Study on the components changes of polysaccharides and saponins during nine steaming and drying of Polygonatum sibiricum

BACKGROUND

In this study, the content and structure of Polygonatum sibiricum polysaccharides and saponins during different processing stages were determined.

RESULTS

After processing of Polygonatum, the content of polysaccharide and glucose decreased, and the content of galactose, glucuronic acid and sugar substitution gradually increased. The content of total saponins increased significantly. Only 18 compounds were found in raw Polygonatum and 17 new compounds were presented in processed Polygonatum. During the processing of Polygonatum, the polysaccharide was partially degraded into oligosaccharides, the molecular weight gradually decreased, and the neutral sugar was converted into uronic acid, resulting in a decrease in polysaccharide content. The saponins were partially degraded into sapogenins or modified.

CONCLUSION

This study clarifies the changes in the content and structure of polysaccharides and saponins in processed Polygonatum, which will pave the way for elucidating the processing mechanism. © 2024 Society of Chemical Industry.

[Applications of ion chromatography for the analysis of Chinese herbal medicine components]

Ion chromatography (IC) is a novel high performance liquid chromatographic technique that is suitable for the separation and analysis of ionic substances in different matrix samples. Since 1975, it has been widely used in many fields, such as the environment, energy, food, and medicine. IC compensates for the separation limitations of traditional gas chromatography and high performance liquid chromatography and can realize the qualitative analysis and quantitative detection of strongly polar components. This chromatographic technique features not only simple operations but also rapid analysis. The sensors used in IC are characterized by high sensitivity and selectivity, and the technique can simultaneously separate and determine multiple components. Several advances in IC instrumentation and chromatographic theories have been developed in recent years. IC can analyze various types of samples, including ions, sugars, amino acids, and organic acids (bases). Chinese herbal medicines are typically characterized by highly complex chemical compositions and may contain carbohydrates, proteins, alkaloids, and other active components. They also contain toxic residues such as sulfur dioxide, which may be produced during the processing of medicinal materials. Therefore, the analysis and elucidation of the precise chemical constituents of Chinese herbal medicines present key problems that must be resolved in modern Chinese herbal medicine research. In this context, IC has become an important method for analyzing and identifying the complex components of Chinese herbal medicines because this method is suitable for detecting a single active ingredients among complex components. This paper introduces the different types and principles of IC as well as research progress in this technique. As the applications of IC-based methods in pharmaceutical science, cell biology, and microbiology increase, further development is necessary to expand the applications of this technique. The development of innovative techniques has enabled IC technologies to achieve higher analytical sensitivity, better selectivity, and wider application. The components of Chinese herbal medicines can be divided into endogenous and exogenous components according to their source: endogenous components include glycosides, amino acids, and organic acids, while exogenous components include toxic residues such as sulfur dioxide. Next, the applications of IC to the complex components of Chinese herbal medicines in recent decades are summarized. The most commonly used IC technologies and methods include ion exchange chromatography and conductivity detection. The advantages of IC for the analysis of alkaloids have been demonstrated. This method exhibits better characteristics than traditional analytical methods. However, the applications of IC for the speciation analysis of inorganic anions are limited. Moreover, few reports on the direct application of the technique for the determination of the main active substances in Chinese herbal medicines, including flavonoids, phenylpropanoids, and steroids, have been reported. Finally, this paper reviews new IC technologies and their application progress in Chinese herbal medicine, focusing on their prospects for the effective separation and analysis of complex components. In particular, we discuss the available sample (on-line) pretreatment technologies and explore possible technologies for the selective and efficient enrichment and separation of different components. Next, we assess innovative research on solid-phase materials that can improve the separation effect and analytical sensitivity of IC. We also describe the features of multidimensional chromatography, which combines the advantages of various chromatographic techniques. This review provides a theoretical reference for the further development of IC technology for the analysis of the complex chemical components of Chinese herbal medicines.

Rapid classification and identification of chemical compositions of Pu-zhi-hui-ling decoction by UHPLC-Q-Orbitrap HRMS

Pu-zhi-hui-ling decoction (PZHLD) is a traditional Chinese medicine (TCM) formula for the treatment of Alzheimer's disease (AD), but its chemical composition has not been reported. In this study, we aimed to establish a mass spectrometry (MS) analysis method for rapid classification and identification of the chemical constituents in PZHLD. The sample was analysed by ultrahigh-performance liquid chromatography coupled to quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). The chemical constituents of PZHLD were identified based on accurate MS data, fragmentation characteristics of MS/MS, and reference information described in the literature. A total of 123 chemical constituents were identified. In addition, we summarised the fragmentation pathways of the chemical constituents in PZHLD. Our finding might lay the foundation for the further pharmacodynamic study and clinical application of PZHLD.

Rapid analysis of the chemical constituents in Qiangli Dingxuan tablets using ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry

Qiangli Dingxuan (QLDX) tablet is a widely recognized traditional Chinese medicine formula that has been extensively used in China for decades to treat vertigo, tinnitus, and dizziness owing to its outstanding therapeutic outcomes. However, the complexity of the chemical components in this tablet makes it challenging to separate and identify these components. This study presented an effective and sensitive strategy for the rapid separation and simultaneous structural identification of QLDX tablet components using ultra-performance liquid chromatography with quadrupole time-of-flight tandem mass spectrometry and the UNIFI platform. Based on retention times, accurate masses, fragment ions, related literature, and authentic standards, 119 compounds were identified or tentatively characterized; these included 9 iridoids, 12 lignans, 21 phenylpropanoids, 27 flavonoids, 7 phthalides, and 43 others. Among them, 36 were confirmed using reference standards. The representative compounds with various chemical structures were studied by analyzing their fragmentation patterns and characteristic ions. In conclusion, this study established a rapid approach for characterizing the chemical constituents in QLDX tablet. The proposed approach provides a basis for qualitative analysis and quality control in the manufacturing process and is beneficial for advancing investigations into the efficacy and mechanism of action of this tablet.

Toward a synthesis of cognitive behaviour therapy via component analysis of self-regulation

The cognitive behavioural therapies (CBTs) are the choice psychotherapies for many clinicians treating a wide range of adult psychological disorders including various anxieties, mood, substance use, eating, schizophrenia and personality-related. Empirical research in the CBTs is ever increasing, and the accumulating evidence supporting efficacious treatments is substantial and well documented. However, with prolific research comes a seemingly accelerating and worrying trend of purportedly different therapies, and numerous hybrids and combinations of therapies and techniques. For many clinicians this is increasingly confusing and not helpful in clinical practice. This article is a critique of current trends and directions in clinical research, which show signs of limited effectiveness, fragmentation, and obfuscation. An alternative strategy is proposed-examining transdiagnostic therapeutic effects, which appear related to treating pervasive dysregulated emotions, with component analyses of four principal self-regulation components (viz., self-monitoring; functional analysis; identifying values, goals and treatment-plans; and feedback). Such a strategy is likely to lead to a more coherently synthesized and effective CBT.

Extraction, Isolation, and Component Analysis of Turmeric-Derived Exosome-like Nanoparticles

As one kind of plant-derived extracellular vesicle, turmeric-derived exosome-like nanoparticles (TELNs) are composed of proteins, lipids, nucleic acids, and small-molecule compounds, which possess good biocompatibility and safety. They are especially rich in information from the "mother plant", which provides more applications in biological fields. In this study, we isolated and purified TELNs using differential centrifugation and ultracentrifugation and systematically detected their physicochemical properties using multi-omics. The TELNs possessed a typical teacup-like exosome morphology, and the extraction rate was approximately 1.71 ± 0.176 mg/g. The average particle size was 183.2 ± 10.9 nm, and the average zeta potential was -17.6 ± 1.19 mV. They were rich in lipids, mainly phosphatidylethanolamine (PE) (17.4%), triglyceride (TG) (12.3%), phosphatidylinositol (PI) (9.82%), and phosphatidylcholine (PC) (7.93%). All of them are the key lipids in the exosomes. The protein content was approximately 12% (M/M), mainly curcumin synthase and other proteins involved in secondary metabolite biosynthesis. In addition, there are critical essential genes for curcumin biosynthesis, such as curcumin synthase (CURS) and diketocoenzyme A synthase (DCS). More importantly, a greater variety of small-molecule compounds, primarily curcumin and curcumin analogs such as demethoxycurcumin and volatile oleoresins such as curcuminoids, have now been revealed. In conclusion, TELNs were successfully isolated, containing 0.17% (M/M) turmeric and a large amount of chemical information, the same as the parent-of-origin plant. This is the first time combining multi-omics to analyze the characteristics and nature of the TELNs, which laid a solid material foundation for the further development of turmeric.

Rapid identification of chemical constituents in Hugan tablets by ultra-performance liquid chromatography-quadrupole-exactive orbitrap mass spectrometry

Hugan tablet is a Chinese medicine preparation. It is composed of Bupleuri Radix, Artemisiae Scopariae Herba, Isatidis Radix, Schisandrae Chinensis Fructus, Suis Fellis Pulvis, and Vigna radiata L. It has the effects of dispersing stagnated liver qi, strengthening the spleen and eliminating food to be used for the treatment of chronic hepatitis and early cirrhosis. However, the chemical composition of Hugan tablet is complex and not fully understood, which hampers the research in pharmacology. In this study, a reliable method for the rapid analysis and identification of the chemical components in Hugan tablet by their characteristic fragments and neutral losses using ultra-performance liquid chromatography-quadrupole-exactive orbitrap mass spectrometry was developed. A total of 144 chemical components were tentatively identified, including 57 organic acids, 19 flavonoids, 23 alkaloids, 18 lignans, 7 saponins, and 20 others. These components may be the active ingredients of Hugan tablet. The established method can systematically and rapidly analyze the chemical components in Hugan tablet, which provides a basis for the pharmacodynamic substance study and is meaningful for the quality control of Hugan tablet.

Evaluation of pharmacological activities and active components in Tremella aurantialba by instrumental and virtual analyses

As a kind of medicinal and edible homologous fungus, there is a lack of data on the medicinal value of Tremella aurantialba. In this study, ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF/MS) was used to screen the chemical components in T. aurantialba. Then, network pharmacology was used to reveal the potential biological activities, active compounds, and therapeutic targets of T. aurantialba. Finally, the potential binding sites of the active compounds of T. aurantialba and key targets were studied by molecular docking. Results showed that 135 chemical components in T. aurantialba, especially linoleic acid, and linolenic acid have significant biological activities in neuroprotective, anticancer, immune, hypoglycemic, and cardiovascular aspects. The existence of these bioactive natural products in T. aurantialba is consistent with the traditional use of T. aurantialba. Moreover, the five diseases have comorbidity molecular mechanisms and therapeutic targets. The molecular docking showed that linolenic acid, adenosine, and vitamin D2 had higher binding energy with RXRA, MAPK1, and JUN, respectively. This study is the first to systematically identify chemical components in T. aurantialba and successfully predict its bioactivity, key active compounds, and drug targets, providing a reliable novel strategy for future research on the bioactivity development and utilization of T. aurantialba.

Bioactivity and Component Analysis of Water Extract of Sophora japonica against Hyperuricemia by Inhibiting Xanthine Oxidase Activity

Hyperuricemia (HUA) is a metabolic condition caused by excessive production or low excretion of uric acid (UA) in the body. Xanthine oxidase (XOD) is the key enzyme in the process of metabolism purines to generate UA. In this study, the in vitro inhibitory effect of water extract of the flower bud of Sophora japonica (WESJ) on XOD was investigated by ultraviolet spectrophotometry. A mice model of HUA was constructed to explore the effect of WESJ on UA levels and the mechanism of action on renal function. Based on Box-Behnken design, the optimal extraction process of WESJ was determined to extract Sophora japonica twice with 8 times of water, 0.5 h each time. Pharmacological results showed that low, medium, and high doses of WESJ (200, 400, 600 mg/kg) could significantly reduce serum UA level, inhibit the activity of XOD in blood and liver, and have a protective effect on kidney damage caused by high UA. Through UPLC-Q-TOF-MS/MS analysis, 214 compounds were identified in WESJ, including flavonoids, polyphenols, triterpenoids, organic acids, and others. The rat serum of WESJ was analyzed, and 23 prototype components entering the blood were identified, including 15 flavonoids and polyphenols, which may be the main bioactive components. In conclusion, flavonoids and polyphenols in WESJ may reduce the level of UA and alleviate kidney damage by inhibiting the activity of XOD. WESJ is expected to be used as a plant-based food and dietary supplement for the treatment of HUA.

Rapid identification of chemical components in Zhizi Baipi decoction by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with a novel informatics UNIFI platform

Zhizi Baipi Decoction is a classic traditional Chinese medicine formula for the treatment of jaundice and various liver diseases. The chemical components of Zhizi baipi decoction were not clear resulting from the paucity of relevant studies, which hindered the elucidation of the pharmacological mechanism, the comprehensive development and utilization of Zhizi baipi decoction in clinical. In this study, ultra performance liquid chromatography-quadrupole-time of flight mass spectrometry combined with UNIFI natural product information analysis platform was used to rapidly analyze and identify the chemical components in Zhizi baipi decoction. A total of 122 chemical components, including 53 flavonoids, 16 alkaloids, 25 terpenoids, 5 phenylpropanoids, 14 organic acids, and 7 others, were identified from Zhizi baipi decoction. These compounds may be the active components of Zhizi baipi decoction. The method established in this study can systematically, rapidly, and accurately resolve the chemical components in Zhizi baipi decoction, which lays the foundation for further establishment of the pharmacodynamic substance basis and quality control of Zhizi baipi decoction. This article is protected by copyright. All rights reserved.

Integrated multicomponent analysis based on UHPLC-Q-Exactive Orbitrap-MS and network pharmacology to elucidate the potential mechanism of Baoyuan decoction against idiopathic pulmonary fibrosis

INTRODUCTION

Idiopathic pulmonary fibrosis (IPF) is a serious lung disease with a high mortality rate. Baoyuan decoction (BYD), a classic medicinal food homology recipe, has anti-apoptotic effects, enhances immune function, and alleviates fibrosis, suggesting that it may be a potential therapeutic drug for IPF.

OBJECTIVES

We aimed to identify the main active ingredients of BYD, determine the basis of its efficacy, prove its anti-IPF effects, and explore the mechanisms underlying its anti-IPF effects.

MATERIALS AND METHODS

In this study, the active components of BYD were detected and analysed by ultra-high-performance liquid chromatography coupled with hybrid quadrupole Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS). A network pharmacology analysis was performed to determine the potential targets and relevant pathways of BYD in treating IPF. Western blotting and quantitative real-time polymerase chain reaction (qPCR) were conducted to verify the efficacy of BYD against IPF. Finally, molecular docking and qPCR were performed to identify the central targets of BYD.

RESULTS

A total of 39 components of BYD were identified. After performing the network pharmacology analysis, 35 active components and eight presumptive targets of BYD were found to play a central role in its anti-IPF effects. The molecular docking results indicated that most of the active components of BYD exhibited good binding activity with these eight central target proteins. In addition, the expression of collagen, α-SMA, and these eight targets in human pulmonary fibroblast (HPF) cells was suppressed from treatment with BYD.

CONCLUSION

This study determined the efficacy of BYD against IPF and clarified its multiple-target and multiple-pathway mechanisms. Furthermore, the study also provides a new method for exploring the chemical and pharmacological bases of other traditional Chinese medicine (TCM).

Component Analysis and Anti-Colorectal Cancer Mechanism via AKT/mTOR Signalling Pathway of Sanghuangporus vaninii Extracts

Sanghuangporus vaninii (Ljub.) L.W. Zhou & Y.C. Dai (SV) is a major cultivar of Sanghuang, which is well known as an excellent anti-tumour drug and reaches the mainstream market in China. Water, 60% ethanol and 95% ethanol were used to extract the drug, and three kinds of polar extracts were obtained separately. Compared with water extracts and 95% ethanol extracts, the 60% ethanol extract had the highest flavonoid content, and its polysaccharide content was greater than that in the 95% ethanol extract and lower than that in the water extract. Its essential components were phenolics whose majority were phenolic acids, flavonoids and phenylpropanoids. This extract has better inhibition effects on the proliferation of SW480 human colon cancer cells, inducing cell apoptosis and blocking G2/M period cells. It can significantly inhibit gene expression and reduce the activation of the AKT/mTOR signalling pathway. The anti-cancer activity of the 60% ethanol extract is satisfactory and may be a result of the combined effects of polysaccharides and flavonoids. The data suggest that the 60% ethanol extract can be used as an adjuvant for chemotherapy and as a potential anti-cancer agent with broad development prospects.

A comparison of RIRD within chained and multiple schedules in the treatment of vocal stereotypy

Slaton and Hanley (2016) compared the effects of multiple and chained schedules on stereotypy and item engagement for 2 individuals who exhibited automatically maintained motor stereotypy. Contingent access to motor stereotypy (i.e., chained schedules) was more effective than time-based access (i.e., multiple schedules) at reducing motor stereotypy, increasing item engagement, and establishing stimulus control for both participants. We systematically replicated Slaton and Hanley with 2 participants by a) targeting vocal stereotypy, b) including response interruption and redirection as a treatment component across conditions, c) conducting sessions in the natural environment with teaching assistants as change agents, and d) conducting an analysis of the effective treatment component(s). Chained schedules were more effective for 1 participant, whereas both treatments were effective for the other participant. The component analysis showed that different components were necessary for effective treatment for each participant.

Rapid characterization of the constituents in Jigucao capsule using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry

Jigucao capsule is a well-known Chinese patent medicine for the treatment of acute and chronic hepatitis and cholecystitis. The chemical components of Jigucao capsule were not clear resulting from the paucity of relevant studies, which hindered the research of the pharmacological mechanism, the comprehensive development, and utilization of Jigucao capsule in clinical studies. By establishing a high-throughput ultra-performance liquid chromatography quadrupole time of flight mass spectrometry in combination with intelligent UNIFI software data processing platform to automatically characterize and identify the chemical profile of Jigucao capsule, 144 compounds were determined rapidly, including 34 terpenoids, 25 flavonoids, 22 steroids, 21 phenylpropanoids, 10 glycosides, six alkaloids, 13 organic acids, and other 13 components. These compounds may be the active components of Jigucao capsule. In this study, a rapid and robust method for comprehensively analyzing the chemical composition of Jigucao capsule was described and established for the first time. The results will provide a reference for the quality control of Jigucao capsule and the establishment of a higher quality standard, as well as for the pharmacodynamic material basis research.

Value of artificial intelligence model based on unenhanced computed tomography of urinary tract for preoperative prediction of calcium oxalate monohydrate stones in vivo

Background

Urolithiasis is a global disease with a high incidence and recurrence rate, and stone composition is closely related to the choice of treatment and preventive measures. Calcium oxalate monohydrate (COM) is the most common in clinical practice, which is hard and difficult to fragment. Preoperative identification of its components and selection of effective surgical methods can reduce the risk of patients having a second operation. Methods that can be used for stone composition analysis include infrared spectroscopy, X-ray diffraction, and polarized light microscopy, but they are all performed on stone specimens in vitro after surgery. This study aimed to design and develop an artificial intelligence (AI) model based on unenhanced computed tomography (CT) images of the urinary tract, and to investigate the predictive ability of the model for COM stones in vivo preoperatively, so as to provide surgeons with more accurate diagnostic information.

Methods

Preoperative unenhanced CT images of patients with urinary calculi whose components were determined by infrared spectroscopy in a single center were retrospectively analyzed, including 337 cases of COM stones and 170 of non-COM stones. All images were manually segmented and the image features were extracted, and randomly divided into the training and testing sets in a ratio of 7:3. The least absolute shrinkage and selection operation algorithm (LASSO) was used to construct the AI model, and classification of the training and testing sets was carried out.

Results

A total of 1,218 radiomics imaging features were extracted, and 8 features with non-zero coefficients were finally obtained. The sensitivity, specificity and accuracy of the AI model were 90.5%, 84.3% and 88.5% for the training set, and 90.1%, 84.3% and 88.3% for the testing set. The area under the curve was 0.935 for the training set and 0.933 for the testing set.

Conclusions

The AI model based on unenhanced CT images of the urinary tract can predict COM and non-COM stones in vivo preoperatively, and the model has high sensitivity, specificity and accuracy.

Mechanism of Pyrolysis Reaction of Al-Rich Al/PTFE/TiH2 Active Material

In order to obtain the chemical reaction mechanism of Al-rich Al/PTFE/TiH₂ composites in argon and oxygen atmosphere, Al/PTFE, PTFE/TiH₂, Al/TiH₂ and Al-rich Al/PTFE/TiH₂ with different contents of TiH₂ composites were prepared by using the wet mixing method. The pyrolysis behavior of the above composites was investigated by thermogravimetric differential scanning calorimeter (TG-DSC). In addition, the calorific value of the above composite was measured by an oxygen bomb calorimeter. The compositions of TG-DSC residues at different peak temperatures and 1000 °C and the residues of oxygen bomb experiment were analyzed by X-ray diffraction (XRD), The results show that the pyrolytic products of Al-rich Al/PTFE/TiH₂ materials under argon atmosphere can be divided into four stages. In the first stage (328.6–378.6 °C), the products are TiH_1.924, (C₂F₄)_n, (CF₂)_n, H₂(g), Al and TiH₂; in the second stage (510.8–534.3 °C), the products are Al, TiH_1.924, (C₂F₄)_n, (CF₂)_n, Ti, AlF₃, TiF₃, TiF₄(g), C and H₂(g). In the third stage (540.8–618.1 °C), the products are Al, C, Ti, (C₂F₄)_n, (CF₂)_n, AlF₃, TiF₃, TiF₄, CF₄(g), C₃F₆(g), C₄F₈(g), C₂F₆(g), Al₅Ti₂ and H₂(g); in the fourth stage (918.5–1000 °C), the products are AlCTi₂, Al₂Ti, AlTi, TiC, AlF₃, Al, TiF₃, TiC_0.957, TiC_0.981 and TiC_0.95. The calorific value of the combustion of Al-rich Al/PTFE/TiH₂ composite with 10% the content of TiH₂ is the highest and is 19,899 J/g, which is 3.776% higher than that of Al-rich Al/PTFE composite. When TiH₂ content is greater than zero and not more than 10%, the chemical reaction mechanism of Al-rich Al/PTFE/TiH₂ is almost the same under oxygen atmosphere. When the content of TiH₂ is higher than 10%, the mechanism of this material is different.

Determination and analysis of monosaccharides in Polygonatum cyrtonema Hua polysaccharides from different areas by ultra-high-performance liquid chromatography quadrupole trap tandem mass spectrometry

We wanted to explore a new method for the determination of monosaccharides in Polygonatum cyrtonema Hua polysaccharide using the ultra-high-performance liquid chromatography quadrupole trap tandem mass spectrometry. In this study, hydrochloric acid was used instead of trifluoroacetic acid to hydrolyze polysaccharides, and hydrolysis time was greatly reduced from 5-9 h to 1 h. The 1-phenyl-3-methyl-5-pyrazolone was used for pre-column derivatization of monosaccharides. The parameters of linearity (R²  > 0.999), stability (1.63-2.52%), intra-day and inter-day precision (0.69-0.95%, 1.81-2.77%), repeatability (1.89-2.65%), and recovery (97.63-102.24%) of the method were verified. Satisfactory validation results showed this method could be used to determine the target components. The results indicated the polysaccharide contained glucose, mannose, rhamnose, galactose, ribose, and arabinose. Technique for order preference by similarity to an ideal solution and principal component analysis were used to build an evaluation model based on the monosaccharide composition. The evaluation results showed that the samples from the Qingyang County of Anhui Province were the best when the monosaccharides were used as the evaluation index. Therefore, a new method was established to detect the monosaccharide content of polysaccharides from Polygonatum cyrtonema Hua and comprehensively evaluate the quality of Chinese medicines with polysaccharides as the main active ingredient.

Interteaching: How much does each component increase its efficacy?

Although interteaching has been shown to improve students' understanding of course material in a multitude of classroom studies, only one laboratory study investigating it has been published. In that study, interteaching led to significantly higher scores on a quiz compared to other teaching methods. The goal of the present study was to add to the laboratory literature in this area by determining which components of interteaching are important for students' academic success. A pretest/posttest design was used in which participants were randomly assigned to experience 1 of 4 conditions: 1) reading; 2) reading plus prep guide; 3) reading, prep guide, plus group discussion; or 4) reading, prep guide, group discussion, plus clarifying lecture. The results demonstrated that condition 3 produced the highest improvement in test scores, implying that the group discussion was integral to producing positive academic outcomes.

STATegra: Multi-Omics Data Integration - A Conceptual Scheme With a Bioinformatics Pipeline

Technologies for profiling samples using different omics platforms have been at the forefront since the human genome project. Large-scale multi-omics data hold the promise of deciphering different regulatory layers. Yet, while there is a myriad of bioinformatics tools, each multi-omics analysis appears to start from scratch with an arbitrary decision over which tools to use and how to combine them. Therefore, it is an unmet need to conceptualize how to integrate such data and implement and validate pipelines in different cases. We have designed a conceptual framework (STATegra), aiming it to be as generic as possible for multi-omics analysis, combining available multi-omic anlaysis tools (machine learning component analysis, non-parametric data combination, and a multi-omics exploratory analysis) in a step-wise manner. While in several studies, we have previously combined those integrative tools, here, we provide a systematic description of the STATegra framework and its validation using two The Cancer Genome Atlas (TCGA) case studies. For both, the Glioblastoma and the Skin Cutaneous Melanoma (SKCM) cases, we demonstrate an enhanced capacity of the framework (and beyond the individual tools) to identify features and pathways compared to single-omics analysis. Such an integrative multi-omics analysis framework for identifying features and components facilitates the discovery of new biology. Finally, we provide several options for applying the STATegra framework when parametric assumptions are fulfilled and for the case when not all the samples are profiled for all omics. The STATegra framework is built using several tools, which are being integrated step-by-step as OpenSource in the STATegRa Bioconductor package.

Component Analysis of Gas Mixture Based on One-Dimensional Convolutional Neural Network

Indoor harmful gases are a considerable threat to the health of residents. In order to improve the accuracy of indoor harmful gas component identification, we propose an indoor toxic gas component analysis method that is based on the combination of bionic olfactory and convolutional neural network. This method uses the convolutional neural network's ability to extract nonlinear features and identify each component of bionic oflactory respense signal. A comparison with the results of other methods verifies the improvement of recognition rate while with the same level of time cost, which proved the effectiveness of the proposed model. The experimental results showed that the recognition rate of different types and concentrations of harmful gas components reached 90.96% and it solved the problem of mutual interference between gases.

The Nature and Extent of Component Analyses for Improving or Mitigating Behavior: A Systematic Review

A component analysis is an approach where two or more independent variables are evaluated as a package and independently. The approach is used to assess and identify which component of a treatment package is the most effective. The purpose of this review is to document the application of component analyses to improve or mitigate non-academic behaviors with individuals with disabilities. We identified 21 research articles that used a component analysis to evaluate treatment packages with students who were identified as having or at-risk for a disability in classroom and/or alternative settings. Results from reviewing 21 articles (22 cases) indicate that 11 intervention packages had a single component that was critical for successful behavior change. Two articles suggested the entire intervention package was necessary while nine articles did not report a critical component or had variable results pertaining to critical components. The benefits and drawbacks of using component analyses for single case research are discussed. Implications for future research are also presented.

An expert consensus on the most effective components of cognitive behavioural therapy for adults with depression: a modified Delphi study

Designing new approaches to delivering cognitive behavioural therapy (CBT) requires an understanding of the key components. This study aimed to establish an expert consensus on the effective components of CBT for depressed adults. An international panel of 120 CBT experts was invited to participate in a modified Delphi study. Thirty-two experts participated in round 1; 21 also provided data in round 2. In round 1, experts rated the effectiveness of 35 content and process components. A priori rules identified components carried forward to round 2, in which experts re-rated items and final consensus items were identified. Consensus was achieved for nine content components (ensuring understanding; developing and maintaining a good therapeutic alliance; explaining the rationale for CBT; eliciting feedback; identifying and challenging avoidant behaviour; activity monitoring; undertaking an initial assessment; relapse prevention methods; homework assignments); and three process components (ensuring therapist competence; scheduling sessions flexibly; scheduling sessions for 45-60 mins). Five of the twelve components identified were generic therapeutic competences rather than specific CBT items. There was less agreement about the effectiveness of cognitive components of CBT. This is an important first step in the development of novel approaches to delivering CBT that may increase access to treatment for patients.

Revealing the Joint Mechanisms in Traditional Data Linked With Big Data

Recent technological advances have made it possible to study human behavior by linking novel types of data to more traditional types of psychological data, for example, linking psychological questionnaire data with genetic risk scores. Revealing the variables that are linked throughout these traditional and novel types of data gives crucial insight into the complex interplay between the multiple factors that determine human behavior, for example, the concerted action of genes and environment in the emergence of depression. Little or no theory is available on the link between such traditional and novel types of data, the latter usually consisting of a huge number of variables. The challenge is to select - in an automated way - those variables that are linked throughout the different blocks, and this eludes currently available methods for data analysis. To fill the methodological gap, we here present a novel data integration method.

[Application progress of gas chromatography-mass spectrometry in the analysis of human body odor]

Gas chromatography-mass spectrometry (GC-MS) is currently the most technical approach for the analysis of human body odor, which can be used to determine the composition of human body odor and compare the differences between different individual odors. This paper focuses on the application progress of GC-MS in human body odor analysis. First, the extraction and sample pretreatment of human body odor are briefly introduced. The applications of the human body odor analysis by GC-MS in collection and storage, the composition analysis and study of difference, and individual identification and health characterization are summarized. Finally, the application trends of GC-MS in human body odor analysis are discussed.

Analysis of Physiological Parameters of Desulfovibrio Strains from Individuals with Colitis

Intestinal sulfate-reducing bacteria are often isolated from patients with inflammatory bowel disease, including ulcerative colitis, and can be involved in the development of gut inflammation. A comparison of the metabolism of intestinal sulfate-reducing bacteria isolated from individuals with colitis and healthy controls using statistical analysis has never been studied and described before. The aim of our research was to evaluate the parameters of dissimilatory sulfate reduction in Desulfovibrio species that were isolated from the feces of healthy objects and individuals with colitis. Principal component analysis indicates that the strains that were isolated from individuals with colitis grouped in the same cluster by biomass accumulation and sulfide production, same as the strains isolated from healthy individuals. Sulfate and lactate consumption measured over time showed negative correlation (Pearson correlations, p<0.01), healthy: -0.760; colitis: -0.770; healthy: -0.828; colitis: -0.847, respectively. The calculated linear regression (R²) was lower in biomass accumulation and hydrogen sulfide production, 0.531; 0.625 respectively. Thus, biomass accumulation and sulfide production, together with measured kinetic parameters play an important factor in bowel inflammation, including ulcerative colitis. Additionally, acetate production can also synergize with H₂S, while sulfate consumption and lactate oxidation likely represent minor factors in bowel disease.

Comparison of components of the Good Behavior Game in a preschool classroom

The Good Behavior Game (GBG) is an effective intervention package for decreasing disruptive behavior in various populations and environments. There is, however, limited research evaluating the GBG with preschoolers. Furthermore, few studies have evaluated the effects of components of the GBG, and of those that have, most have done so only after exposure to the GBG package. We evaluated the effects (a) of the GBG on disruptive behavior of preschoolers during group instruction and (b) the major components of the GBG before and after implementation of the GBG package (c) at both the group and individual level. Results suggest that the GBG package was necessary for decreasing disruptive behavior. However, after exposure to the GBG, a response-independent contingency was effective for maintaining low levels of disruptive behavior at both the group and individual level.

Material basis studies of anti-Influenza A active ingredients in Tanreqing Injection

Tanreqing Injection (TRQ) has been used primarily in treating infections of the upper respiratory tract and serious influenza in China, as a classical compound herbal recipe. TRQ had been demonstrated to have effects of clearing heat, eliminating phlegm, detoxification, reducing inflammation and alleviating cough. The survival rate, histopathology of lungs and viral titers in mice were evaluated in this study to verify the curative effect of TRQ. However, there is not enough information about the components. In the present study, a high-performance and practical LC/QTOF/MS method was developed for characterization and identification of the natural ingredients in TRQ. A total of 60 compounds, including 10 amino acids, 10 iridoid glucosides, 14 flavonoids, 13 other phenolic compounds, 10 steroid acids and three other compounds, were characterized and identified. We also confirmed the material basis of anti-Influenza A active ingredients in TRQ. Therefore, we have developed an accurate analytical method. LC/QTOF/MS could be applied for identification the complex components in traditional Chinese medicine.

PENGUINS, PETRELS, AND PARSIMONY: DOES CLADISTIC ANALYSIS OF BEHAVIOR REFLECT SEABIRD PHYLOGENY?

Whether or not behavior accurately reflects evolutionary relationships (phylogeny) has been hotly debated by ethologists and comparative psychologists. Previous studies attempting to resolve this question have generally lacked a quantitative, phylogenetic approach. In this study we used behavior and life-history (BLH) information (72 characters) to generate phylogenetic trees for 18 seabird species (albatrosses, petrels, and penguins). We compared these trees with trees obtained from isozyme electrophoretic analysis of blood proteins (15 loci and 98 electromorphs) and partial mitochondrial 12S ribosomal DNA sequences (381 base pairs). Cladistic analysis of the BLH data set generated three MP trees (tree length = 243, CI = 0.52, RI = 0.57) with significant cladistic structure. The BLH characters were classified into four types (foraging, agonistic, reproductive, and life history) and levels of homoplasy for each type were measured. No significant differences were found among these categories. The BLH trees were shown to be significantly more congruent with the electrophoretic and 12S sequence trees than expected by chance. This indicates that seabird BLH data contains phylogenetic signal. Areas of incongruence between BLH trees and a phylogeny generated by combining the data sets were predicted to result from ecological constraints that did not covary with phylogeny. These predictions were supported by the results of a concentrated changes test. This study found that this BLH data set was no more homoplasious than molecular data and that BLH trees were significantly congruent with molecular trees.

Systematic review for geo-authentic Lonicerae Japonicae Flos

In traditional Chinese medicine, Lonicerae Japonicae Flos is commonly used as anti-inflammatory, antiviral, and antipyretic herbal medicine, and geo-authentic herbs are believed to present the highest quality among all samples from different regions. To discuss the current situation and trend of geo-authentic Lonicerae Japonicae Flos, we searched Chinese Biomedicine Literature Database, Chinese Journal Full-text Database, Chinese Scientific Journal Full-text Database, Cochrane Central Register of Controlled Trials, Wanfang, and PubMed. We investigated all studies up to November 2015 pertaining to quality assessment, discrimination, pharmacological effects, planting or processing, or ecological system of geo-authentic Lonicerae Japonicae Flos. Sixty-five studies mainly discussing about chemical fingerprint, component analysis, planting and processing, discrimination between varieties, ecological system, pharmacological effects, and safety were systematically reviewed. By analyzing these studies, we found that the key points of geo-authentic Lonicerae Japonicae Flos research were quality and application. Further studies should focus on improving the quality by selecting the more superior of all varieties and evaluating clinical effectiveness.

Efficient generation of receiver operating characteristics for the evaluation of damage detection in practical structural health monitoring applications

Permanently installed guided wave monitoring systems are attractive for monitoring large structures. By frequently interrogating the test structure over a long period of time, such systems have the potential to detect defects much earlier than with conventional one-off inspection, and reduce the time and labour cost involved. However, for the systems to be accepted under real operational conditions, their damage detection performance needs to be evaluated in these practical settings. The receiver operating characteristic (ROC) is an established performance metric for one-off inspections, but the generation of the ROC requires many test structures with realistic damage growth at different locations and different environmental conditions, and this is often impractical. In this paper, we propose an evaluation framework using experimental data collected over multiple environmental cycles on an undamaged structure with synthetic damage signatures added by superposition. Recent advances in computation power enable examples covering a wide range of practical scenarios to be generated, and for multiple cases of each scenario to be tested so that the statistics of the performance can be evaluated. The proposed methodology has been demonstrated using data collected from a laboratory pipe specimen over many temperature cycles, superposed with damage signatures predicted for a flat-bottom hole growing at different rates at various locations. Three damage detection schemes, conventional baseline subtraction, singular value decomposition (SVD) and independent component analysis (ICA), have been evaluated. It has been shown that in all cases, the component methods perform significantly better than the residual method, with ICA generally the better of the two. The results have been validated using experimental data monitoring a pipe in which a flat-bottom hole was drilled and enlarged over successive temperature cycles. The methodology can be used to evaluate the performance of an installed monitoring system and to show whether it is capable of detecting particular damage growth at any given location. It will enable monitoring results to be evaluated rigorously and will be valuable in the development of safety cases.

Efficient generation of receiver operating characteristics for the evaluation of damage detection in practical structural health monitoring applications

Permanently installed guided wave monitoring systems are attractive for monitoring large structures. By frequently interrogating the test structure over a long period of time, such systems have the potential to detect defects much earlier than with conventional one-off inspection, and reduce the time and labour cost involved. However, for the systems to be accepted under real operational conditions, their damage detection performance needs to be evaluated in these practical settings. The receiver operating characteristic (ROC) is an established performance metric for one-off inspections, but the generation of the ROC requires many test structures with realistic damage growth at different locations and different environmental conditions, and this is often impractical. In this paper, we propose an evaluation framework using experimental data collected over multiple environmental cycles on an undamaged structure with synthetic damage signatures added by superposition. Recent advances in computation power enable examples covering a wide range of practical scenarios to be generated, and for multiple cases of each scenario to be tested so that the statistics of the performance can be evaluated. The proposed methodology has been demonstrated using data collected from a laboratory pipe specimen over many temperature cycles, superposed with damage signatures predicted for a flat-bottom hole growing at different rates at various locations. Three damage detection schemes, conventional baseline subtraction, singular value decomposition (SVD) and independent component analysis (ICA), have been evaluated. It has been shown that in all cases, the component methods perform significantly better than the residual method, with ICA generally the better of the two. The results have been validated using experimental data monitoring a pipe in which a flat-bottom hole was drilled and enlarged over successive temperature cycles. The methodology can be used to evaluate the performance of an installed monitoring system and to show whether it is capable of detecting particular damage growth at any given location. It will enable monitoring results to be evaluated rigorously and will be valuable in the development of safety cases.

Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data

In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three reasons: first, multiple highly collinear predictors can be available, making it difficult to grasp their mutual relations as well as their relations to the criterion. In that case, it may be very useful to reduce the predictors to a few summary variables, on which one regresses the criterion and which at the same time yields insight into the predictor structure. Second, the population under study may consist of a few unknown subgroups that are characterized by different regression models. Third, the obtained data are often hierarchically structured, with for instance, observations being nested into persons or participants within groups or countries. Although some methods have been developed that partially meet these challenges (i.e., principal covariates regression (PCovR), clusterwise regression (CR), and structural equation models), none of these methods adequately deals with all of them simultaneously. To fill this gap, we propose the principal covariates clusterwise regression (PCCR) method, which combines the key idea's behind PCovR (de Jong & Kiers in Chemom Intell Lab Syst 14(1-3):155-164, 1992) and CR (Späth in Computing 22(4):367-373, 1979). The PCCR method is validated by means of a simulation study and by applying it to cross-cultural data regarding satisfaction with life.

Do we need both cognitive and behavioural components in interventions for depressed mood in people with mild intellectual disability?

BACKGROUND

A growing literature suggests that people with mild intellectual disability (ID) who have depressed mood may benefit from cognitive-behavioural interventions. There has been some speculation regarding the relative merit of the components of this approach. The aim of this study was to compare (i) cognitive strategies; (ii) behavioural strategies; and (iii) combined cognitive-behavioural (CB) strategies on depressed mood among a sample of 70 individuals with mild ID.

METHODS

Staff from three participating agencies received training in how to screen individuals with mild ID for depressive symptoms and risk factors for depression. Depressive symptoms and negative automatic thoughts were assessed prior to and at the conclusion of the intervention, and at 6-month follow-up. The interventions were run in groups by the same therapist.

RESULTS

A post-intervention reduction in depression scores was evident in participants of all three interventions, with no significant difference between groups. A significant reduction in negative automatic thoughts post-intervention was evident in the CB combination group and was maintained at follow-up. Examination of clinical effectiveness suggests some advantage of the CB combination in terms of improvement and highlights the possible short term impact of behavioural strategies in comparison with the longer-term potential of cognitive strategies.

CONCLUSIONS

The findings support the use of group cognitive-behavioural interventions for addressing symptoms of depression among people with ID. Further research is necessary to determine the effectiveness of components.

Practical aspects of estimating energy components in rodents

Recently there has been an increasing interest in exploiting computational and statistical techniques for the purpose of component analysis of indirect calorimetry data. Using these methods it becomes possible to dissect daily energy expenditure into its components and to assess the dynamic response of the resting metabolic rate (RMR) to nutritional and pharmacological manipulations. To perform robust component analysis, however, is not straightforward and typically requires the tuning of parameters and the preprocessing of data. Moreover the degree of accuracy that can be attained by these methods depends on the configuration of the system, which must be properly taken into account when setting up experimental studies. Here, we review the methods of Kalman filtering, linear, and penalized spline regression, and minimal energy expenditure estimation in the context of component analysis and discuss their results on high resolution datasets from mice and rats. In addition, we investigate the effect of the sample time, the accuracy of the activity sensor, and the washout time of the chamber on the estimation accuracy. We found that on the high resolution data there was a strong correlation between the results of Kalman filtering and penalized spline (P-spline) regression, except for the activity respiratory quotient (RQ). For low resolution data the basal metabolic rate (BMR) and resting RQ could still be estimated accurately with P-spline regression, having a strong correlation with the high resolution estimate (R² > 0.997; sample time of 9 min). In contrast, the thermic effect of food (TEF) and activity related energy expenditure (AEE) were more sensitive to a reduction in the sample rate (R² > 0.97). In conclusion, for component analysis on data generated by single channel systems with continuous data acquisition both Kalman filtering and P-spline regression can be used, while for low resolution data from multichannel systems P-spline regression gives more robust results.

Decreased efficiency of task-positive and task-negative networks during working memory in schizophrenia

Working memory (WM) is one of the most impaired cognitive processes in schizophrenia. Functional magnetic resonance imaging (fMRI) studies in this area have typically found a reduction in information processing efficiency but have focused on the dorsolateral prefrontal cortex. In the current study using the Sternberg Item Recognition Test, we consider networks of regions supporting WM and measure the activation of functionally connected neural networks over different WM load conditions. We used constrained principal component analysis with a finite impulse response basis set to compare the estimated hemodynamic response associated with different WM load condition for 15 healthy control subjects and 15 schizophrenia patients. Three components emerged, reflecting activated (task-positive) and deactivated (task-negative or default-mode) neural networks. Two of the components (with both task-positive and task-negative aspects) were load dependent, were involved in encoding and delay phases (one exclusively encoding and the other both encoding and delay), and both showed evidence for decreased efficiency in patients. The results suggest that WM capacity is reached sooner for schizophrenia patients as the overt levels of WM load increase, to the point that further increases in overt memory load do not increase fMRI activation, and lead to performance impairments. These results are consistent with an account holding that patients show reduced efficiency in task-positive and task-negative networks during WM and also partially support the shifted inverted-U-shaped curve theory of the relationship between WM load and fMRI activation in schizophrenia.

The risk-benefit task of research ethics committees: an evaluation of current approaches and the need to incorporate decision studies methods

BACKGROUND

Research ethics committees (RECs) are tasked to assess the risks and the benefits of a trial. Currently, two procedure-level approaches are predominant, the Net Risk Test and the Component Analysis.

DISCUSSION

By looking at decision studies, we see that both procedure-level approaches conflate the various risk-benefit tasks, i.e., risk-benefit assessment, risk-benefit evaluation, risk treatment, and decision making. This conflation makes the RECs' risk-benefit task confusing, if not impossible. We further realize that RECs are not meant to do all the risk-benefit tasks; instead, RECs are meant to evaluate risks and benefits, appraise risk treatment suggestions, and make the final decision.

CONCLUSION

As such, research ethics would benefit from looking beyond the procedure-level approaches and allowing disciplines like decision studies to be involved in the discourse on RECs' risk-benefit task.

Applications of HPLC/MS in the analysis of traditional Chinese medicines

In China, traditional Chinese medicines (TCMs) have been used in clinical applications for thousands of years. The successful hyphenation of high-Performance liquid chromatography (HPLC) and mass spectrometry (MS) has been applied widely in TCMs and biological samples analysis. Undoubtedly, HPLC/MS technique has facilitated the understanding of the treatment mechanism of TCMs. We reviewed more than 350 published papers within the last 5 years on HPLC/MS in the analysis of TCMs. The present review focused on the applications of HPLC/MS in the component analysis, metabolites analysis, and pharmacokinetics of TCMs etc. 50% of the literature is related to the component analysis of TCMs, which show that this field is the most populär type of research. In the metabolites analysis, HPLC coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry has been demonstrated to be the powerful tool for the characterization of structural features and fragmentation behavior patterns. This paper presented a brief overview of the applications of HPLC/MS in the analysis of TCMs. HPLC/MS in the fingerprint analysis is reviewed elsewhere.

Component analyses using single-subject experimental designs: a review

A component analysis is a systematic assessment of 2 or more independent variables or components that comprise a treatment package. Component analyses are important for the analysis of behavior; however, previous research provides only cursory descriptions of the topic. Therefore, in this review the definition of component analysis is discussed, and a notation system for evaluating the experimental designs of component analyses is described. Thirty articles that included a component analysis were identified via a literature search. The majority of the studies successfully identified a necessary component; however, most of these studies did not evaluate the sufficiency of the necessary component. The notation system may be helpful in developing experimental designs that best suit the purpose of studies aimed at conducting component analyses of treatment packages.

Refuting the net risks test: a response to Wendler and Miller's "Assessing research risks systematically"

Earlier in the pages of this journal (p 481), Wendler and Miller offered the "net risks test" as an alternative approach to the ethical analysis of benefits and harms in research. They have been vocal critics of the dominant view of benefit-harm analysis in research ethics, which encompasses core concepts of duty of care, clinical equipoise and component analysis. They had been challenged to come up with a viable alternative to component analysis which meets five criteria. The alternative must (1) protect research subjects; (2) allow clinical research to proceed; (3) explain how physicians may offer trial enrolment to their patients; (4) address the challenges posed by research containing a mixture of interventions and (5) define ethical standards according to which the risks and potential benefits of research may be consistently evaluated. This response argues that the net risks test meets none of these criteria and concludes that it is not a viable alternative to component analysis.