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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

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide↗

PubMed2026

Access Block and Ambulance Ramping: The Canaries of the Healthcare System.

OBJECTIVE: To identify evidence-based factors leading to the global challenge of hospital access block and inform strategies to improve emergency access performance. METHODS: A mixed methods approach was followed comprising an umbrella review of published systematic reviews, qualitative analysis of the perspectives of patients and healthcare workers, and quantitative analysis of contextual factors and 6 years of ambulance, emergency inpatient and ward movement records for the 25 largest public hospitals in Queensland, Australia. RESULTS: A key set of findings and recommendations were identified to improve emergency access that are practical and actionable. These comprise the introduction of inpatient discharge metrics and monitoring to shift focus from the front door of hospitals to the 'back door'; increasing support for primary care, community care, aged care, NDIS and vulnerable groups; maintaining demand-side strategies such as increasing inpatient-equivalent care alternatives (e.g., hospital in the home, acute care within nursing home services); investment in prehospital flow; improving hospital processes such as extended-hour discharge lounges; improving workforce; and revising funding policies. CONCLUSIONS: The study findings fill a gap in the evidence regarding challenges and recommendations for improving patient flow within hospital emergency departments and across the broader health system. Focussing efforts at the 'back end' of the inpatient journey is a critical step to improve emergency care outcomes.

Humans↗

PubMed2025

Systematic meta-analysis of the toxicities and side effects of the targeted drug lenvatinib.

BACKGROUND: Lenvatinib, an effective targeted drug for various cancers, has clinical medication safety concerns due to its toxicities and side effects. OBJECTIVE: This study evaluated lenvatinib-induced any adverse events (any AEs) and nine aspects: vascular toxicities related to the circulatory system (vascular toxicities, blood system, and heart), toxicities of the skin and its appendages (skin/subcutaneous tissue and taste system), toxicities of the respiratory system (respiratory, thoracic, and mediastinal and respiratory tract), toxicities of the nervous system (nervous system and general), toxicities of the digestive system (gastrointestinal and liver), toxicities of the urinary system, toxicities of the endocrine and metabolic system (endocrine and metabolism/nutrition), toxicities of the musculoskeletal system, and other severe toxicities. Toxicities and side effects were stratified by severity into any and ≥3 grades for analysis. PATIENTS/MATERIALS AND METHODS: Multiple databases were searched for lenvatinib cancer clinical studies (cohort studies and randomized controlled trials) from inception to December 31, 2024; toxicity and side effect data were extracted and analyzed. RESULTS: Nine high-quality studies were included, showing that lenvatinib is effective in cancers but has notable toxicities. Taking hypertension as an example, for any grade, the risk ratio (RR) was 2.34 with a 95% confidence interval (CI) of [2.09, 2.62], a Z-value of 14.74, and a P-value <0.00001; for grade ≥3, the RR was 2.60 with a 95% CI of [2.21, 3.06], a Z-value of 11.44, and a P-value <0.00001. CONCLUSION: Lenvatinib is effective for cancer but toxic, and this study supports its rational clinical use.

Humans↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗

PubMed2026

A comparative systematic review of pharmacist education systems and pharmacy service quality in ASEAN-5: Indonesia, Malaysia, Thailand, the Philippines, and Singapore.

BACKGROUND: The global transition toward patient-centered pharmaceutical care has exposed structural disparities in ASEAN pharmacy workforce training and deployment. This review examines four research questions: how pharmacy education systems and accreditation standards differ across Indonesia, Malaysia, Thailand, the Philippines, and Singapore (collectively, the ASEAN-5); the extent to which pre-registration education influences clinical service scope and professional confidence; how education reform and regulatory change have shaped pharmacist clinical roles; and what barriers and enablers exist for regional qualification harmonization. METHODS: A systematic literature review following PRISMA 2020 was conducted. Searches of PubMed/MEDLINE and Scopus, supplemented by grey literature, were completed in May 2026. Of 78 unique records screened, 46 studies published between 2005 and 2026 met inclusion criteria. Quality appraisal used an adapted Mixed Methods Appraisal Tool; synthesis employed narrative thematic analysis. RESULTS: The five countries represent four structurally distinct pharmacy education architectures: Thailand's standardized six-year Doctor of Pharmacy with dual specialization tracks; four-year Bachelor of Pharmacy programmes in Malaysia and the Philippines with institutional variation; Indonesia's clinically underdeveloped system despite rapid expansion; and Singapore's four-year Bachelor of Pharmacy followed by a nationally mandated one-year pre-registration pathway. Evidence links deeper clinical training to broader practice scope, higher confidence, and improved patient outcomes. Reform produced uneven results: Thailand's PharmD transition improved clinical recognition but exposed deployment paradoxes; Singapore achieved the strongest training-to-practice alignment; Indonesia's health insurance reforms were not absorbed by an underprepared workforce; the Philippines lacks a national competency framework. No binding mutual recognition arrangement was identified; divergent qualification structures, incompatible accreditation systems, and an asymmetric evidence base remain the primary barriers. DISCUSSION: These findings indicate that clinical service scope is bounded less by national policy ambition than by the depth and clinical orientation of the pre-registration education that precedes it, and that credentialing reforms which outpace a health system's capacity to absorb new clinical roles, or the reverse, do not by themselves translate into expanded practice. CONCLUSIONS: Pharmacy education across the ASEAN-5 remains nationally distinct and clinically uneven. Clinical service scope is directly bounded by pre-registration education quality. No country has fully closed the education-practice gap. Regional harmonization requires national-level educational reform as a prerequisite.

Humans↗

PubMed2026

GPR3 in neuro-metabolic-immune-reproductive nexus - a potential therapeutic target for Multi-System diseases.

BACKGROUND: GPR3(G-protein-coupled receptor 3), an orphan G-protein-coupled receptor (GPCR) with constitutive Gs activity, is expressed in the brain, liver, ovary, and other tissues, regulating cell proliferation, differentiation, and apoptosis across the nervous, reproductive, immune, and metabolic systems. This review synthesizes evidence on its integrated signaling and physiological functions to address the lack of a comprehensive multisystem pathophysiology overview. METHODS: A systematic literature search was conducted on PubMed and Web of Science, using keywords such as "GPR3", "GPCR", "neurodegeneration", "metabolism", "immune", "reproduction", "agonist", "inhibitor", and "therapeutic target". This search identified GPR3's roles in neurodegenerative diseases, immune inflammation, reproduction, and energy metabolism. The analysis focused on signaling pathways, ligand regulation, and therapeutic potential. RESULTS: The research indicates that GPR3 is involved in neuronal survival, synaptic plasticity, and microglial activity via the cAMP/PKA, PI3K/Akt, and β - arrestin pathways. It promotes amyloid - β formation in Alzheimer's disease (AD), yet provides neuroprotection in Parkinson's disease (PD) models. It may contribute to anxiety/depression - like states, maintain oocyte meiotic arrest in the ovary, and activate thermogenic genes in adipose tissue. GPR3 modulates immune responses. Using oleic acid (OA) and diphenyleneiodonium (DPI) as activators, and AF64394 and cannabidiol (CBD) as antagonists, it shows potential in disease models. CONCLUSION: GPR3 acts as a central molecular hub integrating neural, metabolic, immune, and reproductive signaling, highlighting its potential as a therapeutic target for chronic multisystem disorders. However, its dual roles in certain pathologies and translation challenges necessitate further research.

Humans↗

PubMed2026

Unconfined compressive strength prediction for the ordinary Portland cement-steel slag-silica fume ternary system based on response surface methodology.

This research was undertaken to address environmental concerns associated with industrial solid waste and to reduce cement consumption in geotechnical engineering. It specifically investigates the feasibility of using steel slag (SS) and silica fume (SF) as partial substitutes for ordinary Portland cement (OPC) in soil stabilization. The effects of SS, SF, OPC, and initial moisture content on the unconfined compressive strength (UCS) of stabilized soil were investigated through single-factor experiments and response surface methodology (RSM). The results show that SS and SF can synergistically enhance the strength of stabilized soil, although their interaction effect was not statistically significant within the investigated ranges. Compared with soil stabilized solely with OPC, the addition of 18 % SS and 10 % SF reduced OPC consumption by 3 % without compromising strength. Microstructural and compositional analyses further revealed that SS mainly supplied calcium- and silica-bearing components, while SF provided highly reactive silica and micro-filling effects, jointly promoting hydration reactions and improving the compactness of the stabilized soil matrix. As a result, more hydration products were formed in the OPC/SS/SF-stabilized soil than in the OPC-stabilized soil, which contributed to pore filling and strength enhancement. This study provides useful guidance for the sustainable utilization of industrial solid waste and the low-carbon development of soil stabilization materials.

Construction Materials↗

PubMed2026

Glymphatic dysfunction mediates inflammation-driven vascular burden and cognitive decline in cerebral small vessel disease.

BACKGROUND: Cerebral small vessel disease (CSVD) is increasingly recognized as a disorder involving microvascular dysfunction, impaired perivascular clearance, and inflammatory processes. However, how systemic inflammatory burden, neurovascular coupling (NVC), glymphatic MRI markers, vascular lesion burden, and cognition are interrelated remains unclear. MATERIALS AND METHODS: In this prospective study, 155 patients with CSVD and 70 healthy controls (HCs) underwent multimodal MRI. NVC was quantified using the cerebral blood flow/fractional amplitude of low-frequency fluctuations ratio. Glymphatic function was assessed via the diffusion tensor image analysis along the perivascular space (ALPS) index, choroid plexus volume (CPV), and perivascular space (PVS) fractions. Structural equation modeling (SEM) was employed to evaluate the direct and indirect effects of inflammatory markers on vascular burden and cognitive performance. RESULTS: Patients with CSVD exhibited significantly diminished NVC (specifically in the right median cingulate and left frontal gyri) and impaired glymphatic function (lower ALPS-index; higher CPV and PVS fractions) compared to HCs. SEM revealed that inflammatory biomarkers exerted both a direct effect on vascular burden and a substantial indirect effect (accounting for 66.3% of the total effect) mediated through two pathways: a single-mediation path via glymphatic function (42.8%) and a serial-mediation path via NVC and glymphatic function (23.5%). Increased vascular burden was significantly associated with poorer cognitive performance. CONCLUSION: Inflammation drives CSVD progression and cognitive decline primarily through the disruption of NVC and glymphatic clearance mechanisms. These findings highlight glymphatic dysfunction as a critical mediator of inflammation-related structural brain damage.

Humans↗

PubMed2026

A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.

INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.

Humans↗

PubMed2026

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals↗

PubMed2026

Comparison of the predictive performance of systemic immune-inflammation index and neutrophil-to-lymphocyte ratio for three-month poor functional outcome in ischemic stroke: a systematic review and meta-analysis.

INTRODUCTION: Ischemic stroke (IS) is a leading cause of global mortality and disability. Early and accurate prognosis is crucial for patient management. The neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) are emerging inflammatory biomarkers; however, their relative predictive value for three-month poor functional outcome (modified Rankin Scale [mRS] > 2) remains uncertain. METHODS: We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library up to 20 July 2025, adhering to PRISMA guidelines. Observational studies reporting the association of SII or NLR with three-month poor outcome were included. Study quality was evaluated using the Newcastle-Ottawa Scale. Area under the curve (AUC), odds ratios (OR), and standardized mean differences (SMD) were pooled using random-effects models in Stata 16.0. RESULTS: Twenty-one studies involving 7520 IS patients were analysed. NLR demonstrated marginally superior discriminative ability compared to SII (AUC 0.71, 95% CI: 0.67-0.76 vs. 0.68, 95% CI: 0.64-0.71), though this difference was not statistically significant. Elevated NLR was significantly associated with poor outcome (OR = 1.26, 95% CI: 1.17-1.37, p < .001), whereas SII was not (OR = 1.00, 95% CI: 1.00-1.00, p = .384). Both markers showed moderate effect sizes (SMD: NLR = 0.69, SII = 0.72; p < .001). NLR performed better in non-intervention and Chinese subgroups, while SII exhibited consistent AUC values across treatment and ethnic subgroups. CONCLUSION: NLR and SII are accessible prognostic markers in IS. NLR demonstrates superior accuracy and a significant association with poor outcome, while SII shows greater stability across patient subgroups. Both may assist in risk stratification, in resource-limited settings.

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

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗