Similarity recognition approach to identify zero-added MSG soy sauce using stable isotopes and amino acid profiles.

Seasonings such as naturally fermented soy sauce without added monosodium glutamate (MSG), are currently a growth market in China. However, fraudulent and mislabeled zero-added MSG soy sauce may cause a risk of excessive MSG intake, increasing food safety issues for consumers. This study investigates stable carbon and nitrogen isotopes and 16 amino acids in typical Chinese in-market soy sauces and uses a similarity method to establish criteria to authenticate MSG addition claims. Results reveal most zero-added MSG soy sauces had lower δ13C values (-25.2 ‰ to -17.7 ‰) and glutamic acid concentrations (8.97 mg mL-1 to 34.76 mg mL-1), and higher δ15N values (-0.27 ‰ +0.95 ‰) and other amino acid concentrations than added-MSG labeled samples. A combined approach, using isotopes, amino acids, similarity coefficients and uncertainty values, was evaluated to rapidly and accurately identify zero-added MSG soy sauces from MSG containing counterparts.

Variant-proof high affinity ACE2 antagonist limits SARS-CoV-2 replication in upper and lower airways.

SARS-CoV-2 has the capacity to evolve mutations that escape vaccine- and infection-acquired immunity and antiviral drugs. A variant-agnostic therapeutic agent that protects against severe disease without putting selective pressure on the virus would thus be a valuable biomedical tool that would maintain its efficacy despite the ongoing emergence of new variants. Here, we challenge male rhesus macaques with SARS-CoV-2 Delta-the most pathogenic variant in a highly susceptible animal model. At the time of challenge, we also treat the macaques with aerosolized RBD-62, a protein developed through multiple rounds of in vitro evolution of SARS-CoV-2 RBD to acquire 1000-fold enhanced ACE2 binding affinity. RBD-62 treatment equivalently suppresses virus replication in both upper and lower airways, a phenomenon not previously observed with clinically approved vaccines. Importantly, RBD-62 does not block the development of virus-specific T- and B-cell responses and does not elicit anti-drug immunity. These data provide proof-of-concept that RBD-62 can prevent severe disease from a highly virulent variant.

Identification of potential drug targets for amyotrophic lateral sclerosis by Mendelian randomization analysis based on brain and plasma proteomics.

Amyotrophic lateral sclerosis as a fatal neurodegenerative disease currently lacks effective therapeutic agents. Thus, finding new therapeutic targets to drive disease treatment is necessary. In this study, we utilized brain and plasma proteins as genetic instruments obtained from genome-wide association studies to conduct a Mendelian randomization analysis to identify potential drug targets for amyotrophic lateral sclerosis. Additionally, we validated our results externally using other datasets. We also used Bayesian co-localization analysis and phenotype scanning. Furthermore, we constructed a protein-protein interaction network to elucidate potential correlations between the identified proteins and existing targets. Mendelian randomization analysis indicated that elevated levels of ANO5 (OR = 1.30; 95 % CI, 1.14-1.49; P = 1.52E-04), SCFD1 (OR = 3.82; 95 % CI, 2.39-6.10; P = 2.19E-08), and SIGLEC9 (OR = 1.05; 95% CI, 1.03-1.07; P = 4.71E-05) are associated with an increased risk of amyotrophic lateral sclerosis, with external validation supporting these findings. Co-localization analysis confirmed that ANO5, SCFD1, and SIGLEC9 (coloc.abf-PPH4 = 0.848, 0.984, and 0.945, respectively) shared the same variant with amyotrophic lateral sclerosis, further substantiating potential role of these proteins as a therapeutic target. There are interactive relationships between the potential proteins and existing targets of amyotrophic lateral sclerosis. Our findings suggested that elevated levels of ANO5, SCFD1, and SIGLEC9 are connected with an increased risk of amyotrophic lateral sclerosis and might be promising therapeutic targets. However, further exploration is necessary to fully understand the underlying mechanisms involved.

Nonlinear causal discovery with confounders.

This article introduces a causal discovery method to learn nonlinear relationships in a directed acyclic graph with correlated Gaussian errors due to confounding. First, we derive model identifiability under the sublinear growth assumption. Then, we propose a novel method, named the Deconfounded Functional Structure Estimation (DeFuSE), consisting of a deconfounding adjustment to remove the confounding effects and a sequential procedure to estimate the causal order of variables. We implement DeFuSE via feedforward neural networks for scalable computation. Moreover, we establish the consistency of DeFuSE under an assumption called the strong causal minimality. In simulations, DeFuSE compares favorably against state-of-the-art competitors that ignore confounding or nonlinearity. Finally, we demonstrate the utility and effectiveness of the proposed approach with an application to gene regulatory network analysis. The Python implementation is available at https://github.com/chunlinli/defuse.

Genetic Algorithm-Based Cooperative Coding and Caching Data Dissemination Scheme in Multi-UAV-Enabled Internet of Vehicles.

Unmanned Aerial Vehicles (UAVs) have emerged as efficient tools in disaster-stricken areas, facilitating efficient data dissemination for post-disaster rescue operations. However, the limited onboard energy of UAVs imposes significant constraints on their operational lifespan, thereby presenting substantial challenges for efficient data dissemination. Therefore, this work investigates a data dissemination scheme to enhance the UAVs' bandwidth efficiency in multi-UAV-enabled Internet of Vehicles, thereby reducing UAVs' energy consumption and improving overall system performance when UAVs hover along designated flight trajectories for data dissemination. Specifically, first, we present a software-defined network-based framework for data dissemination in multi-UAV-enabled IoV. According to this framework, we formulate a problem called C2BS (Coding-based Cooperative Broadcast Scheduling) that focuses on optimizing the UAVs' bandwidth efficiency by leveraging the combined benefits of coding and caching. Furthermore, we demonstrate the NP-hardness of the C2BS problem by employing a polynomial time reduction technique on the simultaneous matrix completion problem. Then, inspired by the benefits offered by genetic algorithms, we propose a novel approach called the Genetic algorithm-based Cooperative Scheduling (GCS) algorithm to address the C2BS problem. This approach encompasses a coding scheme for representing individuals, a fitness function for assessing individuals, operators (i.e., crossover and mutation) for generating offspring, a local search technique to enhance search performance, and a repair operator employed to rectify infeasible solutions. Additionally, we present an analysis of the time complexity for the GCS algorithm. Finally, we present a simulation model to evaluate the performance. Experimental findings provide evidence of the excellence of the proposed scheme.

High dietary Fructose Drives Metabolic Dysfunction-Associated Steatotic Liver Disease via Activating ubiquitin-specific peptidase 2/11ß-hydroxysteroid dehydrogenase type 1 Pathway in Mice.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver-related morbidity and mortality. Though high fructose intake is acknowledged as a metabolic hazard, its role in the etiology of MASLD requires further clarification. Here, we demonstrated that high dietary fructose drives MASLD development and promotes MASLD progression in mice, and identified Usp2 as a fructose-responsive gene in the liver. Elevated USP2 levels were detected in the hepatocytes of MASLD mice; a similar increase was observed following fructose exposure in primary hepatocytes and mouse AML12 cells. Notably, hepatocytes overexpressing USP2 presented with exaggerated lipid accumulation and metabolic inflammation when exposed to fructose. Conversely, USP2 knockdown mitigated these fructose-induced changes. Furthermore, USP2 was found to activate the C/EBPα/11ß-HSD1 signaling, which further impacted the equilibrium of cortisol and cortisone in the circulation of mice. Collectively, our findings revealed the role of dietary fructose in MASLD pathogenesis and identified the USP2-mediated C/EBPα/ 11ß-HSD1 signaling as a potential target for the management of MASLD.

Comparative study of atmospheric brown carbon at Shanghai and the East China Sea: Molecular characterization and optical properties.

The pollution burdens and compositions of atmospheric brown carbon (BrC) that determine their impacts on climate-health-ecosystems have not been well studied, particularly in some mega-economic coastal areas. Herein, atmospheric BrC samples synchronously collected from urban Shanghai (SH) and Huaniao Island (HNI) in the East China Sea during winter were characterized through ultrahigh-performance liquid chromatography-diode array detector-high resolution mass spectrometry (UHPLC-DAD-HRMS). The three polarity-dependent BrC fractions exhibited significant differences in both light absorption and chromophore composition. The average light absorption coefficients of BrC subfractions at 365 nm in SH were 2.6-3.7 times higher than those in HNI. The water-insoluble BrC (WIS-BrC) and humic-likes BrC (HULIS-BrC) dominated the total BrC absorption in SH (45 ± 7 %) and HNI (43 ± 6 %), respectively. Compared with SH, the higher O/Cw, lower molecule conjugation degree, and reduced mass absorption efficiency at 365 nm (MAE365) in HNI imply a potential bleaching mechanism during the transportation oxidation process. Thousands of BrC chromophores were detected at both sites. >20 major chromophores with strong absorption were unambiguously identified in HULIS-BrC and accounted for ∼40 % of the HULIS light absorption at 365 nm at both sites. These chromophores in SH HULIS-BrC featured oxygenated aromatics and nitroaromatics, while alkyl benzenesulfonic acids with emissions from cargo ships were found in HNI HULIS-BrC. Moreover, 22 major chromophores identified in WIS-BrC included alkaloids, polyaromatic hydrocarbons (PAHs), and carbonyl oxygenated PAHs, contributing 39 % and 49 % of the WIS-BrC light absorption at 365 nm in SH and HNI, respectively. Ascertaining the molecular-specific optical properties of BrC chromophores over the mega-economic coastal area is helpful for the predictive understanding of the sources and evolution of BrC, as well as its atmospheric behavior from land to sea.

Soil bacterial community diversity and life strategy during slope restoration on an uninhabited island: changes under the aggregate spray-seeding technique.

AIMS: We investigated the effects of the aggregate spray-seeding (ASS) technique on soil bacterial community diversity, life strategies, and seasonal change. METHODS AND RESULTS: Soil from six plots with original vegetation (CK, n = 6) was compared to soil from 15 plots with spray-seeding restoration (SR, n = 15) using environmental DNA sequencing. The bacterial Shannon and Chao1 indices of SR soils were significantly greater (P < 0.05) than those of CK soils. The Chao1 index for the SR soil bacterial community was significantly greater in summer (P < 0.05) than in winter. The ratio of the relative abundance of bacterial K-strategists to r-strategists (K/r) and the DNA guanine-cytosine (GC) content in the SR soil were significantly lower (P < 0.05) than those in the CK soil. Principal coordinate analysis revealed significant differences between the SR and CK bacterial communities. The GC content was positively correlated with the K/r ratio. Soil conductivity was negatively associated with the K/r ratio and GC content, indicating that ionic nutrients were closely related to bacterial life strategies. CONCLUSIONS: The ASS technique improved soil bacterial diversity, altered community composition, and favored bacterial r-strategists.

Fertilizer Effects on the Nitrogen Isotope Composition of Soil and Different Leaf Locations of Potted Camellia sinensis over a Growing Season.

The nitrogen-stable isotopes of plants can be used to verify the source of fertilizers, but the fertilizer uptake patterns in tea (Camellia sinensis) plants are unclear. In this study, potted tea plants were treated with three types of organic fertilizers (OFs), urea, and a control. The tea leaves were sampled over seven months from the top, middle, and base of the plants and analyzed for the δ15N and nitrogen content, along with the corresponding soil samples. The top tea leaves treated with the rapeseed cake OF had the highest δ15N values (up to 6.6‱), followed by the chicken manure, the cow manure, the control, and the urea fertilizer (6.5‱, 4.1‱, 2.2‱, and 0.6‱, respectively). The soil treated with cow manure had the highest δ15N values (6.0‱), followed by the chicken manure, rapeseed cake, control, and urea fertilizer (4.8‱, 4.0‱, 2.5‱, and 1.9‱, respectively). The tea leaves fertilized with rapeseed cake showed only slight δ15N value changes in autumn but increased significantly in early spring and then decreased in late spring, consistent with the delivery of a slow-release fertilizer. Meanwhile, the δ15N values of the top, middle, and basal leaves from the tea plants treated with the rapeseed cake treatment were consistently higher in early spring and lower in autumn and late spring, respectively. The urea and control samples had lower tea leaf δ15N values than the rapeseed cake-treated tea and showed a generalized decrease in the tea leaf δ15N values over time. The results clarify the temporal nitrogen patterns and isotope compositions of tea leaves treated with different fertilizer types and ensure that the δ15N tea leaf values can be used to authenticate the organic fertilizer methods across different harvest periods and leaf locations. The present results based on a pot experiment require further exploration in open agricultural soils in terms of the various potential fertilizer effects on the different variations of nitrogen isotope ratios in tea plants.

Identification of potential drug targets for insomnia by Mendelian randomization analysis based on plasma proteomics.

Introduction: Insomnia, a common clinical disorder, significantly impacts the physical and mental well-being of patients. Currently, available hypnotic medications are unsatisfactory due to adverse reactions and dependency, necessitating the identification of new drug targets for the treatment of insomnia. Methods: In this study, we utilized 734 plasma proteins as genetic instruments obtained from genome-wide association studies to conduct a Mendelian randomization analysis, with insomnia as the outcome variable, to identify potential drug targets for insomnia. Additionally, we validated our results externally using other datasets. Sensitivity analyses entailed reverse Mendelian randomization analysis, Bayesian co-localization analysis, and phenotype scanning. Furthermore, we constructed a protein-protein interaction network to elucidate potential correlations between the identified proteins and existing targets. Results: Mendelian randomization analysis indicated that elevated levels of TGFBI (OR = 1.01; 95% CI, 1.01-1.02) and PAM ((OR = 1.01; 95% CI, 1.01-1.02) in plasma are associated with an increased risk of insomnia, with external validation supporting these findings. Moreover, there was no evidence of reverse causality for these two proteins. Co-localization analysis confirmed that PAM (coloc.abf-PPH4 = 0.823) shared the same variant with insomnia, further substantiating its potential role as a therapeutic target. There are interactive relationships between the potential proteins and existing targets of insomnia. Conclusion: Overall, our findings suggested that elevated plasma levels of TGFBI and PAM are connected with an increased risk of insomnia and might be promising therapeutic targets, particularly PAM. However, further exploration is necessary to fully understand the underlying mechanisms involved.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study.

BACKGROUND: There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling. METHODS: A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening. RESULTS: At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%. CONCLUSIONS: The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

The prognostic value and immunological role of MVP in pan-cancer study.

Major Vault Protein (MVP) has emerged as a potential prognostic and immunological biomarker in various cancer types. This pan-cancer study aimed to investigate expression of MVP and its correlation with clinical outcomes and immune infiltration across diverse cancer types. We conducted an analysis of extensive transcriptomic and clinical data from publicly available databases. Our findings unveiled a significant association between MVP expression and cancer progression, with higher expression levels predicting poorer overall survival in multiple cancer types. Importantly, MVP expression demonstrated a close relationship with immune infiltration in the tumor microenvironment, showing that higher expression levels were associated with increased immune cell infiltration. We further validated expression of MVP and function in cancer cell lines A549 and AGS. These compelling results suggest that MVP holds promise as a valuable biomarker for prognostic assessment and the development of immunotherapeutic strategies across various cancer types. Consequently, targeting MVP may offer a compelling therapeutic approach in the treatment of human cancers.

Development and internal validation of a clinical prediction model for osteopenia in Chinese middle-aged and elderly men: a prospective cohort study.

BACKGROUND: Early identification of patients at risk of osteopenia is an essential step in reducing the population at risk for fractures. We aimed to develop and validate a prediction model for osteopenia in Chinese middle-aged and elderly men that provides individualized risk estimates. METHODS: In this prospective cohort study, 1109 patients who attend regular physical examinations in the Second Medical Centre of Chinese PLA General Hospital were enrolled from 2015.03 to 2015.09. The baseline risk factors included dietary habits, exercise habits, medical histories and medication records. Osteopenia during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Internal validation was conducted using bootstrapping to correct the optimism. The independent sample T-test analysis, Mann_Whitney U test, Chi-Square Test and multivariable Cox regression analysis were utilized to identify predictive factors for osteopenia in Chinese middle-aged and elderly men. A nomogram based on the seven variables was built for clinical use. Concordance index (C-index), receiver operating characteristic curve (ROC), decision curve analysis (DCA) and calibration curve were used to evaluate the efficiency of the nomogram. RESULTS: The risk factors included in the prediction model were bone mineral density at left femoral neck (LNBMD), hemoglobin (Hb), serum albumin (ALB), postprandial blood glucose (PBG), fatty liver disease (FLD), smoking and tea consumption. The C-index for the risk nomogram was 0.773 in the prediction model, which presented good refinement. The AUC of the risk nomogram at different time points ranged from 0.785 to 0.817, exhibiting good predictive ability and performance. In addition, the DCA showed that the nomogram had a good clinical application value. The nomogram calibration curve indicated that the prediction model was consistent. CONCLUSIONS: Our study provides a novel nomogram and a web calculator that can effectively predict the 7-year incidence risk of osteopenia in Chinese middle-aged and elderly men. It is convenient for clinicians to prevent fragility fractures in the male population.

Endoscopic Cartilage Modified Inlay Technique With Preserving External Auditory Canal Skin for Repairing Posterior Marginal Perforation.

Objective: To evaluate the graft success rate and hearing gain of endoscopic cartilage myringoplasty with preserving external auditory canal (EAC) skin for posterior marginal perforation. Materials and Methods: We performed a prospective study in 36 patients with posterior marginal perforation who underwent endoscopic cartilage modified inlay technique with preserving EAC skin. Patients were followed up for 12 months. Results: All the 36 patients with unilateral posterior marginal perforation were included in this study. Clinical inosculation of the perichondrium graft and remnant tympanic membrane (TM) occurred at 2 to 3 weeks postoperatively. Simultaneously, neovascularization was initiated at the perichondrium graft. The perichondrium graft had been clinically incorporated to the EAC skin at 2 to 3 weeks postoperatively, which could not be distinguished. At 12 months, residual perforation was seen in inferior margin in one but reperforation was not. The graft success rate was 97.2% (35/36). The mean preoperative air bone gap (ABG) was 29.7 ± 3.8 dB, and the mean postoperative ABG at 12 months was 15.2 ± 3.1 dB; the difference between these values was significant (P < .05; paired-samples t test). The successful surgery rate (postoperative ABG ≤ 20 dB) was 91.7% (33/36). No any intratympanic or EAC cholesteatoma was noted during the follow-up period. Conclusions: Endoscopic cartilage modified inlay technique with preserving EAC skin for repairing posterior marginal perforation is simple and minimally invasive technique, which had shorter operative time, similar graft success rate compared with raising a tympanomeatal flap techniques.

Effect of Population Density on Personality of Crayfish (Procambarus clarkii).

Personality is widely observed in animals and has important ecological and evolutionary implications. In addition to being heritable, personality traits are also influenced by the environment. Population density commonly affects animal behavior, but the way in which it shapes animal personality remains largely unknown. In this study, we reared juvenile crayfish at different population densities and measured their personality traits (shyness, exploration, and aggression) after reaching sexual maturity. Our results showed repeatability for each behavior in all treatments, except for the shyness of females at medium density. There was a negative correlation between shyness and exploration in each treatment, and aggression and exploration were positively correlated in medium- and high-density females. These indicate the presence of a behavior syndrome. On average, the crayfish raised at higher population densities were less shy, more exploratory, and more aggressive. We found no behavioral differences between the sexes in crayfish. These results suggested that population density may affect the average values of behavioral traits rather than the occurrence of personality traits. Our study highlights the importance of considering population density as a factor influencing personality traits in animals and, therefore, might help us to understand animal personality development.

The effect of mood on shaping belief and recollection following false feedback.

The current study examined how mood affects the impact of false feedback on belief and recollection. In a three-session experiment, participants first watched 40 neutral mini videos, which were accompanied by music to induce either a positive or negative mood, or no music. Following a recognition test, they received false feedback to reduce belief in the occurrence of the events displayed in some of the videos (Session 2). This was followed by an immediate memory test and a delayed memory assessment one week later (Session 3). The results revealed that participants in negative mood reported higher belief scores compared to those in positive moods, despite an overall decline in belief scores for all groups following the false feedback. Notably, individuals in negative moods exhibited less reduction in their belief scores after encountering challenges, thereby maintaining a higher accuracy in their testimonies. Over time, a reduction in the clarity of participants' memory recall was observed, which correspondingly reduced their testimony accuracy. This study thus indicates that mood states play a role in shaping belief and memory recall under the influence of false feedback.

A novel framework for urban flood risk assessment: Multiple perspectives and causal analysis.

Risk assessment and adaptation have become key focuses in the examination of urban flooding risk. In recent decades, global climate change has resulted in a high incidence of extreme weather events, notably flooding. This study introduces a spatial multi-indicator model developed for assessing flood risk at the urban agglomeration scale. A crucial addition to the model is the incorporation of an adaptive capacity within the IPCC risk framework. The model systematically considers various flood risk indicators related to the economic, social, and geographic environments of the central and southern Liaoning urban agglomeration (CSLN). It generates a spatial distribution map of integrated flood risk for multiple scenario combinations. Furthermore, the intricate relationship between different risk indicators and flood risk was analyzed using correlation analysis and the Light Gradient Boosting Machine model (Light GBM). The findings reveal notable variations in flood risk under different scenarios. The inclusion of vulnerability indicators increased flood risk by 33 %, while the subsequent inclusion of adaptive indicators decreased flood risk by 45 %. Dense populations and assets contribute to high flood risk, while adaptive capacity significantly mitigates urban flood risk. The framework adopted in this paper can be applied to other areas where urban agglomeration-scale flood risk assessment is needed, and can contribute to advancing scientific research on flood forecasting and mitigation.

Enhanced Light Absorption and Elevated Viscosity of Atmospheric Brown Carbon through Evaporation of Volatile Components.

Samples of brown carbon (BrC) material were collected from smoke emissions originating from wood pyrolysis experiments, serving as a proxy for BrC representative of biomass burning emissions. The acquired samples, referred to as "pyrolysis oil (PO1)," underwent subsequent processing by thermal evaporation of their volatile compounds, resulting in a set of three additional samples with volume reduction factors of 1.33, 2, and 3, denoted as PO1.33, PO2, and PO3. The chemical compositions of these POx samples and their BrC chromophore features were analyzed using a high-performance liquid chromatography instrument coupled with a photodiode array detector and a high-resolution mass spectrometer. The investigation revealed a noteworthy twofold enhancement of BrC light absorption observed for the progression of PO1 to PO3 samples, assessed across the spectral range of 300-500 nm. Concurrently, a decrease in the absorption Ångstrom exponent (AAE) from 11 to 7 was observed, indicating a weaker spectral dependence. The relative enhancement of BrC absorption at longer wavelengths was more significant, as exemplified by the increased mass absorption coefficient (MAC) measured at 405 nm from 0.1 to 0.5 m2/g. Molecular characterization further supports this darkening trend, manifesting as a depletion of small oxygenated, less absorbing monoaromatic compounds and the retention of relatively large, less polar, more absorbing constituents. Noteworthy alterations of the PO1 to PO3 mixtures included a reduction in the saturation vapor pressure of their components and an increase in viscosity. These changes were quantified by the mean values shifting from approximately 1.8 × 103 µg/m3 to 2.3 µg/m3 and from ∼103 Pa·s to ∼106 Pa·s, respectively. These results provide quantitative insights into the extent of BrC aerosol darkening during atmospheric aging through nonreactive evaporation. This new understanding will inform the refinement of atmospheric and chemical transport models.