Multiplexed representation of others in the hippocampal CA1 subfield of female mice.

Hippocampal place cells represent the position of a rodent within an environment. In addition, recent experiments show that the CA1 subfield of a passive observer also represents the position of a conspecific performing a spatial task. However, whether this representation is allocentric, egocentric or mixed is less clear. In this study we investigated the representation of others during free behavior and in a task where female mice learned to follow a conspecific for a reward. We found that most cells represent the position of others relative to self-position (social-vector cells) rather than to the environment, with a prevalence of purely egocentric coding modulated by context and mouse identity. Learning of a pursuit task improved the tuning of social-vector cells, but their number remained invariant. Collectively, our results suggest that the hippocampus flexibly codes the position of others in multiple coordinate systems, albeit favoring the self as a reference point.

Novel 15N Metabolic Labeling-Based Large-Scale Absolute Quantitative Proteomics Method for Corynebacterium glutamicum.

With fast growth, synthetic biology powers us with the capability to produce high commercial value products in an efficient resource/energy-consuming manner. Comprehensive knowledge of the protein regulatory network of a bacterial host chassis, e.g., the actual amount of the given proteins, is the key to building cell factories for certain target hyperproduction. Many talent methods have been introduced for absolute quantitative proteomics. However, for most cases, a set of reference peptides with isotopic labeling (e.g., SIL, AQUA, QconCAT) or a set of reference proteins (e.g., commercial UPS2 kit) needs to be prepared. The higher cost hinders these methods for large sample research. In this work, we proposed a novel metabolic labeling-based absolute quantification approach (termed nMAQ). The reference Corynebacterium glutamicum strain is metabolically labeled with 15N, and a set of endogenous anchor proteins of the reference proteome is quantified by chemically synthesized light (14N) peptides. The prequantified reference proteome was then utilized as an internal standard (IS) and spiked into the target (14N) samples. SWATH-MS analysis is performed to obtain the absolute expression levels of the proteins from the target cells. The cost for nMAQ is estimated to be less than 10 dollars per sample. We have benchmarked the quantitative performance of the novel method. We believe this method will help with the deep understanding of the intrinsic regulatory mechanism of C. glutamicum during bioengineering and will promote the process of building cell factories for synthetic biology.

Global Cellular Metabolic Rewiring Adapts Corynebacterium glutamicum to Efficient Nonnatural Xylose Utilization.

Xylose, the major component of lignocellulosic biomass, cannot be naturally or efficiently utilized by most microorganisms. Xylose (co)utilization is considered a cornerstone of efficient lignocellulose-based biomanufacturing. We evolved a rapidly xylose-utilizing strain, Cev2-18-5, which showed the highest reported specific growth rate (0.357 h-1) on xylose among plasmid-free Corynebacterium glutamicum strains. A genetically clear chassis strain, CGS15, was correspondingly reconstructed with an efficient glucose-xylose coutilization performance based on comparative genomic analysis and mutation reconstruction. With the introduction of a succinate-producing plasmid, the resulting strain, CGS15-SA1, can efficiently produce 97.1 g/L of succinate with an average productivity of 8.09 g/L/h by simultaneously utilizing glucose and xylose from corn stalk hydrolysate. We further revealed a novel xylose regulatory mechanism mediated by the endogenous transcription factor IpsA with global regulatory effects on C. glutamicum. A synergistic effect on carbon metabolism and energy supply, motivated by three genomic mutations (Psod(C131T)-xylAB, Ptuf(Δ21)-araE, and ipsAC331T), was found to endow C. glutamicum with the efficient xylose utilization and rapid growth phenotype. Overall, this work not only provides promising C. glutamicum chassis strains for a lignocellulosic biorefinery but also enriches the understanding of the xylose regulatory mechanism. IMPORTANCE A novel xylose regulatory mechanism mediated by the transcription factor IpsA was revealed. A synergistic effect on carbon metabolism and energy supply was found to endow C. glutamicum with the efficient xylose utilization and rapid growth phenotype. The new xylose regulatory mechanism enriches the understanding of nonnatural substrate metabolism and encourages exploration new engineering targets for rapid xylose utilization. This work also provides a paradigm to understand and engineer the metabolism of nonnatural renewable substrates for sustainable biomanufacturing.

Discrimination and quantification of homologous keratins from goat and sheep with dual protease digestion and PRM assays.

Mass spectrometry (MS) technology has a special advantage in species determination for protein-rich samples which requires identification of species-specific peptides. However, for species discrimination of highly homologous proteins, it remains challenging to select the species unique peptides with routine proteomics approaches. In this work, we chose keratins and keratin-associated proteins (KAPs) present in cashmere fibers from goat and wool fibers from sheep as targets, to develop a dual-protease digestion workflow based on in-silico and experimental analysis. Combined usage of Glu-C and trypsin proteases showed the best digestion performance for MS identification of keratins and KAPs from different species. The parallel reaction monitoring (PRM) technique was implemented to validate and quantify the selected species discriminable peptides. The fiber composition of both blended animal hair fibers and industrial textile fabrics were successfully determined with the PRM assay. Furthermore, we identified over 360 peptides from the cashmere fiber beyond the current Uniprot goat proteome database. We expect our new workflow would improve the identification and quantification of keratin and KAPs, and provide inspiration for distinguishing other highly homologous proteins. We also anticipate the set of species-specific peptides from keratin or KAPs validated in this work would benefit the quality assessment for industrial fiber materials and textile products. SIGNIFICANCE: Discriminating species from highly homologous proteins is challenging for MS-based shotgun proteomics. The large percentage of overlapped protein sequence hinders the identification of the species unique peptides. In this work, we aimed to discriminate sample species between goat and sheep from keratins and keratin-associated proteins (KAPs). A dedicated workflow was developed to boost the exposure and quantification of species discriminable peptides. The dual-proteases digestion approach was optimized based on amino acid sequence analysis and protein in-silico digestion analysis. The PRM assays were established to validate and quantify the selected species unique peptides. Additionally, we have identified about 360 novel candidate peptides complementary to the current goat protein sequence database. We expect our workflow would improve the species discrimination for highly homologous proteins and benefit the proteomics study of keratin and KAPs in the human proteome.

Distinct Proteome Remodeling of Industrial Saccharomyces cerevisiae in Response to Prolonged Thermal Stress or Transient Heat Shock.

To gain a deep understanding of yeast-cell response to heat stress, multiple laboratory strains have been intensively studied via genome-wide expression analysis for the mechanistic dissection of classical heat-shock response (HSR). However, robust industrial strains of Saccharomyces cerevisiae have hardly been explored in global analysis for elucidation of the mechanism of thermotolerant response (TR) during fermentation. Herein, we employed data-independent acquisition and sequential window acquisition of all theoretical mass spectra based proteomic workflows to characterize proteome remodeling of an industrial strain, ScY01, responding to prolonged thermal stress or transient heat shock. By comparing the proteomic signatures of ScY01 in TR versus HSR as well as the HSR of the industrial strain versus a laboratory strain, our study revealed disparate response mechanisms of ScY01 during thermotolerant growth or under heat shock. In addition, through proteomics data-mining for decoding transcription factor interaction networks followed by validation experiments, we uncovered the functions of two novel transcription factors, Mig1 and Srb2, in enhancing the thermotolerance of the industrial strain. This study has demonstrated that accurate and high-throughput quantitative proteomics not only provides new insights into the molecular basis for complex microbial phenotypes but also pinpoints upstream regulators that can be targeted for improving the desired traits of industrial microorganisms.

Parvalbumin and Somatostatin Interneurons Control Different Space-Coding Networks in the Medial Entorhinal Cortex.

The medial entorhinal cortex (MEC) contains several discrete classes of GABAergic interneurons, but their specific contributions to spatial pattern formation in this area remain elusive. We employed a pharmacogenetic approach to silence either parvalbumin (PV)- or somatostatin (SOM)-expressing interneurons while MEC cells were recorded in freely moving mice. PV-cell silencing antagonized the hexagonally patterned spatial selectivity of grid cells, especially in layer II of MEC. The impairment was accompanied by reduced speed modulation in colocalized speed cells. Silencing SOM cells, in contrast, had no impact on grid cells or speed cells but instead decreased the spatial selectivity of cells with discrete aperiodic firing fields. Border cells and head direction cells were not affected by either intervention. The findings point to distinct roles for PV and SOM interneurons in the local dynamics underlying periodic and aperiodic firing in spatially modulated cells of the MEC. VIDEO ABSTRACT.

2-Hydroxyisobutyrylation on histone H4K8 is regulated by glucose homeostasis in Saccharomyces cerevisiae.

New types of modifications of histones keep emerging. Recently, histone H4K8 2-hydroxyisobutyrylation (H4K8hib) was identified as an evolutionarily conserved modification. However, how this modification is regulated within a cell is still elusive, and the enzymes adding and removing 2-hydroxyisobutyrylation have not been found. Here, we report that the amount of H4K8hib fluctuates in response to the availability of carbon source in Saccharomyces cerevisiae and that low-glucose conditions lead to diminished modification. The removal of the 2-hydroxyisobutyryl group from H4K8 is mediated by the histone lysine deacetylase Rpd3p and Hos3p in vivo. In addition, eliminating modifications at this site by alanine substitution alters transcription in carbon transport/metabolism genes and results in a reduced chronological life span (CLS). Furthermore, consistent with the glucose-responsive H4K8hib regulation, proteomic analysis revealed that a large set of proteins involved in glycolysis/gluconeogenesis are modified by lysine 2-hydroxyisobutyrylation. Cumulatively, these results established a functional and regulatory network among Khib, glucose metabolism, and CLS.

Identification of Core-Fucosylated Glycoproteome in Human Plasma.

The core-fucosylated (CF) glycoproteins are widely distributed in mammalian tissues and regulated under pathological conditions, especially in cancer progression. The Food and Drug Administration (FDA) has approved the core-fucosylated α-fetoprotein as a biomarker for the early diagnosis of hepatocellular carcinoma (HCC). An approach for identifying CF glycoproteins has significantly practical value. Here we introduce a novel method for identification of CF glycoproteome in human plasma. The method integrates tandem glycopeptide enrichment, stepped fragmentation, and "glycan diagnostic ion"-based spectrum refinement. With this method, the productivity of identifying CF glycopeptides will be significantly improved. We anticipate that this method could be widely utilized to explore the CF glycoproteins and their regulation under physiological or pathological condition.

Optimization of Acquisition and Data-Processing Parameters for Improved Proteomic Quantification by Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectrometry.

Proteomic analysis with data-independent acquisition (DIA) approaches represented by the sequential window acquisition of all theoretical fragment ion spectra (SWATH) technique has gained intense interest in recent years because DIA is able to overcome the intrinsic weakness of conventional data-dependent acquisition (DDA) methods and afford higher throughout and reproducibility for proteome-wide quantification. Although the raw mass spectrometry (MS) data quality and the data-mining workflow conceivably influence the throughput, accuracy and consistency of SWATH-based proteomic quantification, there lacks a systematic evaluation and optimization of the acquisition and data-processing parameters for SWATH MS analysis. Herein, we evaluated the impact of major acquisition parameters such as the precursor mass range, isolation window width and accumulation time as well as the data-processing variables including peak extraction criteria and spectra library selection on SWATH performance. Fine tuning these interdependent parameters can further improve the throughput and accuracy of SWATH quantification compared to the original setting adopted in most SWATH proteomic studies. Furthermore, we compared the effectiveness of two widely used peak extraction software PeakView and Spectronaut in discovery of differentially expressed proteins in a biological context. Our work is believed to contribute to a deeper understanding of the critical factors in SWATH MS experiments and help researchers optimize their SWATH parameters and workflows depending on the sample type, available instrument and software.

Integrating MS1 and MS2 Scans in High-Resolution Parallel Reaction Monitoring Assays for Targeted Metabolite Quantification and Dynamic 13C-Labeling Metabolism Analysis.

Quantification of targeted metabolites, especially trace metabolites and structural isomers, in complex biological materials is an ongoing challenge for metabolomics. Initially developed for proteomic analysis, the parallel reaction monitoring (PRM) technique exploiting high-resolution MS2 fragment ion data has shown high promise for targeted metabolite quantification. Notably, MS1 ion intensity data acquired independently as part of each PRM scan cycle are often underutilized in the PRM assay. In this study, we developed an MS1/MS2-combined PRM workflow for quantification of central carbon metabolism intermediates, amino acids and shikimate pathway-related metabolites on an orthogonal QqTOF system. Concentration curve assessment revealed that exploiting both MS1 and MS2 scans in PRM analysis afforded higher sensitivity, wider dynamic range and better reproducibility than relying on either scan mode for quantification. Furthermore, Skyline was incorporated into our workflow to process the MS1/MS2 ion intensity data, and eliminate noisy signals and transitions with interferences. This integrated MS1/MS2 PRM approach was applied to targeted metabolite quantification in engineered E. coli strains for understanding of metabolic pathway modulation. In addition, this new approach, when first implemented in a dynamic 13C-labeling experiment, showed its unique advantage in capturing and correcting isotopomer labeling curves to facilitate nonstationary 13C-labeling metabolism analysis.

In-depth analysis of secretome and N-glycosecretome of human hepatocellular carcinoma metastatic cell lines shed light on metastasis correlated proteins.

Cancer cell metastasis is a major cause of cancer fatality. But the underlying molecular mechanisms remain incompletely understood, which results in the lack of efficient diagnosis, therapy and prevention approaches. Here, we report a systematic study on the secretory proteins (secretome) and secretory N-glycoproteins (N-glycosecretome) of four human hepatocellular carcinoma (HCC) cell lines with different metastatic potential, to explore the molecular mechanism of metastasis and supply the clues for effective measurement of diagnosis and therapy. Totally, 6242 unique gene products (GPs) and 1637 unique N-glycosites from 635 GPs were confidently identified. About 4000 GPs on average were quantified in each of the cell lines, 1156 of which show differential expression (p<0.05). Ninety-nine percentage of the significantly altered proteins were secretory proteins and proteins correlated to cell movement were significantly activated with the increasing of metastatic potential of the cell lines. Twenty-three GPs increased both in the secretome and the N-glycosecretome were chosen as candidates and verified by western blot analysis, and 10 of them were chosen for immunohistochemistry (IHC) analysis. The cumulative survival rates of the patients with candidate (FAT1, DKK3) suggested that these proteins might be used as biomarkers for HCC diagnosis. In addition, a comparative analysis with the published core human plasma database (1754 GPs) revealed that there were 182 proteins not presented in the human plasma database but identified by our studies, some of which were selected and verified successfully by western blotting in human plasma.

An NGS-Independent Strategy for Proteome-Wide Identification of Single Amino Acid Polymorphisms by Mass Spectrometry.

Detection of proteins containing single amino acid polymorphisms (SAPs) encoded by nonsynonymous SNPs (nsSNPs) can aid researchers in studying the functional significance of protein variants. Most proteogenomic approaches for large-scale SAPs mapping require construction of a sample-specific database containing protein variants predicted from the next-generation sequencing (NGS) data. Searching shotgun proteomic data sets against these NGS-derived databases allowed for identification of SAP peptides, thus validating the proteome-level sequence variation. Contrary to the conventional approaches, our study presents a novel strategy for proteome-wide SAP detection without relying on sample-specific NGS data. By searching a deep-coverage proteomic data set from an industrial thermotolerant yeast strain using our strategy, we identified 337 putative SAPs compared to the reference genome. Among the SAP peptides identified with stringent criteria, 85.2% of SAP sites were validated using whole-genome sequencing data obtained for this organism, which indicates high accuracy of SAP identification with our strategy. More interestingly, for certain SAP peptides that cannot be predicted by genomic sequencing, we used synthetic peptide standards to verify expression of peptide variants in the proteome. Our study has provided a unique tool for proteogenomics to enable proteome-wide direct SAP identification and capture nongenetic protein variants not linked to nsSNPs.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry.

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies.

Combining Untargeted and Targeted Proteomic Strategies for Discrimination and Quantification of Cashmere Fibers.

Cashmere is regarded as a specialty and luxury fiber due to its scarcity and high economic value. For fiber quality assessment, it is technically very challenging to distinguish and quantify the cashmere fiber from yak or wool fibers because of their highly similar physical appearance and substantial protein sequence homology. To address this issue, we propose a workflow combining untargeted and targeted proteomics strategies for selecting, verifying and quantifying biomarkers for cashmere textile authentication. Untargeted proteomic surveys were first applied to identify 174, 157, and 156 proteins from cashmere, wool and yak fibers, respectively. After marker selection at different levels, peptides turned out to afford much higher selectivity than proteins for fiber species discrimination. Subsequently, parallel reaction monitoring (PRM) methods were developed for ten selected peptide markers. The PRM-based targeted analysis of peptide markers enabled accurate determination of fiber species and cashmere percentages in different fiber mixtures. Furthermore, collective use of these peptide makers allowed us to discriminate and quantify cashmere fibers in commercial finished fabrics that have undergone heavy chemical treatments. Cashmere proportion measurement in fabric samples using our proteomic approach was in good agreement with results from traditional light microscopy, yet our method can be more readily standardized to become an objective and robust assay for assessing authenticity of fibers and textiles. We anticipate that the proteomic strategies presented in our study could be further implicated in discovery of quality trait markers for other products containing highly homologous proteomes.

[Analysis on traditional Chinese medicine prescriptions treating cancer based on traditional Chinese medicine inheritance assistance system and discovery of new prescriptions].

Malignant tumor is one of the main causes for death in the world at present as well as a major disease seriously harming human health and life and restricting the social and economic development. There are many kinds of reports about traditional Chinese medicine patent prescriptions, empirical prescriptions and self-made prescriptions treating cancer, and prescription rules were often analyzed based on medication frequency. Such methods were applicable for discovering dominant experience but hard to have an innovative discovery and knowledge. In this paper, based on the traditional Chinese medicine inheritance assistance system, the software integration of mutual information improvement method, complex system entropy clustering and unsupervised entropy-level clustering data mining methods was adopted to analyze the rules of traditional Chinese medicine prescriptions for cancer. Totally 114 prescriptions were selected, the frequency of herbs in prescription was determined, and 85 core combinations and 13 new prescriptions were indentified. The traditional Chinese medicine inheritance assistance system, as a valuable traditional Chinese medicine research-supporting tool, can be used to record, manage, inquire and analyze prescription data.

Hippocampal Remapping after Partial Inactivation of the Medial Entorhinal Cortex.

Hippocampal place cells undergo remapping when the environment is changed. The mechanism of hippocampal remapping remains elusive but spatially modulated cells in the medial entorhinal cortex (MEC) have been identified as a possible contributor. Using pharmacogenetic and optogenetic approaches, we tested the role of MEC cells by examining in mice whether partial inactivation in MEC shifts hippocampal activity to a different subset of place cells with different receptive fields. The pharmacologically selective designer Gi-protein-coupled muscarinic receptor hM4D or the light-responsive microbial proton pump archaerhodopsin (ArchT) was expressed in MEC, and place cells were recorded after application of the inert ligand clozapine-N-oxide (CNO) or light at appropriate wavelengths. CNO or light caused partial inactivation of the MEC. The inactivation was followed by substantial remapping in the hippocampus, without disruption of the spatial firing properties of individual neurons. The results point to MEC input as an element of the mechanism for remapping in place cells.

Strategy integrating stepped fragmentation and glycan diagnostic ion-based spectrum refinement for the identification of core fucosylated glycoproteome using mass spectrometry.

Core fucosylation (CF) is a special glycosylation pattern of proteins that has a strong relationship with cancer. The Food and Drug Administration (FDA) has approved the core fucosylated α-fetoprotein as a biomarker for the early diagnosis of hepatocellular carcinoma (HCC). The technology for identifying core fucosylated proteins has significant practical value. The major method for core fucosylated glycoprotein/glycopeptide analysis is neutral loss-based MS(3) scanning under collision-induced dissociation (CID) by ion trap mass spectrometry. However, due to the limited speed and low resolution of the MS(3) scan mode, it is difficult to achieve high-throughput, with only dozens of core fucosylated proteins identified in a single run. In this work, we developed a novel strategy for the identification of CF glycopeptides at a large scale, integrating the stepped fragmentation function, one novel feature of quadrupole-orbitrap mass spectrometry, with "glycan diagnostic ion"-based spectrum optimization. By using stepped fragmentation, we were able to obtain both highly accurate glycan and peptide information of a simplified CF glycopeptide in one spectrum. Moreover, the spectrum could be recorded with the same high speed as the conventional MS(2) scan. By using the "glycan diagnostic ion"-based spectrum refinement method, the efficiency of the CF glycopeptide discovery was significantly improved. We demonstrated the feasibility and reproducibility of our method by analyzing CF glycoproteomes of mouse liver tissue and HeLa cell samples spiked with standard CF glycoprotein. In total, 1364 and 856 CF glycopeptides belonging to 702 and 449 CF glycoproteins were identified, respectively, within a 78-min gradient analysis, which was approximately a 7-fold increase in the identification efficiency of CF glycopeptides compared to the currently used method. In this work, we took core fucosylated glycopeptides as a practical example to demonstrate the great potential of our novel method for use in glycoproteome analysis, and we also anticipate using the flexible novel method in other research fields.

Multivalent hydrazide-functionalized magnetic nanoparticles for glycopeptide enrichment and identification.

Among the common approaches for global glycopeptide enrichment, hydrazide chemistry is well recognized. However, conventional hydrazide-functionalized products are composed of a single layer of hydrazide functional groups. Due to the limited specific surface area of such a structure, the loading amount of hydrazide groups immobilized on these materials is restricted. Therefore, these materials can only provide a limited reaction rate with glycopeptides in complex protein samples, which is exacerbated by the microheterogeneities of glycosylation. Here, we introduce a new functionalized magnetic nanoparticle coating with hydrazide-modified non-crosslinked polymer chains. The multivalent hydrazide-functionalized particles were synthesized by the surface-initiated atom transfer radical polymerization (SI-ATRP) technique. The density of the hydrazide groups on the surface of these nanoparticles was three-fold higher than that of conventional single-layered materials. The new particles enabled the highly sensitive and selective enrichment of glycopeptides from a digestion mixture of fetuin, even from a background mixture of non-glycosylated protein that was 100-fold more abundant. The recovery ratio of glycopeptides was determined to be 77.8%, and the glycopeptide binding capacity of the materials was determined to be 25 µg mg(-1). Finally, the novel multivalent hydrazide-functionalized particles were applied in the enrichment of N-linked glycopeptides from mouse liver tissues, which resulted in the assignment of 511 unique glycopeptides belonging to 372 different glycoproteins. The results further demonstrated the potential of the multivalent particles for glycopeptide enrichment in complex proteomics samples.

[Study on in vitro release and percutaneous absorption for Zhitong cataplasm].

To evaluate in vitro release and transdermal behaviors of Zhitong cataplasm, modified Franz diffusion cell method was applied to investigate in vitro transdermal absorption of Zhitong cataplasm and the content of tetrahydropalmatine was determined by HPLC. In 24 hours, accumulative release rate of tetrahydropalmatine was 81. 9%, transmission rate was 2.26 microg x cm(-2) x h(-1). In 48 hours, accumulative transdermal rate and transmission rate of tetrahydropalmatine were 20.31%, 0.22 pg x cm(-2) x h(-1). So Zhitong cataplasm had a good release and transdermal properties and transdermal actions were consistent with zero-order kinetics process.