SCAG: A Stratified, Clustered, and Growing-Based Algorithm for Soybean Branch Angle Extraction and Ideal Plant Architecture Evaluation.

Three-dimensional (3D) phenotyping is important for studying plant structure and function. Light detection and ranging (LiDAR) has gained prominence in 3D plant phenotyping due to its ability to collect 3D point clouds. However, organ-level branch detection remains challenging due to small targets, sparse points, and low signal-to-noise ratios. In addition, extracting biologically relevant angle traits is difficult. In this study, we developed a stratified, clustered, and growing-based algorithm (SCAG) for soybean branch detection and branch angle calculation from LiDAR data, which is heuristic, open-source, and expandable. SCAG achieved high branch detection accuracy (F-score = 0.77) and branch angle calculation accuracy (r = 0.84) when evaluated on 152 diverse soybean varieties. Meanwhile, the SCAG outperformed 2 other classic algorithms, the support vector machine (F-score = 0.53) and density-based methods (F-score = 0.55). Moreover, after applying the SCAG to 405 soybean varieties over 2 consecutive years, we quantified various 3D traits, including canopy width, height, stem length, and average angle. After data filtering, we identified novel heritable and repeatable traits for evaluating soybean density tolerance potential, such as the ratio of average angle to height and the ratio of average angle to stem length, which showed greater potential than the well-known ratio of canopy width to height trait. Our work demonstrates remarkable advances in 3D phenotyping and plant architecture screening. The algorithm can be applied to other crops, such as maize and tomato. Our dataset, scripts, and software are public, which can further benefit the plant science community by enhancing plant architecture characterization and ideal variety selection.

Marginalized Augmented Few-Shot Domain Adaptation.

Domain adaptation (DA) has recently drawn a lot of attention, as it facilitates unlabeled target learning by borrowing knowledge from an external source domain. Most existing DA solutions seek to align feature representations between the labeled source and unlabeled target data. However, the scarcity of target data easily results in negative transfer, as it misleads the cross DA to the dominance of the source. To address the challenging few-shot domain adaptation (FSDA) problem, in this article, we propose a novel marginalized augmented FSDA (MAF) approach to address the cross-domain distribution disparity and insufficiency of target data simultaneously. On the one hand, cross-domain continuity augmentation (CCA) synthesizes abundant intermediate patterns across domains leading to a continuous domain-invariant latent space. On the other hand, sufficient source-supervised semantic augmentation (SSA) is explored to progressively diversify the conditional distribution within and across domains. Moreover, the proposed augmentation strategies are implemented efficiently via an expected transferable cross-entropy (CE) loss over the augmented distribution instead of explicit data synthesis, and minimizing the upper bound of the expected loss introduces negligible extra computing cost. Experimentally, our method outperforms the state of the art in various FSDA benchmarks, which demonstrates the effectiveness and contribution of our work. Our source code is provided at https://github.com/scottjingtt/MAF.git.

Generative Inference Network for Imbalanced Domain Generalization.

Domain generalization (DG) aims to learn transferable knowledge from multiple source domains and generalize it to the unseen target domain. To achieve such expectation, the intuitive solution is to seek domain-invariant representations via generative adversarial mechanism or minimization of cross-domain discrepancy. However, the widespread imbalanced data scale problem across source domains and category in real-world applications becomes the key bottleneck of improving generalization ability of model due to its negative effect on learning the robust classification model. Motivated by this observation, we first formulate a practical and challenging imbalance domain generalization (IDG) scenario, and then propose a straightforward but effective novel method generative inference network (GINet), which augments reliable samples for minority domain/category to promote discriminative ability of the learned model. Concretely, GINet utilizes the available cross-domain images from the identical category and estimates their common latent variable, which derives to discover domain-invariant knowledge for unseen target domain. According to these latent variables, our GINet further generates more novel samples with optimal transport constraint and deploys them to enhance the desired model with more robustness and generalization ability. Considerable empirical analysis and ablation studies on three popular benchmarks under normal DG and IDG setups suggests the advantage of our method over other DG methods on elevating model generalization. The source code is available in GitHub https://github.com/HaifengXia/IDG.

Maximum Structural Generation Discrepancy for Unsupervised Domain Adaptation.

Unsupervised domain adaptation (UDA) has recently become an appealing research topic in visual recognition, since it exploits all accessible well-labeled source data to train a model with high generalization on target domain without any annotations. However, due to the significant domain discrepancy, the bottleneck for UDA is to learn effective domain-invariant feature representations. To fight off such an obstacle, we propose a novel cross-domain learning framework named Maximum Structural Generation Discrepancy (MSGD) to accurately estimate and mitigate domain shift via introducing an intermediate domain. First, the cross-domain topological structure is explored to propagate target samples to generate a novel intermediate domain paired with the specific source instances. The intermediate domain plays as the bridge to gradually reduce distribution divergence across source and target domains. Concretely, the similar category semantic across source and intermediate features tends to naturally conduct the class-level alignment on eliminating their domain shift. In terms of no target annotation, the domain-level alignment manner is suitable to narrow down the distance between intermediate and target domains. Moreover, to produce high-quality generative instances, we develop the class-driven collaborative translation (CDCT) module to generate class-consistent cross-domain samples in each mini-batch with the assistance of pseudo-labels. Extensive experimental analyses on five domain adaptation benchmarks demonstrate the effectiveness of our MSGD on solving UDA problem.

Augmented Multimodality Fusion for Generalized Zero-Shot Sketch-Based Visual Retrieval.

Zero-shot sketch-based image retrieval (ZS-SBIR) has attracted great attention recently, due to the potential application of sketch-based retrieval under zero-shot scenarios, where the categories of query sketches and gallery photos are not observed in the training stage. However, it is still under insufficient exploration for the general and practical scenario when the query sketches and gallery photos contain both seen and unseen categories. Such a problem is defined as generalized zero-shot sketch-based image retrieval (GZS-SBIR), which is the focus of this work. To this end, we propose a novel Augmented Multi-modality Fusion (AMF) framework to generalize seen concepts to unobserved ones efficiently. Specifically, a novel knowledge discovery module named cross-domain augmentation is designed in both visual and semantic space to mimic novel knowledge unseen from the training stage, which is the key to handling the GZS-SBIR challenge. Moreover, a triplet domain alignment module is proposed to couple the cross-domain distribution between photo and sketch in visual space. To enhance the robustness of our model, we explore embedding propagation to refine both visual and semantic features by removing undesired noise. Eventually, visual-semantic fusion representations are concatenated for further domain discrimination and task-specific recognition, which tend to trigger the cross-domain alignment in both visual and semantic feature space. Experimental evaluations are conducted on popular ZS-SBIR benchmarks as well as a new evaluation protocol designed for GZS-SBIR from DomainNet dataset with more diverse sub-domains, and the promising results demonstrate the superiority of the proposed solution over other baselines. The source code is available at https://github.com/scottjingtt/AMF_GZS_SBIR.git.

Modification of C-segment of Cfa DnaE split intein for improving clean-in-place in chromatography process.

This research focuses on the construction of an affinity purification system based on Cfa DnaE split intein. Cfa DnaE intein is an artificially constructed intein with the advantages of a fast cleavage reaction and good stability. In a previous study, a purification system that uses Cfa intein as a tag was constructed, the separation of the target protein and the tag during the purification process was completed, and the purity of the purified target protein reached 98.21%. Guided by molecular docking results, we identified flexible regions in the split intein and inserted several glycines into the protein to decrease the stability of the Cfa IC , thereby improving the regenerability of the IN media. Inserting 6 glycines between amino acids 14 and 15 of IC improved the regeneration rate of IC -GFP on the column to approximately 96%.

Flexible FeVOx porous nanorods on carbon cloth for long-life aqueous energy storage.

We report the FeVOx porous nanorods on carbon cloth as a novel cathode material for flexible aqueous energy storage. It exhibits excellent electrochemical properties and cycling stability in supercapacitors and zinc-ion batteries. Moreover, this work makes significant progress for developing high-performance electrodes and provides a foundation for future research.

[Determination of eight organic residues in ion exchange resins by headspace gas chromatography].

An analytical method based on headspace gas chromatography was developed for the determination of eight organic residues in ion exchange resins, methyl isopropyl ketone, methyl butyrate, 3-pentanone, 1,3-diethyl benzene, 1,4-diethyl benzene, dichloroethane, 1,3-dichlorobenzene, and methyl methacrylate. The organic residues in different types of resins were studied to provide a basis for the safe use of ion-exchange resins in food and medicine. The main factors (chromatographic column, equilibrium temperature, equilibrium time, flow rate, etc.) that affect the accuracy and sensitivity of the eight organic residues were investigated during instrument analysis. The extraction solvent and chromatographic conditions for the samples were optimized. According to the extraction efficiencies of methyl benzene, methyl alcohol and dimethyl sulfoxide, 2.0 g of the sample was extracted with dimethyl sulfoxide under ultrasonic conditions at 20 ℃. A DB-23 chromatographic column (60 m×0.32 mm×0.25 µm) and hydrogen flame ionization detector (FID) were selected for the GC method, and good separation and quantitative results were obtained for the eight organic residues. The process and conditions are summarized as follows. The equilibration time of the headspace sampler was 30 min, and the equilibrium temperature was 80 ℃. The temperature of the sampler was 240 ℃, while that of the FID detector was 300 ℃, with nitrogen being used as the carrier gas. The programmed temperature of the column was maintained at 60 ℃ for 16 min, then increased to 200 ℃ at a heating rate of 20 ℃/min, and maintained at this level for 2 min. The flow rate was 1.2 mL/min for detection. The external standard method was utilized for quantitative analysis. Good linear relationships were observed for the eight organic residues, and the correlation coefficients (R2) were all above 0.999 in the mass concentration range of 0.02-200 mg/L. The limits of detection (LODs) were 0.0050-0.0375 ng/g. The average recoveries for the eight organic residues were in the range of 82.3% to 109.2% at three spiked levels, and the relative standard deviation (RSD, n=6) was 1.06% to 4.16%. Eleven types of resin samples were detected by this method, and a certain amount of organic compounds were observed in the resin samples. The methyl methacrylate content in the methacrylate resin XAD761 was 414.4 µg/g, while that in the styrene resin LX-69B was as high as 470.8 µg/g. As opposed to traditional analytical methods, the present method has high sensitivity, good accuracy, and precision, with simple operation without derivatization or the need for acid-base treatment of the sample to reduce contamination. This method can be used to simultaneously detect a variety of organic residues in ion-exchange resins, so that the detection efficiency is significantly improved.

FAM196B promotes proliferation and migration via regulating epithelial-mesenchymal transition in esophageal cancer.

BACKGROUND: EC (esophageal cancer) is a common cancer among people in the world. The molecular mechanism of FAM196B (family with sequence similarity 196 member B) in EC is still unclear. This article aimed to clarify the role of FAM196B in EC. METHODS: The expression of FAM196B in EC tissues was detected using qRT-PCR. The prognosis of FAM196B in EC patients was determined by log-rank kaplan-Meier survival analysis and Cox regression analysis. Furthermore, shRNA was used to knockdown the expression of FAM196B in EC cell lines. MTT, wound healing assays and western blot were used to determine the role of FAM196B in EC cells. RESULTS: In our research, we found that the expression of FAM196B was up-regulated in EC tissues. The increased expression of FAM196B was significantly correlated with differentiation, lymph node metastasis, stage, and poor survival. The proliferation and migration of EC cells were inhibited after FAM196B-shRNA transfection in vitro and vivo. The western blot result showed that FAM196B could regulate EMT. CONCLUSION: These results suggested that FAM196B severs as an oncogene and promotes cell proliferation and migration in EC. In addition, FAM196B may be a potential therapeutic target for EC patients.

Genetic mapping of northern corn leaf blight-resistant quantitative trait loci in maize.

Northern corn leaf blight (NCLB), a corn disease infected by Exserohilum turcicum, can cause loss of harvest and economy. Identification or evaluation of NCLB-resistant quantitative trait loci (QTL) and genes could improve maize breeds. This study aimed to identify novel QTLs for NCLB-resistance.Two maize strains (BB and BC) were utilized to generate B73 × B97 and B73 × CML322 and constructed the genetic linkage using high-throughput single nucleotide polymorphism (SNP) linkage map analysis of 170 (BB) and 163(BC) recombinant inbred line (RIL) genomic DNA samples. NCLB-resistant QTL was associated with phenotypic data from the field trial of 170 BB and 163 BC strains over two years using these 1100 SNPs to identify high-density NCLB-resistant QTLs.In BB, QTL of the NCLB resistance was on chromosome 1 and 3 (LOD scores between 2.74 and 5.44); in BC, QTL of NCLB resistance was on chromosome 1, 2, 4, 8, and 9 (LOD scores between 2.52 and 8.53). A number of genes or genetic information related to NCLB resistance in both BB and BC were identified with the maximum number of genes/NCLB resistance-related QTL on chromosome 3 for BB and on chromosome 1 for BC.This study successfully mapped and identified NCLB-resistant QTL and genes for these 2 different maize strains, which provides insightful information for future study of NCLB-resistance and selection of NCLB-resistant maize variants.

Improved protein purification system based on C-terminal cleavage of Npu DnaE split intein.

A purification system was constructed with the N-segment of the Npu DnaE split intein as an affinity ligand immobilized onto an epoxy-activated medium and the C-segment used as the cleavable tag fusing target protein. The affinity properties of C-tagged proteins adsorbed on IN affinity chromatography medium were studied with GFP as a model target protein. The saturated adsorption capacity and dynamic adsorption capacity reached 51.9-21.0 mg mL-1, respectively. With this system, two model proteins, GFP and alcohol dehydrogenase (ADH), has been successfully taglessly purified with regulation of Zn2+ and DTT. The yield, purification factor and purity of purified tagless GFP reached 39, 11.7 and 97%, respectively; while these values for purified tagless ADH were 38.2, 6.8 and 91%, respectively. These results showed that the system for Npu DnaE split intein-mediated affinity adsorption and in situ cleavage is a potential platform for recombinant protein production.

Co0.85Se@N-doped reduced graphene oxide hybrid polyhedron-in-polyhedron structure assembled from metal-organic framework with enhanced performance for Li-ion storage.

Structure control is widely admitted as a feasible strategy to restrain volume change and enhance electrical conductivity for chalcogenide anode materials. Herein, three-dimensionally hierarchical structure Co0.85Se@N-doped graphene hybrid is well-designed and synthesized by a facile hydrothermal strategy and post-calcination. It is noted that, owing to the nanoscale Kirkendall effect, the Co0.85Se nanograins derived from uniform zeolitic imidazolate framework (ZIF-67) precursor are incorporated into a polyhedron-in-polyhedron structure, which is consisted of in-situ formed amorphous carbon and interconnected pliable graphene nanosheets with enormous N-doping atoms. This unique dual-carbon protecting layers are beneficial to mitigate the volume expansion with high integrity, and facilitate the fast Li/electron transport with improved conductivity simultaneously, thus resulting in the superior Li-storage performance. As expected, the framework-controlled Co0.85Se@N-doped rGO composite demonstrates an outstanding cycling stability (787.7 mA h g-1 after 1000 cycles at 2 A g-1) and remarkable rate capability (400.8 mA h g-1 at ultrahigh rate of 10 A g-1). This work presents an enlightened strategy to design chalcogenide anode with desired nano-/microstructure by structure control and kinetic increase.

Composition and Architecture Design of Double-Shelled Co0.85 Se1- x Sx @Carbon/Graphene Hollow Polyhedron with Superior Alkali (Li, Na, K)-Ion Storage.

The exploration of materials with reversible and stable electrochemical performance is crucial in energy storage, which can (de) intercalate all the alkali-metal ions (Li+ , Na+ , and K+ ). Although transition-metal chalcogenides are investigated continually, the design and controllable preparation of hierarchical nanostructure and subtle composite withstable properties are still great challenges. Herein, component-optimal Co0.85 Se1- x Sx nanoparticles are fabricated by in situ sulfidization of metal organic framework, which are wrapped by the S-doped graphene, constructing a hollow polyhedron framework with double carbon shells (CoSSe@C/G). Benefiting from the synergistic effect of composition regulation and architecture design by S-substitution, the electrochemical kinetic is enhanced by the boosted electrochemistry-active sites, and the volume variation is mitigated by the designed structure, resulting in the advanced alkali-ion storage performance. Thus, it delivers an outstanding reversible capacity of 636.2 mAh g-1 at 2 A g-1 after 1400 cycles for Li-ion batteries. Remarkably, satisfactory initial charge capacities of 548.1 and 532.9 mAh g-1 at 0.1 A g-1 can be obtained for Na-ion and K-ion batteries, respectively. The prominent performance combined with the theory calculation confirms that the synergistic strategy can improve the alkali-ion transportation and structure stability, providing an instructive guide for designing high-performance anode materials for universal alkali-ion storage.

Corallincola holothuriorum sp. nov., a facultative anaerobe isolated from sea cucumber intestine.

Strain C4T, isolated from sea cucumber intestine in Weihai, Shandong, PR China, is a novel Gram-stain-negative, facultatively anaerobic, amphitrichously flagellated, short rod that grows as creamy white bacterial colonies on plates. Optimal growth of the strain was observed at 28-30 °C, pH 6.5-7.0 and at a concentration of 3 % NaCl. The G+C content of the genomic DNA was 49.0 mol%. Phylogenetic analysis based on the 16S rRNA gene sequence indicated that strain C4T is a member of the genus Corallincola and was most similar to Corallincola platygyrae JLT2006T. The major cellular fatty acids of strain C4T were C16 : 1ω7c/iso-C15 : 0 2-OH, C16 : 0 and C18 : 1ω7c. The sole respiratory quinone was Q-8. The predominant polar lipids in strain C4T were phosphatidylethanolamine, phosphatidylglycerol and an unidentified phospholipid. Based on morphology and physiological characteristics, strain C4T should be classified as a novel species in the genus Corallincola, for which Corallincolaholothuriorum is proposed. The type strain is C4T (=ATCC BAA-2611T=CICC 10839T).

Bizionia sediminis sp. nov., isolated from coastal sediment.

A Gram-stain-negative, aerobic, non-gliding, rod-shaped and orange-coloured bacterium, designated strain P131T, was isolated from marine sediment of the coast of Weihai, China, and subjected to a polyphasic study. Strain P131T was found to grow optimally at 28-30 °C, at pH 7.0-7.5 and in the presence of 2-3 % (w/v) NaCl. In a phylogenetic analysis based on 16S rRNA gene sequences, strain P131T was found to belong to the genus Bizionia and exhibited 94.6-97.0 % 16S rRNA gene sequence similarity with recognized Bizionia species. The dominant cellular fatty acids of strain P131T were identified as iso-C15 : 0, iso-C15 : 0 G, iso-C17 : 0 3-OH and iso-C17 : 1ω9c. The predominant polar lipids were phosphatidylethanolamine, phospholipid, two aminolipids and two unidentified lipids. The predominant respiratory quinone was menaquinone MK-6 and the DNA G+C content was 36.7 mol%. On the basis of the phylogenetic and phenotypic evidence presented, strain P131T represents a novel species of the genus Bizionia, for which the name Bizionia sediminis sp. nov. is proposed. The type strain is P131T (=KCTC 42587T=MCCC 1H00124T).

Aquimarina rubra sp. nov., isolated from sediment of a sea cucumber culture pond.

A Gram-stain-negative, non-motile, rod-shaped, red-pigmented, facultatively anaerobic bacterium, designated SS2-9T, was isolated from sediment collected from a sea cucumber culture pond located in Rongcheng, Shandong province, China. Cells of strain SS2-9T were approximately 0.3-0.5 µm in width and 1.5-6.0 µm in length. The strain was able to grow at 10-37 °C, at pH 6.5-8.5 and in the presence of 0.5-6.0 % (w/v) NaCl. It grew optimally at 28 °C and in the presence of 2.0 % (w/v) NaCl. The DNA G+C content was 34.5 mol% and the sole respiratory quinone was menaquinone 6 (MK-6). The predominant cellular fatty acids were C15 : 0, iso-C15 : 1 G, iso-C15 : 0 and iso-C17 : 0 3-OH. The major polar lipids were phosphatidylethanolamine, an unidentified phospholipid, two unidentified aminolipids and four unidentified lipids. Phylogenetic analyses based on 16S rRNA gene sequences revealed that strain SS2-9T was phylogenetically related to members of the genus Aquimarina and was closely related to Aquimarina amphilecti 92VT (97.29 % similarity). On the basis of phenotypic, chemotaxonomic and phylogenetic data, strain SS2-9T was considered to represent a novel species of the genus Aquimarina, for which the name Aquimarina rubra sp. nov. is proposed. The type strain is SS2-9T (=KCTC 52274T=MCCC 1H00142T).

PD-L1 over-expression is associated with a poor prognosis in Asian non-small cell lung cancer patients.

BACKGROUND: The prognostic role of programmed cell death-ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC) remains controversial. This meta-analysis was conducted to clarify the association of PD-L1 with survival in NSCLC patients. METHODS: Relevant studies were collected from PubMed, Embase and Web of Science. Only studies in which PD-L1 expression was detected by immunohistochemical staining in NSCLC patients correlated with patient survival data were included. Stata 12.0 was performed in this meta-analysis. RESULTS: Fifteen studies with 3116 patients were included in this meta-analysis. The combined hazard ratio (HR) of 1.18 (95%CI, 0.90-1.56; P>0.05) shows that PD-L1 over-expression in NSCLC patients didn't associate with overall survival (OS). However, subgroup analysis indicated that PD-L1 over-expression was correlated with poor OS in Asian patients (HR=1.84, 95%CI: 1.14-2.28; P<0.001). Moreover, the results suggested that a significant relationship between PD-L1 expression and OS was also showed in studies with late stage (HR=1.27, 95%CI: 1.06-1.48; P=0.031), poor tumor differentiation (HR=1.86, 95%CI: 1.35-2.64; P=0.001) and anaplastic lymphoma kinase (ALK) translocation (HR=2.58, 95%CI: 1.03-5.78; P=0.028). CONCLUSIONS: PD-L1 over-expression is correlated with a poor prognosis in Asian NSCLC patients.

The PDRG1 is an oncogene in lung cancer cells, promoting radioresistance via the ATM-P53 signaling pathway.

PDRG1, is short for P53 and DNA damage-regulated gene, which have been found over 10 years. Although severe studies have described the roles of PDRG1 separately in many kinds of tumors, how to act as an oncogene are unclear. To better verify the function of PDRG1 in lung cancer, both loss-function and gain-function of PDRG1 studies based on two human lung cancer lines were performed. Following the transfection of PDRG1, both A549 and 95-D cells showed significant changes in cell viability, the expression of some protein and apoptosis, which were all implied the PDRG1 is an oncogene. Another interesting finding is PDRG1 could promote radioresistance involved the ATM-p53 signaling pathway in lung cancer. If we combine radiotherapy with gene-targeted therapy together effectively, predominant effect may be acquired, which is a huge milestone in clinical cure about lung cancer.

Overexpression of VEGF-C correlates with a poor prognosis in esophageal cancer patients.

BACKGROUND: The prognostic value of vascular endothelial growth factor C (VEGF-C) in patients with esophageal cancer (EC) remains controversial. The aim of this meta-analysis was to clarify the association of VEGF-C with survival in EC patients. METHODS: We performed a meta-analysis that included eligible studies to expound the effect of VEGF-C in EC survival. Eligible studies published until November 2015 was identified using available databases. STATA 12.0 was performed in this meta-analysis. RESULTS: We identified 13 studies, including 1203 patients, in this meta-analysis. The combined hazard ratio of 1.70 (95% CI, 1.43-2.03, P < 0.001) shows that VEGF-C overexpression was significantly correlated with poor overall survival in EC patients. Furthermore, the results suggested a significant relationship between VEGF-C expression and overall survival was also showed in studies with patient source, patient number ≥ 70, methods detecting VEGF-C by reverse transcription PCR (RT-PCR) or ELISA and histology type. Moreover, combined odds ratio of VEGF-C displayed that VEGF-C overexpression was significantly association with stage, depth of tumor invasion, lymph node status and metastasis of EC (P < 0.05). However, it has no correlation with differentiation degree of EC (P > 0.05). CONCLUSION: VEGF-C overexpression shows an unfavorable prognosis for EC patients.

Mixed-mode chromatography integrated with high-performance liquid chromatography for protein analysis and separation: Using bovine serum albumin and lysozyme as the model target.

A type of mixed-mode chromatography was integrated with high-performance liquid chromatography for protein analysis and separation. The chromatographic behavior was tested using bovine serum albumin and lysozyme as model proteins. For the mixed-mode column, the silica beads were activated with γ-(2,3-epoxypropoxy)-propytrimethoxysilane and coupled with 4-mercaptopyridine as the functional ligand. The effects of pH, salt, and the organic solvent conditions of the mobile phase on the retention behavior were studied, which provided valuable clues for separation strategy. When eluted with a suitable pH gradient, salt concentration gradient, and acetonitrile content gradient, the separation behavior of bovine serum albumin and lysozyme could be controlled by altering the conditions of the mobile phase. The results indicated this type of chromatography might be a useful method for protein analysis and separation.