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PubMed2026

A systematic review and meta-analysis of visuospatial attentional deficits in Parkinson's patients.

Parkinson's disease (PD) is a neurodegenerative condition primarily characterized by motor deficits, yet cognitive impairments are increasingly recognized. While deficits in executive functioning are well documented even in the absence of cognitive decline, evidence of attentional deficits in PD remains inconsistent, and the role of motor symptom lateralization is unclear. In this systematic review and meta-analysis, we examined visual attention in right-handed, cognitively unimpaired idiopathic PD patients, focusing on the canonical attentional domains (sustained, selective, divided) and processes (alerting, endogenous and exogenous orienting, reorienting), as well as visuospatial bias. Four databases were searched for studies comparing PD patients with healthy controls. Meta-analytic estimates were derived using Hedges' g within random-effects models, and studies that could not be quantitatively integrated were summarized narratively. In addition, studies directly comparing patients with left- and right-predominant motor symptoms (LPD vs. RPD) were reviewed qualitatively. Across 51 studies, PD patients exhibited deficits in sustained, selective, and divided attention. Among attentional processes, only exogenous orienting was impaired, whereas alerting, endogenous orienting, and reorienting were preserved. Findings from the few studies examining visuospatial bias indicated small, context-dependent shifts in spatial attention rather than a consistent directional bias. These findings indicate that PD patients show visual-attentional impairments, particularly under high-demand conditions, while basic alertness and voluntary orienting appear preserved. Exogenous orienting deficits and subtle rightward spatial tendencies in LPD suggest disruption of right-hemisphere attentional networks. These results have implications for early cognitive assessment, rehabilitation strategies, and understanding the neural bases of attentional dysfunction in PD.

Humans↗

PubMed2026

Access to palliative care in rural settings: A mixed-methods systematic review.

BACKGROUND: Rural populations experience persistent inequities in access to palliative care. Existing evidence often describes individual barriers separately, with less attention to how access breaks down across the care pathway or how different service configurations shape access. OBJECTIVES: To synthesise evidence on access to palliative care in rural settings and examine how access barriers, service models, and implementation conditions interact across the care pathway. METHODS: A mixed-methods systematic review using a convergent integrated approach searched nine databases (PubMed, Embase, CINAHL, Web of Science, Scopus, PsycINFO, CNKI, WanFang, SinoMed) from inception to 15 March 2026, supplemented by hand-searching. Eligible studies were primary qualitative, quantitative, and mixed-methods studies on access to palliative care for adults in rural or non-urban settings. Two reviewers independently screened studies, extracted data, and assessed quality using the Mixed Methods Appraisal Tool. Findings were mapped to the Levesque access framework, analysed using the updated Consolidated Framework for Implementation Research, and integrated through mixed-methods synthesis, with additional coding of service models. RESULTS: Thirty-four studies were included, of which 26 were conducted in high-income countries and eight in low- and middle-income countries. Service configurations included specialist or hospice-oriented care, generalist or primary-care-oriented care, mixed specialist-generalist models, home-based and caregiver-centred care, nurse-coordinated services, telehealth-supported care, and community or implementation-oriented approaches. Access broke down cumulatively across four interdependent stages: recognition, entry, reach, and use and continuity, with affordability constraining every stage. Recognition was limited by low awareness, poor service visibility, and delayed identification of need. Entry was shaped by stigma, trust, family expectations, and unclear referral processes. Reach was constrained by distance, transport, workforce shortages, limited specialist capacity, and weak infrastructure. Use and continuity were affected by fragmented coordination, weak transitions, unstable follow-up, and reliance on family caregivers. Access problems varied across service configurations. Evidence on service innovations was methodologically less certain, and the overall evidence base remained concentrated in high-income countries. CONCLUSIONS: Access to palliative care in rural settings is best understood as a pathway and service-configuration problem rather than simply a deficit in service availability. Improving access requires earlier recognition, clearer referral routes, stronger specialist-generalist and nursing links, better support for family caregivers, and greater attention to affordability, continuity, and rural settings with limited resources. REGISTRATION: International Prospective Register of Systematic Reviews: CRD420261340783.

Health Services Accessibility↗

PubMed2025

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

Humans↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii↗

PubMed2026

Robotic assistance in total hip arthroplasty: a systematic review and meta-analysis of leg length, cup orientation, and early outcomes.

This review examined whether robotic assistance alters postoperative leg-length discrepancy (LLD), acetabular cup orientation, or early hip-specific outcomes relative to conventional total hip arthroplasty (THA). We searched PubMed and Web of Science through May 2026 for comparative English-language reports. Study eligibility, data extraction, and methodological appraisal were undertaken independently by two reviewers. Mean differences (MDs) and 95% confidence intervals (CIs) were calculated in Review Manager 5.4. Model selection was based on the target estimand and anticipated clinical and methodological diversity; leave-one-out and alternative-model sensitivity analyses were undertaken for heterogeneous outcomes. The protocol is registered with PROSPERO (CRD420261454043). The review included seven studies and 968 participants. Compared with conventional THA, robot-assisted THA yielded a smaller postoperative LLD (MD = -2.02, 95% CI -3.46 to -0.58; P = 0.006) and a higher Harris Hip Score (MD = 2.96, 95% CI 1.12 to 4.80; P = 0.002). Mean cup anteversion was lower in the robotic group (MD = -1.52, 95% CI -2.29 to -0.76; P < 0.0001), whereas cup inclination did not differ (MD = -0.71, 95% CI -3.26 to 1.83; P = 0.58). The robotic group also had higher Forgotten Joint Score (MD = 14.68, 95% CI 5.02 to 24.33; P = 0.003) and Oxford Hip Score values (MD = 2.61, 95% CI 0.71 to 4.51; P = 0.007). Robotic assistance was linked to a modest improvement in leg-length restoration and to higher scores on several early functional measures. The limited number of studies, predominance of nonrandomized designs, and marked heterogeneity in some analyses temper the certainty of these findings.

Humans↗

PubMed2026

Does future-oriented imagery rescripting increase willingness to carry out a social anxiety-related behavioral experiment? An extended replication.

BACKGROUND AND OBJECTIVES: Mental images of threat are common in social anxiety disorder and could impede exposure to fear-relevant situations. Landkroon et al. (2022) found that imagery rescripting of anticipated future threat, compared to no-task, increases willingness of non-clinical individuals to conduct a social anxiety-related behavioral experiment. The aim of this two-day preregistered extended replication study was to examine whether the effects persist beyond the intervention session by scheduling the behavioral experiment 1-7 days after the intervention. METHODS: On Day 1, 60 pre-screened participants were asked to design a behavioral experiment to test an idiosyncratic negative belief about a feared social situation. They were then randomly assigned to imagery rescripting (focused on their worst feared outcome of the behavioral experiment) or no-task. Participants' willingness to do the behavioral experiment and their threat beliefs was measured. On Day 2, they were asked to carry out the behavioral experiment. RESULTS: The imagery rescripting group, compared to the control group, did not show increased willingness or compliance to do the behavioral experiment on Day 1 or 2. Furthermore, the imagery rescripting did not lead to greater reductions in threat beliefs on either day. LIMITATIONS: The quality of the imagery rescripting intervention was not assessed, and given the brief nature of the intervention, any effects may have dissipated before participants decided whether to carry out the behavioral experiment. CONCLUSIONS: There was no evidence that imagery rescripting leads to changes in willingness or compliance to do a fear-relevant behavioral experiment. More research is needed to examine interventions that can enhance exposure in socially anxious people.

Humans↗

PubMed2026

Spatial proximity or vector orientation? Re-evaluating ECG interpretation in anterior myocardial infarction using cardiac magnetic resonance.

BACKGROUND: The electrocardiogram (ECG) is widely used to infer infarct location and extent in anterior myocardial infarction (MI), based on either anatomical lead proximity or vectorial orientation of ST-segment deviation. However, the validity of these approaches against direct imaging of myocardial injury remains uncertain. METHODS: In this prospective study, 105 patients with anterior MI underwent cardiac magnetic resonance (CMR) imaging 3-7 days after presentation. Admission ECGs were analyzed using (1) conventional ECG localization categories, and (2) simplified frontal and horizontal ST-axis orientation. CMR-defined injury distribution was assessed using late gadolinium enhancement and myocardial edema imaging. RESULTS: Conventional ECG localization categories demonstrated no significant association with CMR-defined infarct distribution (P = 0.24), with poor agreement (κ = 0.122) and substantial overlap across categories. Simplified ST-axis orientation showed modest and inconsistent associations with infarct location and did not meaningfully explain infarct size. In contrast, global ST-segment burden was associated with CMR-defined infarct size (ΣSTE: standardized β = 0.307, P = 0.002; lead count: standardized β = 0.267, P = 0.007). CONCLUSIONS: In this selected cohort of reperfused LAD-related anterior STEMI patients undergoing early CMR, conventional ECG localization categories and simplified ST-axis orientation showed poor or inconsistent correspondence with CMR-defined infarct distribution, whereas global ST-segment burden showed a modest association with infarct size. These findings suggest that, in this cohort, the ECG may be better suited to reflect the extent of myocardial injury rather than its precise anatomical location.

Humans↗

PubMed2026

From bioactive compounds to volatile profiles: a multidimensional characterization of Indonesian stingless bee honeys.

BACKGROUND: Stingless bee honeys are drawing increasing attention as ingredients for functional foods and health-oriented products because of their distinctive sensory characteristics and bioactive potential. In this study, honeys collected from nine stingless bee species reared in West Sumatra, Indonesia, were comprehensively characterized using physicochemical indices, antioxidant assays [DPPH (i.e. 2,2-diphenyl-1-picrylhydrazyl) and ferric reducing antioxidant power], microbiological screening, volatile profiling [gas chromatography-mass spectrometry (GC-MS)] and Fourier transform infrared (FTIR) fingerprinting. RESULTS: Marked between-sample variability was observed across key quality attributes, including pH (2.80-3.68), Brix (49.83-61.25), viscosity (23.36-175.22 cP) and color parameters. FTIR spectra were consistent with carbohydrate-rich matrices and exhibited carbonyl-related bands. GC-MS profiling identified linalool oxide isomers and junenol among the predominant volatiles. To the best of our knowledge, junenol has not previously been reported in stingless bee honey and may represent a potential regional chemical marker for Indonesian stingless bee honeys. Lactic acid bacteria were detected in selected samples, whereas yeast and mold were not detected. Antioxidant activities were comparatively low, which may reflect local environmental and ecosystem-related factors. CONCLUSION: The results provide a multi-parameter baseline for stingless bee honeys produced within a shared ecosystem in West Sumatra and demonstrate the value of integrating conventional chemical indices with FTIR and volatile fingerprints for quality assessment. This combined approach may also support future authentication and origin-tracing frameworks for Indonesian stingless bee honeys. © 2026 Society of Chemical Industry.

Animals↗

PubMed2026

Impact of a CARE-ORIENT Education Program on Oral Hygiene Among Institutionalized Older Adults: A Double Blinded Cluster Randomized Controlled Study.

BACKGROUND: Older adults residing in long-term care facilities often depend on caregivers for daily oral care. Inadequate caregiver training may contribute to poor plaque control and denture hygiene. METHODS: A six-month parallel-arm cluster randomized controlled study was conducted in selected long-term care facilities in Northern India. Two old age homes were randomly selected, with one allocated to the intervention group and the other to the control group. A total of 150 older adults and 46 caregivers participated. Caregivers in the intervention group received a structured caregiver oriented oral health education. Clinical assessments were performed at baseline, 3 and 6 months. Outcomes included Debris Index, Turesky-Gilmore-Glickman Plaque Index, Denture Plaque Index and Denture Stomatitis Index. Caregiver knowledge and practice were evaluated using a validated questionnaire. RESULTS: Caregiver knowledge and practice scores improved significantly in the intervention group at 3 and 6 months. Significant differences were observed in Debris Index (DI), Plaque Index (PI), and Denture Plaque Index (DPI) in the intervention group over the six-month follow-up (p < 0.001). The Debris Index decreased from 2.76 ± 0.07 at baseline to 1.54 ± 0.05 at 6 months. Plaque Index scores declined from 3.26 ± 0.06 to 1.85 ± 0.08, and Denture Plaque Index scores reduced from 3.22 ± 0.03 to 1.74 ± 0.05. Denture Stomatitis Index improved over time; however, intergroup differences were not statistically significant. CONCLUSION: Structured caregiver-focused oral health education significantly improved oral hygiene among institutionalized older adults over six months, supporting integration of caregiver training within routine long-term care.

Humans↗

PubMed2026

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 × 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (β=0.087; P=.003), injunctive norms (β=0.078; P=.009), perceived susceptibility (β=0.051; P=.03), perceived benefits (β=0.253; P<.001), and trust (β=0.33; P<.001), and negatively associated with perceived severity (β=-0.047; P=.049) and privacy concerns (β=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

Humans↗

PubMed2026

Standardized visual overlays enhance laparoscopic instruction: A mixed-methods evaluation.

Effective communication during laparoscopic procedures is frequently undermined by spatial disorientation and inconsistent terminology between instructors and trainees. This study examined whether standardized visual overlays on endoscopic monitors could enhance communication and learning. We conducted a three-phase mixed-methods study: qualitative observation of 20 laparoscopic teaching cases; a randomized trial of 63 second-year medical students assigned to control, clock, or alphanumeric grid (AG) overlays during three trials of a standardized transfer task; and intraoperative implementation in 44 cases (30 AG, 14 clock) with post-case surveys and qualitative feedback. In simulation, the clock overlay produced the fastest completion times, whereas the AG yielded the lowest error scores, and both overlays outperformed the control. Intraoperatively, the AG was rated higher than the clock for communication clarity, spatial orientation, perceived operative efficiency, and trainee confidence. Standardized visual overlays, particularly the AG, appear to support intraoperative teaching by providing a shared spatial frame of reference.

Laparoscopy↗

PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗

PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans↗

PubMed2026

Post-intervention effectiveness of a computerized personalized cognitive stimulation program adapted according to cognitive reserve in older adults without cognitive impairment in Primary Care: A randomized clinical trial.

BACKGROUND: Cognitive reserve may influence responsiveness to cognitive interventions, yet it is rarely used to tailor computerized stimulation. OBJECTIVE: To evaluate the effectiveness of a computerized cognitive stimulation program personalized according to cognitive reserve on cognition, reserve-related activities, and digital competence in community-dwelling older adults without cognitive impairment in Primary Care. METHODS: In this randomized clinical trial, 102 adults aged ≥65 years with normal cognitive performance were recruited from three primary care centers in Zaragoza, Spain, and stratified by cognitive reserve level before random allocation to intervention or control. The intervention comprised digital literacy sessions followed by 8 weeks of home-based computerized cognitive stimulation tailored to participants' cognitive reserve profiles and life history. Controls received a single group-based health education session focused on maintaining everyday cognitive activity. Outcomes were assessed at baseline and post-intervention using global cognition (MEC-35), the Cognitive Reserve Questionnaire, the Mobile Device Proficiency Questionnaire-16, and domain-specific neuropsychological tests. A total of 100 participants completed the final evaluation and were included in complete-case analyses. RESULTS: Compared with controls, the intervention group showed greater adjusted post-intervention improvements in global cognition (MEC-35 between-group difference: 1.8 points) and several cognitive measures, including temporal orientation, calculation, attention, praxis, verbal fluency, processing speed, executive functions, and verbal learning. CRQ scores and digital competence also improved, with small-to-large effect sizes. CONCLUSIONS: A computerized cognitive stimulation program adapted according to cognitive reserve appears feasible in Primary Care and may improve cognition, engagement in reserve-related activities, and digital competence in older adults without cognitive impairment.

Humans↗

PubMed2026

The effect of olfactory training and odor exposure on visual selective attention.

Olfactory training (OT) is a well-established, non-invasive intervention that improves olfactory function by repeated, structured exposure to odorants. Beyond sensory outcomes, it also influences multiple aspects of cognition. Yet, its influence on attention, a fundamental process underlying many cognitive domains, remains unclear. This study examined the impact of a 12-week OT program on visual selective attentional performance and the effect of on-task odor exposure. Ninety-four healthy participants were initially included, and randomized into OT or placebo groups. Participants completed the d2 Test of Attention simultaneously with and without odor exposure in a randomized sequence at baseline, post-training, and a follow-up four weeks after stopping the training. The d2 test measures commission errors, omission errors, and concentration performance. Ninety-three participants (OT=51, placebo=42) completed baseline measurement, 74 (OT=39, placebo=35) returned for post-training session, and 57 participants (OT=29, placebo=28) returned for the follow-up appointment. Results showed that OT did not significantly improve d2 test performance. In the primary model, on-task PEA exposure reduced commission errors compared to the odorless condition, suggesting a possible transient effect of olfactory input on the inhibitory control in the context of the d2 attentional test. This effect, however, was no longer significant once the follow-up data were included and should be regarded as preliminary. Overall, these findings raise the possibility of a distinction between relatively long-term OT and short-term odor exposure: while OT did not improve visual selective attention, brief on-task odor exposure may transiently enhance inhibitory control during attentional tasks, a possibility that remains to be confirmed.

Humans↗

PubMed2026

Ultra-high-field 7T MRI reveals neural abnormalities of attention networks in relation to cognitive impairment in hypertension.

Hypertension is a significant risk factor for cognitive impairment (CI), yet the corresponding neural network abnormalities remain underexplored. In this study, we examined the associations among global and domain-specific cognitive dysfunction, neuroimaging measures, and blood pressure in a subgroup of hypertensive patients with CI (N = 41) from a randomized controlled trial who underwent ultra-high-field 7 T MRI. Structural atrophy related to CI was localized to regions overlapping the attention networks. Both whole-brain and within-network dysfunction of the attention networks were associated with worse global cognitive performance. Notably, hyperconnectivity within key attention network hubs, including the right anterior insula and posterior intraparietal sulcus, was associated with declined processing speed in hypertensive patients, mediating the association between pulse pressure and processing speed. These findings provide new insights into the neural pathophysiology of hypertension-related CI and suggest potential network-based targets for intervention.

Magnetic Resonance Imaging↗

PubMed2026

Angiotensin II regulates anxiety and social-affective top-down and bottom-up attention control in a sex-dependent manner.

BACKGROUND: The renin-angiotensin system (RAS) has been increasingly recognized as potent modulator of cognitive and affective functions, with angiotensin II type 1 receptor (AT1R) antagonists emerging as repurposing candidate for anxiety and stress-related disorders. However, it remains unclear whether transient AT1R blockade modulates emotional attentional control and whether these effects are sex-dependent. METHODS: We conducted a preregistered, randomized, double-blind, placebo-controlled pharmacological eye-tracking study in 79 healthy adults (males and females) and determined effects of transient AT1R blockade via losartan (50 mg) on emotional attention control using a validated anti-saccade paradigm with social (emotional faces) and non-social stimuli. Treatment effects on state anxiety and oculomotor responses were characterized using traditional metrics and a novel trial-history informed dynamic control framework. RESULTS: Losartan reduced state anxiety irrespective of sex but induced sexually dimorphic effects on attentional control. In females, losartan enhanced performance by reducing endpoint error without altering latency. Conversely, in males, losartan increased endpoint error and prolonged latency of the first correct saccade. Trial-history analyses revealed losartan reduced error probabilities following errors and repeat trials in both sexes. Yet, following correct trials, females receiving losartan maintained lower error probabilities, while males exhibited higher errors, potentially reflecting failure to disengage from effortful control. CONCLUSIONS: The RAS modulates anxiety and attentional control, the latter sex-dependently. AT1R blockade reconfigures attentional processing and adaptive control, suggesting sex-specific therapeutic potential in disorders characterized by excessive anxiety and attentional dysregulation. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov; https://clinicaltrials.gov/;NCT06329050.

Humans↗