ABSTRACT
Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.
Subject(s)
Databases, Protein , Protein Processing, Post-Translational , Proteomics , Knowledge Bases , Mass Spectrometry , Single-Cell AnalysisABSTRACT
Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.
Subject(s)
Databases, Factual , Gene Expression Profiling , Single-Cell Analysis , TranscriptomeABSTRACT
Ribonucleic acids (RNAs) involve in various physiological/pathological processes by interacting with proteins, compounds, and other RNAs. A variety of powerful computational methods have been developed to predict such valuable interactions. However, all these methods rely heavily on the 'digitalization' (also known as 'encoding') of RNA-associated interacting pairs into a computer-recognizable descriptor. In other words, it is urgently needed to have a powerful tool that can not only represent each interacting partner but also integrate both partners into a computer-recognizable interaction. Herein, RNAincoder (deep learning-based encoder for RNA-associated interactions) was therefore proposed to (a) provide a comprehensive collection of RNA encoding features, (b) realize the representation of any RNA-associated interaction based on a well-established deep learning-based embedding strategy and (c) enable large-scale scanning of all possible feature combinations to identify the one of optimal performance in RNA-associated interaction prediction. The effectiveness of RNAincoder was extensively validated by case studies on benchmark datasets. All in all, RNAincoder is distinguished for its capability in providing a more accurate representation of RNA-associated interactions, which makes it an indispensable complement to other available tools. RNAincoder can be accessed at https://idrblab.org/rnaincoder/.
Subject(s)
Computational Biology , RNA , Computational Biology/methods , Deep Learning , Proteins/metabolism , RNA/genetics , RNA/metabolism , InternetABSTRACT
Corn leaf aphids (Rhopalosiphum maidis) are highly destructive pests of maize (Zea mays) that threaten growth and seed yield, but resources for aphid resistance are scarce. Here, we identified an aphid-resistant maize mutant, resistance to aphids 1 (rta1), which is allelic to LIGULELESS1 (LG1). We confirmed LG1's role in aphid resistance using the independent allele lg1-2, allelism tests and LG1 overexpression lines. LG1 interacts with, and increases the stability of ZINC-FINGER PROTEIN EXPRESSED IN INFLORESCENCE MERISTEM (ZIM1), a central component of the jasmonic acid (JA) signalling pathway, by disturbing its interaction with the F-box protein CORONATINE INSENSITIVE 1a (COI1a). Natural variation in the LG1 promoter was associated with aphid resistance among inbred lines. Moreover, a loss-of-function mutant in the LG1-related gene SPL8 in the dicot Arabidopsis thaliana conferred aphid resistance. This study revealed the aphid resistance mechanism of lg1, providing a theoretical basis and germplasm for breeding aphid-resistant crops.
ABSTRACT
MOTIVATION: With the rapid advances of RNA sequencing and microarray technologies in non-coding RNA (ncRNA) research, functional tools that perform enrichment analysis for ncRNAs are needed. On the one hand, because of the rapidly growing interest in circRNAs, snoRNAs, and piRNAs, it is essential to develop tools for enrichment analysis for these newly emerged ncRNAs. On the other hand, due to the key role of ncRNAs' interacting target in the determination of their function, the interactions between ncRNA and its corresponding target should be fully considered in functional enrichment. Based on the ncRNA-mRNA/protein-function strategy, some tools have been developed to functionally analyze a single type of ncRNA (the majority focuses on miRNA); in addition, some tools adopt predicted target data and lead to only low-confidence results. RESULTS: Herein, an online tool named RNAenrich was developed to enable the comprehensive and accurate enrichment analysis of ncRNAs. It is unique in (i) realizing the enrichment analysis for various RNA types in humans and mice, such as miRNA, lncRNA, circRNA, snoRNA, piRNA, and mRNA; (ii) extending the analysis by introducing millions of experimentally validated data of RNA-target interactions as a built-in database; and (iii) providing a comprehensive interacting network among various ncRNAs and targets to facilitate the mechanistic study of ncRNA function. Importantly, RNAenrich led to a more comprehensive and accurate enrichment analysis in a COVID-19-related miRNA case, which was largely attributed to its coverage of comprehensive ncRNA-target interactions. AVAILABILITY AND IMPLEMENTATION: RNAenrich is now freely accessible at https://idrblab.org/rnaenr/.
Subject(s)
COVID-19 , MicroRNAs , RNA, Long Noncoding , Humans , Animals , Mice , RNA, Untranslated/genetics , MicroRNAs/genetics , RNA, Long Noncoding/genetics , RNA, Small Nucleolar , RNA, Messenger/genetics , RNA, CircularABSTRACT
BACKGROUND: This study aimed to develop a risk prediction model for stress urinary incontinence (SUI) throughout pregnancy in Indonesian women. METHODS: We conducted a multicenter retrospective longitudinal study involving pregnant women in Indonesia, who sought care at obstetrics clinics from January 2023 to March 2023, encompassing all stages of pregnancy. We collected data on their predictive factors and SUI outcome. SUI was diagnosed based on responses to the "leaks when you are physically active/exercising" criterion in the ICIQ-UI-SF questionnaire during our investigation of the participants. The models underwent internal validation using a bootstrapping method with 1000 resampling iterations to assess discrimination and calibration. RESULTS: A total of 660 eligible pregnant women were recruited from the two study centers, with an overall SUI prevalence of 39% (258/660). The final model incorporated three predictive factors: BMI during pregnancy, constipation, and previous delivery mode. The area under the curve (AUROC) was 0.787 (95% CI: 0.751-0.823). According to the max Youden index, the optimal cut-off point was 44.6%, with a sensitivity of 79.9% and specificity of 65.9%. A discrimination slope of 0.213 was found. CONCLUSION: The developed risk prediction model for SUI in pregnant women offers a valuable tool for early identification and intervention among high-risk SUI populations in Indonesian pregnant women throughout their pregnancies. These findings challenge the assumption that a high BMI and multiple previous deliveries are predictors of SUI in Indonesian women. Further research is recommended to validate the model in diverse populations and settings.
Subject(s)
Urinary Incontinence, Stress , Female , Humans , Pregnancy , Urinary Incontinence, Stress/diagnosis , Urinary Incontinence, Stress/epidemiology , Indonesia/epidemiology , Retrospective Studies , Longitudinal Studies , Surveys and QuestionnairesABSTRACT
A deep-seated landslide could release numerous microseismic signals from creep-slip movement, which includes a rock-soil slip from the slope surface and a rock-soil shear rupture in the subsurface. Machine learning can effectively enhance the classification of microseismic signals in landslide seismic monitoring and interpret the mechanical processes of landslide motion. In this paper, eight sets of triaxial seismic sensors were deployed inside the deep-seated landslide, Jiuxianping, China, and a large number of microseismic signals related to the slope movement were obtained through 1-year-long continuous monitoring. All the data were passed through the seismic event identification mode, the ratio of the long-time average and short-time average. We selected 11 days of data, manually classified 4131 data into eight categories, and created a microseismic event database. Classical machine learning algorithms and ensemble learning algorithms were tested in this paper. In order to evaluate the seismic event classification performance of each algorithmic model, we evaluated the proposed algorithms through the dimensions of the accuracy, precision, and recall of each model. The validation results demonstrated that the best performing decision tree algorithm among the classical machine learning algorithms had an accuracy of 88.75%, while the ensemble algorithms, including random forest, Gradient Boosting Trees, Extreme Gradient Boosting, and Light Gradient Boosting Machine, had an accuracy range from 93.5% to 94.2% and also achieved better results in the combined evaluation of the precision, recall, and F1 score. The specific classification tests for each microseismic event category showed the same results. The results suggested that the ensemble learning algorithms show better results compared to the classical machine learning algorithms.
ABSTRACT
Neuromorphic vision has been attracting much attention due to its advantages over conventional machine vision (e.g., lower data redundancy and lower power consumption). Here we develop synaptic phototransistors based on the silicon nanomembrane (Si NM), which are coupled with lead sulfide quantum dots (PbS QDs) and poly(3-hexylthiophene) (P3HT) to form a heterostructure with distinct photogating. Synaptic phototransistors with optical stimulation have outstanding synaptic functionalities ranging from ultraviolet (UV) to near-infrared (NIR). The broadband synaptic functionalities enable an array of synaptic phototransistors to achieve the perception of brightness and color. In addition, an array of synaptic phototransistors is capable of simultaneous sensing, processing, and memory, which well mimics human vision.
ABSTRACT
During their co-evolution with herbivorous insects, plants have developed multiple defense strategies that resist pests, such as releasing a blend of herbivory-induced plant volatiles (HIPVs) that repel pests or recruit their natural enemies. However, the responses of insects to HIPVs in maize (Zea mays L.) are not well understood. Here, we demonstrate that the Asian corn borer (ACB, Ostrinia furnacalis), a major insect pest of maize, shows a preference for maize pre-infested with ACB larvae rather than being repelled by these plants. Through combined transcriptomic and metabolomics analysis of ACB-infested maize seedlings, we identified two substances that explain this behavior: (E)-4,8-dimethylnona-1,3,7-triene (DMNT) and (3E,7E)-4,8,12-trimethyltrideca-1,3,7,11-tetraene (TMTT). DMNT and TMTT attracted ACB larvae, and knocking out the maize genes responsible for their biosynthesis via gene editing impaired this attraction. External supplementation with DMNT/TMTT hampered the larvae's ability to locate pre-infested maize. These findings uncover a novel role for DMNT and TMTT in driving the behavior of ACB. Genetic modification of maize to make it less detectable by ACB might be an effective strategy for developing maize germplasm resistant to ACB and for managing this pest effectively in the field.
ABSTRACT
The newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2.75 and BA.2.76 subvariants contained 35 and 29 additional mutations in its spike (S) protein compared with the reference SARS-CoV-2 genome, respectively. Here, we measured the evasion degree of the BA.1, BA.2, BA.4, BA.5, BA.2.75, and BA.2.76 subvariants from neutralizing immunity in people previously infected with the Omicron BA.1 and BA.2, determined the effect of vaccination on immune evasion, and compared the titers of neutralizing antibodies in serums between acute infection and convalescence. Results showed that the neutralization effect of serums from patients with different vaccination statuses and BA.1/BA.2 breakthrough infection decreased with the Omicron evolution from BA.1 to BA.2, BA.4, BA.5, BA.2.75, and BA.2.76. This study also indicated that the existing vaccines could no longer provide effective protection, especially for the emerging BA.2.75 and BA.2.76 subvariants. Therefore, vaccines against emerging epidemic strains should be designed specifically. In the future, we can not only focus on the current strains, but also predict and design new vaccines against potential mutant strains. At the same time, we can combine the virus strains' infection characteristics to develop protective measures for virus colonization areas, such as nasal protection spray. Besides, further studies on the Y248N mutation of BA.2.76 subvariant were also necessary to explore its contribution to the enhanced immune evasion ability.
Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , Antibodies, Neutralizing , Antibodies, Viral , COVID-19/immunology , COVID-19/prevention & control , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Vaccination , COVID-19 Vaccines/immunologyABSTRACT
The lepidopteran crop pest Plutella xylostella causes severe constraints on Brassica cultivation. Here, we report a novel role for RPX1 (resistance to P. xylostella) in resistance to this pest in Arabidopsis thaliana. The rpx1-1 mutant repels P. xylostella larvae, and feeding on the rpx1-1 mutant severely damages the peritrophic matrix structure in the midgut of the larvae, thereby negatively affecting larval growth and pupation. This resistance results from the accumulation of defence compounds, including the homoterpene (3E)-4,8-dimethyl-1,3,7-nonatriene (DMNT), due to the upregulation of PENTACYCLIC TRITERPENE SYNTHASE 1 (PEN1), which encodes a key DMNT biosynthetic enzyme. P. xylostella infestation and wounding induce RPX1 protein degradation, which may confer a rapid response to insect infestation. RPX1 inactivation and PEN1 overexpression are not associated with negative trade-offs for plant growth but have much higher seed production than the wild-type in the presence of P. xylostella infestation. This study offers a new strategy for plant molecular breeding against P. xylostella.
Subject(s)
Arabidopsis , Brassica , Moths , Triterpenes , Animals , Arabidopsis/genetics , Moths/physiology , Larva/physiology , Triterpenes/metabolism , Brassica/metabolismABSTRACT
The corn leaf aphid (Rhopalosiphum maidis) is a major maize pest that frequently causes substantial yield losses. Exploring the genetic basis of resistance to aphids is important for improving maize yield and quality. Here, we used a maize recombinant inbred line population derived from two parents with different susceptibility to aphids, B73 (susceptible) and Abe2 (resistant), and performed quantitative trait locus (QTL) mapping using aphid resistance scores as an indicator. We mapped a stable QTL, qRTA6, to chromosome 6 using data from 2 years of field trials, which explained 40.12-55.17% of the phenotypic variation. To further investigate the mechanism of aphid resistance in Abe2, we constructed transcriptome and metabolome libraries from Abe2 and B73 leaves with or without aphid infestation at different time points. Integrating QTL mapping and transcriptome data revealed three aphid resistance candidate genes (Zm00001d035736, Zm00001d035751, and Zm00001d035767) associated with the hypersensitive response, the jasmonic acid pathway, and protein ubiquitination. Integrated transcriptomic and metabolomic analysis revealed that the differentially expressed genes and metabolites were enriched in flavonoid biosynthesis. These findings extend our understanding of the molecular mechanisms controlling aphid resistance in maize, and the QTL and candidate genes are valuable resources for increasing this resistance.
Subject(s)
Aphids , Animals , Aphids/physiology , Zea mays/genetics , Zea mays/metabolism , Quantitative Trait Loci , Multiomics , Plant Leaves/geneticsABSTRACT
Exploring cost-efficient/durability bifunctional electrocatalysts are of upmost importance for the practical application of metal-air batteries. However, preparing bifunctional electrocatalysts with the above three advantages remains conceptually challenging. This work reports the preparation of N-doped carbon confined NiCo alloy hollow spheres (NiCo@N-C HS) as bifunctional oxygen electrocatalyst for Zn-air battery with a higher energy density (788.7â mWh gZn -1 ) and outstanding cycling stability (over 200â h), which are more durable than the commercialized Pt/C+RuO2 -based device. Electrochemical results and theoretical calculation demonstrate that the synergy in the NiCo@N-C accelerates the electronic transmission for improving activation of O2 * and OH* intermediates and optimizing reacted free energy pathways, while the hollow structures exposure more active sites for improving the reaction kinetics and enhancing the activity of ORR/OER reaction. This work provides crucial understanding for constructing low-cost transition metal-based catalyst to overcome the efficiency and durability barriers of metal-air batteries for widespread applications.
ABSTRACT
Photobiomodulation (PBM) is the use of low irradiance light of specific wavelengths to generate physiological changes and therapeutic effects. However, there are few studies on the effects of PBM of different LED light modes on cells. Here, we investigated the difference of influence between continuous wave (CW) and pulse-PBM on B16F10 melanoma cells. Our results suggested that the pulse mode had a more significant PBM than the CW mode on B16F10 melanoma cells. Our study confirmed that ROS and Ca2+ levels in B16F10 melanoma cells treated with pulse-PBM were significantly higher than those in the control and CW-PBM groups. One mechanism that causes the difference in CW and pulse-PBM action is that pulse-PBM activates autophagy of melanoma cells through the ROS/OPN3/Ca2+ signaling pathway, and excessive autophagy activation inhibits proliferation and apoptosis of melanoma cells. Autophagy may be one of the reasons for the difference between pulse- and CW-PBM on melanoma cells. More importantly, melanoma cells responded to brief PBM pulses by increasing intracellular Ca2+ levels.
Subject(s)
Low-Level Light Therapy , Melanoma , Humans , Reactive Oxygen Species/metabolism , Signal Transduction , Autophagy , Melanoma/radiotherapy , Low-Level Light Therapy/methods , Rod OpsinsABSTRACT
BACKGROUND: Flowering time is an important agronomic trait of crops and significantly affects plant adaptation and seed production. Flowering time varies greatly among maize (Zea mays) inbred lines, but the genetic basis of this variation is not well understood. Here, we report the comprehensive genetic architecture of six flowering time-related traits using a recombinant inbred line (RIL) population obtained from a cross between two maize genotypes, B73 and Abe2, and combined with genome-wide association studies to identify candidate genes that affect flowering time. RESULTS: Our results indicate that these six traits showed extensive phenotypic variation and high heritability in the RIL population. The flowering time of this RIL population showed little correlation with the leaf number under different environmental conditions. A genetic linkage map was constructed by 10,114 polymorphic markers covering the whole maize genome, which was applied to QTL mapping for these traits, and identified a total of 82 QTLs that contain 13 flowering genes. Furthermore, a combined genome-wide association study and linkage mapping analysis revealed 17 new candidate genes associated with flowering time. CONCLUSIONS: In the present study, by using genetic mapping and GWAS approaches with the RIL population, we revealed a list of genomic regions and candidate genes that were significantly associated with flowering time. This work provides an important resource for the breeding of flowering time traits in maize.
Subject(s)
Genome-Wide Association Study , Zea mays , Chromosome Mapping/methods , Genetic Linkage , Genome-Wide Association Study/methods , Phenotype , Plant Breeding , Polymorphism, Single Nucleotide/genetics , Quantitative Trait Loci/genetics , Zea mays/geneticsABSTRACT
Twenty-two sesquiterpenoids (1-22) and 11 polyacetylenes (23-33) were obtained from the rhizomes of Atractylodes lancea. Among them, 11 compounds (1-5, 11, 12, 23, 24, 30, and 31) are new. The scaffolds represented by the isolates of sesquiterpenoids were found to be varied and included two rare rearranged spirovetivane sesquiterpenoids with a spiro [4,4] skeleton, eight spirovetivanes, three guaianes, eight eudesmanes, and one eremophilane. Their planar structures and relative configurations were elucidated by UV, IR, 1D and 2D NMR, and HRESIMS data analysis. The absolute configurations of the new sesquiterpenoids were determined using X-ray diffraction analysis and by comparison of the calculated and experimental electronic circular dichroism and optical rotation data, as well as chemical transformations. All the isolated compounds (1-33) were evaluated for their activity against RANKL-induced osteoclastogenesis in bone marrow macrophages. Two polyacetylene-type compounds, 25 and 32, showed potent activity with IC50 values of 1.3 and 0.64 µM, respectively. Rearranged spirovetivane sesquiterpenoids with a spiro [4,4] skeleton are reported herein from the genus Atractylodes for the first time. Polyacetylenes were demonstrated as the main active constituents of A. lancea with osteoclastogenesis inhibitory activity.
Subject(s)
Atractylodes , Sesquiterpenes , Atractylodes/chemistry , Molecular Structure , Osteogenesis , Polyynes/chemistry , Polyynes/pharmacology , Rhizome/chemistry , Sesquiterpenes/chemistryABSTRACT
Photobiomodulation (PBM) uses low-intensity visible or near-infrared light to produce beneficial effects on cells or tissues, such as brain therapy, wound healing. Still there is no consistent recommendation on the parameters (dose, light mode, wavelength, irradiance) and protocols (repetition, treatment duration) for its clinical application. Herein, we summarize the current PBM parameters for the treatment of melanoma, and we also discuss the potential photoreceptors and downstream signaling mechanisms in the PBM treatment of melanoma cells. It is hypothesized that PBM may inhibit the melanoma cells by activating mitochondria, OPNs, and other receptors. Regardless of the underlying mechanisms, PBM has been shown to be beneficial in treating melanoma. Through further in-depth studies of the underlying potential mechanisms, it can strengthen the applications of PBM for the therapy of melanoma.
Subject(s)
Low-Level Light Therapy , Melanoma , Humans , Infrared Rays , Melanoma/radiotherapy , Signal Transduction , Wound HealingABSTRACT
KEY MESSAGE: A novel genomic region controlling thermotolerance at flowering was identified by the combination of whole genomic re-sequencing and bulked segregant analysis in maize. The increasing frequency of extreme high temperature has brought a great threat to the development of maize throughout its life cycle, especially during the flowering phase. However, the genetic basis of thermotolerance at flowering in maize remains poorly understood. Here, we characterized a thermotolerant maize ecotype Abe2 and dissected its genetic basis using a F2:8 recombinant inbred line (RIL) population generated from a cross between Abe2 and B73. After continuous high temperature stress above 35 °C for 17 days, Abe2 and B73 show distinct leaf scorching phenotype under field conditions. To identify the genomic regions associated with the phenotypic variation, we applied a combination of whole genomic re-sequencing and bulked segregant analysis, and revealed 10,316,744 SNPs and 1,488,302 InDels between the two parental lines, and 2,693,054 SNPs and 313,757 InDels between the two DNA pools generated from the thermos-tolerant and the sensitive individuals of the RIL, of which, 108,655 and 17,853 SNPs may cause nonsynonymous variations. Finally, a 7.41 Mb genomic region on chromosome 1 was identified, and 7 candidate genes were annotated to participate in high temperature-related stress response. A candidate gene Zm00001d033339 encoding a serine/threonine protein kinase was proposed to be the most likely causative gene contributing to the thermotolerance at flowering by involving in stomatal movement (GO: 0010119) via Abscisic acid (ABA) pathway (KO04075). This work could provide an opportunity for gene cloning and pyramiding breeding to improve thermotolerance at flowering in maize.
Subject(s)
Flowers/physiology , Genome, Plant , Thermotolerance , Zea mays/genetics , INDEL Mutation , Phenotype , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Whole Genome Sequencing , Zea mays/physiologyABSTRACT
Some mutations which occur in the α/ß-discordant region (resides 15 to 23) of ß-amyloid peptide (Aß) lead to familial Alzheimer's disease (FAD). In vitro studies have shown that these genetic mutations could accelerate Aß aggregation. We recently showed that mutations in this region could alter the structural propensity, resulting in a different aggregative propensity of Aß. Whether these genetic mutations display similar effects remains largely unknown. Here, we characterized the structural propensity and aggregation kinetics of Dutch-type Aß40 (Aß40(E22Q)) and its L17A/F19A-substituted mutant (Aß40(L17A/F19A/E22Q)) using circular dichroism spectroscopy, nuclear magnetic spectroscopy, and thioflavin T fluorescence assay. In comparison with wild-type Aß40, we found that Dutch-type mutation, unlike Artic-type mutation (E22G), does not reduce the α-helical propensity of the α/ß-discordant region in sodium dodecyl sulfate micellar solution. Moreover, we found that Aß40(L17A/F19A/E22Q) displays a higher α-helical propensity of the α/ß-discordant region and a slower aggregation rate than Aß40(E22Q), suggesting that the inhibition of aggregation might be via increasing the α-helical propensity of the α/ß-discordant region, similar to that observed in wild-type and Artic-type Aß40. Taken together, Dutch-type and Artic-type mutations adopt different mechanisms to promote Aß aggregation, however, the L17A/F19A mutation could increase the α-helical propensities of both Dutch-type and Artic-type Aß40 and inhibit their aggregation.
Subject(s)
Amino Acid Substitution/genetics , Amyloid beta-Peptides/chemistry , Amyloid beta-Peptides/genetics , Peptide Fragments/genetics , Alzheimer Disease/genetics , Humans , Mutation/genetics , Peptide Fragments/chemistry , Protein Structure, Secondary/genetics , Sodium Dodecyl Sulfate/chemistryABSTRACT
A simple and sensitive method for simultaneous determination of furan and vinyl acetate (VA) in vapor phase of mainstream cigarette smoke with cold trap and gas chromatography-mass spectrometry (GC-MS) was developed. A Cambridge filter pad (CFP) was placed in front of the impingers of smoking machine to remove the particle phase from cigarette smoke. Furan and VA in vapor phase of mainstream cigarette smoke were collected in two impingers connected in series by filled with methanol at -78°C. The solutions were added with deuterium-labeled furan-d4 and VA-d6 as internal standards and analyzed by GC-MS. The results showed that the calibration curves for furan and VA were linear (r2 > 0.9995) over the studied concentration range. The intra- and inter-day precision values for furan and VA were <7.07% and <9.62%, respectively. The extraction recoveries of furan and VA were in the range of 94.5-97.7% and 92.3-94.9%, respectively. Moreover, the limits of detection for furan and VA were 0.028 µg mL-1 and 1.3 ng mL-1, respectively. The validated method has been successfully applied to determine the emissions of furan and VA in the vapor phase of mainstream cigarette smoke under International Organization for Standardization (ISO) and Canadian Intense (CI) smoking regimen.