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PubMed2026

The voice clone intelligibility benefit in noise in middle-aged listeners.

Research with younger adults showed that cloned voices are more intelligible than human voices in noise, with a benefit of 13.4%. This study tested whether this benefit extends to 40 middle-aged listeners (45-65 years), as this population may show emerging difficulties with speech-in-noise. Participants recognised sentences by ten human voices and ten voice clones in four noise levels. Cloned voices were 11.8% more intelligible, with benefits enhanced at the two most severe noise levels (15.9% at -6 dB and 17.5% at -3 dB), suggesting cloned speech enhanced perception in middle-aged listeners, potentially by reducing listening effort and compensating for emerging age-related auditory-cognitive decline.

Humans↗

PubMed2026

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

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

Journal Article↗

PubMed2026

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

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

Hyperspectral Imaging↗

PubMed2026

Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of auditory nerve output after threshold recovery.

BACKGROUND: Acoustic stress can alter cochlear function even in the absence of permanent threshold elevation; however, synaptic consequences of transient acoustic stimulation remain incompletely understood. OBJECTIVE: This study aimed to investigate whether transient acoustic stimulation induces changes in the auditory nerve output and cochlear ribbon synapse morphology following hearing threshold recovery. METHODS: Young adult CBA/CaJ mice were exposed to band-limited acoustic stimulation (45-2,000 Hz, 95 dB SPL, 2 h). Auditory brainstem responses (ABRs), hair cell and spiral ganglion neuron survival, and synaptic morphology were evaluated before exposure and up to 2 weeks post-exposure. RESULTS: ABR thresholds were transiently elevated immediately after exposure but largely recovered by 1 day post-exposure. In contrast, ABR wave I amplitudes significantly increased after threshold recovery across multiple test frequencies. Ribbon-associated puncta in both inner and outer hair cell regions exhibited biphasic temporal changes, with an initial decrease immediately after exposure followed by an increase at 1 day post-exposure. The ribbon-associated punctal area also increased after exposure and remained elevated at later post-exposure time points. No significant loss of hair cells or spiral ganglion neurons was observed. Exploratory genomic analysis suggested enrichment of pathways related to metabolic defense and cellular stress responses. CONCLUSIONS: Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of peripheral auditory nerve output without overt cellular degeneration. These findings support a model in which early cochlear responses to acoustic perturbation include adaptive synaptic plasticity and gain regulation, extending current concepts of noise-induced cochlear change beyond irreversible synaptic loss.

Animals↗

PubMed2026

Neuromodulation for Subjective Tinnitus: A Systematic Review and Meta-Analysis of Randomized Trials.

OBJECTIVE: To evaluate the effectiveness and safety of neuromodulation and bimodal stimulation for chronic subjective tinnitus in randomized controlled trials (RCTs). DATA SOURCES: PubMed/MEDLINE, Web of Science, and EMBASE (January 2015-December 2025) searched per PRISMA 2020. REVIEW METHODS: Adult RCTs (≥ 18 years) with chronic subjective tinnitus (> 3 months) assessing validated outcomes (THI, TFI, TQ) for neuromodulation/bimodal interventions vs. sham/controls. Two-stage screening, Cochrane RoB-2 risk-of-bias assessment. Random-effects meta-analyses (REML) were performed when ≥ 3 comparable trials were available; effects reported as standardized mean differences (SMD) with 95% CIs. Main Outcomes and measures included change in tinnitus severity (THI/TFI/TQ) while secondary outcomes included loudness (VAS/NRS), durability, and adverse events. RESULTS: Twenty-six RCTs (n = 1576) met criteria: tES (11; n = 372), rTMS (8; n = 432), acoustic coordinated reset (1; n = 100), vagus nerve stimulation (2; n = 90), and bimodal stimulation (4; n = 582). Meta-analysis showed a nonsignificant pooled effect for tDCS (SMD -0.36; 95% CI -0.75 to 0.02; I 2 = 51%) and rTMS (SMD -0.15; 95% CI -0.37 to 0.07; I 2 = 0%). Single-trial evidence for coordinated reset showed no advantage over broadband noise. VNS demonstrated modest benefits with safety concerns limited to implanted approaches. Bimodal stimulation yielded consistent, clinically meaningful reductions (often ≥ 10-20 points on THI/TFI), with durability up to 12 months. Adverse events were mild/transient across noninvasive modalities. CONCLUSIONS: Noninvasive neuromodulation appears safe with average benefits; among modalities, bimodal stimulation shows the most consistent and durable clinical improvements. Standardized, adequately powered RCTs with harmonized protocols and long-term follow-up are needed to refine targets and dosing.

Humans↗

PubMed2026

Urban Design Quality and Clinical Mental Health: A Systematic Review.

ObjectivesThis systematic review synthesizes empirical evidence on core urban design dimensions that affect clinical mental health outcomes and examines how environmental exposures mediate or moderate these relationships.BackgroundUrban design has increasingly been recognized as a determinant of psychological well-being, yet a standardized framework to evaluate its mental health impact remains underdeveloped.MethodsFollowing PRISMA 2020 guidelines, we systematically reviewed 19 quantitative empirical studies published through January 2025, examining relationships between outdoor urban design features and validated clinical mental health indicators across four major databases.ResultsFindings reveal that urban design influences clinical mental health outcomes (depression, anxiety, stress, cognitive decline) through two objective spatial scales: street-level features (imageability, enclosure, human scale, complexity) and neighborhood environments (land use mix, density, green infrastructure). Environmental exposures (traffic, noise, air pollution) operate as perceptual and experiential mechanisms that mediate or moderate the mental health effects of these spatial design features.ConclusionsWe propose an integrated three-domain conceptual framework distinguishing objective spatial design scales from subjective exposure mechanisms. This framework provides evidence-based guidance for urban planners and policymakers toward creating mentally healthier urban environments.

Humans↗

PubMed2026

Disentangling oscillatory and aperiodic neural activity in autism: A spectral parameterization analysis of neurofeedback intervention.

BACKGROUND: Autism Spectrum Disorder (ASD) is characterized by atypical neural oscillations and heterogeneous alterations in excitation/inhibition (E/I) balance, the directionality of which varies across individuals, neural circuits, and developmental stages. While Alpha-band neurofeedback (NFB) is a promising intervention, its underlying neurophysiological mechanisms remain unclear, partly due to the conflation of periodic and aperiodic signals in traditional EEG analysis. METHODS: This randomized controlled trial recruited 40 children with ASD, assigned to either an experimental group (Alpha-training NFB) or a no-feedback group. Resting-state EEG and behavioral assessments (SRS, ABC) were collected pre- and post-intervention. We employed spectral parameterization to decompose neural activity into aperiodic (1/f slope, offset) and periodic (periodic alpha power, center frequency) components. RESULTS: NFB training yielded significant behavioral improvements in social cognition and relating skills. Physiologically, the experimental group exhibited a significant steepening of the aperiodic slope (increased exponent), reflecting a reduction in neural noise and potential optimization of inhibitory modulation. Furthermore, we observed enhanced periodic alpha power and an acceleration of the alpha center frequency (ACF), indicative of improved neural efficiency and maturation. These physiological shifts in frontal and occipital regions were significantly correlated with improvements in behavioral scores. CONCLUSION: Alpha-training NFB was associated with improvements in caregiver-rated behavioral scores and modulated spectral features of resting-state EEG in children with ASD. These findings validate the utility of spectral parameterization markers in evaluating neuromodulatory interventions.

Humans↗

PubMed2026

Impact of Physical Environment of Pediatric Inpatient Wards on Children: A Systematic Literature Review.

ObjectiveThe study aimed to examine empirical studies published between 2003 and 2025 to identify elements of physical environments influencing health outcomes and experiences of children and families.BackgroundIn the past 40 years, research has shown that the physical environment influences the health and well-being of patients in the healthcare environment. However, similar research in the context of "pediatric inpatient wards" remains underexplored.MethodsPubMed, Embase, Scopus, and Web of Science were used to identify relevant articles. All extracted articles underwent a three-step screening process using PRISMA. A total of 30 eligible articles were used for the analysis. The protocol is registered at PROSPERO (CRD42023408997).ResultsKey findings reveal positive and negative impacts of identified elements. Positive-effect elements include play spaces, space for parents, natural light, connections with nature, and so on, which promote comfort, healing, and emotional resilience. Conversely, negative-effect elements, such as noise, artificial lighting, uncomfortable temperature, and so on, contribute to stress and disrupted sleep. Mixed effects were observed for elements like art and television, which underscore the complexity of designing environments that address the diverse needs of different age groups and genders.ConclusionsThe review findings highlight significant knowledge gaps. The study also tries to bridge existing gaps between research and practice by systematically identifying environmental elements, offering actionable insights to architects, designers, healthcare providers, and policymakers. Future research must adopt rigorous, culturally inclusive approaches to advance the field of pediatric healthcare design and ensure equitable care across diverse sociocultural contexts.

Humans↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Introgression shapes the genomic conflict landscape of Malus, providing evidence for a reticulate backbone in a woody crop lineage.

Phylogenomic discordance is widespread across plants, but its evolutionary significance is often obscured when conflict is treated primarily as analytical noise rather than as evidence of underlying processes. In woody lineages in particular, incomplete lineage sorting, introgression, and genome duplication can interact over long timescales to produce complex genomic histories that are not adequately summarized by a strictly bifurcating tree. Here, we use Malus as a model woody genus to investigate how these processes structure conflict across a genus-scale, accession-based phylogenomic framework. Using broad taxon sampling, hundreds of nuclear loci, plastid genomes, and genome-wide SNP summaries, we reconstruct a robust nuclear backbone for sampled Malus lineages and evaluate where discordance is concentrated and which processes best explain it. Nuclear analyses resolve eight major clades, whereas conflict is non-random and localized to recurrent hotspots rather than evenly distributed across the tree. Cytonuclear discordance is similarly concentrated, especially around Clade H, represented by sampled accessions of M. tschonoskii, where localized plastid-nuclear disagreement is consistent with candidate plastid capture or organellar introgression. Multiple complementary analyses further indicate that the strongest conflict is not explained by ILS alone, but instead reflects lineage-structured introgression, while polyploid complexes represent additional localized sources of evolutionary complexity. Together, these results provide evidence for a reticulate genomic backbone in Malus and show how integrating nuclear, plastid, and genome-wide conflict analyses can help distinguish background discordance from process-specific signals in woody plant radiations. Several lineage-level reticulation hypotheses identified here should now be tested with broader population-level sampling and curated reference accessions.

Malus↗

PubMed2026

Physiological and molecular responses of coelomocytes to low- to mid-frequency acoustic exposure in the sea urchin Strongylocentrotus intermedius.

Underwater noise is a widespread environmental pollutant in marine ecosystems, yet the effects of low- to mid-frequency acoustic exposure on immune physiology and molecular responses in echinoderms remain unclear. In this study, the sea urchin Strongylocentrotus intermedius was exposed to continuous pure-tone acoustic stimulation at 80, 125, 250, 500, 750, and 1000 Hz for 3 h. Results showed that acoustic exposure significantly affected redox homeostasis, energy metabolism, and immune function in S. intermedius coelomocytes: the antioxidant system and glutathione redox balance were altered, as indicated by increased superoxide dismutase (SOD) and catalase (CAT) activities, elevated reduced glutathione (GSH) content, and a higher GSH/GSSG ratio; glycolysis-related enzyme activities were enhanced, with increased pyruvate kinase (PK) activity under 125-500 Hz exposure and elevated hexokinase (HK) activity at 250 Hz; and immune function was impaired, as shown by increased coelomocyte mortality, reduced phagocytic activity, and inhibited acid phosphatase (ACP) and alkaline phosphatase (AKP) activities, whereas respiratory burst activity showed no significant change. Among all treatments, 250 Hz induced the most pronounced physiological responses. Transcriptomic analysis of coelomocytes from the 250 Hz group identified 663 differentially expressed genes, including 537 upregulated and 126 downregulated genes, mainly enriched in pathways related to apoptosis, phagosome, lysosome, glutathione metabolism, arachidonic acid metabolism, and carbohydrate metabolism. These findings indicate that low- to mid-frequency acoustic exposure can act as a physiological and molecular stressor to S. intermedius coelomocytes by affecting redox homeostasis, enhancing energy metabolism, and suppressing immune effector processes, with 250 Hz showing the strongest effect under the present exposure conditions. This study provides experimental evidence for evaluating the potential biological effects of low- to mid-frequency acoustic exposure on benthic echinoderms.

Animals↗

PubMed2026

Reducing state anxiety with alpha-frequency transcranial alternating current stimulation.

BACKGROUND: Anxiety reactivity to acute stress is a transdiagnostic vulnerability factor. We tested whether a single session of alpha-frequency transcranial alternating current stimulation (tACS) targeting the frontoparietal control network reduces stress-evoked state anxiety in healthy adults. METHODS: In a randomized, blinded, sham-controlled study, 42 participants (mean age 58.9 years) completed an acute stress task before and after stimulation. The task was an adapted moving-circles paradigm in which circle collisions triggered a brief aversive event (mild electric shock plus unpleasant noise and a white flash). Active stimulation consisted of 20 min of 10-Hz tACS (2.0 mA/channel; 30-s ramp up/down) delivered via electrodes at F3, P3, Cz, and T7 (0° phase at F3/P3; 180° at Cz/T7). Sham stimulation used the same montage and ramp periods but no sustained current. RESULTS: State anxiety showed a significant Time × Protocol interaction (F(1,35) = 4.22, p = .047): STAI-S decreased after active tACS (Δ = -3.16) but increased slightly after sham (Δ = +1.17). Perceived stress appraisal (SAAS) did not change. Resting-state alpha power at F3/P3 showed no reliable pre-post effects. During the task, left-frontal relative alpha differed by protocol and showed a trend toward larger increases following active tACS. Electrodermal and pupil indices changed across sessions in both groups, with no differential stimulation effects. CONCLUSIONS: A single alpha-tACS session produced a modest, selective reduction in stress-evoked state anxiety, supporting oscillatory neuromodulation as a scalable approach to dampen anxiety reactivity.

Humans↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Performance of Photon-counting CT for Assessing Pretreatment Breast Cancer: Comparison with Mammography, MRI, and 18F-FDG PET/CT.

Background Photon-counting CT (PCCT) offers improved spatial resolution, contrast to noise ratio, and dose efficiency, but its clinical utility remains incompletely defined for breast cancer. Purpose To evaluate the feasibility of PCCT for pretreatment breast cancer assessment through comparisons with MRI, full-field digital mammography (FFDM), and fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT. Materials and Methods In this prospective study (March-May 2025), female participants with breast lesions categorized as Breast Imaging Reporting and Data System 4C or higher at US or FFDM underwent breast MRI and multiphasic contrast-enhanced PCCT. 18F-FDG PET/CT was performed in a subset with locally advanced disease. Four radiologists independently evaluated lesion morphologic characteristics, additional findings, and clinical TNM stage. Agreement was analyzed using intraclass correlation coefficients (ICCs) and κ statistics. The diagnostic performance for additional lesions and nodal metastasis was compared with the reference standard (pathologic examination). Results Among 126 participants (mean age, 58.1 years ± 12.3 [SD]), interreader agreement across PCCT, MRI, and FFDM was good to excellent. PCCT agreed with MRI for lesion characterization (κ = 0.57-0.96) and clinical T categorization (κ = 0.86-0.88), with highest agreement with pathologic size (ICC, 0.70-0.81). For 46 pathologically confirmed additional lesions, PCCT was more sensitive than FFDM (difference, 44% [95% CI: 19, 66]) and similar to MRI (difference, 7% [95% CI: -5, 21]). Additionally, 44% (95% CI: 27, 52) of microcalcifications were missed at PCCT versus FFDM. For pathologically confirmed nodal metastasis, PCCT was more sensitive (difference, 10% [95% CI: 1, 20]) and accurate (difference, 6% [95% CI: 1, 11]) than MRI. For clinical N category, PCCT agreed with PET/CT (κ = 0.82 [95% CI: 0.62, 0.96]; n = 19). Two distant metastases identified at PCCT were consistent with 18F-FDG PET/CT and pathologic findings. Conclusion PCCT demonstrated similar performance to MRI for lesion characterization and detection of additional lesions, with better performance for nodal metastasis evaluation; however, detection of microcalcifications was limited. © RSNA, 2026 Supplemental material is available for this article.

Humans↗

PubMed2026

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗