Ultrafast Optomechanical Strain in Layered GeS.

Strong coupling between light and mechanical strain forms the foundation for next-generation optical micro- and nano-electromechanical systems. Such optomechanical responses in two-dimensional materials present novel types of functionalities arising from the weak van der Waals bond between atomic layers. Here, by using structure-sensitive megaelectronvolt ultrafast electron diffraction, we report the experimental observation of optically driven ultrafast in-plane strain in the layered group IV monochalcogenide germanium sulfide (GeS). Surprisingly, the photoinduced structural deformation exhibits strain amplitudes of order 0.1% with a 10 ps fast response time and a significant in-plane anisotropy between zigzag and armchair crystallographic directions. Rather than arising due to heating, experimental and theoretical investigations suggest deformation potentials caused by electronic density redistribution and converse piezoelectric effects generated by photoinduced electric fields are the dominant contributors to the observed dynamic anisotropic strains. Our observations define new avenues for ultrafast optomechanical control and strain engineering within functional devices.

Evaluating the efficacy of recombinant human growth factors in scar remodelling for patients with facial soft tissue injuries.

Facial soft tissue injuries, often resulting in scarring, pose a challenge in reconstructive and aesthetic surgery due to the need for functional and aesthetic restoration. This study evaluates the efficacy of recombinant human growth factors (rhGFs) in scar remodelling for such injuries. A retrospective evaluation was conducted from January 2020 to January 2023, involving 100 patients with facial soft tissue injuries. Participants were divided equally into a control group, receiving standard cosmetic surgical repair, and an observation group, treated with rhGFs supplemented cosmetic surgery. The study assessed scar characteristics (pigmentation, pliability, vascularity, height), hospital stay duration, tissue healing time, complication rates and patient satisfaction. The observation group demonstrated significant improvements in all scar characteristics, with notably better pigmentation, pliability, vascularity and height compared with the control group. The rhGF treatment also resulted in reduced hospital stay duration and faster tissue healing. Notably, the total complication rate was significantly lower in the observation group (10%) compared with the control group (34%). Additionally, patient satisfaction levels were higher in the observation group, with 98% combined satisfaction compared with 76% in the control group. The application of rhGFs in treating facial soft tissue injuries significantly enhances scar remodelling, expedites healing, reduces complications and improves patient satisfaction. These findings establish rhGFs as a valuable tool in the management of facial soft tissue injuries, highlighting their potential in improving both functional and aesthetic outcomes.

Organic Matter Decomposition in River Ecosystems: Microbial Interactions Influenced by Total Nitrogen and Temperature in River Water.

Microbes contribute to the organic matter decomposition (OMD) in river ecosystems. This study considers two aspects of OMD in river ecosystems which have not been examined in scientific studies previously, and these are the microbial interactions in OMD and the influence of environmental factors on microbial interactions. Cotton strip (CS), as a substitute for organic matter, was introduced to Luanhe River Basin in China. The results of CS assay, microbial sequencing, and redundancy analysis (RDA) showed that CS selectively enriched bacterial and fungal groups related to cellulose decomposition, achieving cotton strip decomposition (CSD). Bacterial phylum Proteobacteria and fungal phyla Rozellomycota and Ascomycota were the dominant groups associated with CSD. Network analysis and Mantel test results indicated that bacteria and fungi on CS cooperatively formed an interaction network to achieve the CSD. In the network, modules 2 and 4 were significantly positively associated with CSD, which were considered as the key modules in this study. The key modules were mainly composed of phyla Proteobacteria and Ascomycota, indicating that microbes in key modules were the effective decomposers of CS. Although keystone taxa were not directly associated with CSD, they may regulate the genera in key modules to achieve the CSD, since some keystone taxa were linked with the microbial genera associated with CSD in the key modules. Total nitrogen (TN) and temperature in water were the dominant environmental factors positively influenced CSD. The key modules 2 and 4 were positively influenced by water temperature and TN in water, respectively, and two keystone taxa were positively associated with TN. This profoundly revealed that water temperature and TN influenced the OMD through acting on the keystone taxa and key modules in microbial interactions. The research findings help us to understand the microbial interactions influenced by environmental factors in OMD in river ecosystems.

Transport of Microplastic and Dispersed Oil Co-contaminants in the Marine Environment.

Microplastics (MPs) and oil pollution are major concerns in oceans. Although their coexistence in oceans and the associated MP-oil-dispersant agglomerates (MODAs) have been reported, limited attention is given to the behavior of the co-contaminants. This study investigated MODA transport in a simulated ocean system and explored related mechanisms under various oil types, salinities, and mineral concentrations. We found that more than 90% of the heavy oil-formed MODAs stayed at the seawater surface, while the light oil-formed MODAs were widely distributed throughout the seawater column. The increased salinity promoted MODAs formed by 7 and 90 µm MPs to transport from the seawater surface to the column. This was elucidated by the Derjaguin-Landau-Verwey-Overbeek theory as more MODAs formed under higher salinities and dispersants kept them stable in the seawater column. Minerals facilitated the sinking of large MP-formed MODAs (e.g., 40 µm) as minerals were adsorbed on the MODA surface, but their impact on small MP-formed MODAs (e.g., 7 µm) was negligible. A MODA-mineral system was proposed to explain their interaction. Rubey's equation was recommended to predict the sinking velocity of MODAs. This study is the first attempt to reveal MODA transport. Findings will contribute to the model development to facilitate their environmental risk evaluation in oceans.

N-glycosylation shields Phytophthora sojae apoplastic effector PsXEG1 from a specific host aspartic protease.

Hosts and pathogens are engaged in a continuous evolutionary struggle for physiological dominance. A major site of this struggle is the apoplast. In Phytophthora sojae-soybean interactions, PsXEG1, a pathogen-secreted apoplastic endoglucanase, is a key focal point of this struggle, and the subject of two layers of host defense and pathogen counterdefense. Here, we show that N-glycosylation of PsXEG1 represents an additional layer of this coevolutionary struggle, protecting PsXEG1 against a host apoplastic aspartic protease, GmAP5, that specifically targets PsXEG1. This posttranslational modification also attenuated binding by the previously described host inhibitor, GmGIP1. N-glycosylation of PsXEG1 at N174 and N190 inhibited binding and degradation by GmAP5 and was essential for PsXEG1's full virulence contribution, except in GmAP5-silenced soybeans. Silencing of GmAP5 reduced soybean resistance against WT P. sojae but not against PsXEG1 deletion strains of P. sojae. The crucial role of N-glycosylation within the three layers of defense and counterdefense centered on PsXEG1 highlight the critical importance of this conserved apoplastic effector and its posttranslational modification in Phytophthora-host coevolutionary conflict.

Importing Antibonding-Orbital Occupancy through Pd-O-Gd Bridge Promotes Electrocatalytic Oxygen Reduction.

The active-site density, intrinsic activity, and durability of Pd-based materials for oxygen reduction reaction (ORR) are critical to their application in industrial energy devices. This work constructs a series of carbon-based rare-earth (RE) oxides (Gd2 O3 , Sm2 O3 , Eu2 O3 , and CeO2 ) by using RE metal-organic frameworks to tune the ORR performance of the Pd sites through the Pd-REx Oy interface interaction. Taking Pd-Gd2 O3 /C as a representative, it is identified that the strong coupling between Pd and Gd2 O3 induces the formation of the Pd-O-Gd bridge, which triggers charge redistribution of Pd and Gd2 O3 . The screened Pd-Gd2 O3 /C exhibits impressive ORR performance with high onset potential (0.986 VRHE ), half-wave potential (0.877 VRHE ), and excellent stability. Similar ORR results are also found for Pd-Sm2 O3 /C, Pd-Eu2 O3 /C, and Pd-CeO2 /C catalysts. Theoretical analyses reveal that the coupling between Pd and Gd2 O3 promotes electron transfer through the Pd-O-Gd bridge, which induces the antibonding-orbital occupancy of Pd-*OH for the optimization of *OH adsorption in the rate-determining step of ORR. The pH-dependent microkinetic modeling shows that Pd-Gd2 O3 is close to the theoretical optimal activity for ORR, outperforming Pt under the same conditions. By its ascendancy in ORR, the Pd-Gd2 O3 /C exhibits superior performance in Zn-air battery as an air cathode, implying its excellent practicability.

G protein α subunit suppresses sporangium formation through a serine/threonine protein kinase in Phytophthora sojae.

Eukaryotic heterotrimeric guanine nucleotide-binding proteins consist of α, ß, and γ subunits, which act as molecular switches to regulate a number of fundamental cellular processes. In the oomycete pathogen Phytophthora sojae, the sole G protein α subunit (Gα; encoded by PsGPA1) has been found to be involved in zoospore mobility and virulence, but how it functions remains unclear. In this study, we show that the Gα subunit PsGPA1 directly interacts with PsYPK1, a serine/threonine protein kinase that consists of an N-terminal region with unknown function and a C-terminal region with a conserved catalytic kinase domain. We generated knockout and knockout-complemented strains of PsYPK1 and found that deletion of PsYPK1 resulted in a pronounced reduction in the production of sporangia and oospores, in mycelial growth on nutrient poor medium, and in virulence. PsYPK1 exhibits a cytoplasmic-nuclear localization pattern that is essential for sporangium formation and virulence of P. sojae. Interestingly, PsGPA1 overexpression was found to prevent nuclear localization of PsYPK1 by exclusively binding to the N-terminal region of PsYPK1, therefore accounting for its negative role in sporangium formation. Our data demonstrate that PsGPA1 negatively regulates sporangium formation by repressing the nuclear localization of its downstream kinase PsYPK1.

Metagenomic and Metatranscriptomic Responses of Chemical Dispersant Application during a Marine Dilbit Spill.

The global increase in marine transportation of dilbit (diluted bitumen) can increase the risk of spills, and the application of chemical dispersants remains a common response practice in spill events. To reliably evaluate dispersant effects on dilbit biodegradation over time, we set large-scale (1,500 mL) microcosms without nutrient addition using a low dilbit concentration (30 ppm). Shotgun metagenomics and metatranscriptomics were deployed to investigate microbial community responses to naturally and chemically dispersed dilbit. We found that the large-scale microcosms could produce more reproducible community trajectories than small-scale (250 mL) ones based on the 16S rRNA gene amplicon sequencing. In the early-stage large-scale microcosms, multiple genera were involved in the biodegradation of dilbit, while dispersant addition enriched primarily Alteromonas and competed for the utilization of dilbit, causing depressed degradation of aromatics. The metatranscriptomic-based metagenome-assembled genomes (MAG) further elucidated early-stage microbial antioxidation mechanism, which showed that dispersant addition triggered the increased expression of the antioxidation process genes of Alteromonas species. Differently, in the late stage, the microbial communities showed high diversity and richness and similar compositions and metabolic functions regardless of dispersant addition, indicating that the biotransformation of remaining compounds can occur within the post-oil communities. These findings can guide future microcosm studies and the application of chemical dispersants for responding to a marine dilbit spill. IMPORTANCE In this study, we employed microcosms to study the effects of marine dilbit spill and dispersant application on microbial community dynamics over time. We evaluated the impacts of microcosm scale and found that increasing the scale is beneficial for reducing community stochasticity, especially in the late stage of biodegradation. We observed that dispersant application suppressed aromatics biodegradation in the early stage (6 days), whereas exerting insignificant effects in the late stage (50 days), from both substance removal and metagenomic/metatranscriptomic perspectives. We further found that Alteromonas species are vital for the early-stage chemically dispersed oil biodegradation and clarified their degradation and antioxidation mechanisms. These findings help us to better understand microcosm studies and microbial roles for biodegrading dilbit and chemically dispersed dilbit and suggest that dispersant evaluation in large-scale systems and even through field trails would be more realistic after marine oil spill response.

Impacts of Frazil Ice on the Effectiveness of Oil Dispersion and Migration of Dispersed Oil.

Oil spills in the Arctic have drawn dramatic attention in recent years. Frazil ice, as the essential formation of sea ice, may affect the effectiveness of dispersants during oil spill response and the associated behaviors of dispersed oil. However, these impacts remain poorly understood, limiting the appropriate usage of dispersants in ice-covered regions. Herein this work explored the effects of frazil ice on the dispersion effectiveness of two dispersants (Corexit 9500A and hydrolyzed shrimp waste) and the migration of dispersed oil within frazil ice. We discovered that frazil ice inhibited dispersion effectiveness by attenuating water velocity. Permeable frazil ice encapsulated 11-30% of dispersed oil, implying a lower oil bioavailability. We thus proposed and verified a microscopic mechanism to unravel the migration of dispersed oil toward permeable constrictions in frazil ice. We predicted the concentration of dispersed oil encapsulated in frazil ice using bed filtration theory and verified the prediction through experiments. Furthermore, the presence of frazil ice can lead to the breakup and coalescence of dispersed oil. Overall, our findings would facilitate the appropriate planning and decision-making of dispersant-based oil spill response and a better understanding of the fate of dispersed oil in the frazil ice-infested ocean.

An Oomycete-Specific Leucine-Rich Repeat-Containing Protein Is Involved in Zoospore Flagellum Development in Phytophthora sojae.

A leucine-rich repeat (LRR) is a widespread structural motif of 20 to 30 amino acids with characteristic repetitive sequences rich in leucine. LRR-containing proteins are critical for ligand recognition and binding, participating in plant development and defense. Like plants, oomycetes also harbor genes encoding LRR-containing proteins, but their functions remain largely unknown. We identified a zoospore-upregulated gene from Phytophthora sojae with LRRs and an extra structural maintenance of chromosomes-like domain. We generated knockout and complemented knockout strains of this LRR protein and found that its deletion resulted in a pronounced reduction in zoospore mobility and chemotaxis, cyst germination, and virulence. Interestingly, micro-examination of zoospores under a scanning electron microscope revealed irregularly shaped zoospores without flagella in these deletion mutants. In addition, the reintroduction of this LRR protein into the knockout mutant reversed all the deficiencies. Our data demonstrate a critical role for the Phytophthora LRR protein in modulating zoospore development, which impairs migration to the host soybean and affects the spread of Phytophthora pathogens.

Dermal exposure to synthetic musks: Human health risk assessment, mechanism, and control strategy.

Synthetic musks (SMs) have been widely used as odor additives in personal care products (PCPs). Dermal exposure to SMs is the main pathway of the accumulation of these chemicals in human kerateins and poses potential health risks. In this study, in silico methods were established to reduce the human health risk of SMs from dermal exposure by investigating the risk mechanisms, designing lower bioaccumulation ability SMs and suggesting proper PCP ingredients using molecular docking, molecular dynamics simulation, and quantitative structure-activity relationship (QSAR) models. The binding energy, a parameter reflecting the binding ability of SMs and human keratin protein (4ZRY), was used as the indicator to assess the human health risk of SMs. According to the mechanism analysis, total energy was found as the most influential molecular structural feature influencing the bioaccumulation ability of a SM, and as one of the main factors influencing the function (i.e., odor sensitivity) of an SM. The 3D-QSAR models were constructed to control the human health risk of SMs by designing lower-risk SMs derivatives. The phantolide (PHAN)- 58 was determined to be the optimum SM derivative with lower bioaccumulation ability (reduced 17.25%) and improved odor sensitivity (increased 7.91%). A further reduction of bioaccumulation ability of PHAN-58 was found when adding proper body wash ingredients (i.e., alkyl ethoxylate sulfate (AES), dimethyloldimethyl (DMDM), EDTA-Na4, ethylene glycol distearate (EGDS), hydroxyethyl cellulose (HEC), lemon yellow and octyl glucose), leading to a significant reduction of the bioaccumulation ability (42.27%) compared with that of PHAN. Results demonstrated that the proposed theoretical mechanism and control strategies could effectively reduce the human health risk of SMs from dermal exposure.

Treatment of septate uterus. / 纵隔子宫的治疗（英文）.

Although there is insufficient evidence supporting the link between septate uterus and infertility, there are many studies demonstrated the effect of spetal incision on pregnancy in women diagnosed with septate uterus associated with infertility. Hysteroscopic metroplasty can significantly improve the reproductive performance of those with septate uterus. Some Müllerian malformations can be healed by surgery. The accurate diagnosis and appropriate therapeutic approch are fundamental for successful treatment. Any attempt at surgical correction of uterine abnormalities must be aimed at preserving or improving reproductive function. Among congenital uterine anomalies, septate uterus is the most amenable to simple hysteroscopic treatment. The resection of the septum is performed as standard treatment worldwide.

A novel peptide identified from skin secretions of Bombina maxima possesses LPS-neutralizing activity.

Lipopolysaccharide (LPS) is a major pathogenic factor in endotoxin shock or sepsis. Most antibiotics have little clinical anti-endotoxin activity, but some antimicrobial peptides (AMPs) have been shown to be effective in blocking LPS. We identified a novel peptide from the skin secretions of Bombina maxima (B. _maxima) by challenging the skin of frogs with an LPS solution. Peptide 2 has an amino acid sequence of LVGKLLKGAVGDVCGLLPIC. Peptide 2 possesses low hemolytic activity, low cytotoxicity against RAW 264.7 cells, and strong anti-inflammatory activity. Moreover, peptide 2 plays an anti-inflammatory role by inhibiting inflammatory cytokines such as tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6). A biolayer interferometry (BLI) assay indicated that peptide 2 binds to LPS with strong affinity and that this interaction has an affinity constant (KD) value of 1.05 × 10-9 M. A survival study showed that peptide 2 possesses potent LPS-neutralizing activity to protect LPS-treated mice from death. In conclusion, we have identified a potent peptide with LPS neutralizing activity, which lays a foundation for future research and development.

Machine Learning-Aided Causal Inference Framework for Environmental Data Analysis: A COVID-19 Case Study.

Links between environmental conditions (e.g., meteorological factors and air quality) and COVID-19 severity have been reported worldwide. However, the existing frameworks of data analysis are insufficient or inefficient to investigate the potential causality behind the associations involving multidimensional factors and complicated interrelationships. Thus, a causal inference framework equipped with the structural causal model aided by machine learning methods was proposed and applied to examine the potential causal relationships between COVID-19 severity and 10 environmental factors (NO2, O3, PM2.5, PM10, SO2, CO, average air temperature, atmospheric pressure, relative humidity, and wind speed) in 166 Chinese cities. The cities were grouped into three clusters based on the socio-economic features. Time-series data from these cities in each cluster were analyzed in different pandemic phases. The robustness check refuted most potential causal relationships' estimations (89 out of 90). Only one potential relationship about air temperature passed the final test with a causal effect of 0.041 under a specific cluster-phase condition. The results indicate that the environmental factors are unlikely to cause noticeable aggravation of the COVID-19 pandemic. This study also demonstrated the high value and potential of the proposed method in investigating causal problems with observational data in environmental or other fields.

A data-driven binary-classification framework for oil fingerprinting analysis.

A marine oil spill is one of the most challenging environmental issues, resulting in severe long-term impacts on ecosystems and human society. Oil dispersants are widely applied as a treating agent in oil spill response operations. The usage of dispersants significantly changes the behaviors of dispersed oil and consequently challenges the oil fingerprinting analysis. In this study, machine learning was first introduced to analyze oil fingerprinting by developing a data-driven binary classification framework. The modeling integrated dimensionality reduction algorithms (e.g., principal component analysis, PCA) to distinguish. Five groups of biomarkers, including terpanes, steranes, triaromatic steranes (TA-steranes), monoaromatic steranes (MA-steranes), and diamantanes, were selected. Different feature spaces were created from the diagnostic index of biomarkers, and six ML algorithms were applied for comparative analysis and optimizing the modeling process, including k-nearest neighbor (KNN), support vector classifier (SVC), random forest classifier (RFC), decision tree classifier (DTC), logistic regression classifier (LRC), and ensemble vote classifier (EVC). Hyperparameter optimization and cross-validation through GridSearchCV were applied to prevent overfitting and increase the model accuracy. Model performance was evaluated by model score and F-score through confusion matrices. The results indicated that the RFC algorithm from the diamantanes dataset performed the best. It delivered the highest F-score (0.871) versus the lowest F-score (0.792) from the EVC algorithm from the TA-steranes dataset by PCA with a variance of 95%. Therefore, diamantanes were recommended as the most suitable biomarker for distinguishing WCO and CDO to aid oil fingerprinting under the conditions in this study. The results proved the proposed method as a potential analysis tool for oil spill source identification through ML-aided oil fingerprinting. The study also showed the value of ML methods in oil spill response research and practice.

Atomic Hourglass and Thermometer Based on Diffusion of a Mobile Dopant in VO2.

Transformations between different atomic configurations of a material oftentimes bring about dramatic changes in functional properties as a result of the simultaneous alteration of both atomistic and electronic structure. Transformation barriers between polytypes can be tuned through compositional modification, generally in an immutable manner. Continuous, stimulus-driven modulation of phase stabilities remains a significant challenge. Utilizing the metal-insulator transition of VO2, we exemplify that mobile dopants weakly coupled to the crystal lattice provide a means of imbuing a reversible and dynamical modulation of the phase transformation. Remarkably, we observe a time- and temperature-dependent evolution of the relative phase stabilities of the M1 and R phases of VO2 in an "hourglass" fashion through the relaxation of interstitial boron species, corresponding to a 50 °C modulation of the transition temperature achieved within the same compound. The material functions as both a chronometer and a thermometer and is "reset" by the phase transition. Materials possessing memory of thermal history hold promise for applications such as neuromorphic computing, atomic clocks, thermometry, and sensing.

Plasmonic-Enhanced Oxygen Reduction Reaction of Silver/Graphene Electrocatalysts.

Oxygen reduction reaction (ORR) is of paramount importance in polymer electrolyte membrane fuel cells due to its sluggish kinetics. In this work, a plasmon-induced hot electrons enhancement method is introduced to enhance ORR property of the silver (Ag)-based electrocatalysts. Three types of Ag nanostructures with differently localized surface plasmon resonances have been used as electrocatalysts. The thermal effect of plasmonic-enhanced ORR can be minimized in our work by using graphene as the support of Ag nanoparticles. By tuning the resonance positions and laser power, the enhancement of ORR properties of Ag catalysts has been optimized. Among these catalysts, Ag nanotriangles after excitation show the highest mass activity and reach 0.086 mA/µgAg at 0.8 V, which is almost 17 times that of a commercial Pt/C catalyst after the price is accounted. Our results demonstrate that the hot electrons generated from surface plasmon resonance can be utilized for electrochemical reaction, and tuning the resonance positions by light is a promising and viable approach to boost electrochemical reactions.

Digital PCR as an Emerging Tool for Monitoring of Microbial Biodegradation.

Biodegradation of contaminants is extremely complicated due to unpredictable microbial behaviors. Monitoring of microbial biodegradation drives us to determine (1) the amounts of specific degrading microbes, (2) the abundance, and (3) expression level of relevant functional genes. To this endeavor, the cultivation independent polymerase chain reaction (PCR)-based monitoring technique develops from endpoint PCR, real-time quantitative PCR, and then into novel digital PCR. In this review, we introduce these three categories of PCR techniques and summarize the timely applications of digital PCR and its superiorities than qPCR for biodegradation monitoring. Digital PCR technique, emerging as the most accurately absolute quantification method, can serve as the most promising and robust tool for monitoring of microbial biodegradation.

Multi-agent hybrid particle swarm optimization (MAHPSO) for wastewater treatment network planning.

The planning of municipal wastewater treatment networks has been recognized as a valuable means for achieving the optimal use of resources and improving the cost-efficient operation of plants. In this study, a multi-agent hybrid particle swarm optimization (MAHPSO) approach was developed as a new systematic planning tool by the integration of hybrid particle swarm optimization and multi-agent system. Its effectiveness and feasibility were demonstrated by a simplified real-world case in the metropolitan area of St. John's, Canada. Genetic algorithm and hybrid particle swarm optimization were also employed for comparison and the results indicated the better performance with the proposed approach in terms of efficiency in finding the solutions, computational requirements, and overall costs of the network. The MAHPSO can be used as an effective evolutionary algorithm in supporting wastewater treatment network operation and other complex environmental management problems.

Differentiation of weathered chemically dispersed oil from weathered crude oil.

Oil fingerprinting is a crucial technology to trace the sources and behaviors of spilled oil. The use of dispersants enhances the stay of dispersed oil in a water column and changes the important properties of spilled oil. In case of fingerprinting of dispersed oil driven by dispersants, the fate and behaviors of biomarkers may be affected by the application of dispersants. Limited studies have investigated the statistical difference between fingerprinting of dispersed oil and non-dispersed oil using biomarkers, and the possible influence of the differences, if present. This study applied several principal component analyses (PCA) to differentiate weathered chemically dispersed oil from weathered crude (non-dispersed) oil using 103 diagnostic ratios of the same type of biomarkers and those of two types of biomarkers as input data. It showed that weathered chemically dispersed oil (CDO) can be differentiated from weathered crude oil (WCO) using specific diagnostic ratios that are affected by weathering. PCA analyses indicated the effects of the application of dispersants and weathering duration on weathering of biomarkers in CDO and WCO.