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Fluoride as a Modifier of Metallome Homeostasis: A Systematic Review of Animal Studies.

Fluoride is widely used for caries prevention due to its effects on mineralized tissues, yet its potential role as a modifier of systemic metal homeostasis remains insufficiently explored. This systematic review synthesizes preclinical evidence on the association between fluoride exposure and changes in metal and semi-metal concentrations across biological matrices. A comprehensive search strategy was conducted across major databases without language or date restrictions, following SyRF, CAMARADES and PRISMA 2020 guidelines. Thirty-one animal studies were included, encompassing multiple species, exposure conditions and analytical approaches. Despite substantial methodological heterogeneity, consistent patterns emerged. Fluoride exposure was associated with element-specific redistribution of the metallome rather than uniform change. Essential elements were predominantly depleted, most consistently zinc, copper and manganese, whereas the toxic metals lead and cadmium tended to be retained. This contrast between homeostatically regulated essential elements that are lost and non-regulated toxic metals that accumulate supports the hypothesis that fluoride differentially modifies the distribution and retention of co-existing elements. The novelty of this review lies in integrating metallomic outcomes across experimental models, highlighting fluoride as a potential systemic modulator rather than a tissue-specific agent. Although variability in study design and risk of bias limits causal inference, the consistent directionality of findings across models reinforces their biological plausibility and translational relevance.

Animals

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

Morphology-engineered NiFe@C nanocages boosting electrochemical quantification of ractopamine in meat samples.

It is essential to acquire efficient electrocatalysts to develop ractopamine (RAC) electrochemical sensors. Herein, we report the synthesis of a series of carbon coated NiFe alloy nanostructures (e.g., NiFe@C nanoparticles, nanocubes and nanocages) using NiFe Prussian blue analogue (PBA) as the precursor. The NiFe@C nanocages exhibited the best electrocatalytic performance for RAC sensing. This is attributed to the embedded NiFe alloy nanoparticles that provide abundant active sites, and the unique nanocage structure facilitates electron transfer pathways while offering a high specific surface area. The resulting sensor achieves a low detection limit (LOD) of 54 nM (S/N = 3) within a linear range of 0.2-12 μM. Moreover, the sensor demonstrates good reproducibility, stability, and excellent long-term stability. Practical applicability was confirmed in meat samples, yielding satisfactory recovery rates ranging from 98% to 108%. A feasible strategy was introduced herein for rational design of metal@carbon electrocatalysts.

Phenethylamines

Tracking microplastic contamination across seasons in a freshwater reservoir: Evidence from surface water, sediments, and fishes.

Microplastics (MPs) are prevalent contaminants in aquatic environments, posing substantial ecological and health risks. These particles migrate within the different layers of aquatic bodies with time and affect the respective biota. Thus, to get an in-depth understanding of the particles, this current study investigated the seasonal distribution, morphological and chemical characteristics, along with potential ecological and human health impacts in the samples including surface water, sediment, and fish from a drinking water supplying reservoir in eastern India. Across three different seasons, pre-monsoon, monsoon, and post-monsoon samples were collected using optimized methods. Results revealed distinct seasonal trends: MP abundance in surface water peaked during the monsoon (mean: 1.15 MPs/L), while sediment showed the highest concentrations in the pre-monsoon (mean: 596 MPs/kg), indicating temporal accumulation dynamics influenced by runoff, hydrodynamics, and sedimentation. Fish gut analysis confirmed ingestion of MPs across five species, with concentrations ranging from 26 to 100 MPs/kg, depending on feeding habits. The most dominant MP type were fragments, followed by fibers, films, and beads. Polymer analysis via µFTIR identified polyethylene, polypropylene, and polyvinyl chloride as prevalent, with hazard assessments (i.e., Polymer Hazard Index (PHI)) indicating medium to very high ecological risks. Heavy metal association was more dominant in the MPs isolated from sediments than the waterborne MPs. Pollution Load Index (PLI) values were > 1 in most seasons, confirming contamination. Health risk analysis suggested potential exposure through both drinking water and fish consumption. This study emphasizes the need for seasonal monitoring, improved waste management, and mitigation strategies to address MP pollution in freshwater ecosystems.

Microplastics

Dual signal-enhanced immunochromatographic test strip based on Au@PtNPs: From sensitive detection of thiamethoxam to multiplex pesticide screening in vegetables.

Immunochromatographic test strip (ICTS) is a rapid analytical technique widely used in environmental and food detection owing to its merits of simple operation and short analysis time. Herein, three-dimensional nanoflower-structured gold‑platinum nanoparticles (Au@PtNPs) were synthesized via a seed-growth method. Compared with conventional gold nanoparticles (AuNPs), Au@PtNPs exhibited stronger signal intensity, excellent catalytic performance, and efficient antibody binding efficiency. Colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS were developed for the sensitive detection of thiamethoxam (THI) in vegetables. The limits of detection (LODs) for colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS quantitative analysis were 0.18 ng/mL and 0.093 ng/mL, respectively, representing approximately 3-fold and 6-fold improvement compared to AuNPs-ICTS (0.56 ng/mL). Furthermore, highly sensitive detection of multiple pesticide residues (chlorpyrifos, acetamiprid, and imidacloprid) was achieved by replacing the corresponding target antigens and antibodies, which further verified the universality of this immunochromatographic strategy.

Thiamethoxam

Engineering copper ferrite (CuFe2O4) nanocomposites for enhanced eco-friendly photocatalysis: a systematic critical review on mechanisms, performance, and environmental applications.

Water pollution caused by organic and inorganic contaminants, particularly dyes and pharmaceuticals, represents a major environmental challenge. Advanced oxidation processes based on photocatalysts have emerged as efficient and sustainable approaches for water and wastewater treatment. Copper ferrite (CuFe2O4) is considered a promising photocatalyst owing to its narrow bandgap, visible-light activity, chemical stability, and magnetic properties. Despite extensive experimental investigations, a comprehensive systematic comparison of CuFe2O4-based photocatalysts under diverse operational conditions has remained limited. In this study, a systematic review following PRISMA guidelines was conducted using studies published between January 2014 and November 2025 indexed in Scopus, PubMed, Web of Science, and ScienceDirect. From an initial pool of 397 studies, 98 articles met the inclusion criteria. Key parameters - including pollutant type, pH, catalyst dosage, initial pollutant concentration, irradiation time, light source, and degradation efficiency - were quantitatively compared to identify performance trends and operational optima. The results demonstrate that CuFe2O4-based nanocomposites, particularly heterojunction, Z-scheme, and S-scheme architectures combined with TiO2, g-C3N4, graphene, and metal oxides, achieve high degradation efficiencies (often >90 %) for a wide range of organic pollutants and selected inorganic contaminants (e.g., Cr(VI)). Enhanced charge separation and suppressed electron-hole recombination were identified as the primary factors contributing to improved photocatalytic activity. In addition, the intrinsic magnetic properties of these nanocomposites enable facile catalyst recovery and reuse. In conclusion, CuFe2O4-based nanocomposites, especially those incorporating advanced heterojunction architectures, emerge as highly efficient and magnetically recoverable photocatalytic platforms for sustainable water and wastewater treatment, with strong potential for scalable implementation and real-wastewater applications.

Catalysis

Spatially confined electrochemical strategy with DNA-assembled nanogaps for SNP detection.

Accurate detection of low-abundance single nucleotide polymorphisms (SNPs) against a large excess of homologous wild-type sequences requires both selective molecular recognition and effective transduction of small sequence differences into measurable signals. Here, we report a spatially confined electrochemical strategy that couples sequence-selective recognition with size-dependent mass-transport gating. DNA-hybridization-driven self-assembly of gold nanoparticles (AuNPs) forms a three-dimensional self-assembled electrode (3D-SAE) with a DNA-defined interparticle architecture. Competitive probes (SP/WP) convert single-base recognition into distinct molecular-size states: the SNP-associated pathway preferentially triggers a hybridization chain reaction (HCR), generating bulky AuNP-anchored HCR/methylene blue complexes (Au@HCR/MB) with reduced electrochemical accessibility through the porous 3D-SAE, whereas the wild-type pathway does not trigger HCR and maintains a high-current response from more readily accessible MB-containing species. Thus, sequence recognition is translated into a molecular-size difference and subsequently into an electrochemical signal through differential mass transport. Under buffer conditions, the platform achieved a statistically estimated detection limit of ∼0.47 fM and a quantitative range of 1 fM-100 pM. It discriminated a 0.1% mutant abundance in a fragmented genomic-DNA background. The downstream signal-transduction chemistry is enzyme-free and isothermal. This work establishes a mechanistical recognition-size-conversion-mass-transport-gating architecture for electrochemical nucleic acid analysis.

Polymorphism, Single Nucleotide

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans

Health and Physical Activity Outcomes in Age-Friendly Cities and Communities: A Systematic Review of Emerging Evidence and a Future Research Agenda.

OBJECTIVES: The World Health Organization's (WHO) Global Network of Age-Friendly Cities and Communities (AFCCs) promotes the development of urban environments, policies and services that support the health and participation of older adults. This systematic review examined contemporary evidence concerning associations between WHO AFCC conditions and directly measured health and physical activity outcomes among older residents. METHODS: The registered review adhered to the PRISMA protocol for systematic reviews and meta-analyses and applied the Downs and Black quality criteria for randomised and non-randomised research. RESULTS: Structured Boolean searches of five research repositories identified 17 peer-reviewed studies published between 2017 and 2025 based upon original research conducted in WHO AFCC signatory cities. Although most studies reported positive associations between age-friendly features and domains, such as accessible transport, walkable environments, outdoor infrastructure and self-rated health or physical activity, the strength of evidence was limited by methodological inconsistency, variable study quality and reliance on self-reports. Barriers to evaluation included limited use of longitudinal or quasi-experimental designs, heterogeneous outcome measures, subjective response data and the challenge of establishing appropriate comparison conditions in complex municipal settings. CONCLUSIONS: Strengthening evaluation frameworks for AFCC initiatives is essential for evidence-based urban health policy and governance in rapidly ageing societies. A research agenda is proposed to strengthen AFCC evaluation through standardised measurement, community-based and mixed-methods research, and a greater commitment to co-designed assessment frameworks.

Humans

The Interrelationship between Cadmium, Smoking, and Migraine in the ELSA-Brasil Study.

This study explored the relationship between serum cadmium (Cd), smoking exposure, and migraine in the ELSA-Brasil cohort (2008-2010). The analysis included 2,750 participants whose serum Cd levels were measured using inductively coupled plasma mass spectrometry. Smoking exposure was assessed using self-report data of active smoking and second-hand smoke. Migraine, including definite and probable migraine, was diagnosed according to the International Classification of Headache Disorders, 3rd edition (ICHD-3). Logistic regression was used to estimate the odds of migraine across serum Cd quintiles, using the third quintile as the reference category, while linear regression examined the relationship between smoking exposure and Cd levels. Polynomial contrasts tested linear trends. Participants had a mean (SD) age of 53.2 (9.0) years and 53.1% were women. Migraine prevalence was 29.1% (including probable migraine). Individuals with migraine had slightly higher median serum Cd levels than controls [0.050&#xa0;&#xb5;g/L (IQR 0.035-0.077) vs. 0.048&#xa0;&#xb5;g/L (0.035-0.066); p&#x2009;=&#x2009;0.021], although smoking exposure scores did not differ between groups. Smoking exposure showed a strong positive association with serum Cd concentrations (p-trend&#x2009;<&#x2009;0.001). Participants in the highest Cd quintile had greater odds of migraine [aOR 1.51 (95% CI 1.09-2.08), p&#x2009;=&#x2009;0.011] after adjustment for smoking exposure and sociodemographic and clinical confounders. Sex-stratified analysis yielded even stronger associations among males [aOR 1.84 (95% CI 1.07-3.16), p&#x2009;=&#x2009;0.027]. However, in the sensitivity analysis including definite migraine cases only, this association was no longer significant [aOR: 1.14 (0.71, 1.83), p&#x2009;=&#x2009;0.579]. Main findings suggest that Cd exposure from smoking may contribute to migraine occurrence, particularly in males. However, other sources of Cd that could influence migraine should not be disregarded, and future investigation in this field is warranted.

Cadmium

Ecological Restoration of the Soil-Like Function in the Bauxite Residue: Natural Microbiomes Mediated Molecular Transformation of Dissolved Organic Matter.

Soilization of bauxite residues offers a scalable route for long-term carbon management and ecological restoration. However, the microbial processes that transform exogenous organic inputs into stable soil-like carbon pools remain poorly resolved. Here, we combined cross-ecosystem meta-analysis, machine-learning prediction, native synthetic community (SynCom) construction, 13C-labeled straw microcosms, field validation, Fourier transform ion cyclotron resonance mass spectrometry, and genome-resolved metagenomics to unravel microbiome-mediated carbon transformation at the dissolved organic matter (DOM) molecular scale. Our meta-analysis revealed that alkaline industrial wastes retained soil-like DOM signatures but were enriched in microbial humic- and protein-like components, indicating active yet incomplete carbon processing. Guided by these patterns, native SynCom inoculation increased 13C incorporation into total organic carbon (TOC) and dissolved organic carbon (DOC), enlarged biodegradable and adsorbable DOC fractions, and shifted DOM from recalcitrant aromatic pools toward oxygenated carbohydrate-, tannin-, and phenolic-like molecular classes. Genome-resolved analyses linked this transformation to complementary polymer degradation and nutrient-cycling functions across fungal and bacterial guilds, including enriched carbohydrate-active enzymes in straw-carbon-utilizing metagenome-assembled genomes. Null model and thermodynamic analyses further showed that microbial communities were constrained by homogeneous selection, whereas DOM molecules were diversified through variable selection and redox-dependent transformation. Field-scale validation confirmed that SynCom promoted TOC and DOC accumulation and humic-like, high-density DOM fractions under alkaline conditions. Together, these findings establish a mechanistic framework in which functional microbiomes couple plant carbon depolymerization, DOM molecular diversification, and mineral-interactive carbon stabilization, providing a microbiome-guided strategy for carbon sequestration and soilization in the bauxite residue.

Soil

Three-dimensional source apportionment and quantitative characterization of horizontal and vertical transport fluxes of O3 and its precursors in the Beijing-Tianjin-Hebei region, China.

Persistent surface ozone (O3) pollution in the Beijing-Tianjin-Hebei (BTH) region is driven by coupled precursor emissions and multi-scale transport, yet its altitude-dependent transport and source contributions remain insufficiently quantified. Here we integrated the Weather Research and Forecasting and the Comprehensive Air Quality Model with Extensions with the Ozone Source Apportionment Technology and a quantitative transport-flux framework to characterize three-dimensional source apportionment and horizontal/vertical fluxes of O3, Volatile Organic Compounds&#x200c; (VOCs), and Nitrogen Oxides (NOx) across dynamic meteorological scenarios. Simulations showed that VOCs and NOx were dominated by local emissions near the surface (73.61 %-82.18 %), whereas surface O3 was primarily controlled by regional transport, with local contributions of only 11.01 %-13.75 %. Notably, the transport dominance further strengthened with altitude, exceeding 93 % at 1.8 km. Industrial and transportation emissions together contributed more than 75 % of precursor emissions and account for approximately 80 % of O3 formation, while favorable/unfavorable meteorological years modulated long-range transport efficiency and the vertical distribution of contributions. Horizontal flux analysis highlighted three major pathways (Northwest-Southeast, Southeast-Northwest, and Southwest-Northeast), with Shijiazhuang serving as a critical pollutant "sink" across altitude layers. Vertical fluxes revealed an altitude transition near 600 m: net downward transport dominated below 600 m, whereas enhanced summer convection promoted upward transport above 600 m. These results support altitude-dependent, scenario-specific strategies for coordinated regional O3 mitigation in the BTH region.

Ozone

Epithelial regeneration in the gastrointestinal tract.

The gastrointestinal tract possesses a remarkable regenerative capacity to maintain tissue homeostasis against various injuries. However, the intestine and stomach exhibit distinct regenerative strategies. In the intestine, damage to Lgr5-positive (Lgr5+) stem cells induces cellular plasticity and the emergence of transient Revival stem cells (RevSCs), a process critically dependent on YAP/TAZ signaling. Conversely, the stomach utilizes paligenosis, where quiescent p57-positive (p57+) mature chief cells act as reserve stem cells, dedifferentiating to restore damaged tissue. Although the cellular origins differ, both organs appear to share some common regenerative features, including transient activation of pro-proliferative programs such as YAP/TAZ signaling. In contrast, whether Retinoic Acid (RA) signaling also serves as a conserved mechanism for regenerative resolution in the stomach remains to be determined. In this review, we discuss the cellular and molecular mechanisms governing regeneration in these two organs. This comparative analysis provides a framework for future research.

Regeneration

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

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

Context-dependent functional diversity of dorsomedial posterior parietal neurons revealed by single-unit fMRI mapping during naturalistic viewing.

The dorsomedial posterior parietal cortex (dmPPC) plays an important role in episodic processing by integrating sensory, cognitive, and motor information across distributed brain systems. However, how individual dmPPC neurons participate in large-scale functional organization during naturalistic experience remains poorly understood. To address this question, we combined single-unit electrophysiology and awake fMRI in five rhesus macaques of both sexes viewing identical naturalistic video stimuli. Using single-unit fMRI mapping, we generated whole-brain neuron-BOLD functional maps by correlating individual neuronal activity with voxel-wise fMRI signals across the brain. We found that neuron-BOLD functional maps exhibited strong context-dependent organization, with neurons recorded during the same video context showing substantially greater similarity than neurons recorded during different video conditions. Compared with neuronal spiking activity or critical fMRI frames alone, neuron-BOLD functional maps more robustly captured contextual structure. Despite this shared large-scale organization, a substantial subset of neighboring neurons recorded simultaneously from the same electrode displayed markedly distinct whole-brain association patterns, revealing substantial local functional heterogeneity within the dmPPC. This local heterogeneity was not readily explained by waveform-based putative cell class or by opposing neuronal firing dynamics. In addition, distributed cortical and medial temporal regions exhibited highly context-dependent neuron-BOLD association patterns during naturalistic viewing. Together, these findings demonstrate that dmPPC neurons participate in dynamic and heterogeneous large-scale functional organization during naturalistic episodic processing. More broadly, this study establishes single-unit fMRI mapping as a framework for linking single-neuron activity to distributed whole-brain dynamics across contextual conditions.Significance Statement Using single-unit fMRI mapping, this study examined how individual dorsomedial posterior parietal cortex (dmPPC) neurons relate to large-scale brain activity during naturalistic video viewing in macaque monkeys. We found that neuron-BOLD functional maps exhibit strong context-dependent organization and capture contextual structure more robustly than neuronal spiking activity or fMRI frames alone. Despite this shared organization, a substantial subset of neighboring dmPPC neurons displayed markedly distinct whole-brain association patterns, revealing local functional heterogeneity that was not readily explained by waveform-based putative cell class or opposing firing dynamics. These findings provide insight into how local neuronal populations participate in distributed brain-wide functional organization during naturalistic episodic processing.

Journal Article

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

MET-Aberrant non-small cell lung cancer: from kinase dependence to cell-surface targetability-mechanistic basis and biomarker framework for bispecific antibodies and antibody-drug conjugates.

MET-aberrant non-small cell lung cancer (NSCLC) is not a uniform therapeutic entity. Its biology, diagnostic pathways, and treatment sensitivity differ across MET exon 14 skipping alteration (METex14), MET amplification, and MET overexpression. This heterogeneity cannot be fully explained by conventional event-based classification and is reflected in the distinct clinical activity of MET tyrosine kinase inhibitors (MET-TKIs), bispecific antibodies (BsAbs), and antibody-drug conjugates (ADCs). With the emergence of antibody-based therapies, MET has evolved from a signaling driver to a cell-surface target for receptor modulation and payload delivery. We therefore propose a clinically anchored two-dimensional framework for interpreting therapeutic relevance in MET-aberrant NSCLC: kinase dependence and cell-surface targetability. Neither dimension should be regarded as a directly measurable binary variable. Kinase dependence is inferred from genomic and treatment-contextual proxies, most strongly METex14 and, more conditionally, high-level focal MET amplification. Cell-surface targetability is approximated by drug-specific IHC assessment of assay-defined c-MET protein expression; however, receptor internalization, intracellular trafficking, and payload delivery capacity remain incompletely measurable in routine clinical practice. Within this framework, MET-TKIs have the most evidence-supported established role in tumors with evidence of MET-driven kinase dependence. EGFR &#xd7; MET BsAbs have demonstrated clinical activity in broad post-osimertinib EGFR-mutant NSCLC, while EGFR/MET co-dependence or MET-mediated bypass activation provides a mechanistic rationale for their use; MET-defined preferential benefit remains to be prospectively established. MET-directed antibody-drug conjugates (MET-ADCs) are supported in drug- and assay-defined populations with high c-MET protein overexpression, although the predictive relevance of delivery-related factors remains hypothesis-generating. Accordingly, MET testing should shift from single-event detection to platform-oriented stratification: next-generation sequencing (NGS) for driver alterations and resistance profiles, fluorescence in situ hybridization (FISH) for high-level focal amplification, and immunohistochemistry (IHC) for surface expression relevant to antibody-based therapies. This framework is intended to organize current biological and clinical evidence rather than to replace drug-specific companion diagnostics, regulatory indications, or prospectively validated treatment-selection algorithms. Precision treatment of MET-aberrant NSCLC is thus moving from event-based drug selection toward mechanism-based therapeutic matching. Future priorities include standardizing biomarkers, defining optimal target populations, and aligning biological subtypes, diagnostic strategies, and therapeutic platforms.

Antibody-drug conjugate