Search Results (9,243)

Background/Objectives: Tai Chi (TC) practice has been shown to positively affect the physical, psychological, and cognitive health of older adults. However, discrepancies persist regarding its effectiveness compared to strength training (ST). This study aimed to determine the effect of TC training compared to ST on body composition, physical performance, cognitive function, and psychological well-being in older adults. Methods: A quasi-experimental study was conducted with a convenience sample of 68 women 60 years or older, divided into three groups: (i) Tai Chi Group (TCG) n = 26; (ii) Strength Training Group (STG) n = 21; and (iii) Control Group (CG) n = 21. TCG and STG performed physical training four days a week, 60 min/day, for six months. All participants were assessed for body composition (BFP, body fat percentage; SMM, skeletal muscle mass; SMMI, skeletal muscle mass index); physical performance (4MWT, 4 m walk test; STST, sit-to-stand test; OPP, overall physical performance; HGS, handgrip strength) and Wellbeing (PWBS, psychological well-being scale of Ryff, validated for the Mexican population). The data were analyzed per protocol using repeated-measures ANOVA (TCG & STG vs. CG; TCG vs. STG), and the mean difference (MD) was calculated. Results: TCG showed statistically significant changes in body composition, BFP (MD, −3.4 ± 8.2, p < 0.05), SMM (MD, 1.6 ± 1.4, p < 0.001), and SMMI (MD, 0.72 ± 0.61, p < 0.001) after the intervention compared to CG. However, no differences were observed between TCG and STG (p > 0.05). Regarding physical performance, TCG showed significant changes in 4MWT (MD, −1.0 ± 1.8, p < 0.01) and STST (MD, −3.7 ± 4.8, p < 0.05) compared to CG. Differences were also observed in STST between TCG and STG (MD, −3.7 ± 4.8 vs. 0.45 ± 3, p < 0.05). In addition, TCG showed a significant increase in HGS (MD, 1.1 ± 1.9, p < 0.05) compared to CG, although no differences were observed with STG (p > 0.05). Conclusions: Our findings suggest that TC is more effective than strength training for improving body composition, physical performance, and handgrip strength in older adults living in the community. Full article

Background and Aim: Low back pain (LBP) represents an important public health issue, with approximately 20% of acute cases progressing to chronic low back pain (CLBP). In addition to pain, patients with CLBP also suffer from reduced cognitive performance, depressive symptoms and catastrophic thoughts. Central sensitization (CS) is considered a key point in pain persistence. This study examines CS and its impact on cognitive, emotional, and behavioral functioning in patients with CLBP. Methods: In this cross-sectional study, 67 patients with CLBP were classified using the Central Sensitization Inventory (CSI) into groups with (WCS, n = 32) and without central sensitization (WoCS, n = 35). Cognitive functioning was assessed using the Montreal Cognitive Assessment (MoCA), emotional functioning using the Center for Epidemiologic Studies Depression Scale (CES-D), and behavioral functioning using the Pain Catastrophizing Scale (PCS), including helplessness, rumination, and magnification domains. Normality was assessed using the Shapiro–Wilk test. Between-group comparisons were performed using Mann–Whitney U, chi-square, or Welch’s t-tests. Multivariable linear regression analyses adjusted for age and gender were conducted. Results: Compared with the WoCS group, patients with central sensitization were older (median 58 vs. 50 years, p = 0.001) and more frequently female (71.9% vs. 40.0%, p = 0.018). The WCS group showed higher PCS total scores (31.8 ± 14.2 vs. 16.0 ± 11.9), higher helplessness (14.3 ± 6.1 vs. 6.9 ± 5.5), rumination (12.7 ± 6.2 vs. 7.0 ± 4.8), and magnification scores (4.8 ± 2.4 vs. 2.1 ± 2.1), higher CES-D scores (26.3 ± 10.4 vs. 11.7 ± 7.2), and lower MoCA scores (23.6 ± 3.0 vs. 26.1 ± 2.1) (all p < 0.001). All associations remained significant after adjustment for age and gender. Conclusions: Central sensitization in CLBP is independently associated with greater pain catastrophizing across all domains, increased depressive symptoms, and reduced cognitive performance, supporting its role as a multidimensional clinical phenotype. Full article

Optical microscopy is a fundamental tool in the physical, chemical, and life sciences, enabling direct investigation of structure, dynamics, and function across multiple spatial and temporal scales. Advances in optical design, detectors, and computational techniques have greatly enhanced performance, but have also increased the complexity of modern microscopes, which are now software-driven and embedded in data-intensive workflows. Artificial intelligence has become an important component of this landscape, particularly through task-specific machine learning approaches for image analysis, optimization, and limited instrument control. While effective, these solutions are often fragmented and lack the ability to integrate experimental intent, contextual knowledge, and multi-step reasoning. Recent progress in large language models (LLMs) offers a new paradigm for intelligent microscopy. As foundation models trained on large-scale text and code, LLMs exhibit emergent capabilities in reasoning, abstraction, and tool coordination, allowing them to act as natural interfaces between users and complex experimental systems. This perspective highlights how LLMs can function as cognitive and orchestration layers that connect experiment design, instrument control, data analysis, and knowledge integration. Emerging applications include conversational microscope control, workflow supervision, and scientific assistance for data exploration and hypothesis generation, alongside important technical, ethical, and governance challenges. Full article

Alzheimer’s disease (AD), the most common form of dementia, is a progressive and irreversible neurodegenerative disorder. Structural MRI is widely used for diagnosis, revealing brain changes associated with AD. However, these alterations are often subtle and difficult to detect manually, particularly at early stages. Early intervention during prodromal stages, such as mild cognitive impairment (MCI), can help slow disease progression, highlighting the need for reliable automated methods. In this work, we introduce a dual-level evaluation framework comparing fifteen deep learning architectures, including convolutional neural networks (CNNs), Transformers, and hybrid models, for classifying AD, MCI, and cognitively normal (CN) subjects using the ADNI dataset. A central focus of our work is the impact of robust and standardized preprocessing pipelines, which we identified as a critical yet underexplored factor influencing model reliability. By evaluating performance at both slice-level and scan-level, we reveal that multi-slice aggregation affects architectures asymmetrically. By systematically optimizing preprocessing steps to reduce data variability and enhance feature consistency, we established preprocessing quality as an essential determinant of deep learning performance in neuroimaging. Experimental results show that CNNs and hybrid pre-trained models outperform Transformer-based models in both slice-level and scan-level classification. ConvNeXtV2-L achieved the best scan-level performance (91.07%), EfficientNetV2-L the highest slice-level accuracy (86.84%), and VGG19 balanced results (86.07%/88.52%). ConvNeXtV2-L and SwinV1-L exhibited scan-level improvements of 7.60% and 9.04% respectively, while EfficientNetV2-L experienced degradation of 2.66%, demonstrating that architectural selection and aggregation strategy are interdependent factors. These findings suggest that carefully designed preprocessing not only improves classification accuracy but may also serve as a foundation for more reproducible and interpretable Alzheimer’s disease detection pipelines. Full article

This study evaluated the test–retest reliability of a depth sensor-based Fukuda Stepping Test and examined associations between sensor-derived kinematic parameters and established clinical outcomes in older adults. Eighty-six community-dwelling older adults (mean age 70.3 ± 4.7 years) performed an eyes-closed stepping task monitored by a Microsoft Kinect v2 sensor. Clinical assessments included the Berg Balance Scale, Timed Up and Go test, Five Times Sit-to-Stand, Montreal Cognitive Assessment, International Physical Activity Questionnaire, and WHOQOL-OLD. Test–retest reliability was assessed using intraclass correlation coefficients in a randomly selected subgroup. Reliability estimates varied across parameters, with temporal and displacement-based measures demonstrating more consistent agreement across sessions, whereas selected angular variables showed greater variability. Correlation analyses identified statistically significant associations between trunk kinematic changes and clinical measures, with effect sizes generally ranging from weak to moderate magnitude. Upper trunk rotation was associated with functional mobility measures, while traditional displacement-based metrics demonstrated limited clinical relationships. These findings support the feasibility of markerless depth-sensing technology for objective quantification of movement during the Fukuda Stepping Test and highlight the potential contribution of segmental kinematic parameters to multidimensional functional assessment in older adults. Full article

Background and Purpose: Neurology requires integration of clinical reasoning, imaging interpretation, and current knowledge, making it an ideal field for evaluating large language models (LLMs). Methods: Using 1715 questions from the Taiwan Neurology Board Examination (2018–2024), we assessed four LLMs—GPT-4o, GPT-o1, DeepSeek-V3, and DeepSeek-R1—across four formats: single-choice, multiple-choice, true–false, and image-based items. Results: GPT-o1 achieved the highest overall accuracy (83.86%) and demonstrated strong performance on cognitively demanding tasks (82.50% on true–false; 77.26% on image-based). DeepSeek-V3 scored lowest (65.62%) and showed the greatest variability. Statistical analyses confirmed significant inter-model differences (p < 0.01). Accuracy declined across all models in 2024, coinciding with shifts in question design. DeepSeek-R1 was further penalized by alignment-based refusals, resulting in up to 3.81% score loss. Conclusions: These results position the Taiwan Neurology Board Exam as a rigorous benchmark for LLM evaluation and underscore GPT-o1’s potential utility in neurology education and decision support. Full article

This study examined associations between vocabulary knowledge, reading fluency, cognitive flexibility, and metacognitive monitoring accuracy in reading comprehension among fifth-grade students. Participants (N = 104) completed measures of cognitive–linguistic abilities and reading comprehension, with global metacomprehension judgments after reading and item-level confidence ratings. Metacognitive monitoring accuracy was assessed using calibration of global metacomprehension judgments and item-level confidence ratings. Calibration bias (confidence minus performance) indexed miscalibration direction, and its absolute value indexed calibration accuracy. Resolution reflected discrimination between correct and incorrect item-level responses. Structural equation modeling (SEM) was used exploratorily to examine theoretically motivated direct and indirect pathways via reading comprehension. Vocabulary knowledge showed the strongest associations with calibration accuracy and resolution, fully mediated by comprehension. Reading fluency showed a dual pattern: it contributed positively to resolution through comprehension, while also showing direct associations with lower calibration accuracy, indicating greater miscalibration and overconfident judgment tendencies among more fluent readers. Cognitive flexibility was not significantly related to any monitoring index. By jointly examining distinct indices of monitoring accuracy and separating comprehension-mediated from direct pathways, the study clarifies how cognitive–linguistic abilities may support or bias metacognitive monitoring in developing readers. Linguistic abilities, particularly vocabulary and fluency were central to students’ comprehension monitoring accuracy. Full article

Background/Objectives: Gambling disorder (GD) is a behavioral addiction characterized by persistent and repetitive gambling behaviors that cause significant psychological distress and functional impairment. Increasing evidence indicates that difficulties in emotion regulation are a key factor in the development and persistence of GD. This systematic review aimed to summarize and critically evaluate the existing literature on the relationship between emotion regulation strategies and gambling disorder, with a specific focus on studies using the Emotion Regulation Questionnaire (ERQ) and the Cognitive Emotion Regulation Questionnaire (CERQ). Methods: The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. Systematic searches were performed in PubMed and Scopus databases for studies published between 25 October 2015 and 25 October 2025. The methodological quality and risk of bias of the included studies were evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist and JBI Checklist for Randomized Controlled Trials. Data extraction and synthesis were performed manually by two independent reviewers. Eligible studies included adult participants (≥18 years) diagnosed with gambling disorder or pathological gambling and using the ERQ or CERQ to assess emotion regulation. Results: Nine studies met the inclusion criteria, comprising a total of 607 patients with GD. Across studies, individuals with GD consistently showed reduced cognitive reappraisal, greater expressive suppression, and higher use of maladaptive cognitive strategies such as rumination, catastrophizing, and self-blame. All studies identified impulsivity, emotion dysregulation, alexithymia, or gambling-related cognitive distortions as significant predictors of gambling severity. Neuroimaging evidence from one study further revealed altered activation of frontal regions during negative emotion regulation. Conclusions: This review highlights the central role of emotion regulation in GD. However, the limited available ERQ/CERQ studies in GD were mostly cross-sectional, limiting causal inferences. Second, samples were predominantly male, reducing generalizability to women. Finally, only one study used neurobiological measures, hindering integration of self-report and neural data. These findings emphasize the importance of integrating emotion regulation-based interventions within therapeutic programs for gambling disorder, with ERQ and CERQ being useful tools to assess the pathology. Full article

Creativity involves generating ideas that are both original and useful, relying on intertwined cognitive and metacognitive processes. We examined how individual differences in semantic memory structure and ideation fluency predict creative performance and self-evaluations across two studies. In Study 1, participants completed a creative problem-solving (CPS) task, with semantic memory networks estimated from a relatedness judgment task. Creative output was assessed for originality and usefulness, alongside participants’ self-evaluations. In Study 2, a within-subjects design compared participants’ output and self-evaluation of their performance in a divergent thinking task (alternative uses task) and CPS. Results revealed that ideation fluency and semantic memory network integration consistently predicted originality across tasks. In contrast, usefulness was less reliably predicted, showing task-specific associations with semantic memory network properties primarily in CPS. Importantly, self-evaluations often diverged from objective outcomes, reflecting metacognitive biases shaped by heuristic cues. These findings highlight both stable and context-sensitive mechanisms in creative performance and self-evaluation. Full article

Peer action coordination in middle childhood is thought to benefit from socio-cognitive abilities such as emotion understanding and inhibitory control, but empirical evidence for their role is limited. This study replicates and extends a previous study by examining whether emotion understanding and inhibitory control correlate with children’s peer action coordination in a cooperative sensorimotor problem-solving task. To test this hypothesis, 6- to 10-year-old children (N = 108, M = 8 years, 8 months, 46.3% girls, 53.7% boys) completed the Test of Emotion Comprehension and the Attention Network Task. To assess children’s performance in coordinating their actions with a peer, they were asked to complete the Labyrinth Ball Game—a sensorimotor task that they first performed individually and then together with a peer. Contrary to expectations, there was no direct association between emotion understanding or inhibitory control and children’s peer action coordination after controlling for age, gender, and individual sensorimotor skills. However, a significant interaction between age and gender revealed that older boys showed greater cooperative action coordination performance than younger boys, whereas girls’ performance remained stable across age. These findings challenge the view that individual socio-cognitive abilities straightforwardly support cooperative success, suggesting that peer action coordination in middle childhood may rely on more complex mechanisms, such as gender-specific communicative strategies or social play, rather than on emotion understanding and inhibitory control. Full article

Effective indoor navigation remains a challenge in complex built environments such as hospitals and airports, where disorientation can lead to anxiety, inefficiency, and safety risks. While prior research has focused on outdoor wayfinding or single-metric performance assessments, few studies have examined spatial cognitive efficiency—a multidimensional metric defined as the standardized difference between spatial knowledge acquisition (P) and cognitive resource expenditure (R). In this study, P was derived from expert-rated sketch maps that captured participants’ environmental understanding, while R was indexed by navigation path length, which reflected their exploration effort. This study employed virtual reality to investigate how individual differences and environmental cues shape cognitive efficiency during indoor navigation. Thirty participants explored a high-fidelity virtual environment while behavioral, sketch-based, and questionnaire data were collected. Results revealed a non-significant linear correlation between P and R, consistent with cognitive efficiency as a distinct construct. High-efficiency participants relied more on boundary cues and exhibited “low-speed, short-distance” exploration patterns, whereas landmark-dependent strategies showed lower stability. These findings underscore the theoretical and practical value of cognitive efficiency as a multidimensional metric, offering evidence-based guidance for designing cognitively supportive indoor navigation systems. Full article

Background/Objectives: A widespread assumption exists among scientists, health care providers, and the public that later life is a time of inevitable and universal cognitive and physical decline. This assumption is likely due to considering older persons who improve to be exceptions, and the reliance on aging-health measures that do not allow for improvement. In contrast, we utilized a measure that allowed for an upward trajectory to occur. Our objective was to examine whether a meaningful number of older persons improve with this measure and, if so, to examine whether a promising modifiable culture-based variable, positive age beliefs, contributes to this improvement. Methods: Individuals 65 years and older, who participated in a nationally representative longitudinal study, had their physical health assessed by walking speed and their cognitive health assessed by a global performance measure. We calculated the percentage of the sample that showed improvement in each domain from baseline to the last measurement up to 12 years later. We also examined whether a positive-age-belief measure predicted this improvement in regression models. Results: It was found that 45.15% of persons improved in cognitive and/or physical function over this period, and positive age beliefs predicted these two types of improvement, both with and without adjusting for relevant covariates. Conclusions: Our findings underscore the need to instill or magnify the positivity of age beliefs and to redefine aging so that it includes the possibility of improvement. Full article

Background: Liver cirrhosis is a chronic and progressive disease, and it affects liver parenchymal cells. Although it is known that during the course of this disease, cognitive function, balance, and physical activity levels decrease, and fatigue severity increases, the relationship between these variables remains unclear. This study is the first to examine the relationship between cognitive function level and balance, fatigue, and physical activity levels in patients with liver cirrhosis and was conducted to provide a new perspective on treatment. Aim: This study aims to investigate the relationship between cognitive function and balance, physical activity, and fatigue in patients with liver cirrhosis. Method: A total of 132 patients were included in the study. Cognitive function levels of the patients were measured with the Montreal Cognitive Assessment Scale, balance performance using the One-Legged Stance Test and timed up and go tests, physical activity levels with the International Physical Activity Scale-Short Form, and fatigue levels with the Fatigue Severity Scale. Results: Correlation analyses showed that cognitive function (MoCA) was significantly associated with static balance (r = 0.232, p = 0.007) and fatigue severity (r = −0.297, p = 0.001), whereas no statistically significant relationships were observed with dynamic balance (r = −0.068, p = 0.441) or physical activity (r = −0.011, p = 0.903). Multivariable regression analyses indicated that disease duration (β = 0.02, p = 0.009) and exercise habits (β = 0.65, p = 0.031) were independently associated with cognitive function (MoCA), while disease duration was also independently associated with static balance performance (β = 0.08, p = 0.002). Conclusions: These findings indicate statistically significant associations between cognitive function, static balance, and fatigue severity, whereas no significant associations were observed with dynamic balance or physical activity. These relationships should be interpreted as associative rather than causal and suggest that cognitive status may be clinically relevant when evaluating balance performance and fatigue burden in patients with cirrhosis. Full article

This narrative review synthesizes 24 empirical studies on the role of four types of pedagogical gestures (beat, durational, pitch, and articulatory) in second language (L2) phonetic training since 2010. We reviewed studies involving training interventions to assess the efficacy, mediating factors, and robustness of multimodal training. The findings confirm that gestural training is a powerful tool, yielding the most robust positive effects for L2 speech production and the acquisition of suprasegmental features. Crucially, the effectiveness is highly dependent on gesture-sound consistency and visual saliency of the target phonetic/prosodic feature. However, results are mixed regarding perceptual learning and the generalization of gains to untrained items or novel contexts. While the literature supports the value of gestural training, there are gaps in determining the optimal training paradigm (observing gestures vs. performing gestures), accounting for individual learner differences, and establishing long-term retention and ecological validity. Future research should incorporate longitudinal designs and neurophysiological methods to fully illuminate the cognitive mechanisms that drive the body–mind link in L2 speech acquisition. Full article

Cognitive warfare is a hybrid threat that combines information manipulation with psychological influence, often amplified by digital platforms and synthetic media. Conventional cybersecurity tooling is optimized for technical intrusion and offers limited support for anticipating and responding to influence operations. This paper presents a conceptual framework that structures cognitive warfare threats with General Morphological Analysis (GMA) and links plausible configurations to indicator profiles and response playbooks. We first conduct a PRISMA-informed literature review (2018–2025) to derive a five-dimensional taxonomy (actor, tactic, medium, target, objective). We then apply cross-consistency assessment to remove implausible state-pair combinations and obtain a reduced library of internally consistent scenarios. To support analyst-guided triage, we outline an AI-enabled workflow that maps observable signals to taxonomy states, matches events to scenarios, and prioritizes responses via an auditable, policy-set risk score. Finally, we illustrate the framework on three publicly documented cases and show how each case maps to scenario vectors, indicators, and playbooks. No end-to-end system implementation or performance metrics are reported; the contribution is the structured scenario library and the traceable mapping from observations to response guidance. Full article