive impairment (MCI) and sarcopenia are prevalent age-related conditions that often coexist and share common mechanisms such as chronic inflammation, reduced neuroplasticity, and impaired muscle function. Resistance exercise training (RET) has emerged as a promising non-pharmacological strategy capable of addressing both physical and cognitive decline. The aim of this narrative review is to synthesize preclinical and clinical evidence on the effects of RET in older adults with MCI and sarcopenia, with a specific focus on its impact on neuroinflammation, cognitive performance and structural brain changes. At the molecular level, RET activates anabolic pathways, including PI3K/Akt/mTOR, enhances neurotrophic support via BDNF, NT-3, and IGF-1, and promotes hippocampal neurogenesis through exercise-induced myokines such as irisin and cathepsin B. RET also exerts immunomodulatory actions by shifting microglia toward anti-inflammatory M2 phenotypes, attenuating reactive astrogliosis, and supporting oligodendrocyte precursor cell differentiation, thereby improving myelin integrity. Neuroimaging studies consistently report preservation of hippocampal and precuneus gray matter, as well as improved white matter connectivity following RET. Clinically, RET has demonstrated significant and sustained improvements in executive function, memory, and global cognition, with effects persisting for up to 18 months. Collectively, RET represents a multifaceted intervention with the potential to delay progression from MCI to Alzheimer’s disease by integrating neuroprotective, anti-inflammatory, and anabolic effects. Standardization of RET protocols and identification of biomarkers of responsiveness are needed to optimize its role within multimodal dementia-prevention strategies. Full article

Plasticity is a fundamental property of the brain that enables the nervous system to respond appropriately to internal and external stimuli. It primarily involves changes at the synaptic level, mediated by a wide array of molecules, ultimately leading to cognitive and behavioral changes. This review critically contrasts the developmental timing and mechanisms of plasticity in Autism spectrum disorder (early hyperplasticity and excitation–inhibition imbalance) versus Schizophrenia (adolescent overpruning and NMDAR hypofunction) and evaluates evidence for interventions that harness plasticity to improve cognitive and behavioral outcomes. Preclinical and small clinical studies suggest that interventions targeting plasticity-related pathways may improve specific cognitive and behavioral domains. However, effects appear to be symptom-domain-specific and protocol-dependent and larger randomized controlled trials are needed to confirm efficacy. Cognitive remediation for Schizophrenia has been associated with improved executive function and increased hippocampal volume, while virtual reality-based training for Autism spectrum disorder has shown gains in attention and planning skills. By highlighting both molecular mechanisms and therapeutic strategies, this review aims to provide an integrated perspective on how plasticity-targeted interventions could be optimized across neurodevelopmental and neuropsychiatric disorders. Full article

Background: Primary headaches in children and adolescents impose emotional, cognitive, and functional burdens beyond pain. This review synthesizes their psychopathological and neuropsychological dimensions and outlines implications for assessment and care. Methods: We performed a comprehensive review with systematic searches of PubMed, Scopus, and Embase (2015–2025). We included observational/experimental studies and evidence syntheses on 0–18-year-olds with migraine, tension-type, or cluster headache; treatment-only reports were excluded. Results: Across population and clinic samples, primary headaches co-occur with elevated anxiety/depression, frequent ADHD/learning problems, and pervasive sleep disturbances with likely bidirectionality. Interictally, small to moderate neurocognitive differences are most consistent in attention/executive control, processing speed, and verbal memory. Quality of life and school participation are reduced. Standardized tools (e.g., PedMIDAS, PedsQL/KIDSCREEN, SDQ/CBCL, SDSC±actigraphy, NEPSY-II/BRIEF) support multidisciplinary assessment. Conclusions: Care should look beyond pain counts, integrating routine screening of mood, sleep, and cognition; active family involvement; and school–healthcare coordination within stepped-care pathways (education and sleep hygiene for all; targeted CBT for catastrophizing/avoidance) with monitoring that pairs headache frequency with functional outcomes. Full article

This paper proposes a scalable serverless architecture for real-time natural language processing (NLP) on large datasets using Amazon Web Services (AWS). The framework integrates AWS Lambda, Step Functions, and S3 to enable fully parallel sentiment analysis with Transformer-based models such as DistilBERT, RoBERTa, and ClinicalBERT. By containerizing inference workloads and orchestrating parallel execution, the system eliminates the need for dedicated servers while dynamically scaling to workload demand. Experimental evaluation on the IMDb Reviews dataset demonstrates substantial efficiency gains: parallel execution achieved a 6.07× reduction in wall-clock duration, an 81.2% reduction in total computing time and energy consumption, and a 79.1% reduction in variable costs compared to sequential processing. These improvements directly translate into a smaller carbon footprint, highlighting the sustainability benefits of serverless architectures for AI workloads. The findings show that the proposed framework is model-independent and provides consistent advantages across diverse Transformer variants. This work illustrates how cloud-native, event-driven infrastructures can democratize access to large-scale NLP by reducing cost, processing time, and environmental impact while offering a reproducible pathway for real-world research and industrial applications. Full article

Background: Autosomal dominant intellectual developmental disorder 51 (MIM #617788) is caused by pathogenic variants in KMT5B, a histone methyltransferase essential for transcriptional repression and central nervous system development. The disorder manifests as a complex neurodevelopmental syndrome with variable neurological and systemic features. Methods: Two adolescents with nonsense KMT5B variants underwent detailed clinical, neuropsychological, and neuroimaging evaluations, including MRI and ¹⁸FDG PET/CT, analyzed with Statistical Parametric Mapping against matched controls. RNA sequencing was performed, and the literature was reviewed to assess genotype–phenotype correlations. Results: Both patients showed global developmental delay, progressing to autism spectrum disorder (ASD) and developmental coordination disorder (DCD), without intellectual disability (ID). The MRI was normal, but neuropsychological testing revealed executive function impairment, expressive language deficits, and behavioral disturbances. PET/CT consistently demonstrated cerebellar and temporal lobe hypometabolism, correlating with symptom severity. RNA sequencing identified shared dysregulated pathways, notably DDIT4 upregulation, linked to synaptic dysfunction and neuronal atrophy in animal models. Conclusions: The findings highlight cerebellar involvement in DCD and ASD, medial temporal lobe contribution to ASD and executive dysfunction, and DDIT4 as a possible molecular signature of KMT5B loss-of-function. An integrative multimodal approach refined genotype–phenotype correlations and revealed novel brain regions and pathways implicated in KMT5B-related disorders. Full article

Background: Cardiovascular diseases (CVD) are major contributors to global morbidity and mortality, and their association with cognitive impairment has gained increasing attention. Recent studies indicate that the prevalence of post-myocardial infarction (MI) cognitive impairment ranges from 22% to 37%, with attention being one of the most frequently affected domains. Moreover, novel approaches, such as normobaric hypoxic training in cardiac rehabilitation, show potential in improving both cardiovascular and cognitive outcomes. Aim: This narrative review aims to synthesize current evidence on the role of hypoxia in the development of cognitive dysfunction among patients with cardiac diseases, emphasizing shared mechanisms along the heart–brain axis. Methods: We performed a narrative search of PubMed, Scopus, and Web of Science databases using the keywords “hypoxia”, “cognitive impairment”, “myocardial infarction”, “heart failure”, and “CABG surgery”. We included original studies, reviews, and meta-analyses published between 2000 and up to the present in English. Priority was given to peer-reviewed human studies; animal models were included when providing mechanistic insights. Exclusion criteria included case reports, conference abstracts, and non-peer-reviewed sources. Narrative reviews, while useful for providing a broad synthesis, carry an inherent risk of selective bias. To minimize this limitation, independent screening of sources and discussions among multiple authors were conducted to ensure balanced inclusion of the most relevant and high-quality evidence. Results: Hypoxia contributes to cognitive decline through multiple pathophysiological pathways, including blood–brain barrier disruption, white matter degeneration, oxidative stress, and chronic neuroinflammation. The concept of “cardiogenic dementia”, although not yet formally classified, highlights cardiac-related contributions to cognitive impairment beyond classical vascular dementia. Clinical assessment tools such as the Stroop test, Trail Making Test (TMT), and Montreal Cognitive Assessment (MoCA) are useful in detecting subtle executive dysfunctions. Both pharmacological treatments (ACE inhibitors, ARBs) and innovative rehabilitation methods (including normobaric hypoxic training) may improve outcomes. Conclusions: Cognitive impairment in cardiac patients is common, clinically relevant, and often underdiagnosed. Routine cognitive screening after cardiac events and integration of cognitive rehabilitation into standard cardiology care are recommended. Future studies should incorporate cognitive endpoints into cardiovascular trials. Full article

Background/Objectives: Sudden cardiac arrest (SCA) is a major global health concern with high mortality despite advances in resuscitation techniques. Achieving return of spontaneous circulation (ROSC) represents merely the initial step in the extensive rehabilitation journey. This review highlights the critical role of structured, multidisciplinary rehabilitation following ROSC, emphasizing the necessity of integrated physiotherapy, neurocognitive therapy, and psychosocial support to enhance quality of life and societal reintegration in survivors. Methods: This narrative review analyzed peer-reviewed literature from 2020–2025, sourced from databases such as PubMed, Scopus, Web of Science, and Google Scholar. Emphasis was on clinical trials, expert guidelines (e.g., European Resuscitation Council 2021, American Heart Association 2020), and high-impact journals, with systematic thematic analysis across rehabilitation phases. Results: The review confirms rehabilitation as essential in addressing Intensive Care Unit–acquired weakness, cognitive impairment, and post-intensive care syndrome. Early rehabilitation (0–7 days post-ROSC), focusing on parameter-guided mobilization and cognitive stimulation, significantly improves functional outcomes. Structured interdisciplinary interventions encompassing cardiopulmonary, neuromuscular, and cognitive domains effectively mitigate long-term disability, facilitating return to daily activities and employment. However, access disparities and insufficient randomized controlled trials limit evidence-based standardization. Discussion: Optimal recovery after SCA necessitates early and continuous interdisciplinary engagement, tailored to individual physiological and cognitive profiles. Persistent cognitive fatigue, executive dysfunction, and emotional instability remain significant barriers, underscoring the need for holistic and sustained rehabilitative approaches. Conclusions: Comprehensive, individualized rehabilitation following cardiac arrest is not supplementary but fundamental to meaningful recovery. Emphasizing early mobilization, neurocognitive therapy, family involvement, and structured social reintegration pathways is crucial. Addressing healthcare disparities and investing in rigorous randomized trials are imperative to achieving standardized, equitable, and outcome-oriented rehabilitation services globally. Full article

Background: Despite growing interest in the literature on Parkinson’s disease (PD) on cognitive functioning, financial incompetence—a crucial aspect of daily living—and its modulation susceptibility by PD treatment regimens remains relatively understudied. Objective: This systematic review and meta-analysis aimed to synthesize existing evidence on how PD treatments affect financial capacity, assessing both direct financial competence and cognitive or behavioral proxies of financial decision-making. Methods: A comprehensive literature search according to PRISMA protocol was conducted across major biomedical databases, supplemented by gray literature and manual reference list checks. Eligible studies assessed financial capacity directly or indirectly through cognitive proxies (e.g., executive function, decision-making) or financial risk behaviors (e.g., impulse control disorders). Two separate meta-analyses were performed. Heterogeneity (I²), publication bias (Egger’s test), and sensitivity analyses were conducted to assess robustness. Results: Twenty-three studies met inclusion criteria. One study directly measured financial capacity and was analyzed narratively, reporting diminished competence in patients on levodopa therapy. A meta-analysis of cognitive proxies (10 studies) showed a moderate effect size (Hedges’ g = 0.70, 95% CI [0.45, 0.92], p < 0.001), indicating that PD treatments negatively affect executive function and financial decision-making. A second meta-analysis of impulse control and financial risk behaviors (12 studies) revealed a larger effect size (Hedges’ g = 0.98, 95% CI [0.75, 1.22], p < 0.001), strongly linking dopamine agonists to increased financial risk-taking. Moderate heterogeneity (I² = 45.8–60.5%) and potential publication bias (Egger’s test p = 0.027) were noted. Conclusions: These findings suggest that PD treatments negatively impact financial decision-making both directly and indirectly through cognitive and behavioral pathways. Integrating financial decision-making assessments into PD care, particularly for patients on dopamine agonists, is recommended. Future research should prioritize longitudinal studies and standardized neuropsychological measures to guide clinical practice and optimize patient outcomes. Full article