SEARCH · Search PubMed

Results for “Hermaphroditic Organisms”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

255 records · Page 3Linked to original sources

PubMed2026

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

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

Humans↗

PubMed2026

The effect of dexmedetomidine in mechanically ventilated patients with sepsis and septic shock: a meta-analysis of randomized controlled trials.

PURPOSE: Dexmedetomidine (DEX) is a central sympatholytic with sedative properties widely used in critically ill patients. However, its effects in patients with sepsis and septic shock remain controversial. This meta-analysis evaluated the efficacy and safety of DEX compared to other sedatives in mechanically ventilated patients with sepsis and septic shock. METHODS: A systematic search was conducted across PubMed, Embase, Scopus, and Cochrane Library from inception through May 1, 2025 for randomized controlled trials comparing DEX with other sedatives or placebo in mechanically ventilated patients with sepsis and septic shock. Primary outcomes included overall mortality and Sequential Organ Failure Assessment (SOFA) scores. Secondary outcomes encompassed duration of mechanical ventilation (MV), length of stay in Intensive Care Unit (ICU), incidence of hypotension and bradycardia. RESULTS: Fifteen studies involving 3,882 patients (1,945 in the DEX group, 1,937 in the control group) were included. DEX was demonstrated no significant differences compared to other sedatives or placebo in overall mortality (Risk Ratio [RR] 0.98, 95% Confidence Interval [CI] 0.90 to 1.07, p = 0.71, I2 = 0%), SOFA scores (Mean Difference [MD] - 0.14, 95% CI -0.81 to 0.52, p = 0.67, I2 = 0%), length of stay in ICU (MD -0.32, 95% CI -1.69 to 1.06, p = 0.65, I2 = 77%), or incidence of hypotension (RR 1.15, 95% CI 0.81 to 1.62, p = 0.44, I2 = 14%). However, DEX significantly reduced the duration of MV (MD -0.54, 95% CI -0.98 to -0.10, p = 0.02, I2 = 25%) but was associated with an increased incidence of bradycardia (RR 1.67, 95% CI 1.22 to 2.28, p = 0.001, I2 = 0%). CONCLUSIONS: In mechanically ventilated patients with sepsis and septic shock, DEX shortened duration of MV but was associated increased bradycardia risk. No mortality or organ dysfunction benefits were observed. These findings suggest DEX is a reasonable therapeutic option to facilitate earlier ventilator weaning in selected patients (particularly those without shock), but careful monitoring for cardiovascular adverse effects is warranted.

Humans↗

PubMed2026

The impact of sex, age, and genetic ancestry on DNA methylation across tissues.

Understanding the consequences of individual DNA methylation variation is crucial for advancing our knowledge of human biology and disease, yet the collective impact of individual traits on DNA methylation and their downstream effects on gene expression across human tissues remains poorly understood. Here, we quantify the contributions of sex, age, genetic ancestry, and BMI on autosomal DNA methylation variation across nine human tissues and 424 individuals from the Genotype-Tissue Expression project. We show that genetic ancestry and age have a greater impact on DNA methylation compared with sex, with aging effects being more widespread but less pronounced. On average, <10% of the gene expression variation in sex, age, and ancestry is mediated by DNA methylation differences, with ancestry showing the largest proportion of mediation. We further show that ancestry-associated DNA methylation differences accumulate at CpG sites with extreme methylation states and are largely under genetic control. The female autosomal genome exhibits consistent hypermethylation across tissues at Polycomb-repressed regions. Ultimately, we show that age-related Polycomb target hypermethylation is observed across multiple tissues but not in the gonads. Our multi-individual, multitissue approach defines the key drivers of human DNA methylation variation in healthy conditions, establishing a baseline for the interpretation of DNA methylation changes in disease contexts.

Humans↗

PubMed2026

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV > 100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation↗

PubMed2026

Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Unraveling the Clinical Spectrum of DNASE1L3 Deficiency: Insights from Case Series and Systematic Literature Review.

BACKGROUND: DNASE1L3 deficiency is a rare monogenic cause of lupus and lupus-like autoimmunity resulting from impaired extracellular DNA clearance and sustained immune activation. Although most reported patients present with early-onset systemic lupus erythematosus (SLE), emerging evidence suggests broader phenotypic variability, including vasculitic and overlap manifestations. Whether these presentations represent distinct clinical entities or a continuum of DNASE1L3-associated immune dysregulation remains unclear. We aimed to define the clinical spectrum of DNASE1L3 deficiency and examine the relationship between recurrent pathogenic variants and disease severity. METHODS: We conducted a combined pediatric case series and systematic literature review. Four children with genetically confirmed biallelic DNASE1L3 variants followed at a tertiary pediatric rheumatology centre were retrospectively analysed for clinical, immunological, genetic, treatment, and outcome data. In parallel, a systematic search of PubMed/MEDLINE, Scopus, and Web of Science identified previously reported patients with confirmed biallelic pathogenic or likely pathogenic DNASE1L3 variants and extractable patient-level clinical data. To facilitate cross-case comparison, we applied an exploratory three-tier descriptive framework reflecting increasing disease severity: vasculitic or organ-limited disease (G1), systemic lupus or overlap phenotypes without irreversible organ damage (G2), and severe systemic organ-damaging disease (G3). The assigned grades were descriptive rather than permanent categories, as some patients may meet the criteria for a higher grade if broader systemic manifestations or irreversible organ damage develop during follow-up. FINDINGS: Fifteen reports provided extractable patient-level data, corresponding to 45 unique previously reported patients after accounting for known or probable overlapping reports. Combined with four patients from our centre, the analysis included 49 genetically confirmed individuals. SLE-dominant disease was the most frequent phenotype (27 [60%] of 45), followed by hypocomplementaemic urticarial vasculitis/HUVS-dominant disease (10 [22.2%]) and overlap phenotypes (8 [17.8%]). Renal involvement was reported in 30 (66.7%) of 45 patients, and disease onset occurred by age 3 years in 20 (44.4%). Persistent hypocomplementemia affecting C3 and C4 was frequently reported across the spectrum. Recurrent DNASE1L3 variants were observed across multiple phenotypic and severity grades. Variants such as p.Asn191Ser and p.Thr97Ilefs*2 occurred in patients spanning organ-limited vasculitic disease, lupus overlap phenotypes, and severe multisystem lupus with major organ involvement. CONCLUSION: DNASE1L3 deficiency was associated with a broad clinical spectrum of immune-mediated disease rather than a single clinicopathological entity. The occurrence of identical pathogenic variants across distinct phenotypic and severity states argues against a simple genotype-phenotype model and suggests that additional modifiers influence disease expression.

Humans↗

PubMed2026

Structural and tissue-specific organisation of endocrine Fgf19 and Fgf21 signalling in rainbow trout.

Endocrine fibroblast growth factors (FGF19 subfamily) play a key role in regulating metabolic homeostasis in vertebrates. However, their functional diversification in salmonids remains poorly understood. In this study, we conducted an integrative characterisation of Fgf19 and Fgf21 signalling in rainbow trout (Oncorhynchus mykiss) by combining phylogenetic, structural and expression analyses. Phylogenetic analyses revealed the conservation of single fgf19 and fgf21 genes, despite the extensive expansion of receptors post-Ss4R (salmonid-specific fourth-round whole genome duplication). Structural modelling and molecular dynamics simulations demonstrated the stable interactions of both ligands to multiple Fgfr isoforms, with receptor-specific energetic profiles and conserved core interaction residues. Tissue expression profiling revealed clear differences from mammalian models, such as predominant hepatic fgf19 expression and the absence of hepatic fgf21 under basal conditions. In addition, there were complex and tissue-dependent distributions of fgfr and klotho transcripts. These findings support a receptor-driven diversification model of endocrine Fgf signalling in salmonids, suggesting enhanced endocrine plasticity associated with the retention of receptors following post-genomic duplication. Taken together, our findings provide new insights into the structural and regulatory organisation of endocrine Fgf signalling, as well as its potential role in metabolic regulation in rainbow trout.

Animals↗

PubMed2026

Mechanistic insights into flavor deterioration in bitter sturgeon caviar: Evidence from lipidomics and metagenomics.

This study systematically compared the flavor and multi-omics differences between normal caviar and bitter caviar based on quantitative descriptive analysis (QDA), volatile compounds (VOCs) analysis, untargeted lipidomics, and metagenomics. The results showed that bitter caviar was characterized not only by increased bitterness, but also by decreased positive sensory attributes, including buttery, nutty, and marine fresh. VOCs analysis indicated that the volatile profile of bitter caviar was reorganized. Compounds such as 3-hydroxy-2-butanone, 1-octen-3-ol, and (E, Z)-2,6-nonadienal showed higher relative odor activity values (rOAVs); however, these changes did not improve its overall sensory experience. Untargeted lipidomics identified 492 differential lipids. These changes were mainly characterized by decreased PC and increased DG and LPC in bitter caviar. KEGG pathways analysis showed that these differential lipids were mainly associated with glycerophospholipid metabolism, choline metabolism in cancer, and retrograde endocannabinoid signaling. Metagenomic analysis showed that bacteria dominated the microbial community of caviar. Among them, Bacillus and Micromonospora showed relatively high abundance in the caviar microbiota. They were also closely associated with lipid metabolic changes involving PC, DG, and LPC, suggesting their potential as candidate targets for future microbiota-directed regulation of caviar quality. These findings provide new insights into the mechanisms underlying sensory deterioration and flavor formation in bitter caviar, and offer a theoretical basis for improving caviar quality in industrial production.

Animals↗

PubMed2026

Paediatric penile length: a systematic review and meta-analysis.

OBJECTIVE: To assess geographical variation in stretched penile length among prepubertal boys and evaluate temporal trends over the past two decades, as defining reference values for genital organ size remains crucial for early identification of development disorders. METHODS: The PubMed, Cochrane and Scopus databases (no deadlines for publishing were imposed) were searched according to the Preferred Reporting Items for Systematic Review and Meta-analyses statement. Five authors independently extracted individual participant data and assessed the risk of bias. Studies with quantitative penile lengths were included; those involving congenital malformations were excluded. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (registration number CRD42022335643). RESULTS: A total of 55 studies from 2000 to 2024 were evaluated, including data from 31 915 boys. Pooled mean stretched penile length estimates were 3.07 cm (95% confidence interval [CI] 2.88-3.26 cm) for the 1-week-old boys, 3.73 cm (95% CI 3.53-3.93 cm) for the 1-year-old boys, 4.69 cm (95% CI 4.49-4.88 cm) for the 2-5 year-old boys, and 5.43 cm (95% CI 5.20-5.66 cm) for the 5-10 year- old boys. When comparing data from the 2000s to the 2020s, stretched penile length decreased by 16.2% (from 3.46 to 2.90 cm), 16.3% (from 4.17 to 3.49 cm), 21.5% (from 5.31 to 4.17) and 26.2% (from 6.46 to 4.77 cm) in the 1-week-old, 1-year-old, 2-5-year-old and 5-10-year-old boys, respectively. Subgroup analysis for those aged >2 years showed significant variations by geographical region (P < 0.001). CONCLUSIONS: The present study observed large variations in penile length across geographical regions and among prepubescent boys of different ages, while also suggesting a possible decline over the past two decades.

Humans↗

PubMed2026

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

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

Animals↗

PubMed2026

Failure modes and effects analysis for clinical implementation of online adaptive radiotherapy: A systematic review.

BACKGROUND: The accuracy of radiotherapy is limited by anatomical variations occurring over time scales ranging from sub-seconds to days. Online Adaptive Radiotherapy (OART) addresses this by enabling daily plan adaptation based on real-time imaging. While OART offers improved dose conformity, its dynamic, time-constrained workflow introduces novel failure modes that challenge traditional quality assurance protocols. PURPOSE: This study aims to synthesize the existing literature on Failure Modes and Effects Analysis (FMEA) for OART to systematically catalog risks and identify mitigation strategies. METHODS: A systematic literature search was conducted to identify studies applying FMEA to OART workflows. Eleven studies were included, covering MR-guided (ViewRay MRIdian, Elekta Unity), CBCT-guided (Varian Ethos), and MR-enhanced C-arm linac systems. To address heterogeneity in risk scoring methodologies (e.g., TG-100 10-point scales vs. 5-point rankings), extracted failure modes were harmonized into a standardized three-tier risk classification system (Class I: Low, Class II: Intermediate, Class III: High). RESULTS: A total of 300 unique failure modes were identified, with 49.6 percent classified as high-risk (Class III). Analysis revealed that the majority of high-risk failures were concentrated in the online treatment delivery phase, specifically within human-computer interactions and anatomical contouring steps. CONCLUSIONS: This study supports the development of tailored, robust QA frameworks that prioritize human factors and process consistency to guide safe implementation in diverse clinical settings.

Humans↗

PubMed2026

Evidence of genome-wide relaxed selection on mildly deleterious mutations in an ancient subterranean catfish.

About one hundred subterranean catfish species have been described, resulting from repeated colonization of cave environments by multiple surface lineages. Most cave-dwelling species are found in the Americas, in particular in South America, but a few species also live in Central and North America. Despite the availability of high-quality genome assemblies for two cave species, the Mexican blind catfish Prietella phreatophila and the Colombian blind catfish Trichomycterus rosablanca, genomic approaches to investigate genetic changes associated with subterranean life or to estimate cave colonization times remain largely unexplored. To fill this gap, we additionally sequenced the genomes of four blind and depigmented subterranean catfishes from Peru (three Trichomycterus and one Astroblepus), as well as the genomes of four close surface relatives. We first extracted a large set of light-related genes, such as phototransduction and crystallin genes, and found contrasting decays of these sequences in different cave species, from 1% of pseudogenes in T. rosablanca to 48% in P. phreatophila. Two independent molecular dating methods gave congruent ages, indicating that these catfishes colonized subterranean habitats at different times, ranging from Early Pliocene to Late Pleistocene, supporting the hypothesis that surface catfishes repeatedly and rapidly adapted to subterranean habitats. The oldest cave species, P. phreatophila, appears to have been thriving in the dark for over 3.5 million years. Moreover, a genome-wide analysis of protein-coding genes suggests weaker purifying selection on mildly deleterious mutations in this cavefish than in other catfish lineages, likely reflecting a long-term small effective population size.

cavefishes↗

PubMed2026

Factors influencing the enhancement of the new iron triangle in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise´s Multiplication Appliqué´ a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans↗

PubMed2026

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2026

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation↗