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PubMed2026

Messaging Strategies for Tobacco Prevention and Cessation Among People with Depression: A Scoping Review.

INTRODUCTION: Depression is strongly associated with higher tobacco use and lower quit rate; few communication campaigns have been designed with these mental health factors in mind. This scoping review compiles existing research on tobacco prevention and cessation messaging involving people with depression to identify gaps and opportunities for future message development. METHODS: Sources included PubMed, PsycINFO, Scopus, Academic Search Premier, and ProQuest Central (November - December 2024). The 55 studies included examined tobacco prevention or cessation messages and measured depression, depressive symptoms, or mental health as a primary outcome or analytic covariate. Study characteristics, target population, delivery format, message content, theoretical frameworks, outcomes, and gaps were extracted. RESULTS: RCTs made up half (51%) of the included studies, and most (78%) were conducted in the U.S. Nearly half (46%) required participants to have a mental health condition. Interventions most often used interactive (65.5%) or text-based (47.3%) communication and focused on tobacco cessation (89%) rather than vaping (9%). Common outcomes included feasibility or acceptability (37.7%) and point prevalence abstinence (37.7%). Mental health-specific messages showed mixed effectiveness. CONCLUSIONS: Despite progress in integrating mental health into tobacco messaging, targeted interventions for people with depression remain limited. Few studies tested long-term outcomes or used biochemical verification; many relied on untargeted generalized messaging.

Journal Article↗
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

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9↗
PubMed2026

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans↗
PubMed2026

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article↗
PubMed2026

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article↗
PubMed2026

Watershed-scale risk assessment of cadmium contamination in Chinese cropland soils: Dual pathways of irrigation input and flood-driven transport.

Irrigation and flood events serve as critical pathways for the transport of cadmium (Cd) from industrial sources into cropland soils at the watershed scale, constituting a major driver of widespread Cd contamination in China's cropland soil. This study evaluated the risk of Cd contamination in cropland soils across China's nine major river basins at the watershed scale, focusing on the contributions of irrigation and flood events, and conducted a sensitivity analysis of key risk factors. The assessment was conducted within a framework that considered factors including hazard, exposure, and vulnerability. The results revealed that numerous watersheds in southeastern China are exposed to dual pressures of Cd contamination risks in cropland soils, driven by both irrigation practices and flood events. Watersheds categorized as High-High, High-Moderate, or Moderate-High risk, reflecting combined Cd contamination risks from irrigation and flood, are vital to China's grain production, contributing 67.1 % of the national cropland area and 66.4 % of the grain yield. The study suggests localized strategies for managing cropland soils Cd contamination risks from irrigation and flood at the watershed scale in China, alongside strengthened cross-regional collaboration in southeastern China.

Cadmium↗
PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗
PubMed2026

Dispositional optimism and open-label placebo responses in hair cortisol concentrations and psychological distress-A randomized controlled trial.

Open-label placebo (OLP) treatments show beneficial effects on various health-related outcomes, but studies investigating OLP effects on physiological measures remain scarce. This randomized controlled trial examined the effect of a 4-week OLP intervention on psychological distress and hair cortisol concentrations (HCC) in 202 healthy university students preparing for mandatory oral exams and whether dispositional optimism moderates the OLP effects. Participants were randomly assigned to an OLP or control group. Psychological distress was repeatedly assessed via negative affect, test anxiety, and subjective stress. HCC was measured before and within the intervention. Treatment expectations were additionally examined in interaction with optimism. Results show that OLPs significantly reduced psychological distress and HCC compared to the controls. Optimism moderated the OLP effect on HCC, with less optimistic individuals demonstrating the strongest reduction, independent of expectation. Optimism did not moderate OLP effects in psychological distress. However, the OLP effect on psychological distress depended on the three-way interaction of group, optimism, and expectation. The results suggest that OLPs alleviate the psychophysiological impact of a real-life stressor and indicate that optimism and expectation differently shape psychological and physiological OLP responses. These findings are discussed within the framework of the interactionist perspective.

Humans↗
PubMed2026

Instruments for measuring body image in breast cancer patients: a systematic review of measurement properties.

PURPOSE: To evaluate the psychometric properties of PROMs for measuring body image in breast cancer patients. METHODS: In December 2024, a psychometric systematic review was performed in the nine databases. The COSMIN checklist was employed to evaluate the methodological quality and psychometric properties of the included body image measures. The level of evidence was assessed using the GRADE framework, and final recommendations were formulated for the scale. RESULTS: Thirty-eight articles evaluating fifteen PROMs were included in this review. Structural validity, internal consistency, and hypothesis testing had been most frequently evaluated. Measurement error had not been assessed for all PROMs. Twelve instruments show potential application value but require further research. The BAS-BC, PSPP, and ASI-R are not recommended for use, as these instruments do not meet the strict COSMIN thresholds for full recommendation. CONCLUSION: The BIS can be recommended as a temporary screening tool for assessing body image outcome in clinical practice. The BIRS can be tentatively advised for measuring specific postoperative body image changes. However, further comprehensive studies are required to validate the psychometric properties of existing PROMs.

Female↗
PubMed2026

Efferocytosis regulatory factors in atherosclerosis: A preclinical systematic review.

BACKGROUND: Impaired efferocytosis is a key driver of plaque instability during atherosclerosis progression. Efficient clearance of apoptotic cells through efferocytosis relies on the coordinated action of multiple regulatory factors. METHODS: PubMed, Web of Science, ScienceDirect, OVID MEDLINE, and Scopus were searched for studies published up to February 7, 2026. Eligible preclinical studies were systematically reviewed to identify endogenous factors that regulate efferocytosis in atherosclerosis. Clinical evidence was also incorporated to enable a preliminary translational assessment of these regulatory factors. RESULTS: Thirty-five endogenous regulatory factors were identified from 36 included studies, and their functional roles across distinct stages of efferocytosis were characterized. Notably, metabolic regulators such as PKM2, PFKFB3, GLS1, and Drp1 were involved in distinct efferocytosis stages. This suggests that metabolic reprogramming may provide the metabolic support require for efficient efferocytosis and inflammation resolution. Ten factors were supported by preliminary clinical evidence consistent with preclinical data. PKM2 was the only candidate biomarker with prospective observational data. However, its independent predictive value still requires validation in multicenter prospective studies. CONCLUSIONS: This review provides a systematic synthesis of 35 endogenous efferocytosis regulators and elucidates their regulatory network in atherosclerosis based on a functional stage framework. Metabolic reprogramming is identified as a central hub linking efferocytosis efficiency to inflammation resolution. This review offers a new theoretical basis for efferocytosis-targeted intervention strategies.

Animals↗
PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗
PubMed2026

Psychological consequences of AI-assisted training and the buffering role of mindfulness.

The integration of artificial intelligence (AI) into athletic training is accelerating, yet its psychological implications for athletes remain insufficiently understood. Drawing on the transactional model of stress and the stress-buffering framework of mindfulness, this study examined whether mindfulness training can mitigate adverse psychological responses associated with AI-assisted training. Using a randomized controlled factorial design, 160 collegiate athletes were assigned to AI-assisted training or standard training, with or without concurrent mindfulness intervention, and assessed at baseline, week 4, and week 8. Athletes exposed to AI-assisted training without psychological support exhibited increases in perceived stress and AI dependence over time. In contrast, these stress increases were substantially attenuated when mindfulness training was implemented alongside AI-assisted training. A significant AI × Mindfulness × Time interaction emerged for perceived stress at post-intervention, and difference-in-differences analyses corroborated a robust buffering effect. Mediation analyses further indicated that mindfulness training reduced stress partially through enhancing mindful awareness; a three-wave cross-lagged analysis showed that mindful awareness and stress were reciprocally related over time, with the hypothesized awareness-to-stress pathway remaining robust. Together, these findings suggest that AI-assisted training introduces a distinct form of evaluative pressure, and that mindfulness training may serve as an effective psychological buffer during the adoption of continuous algorithmic performance evaluation systems.

Humans↗
PubMed2026

Vitamin B12 Deficiency in Sickle Cell Disease: Method-Driven Estimates and Systematic Diagnostic Misclassification.

OBJECTIVES: To determine whether the reported 0%-70% prevalence of vitamin B12 deficiency in sickle cell disease (SCD) reflects true population variation or diagnostic misclassification. METHODS: We conducted a PRISMA 2020-compliant systematic review of observational studies (January 1, 2000-May 13, 2026; PROSPERO CRD420251087800) assessing B12 status in SCD. PubMed, AJOL, and Google Scholar were searched with citation tracking and dual screening. Diagnostic validity was assessed across biomarker strategy, analytical platform, thresholds, and confounder control using a proposed context-integrated framework to classify methodological robustness and discordance. RESULTS: Fourteen studies were included (57% high-income; 43% LMIC). The evidence base was dominated by limited diagnostic approaches: 71% used immunoassays, over one-third relied on circulating B12 alone, and functional biomarkers were inconsistently applied without systematic confounder adjustment. Prevalence estimates were strongly influenced by diagnostic methods rather than underlying population biology, ranging from 0% to 70% in single-marker studies (mostly 0%-7.1%, with outliers ~50%-70%) and 6.9%-53% in multi-marker studies. Discordance was substantial and greater in LMIC settings than HIC. CONCLUSION: Current diagnostic approaches in SCD appear method-dependent, generating heterogeneous prevalence estimates with uncertain clinical validity. These findings challenge existing estimates and have implications for clinical practice, research design, and diagnostic equity. TRIAL REGISTRATION: ClinicalTrials.gov identifier: CRD420251087800.

Humans↗
PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗
PubMed2026

Hydroxyl Radical Inactivation of Vesicle-Cloaked and Free Murine Norovirus: Linking Biomolecular Oxidation to Lifecycle Disruption and Infectivity Loss.

Hydroxyl radicals (•OH) play a central role in inactivating human viruses during advanced oxidation processes for water and wastewater treatment, solar disinfection, and natural attenuation in sunlit aquatic environments. Human norovirus, a leading cause of gastroenteritis, is efficiently transmitted through water and exhibits strong environmental persistence. The recent discovery of vesicle-cloaked virus clusters (viral vesicles) further challenges water treatment and reuse, particularly for norovirus elimination. We investigated •OH inactivation kinetics and mechanisms of murine norovirus 1 (MNV-1), a human norovirus surrogate, in free-virus and vesicle-cloaked forms. •OH rapidly inactivated both MNV-1 vesicles and free MNV-1 with second rate constants of ∼1010 M-1 s-1; however, the vesicle membrane provided a 2.24-fold protective effect to cloaked MNV-1, resulting in slower inactivation kinetics than those of free MNV-1. •OH oxidized viral capsid proteins and genomes together with vesicle proteins and lipids, resulting in impaired CD300lf receptor and cell-based binding, disrupted genome replication, and diminished viral assembly. Despite these biochemical and functional impairments, most vesicle structures remained largely intact following •OH exposure. This study establishes a quantitative framework linking biomolecular damage to viral infectivity loss through functional impairment and lifecycle disruption, providing mechanistic insights into advance water disinfection strategies and public health protection.

Norovirus↗
PubMed2026

Three-dimensional porous nano-hydroxyapatite@gelatin composite as efficient adsorbent for uranyl ion removal from low-level radioactive wastewater.

The contamination of water resources by uranyl (UO22+) ions poses significant environmental and health risks, requiring the development of efficient and sustainable remediation strategies. Adsorption-based techniques have emerged as promising approaches in the field of UO22+ removal, but the design of cost-effective, high-capacity, and environmentally friendly adsorbents remains challenging. In this study, a three-dimensional porous nano-hydroxyapatite@gelatin (nHAP@Ge) composite was synthesized through glutaraldehyde cross-linking, combining the structural stability of Ge with the high uranium affinity of nHAP. The optimized nHAP@Ge, with a nHAP:Ge mass ratio of 1:0.5, exhibited exceptional UO22+ removal efficiency (97 %), along with high adsorption capacity (364.03 mg/g). Systematic characterizations using scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transform infrared (FT-IR) spectroscopy, and X-ray photoelectron spectroscopy (XPS) methods revealed that the porous structure and surface functional groups (-OH, Ca2+, and PO43-) of the material synergistically contributed to binding UO22+ species. Furthermore, the incorporation of nHAP into the Ge framework resulted in enhanced thermal stability while significantly improving the UO22+ adsorption performance. This work presents a scalable, eco-friendly, and recyclable strategy for the effective treatment of uranium-contaminated water, with potential applications in nuclear wastewater treatment and environmental remediation.

Adsorption↗
PubMed2026

How is goal setting used in interventions for chronic disease prevention and management in sub-Saharan Africa? A systematic review and narrative synthesis.

Non-communicable diseases are increasingly prevalent in sub-Saharan Africa, and goal setting is often used to promote healthy self-management behaviours. In this review, we aimed to synthesise literature around how goal setting is used, for application in future interventions in the region. A systematic search was conducted in six databases and results screened for eligibility. Study characteristics, intervention details, goal setting components, feedback from participants and facilitators were extracted. Data were analysed using narrative synthesis and thematic analysis. The Mixed Methods Appraisal Tool was used to assess study quality. We included 24 publications describing 18 unique interventions. Included studies were of high to moderate methodological quality. Goal setting intervention components were informed by a variety of frameworks and involved a range of tasks. Interventions were often facilitator-led; many were conducted in group settings. Participants reported goal setting as useful for putting self-management into practice but encountered challenges related to language and literacy levels. Adequate detail on goal setting intervention components was not always present. Through this review, we provide a comprehensive picture of the variability of goal setting approaches in chronic disease prevention and management in sub-Saharan Africa and recommend more standardised use and reporting of goal setting intervention components.

Humans↗