An evaluation of Astragali Radix with different growth patterns and years, based on a new multidimensional comparison method.

Introduction: With the depletion of wild Astragali Radix (WA) resources, imitated-wild Astragali Radix (IWA) and cultivated Astragali Radix (CA) have become the main products of Astragali Radix. However, the quality differences of three growth patterns (WA, IWA, CA) and different growth years of Astragali Radix have not been fully characterized, leading to a lack of necessary scientific evidence for their use as substitutes for WA. Methods: We innovatively proposed a multidimensional evaluation method that encompassed traits, microstructure, cell wall components, saccharides, and pharmacodynamic compounds, to comprehensively explain the quality variances among different growth patterns and years of Astragali Radix. Results and discussion: Our study showed that the quality of IWA and WA was comparatively similar, including evaluation indicators such as apparent color, sectional structure and odor, thickness of phellem, diameter and number of vessels, morphology of phloem and xylem, and the levels and ratios of cellulose, hemicellulose, lignin, sucrose, starch, water-soluble polysaccharides, total-saponins. However, the content of sucrose, starch and sorbose in CA was significantly higher than WA, and the diameter and number of vessels, total-flavonoids content were lower than WA, indicating significant quality differences between CA and WA. Hence, we suggest that IWA should be used as a substitute for WA instead of CA. As for the planting years of IWA, our results indicated that IWA aged 1-32 years could be divided into three stages according to their quality change: rapid growth period (1-5 years), stable growth period (6-20 years), and elderly growth period (25-32 years). Among these, 6-20 years old IWA exhibited consistent multidimensional comparative results, showcasing elevated levels of key active components such as water-soluble polysaccharides, flavonoids, and saponins. Considering both the quality and cultivation expenses of IWA, we recommend a cultivation duration of 6-8 years for growers. In conclusion, we established a novel multidimensional evaluation method to systematically characterize the quality of Astragali Radix, and provided a new scientific perspective for the artificial cultivation and quality assurance of Astragali Radix.

[Dead heart of pith-decayed Scutellariae Radix: a study based on multi-omics].

Dead heart is an important trait of pith-decayed Scutellariae Radix. The purpose of this study was to clarify the scientific connotation of the dead heart using multi-omics. Metabolomics and transcriptomics combined with multivariate statistical analysis such as principal component analysis(PCA) and partial least squares discriminant analysis(PLS-DA) were used to systematically compare the differences in chemical composition and gene expression among phloem, outer xylem and near-dead xylem of pith-decayed Scutella-riae Radix. The results revealed significant differences in the contents of flavonoid glycosides and aglycones among the three parts. Compared with phloem and outer xylem, near-dead xylem had markedly lowered content of flavonoid glycosides(including baicalin, norwogonin-7-O-ß-D-glucuronide, oroxylin A-7-O-ß-D-glucuronide, and wogonoside) while markedly increased content of aglycones(including 3,5,7,2',6'-pentahydroxy dihydroflavone, baicalin, wogonin, and oroxylin A). The differentially expressed genes were mainly concentrated in KEGG pathways such as phenylpropanoid metabolism, flavonoid biosynthesis, ABC transporter, and plant MAPK signal transduction pathway. This study systematically elucidated the material basis of the dead heart of pith-decayed Scutellariae Radix with multiple growing years. Specifically, the content of flavonoid aglycones was significantly increased in the near-dead xylem, and the gene expression of metabolic pathways such as flavonoid glycoside hydrolysis, interxylary cork development and programmed apoptosis was significantly up-regulated. This study provided a theoretical basis for guiding the high-quality production of pith-decayed Scutellariae Radix.

Multi-factor combined biomarker screening strategy to rapidly diagnose Alzheimer's disease and evaluate drug effect based on a rat model.

Alzheimer's disease (AD) represents the main form of dementia; however, valid diagnosis and treatment measures are lacking. The discovery of valuable biomarkers through omics technologies can help solve this problem. For this reason, metabolomic analysis using ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS) was carried out on plasma, hippocampus, and cortex samples of an AD rat model. Based on the metabolomic data, we report a multi-factor combined biomarker screening strategy to rapidly and accurately identify potential biomarkers. Compared with the usual procedure, our strategy can identify fewer biomarkers with higher diagnostic specificity and sensitivity. In addition to diagnosis, the potential biomarkers identified using our strategy were also beneficial for drug evaluation. Multi-factor combined biomarker screening strategy was used to identify differential metabolites from a rat model of amyloid beta peptide 1-40 (Aß1-40) plus ibotenic acid-induced AD (compared with the controls) for the first time; lysophosphatidylcholine (LysoPC) and intermediates of sphingolipid metabolism were screened as potential biomarkers. Subsequently, the effects of donepezil and pine nut were successfully reflected by regulating the levels of the abovementioned biomarkers and metabolic profile distribution in partial least squares-discriminant analysis (PLS-DA). This novel biomarker screening strategy can be used to analyze other metabolomic data to simultaneously enable disease diagnosis and drug evaluation.

Multi-factor combined biomarker screening strategy to rapidly diagnose Alzheimer's disease and evaluate drug effect based on a rat model / 药物分析学报

Alzheimer's disease(AD)represents the main form of dementia;however,valid diagnosis and treatment measures are lacking.The discovery of valuable biomarkers through omics technologies can help solve this problem.For this reason,metabolomic analysis using ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS)was carried out on plasma,hippocampus,and cortex samples of an AD rat model.Based on the metabolomic data,we report a multi-factor combined biomarker screening strategy to rapidly and accurately identify potential bio-markers.Compared with the usual procedure,our strategy can identify fewer biomarkers with higher diagnostic specificity and sensitivity.In addition to diagnosis,the potential biomarkers identified using our strategy were also beneficial for drug evaluation.Multi-factor combined biomarker screening strategy was used to identify differential metabolites from a rat model of amyloid beta peptide 1-40(Aβ1-40)plus ibotenic acid-induced AD(compared with the controls)for the first time;lysophosphati-dylcholine(LysoPC)and intermediates of sphingolipid metabolism were screened as potential bio-markers.Subsequently,the effects of donepezil and pine nut were successfully reflected by regulating the levels of the abovementioned biomarkers and metabolic profile distribution in partial least squares-discriminant analysis(PLS-DA).This novel biomarker screening strategy can be used to analyze other metabolomic data to simultaneously enable disease diagnosis and drug evaluation.

Correction: Predicting Health Material Accessibility: Development of Machine Learning Algorithms.

[This corrects the article DOI: 10.2196/29175.].

Predicting Health Material Accessibility: Development of Machine Learning Algorithms.

BACKGROUND: Current health information understandability research uses medical readability formulas to assess the cognitive difficulty of health education resources. This is based on an implicit assumption that medical domain knowledge represented by uncommon words or jargon form the sole barriers to health information access among the public. Our study challenged this by showing that, for readers from non-English speaking backgrounds with higher education attainment, semantic features of English health texts that underpin the knowledge structure of English health texts, rather than medical jargon, can explain the cognitive accessibility of health materials among readers with better understanding of English health terms yet limited exposure to English-based health education environments and traditions. OBJECTIVE: Our study explores multidimensional semantic features for developing machine learning algorithms to predict the perceived level of cognitive accessibility of English health materials on health risks and diseases for young adults enrolled in Australian tertiary institutes. We compared algorithms to evaluate the cognitive accessibility of health information for nonnative English speakers with advanced education levels yet limited exposure to English health education environments. METHODS: We used 113 semantic features to measure the content complexity and accessibility of original English resources. Using 1000 English health texts collected from Australian and international health organization websites rated by overseas tertiary students, we compared machine learning (decision tree, support vector machine [SVM], ensemble tree, and logistic regression) after hyperparameter optimization (grid search for the best hyperparameter combination of minimal classification errors). We applied 10-fold cross-validation on the whole data set for the model training and testing, and calculated the area under the operating characteristic curve (AUC), sensitivity, specificity, and accuracy as the measurement of the model performance. RESULTS: We developed and compared 4 machine learning algorithms using multidimensional semantic features as predictors. The results showed that ensemble tree (LogitBoost) outperformed in terms of AUC (0.97), sensitivity (0.966), specificity (0.972), and accuracy (0.969). Decision tree (AUC 0.924, sensitivity 0.912, specificity 0.9358, and accuracy 0.924) and SVM (AUC 0.8946, sensitivity 0.8952, specificity 0.894, and accuracy 0.8946) followed closely. Decision tree, ensemble tree, and SVM achieved statistically significant improvement over logistic regression in AUC, specificity, and accuracy. As the best performing algorithm, ensemble tree reached statistically significant improvement over SVM in AUC, specificity, and accuracy, and statistically significant improvement over decision tree in sensitivity. CONCLUSIONS: Our study shows that cognitive accessibility of English health texts is not limited to word length and sentence length as had been conventionally measured by medical readability formulas. We compared machine learning algorithms based on semantic features to explore the cognitive accessibility of health information for nonnative English speakers. The results showed the new models reached statistically increased AUC, sensitivity, and accuracy to predict health resource accessibility for the target readership. Our study illustrated that semantic features such as cognitive ability-related semantic features, communicative actions and processes, power relationships in health care settings, and lexical familiarity and diversity of health texts are large contributors to the comprehension of health information; for readers such as international students, semantic features of health texts outweigh syntax and domain knowledge.

Predicting Writing Styles of Web-Based Materials for Children's Health Education Using the Selection of Semantic Features: Machine Learning Approach.

BACKGROUND: Medical writing styles can have an impact on the understandability of health educational resources. Amid current web-based health information research, there is a dearth of research-based evidence that demonstrates what constitutes the best practice of the development of web-based health resources on children's health promotion and education. OBJECTIVE: Using authoritative and highly influential web-based children's health educational resources from the Nemours Foundation, the largest not-for-profit organization promoting children's health and well-being, we aimed to develop machine learning algorithms to discriminate and predict the writing styles of health educational resources on children versus adult health promotion using a variety of health educational resources aimed at the general public. METHODS: The selection of natural language features as predicator variables of algorithms went through initial automatic feature selection using ridge classifier, support vector machine, extreme gradient boost tree, and recursive feature elimination followed by revision by education experts. We compared algorithms using the automatically selected (n=19) and linguistically enhanced (n=20) feature sets, using the initial feature set (n=115) as the baseline. RESULTS: Using five-fold cross-validation, compared with the baseline (115 features), the Gaussian Naive Bayes model (20 features) achieved statistically higher mean sensitivity (P=.02; 95% CI -0.016 to 0.1929), mean specificity (P=.02; 95% CI -0.016 to 0.199), mean area under the receiver operating characteristic curve (P=.02; 95% CI -0.007 to 0.140), and mean macro F1 (P=.006; 95% CI 0.016-0.167). The statistically improved performance of the final model (20 features) is in contrast to the statistically insignificant changes between the original feature set (n=115) and the automatically selected features (n=19): mean sensitivity (P=.13; 95% CI -0.1699 to 0.0681), mean specificity (P=.10; 95% CI -0.1389 to 0.4017), mean area under the receiver operating characteristic curve (P=.008; 95% CI 0.0059-0.1126), and mean macro F1 (P=.98; 95% CI -0.0555 to 0.0548). This demonstrates the importance and effectiveness of combining automatic feature selection and expert-based linguistic revision to develop the most effective machine learning algorithms from high-dimensional data sets. CONCLUSIONS: We developed new evaluation tools for the discrimination and prediction of writing styles of web-based health resources for children's health education and promotion among parents and caregivers of children. User-adaptive automatic assessment of web-based health content holds great promise for distant and remote health education among young readers. Our study leveraged the precision and adaptability of machine learning algorithms and insights from health linguistics to help advance this significant yet understudied area of research.

Use of Machine Learning Algorithms to Predict the Understandability of Health Education Materials: Development and Evaluation Study.

BACKGROUND: Improving the understandability of health information can significantly increase the cost-effectiveness and efficiency of health education programs for vulnerable populations. There is a pressing need to develop clinically informed computerized tools to enable rapid, reliable assessment of the linguistic understandability of specialized health and medical education resources. This paper fills a critical gap in current patient-oriented health resource development, which requires reliable and accurate evaluation instruments to increase the efficiency and cost-effectiveness of health education resource evaluation. OBJECTIVE: We aimed to translate internationally endorsed clinical guidelines to machine learning algorithms to facilitate the evaluation of the understandability of health resources for international students at Australian universities. METHODS: Based on international patient health resource assessment guidelines, we developed machine learning algorithms to predict the linguistic understandability of health texts for Australian college students (aged 25-30 years) from non-English speaking backgrounds. We compared extreme gradient boosting, random forest, neural networks, and C5.0 decision tree for automated health information understandability evaluation. The 5 machine learning models achieved statistically better results compared to the baseline logistic regression model. We also evaluated the impact of each linguistic feature on the performance of each of the 5 models. RESULTS: We found that information evidentness, relevance to educational purposes, and logical sequence were consistently more important than numeracy skills and medical knowledge when assessing the linguistic understandability of health education resources for international tertiary students with adequate English skills (International English Language Testing System mean score 6.5) and high health literacy (mean 16.5 in the Short Assessment of Health Literacy-English test). Our results challenge the traditional views that lack of medical knowledge and numerical skills constituted the barriers to the understanding of health educational materials. CONCLUSIONS: Machine learning algorithms were developed to predict health information understandability for international college students aged 25-30 years. Thirteen natural language features and 5 evaluation dimensions were identified and compared in terms of their impact on the performance of the models. Health information understandability varies according to the demographic profiles of the target readers, and for international tertiary students, improving health information evidentness, relevance, and logic is critical.

Antiparasitic Efficacy of Crude Plant Extracts and Compounds Purified from Plants against the Fish Monogenean Neobenedenia girellae.

Neobenedenia girellae is a pathogenic ectoparasite of many marine fishes, and it causes major epidemics in marine aquaculture. In this study, the efficacy of ethanol extracts of huangqi Astragalus membranaceus (known as milkvetch in North America), guanzhong Dryopteris setosa (known as beaded wood fern in North America), gancao Glycyrrhiza uralensis (known as Chinese licorice in North America), danshen Salvia miltiorrhiza (known as red sage in North America), and pomegranate Punica granatum, as well as seven phytochemicals (10-gingerol, curcumin, cynatratoside-C, emodin, kuwanon-G, kuwanon-O, and sophoraflavanone-G), against adult N. girellae was investigated. In vitro results indicated that pomegranate extract killed all adult N. girellae at a 62.5-mg/L concentration with an 8-h exposure, but gancao extract did not cause 100% mortality until a 1,000-mg/L concentration was used. Additionally, all adult N. girellae died after an 8-h exposure to cynatratoside-C, kuwanon-G, kuwanon-O, or sophoraflavanone-G at a concentration of 125 mg/L. Curcumin, emodin, and 10-gingerol at a concentration of 1,000 mg/L did not kill all parasites after an 8-h exposure. These findings demonstrate that plant extracts and active phytochemicals are potential sources of botanical drugs for controlling N. girellae infection in aquaculture.

The transcriptional factor GATA-4 negatively regulates Hsp70 transcription in Crassostrea hongkongensis.

To better explore the application potential of heat shock protein Hsp70s in diverse areas including biomonitoring, a further investigation of the details of the regulatory mechanism governing Hsp70 transcription is required. A transcriptional factor ChGATA-4 that displayed affinity to the ChHsp70 promoter of Crassostrea hongkongensis was isolated and identified by DNA affinity purification as well as mass spectrometry analysis. The ChGATA-4 cDNA is 2162 bp in length and the open reading frame encodes a polypeptide containing 482 amino acids with a conserved zinc finger domain. The over-expression of ChGATA-4 significantly inhibited the expression of ChHsp70 promoter in heterologous HEK293T cells. However, the depletion of ChGATA-4 mRNA by RNAi technique resulted in significant increase of ChHsp70 transcription in oyster hemocytes. The RT-PCR results demonstrated that the transcription of both ChHsp70 and ChGATA-4 were induced by heat, Cd, or NP (Nonyl phenol) stress. This suggested a potential correlation between ChHsp70 and ChGATA-4 in the stress-mediated genetic regulatory cascade. This study demonstrated that ChGATA-4 acts in a negative manner in controlling ChHsp70 transcription in C. hongkongensis and promotes to further understand the mechanisms leading Hsp70 transcription.

Low-cost and efficient confocal imaging method for arabidopsis flower.

For an extensive period of time apical meristem (SAM) has been considered as a mysterious organ, due to its small, hidden and dynamic structure. Confocal imaging, combined with fluorescent reporters, enables researchers to unveil the mechanisms underlying cellular activities, such as gene expression, cell division, growth patterns and cell-cell communications. Recently, a series of protocols were developed for confocal imaging of inflorescence meristem (IM) and floral meristem (FM). However, the requirement of high configuration, such as the need of a water-dipping lens without coverslip and the specialized turrets associated with fixed-stage microscopes, impedes the wide adoption of these methods. We exploited an improved object slide and matching method aiming to decrease the configuration requirement. Following this protocol, various dry microscope lenses can be selected with flexibility for building 3D images of IM and FM.

Biomimetic cell-cell adhesion capillary electrophoresis for studying Gu-4 antagonistic interaction between cell membrane receptor and ligands.

We report a new method: biomimetic cell-cell adhesion capillary electrophoresis (BCCACE) to screen drugs targeting interactions between cell membrane receptors and ligands under an environment close to physiological conditions, in which the cell membrane receptors/ligands can maintain their natural conformations and bioactivity without being isolated and purified. Firstly, we screened twenty-one lactose derivatives by cell-immobilized capillary electrophoresis and obtained Gu-4 with the best activity (K = 3.58 ±â€¯0.22 × 104) targeting macrophage antigen-1 (Mac-1). Then, BCCACE was performed as follows: HEK 293 cells overexpressed with receptor (intercellular adhesion molecules-1, ICAM-1) were cultured and immobilized on the inner wall of capillaries as stationary phase, which simulated the endothelial cells lining on the inner surface of blood vessels. HEK 293 cells overexpressed with ligand Mac-1 as samples were used to simulate the neutrophils cells in blood vessels. And Gu-4 added into the running buffer solution as the antagonist was used to simulate the drug in blood. The results showed that Gu-4 (40 µM) could selectively inhibit cell-cell adhesion by targeting the interaction between Mac-1 and ICAM-1. Finally, the pharmaceutical efficacy assays of Gu-4 at cellular and animal levels were carried out using the concentration of 40 µM and the dose of 20 mg kg-1 respectively, which showed the anti-cancer metastasis activity of Gu-4 and the validity of the method. This method simulated a complete three-dimensional vascular model, which can easily obtain the suitable blood concentration of drugs. This system simulated the interaction between leukocytes and vascular endothelial cells in the bloodstream antagonized by drugs, and obtained the effective concentration of the antagonist. It can be used as an accuracy and efficient drug screening method and will be expected to become a new method to screen drugs targeting cell-cell adhesion.

Efficacy and antiparasitic mechanism of 10-gingerol isolated from ginger Zingiber officinale against Ichthyophthirius multifiliis in grass carp.

Ichthyophthirius multifiliis is a ciliate parasite of freshwater fish with a global distribution and results in severe economic losses in aquaculture. The present study aimed to investigate the efficacy and antiparasitic mechanism of active compounds isolated from Zingiber officinale against I. multifiliis. Three compounds were isolated from the Z. officinale extract and identified as 10-gingerol, 6-dehydroshogaol, and 6-dehydro-10-gingerol. 10-gingerol demonstrated the greatest antiparasitic efficacy in vitro. 10-gingerol resulted in 100% mortalities of theronts, nonencysted tomonts, and encysted tomonts at concentrations of 2, 8, and 16 mg/L, respectively. 10-gingerol significantly reduced theronts infectivity (p < 0.05) at a concentration of 1 mg/L, and it was effective in treating infected grass carp and protecting naïve fish from I. multifiliis infestation at a concentration of 4 mg/L. The antiparasitic mechanism might be attributed to the increase of intracellular osmotic pressure, accumulation of free radicals, and membrane damage of I. multifiliis post 10-gingerol treatment. The study demonstrated that 10-gingerol had the potential as a therapeutic agent against I. multifiliis.

Grass carp which survive Dactylogyrus ctenopharyngodonid infection also gain partial immunity against Ichthyophthirius multifiliis.

Dactylogyrus ctenopharyngodonid and Ichthyophthirius multifiliis are 2 important ectoparasites of fish. Both parasites can induce an immune response in fish that leads to a decrease in parasitic infection intensity and the development of resistance against parasitic reinfection. The present study evaluated whether grass carp Ctenopharyngodon idella that survived a D. ctenopharyngodonid infection could develop immunity against infection by D. ctenopharyngodonid and I. multifiliis. The results demonstrated that when grass carp were infected with D. ctenopharyngodonid, the number of red blood cells and the percentages of thrombocytes, monocytes, and neutrophils in the white blood cells increased significantly in the early stage of infection. The percentage of lymphocytes increased over time following parasitic infection. The mean infection intensity of D. ctenopharyngodonid decreased to 0 on Day 28. The activities of serum acid phosphatase, alkaline phosphatase, lysozyme, and superoxide dismutase increased significantly after D. ctenopharyngodonid infection. In addition, the grass carp that survived a previous D. ctenopharyngodonid infection could completely resist D. ctenopharyngodonid reinfection and partially resist I. multifiliis infection.

Mechanisms of the active components from Korean pine nut preventing and treating d-galactose-induced aging rats.

Age-related neuronal injury and oxidative damage are the predominant factors for neurodegenerative diseases like Alzheimer's disease (AD). The aim of this study was to explore whether chronic administration of d-galactose (d-gal) can cause neuronal injury and oxidative damage, and to investigate the neuroprotective and antioxidative effects of the active components (UPNO-1) from Korean pine nut (Pinus koraiensis). Two dosing regimens were designed, one for the evaluation of preventive effects in which the rats were simultaneously administrated d-gal and UPNO-1/fishoil for 12 weeks, the other for the evaluation of therapeutic effects in which the rats were given d-gal for 8 weeks before treated with UPNO-1/selegiline for 8 weeks. The experimental results demonstrated that chronic administration of d-gal produced histopathological changes and increased neuronal apoptosis, and decreased significantly the activities of T-AOC, T-SOD and CAT. Additionally, a comprehensive metabolic profiling of d-gal-treated rats was performed for the first time to investigate the metabolic disorders in the hippocampus, cortex and plasma, and a total of 32 annotated metabolites were significantly increased or decreased in the modeled rats. Major disturbed metabolic pathways were fatty acid, glycerolphospholipid and arachidonic acid metabolic pathways. UPNO-1 significantly diminished neuronal apoptosis, ameliorated histopathological findings, and increased the activities of T-SOD and CAT but not T-AOC. Furthermore, UPNO-1 attenuated the decreased plasma levels of 3-oxooctanoic acid, l-tryptophan, 12-hydroxyheptadecanoic acid, lysophosphatidylcholine (16:0) (LPC(16:0)), LPC(18:3) and LPC(18:1) in the modeled rats. These results illustrated the mechanisms of d-gal induced neurotoxicity and oxidative stress and proved the positive effects of UPNO-1 on preventing and treating d-gal-induced-aging rats.

Evaluation of an antiparasitic compound extracted from Polygonum cuspidatum against Ichthyophthirius multifiliis in grass carp.

Ichthyophthirius multifiliis is a ciliated parasite that infests almost all freshwater fish species and causes great economic losses to the aquaculture industry. In this study, a compound with anti-I. multifiliis activity was isolated from Polygonum cuspidatum and identified as emodin. In vitro anti-I. multifiliis results showed that emodin at 1 mg/L killed all I. multifiliis theronts for 96.0 min, and at 0.5 mg/L or lower concentrations could not kill all I. multifiliis theronts, but could significantly reduce the infectivity of theronts after pretreatment with emodin at the low concentrations mentioned above for 2 h. Additionally, emodin at 1 mg/L and 2 mg/L completely terminated the reproduction of nonencysted and encysted tomonts, respectively. In vivo tests, emodin at 0.5 mg/L could cure infected grass carp and protect naive fish from I. multifiliis infection by continuous adding emodin for 10 days. The 96 h median lethal concentration (LC50) of emodin to grass carp was 3.15 mg/L, which were approximately 18 and 7 times the median effective concentration (EC50) of emodin for killing theronts (0.18 mg/L) and nonencysted tomonts (0.45 mg/L), respectively. On the basis of these results, emodin is an effective compound for the development of a new drug against I. multifiliis.

Nonimmobilized Biomaterial Capillary Electrophoresis for Screening Drugs Targeting Human Glucose Transporter 1.

We report an online ligand screening method that targets human glucose transporter 1 (hGlut1) under approximately physiological conditions, named nonimmobilized biomaterial capillary electrophoresis (NIBCE), and we investigated the interactions between drugs/candidate compounds and HEK293 cells, hGlut1-overexpressing HEK293 cells, non-small-cell lung cancer A549 cells, A549 tumor tissue, and normal lung tissue by simulating the interactions between drugs and moving target cells or the space-occupying tumor. NIBCE omits the trouble of isolating and purifying target receptors from cell membrane while maintaining their native conformation and binding activity. The biomaterials were intercepted by porous frits in capillary columns and cannot flow through the detection window, thereby solving the problem of interference detection, and they can be renewed any time flexibly, thus effectively maintaining their surface bioactivity. Furthermore, the binding kinetic parameters (K, ka, kd, and k') were calculated by nonlinear chromatography (NLC) theory, and competitive binding experiments, ligand docking studies, and antitumor activity assays in vitro and in vivo were performed to verify the feasibility of NIBCE.

Studies on diagnostic biomarkers and therapeutic mechanism of Alzheimer's disease through metabolomics and hippocampal proteomics.

Alzheimer's disease (AD) is the main cause of dementia, but precise diagnosis and treatment are not sufficient so far. The purpose of this study is to develop biomarkers and therapeutic targets for diagnosis and better understanding of AD. As a result, lysophosphatidylcholine and intermediates of sphingolipid metabolism including sphinganine-1-phosphate, sphingosine-1-phosphate, sphingomyelin, and sphingosine in plasma were annotated as potential biomarkers by using UPLC-Q-TOF-MS and UHPLC-Q-Exactive-MS. Besides, glutathione S-transferases (GSTs) including GstA3, Gstm1, Gstm5, Gstm3, Gstk1 and Gstp1 were significantly enhanced in AD hippocampus by using label free nano-LC-MS/MS. Thus, pathogenesis of AD was involved with increasing of choline, decreasing of ACh, enhancement of GSTs and increasing of glutamate which led to oxidative stress and excitotoxity. Effects of donepezil and a natural medicine were evaluated through metabolomics and proteomics. In summary, proteomic and metabolomic analysis on constructed AD rat model were performed through rapid, sensitive and high resolution LC-MS methods to reveal candidate biomarkers. The data suggested that GSTs have great value as therapeutic targets. This study provided valuable information for the diagnosis mechanism and drug discovery of AD.

Combined effects of Chinese medicine feed and ginger extract bath on co-infection of Ichthyophthirius multifiliis and Dactylogyrus ctenopharyngodonid in grass carp.

Dactylogyrus ctenopharyngodonid and Ichthyophthirius multifiliis are two important ectoparasites of freshwater fish. Co-infection by the two parasites leads to high fish mortality and results in heavy economic losses. This study aimed to evaluate the efficacy of medicated feed and a ginger extract bath against D. ctenopharyngodonid and I. multifiliis on grass carp and investigate the hematological response of grass carp co-infected by the two parasites. These results demonstrated that red blood cell (RBC) and thrombocyte percentage among leucocytes significantly decreased after grass carp were co-infected by D. ctenopharyngodonid and I. multifiliis. The monocyte and neutrophil percentages significantly increased with the increment of parasite mean intensities, while the lymphocyte percentage decreased. The activities of serum acid phosphatase (ACP), alkaline phosphatase (AKP), lysozyme (LZM), and superoxide dismutase (SOD) significantly increased after co-infection. When grass carp treated with medicated feed containing 4% of Astragalus membranaceus, Allium sativum, Morus alba, and Glycyrrhiza uralensis, the activities of ACP, AKP, LZM, and SOD were significantly enhanced, and the mean intensities of D. ctenopharyngodonid and I. multifiliis were significantly decreased. When grass carp was treated with medicated feed and a 4-mg/L ginger extract bath, all parasites were eliminated during 28 days. The bath of ginger extract at a concentration of 4 mg/L kept a low mean intensity of I. multifiliis and D. ctenopharyngodonid, then the two parasites were eliminated by oral administration of the medicated feed with an immunostimulant (Chinese medicine compound).

Antiparasitic efficacy of curcumin from Curcuma longa against Ichthyophthirius multifiliis in grass carp.

Ichthyophthirius multifiliis is a ciliated parasite that elicits great economic losses in aquaculture. In the present study, a polyphenol compound, curcumin, was obtained from the rhizome of Curcuma longa by bioassay-guided isolation based on the efficacy of anti-I. multifiliis theronts. Anti-I. multifiliis efficacy of curcumin was evaluated in vitro and in vivo. Curcumin resulted in 100% mortality of I. multifiliis theronts at a concentration of 1mg/L within 21.7±1.2min and killed all tomonts at 8mg/L within 31.0±1.0min. Curcumin at 4mg/L for 16h exposure can completely terminate the reproduction of tomonts. The pretreatment with curcumin at concentrations of 0.5, 0.25, and 0.125mg/L for 2h significantly reduced the infectivity of I. multifiliis theronts. Curcumin at 4mg/L completely cured the infected grass carp and protected naive fish from I. multifiliis infection after 10days exposure. The 4h median effective concentration (EC50) of curcumin to I. multifiliis theronts and the 5h EC50 of curcumin to I. multifiliis tomonts were 0.303mg/L and 2.891mg/L, respectively. The 96h median lethal concentration (LC50) of curcumin to grass carp was 56.8mg/L, which was approximately 187.4 times EC50 of curcumin to theronts and 19.6 times EC50 of curcumin to tomonts. The results demonstrated that curcumin has the potential to be a safe and effective therapeutant for controlling ichthyophthiriasis in aquaculture.