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A full review of online education resources available on antifungal stewardship.

BACKGROUND AND OBJECTIVES: Antifungal resistance represents an increasing global threat, driven by the rising burden of fungal disease. Antifungal stewardship (AFS) is a critical component of broader antimicrobial resistance (AMR) efforts, but education in this area remains less established than antibacterial stewardship initiatives. The scope and characteristics of the current landscape of online AFS resources have not yet been systematically described. To identify and evaluate online educational resources focused on fungal disease management and AFS, and assess their accessibility, format, educational design and implementation focus. METHODS: A structured search of internet search engines, distribution platforms and organizational websites was conducted to identify English-language web-based resources related to fungal disease management and stewardship. Resources were evaluated using predefined criteria including access model, format, length, educational design, interactivity and AFS content. An overall educational value score (1-10) was assigned. RESULTS: Twenty-three educational resources were identified. Most were delivered as online unfacilitated courses (11, 48%) and were short (<4&#x2005;h) (12, 52%). Most focused on guidelines and syndromic management (18, 78%) and targeted doctors and/or nurses/midwives (22, 96%). Limited interactivity was reported in nine (39%) courses. Five courses (22%) had either a substantial or comprehensive focus on AFS. CONCLUSIONS: Online AFS educational resources are available and support awareness and knowledge development. However, they remain relatively few in number. Greater emphasis on implementation-focused learning, behaviour change components and broader global representation may enhance their impact.

Journal Article

Comparative analysis of histological and transcriptomic characteristics in caudal muscles of nile crocodiles (Crocodylus niloticus), siamese crocodiles (Crocodylus siamensis), and their hybrids.

Crocodylus niloticus and Crocodylus siamensis are high-value aquaculture species. C. niloticus is large-bodied but less abundant, while C. siamensis grows fast but is small-sized. Their hybrids combine parental advantages, yet relevant research is scarce. This study compared the histological and transcriptomic characteristics of the caudal muscle across the three taxa. HE staining indicated that C. niloticus had significantly larger myofiber diameters (p&#xa0;<&#xa0;0.05); C. siamensis had the smallest, and the myofiber density of hybrids was much closer to that of C. siamensis. Masson's trichrome staining indicated that C. niloticus had the thickest collagen fibers (p&#xa0;<&#xa0;0.05), C. siamensis the thinnest, and hybrids exhibited highly similar histological traits to C. siamensis. C. niloticus had higher LDH and SDH activities in caudal muscles, whereas the hybrid crocodile indicated the highest CK activity. Transcriptomic analysis identified numerous differentially expressed genes (DEGs), which were enriched in growth, muscle metabolism, and energy allocation pathways via GO/KEGG annotations. PPI analysis screened 24 hub genes related to energy metabolism. This study systematically reveals caudal muscle differences, providing insights into growth-related molecular mechanisms and theoretical support for crocodile artificial breeding.

Animals

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans

Chemical Complementarities of Neuroblastoma Tumor-Resident TCR CDR3s and CMV Antigens are Associated with a Better Outcome.

A likely immune response to a virus can be detected via the presence of TCR CDR3s that (a) exactly match CDR3s known to bind viral antigens or (b) represent chemical complementarity to viral antigens. Previous studies, based on genomics approaches to characterizing anti-CMV TCR CDR3s in patient blood samples, have indicated the possibility that a systemic CMV infection is associated with worse outcomes for NBL, as well as for breast cancer. Thus, the association of NBL tumor-resident anti-CMV TCR CDR3s and patient outcomes was evaluated here, with results indicating that high levels of chemical complementarity between tumor-resident TCR CDR3s and CMV antigens represented a better outcome. This is in apparent contrast to results obtained via the previous study of blood sourced, anti-CMV TCR CDR3s representing a worse outcome. This study identified gene expression values associated with the tumor-specific anti-CMV TCR CDR3s, representing exact matches to known anti-CMV TCR CDR3s, which may assist in identifying a potential underlying mechanism effecting the better outcomes associated with the tumor-resident, anti-CMV TCR CDR3s. Overall, results here raise the question of whether an anti-CMV response directly against the tumor, or within the tumor microenvironment, is involved in reductions in tumor progression or responsiveness to treatment?

Humans

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

Systematic review of microorganism disinfection performance by chemical and ultraviolet light water treatment methods.

Safe drinking water is critical for public health, yet microbial contamination remains a significant global challenge. We conducted a systematic review to update World Health Organization guidance on water disinfection technologies by synthesizing peer-reviewed literature from 1997 to 2021 on the performance of free chlorine, chlorine dioxide, ozone, and ultraviolet (UV) light against bacteria, viruses, and protozoa. Following PRISMA guidelines, we analyzed log10 reduction values (LRVs) and contact times (Ct) or fluence (for UV) from laboratory and field studies. We included studies from multiple databases and expert-recommended studies. Results show mean Cts for 2 LRV of non-opportunistic bacteria as 6.0 (free chlorine), 0.4 (chlorine dioxide), and 1.2 (ozone) mg/L*min, and a mean UV fluence of 8.2 mJ/cm&#xb2; (all bacteria). Viruses required lower Cts, except for UV-resistant adenoviruses, while protozoa required higher Cts or fluences. Opportunistic bacteria required significantly higher Cts than non-opportunistic bacteria for free chlorine and chlorine dioxide. Temperature and pH effects were inconsistent, highlighting data variability and gaps in field studies. These findings support global guidance on water treatment and may be used alongside other context-specific data to understand the roles these technologies play in reducing waterborne exposures. We recommend standardized reporting from performance studies to enable straightforward synthesis of evidence.

Disinfection

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating immune cells (TIICs) play a critical role in EAC prognosis and treatment response. METHODS: We integrated single-cell RNA sequencing and bulk transcriptome data from TCGA and GEO databases. TIIC-specific RNAs were identified via tissue specificity index calculation combined with machine learning feature selection. Twenty machine learning algorithms were benchmarked to construct an optimal TIIC signature score (TIIC-Score) based on the comprehensive C-index. Immunotherapy response, genomic mutation, and copy number variation were analyzed. Summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) were performed to explore genetic associations. Core prognostic TIIC-related genes were functionally validated in esophageal cancer cell lines through loss-of-function assays. RESULTS: The TIIC-Score demonstrated robust prognostic value for 1-, 2-, and 3-year overall survival across multiple cohorts, outperforming 22 published models. High TIIC-Score was associated with poor survival and increased chromosomal instability. Mutation profiling revealed high frequencies of TP53 (78.2%), TTN (48.7%), and SYNE1 (30.8%). MR analysis identified a significant association between gastro-oesophageal reflux and EAC risk at SNP rs8130507. Functionally, CCNI was upregulated in esophageal cancer cells, and its knockdown suppressed malignant phenotypes while promoting apoptosis, supporting its pro-tumorigenic role. CONCLUSION: The TIIC-Score provides a novel prognostic framework for EAC that effectively stratifies patient risk and may help identify individuals most likely to benefit from immunotherapy.

Esophageal adenocarcinoma

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

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP&#xa0;+&#xa0;AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics

Ictal electroencephalography and heart rate as treatment criteria in electroconvulsive therapy: a systematic review of the literature.

BACKGROUND: Decades before the emergence of precision medicine, psychiatrists raised the question of whether specific seizure characteristics could help optimize electroconvulsive therapy (ECT), as relationships between some of these characteristics and better outcomes were found. From 1990 onward, researchers focused on electroencephalography (EEG) and cardiovascular markers, which were broadly adopted by guidelines worldwide. However, the prognostic value of these markers is still controversial. Here, we provide a systematic summary of the studies on this topic. METHODS: We conducted a literature review on the use of ictal EEG and heart rate as outcome predictors in ECT using the PubMed, EMBASE, Cochrane and PsycINFO databases. RESULTS: Thirty-seven studies addressing more than 100 quality markers fulfilled our inclusion criteria. Single EEG markers were assigned to five categories (postictal inhibition, amplitude, coherence, regularity, and seizure duration). Heart rate and composite markers were considered separately. In contrast to single EEG markers, heart rate and composite markers could be consistently linked to better outcomes in patients with depression. Only a few studies on schizophrenia could be retrieved. CONCLUSION: Multiparametric markers outperformed single markers. Furthermore, changes in heart rate during seizures were related to better outcomes. Although clinical assessment remains the cornerstone of treatment guidance decisions, EEG and cardiac monitoring could help prevent insufficient seizures during the period preceding clinical improvement. Evidence on schizophrenia remains limited. More randomized trials are needed to analyze the role of composite markers as prognostic tools.

Humans

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries

PPRC1 is a prognostic biomarker and key regulator of mitochondrial oxidative phosphorylation in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) remains an incurable haematological malignancy, underscoring the need for novel prognostic biomarkers and therapeutic targets. This study aimed to investigate the clinical and biological significance of peroxisome proliferator-activated receptor gamma coactivator-related protein 1 (PPRC1) in MM. METHODS: Expression and clinical data were obtained from public databases and an independent local cohort. Kaplan-Meier and Cox regression analyses were performed to evaluate prognostic value. Differential expression analysis, pathway enrichment analysis and single-cell RNA-seq data analysis were used to explore biological functions. PPRC1 was silenced in MM cell lines using siRNA to assess its effects on cell survival and oxidative phosphorylation. RESULTS: PPRC1 was significantly upregulated in MM and was associated with advanced disease stage and poor overall survival. Multivariate Cox analysis identified PPRC1 as an independent prognostic factor. A nomogram incorporating PPRC1 and revised-ISS improved survival prediction. Functional analyses revealed that PPRC1 was positively correlated with oxidative phosphorylation and oncogenic signalling pathways. A potential connection between PPRC1 expression and immune cell infiltration was observed. PPRC1 knockdown inhibited cell proliferation, induced cell cycle arrest and apoptosis and impaired oxidative phosphorylation in MM. CONCLUSIONS: PPRC1 acts as a prognostic biomarker and metabolic regulator in MM by sustaining mitochondrial oxidative phosphorylation. These findings highlight PPRC1 as a potential therapeutic target in MM.

Humans

In vitro evaluation of sacituzumab govitecan in non-small cell lung cancer with actionable genomic alterations.

PURPOSE: The TROP2-directed antibody-drug conjugate sacituzumab govitecan (SG) has shown substantial therapeutic benefit in several malignancies; however, preclinical evidence supporting its activity in non-small cell lung cancer (NSCLC) is rare. MATERIALS AND METHODS: We evaluated 16 NSCLC cell lines harboring actionable genomic alterations for TROP2 expression and treated them with SG or its unconjugated payload, SN-38, for 3 days to determine cytotoxic effects. Apoptosis and DNA damage signaling were assessed using flow cytometry and western blot. SG internalization and lysosomal trafficking were visualized by confocal microscopy. RESULTS: SG had greater cytotoxic potency than SN-38, across all NSCLC cell lines, independent of genomic subtype or TROP2 expression level. Cell lines that were sensitive to SN-38 showed enhanced vulnerability to SG (P < 0.0001). Higher SLFN11 expression, a recognized determinant of SN-38 responsiveness, correlated with lower SG IC50 values. Both SG and SN-38 triggered apoptotic and DNA damage responses within 6-48 h, with SG inducing stronger activation of these pathways than SN-38. SG was efficiently taken up in CUTO17 and SNU-3173 adenocarcinoma cells, with more than 60% of the conjugate internalized within 3 h and subsequently localized to lysosomes. CONCLUSION: Our study provides in vitro evidence supporting the potential activity of SG in NSCLC with actionable genomic alterations. The efficacy of SG closely paralleled intrinsic sensitivity to the SN-38 payload, suggesting that DNA-damage responses, rather than oncogenic drivers, predominantly contribute to SG activity.

Actionable genomic alterations

Genome-wide identification of the peanut HD-Zip gene family and AhHDZ15 positively regulating salt and drought stress in heterologously overexpressed Arabidopsis.

Homeodomain-leucine zipper (HD-Zip) transcription factors play important roles in plant growth, development, and abiotic stress responses. However, bioinformatic analyses and functional studies of HD-Zip family in peanut are scarce. In this study, 128 AhHDZ genes were identified and classified into four subfamilies in the phylogenetic analysis. Transcriptomic data and RT-qPCR analysis indicated the expression levels of AhHDZ4 and AhHDZ15 were significantly elevated in response to 12&#x202f;h of salt stress, while AhHDZ4/15/60/69/126 all showed a progressive increase over time in response to drought stress. AhHDZ15 protein was localized in the nucleus. Under salt and drought stress, the germination rates of AhHDZ15-overexpressing in Arabidopsis were significantly higher than wild-type (WT), and root lengths were also significantly longer than WT. In addition, the SOD, CAT, chlorophyll content, and Relative Leaf Water Content (RLWC) value of leaves in AhHDZ15-overexpressing lines were significantly higher than WT, while the MDA content was significantly lower than WT. The above results indicate that heterologous overexpression of AhHDZ15 enhanced salt and drought tolerance in Arabidopsis. Furthermore, AhHDZ15 could bind to the L1-box element of the AhVNI2 promoter, thereby activating AhVNI2 transcription and enhancing the expression of downstream salt stress-responsive genes. These findings implies a potential function of AhHDZ15 in peanut that requires further validation.

Arabidopsis

Clinical pharmacokinetics of afatinib: A systematic review.

BACKGROUND: Afatinib is commonly used in the treatment of non-small cell lung cancer (NSCLC). This systematic review summarizes clinical pharmacokinetics (PK) evidence focusing on the effect of disease state and drug interactions on afatinib exposure. METHODS: Google Scholar, Science Direct, PubMed, and the Cochrane library were searched for human studies reporting the clinical PK of afatinib. The search yielded 24 articles that met the predefined inclusion criteria. RESULTS: Afatinib exposure increased slightly more than dose proportionally, with higher doses producing greater AUC0-24 and Cmax values. The apparent oral clearance reported after administration of the oral solution was lower than that observed following tablet administration. The Cmax of afatinib increases by 38.5% after coadministration with ritonavir and exposure decreases 34.3% with rifampicin. The Cmax decreases 31.45% when given with pemetrexed. Both the AUC0-24 and Cmax increase in NSCLC and tumor state. The AUC0-24 of afatinib is 2.61 folds higher following multiple oral doses among patients with solid tumors. Afatinib exposure is 22.1 % higher in renal impaired patients than in healthy controls. In grade 2 diarrhea, the AUC0-24 of afatinib is 83.93% higher as than in grade 0-1 diarrhea in solid tumor patients. CONCLUSION: This systematic review provides an updated synthesis of clinical PK evidence on afatinib. Afatinib exposure is influenced by dose, repeated administration, renal impairment, diarrhea associated toxicity, and P-glycoprotein mediated drug interactions. These findings may support individualized dosing, toxicity-guided dose adjustment, and future development of PK models for afatinib.

Humans

Depression and amyloid-&#x3b2; across CSF, PET, and plasma biomarkers: a systematic review and meta-analysis.

Alzheimer's disease is increasingly defined by biomarker evidence of amyloid-&#x3b2; and tau pathology, sharpening questions about whether late-life depression contributes to, or instead reflects, this pathology. We conducted a systematic review and meta-analysis of studies published between 2000 and 2025 that compared amyloid-&#x3b2; biomarkers in adults with and without depression, with depression defined by validated clinical diagnoses or symptom rating scales. Twenty-four studies were included, spanning three biomarker sources: cerebrospinal fluid, positron emission tomography imaging, and plasma. Across all sources, the pooled difference in amyloid-&#x3b2; burden between depressed and non-depressed individuals was small and clustered near zero, indicating only a weak, statistically non-significant tendency toward higher amyloid in depression. When the three sources were examined separately, each yielded a similar near-null result, although between-study heterogeneity was considerable for cerebrospinal fluid and plasma and moderate for imaging. Importantly, a prespecified subgroup analysis showed that imaging results diverged by quantification method: studies using the simpler standardized uptake value ratio clustered around zero, whereas the smaller group of studies using kinetic distribution volume ratio modelling showed a significant positive association, suggesting that methodological choices critically influence the observed relationship. Taken together, these findings indicate that depression is not consistently accompanied by greater amyloid-&#x3b2; burden across widely used biomarker platforms. The distribution volume ratio signal nonetheless raises the possibility of subtle associations that cruder methods may obscure, and suggests that depression may shape Alzheimer's disease trajectories more by modifying the clinical impact of amyloid than by altering its amount.

Humans

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&#x2009;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. &#xa9; 2026 Society of Chemical Industry.

Animals