Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review.

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Identification, rapid screening, docking mechanism and in vitro digestion stability of novel DPP-4 inhibitory peptides from wheat gluten with ginger protease.

To better understand the hypoglycemic potential of wheat gluten (WG), we screened dipeptidyl peptidase IV (DPP-4) inhibitory active peptides from WG hydrolysates. WG hydrolysates prepared by ginger protease were found to have the highest DPP-4 inhibitory activity among the five enzymatic hydrolysates, from which a 1-3 kDa fraction was isolated by ultrafiltration. Further characterization of the fraction with nano-HPLC-MS/MS revealed 1133 peptides. Among them, peptides with P'2 (the second position of the N-terminal) and P2 (the second position of the C-terminal) as proline residues (Pro) accounted for 12.44% and 43.69%, respectively. The peptides including Pro-Pro-Phe-Ser (PPFS), Ala-Pro-Phe-Gly-Leu (APFGL), and Pro-Pro-Phe-Trp (PPFW) exhibited the most potent DPP-4 inhibitory activity with IC50 values of 56.63, 79.45, and 199.82 µM, respectively. The high inhibitory activity of PPFS, APFGL, and PPFW could be mainly attributed to their interaction with the S2 pocket (Glu205 and Glu206) and the catalytic triad (Ser630 and His740) of DPP-4, which adopted competitive, mixed, and mixed inhibitory modes, respectively. After comparative analysis of PPFS, PPFW, and PPF, Ser was found to be more conducive to enhancing the DPP-4 inhibitory activity. Interestingly, peptides with P2 as Pro also exhibited good DPP-4 inhibitory activity. Meanwhile, DPP-4 inhibitory peptides from WG showed excellent stability, suggesting a potential application in type 2 diabetes (T2DM) therapy or in the food industry as functional components.

Characterization of mung bean endogenous proteases and globulins and their effects on the production of mung bean protein.

Mung bean protein possesses several health benefits, and aqueous processing methods are used for its production. However, mung bean protein yields are different with different methods, which are actually different in conditions (e.g., pH, temperature, and time). Herein, liquid chromatography tandem mass spectrometry identified 28 endopeptidases and exopeptidases in mung bean protein extract, and the positions of 8S and 11S globulins on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel were confirmed in our experimental conditions. The SDS-PAGE, trichloroacetic acid-nitrogen solubility index, and free amino acid analysis revealed that (1) 8S globulins showed strong resistance to the endopeptidases (optimal at pH 5 and 50 °C) at pH 3-9, and 11S globulin exhibit strong resistance expect at pH 3-3.5; (2) the exopeptidases (optimal at pH 6 and 50 °C) preferred to liberate methionine and tryptophan. These proteases negatively affected protein yield, and short production time and low temperature were recommended.

Cascading climate effects in deep reservoirs: Full assessment of physical and biogeochemical dynamics under ensemble climate projections and ways towards adaptation.

We coupled twenty-first century climate projections with a well-established water quality model to depict future ecological changes of Rappbode Reservoir, Germany. Our results document a chain of climate-driven effects propagating through the aquatic ecosystem and interfering with drinking water supply: intense climate warming (RCP8.5 scenario) will firstly trigger a strong increase in water temperatures, in turn leading to metalimnetic hypoxia, accelerating sediment nutrient release and finally boosting blooms of the cyanobacterium Planktothrix rubescens. Such adverse water quality developments will be suppressed under RCP2.6 and 6.0 indicating that mitigation of climate change is improving water security. Our results also suggested surface withdrawal can be an effective adaptation strategy to make the reservoir ecosystem more resilient to climate warming. The identified consequences from climate warming and adaptation strategies are relevant to many deep waters in the temperate zone, and the conclusion should provide important guidances for stakeholders to confront potential climate changes.

Lipid metabolism as a target for cancer drug resistance: progress and prospects.

Cancer is the world's leading cause of human death today, and the treatment process of cancer is highly complex. Chemotherapy and targeted therapy are commonly used in cancer treatment, and the emergence of drug resistance is a significant problem in cancer treatment. Therefore, the mechanism of drug resistance during cancer treatment has become a hot issue in current research. A series of studies have found that lipid metabolism is closely related to cancer drug resistance. This paper details the changes of lipid metabolism in drug resistance and how lipid metabolism affects drug resistance. More importantly, most studies have reported that combination therapy may lead to changes in lipid-related metabolic pathways, which may reverse the development of cancer drug resistance and enhance or rescue the sensitivity to therapeutic drugs. This paper summarizes the progress of drug design targeting lipid metabolism in improving drug resistance, and providing new ideas and strategies for future tumor treatment. Therefore, this paper reviews the issues of combining medications with lipid metabolism and drug resistance.

Modeling the Functional Network for Spatial Navigation in the Human Brain.

Spatial navigation is a complex function involving the integration and manipulation of multisensory information. Using different navigation tasks, many promising results have been achieved on the specific functions of various brain regions (e.g., hippocampus, entorhinal cortex, and parahippocampal place area). Recently, it has been suggested that a non-aggregate network process involving multiple interacting brain regions may better characterize the neural basis of this complex function. This paper presents an integrative approach for constructing and analyzing the functionally-specific network for spatial navigation in the human brain. Briefly, this integrative approach consists of three major steps: 1) to identify brain regions important for spatial navigation (nodes definition); 2) to estimate functional connectivity between each pair of these regions and construct the connectivity matrix (network construction); 3) to investigate the topological properties (e.g., modularity and small worldness) of the resulting network (network analysis). The presented approach, from a network perspective, could help us better understand how our brain supports flexible navigation in complex and dynamic environments, and the revealed topological properties of the network can also provide important biomarkers for guiding early identification and diagnosis of Alzheimer's disease in clinical practice.

TLR8 aggravates skin inflammation and fibrosis by activating skin fibroblasts in systemic sclerosis.

OBJECTIVES: Innate immunity significantly contributes to systemic sclerosis (SSc) pathogenesis. TLR8 is an important innate immune mediator that is implicated in autoimmunity and fibrosis. However, the expression, mechanism of action, and pathogenic role of TLR8 in SSc remain unclear. The aim of this study was to explore the roles and underlying mechanisms of TLR8 in SSc. METHODS: The expression of TLR8 was analyzed based on a public dataset and then verified in skin tissues and skin fibroblasts of SSc patients. The role of TLR8 in inflammation and fibrosis was investigated using a TLR8-overexpression vector, activator (VTX-2337), inhibitor (cu-cpt-8m), and TLR8 siRNA in skin fibroblasts. The pathogenic role of TLR8 in skin inflammation and fibrosis was further validated in a bleomycin (BLM)-induced mouse skin inflammation and fibrosis model. RESULTS: TLR8 levels were significantly elevated in SSc skin tissues and myofibroblasts, along with significant activation of the TLR8 pathway. In vitro studies showed that overexpression or activation of TLR8 by a recombinant plasmid or VTX-2337 upregulated IL-6, IL-1ß, COL I, COL III, and α-SMA in skin fibroblasts. Consistently, both TLR8-siRNA and cu-cpt-8m reversed the phenotypes observed in TLR8-activating fibroblasts. Mechanistically, TLR8 induces skin fibrosis and inflammation in a manner dependent on the MAPK, NF-κB, and SMAD2/3 pathways. Subcutaneous injection of cu-cpt-8m significantly alleviated BLM-induced skin inflammation and fibrosis in vivo. CONCLUSION: TLR8 might be a promising therapeutic target to improve the treatment strategy for SSc skin inflammation and fibrosis.

Complexity analysis of electrical activity during endocardial and epicardial biventricular mapping of ventricular fibrillation.

BACKGROUND: Ventricular fibrillation (VF) is a lethal cardiac arrhythmia that is a significant cause of sudden cardiac death. Comprehensive studies of spatiotemporal characteristics of VF in situ are difficult to perform with current mapping systems and catheter technology. OBJECTIVE: The goal of this study was to develop a computational approach to characterize VF using a commercially available technology in a large animal model. Prior data suggests that characterization of spatiotemporal organization of electrical activity during VF can be used to provide better mechanistic understanding and potential ablation targets to modify VF and its substrate. We therefore evaluated intracardiac electrograms during biventricular mapping of the endocardium (ENDO) and epicardium (EPI) in acute canine studies. METHODS: To develop thresholds for organized and disorganized activity, a linear discriminant analysis (LDA)-based approach was performed to the known organized and disorganized activities recorded in ex vivo Langendorff-perfused rat and rabbit hearts using optical mapping experiments. Several frequency- and time-domain approaches were used as individual and paired features to identify the optimal thresholds for the LDA approach. Subsequently, VF was sequentially mapped in 4 canine hearts, using the CARTO mapping system with a multipolar mapping catheter in the ENDO left and right ventricles and EPI to capture the progression of VF at 3 discrete post-induction time intervals: VF period 1 (just after induction of VF to 15 min), VF period 2 (15 to 30 min), and VF period 3 (30 to 45 min). The developed LDA model, cycle lengths (CL), and regularity indices (RI) were applied to all recorded intracardiac electrograms to quantify the spatiotemporal organization of VF in canine hearts. RESULTS: We demonstrated the presence of organized activity in the EPI as VF progresses, in contrary to the ENDO, where the activity stays disorganized. The shortest CL always occurred in the ENDO, especially the RV, indicating a faster VF activity. The highest RI was found in the EPI in all hearts for all VF stages, indicating spatiotemporal consistency of RR intervals. CONCLUSION: We identified electrical organization and spatiotemporal differences throughout VF in canine hearts from induction to asystole. Notably, the RV ENDO is characterized by a high level of disorganization and faster VF frequency. In contrast, EPI has a high spatiotemporal organization of VF and consistently long RR intervals.

A New Binary Biclustering Algorithm Based on Weight Adjacency Difference Matrix for Analyzing Gene Expression Data.

Biclustering algorithms are essential for processing gene expression data. However, to process the dataset, most biclustering algorithms require preprocessing the data matrix into a binary matrix. Regrettably, this type of preprocessing may introduce noise or cause information loss in the binary matrix, which would reduce the biclustering algorithm's ability to effectively obtain the optimal biclusters. In this paper, we propose a new preprocessing method named Mean-Standard Deviation (MSD) to resolve the problem. Additionally, we introduce a new biclustering algorithm called Weight Adjacency Difference Matrix Binary Biclustering (W-AMBB) to effectively process datasets containing overlapping biclusters. The basic idea is to create a weighted adjacency difference matrix by applying weights to a binary matrix that is derived from the data matrix. This allows us to identify genes with significant associations in sample data by efficiently identifying similar genes that respond to specific conditions. Furthermore, the performance of the W-AMBB algorithm was tested on both synthetic and real datasets and compared with other classical biclustering methods. The experiment results demonstrate that the W-AMBB algorithm is significantly more robust than the compared biclustering methods on the synthetic dataset. Additionally, the results of the GO enrichment analysis show that the W-AMBB method possesses biological significance on real datasets.

Clinical diagnostic value of amino acids in laryngeal squamous cell carcinomas.

Background: Early diagnosis and treatment can improve the survival rates of patients with laryngeal squamous cell carcinoma (LSCC). Therefore, it is necessary to discover new biomarkers for laryngeal cancer screening and early diagnosis. Methods: We collected fasting plasma from LSCC patients and healthy volunteers, as well as cancer and para-carcinoma tissues from LSCC patients, and performed quantitative detection of amino acid levels using liquid chromatography-mass spectrometry. We used overall analysis and multivariate statistical analysis to screen out the statistically significant differential amino acids in the plasma and tissue samples, conducted receiver operating characteristic (ROC) analysis of the differential amino acids to evaluate the sensitivity and specificity of the differential amino acids, and finally determined the diagnostic value of amino acids for laryngeal cancer. Additionally, we identified amino acids in the plasma and tissue samples that are valuable for the early diagnosis of laryngeal cancer classified according to the tumor-node-metastasis (TNM) classification. Results: Asparagine (Asp) and homocysteine (Hcy) were two amino acids of common significance in plasma and tissue samples, and their specificity and sensitivity analysis showed that they may be new biomarkers for the diagnosis and treatment of LSCC. According to the TNM staging system, phenylalanine (Phe) and isoleucine (Ile) were screened out in the plasma of LSCC patients at early (I and II) and advanced (III and IV) stages; ornithine hydrochloride (Orn), glutamic acid (Glu), and Glycine (Gly) were selected in the tissue. These dysregulated amino acids found in LSCC patients may be useful as clinical biomarkers for the early diagnosis and screening of LSCC.

Significant heterogeneity in structural asymmetry of the habenula in the human brain: A systematic review and meta-analysis.

Understanding the evolutionarily conserved feature of functional laterality in the habenula has been attracting attention due to its potential role in human cognition and neuropsychiatric disorders. Deciphering the structure of the human habenula remains to be challenging, which resulted in inconsistent findings for brain disorders. Here, we present a large-scale meta-analysis of the left-right differences in the habenular volume in the human brain to provide a clearer picture of the habenular asymmetry. We searched PubMed, Web of Science, and Google Scholar for articles that reported volume data of the bilateral habenula in the human brain, and assessed the left-right differences. We also assessed the potential effects of several moderating variables including the mean age of the participants, magnetic field strengths of the scanners and different disorders by using meta-regression and subgroup analysis. In total 52 datasets (N = 1427) were identified and showed significant heterogeneity in the left-right differences and the unilateral volume per se. Moderator analyses suggested that such heterogeneity was mainly due to different MRI scanners and segmentation approaches used. While inversed asymmetry patterns were suggested in patients with depression (leftward) and schizophrenia (rightward), no significant disorder-related differences relative to healthy controls were found in either the left-right asymmetry or the unilateral volume. This study provides useful data for future studies of brain imaging and methodological developments related to precision habenula measurements, and also helps to further understand potential roles of the habenula in various disorders.

KGLRR: A low-rank representation K-means with graph regularization constraint method for Single-cell type identification.

Single-cell RNA sequencing technology provides a tremendous opportunity for studying disease mechanisms at the single-cell level. Cell type identification is a key step in the research of disease mechanisms. Many clustering algorithms have been proposed to identify cell types. Most clustering algorithms perform similarity calculation before cell clustering. Because clustering and similarity calculation are independent, a low-rank matrix obtained only by similarity calculation may be unable to fully reveal the patterns in single-cell data. In this study, to capture accurate single-cell clustering information, we propose a novel method based on a low-rank representation model, called KGLRR, that combines the low-rank representation approach with K-means clustering. The cluster centroid is updated as the cell dimension decreases to better from new clusters and improve the quality of clustering information. In addition, the low-rank representation model ignores local geometric information, so the graph regularization constraint is introduced. KGLRR is tested on both simulated and real single-cell datasets to validate the effectiveness of the new method. The experimental results show that KGLRR is more robust and accurate in cell type identification than other advanced algorithms.

Functional dysconnectivity of anterior cingulate subregions in schizophrenia and psychotic and nonpsychotic bipolar disorder.

Aberrant resting-state functional connectivity (FC) of anterior cingulate cortex (ACC) has been implicated in the pathophysiology of schizophrenia and bipolar disorder (BP). This study investigated the subregional FC of ACC across schizophrenia and psychotic (PBP) and nonpsychotic BP (NPBP) and the relationship between brain functional alterations and clinical manifestations. A total of 174 first-episode medication-naive patients with schizophrenia (FES), 80 patients with PBP, 77 patients with NPBP and 173 demographically matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Brain-wide FC of ACC subregions was computed for each individual, and compared between the groups. General intelligence was evaluated using the short version of the Wechsler Adult Intelligence Scale. Relationships between FC and various clinical and cognitive variables were estimated using the skipped correlation. The FES, PBP and NPBP groups showed differing connectivity patterns in the left caudal, dorsal and perigenual ACC. Transdiagnostic dysconnectivity was found in the subregional ACC associated with cortical, limbic, striatal and cerebellar regions. Disorder-specific dysconnectivity in FES was identified between the left perigenual ACC and bilateral orbitofrontal cortex, and the left caudal ACC coupling with the default mode network (DMN) and visual processing region was correlated with psychotic symptoms. In the PBP group, FC between the left dorsal ACC and the right caudate was correlated with psychotic symptoms, and FC connected with the DMN was associated with affective symptoms. The current findings confirmed that subregional ACC dysconnectivity could be a key transdiagnostic feature and associated with differing clinical symptomology across schizophrenia and PBP.

Sudden eutrophication of an aluminum sulphate treated lake due to abrupt increase of internal phosphorus loading after three decades of mesotrophy.

Aluminum salts are widely used to immobilize phosphorus (P) in lakes suffering from internal loading. However, longevity of treatments varies among lakes; some lakes eutrophy faster than others. We conducted biogeochemical investigations of sediments of a closed artificial Lake Barleber, Germany that was successfully remediated with aluminum sulfate in 1986. The lake became mesotrophic for almost 30 years; a rather rapid re-eutrophication took place in 2016 leading to massive cyanobacterial blooms. We quantified internal loading from sediment and analyzed two environmental factors that might have contributed to the sudden shift in trophic state. Increase in lake P concentration started in 2016, reaching 0.3 mg L-1, and remained elevated into the spring of 2018. Reducible P fraction in the sediment was 37 - 58% of total P, indicating a high potential for mobilization of benthic P during anoxia. Estimated P release from sediments for 2017 was approximately 600 kg for the whole lake. This is consistent with sediment incubation results; higher temperature (20°C) and anoxia contributed to release of P (27.9 ± 7.1 mg m-2 d-1, 0.94 ± 0.23 mmol m-2 d-1) to the lake, triggering re-eutrophication. Loss of aluminum P adsorption capacity together with anoxia and high water temperatures (organic matter mineralization) are major drivers of re-eutrophication. Accordingly, treated lakes at some time require a repeated aluminum treatment for sustaining acceptable water quality and we recommend regular sediment monitoring in treated lakes. This is crucial given the effects of climate warming on duration of stratification in lakes which may result in the need for treatment of many lakes.

A Data-Driven Preprocessing Framework for Atrial Fibrillation Intracardiac Electrocardiogram Analysis.

Atrial Fibrillation (AF) is the most common cardiac arrhythmia. Signal-processing approaches are widely used for the analysis of intracardiac electrograms (iEGMs), which are collected during catheter ablation from patients with AF. In order to identify possible targets for ablation therapy, dominant frequency (DF) is widely used and incorporated in electroanatomical mapping systems. Recently, a more robust measure, multiscale frequency (MSF), for iEGM data analysis was adopted and validated. However, before completing any iEGM analysis, a suitable bandpass (BP) filter must be applied to remove noise. Currently, no clear guidelines for BP filter characteristics exist. The lower bound of the BP filter is usually set to 3-5 Hz, while the upper bound (BP¯th) of the BP filter varies from 15 Hz to 50 Hz according to many researchers. This large range of BP¯th subsequently affects the efficiency of further analysis. In this paper, we aimed to develop a data-driven preprocessing framework for iEGM analysis, and validate it based on DF and MSF techniques. To achieve this goal, we optimized the BP¯th using a data-driven approach (DBSCAN clustering) and demonstrated the effects of different BP¯th on subsequent DF and MSF analysis of clinically recorded iEGMs from patients with AF. Our results demonstrated that our preprocessing framework with BP¯th = 15 Hz has the best performance in terms of the highest Dunn index. We further demonstrated that the removal of noisy and contact-loss leads is necessary for performing correct data iEGMs data analysis.

Synergistic Effects of Warming and Internal Nutrient Loading Interfere with the Long-Term Stability of Lake Restoration and Induce Sudden Re-eutrophication.

Phosphorus (P) precipitation is among the most effective treatments to mitigate lake eutrophication. However, after a period of high effectiveness, studies have shown possible re-eutrophication and the return of harmful algal blooms. While such abrupt ecological changes were attributed to the internal P loading, the role of lake warming and its potential synergistic effects with internal loading, thus far, has been understudied. Here, in a eutrophic lake in central Germany, we quantified the driving mechanisms of the abrupt re-eutrophication and cyanobacterial blooms in 2016 (30 years after the first P precipitation). A process-based lake ecosystem model (GOTM-WET) was established using a high-frequency monitoring data set covering contrasting trophic states. Model analyses suggested that the internal P release accounted for 68% of the cyanobacterial biomass proliferation, while lake warming contributed to 32%, including direct effects via promoting growth (18%) and synergistic effects via intensifying internal P loading (14%). The model further showed that the synergy was attributed to prolonged lake hypolimnion warming and oxygen depletion. Our study unravels the substantial role of lake warming in promoting cyanobacterial blooms in re-eutrophicated lakes. The warming effects on cyanobacteria via promoting internal loading need more attention in lake management, particularly for urban lakes.

Comparison of physicochemical properties and volatile flavor compounds of plant-based yoghurt and dairy yoghurt.

The aim of this study was to investigate and compare the physicochemical characteristics and volatile flavor compounds of three kinds of yoghurt made from reconstituted milk, soy drink and oat drink. The results showed that with the same fermentation ending pH of 4.5, reconstituted yoghurt had the highest titratable acidity mainly due to the highest buffering capacity and microbial counts (LAB). The textural and water holding capacity (WHC) parameters revealed that soy-based yoghurt had the highest firmness, consistency and WHC, indicating more rigid gel was formed. Meanwhile, rheological analysis showed soy-based yoghurt owned higher G' and G'' values and higher stability against external stress, demonstrating that more and stronger interactions between soy proteins were built during fermentation. The confocal laser scanning microscopy (CLSM) image witnessed that soy-based yoghurt had the densest and finest network, while oat-based yoghurt had much coarser and looser structure, which was consistent with the lowest firmness and G' value for oat-based yoghurt. In terms of color, reconstituted yoghurt was the lightest and oat-based yoghurt showed more reddish and yellowish. The main volatile flavor compounds in all yoghurts were ketones, while aldehydes contributed more in soy and oat yoghurt. PCA plot showed that volatile flavor compounds of reconstituted yoghurt and oat-based yoghurt were relatively similar, while soy-based yoghurt was much more different with high OAVs of hexanal, 1-octen-3-one, 1-octen-3-ol and 2-octenal. This study supplied a theoretical basis and an improvement direction for the better development of healthier plant-based yoghurt similar to dairy yoghurt.

Temporal relative transformer encoding cooperating with channel attention for EEG emotion analysis.

Electroencephalogram (EEG)-based emotion computing has become a hot topic of brain-computer fusion. EEG signals have inherent temporal and spatial characteristics. However, existing studies did not fully consider the two properties. In addition, the position encoding mechanism in the vanilla transformer cannot effectively encode the continuous temporal character of the emotion. A temporal relative (TR) encoding mechanism is proposed to encode the temporal EEG signals for constructing the temporality self-attention in the transformer. To explore the contribution of each EEG channel corresponding to the electrode on the cerebral cortex to emotion analysis, a channel-attention (CA) mechanism is presented. The temporality self-attention mechanism cooperates with the channel-attention mechanism to utilize the temporal and spatial information of EEG signals simultaneously by preprocessing. Exhaustive experiments are conducted on the DEAP dataset, including the binary classification on valence, arousal, dominance, and liking. Furthermore, the discrete emotion category classification task is also conducted by mapping the dimensional annotations of DEAP into discrete emotion categories (5-class). Experimental results demonstrate that our model outperforms the advanced methods for all classification tasks.

Phenolic compounds in walnut pellicle improve walnut (Juglans regia L.) protein solubility under pH-shifting condition.

This study focused on the interaction of walnut protein with phenolic extracts of walnut pellicle (PEWP) under alkaline condition, leading to enhancement of protein solubility under neutral condition. First, the change of PEWP under alkaline condition was determined by RP-HPLC and mass spectrometry, and the results showed that most ellagitannins in PEWP could be retained under alkaline condition within 3 h. Interaction between PEWP and walnut protein under pH-shifting condition resulted in the remarkable increase of protein solubility (above 90%) at neutral pH. The results from SDS-PAGE and SEC showed that the improved solubility lied in the formation of large and soluble protein aggregates due to the covalent interaction among walnut protein and polyphenols. A significant change in tertiary structure of protein-phenolic complex was witnessed by fluorescence spectrum and near-UV circular dichroism. Meanwhile, walnut protein-polyphenol interaction led to a slight increase in ß-turn while a slight decrease in ß-sheet. Combined with amino acid composition, it could be illustrated that the covalent bonding for walnut protein with polyphenol mainly occurred at Lysine residues.

Growing of fungi on the stored low denatured defatted soybean meals and the hydrolysis of proteins and isoflavone glycosides by fungal enzymes.

Recently, more and more attention has been paid to the effects of fungal contamination and fungal enzymes secreted in raw grain on product quality. As the starting material of protein and active components, the quality of low denatured defatted soybean meals (LDSM) directly determines the qualities of subsequent products. In previous studies, we have revealed that infection with Aspergillus ochraceus protease causes significant hydrolysis of proteins. In this study, growing of fungi on the stored low denatured defatted soybean meals (LDSM) was analyzed by high-throughput sequencing and real-time PCR, which revealed that the abundance of Aspergillus increased significantly after storage. Twenty fungal proteases and 9 fungal glucosidases were found in stored LDSM and zymography showed that the proteases were of serine-type with some cysteine and aspartic activities. Proteolysis of the soybean storage proteins mainly occurred after the hydration of LDSM and the average molecular weight of soy proteins decreased from 57.9 kDa to 30.7 kDa after 60 min's of hydrolysis. Two-dimensional electrophoresis (2-DE) analysis found the polypeptide fragments from soybean 7S and 11S proteins with molecular weight around 10-25 kDa in the hydrated LDSM. Glycosylated isoflavones were hydrolyzed in both dry and hydrated stored LDSM which resulted in significant (p < 0.05) increase in the contents of isoflavone aglycones. This study suggested that fungi contamination be a new factor affecting the properties of LDSM derived soy protein products.