Gibberellin signaling modulates flowering via the DELLA-BRAHMA-NF-YC module in Arabidopsis.

Gibberellin (GA) plays a key role in floral induction by activating the expression of floral integrator genes in plants, but the epigenetic regulatory mechanisms underlying this process remain unclear. Here, we show that BRAHMA (BRM), a core subunit of the chromatin-remodeling SWItch/sucrose nonfermentable (SWI/SNF) complex that functions in various biological processes by regulating gene expression, is involved in GA-signaling-mediated flowering via the formation of the DELLA-BRM-NF-YC module in Arabidopsis (Arabidopsis thaliana). DELLA, BRM, and NF-YC transcription factors interact with one another, and DELLA proteins promote the physical interaction between BRM and NF-YC proteins. This impairs the binding of NF-YCs to SOC1, a major floral integrator gene, to inhibit flowering. On the other hand, DELLA proteins also facilitate the binding of BRM to SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1). The GA-induced degradation of DELLA proteins disturbs the DELLA-BRM-NF-YC module, prevents BRM from inhibiting NF-YCs, and decreases the DNA-binding ability of BRM, which promote the deposition of H3K4me3 on SOC1 chromatin, leading to early flowering. Collectively, our findings show that BRM is a key epigenetic partner of DELLA proteins during the floral transition. Moreover, they provide molecular insights into how GA signaling coordinates an epigenetic factor with a transcription factor to regulate the expression of a flowering gene and flowering in plants.

Primary cilia in satellite cells are the mechanical sensors for muscle hypertrophy.

Skeletal muscle atrophy is commonly associated with aging, immobilization, muscle unloading, and congenital myopathies. Generation of mature muscle cells from skeletal muscle satellite cells (SCs) is pivotal in repairing muscle tissue. Exercise therapy promotes muscle hypertrophy and strength. Primary cilium is implicated as the mechanical sensor in some mammalian cells, but its role in skeletal muscle cells remains vague. To determine mechanical sensors for exercise-induced muscle hypertrophy, we established three SC-specific cilium dysfunctional mouse models-Myogenic factor 5 (Myf5)-Arf-like Protein 3 (Arl3)-/-, Paired box protein Pax-7 (Pax7)-Intraflagellar transport protein 88 homolog (Ift88)-/-, and Pax7-Arl3-/--by specifically deleting a ciliary protein ARL3 in MYF5-expressing SCs, or IFT88 in PAX7-expressing SCs, or ARL3 in PAX7-expressing SCs, respectively. We show that the Myf5-Arl3-/- mice develop grossly the same as WT mice. Intriguingly, mechanical stimulation-induced muscle hypertrophy or myoblast differentiation is abrogated in Myf5-Arl3-/- and Pax7-Arl3-/- mice or primary isolated Myf5-Arl3-/- and Pax7-Ift88-/- myoblasts, likely due to defective cilia-mediated Hedgehog (Hh) signaling. Collectively, we demonstrate SC cilia serve as mechanical sensors and promote exercise-induced muscle hypertrophy via Hh signaling pathway.

A premium for positive social interest and attractive voices in the acceptability of unfair offers? An ERP study.

Although the attractiveness of voices plays an important role in social interactions, it is unclear how voice attractiveness and social interest influence social decision-making. Here, we combined the ultimatum game with recording event-related brain potentials (ERPs) and examined the effect of attractive versus unattractive voices of the proposers, expressing positive versus negative social interest ("I like you" vs. "I don't like you"), on the acceptance of the proposal. Overall, fair offers were accepted at significantly higher rates than unfair offers, and high voice attractiveness increased acceptance rates for all proposals. In ERPs in response to the voices, their attractiveness and expressed social interests yielded early additive effects in the N1 component, followed by interactions in the subsequent P2, P3 and N400 components. More importantly, unfair offers elicited a larger Medial Frontal Negativity (MFN) than fair offers but only when the proposer's voice was unattractive or when the voice carried positive social interest. These results suggest that both voice attractiveness and social interest moderate social decision-making and there is a similar "beauty premium" for voices as for faces.

Harnessing Biomimicry for Controlled Adhesion on Material Surfaces.

Nature serves as an abundant wellspring of inspiration for crafting innovative adhesive materials. Extensive research is conducted on various complex forms of biological attachment, such as geckos, tree frogs, octopuses, and mussels. However, significant obstacles still exist in developing adhesive materials that truly replicate the behaviors and functionalities observed in living organisms. Here, an overview of biological organs, structures, and adhesive secretions endowed with adhesion capabilities, delving into the intricate relationship between their morphology and function, and potential for biomimicry are provided. First, the design principles and mechanisms of adhesion behavior and individual organ morphology in nature are summarized from the perspective of structural and size constraints. Subsequently, the value of engineered and bioinspired adhesive materials through selective application cases in practical fields is emphasized. Then, a forward-looking gaze on the conceivable challenges and associated opportunities in harnessing biomimetic strategies and biological materials for advancing adhesive material innovation is highlighted and cast.

High-Sensitivity Photoelectrochemical Ultraviolet Photodetector with Stable pH-Universal Adaptability Based on Whole Single-Crystal Integrated Self-Supporting 4H-SiC Nanoarrays.

Emerging photoelectrochemical (PEC) photodetectors (PDs) have notable advantages over conventional PDs and have attracted extensive attention. However, harsh liquid environments, such as those with high corrosivity and attenuation, substantially restrict their widespread application. Moreover, most PEC PDs are constructed by assembling numerous nanostructures on current collector substrates, which inevitably contain abundant interfaces and defects, thus greatly weakening the properties of PDs. To address these challenges, a high-performance pH-universal PEC ultraviolet (UV) PD based on a whole single-crystal integrated self-supporting 4H-SiC nanopore array photoelectrode is constructed, which is fabricated using a two-step anodic oxidation approach. The PD exhibits excellent photodetection behavior, with high responsivity (218.77 mA W-1), detectivity (6.64 × 1013 Jones), external quantum efficiency (72.47%), and rapid rise/decay times (17/48 ms) under 375 nm light illumination with a low intensity of 0.15 mW cm-2 and a bias voltage of 0.6 V, which is fall in the state-of-the-art of the wide-bandgap semiconductor-based PDs reported thus far. Furthermore, the SiC PEC PD exhibits excellent photoresponse and long-term operational stability in pH-universal liquid environments. The improved photodetection performance of the SiC PEC PD is primarily attributed to the synergistic effect of the nanopore array structure, integrated self-supporting configuration, and single-crystal structure of the whole photoelectrode.

HPTRMF: Collaborative Matrix Factorization-Based Prediction Method for LncRNA-Disease Associations Using High-Order Perturbation and Flexible Trifactor Regularization.

Existing matrix factorization methods face challenges, including the cold start problem and global nonlinear data loss during similarity learning, particularly in predicting associations between long noncoding RNAs (LncRNAs) and diseases. To overcome these issues, we introduce HPTRMF, a matrix factorization approach incorporating high-order perturbation and flexible trifactor regularization. HPTRMF constructs a high-order correlation matrix utilizing the known association matrix, leveraging high-order perturbation to effectively address the cold start problem caused by data sparsity. Additionally, HPTRMF incorporates a flexible trifactor regularization term to capture similarity information on LncRNAs and diseases, enabling the effective handling of global nonlinear data loss by capturing such data in the similarity matrix. Experimental results demonstrate the superiority of HPTRMF over nine state-of-the-art algorithms in Leave-One-Out Cross-Validation (LOOCV) and Five-Fold Cross-Validation (5-Fold CV) on three data sets.HPTRMF and data sets are available in https://github.com/Llvvvv/HPTRMF.

Quantification and Characterization of Fine Plastic Particles as Considerable Components in Atmospheric Fine Particles.

The negative effects of air pollution, especially fine particulate matter (PM2.5, particles with an aerodynamic diameter of ≤2.5 µm), on human health, climate, and ecosystems are causing significant concern. Nevertheless, little is known about the contributions of emerging pollutants such as plastic particles to PM2.5 due to the lack of continuous measurements and characterization methods for atmospheric plastic particles. Here, we investigated the levels of fine plastic particles (FPPs) in PM2.5 collected in urban Shanghai at a 2 h resolution by using a novel versatile aerosol concentration enrichment system that concentrates ambient aerosols up to 10-fold. The FPPs were analyzed offline using the combination of spectroscopic and microscopic techniques that distinguished FPPs from other carbon-containing particles. The average FPP concentrations of 5.6 µg/m3 were observed, and the ratio of FPPs to PM2.5 was 13.2% in this study. The FPP sources were closely related to anthropogenic activities, which pose a potential threat to ecosystems and human health. Given the dramatic increase in plastic production over the past 70 years, this study calls for better quantification and control of FPP pollution in the atmosphere.

Music training affects listeners' processing of different types of accentuation information: Evidence from ERPs.

Previous studies found that prolonged musical training can promote language processing, but few studies have examined whether and how musical training affects the processing of accentuation in spoken language. In this study, a vocabulary detection task was conducted, with Chinese single sentences as materials, to investigate how musicians and non-musicians process corrective accent and information accent in the sentence-middle and sentence-final positions. In the sentence-middle position, results of the cluster-based permutation t-tests showed significant differences in the 574-714 ms time window for the control group. In the sentence-final position, the cluster-based permutation t-tests revealed significant differences in the 612-810 ms time window for the music group and in the 616-812 ms time window for the control group. These significant positive effects were induced by the processing of information accent relative to that of corrective accent. These results suggest that both groups were able to distinguish corrective accent from information accent, but they processed the two accent types differently in the sentence-middle position. These findings show that musical training has a cross-domain effect on spoken language processing and that the accent position also affects its processing.

Evaluation of pelvic structural abnormalities in primiparous women with stress urinary incontinence.

INTRODUCTION AND HYPOTHESIS: The objective was to evaluate the morphological characteristics of pelvic floor structure specific to de novo stress urinary incontinence (SUI) in primiparous women using three-dimensional (3D) reconstruction fusion technology based on static MRI combined with dynamic MRI. METHODS: Eighty-one primiparous women after the first vaginal delivery were studied, 40 with SUI and 41 without SUI. 3D reconstruction models based on static MRI were used to describe the anatomical abnormalities of pelvic floor tissues. Dynamic MRI was used to describe segmental activities of the urethra and vagina. The relationship between the morphometry and postpartum SUI was evaluated by logistic regression analysis and receiver operator characteristic curve. RESULTS: The differences in the distance from the bladder neck to the pubic symphysis (BSD), the angle between the posterior wall of the urethra and the anterior wall of the vagina, the width of the distal region of the vagina, urethral length, urethral compression muscle volume (CUV), and pubovisceral muscle volume, puborectal muscle volume, were measured, and except for the extremity of the anterior urethral wall, the total displacements (TDs) of the other sites between the two groups were statistically significant (p < 0.05). Logistic regression analysis showed that the BSD decreased, the CUV decreased, the TDs of the first site and the eighth site increment correlated significantly with postpartum SUI occurrence (p < 0.05). CONCLUSIONS: 3D reconstruction fusion technology provides an important support for a precise assessment of the pelvic floor dysfunction. The BSD, CUV, and iliococcygeus muscle volume have certain values in predicting de novo SUI after first vaginal birth.

Application of computer vision and deep learning models to automatically classify medically important mosquitoes in North Borneo, Malaysia.

Mosquito-borne diseases have emerged in North Borneo in Malaysia due to rapid changes in the forest landscape, and mosquito surveillance is key to understanding disease transmission. However, surveillance programmes involving sampling and taxonomic identification require well-trained personnel, are time-consuming and labour-intensive. In this study, we aim to use a deep leaning model (DL) to develop an application capable of automatically detecting mosquito vectors collected from urban and suburban areas in North Borneo, Malaysia. Specifically, a DL model called MobileNetV2 was developed using a total of 4880 images of Aedes aegypti, Aedes albopictus and Culex quinquefasciatus mosquitoes, which are widely distributed in Malaysia. More importantly, the model was deployed as an application that can be used in the field. The model was fine-tuned with hyperparameters of learning rate 0.0001, 0.0005, 0.001, 0.01 and the performance of the model was tested for accuracy, precision, recall and F1 score. Inference time was also considered during development to assess the feasibility of the model as an app in the real world. The model showed an accuracy of at least 97%, a precision of 96% and a recall of 97% on the test set. When used as an app in the field to detect mosquitoes with the elements of different background environments, the model was able to achieve an accuracy of 76% with an inference time of 47.33 ms. Our result demonstrates the practicality of computer vision and DL in the real world of vector and pest surveillance programmes. In the future, more image data and robust DL architecture can be explored to improve the prediction result.

High energy density and extremely stable supercapacitors based on carbon aerogels with 100% capacitance retention up to 65,000 cycles.

In terms of ideal future energy storage systems, besides the always-pursued energy/power characteristics, long-term stability is crucial for their practical application. Here, we report a facile and sustainable strategy for the scalable fabrication of carbon aerogels with three-dimensional interconnected nanofiber networks and rationally designed hierarchical porous structures, which are based on the carbonization of bacterial cellulose assisted by the soft template of Zn-1,3,5-benzenetricarboxylic acid. As binder-free electrodes, they deliver a fundamentally enhanced specific capacitance of 352 F ⋅ g-1 at 1 A ⋅ g-1 in a wide potential window (1.2 V, 6 M KOH) in comparison with those of bacterial cellulose-derived carbons (178 F ⋅ g-1) and most activated carbons (usually lower than 250 F ⋅ g-1). The as-assembled supercapacitors exhibit an ultrahigh capacitance of 297 F ⋅ g-1 at 1 A ⋅ g-1, remarkable energy density (14.83 Wh ⋅ kg-1 at 0.60 kW ⋅ kg-1), and extremely high stability, with 100% capacitance retention for up to 65,000 cycles at 6 A ⋅ g-1, representing their superior energy storage performance when compared with that of state-of-the-art supercapacitors of commercial activated carbons and biomass-derived analogs.

Aqueous production of secondary organic aerosol from fossil-fuel emissions in winter Beijing haze.

Secondary organic aerosol (SOA) produced by atmospheric oxidation of primary emitted precursors is a major contributor to fine particulate matter (PM2.5) air pollution worldwide. Observations during winter haze pollution episodes in urban China show that most of this SOA originates from fossil-fuel combustion but the chemical mechanisms involved are unclear. Here we report field observations in a Beijing winter haze event that reveal fast aqueous-phase conversion of fossil-fuel primary organic aerosol (POA) to SOA at high relative humidity. Analyses of aerosol mass spectra and elemental ratios indicate that ring-breaking oxidation of POA aromatic species, leading to functionalization as carbonyls and carboxylic acids, may serve as the dominant mechanism for this SOA formation. A POA origin for SOA could explain why SOA has been decreasing over the 2013-2018 period in response to POA emission controls even as emissions of volatile organic compounds (VOCs) have remained flat.

Musical training alters neural processing of tones and vowels in classic Chinese poems.

Long-term rigorous musical training promotes various aspects of spoken language processing. However, it is unclear whether musical training provides an advantage in recognizing segmental and suprasegmental information of spoken language. We used vowel and tone violations in spoken unfamiliar seven-character quatrains and a rhyming judgment task to investigate the effects of musical training on tone and vowel processing by recording ERPs. Compared with non-musicians, musicians were more accurate and responded faster to incorrect than correct tones. Musicians showed larger P2 components in their ERPs than non-musicians during both tone and vowel processing, revealing increased focused attention on sounds. Both groups showed enhanced N400 and LPC for incorrect vowels (vs. correct vowels) but non-musicians showed an additional P2 effect for vowel violations. Moreover, both groups showed enhanced LPC for incorrect tones (vs. correct tones) but only non-musicians showed an additional N400 effect for tone violations. These results indicate that vowel/tone processing is less effortful for musicians (vs. non-musicians). Our study suggests that long-term musical training facilitates speech tone and vowel processing in a tonal language environment by increasing the attentional focus on speech and reducing demands for detecting incorrect vowels and integration costs for tone changes.

Characterization of the complete mitochondrial genome of Cryptotermes domesticus (Blattodea: Kalotermitidae): Genome description and phylogenetic implications.

The complete mitochondrial genome of Cryptotermes domesticus (Haviland) was sequenced and annotated to study its characteristics and the phylogenetic relationship of C. domesticus to other termite species. The mitogenome of C. domesticus is a circular, close, and double-stranded molecule with a length of 15,655 bp. The sequenced mitogenome contains 37 typical genes, which are highly conserved in gene size, organization, and codon usage. Transfer RNA genes (tRNAs) also have typical secondary structures. All of the 13 protein-coding genes (PCGs) start with an ATN codon, except for nad4, which starts with GTG and terminates with the terminal codon TAA and TAG or the incomplete form T-- (cox2 and nad5). Most tRNAs have a typical cloverleaf structure, except for trnS1, in which this form is replaced by a simple loop and lacks the dihydrouridine (DHU) arm. The nucleotide diversity (Pi) and nonsynonymous (Ka)/synonymous (Ks) mutation rate ratios indicate that nad1, cox1, and cox3 are the most conserved genes, and that cox1 has the lowest rate of evolution. In addition, an 89 bp repeated sequence was found in the A + T-rich region. Phylogenetic analysis was performed using Bayesian inference (BI) and maximum likelihood (ML) methods based on 13 PCGs, and the monophyly of Kalotermitidae was supported.

Low Bandgap 2D Perovskite Single Crystal with Anomalous-large Charges/ions Collection Ratio for Ultra-sensitive and Stable X-ray Detectors.

The low-dimensional halide perovskites have attracted increasing attention due to their improved moisture stability, reduced defects, and suppressed ions migration in many optoelectronic devices such as solar cells, light-emitting diodes, X-ray detectors, and so on. However, they are still limited by their large band gap and short charge carriers' diffusion length. Here, we demonstrate that the introduction of metal ions into organic interlayers of two-dimensional (2D) perovskite by cross-linking the copper paddle-wheel cluster-based lead bromide ([Cu(O2 C-(CH2 )3 -NH3 )2 ]PbBr4 ) perovskite single crystals with coordination bonds can not only significantly reduce the perovskite band gap to 0.96 eV to boost the X-ray induced charge carriers, but can also selectively improve the charge carriers' transport along the out-of-plane direction and blocking the ions motion paths. The [Cu(O2 C-(CH2 )3 -NH3 )2 ]PbBr4 single-crystal device can reach a record charges/ions collection ratio of 1.69×1018 ±4.7 % µGyair -1 s, and exhibit a large sensitivity of 1.14×105 ±7% µC Gyair -1 cm-2 with the lowest detectable dose rate of 56 nGyair s-1 under 120 keV X-rays irradiation. In addition, [Cu(O2 C-(CH2 )3 -NH3 )2 ]PbBr4 single-crystal detector exposed to the air without any encapsulation shows excellent X-ray imaging capability with long-term operational stability without any attenuation of 120 days.

Perovskite Dimensional Evolution Through Cations Engineering to Tailor the Detection Limit in Hard X-ray Response.

Halide perovskites with various compositions are potential candidates in low-dosage X-ray detection due to their large sensitivity and tunable optoelectronic properties. Here, cations engineering induced dimensional evolution of halide perovskites between 0D, 2D, and 3D is reported. Centimeter-sized 2D lead-free perovskite single-crystal of 4-fluorophenethylammonium antimony iodide (FPEA3 SbI6 ) is synthesized. In contrast to the 0D phenethylammonium antimony iodide (PEA3 Sb2 I9 ), face-shared [Sb2 I9 ]3- of the bi-octahedral structure of PEA3 Sb2 I9 is split into corner-shared [SbI6 ]3- by intermolecular interactions and steric hindrance of FPEA+ ions in 2D FPEA3 SbI6 . Two Sb3+ ions share three octahedral [SbI6 ]3- , leaving one-third of Sb3+ vacancies in the framework of FPEA3 SbI6 . Furthermore, Sn2+ ions can be filled into the vacancies to form continuous 2D frameworks to tune the anisotropic conductivity and device sensitivity to hard X-rays. The dimensional evolution of perovskite single-crystals from 3D to 2D or 0D to 2D maximizes the signal/noise ratio to facilize the adjustability of detection limit in hard X-ray detection, which is determined by both device sensitivity and device noise current. A record low detection limit coefficient of 0.65 is achieved in the 2D FPEA3 SbSn0.5 I7 single-crystal sample, which results from selective charges collection over mobile ions/noise current in the 2D perovskite structure.

Vicariance and dispersal events inferred from mitochondrial genomes and nuclear genes (18S, 28S) shaped global Cryptocercus distributions.

Cryptocercus Scudder, a genus of wingless, subsocial cockroaches, has low vagility but exhibits a disjunct distribution in eastern and western North America, and in China, South Korea and the Russian Far East. This distribution provides an ideal model for testing hypotheses of vicariance through plate tectonics or other natural barriers versus dispersal across oceans or other natural barriers. We sequenced 45 samples of Cryptocercus to resolve phylogenetic relationships among members of the genus worldwide. We identified four types of tRNA rearrangements among samples from the Qin-Daba Mountains. Our maximum-likelihood and Bayesian phylogenetic trees, based on mitochondrial genomes and nuclear genes (18S, 28S), strongly supported six major lineages of Cryptocercus, which displayed a clear geographical distribution pattern. We used Bayesian molecular dating to estimate the evolutionary timescale of the genus, and reconstructed Cryptocercus ancestral ranges using statistical dispersal-vicariance analysis (S-DIVA) in RASP. Two dispersal events and six vicariance events for Cryptocercus were inferred with high support. The initial vicariance event occurred between American and Asian lineages at 80.5 Ma (95% credibility interval: 60.0-104.7 Ma), followed by one vicariance event within the American lineage 43.8 Ma (95% CI: 32.0-57.5 Ma), and two dispersal 31.9 Ma (95% CI: 25.8-39.5 Ma), 21.7 Ma (95% CI: 17.3-27.1 Ma) plus four vicariance events c. 29.3 Ma, 27.2 Ma, 24.8 Ma and 16.7 Ma within the Asian lineage. Our analyses provide evidence that both vicariance and dispersal have played important roles in shaping the distribution and diversity of these woodroaches.

Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning.

Atmospheric aerosols are important drivers of Arctic climate change through aerosol-cloud-climate interactions. However, large uncertainties remain on the sources and processes controlling particle numbers in both fine and coarse modes. Here, we applied a receptor model and an explainable machine learning technique to understand the sources and drivers of particle numbers from 10 nm to 20 µm in Svalbard. Nucleation, biogenic, secondary, anthropogenic, mineral dust, sea salt and blowing snow aerosols and their major environmental drivers were identified. Our results show that the monthly variations in particles are highly size/source dependent and regulated by meteorology. Secondary and nucleation aerosols are the largest contributors to potential cloud condensation nuclei (CCN, particle number with a diameter larger than 40 nm as a proxy) in the Arctic. Nonlinear responses to temperature were found for biogenic, local dust particles and potential CCN, highlighting the importance of melting sea ice and snow. These results indicate that the aerosol factors will respond to rapid Arctic warming differently and in a nonlinear fashion.

Connecting the Light Absorption of Atmospheric Organic Aerosols with Oxidation State and Polarity.

The light-absorbing organic aerosol (OA) constitutes an important fraction of absorbing components, counteracting major cooling effect of aerosols to climate. The mechanisms in linking the complex and changeable chemistry of OA with its absorbing properties remain to be elucidated. Here, by using solvent extraction, ambient OA from an urban environment was fractionated according to polarity, which was further nebulized and online characterized with compositions and absorbing properties. Water extracted high-polar compounds with a significantly higher oxygen to carbon ratio (O/C) than methanol extracts. A transition O/C of about 0.6 was found, below and above which the enhancement and reduction of OA absorptivity were observed with increasing O/C, occurring on the less polar and high polar compounds, respectively. In particular, the co-increase of nitrogen and oxygen elements suggests the important role of nitrogen-containing functional groups in enhancing the absorptivity of the less polar compounds (e.g., forming nitrogen-containing aromatics), while further oxidation (O/C > 0.6) on high-polar compounds likely led to fragmentation and bleaching chromophores. The results here may reconcile the previous observations about darkening or whitening chromophores of brown carbon, and the parametrization of O/C has the potential to link the changing chemistry of OA with its polarity and absorbing properties.

Contrasting resistance of polycyclic aromatic hydrocarbons to atmospheric oxidation influenced by burning conditions.

The oxidation of polycyclic aromatic hydrocarbons (PAHs) determines their lifetime, toxicity and consequent environmental and climate impacts. The residential solid fuel burning composes of a substantial fraction of PAH emissions; however, their oxidation rate is yet to be explicitly understood, which is complicated by the contrasting emission factors under different combustion conditions and their subsequent evolution in the atmosphere. Here we used a plume evolution chamber using ambient oxidants to simulate the evolution of residential solid fuel burning emissions under real-world solar radiation, and then to investigate the oxidation process of the emitted PAHs. Contrasting oxidation rate of PAHs was found to be influenced by particles with or without presence of substantial amount of black carbon (BC). In the flaming burning phase, which contained 46% of BC mass fraction and 8% of organic aerosol (OA) internally mixed with BC, the larger PAHs (with 4-7 rings) was rapidly oxidized 12% for every hour of evolution under solar radiation; however, the larger PAHs from smoldering phase tended to maintain unmodified during the evolution, when 95% of OA was externally mixed with only minor fraction of BC (<5%). This may be ascribed to the complex morphology of BC, allowing more exposure for the internally-mixed OA to the oxidants; in contrast with those externally-mixed OA which was prone to be coated by condensed secondary substances. This raises an important consideration about the particle mixing state in influencing the oxidation of PAHs, particularly the coating on PAHs which may extend their lifetime and environmental impacts.