A Perspective of Bioinspired Interfaces Applied in Renewable Energy Storage and Conversion Devices.

The natural world renders a large number of opportunities to design intriguing structures and fascinating functions for innovations of advanced surfaces and interfaces. Currently, bioinspired interfaces have attracted much attention in practical applications of renewable energy storage and conversion devices including rechargeable batteries, fuel cells, dye-sensitized solar cells, and supercapacitors. By mimicking miscellaneous natural creatures, many novel bioinspired interfaces with various components, structures, morphology, and configurations are exerted on the devices' electrodes, electrolytes, additives, separators, and catalyst matrixes, resorting to their wonderful mechanical, optical, electrical, physical, chemical, and electrochemical features compared with the corresponding traditional modes. In this Perspective, the principles of designing bioinspired interfaces are discussed with respect to biomimetic chemical components, physical morphologies, biochemical reactions, and macrobiomimetic assembly configurations. A brief summary, subsequently, is mainly focused on the recent progress on bioinspired interfaces applied in key materials for rechargeable batteries. Ultimately, a critical comment is projected on significant opportunities and challenges existing in the future development course of bioinspired interfaces. It is expected that this Perspective is able to provide a profound perception into some underlying artificial intelligent energy storage and conversion device design as a promising candidate to resolve the global energy crisis and environmental pollution.

Tobacco rattle virus-induced gene silencing in Hevea brasiliensis.

Virus-induced gene silencing (VIGS) is a powerful gene-silencing tool that has been intensively applied in plants. To data, the application of VIGS in rubber tree has not yet been reported. In this study, we described the efficient gene silencing in rubber tree by VIGS. The gene encoding Hevea brasiliensis phytoene desaturase (HbPDS) was identified in rubber tree genome. Small interfering RNAs from HbPDS and the silencing gene fragment were predicted and a length of 399 bp was selected to be tested. We showed that the tobacco rattle virus (TRV)-VIGS could induce effective HbPDS silencing in rubber tree. This study was the first to report VIGS in rubber tree. The present TRV-VIGS method could be used to perform reverse genetic approaches to identify unknown gene functions and might be further applied to produce gene silenced rubber tree plants, to advance functional gene of rubber tree.

Few-Layer Boron Nitride with Engineered Nitrogen Vacancies for Promoting Conversion of Polysulfide as a Cathode Matrix for Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries have become one of the most promising candidates as next-generation batteries, owing to their high specific capacity, low cost, and environmental benignity. Although many strategies have been proposed to restrain the shuttle of lithium polysulfides (LiPSs) through physical trapping and chemical binding, the sluggish kinetics of PS conversion still degrade the capacity, rate, and cycling performance of Li-S batteries. Herein, a novel kind of few-layer BN with engineered nitrogen vacancies (v-BN) has been developed as a cathode matrix for Li-S batteries. The positive vacancies in the BN nanosheets not only promote the immobilization and conversion of LiPSs, but also accelerate the lithium ion diffusion in cathode electrodes. Compared with pristine BN, the v-BN cathodes exhibit higher initial capacities from 775 mA h g-1 to 1262 mA h g-1 at 0.1 C and a high average coulombic efficiency of over 98 % during 150 cycles. Upon increasing the current density to 1 C, the cell still preserves a capacity of 406 mA h g-1 after 500 cycles, exhibiting a capacity decay of only 0.084 % per cycle. The new vacancy-engineered material provides a promising method for achieving excellent performance in Li-S batteries.

The Optimization and Characterization of an RNA-Cleaving Fluorogenic DNAzyme Probe for MDA-MB-231 Cell Detection.

Breast cancer is one of the most frequently diagnosed cancers in females worldwide and lacks specific biomarkers for early detection. In a previous study, we obtained a selective RNA-cleaving Fluorogenic DNAzyme (RFD) probe against MDA-MB-231 cells, typical breast cancer cells, through the systematic evolution of ligands by exponential process (SELEX). To improve the performance of this probe for actual application, we carried out a series of optimization experiments on the pH value of a reaction buffer, the type and concentration of cofactor ions, and sequence minimization. The length of the active domain of the probe reduced to 25 nt from 40 nt after optimization, which was synthesized more easily and economically. The detection limit of the optimized assay system was 2000 MDA-MB-231 cells in 30 min, which is more sensitive than the previous one (almost 5000 cells). The DNAzyme probe was also capable of distinguishing MDA-MB-231 cell specifically from 3 normal cells and 10 other tumor cells. This probe with high sensitivity, selectivity, and economic efficiency enhances the feasibility for further clinical application in breast cancer diagnosis. Herein, we developed an optimization system to produce a general strategy to establish an easy-to-use DNAzyme-based assay for other targets.

Highly specific recognition of breast tumors by an RNA-cleaving fluorogenic DNAzyme probe.

Breast cancer is one of the most commonly diagnosed cancers among females worldwide. Early detection of breast cancer is of vital importance to the reduction of the mortality rate. However, the lack of specific biomarkers that can effectively identify breast cancer cells limits the ability for early diagnosis of breast cancer. RNA-cleaving fluorogenic DNAzymes (RFDs), which can be produced through the systematic evolution of ligands by exponential enrichment (SELEX) process, are catalytic DNA molecules capable of generating a fluorescent signal when the appropriate target is bound. In this study, we carried out a SELEX experiment to select for RFDs that are active in the cell lysate of MDA-MB-231, a model breast cancer cell line. We obtained a RFD probe, named AAI2-5, that can detect MDA-MB-231 at a concentration of cell lysate proteins as low as 0.5 µg/mL (which is equivalent to ∼5000 cell/mL). AAI2-5 is capable of distinguishing MDA-MB-231 cells from normal cells as well as other types of tumor cells, including other subtypes of breast cancer cells. Moreover, AAI2-5 responded positively to more than 90% of malignant breast tumors. This report is the first study to explore the RFD system for the detection of cancer cells. The results suggest that RFD can be potentially applied for the diagnosis and treatment of breast cancer in the future.

Effect of expressions of tumor necrosis factor α and interleukin 1B on peritoneal metastasis of gastric cancer.

Our study aimed to investigate effect of expressions of tumor necrosis factor α (TNF-α) and interleukin 1B (IL-1B) on peritoneal metastasis of gastric cancer (GC). From June 2012 to June 2014, a total of 60 patients with advanced peritoneal metastasis from GC were collected from Department of Gastrointestinal and Nutriology Surgery at Shengjing Hospital of China Medical University. Furthermore, 60 GC patients without peritoneal metastasis were enrolled as controls. Immunohistochemistry was performed to test TNF-α and IL-1B expression, and logistic regression analysis was employed for evaluating risk factors for peritoneal metastasis of GC. Our results showed that TNF-α expression in metastatic group and non-metastatic group was significantly different (P = 0.043), but no significant difference was found in IL-1B expression between two groups (P = 0.261). In addition, TNF-α expression in metastatic group and non-metastatic group was associated with tumor size, depth of invasion, the degree of differentiation (all P < 0.05). Logistic regression analysis indicated that tumor size, depth of invasion, the degree of differentiation and TNF-α expression were risk factors for peritoneal metastasis of GC (all P < 0.05). Our study found that TNF-α expression may play a vital role in peritoneal metastasis of GC, while IL-1B expression might not be correlated with peritoneal metastasis.

Combining dependent F-tests for robust association of quantitative traits under genetic model uncertainty.

In association mapping of quantitative traits, the F-test based on an assumed genetic model is a basic statistical tool for testing association of each candidate locus with the trait of interest. However, the true underlying genetic model is often unknown, and using an incorrect model may cause serious loss of power. For case-control studies, it is known that the combination of several tests that are optimal for different models is robust to model misspecification. In this paper, we extend the test combination approach to quantitative trait association. We first derive the exact correlations among transformed test statistics and discuss interesting special cases. We then propose and evaluate a multivariate normality based approximation to the joint distribution of test statistics, such that the marginal distributions and pairwise correlations among test statistics are accounted for. Through simulations, we show that the sizes of the resulting approximate combined tests are accurate for practical purposes under a variety of situations. We find that the combination of the tests from the additive model and the genotypic model performs well, because it demonstrates both robustness to incorrect models and satisfactory power. A mouse lipoprotein data set is used to demonstrate the method.

A fast and efficient Gibbs sampler for BayesB in whole-genome analyses.

BACKGROUND: In whole-genome analyses, the number p of marker covariates is often much larger than the number n of observations. Bayesian multiple regression models are widely used in genomic selection to address this problem of [Formula: see text] The primary difference between these models is the prior assumed for the effects of the covariates. Usually in the BayesB method, a Metropolis-Hastings (MH) algorithm is used to jointly sample the marker effect and the locus-specific variance, which may make BayesB computationally intensive. In this paper, we show how the Gibbs sampler without the MH algorithm can be used for the BayesB method. RESULTS: We consider three different versions of the Gibbs sampler to sample the marker effect and locus-specific variance for each locus. Among the Gibbs samplers that were considered, the most efficient sampler is about 2.1 times as efficient as the MH algorithm proposed by Meuwissen et al. and 1.7 times as efficient as that proposed by Habier et al. CONCLUSIONS: The three Gibbs samplers presented here were twice as efficient as Metropolis-Hastings samplers and gave virtually the same results.

Endometrial gene expression profiling in pregnant Meishan and Yorkshire pigs on day 12 of gestation.

BACKGROUND: Litter size in pigs is a major factor affecting the profitability in the pig industry. The peri-implantation window in pigs is characterized by the coordinated interactions between the maternal uterine endometrium and the rapidly elongating conceptuses and represents a period of time during which a large percentage of the developing conceptuses are lost. However, the gene expression and regulatory networks in the endometrium contributing to the establishment of the maternal: placental interface remain poorly understood. RESULTS: We characterized the endometrial gene expression profile during the peri-implantation stage of development by comparing two breeds that demonstrate very different reproductive efficiencies. We employed the porcine Affymetrix GeneChip® to assay the transcriptomic profiles of genes expressed in the uterine endometrium obtained from Meishan and Yorkshire gilts (n = 4 for each breed) on day 12 of gestation (M12 and Y12, respectively). Total of 17,076 probesets were identified as "present" in at least two arrays. A mixed model-based statistical analysis predicted a total of 2,656 (q < 0.1) transcripts as differentially expressed between Meishan and Yorkshire pigs. Eighteen differentially expressed transcripts of interest were validated by quantitative real-time PCR. Gene ontology (GO) annotation revealed that the known functions of the differentially expressed genes were involved in a series of important biological processes relevant to early pregnancy establishment in the pig. CONCLUSIONS: The results identified endometrial gene expression profiles of two breeds differing in litter size and identified candidate genes that are related to known physiological pathways related to reproductive prolificacy. These findings provide a deeper understanding of molecular pathways differing between two breeds at the critical peri-implantation stage of pregnancy, which can be utilized to better understand the events contributing to pregnancy establishment in the pig.

A transcriptomic network underlies microstructural and physiological responses to cadmium in Populus x canescens.

Bark tissue of Populus × canescens can hyperaccumulate cadmium, but microstructural, transcriptomic, and physiological response mechanisms are poorly understood. Histochemical assays, transmission electron microscopic observations, energy-dispersive x-ray microanalysis, and transcriptomic and physiological analyses have been performed to enhance our understanding of cadmium accumulation and detoxification in P. × canescens. Cadmium was allocated to the phloem of the bark, and subcellular cadmium compartmentalization occurred mainly in vacuoles of phloem cells. Transcripts involved in microstructural alteration, changes in nutrition and primary metabolism, and stimulation of stress responses showed significantly differential expression in the bark of P. × canescens exposed to cadmium. About 48% of the differentially regulated transcripts formed a coregulation network in which 43 hub genes played a central role both in cross talk among distinct biological processes and in coordinating the transcriptomic regulation in the bark of P. × canescens in response to cadmium. The cadmium transcriptome in the bark of P. × canescens was mirrored by physiological readouts. Cadmium accumulation led to decreased total nitrogen, phosphorus, and calcium and increased sulfur in the bark. Cadmium inhibited photosynthesis, resulting in decreased carbohydrate levels. Cadmium induced oxidative stress and antioxidants, including free proline, soluble phenolics, ascorbate, and thiol compounds. These results suggest that orchestrated microstructural, transcriptomic, and physiological regulation may sustain cadmium hyperaccumulation in P. × canescens bark and provide new insights into engineering woody plants for phytoremediation.

Transcriptome analyses describe the consequences of persistent HIF-1 over-activation in Caenorhabditis elegans.

Metazoan animals rely on oxygen for survival, but during normal development and homeostasis, animals are often challenged by hypoxia (low oxygen). In metazoans, many of the critical hypoxia responses are mediated by the evolutionarily conserved hypoxia-inducible transcription factors (HIFs). The stability and activity of HIF complexes are strictly regulated. In the model organism C. elegans, HIF-1 stability and activity are negatively regulated by VHL-1, EGL-9, RHY-1 and SWAN-1. Importantly, C. elegans mutants carrying strong loss-of-function mutations in these genes are viable, and this provides opportunities to interrogate the molecular consequences of persistent HIF-1 over-activation. We find that the genome-wide gene expression patterns are compellingly similar in these mutants, supporting models in which RHY-1, VHL-1 and EGL-9 function in common pathway(s) to regulate HIF-1 activity. These studies illuminate the diversified biological roles played by HIF-1, including metabolism and stress response. Genes regulated by persistent HIF-1 over-activation overlap with genes responsive to pathogens, and they overlap with genes regulated by DAF-16. As crucial stress regulators, HIF-1 and DAF-16 converge on key stress-responsive genes and function synergistically to enable hypoxia survival.

Whole genome profiling of short-term hypoxia induced genes and identification of HIF-1 binding sites provide insights into HIF-1 function in Caenorhabditis elegans.

Oxygen is essential to all the aerobic organisms. However, during normal development, disease and homeostasis, organisms are often challenged by hypoxia (oxygen deprivation). Hypoxia-inducible transcription factors (HIFs) are master regulators of hypoxia response and are evolutionarily conserved in metazoans. The homolog of HIF in the genetic model organism C. elegans is HIF-1. In this study, we aimed to understand short-term hypoxia response to identify HIF-1 downstream genes and identify HIF-1 direct targets in C. elegans. The central research questions were: (1) which genes are differentially expressed in response to short-term hypoxia? (2) Which of these changes in gene expression are dependent upon HIF-1 function? (3) Are any of these hif-1-dependent genes essential to survival in hypoxia? (4) Which genes are the direct targets of HIF-1? We combine whole genome gene expression analyses and chromatin immunoprecipitation sequencing (ChIP-seq) experiments to address these questions. In agreement with other published studies, we report that HIF-1-dependent hypoxia-responsive genes are involved in metabolism and stress response. Some HIF-1-dependent hypoxia-responsive genes like efk-1 and phy-2 dramatically impact survival in hypoxic conditions. Genes regulated by HIF-1 and hypoxia overlap with genes responsive to hydrogen sulfide, also overlap with genes regulated by DAF-16. The genomic regions that co-immunoprecipitate with HIF-1 are strongly enriched for genes involved in stress response. Further, some of these potential HIF-1 direct targets are differentially expressed under short-term hypoxia or are differentially regulated by mutations that enhance HIF-1 activity.

Cloud inversion analysis of surrounding rock parameters for underground powerhouse based on PSO-BP optimized neural network and web technology.

Aiming at the shortcomings of the BP neural network in practical applications, such as easy to fall into local extremum and slow convergence speed, we optimized the initial weights and thresholds of the BP neural network using the particle swarm optimization (PSO). Additionally, cloud computing service, web technology, cloud database and numerical simulation were integrated to construct an intelligent feedback analysis cloud program for underground engineering safety monitoring based on the PSO-BP algorithm. The program could conveniently, quickly, and intelligently carry out numerical analysis of underground engineering and dynamic feedback analysis of surrounding rock parameters. The program was applied to the cloud inversion analysis of the surrounding rock parameters for the underground powerhouse of the Shuangjiangkou Hydropower Station. The calculated displacement simulated with the back-analyzed parameters matches the measured displacement very well. The posterior variance evaluation shows that the posterior error ratio is 0.045 and the small error probability is 0.999. The evaluation results indicate that the intelligent feedback analysis cloud program has high accuracy and can be applied to engineering practice.

Modelling the dynamic gas/particle partitioning process of semi-volatile organic compounds emitted from point sources: Quantitative analysis and impact assessment.

The deleterious impact of pollution point sources on the surrounding environment and human has long been a focal point of environmental research. When considering the local atmospheric dispersion of semi-volatile organic compounds (SVOCs) around the emission sites, it is essential to account the dynamic process for the gas/particle (G/P) partitioning, which involves the transition from an initial state to a steady state. In this study, we have developed a model that enables the prediction of the dynamic process for G/P partitioning of SVOCs, particularly considering the influence from emission. It is important to note that the dynamic processes of the concentrations of SVOCs in particle phase (CP) and in gas phase (CG) differ significantly. These differences arise due to the influence of two critical factors: particulate proportion of SVOCs in the emissions (ϕ0) and octanol-air partitioning coefficient (KOA). The validity of our model was assessed by comparing its predictions of the extremum value of the G/P partitioning quotient (KP) with the results obtained from the steady-state model. Remarkably, the characteristic time (tC), used to evaluate the timescale required for SVOCs to reach steady state, demonstrated different variations with KOA for CP and CG. Additionally, the values of tC were quite different for CP and CG, which were markedly influenced by ϕ0. For some SVOCs with high KOA values, it took approximately 35 h to reach steady state. Furthermore, it was found that the time to achieve 95 % of steady state (t95 ≈ 3tC) could reach approximately 105 h. This duration is sufficient for chemicals to disperse from their emission site to the surrounding areas. Therefore, it is crucial to consider the dynamic process of G/P partitioning in local atmospheric transport studies. Moreover, the influence of ϕ0 should be incorporated into future investigations examining the dynamic process of G/P partitioning.

AZD1390, an ataxia telangiectasia mutated inhibitor, attenuates microglia-mediated neuroinflammation and ischemic brain injury.

AIMS: Excessive neuroinflammation mediated mainly by microglia plays a crucial role in ischemic stroke. AZD1390, an ataxia telangiectasia mutated (ATM) specific inhibitor, has been shown to promote radio-sensitization and survival in central nervous system malignancies, while the role of AZD1390 in ischemic stroke remains unknown. METHODS: Real-time PCR, western blot, immunofluorescence staining, flow cytometry and enzyme-linked immunosorbent assays were used to assess the activation of microglia and the release of inflammatory cytokines. Behavioral tests were performed to measure neurological deficits. 2,3,5-Triphenyltetrazolium chloride staining was conducted to assess the infarct volume. The activation of NF-κB signaling pathway was explored through immunofluorescence staining, western blot, co-immunoprecipitation and proximity ligation assay. RESULTS: The level of pro-inflammation cytokines and activation of NF-κB signaling pathway was suppressed by AZD1390 in vitro and in vivo. The behavior deficits and infarct size were partially restored with AZD1390 treatment in experimental stroke. AZD1390 restrict ubiquitylation and sumoylation of the essential regulatory subunit of NF-κB (NEMO) in an ATM-dependent and ATM-independent way respectively, which reduced the activation of the NF-κB pathway. CONCLUSION: AZD1390 suppressed NF-κB signaling pathway to alleviate ischemic brain injury in experimental stroke, and attenuated microglia activation and neuroinflammation, which indicated that AZD1390 might be an attractive agent for the treatment of ischemic stroke.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests.

Simultaneous determination of 24 or more acidic and alkaline phytohormones in femtomole quantities of plant tissues by high-performance liquid chromatography-electrospray ionization-ion trap mass spectrometry.

Phytohormones act at relatively low concentrations as major regulatory factors of plant growth and development, and cross talk of phytohormones is currently of great interest throughout the plant science community. To meet this demand, a method that is capable of simultaneously analyzing diverse plant hormones is essential. This paper introduces a high-performance liquid chromatographic separation technique coupled with sensitive and selective ion trap mass spectrometry to simultaneously determine 24 or more acidic and alkaline phytohormones, including auxin, cis- and trans-abscisic acid, 11 cytokinins, and 10 gibberellins, in a single injection of sample. A binary solid-phase extraction using Oasis MCX cartridges for cations and Oasis MAX cartridges for anions was used to prepurify more than 24 acidic and alkaline phytohormones from a single plant extract. The method showed good linearity for all 24 phytohormones with R(2) values ranging from 0.9903 to 0.9997. Limits of detection for most of the phytohormones were in the femtomole range with some extending into the sub-femtomole range. This method was applied to hundreds of plant samples comprising different tissues from various plants, including herbaceous, woody climbing, and woody plants to demonstrate feasibility and to validate the methodology.

Whole genome profiling of short-term hypoxia induced genes and identification of HIF-1 binding sites provide insights into HIF-1 function in Caenorhabditis elegans.

Oxygen is essential to all the aerobic organisms. However, during normal development, disease and homeostasis, organisms are often challenged by hypoxia (oxygen deprivation). Hypoxia-inducible transcription factors (HIFs) are master regulators of hypoxia response and are evolutionarily conserved in metazoans. The homolog of HIF in the genetic model organism C. elegans is HIF-1. In this study, we aimed to understand short-term hypoxia response and to identify HIF-1 direct targets in C. elegans. The central research questions were: (1) which genes are differentially expressed in response to short-term hypoxia? (2) Which of these changes in gene expression are dependent upon HIF-1 function? (3) How do HIF-1-dependent hypoxia-responsive genes affect hypoxia adaptation? (4) Which genes are the direct targets of HIF-1? We combine whole genome gene expression analyses and chromatin immunoprecipitation sequencing (ChIP-seq) experiments to address these questions. In agreement with other published studies, we report that HIF-1-dependent hypoxia-responsive genes are involved in metabolism, oxidation-reduction process, and stress response. Some HIF-1-dependent hypoxia-responsive genes like efk-1 andphy-2 dramatically impact survival in hypoxic conditions. HIF-1 co-immunoprecipitates with genomic regions proximal genes involved in stress response, protein processing in endoplasmic reticulum, and cell recognition. Further, some of these potential HIF-1 direct targets are differentially expressed under short-term hypoxia or are differentially regulated by mutations that enhance HIF-1 activity.

Transcriptome analyses describe the consequences of persistent HIF-1 over-activation in Caenorhabditis elegans.

Metazoan animals rely on oxygen for survival, but during normal development and homeostasis, animals are often challenged by hypoxia (low oxygen). In metazoans, many of the critical hypoxia responses are mediated by the evolutionarily conserved hypoxia-inducible transcription factors (HIFs). The stability and activity of HIF complexes are strictly regulated. In the model organism C. elegans, HIF-1 stability and activity are negatively regulated by VHL-1, EGL-9, RHY-1 and SWAN-1. Importantly, C. elegans mutants carrying strong loss-of-function mutations in these genes are viable, and this provides opportunities to interrogate the molecular consequences of persistent HIF-1 over-activation. We find that the genome-wide gene expression patterns are compellingly similar in these mutants, supporting models in which RHY-1, SWAN-1 and EGL-9 function in common pathway(s) to regulate HIF-1 activity. These studies illuminate the diversified biological roles played by HIF-1, including metabolism, hypoxia and other stress responses, reproduction and development. Genes regulated by persistent HIF-1 over-activation overlap with genes responsive to pathogens, and they overlap with genes regulated by DAF-16. As crucial stress regulators, HIF-1 and DAF-16 converge on key stress-responsive genes and function synergistically to enable hypoxia survival.

Temporal variation of mineralization rates and its influence on carbon storage over the last 50 years in Bohai Bay, China.

Recorded information on marine sediments is affected by mineralization. In this study, we collected sediment samples from Bohai Bay, where human interference is typically high. Overall, the CO2 fluxes in the columnar sediments decreased with increasing depth. The change in constants revealed a "C-curve" in which the mineralization rate first decreased significantly (i.e., from the 2020s to the 1980s) and subsequently increased slowly (i.e., from the 1980s to 1965). This may be explained by the fact that sediments from the 1980s-2020s were markedly influenced by the sedimentation rate, whereas sediments from the 1960s-1980s were predominantly influenced by microbial action. The loss of organic carbon due to mineralization accounted for approximately 15-20 % of the initial total organic carbon; therefore, when performing an inversion of the historical environment change using information derived from organic carbon in marine sediments, the influence of mineralization on this information should be fully considered.