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PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Association between pulse pressure and markers of cognitive function: a systematic review and meta-analysis.

Our aim was to systematically review and meta-analyse evidence on the association between pulse pressure (PP) and cognitive function using PubMed, PsycInfo, Embase and Scopus (inception-July 2025) publication databases. Studies were included if they reported an association between PP and cognitive function and summarized narratively and by performing fixed-effects meta-analysis. The search identified 4171 publications with 43 studies meeting inclusion criteria. Domains assessed included global cognition, memory, language, attention, executive function, processing speed and visuospatial ability. Meta-analysis suggests a positive association between PP and global cognition, and a negative association with memory in both cross-sectional and longitudinal studies with inconsistent findings from narratively summarized studies. Processing speed, executive function and language negatively associated with PP in cross-sectional studies with limited evidence provided by longitudinal studies or narratively summarized studies. There was limited evidence of an association with attention and visuospatial ability.

Humans↗

PubMed2026

Evaluation of the effects of domestic tomato processing on biopesticide residue using natural deep eutectic solvents (NADES) extractions.

The present study evaluated the fate of fourteen botanical biopesticides in processed tomato samples. Various processing methods were employed, including washing, dehydration, and the preparation of juice and sauce. The extraction was performed using more sustainable techniques, aimed at minimizing the environmental impact of conventional organic solvents by substituting them with natural deep eutectic solvents (NADES). Solid-liquid extraction (SLE) and dispersive liquid-liquid microextraction with solidification of floating organic drop (DLLME-SFOD) were utilized for solid and liquid tomato samples, respectively. The NADES used was choline chloride:2,3-butanediol (ChClBt) at a 1:4 molar ratio for both techniques, resulting in recovery values ranging from 69.2 to 106.2% for SLE, and extraction efficiencies reaching up to 46.2% for DLLME-SFOD. The impact of these processes was evaluated employing the processing factor (PF), yielding PF values of less than 1 in all cases. Compounds as pyrethrins, azadirachtin, and rotenone persisted after processing, posing a potential consumer risk.

Solanum lycopersicum↗

PubMed2026

Genomic history of the Caucasus: A systematic review and meta-analysis of ancient DNA studies.

The Caucasus region represents a unique natural laboratory for paleogenetic research due to its complex topography, long-standing role as a migratory corridor and glacial refugium, and exceptional preservation conditions for ancient DNA. This review synthesizes recent genome-wide studies to reconstruct the demographic history shaping the distinctive genetic landscape of modern Caucasus populations. The analysis reveals a deep pattern of continuity, isolation, and periodic admixture. Early genetic differentiation emerged in the Neolithic and Chalcolithic, forming distinct steppe and mountain population clusters. The Bronze Age was a pivotal period marked by large-scale gene flow from the Eurasian Steppe, particularly linked to the Yamnaya expansion, and interactions with Iranian and Anatolian-related groups. Despite these influences, many populations demonstrate remarkable genetic continuity from the Bronze Age to the present day. Significant knowledge gaps persist, particularly for the Paleolithic, Mesolithic, and Neolithic of the North Caucasus, as well as for the Late Medieval and Early Modern periods across the entire region. Addressing these gaps through targeted archaeogenomic studies is crucial for understanding the fine-scale processes that formed the hierarchical structure and high linguistic diversity of Caucasus populations, offering a powerful model for studying human adaptation, interaction, and language-genetics dynamics in a mountainous environment.

Humans↗

PubMed2026

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗

PubMed2026

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

Modulating sentence comprehension in people with aphasia through anodal tDCS: A double-blind randomized cross-over study.

This double-blind randomized cross-over study investigated the effects of perilesional anodal transcranial direct current stimulation (AtDCS) combined with speech-language therapy on sentence comprehension in eight individuals with chronic nonfluent agrammatic aphasia. The behavioral therapy consisted of an intensive comprehension treatment including drilling in sentence-to-picture matching and Mapping Therapy. Each participant underwent both the anodal tDCS and sham stimulation conditions (five received sham first followed by real stimulation, and the remaining three the reverse sequence), with each condition paired with the same behavioral treatment and separated by a four-month washout period. Stimulation was applied over the perilesional area (left BA6) for 20 min during daily 40-min therapy sessions over four consecutive weeks. Sentence comprehension was assessed with the RiComprendo battery and functional communication with the Communicative Effectiveness Index (CETI). Data were analyzed using paired t-tests, Bayesian analyses, and linear mixed-effects models to control for baseline performance and individual variability. Both stimulation conditions produced significant pre-to-post improvements in sentence comprehension, particularly for syntactically complex structures such as passives and center-embedded object relatives. However, gains were overall greater following AtDCS, as reflected in larger effect sizes, stronger Bayes factors, and a significant treatment effect in the mixed-effects models. Only the AtDCS condition yielded significant improvements in self-perceived comprehension abilities on the CETI. These findings suggest that AtDCS over perilesional cortical areas may boost the effects of traditional language therapy on sentence comprehension, supporting its feasibility and potential as an adjuvant intervention in post-stroke aphasia rehabilitation.

Humans↗

PubMed2026

Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

Humans↗

PubMed2026

Probiotic-derived extracellular vesicles as food-based nanocarriers: Mechanisms, functional applications, and future perspectives in food systems.

Probiotic-derived extracellular vesicles (PDEVs) are a promising type of postbiotic nanoparticle derived by fermentation of probiotics, and have gained growing interest as a potential application in food science and nutrition. These are lipid bilayer vesicles of nanoscale, which are naturally released by probiotic cells and contain a wide variety of bioactive molecules, such as proteins, nucleic acids, and metabolites. Moreover, PDEVs are highly stable, biocompatible, and can be easily engineered to have surfaces with high functionality, which makes them good candidates in functional engineering. In contrast to traditional live probiotics, PDEVs overcome the difficulties of preserving microbial viability during processing and storage, thus providing superior safety, stability, and predictable biological performance. This is a systematic review of the various functions of PDEVs in food systems. We conclude on the processes through which PDEVs control intestinal barrier integrity, alter gut microbiota composition, and alter host immune responses, and their potential to enhance gut health when added to functional foods. In addition to their health-promoting effects, PDEVs have shown significant potential as natural antimicrobial agents to preserve food and as effective nanocarriers of hydrophobic bioactive compounds, including fucoxanthin, to improve their stability, bioavailability, and targeted delivery. Moreover, PDEVs can be used as new regulators of microbial fermentation. However, it should be noted that a lot of the evidence that is available is still preliminary and the effectiveness of these applications in real food-processing and storage conditions has not been fully proven. Although they have potential, there are a number of challenges that still hinder the widespread use of PDEVs in the food industry. These involve the creation of scalable and cost-effective production processes, batch-to-batch consistency, vesicle stability in a variety of food matrices, and regulatory and safety considerations. Other emerging engineering approaches, such as surface functionalization and cargo loading, are also discussed in this review and could further increase the specificity, functionality, and application versatility of PDEVs in food systems. Moving forward, the incorporation of PDEVs into the next generation functional foods, novel food preservation methods, and customized nutrition plans should be prioritized in future studies. Further developments in these fields can make PDEVs useful platforms at the interface of food microbiology, nanotechnology, and human health.

Probiotics↗

PubMed2026

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans↗

PubMed2026

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation↗

PubMed2026

Chemical and sensory profiling of fermented, washed, and artificially flavored coffee beans: Insights into flavour quality, authenticity, and food safety implications.

This study establishes an integrated framework combining chemical profiling, sensory analysis, and molecular mechanism evaluation to compare flavour quality and authenticity among fermented, washed, and artificially flavored coffees. GC × GC-TOF-MS and UHPLC-HRMS showed that fermented samples had markedly higher ester and aromatic alcohol levels (total esters 74.5 ± 7.8 mg kg-1; phenylethanol 27.5 ± 3.2 mg kg-1, p < 0.01), enhancing fruity-floral notes. Washed coffees contained the highest organic acid concentrations (45.2 ± 3.8 mg kg-1, p < 0.01), supporting brightness and umami. Artificially flavored coffees exhibited elevated exogenous aromatics (vanillin 21.5 ± 3.1 mg kg-1) but significantly fewer Maillard products (p < 0.05) and reduced flavour retention (55% after 14 days). Molecular docking revealed higher theoretical binding affinities for naturally generated compounds, suggesting a potential molecular basis for their greater sensory persistence. The framework supports constructing coffee quality fingerprints and verifying flavour authenticity.

Flavoring Agents↗

PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗

PubMed2026

Impact of Physical Environment of Pediatric Inpatient Wards on Children: A Systematic Literature Review.

ObjectiveThe study aimed to examine empirical studies published between 2003 and 2025 to identify elements of physical environments influencing health outcomes and experiences of children and families.BackgroundIn the past 40 years, research has shown that the physical environment influences the health and well-being of patients in the healthcare environment. However, similar research in the context of "pediatric inpatient wards" remains underexplored.MethodsPubMed, Embase, Scopus, and Web of Science were used to identify relevant articles. All extracted articles underwent a three-step screening process using PRISMA. A total of 30 eligible articles were used for the analysis. The protocol is registered at PROSPERO (CRD42023408997).ResultsKey findings reveal positive and negative impacts of identified elements. Positive-effect elements include play spaces, space for parents, natural light, connections with nature, and so on, which promote comfort, healing, and emotional resilience. Conversely, negative-effect elements, such as noise, artificial lighting, uncomfortable temperature, and so on, contribute to stress and disrupted sleep. Mixed effects were observed for elements like art and television, which underscore the complexity of designing environments that address the diverse needs of different age groups and genders.ConclusionsThe review findings highlight significant knowledge gaps. The study also tries to bridge existing gaps between research and practice by systematically identifying environmental elements, offering actionable insights to architects, designers, healthcare providers, and policymakers. Future research must adopt rigorous, culturally inclusive approaches to advance the field of pediatric healthcare design and ensure equitable care across diverse sociocultural contexts.

Humans↗

PubMed2026

Nature-based meaning-focused photography intervention enhances subjective well-being: A three-arm randomized controlled study.

Gaining meaning from nature contact can promote subjective well-being. However, few studies have validated the effectiveness of nature-based meaning interventions in enhancing subjective well-being. This study consisted of a 7-day online intervention to examine the effects of nature-based meaning-focused photography on well-being by comparing a photo-only group, a photo + writing group, and a waiting list control group and how meaning in life mediates the relationship between nature contact and well-being. A pre-registered three-arm randomized controlled trial (groups: photo + writing group vs. photo-only group vs. control group) * (time: pre-test vs. post-test vs. 1-month follow-up) was conducted with 219 college students. In the photo + writing group, participants captured nature scenes and wrote 100-word reflections. The photo-only group only took nature photos. The primary outcomes were meaning in life and well-being, and the secondary outcome was life satisfaction. A conservative Bayesian causal forest analysis based on machine learning was used to detect both treatment and heterogeneous intervention effects. Compared with the control group, the photo + writing group showed positive effects on meaning in life, subjective well-being, and life satisfaction, with average treatment effects of 0.36, 0.27, and 0.66 standard deviations (SD), respectively. The photo-only group also showed generally positive effects on these outcomes, with average treatment effects of 0.27, 0.24, and 0.54 SD, respectively. However, these effects were not sustained after 1 month. The intervention was especially beneficial for participants from lower subjective socioeconomic status, with limited prior nature exposure, or lower baseline psychological well-being. Importantly, enhanced meaning in life helped explain how the intervention improved well-being and life satisfaction. This study also demonstrated that combining nature-based photography and reflective writing can improve well-being.

Humans↗

PubMed2026

Neighborhood Deprivation and Screening Mammography Utilization: A Retrospective Cross-Sectional Study.

RATIONALE AND OBJECTIVES: Access to screening mammography reduces breast cancer mortality disparities. The Area Deprivation Index (ADI) is a validated measure of neighborhood socioeconomic disadvantage linked to adverse health outcomes. There is limited data evaluating mammography utilization among patients residing in areas of higher deprivation. This study evaluated the association between ADI and screening mammography utilization within an accountable care organization (ACO) affiliated with a multicenter academic medical center in the Upper Midwest. METHODS: This retrospective cross-sectional study included women aged 40-85 years attributed to the ACO in 2022, based on Wisconsin Collaborative for Healthcare Quality criteria. The primary outcome was receipt of screening mammography within two years. The primary exposure was ADI, analyzed by decile (ordinal) and as low (deciles 1-5) versus high (deciles 6-10) deprivation. The logistic regression models evaluated associations between ADI and screening, unadjusted and adjusted for age, race, ethnicity, and preferred language. RESULTS: Among 7463 participants with geographic data, 74.4% completed screening. Screening rates were 75.7% in low-deprivation areas versus 66.2% in high-deprivation areas. Increasing ADI decile was associated with reduced screening in unadjusted (OR 0.891, 95% CI 0.87-0.91, p<0.001) and adjusted analyses (OR 0.897, 95% CI 0.88-0.92, p<0.001). Black participants (OR 0.444, p<0.001) and individuals preferring non-English languages (OR 0.333, p<0.001) had lower screening odds after adjustment. CONCLUSION: Higher neighborhood deprivation is independently associated with lower screening mammography utilization. Targeted, equity-focused interventions addressing neighborhood, racial, and language-related barriers are needed to reduce screening disparities.

Area deprivation Index↗

PubMed2026

Peripheral inflammation and executive function among community samples across the lifespan: A systematic review and meta-analysis.

Higher levels of peripheral inflammatory markers are proposed to disrupt cognitive processes; however, the extent to which this relationship applies to executive functions, specifically, has yet to be systematically evaluated. The current meta-analysis synthesizes all available literature measuring the association between peripheral inflammation and executive functions among community individuals across the lifespan. This systematic review searched Web of Science, PubMed, and PsycINFO for published and unpublished studies, in the English language, that assessed the association between markers of peripheral inflammation and self-report and behavioral measures of executive function. In addition to methodological and demographic information, correlation/beta coefficients were extracted from included studies to quantify the association between inflammation and executive functions. This review included 58 studies, 41 of which were included in the random-effects meta-analysis (N = 255,539). Among community individuals, higher levels of CRP and IL-6 were associated with poorer executive functioning. These results did not differ when models accounted for potential confounding variables. Meta-regressions revealed that the relationship between inflammatory biomarkers and executive function did not differ as a function of age, adiposity, or percentage of the sample who identified as female. Results of the present review indicate that higher levels of specific inflammatory markers are associated with lower performance on executive function measures; however, we observed significant heterogeneity in the study design and measurement of both inflammation and executive functioning, suggesting important considerations for future research.

Humans↗