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  1. Book ; Online ; E-Book: Treatment-Resistant Depression

    Li, Cheng-Ta / Zheng, Zhiming

    (Issn Series)

    2023  

    Author's details Cheng-Ta Li and Chih-Ming Cheng
    Series title Issn Series
    Keywords Depression, Mental/Treatment
    Subject code 616.852706
    Language English
    Size 1 online resource (190 pages)
    Edition First edition.
    Publisher Zoe Kruze
    Publishing place Cambridge, MA
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 0-323-95778-1 ; 0-323-95779-X ; 978-0-323-95778-6 ; 978-0-323-95779-3
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online ; E-Book: Treatment-Resistant Depression Part B

    Zheng, Zhiming / Li, Cheng-Ta

    2023  

    Author's details Chih-Ming Cheng and Cheng-Ta Li
    Keywords Depression/Mental Treatment
    Subject code 733
    Language English
    Size 1 online resource (190 pages)
    Edition First edition.
    Publisher Elsevier
    Publishing place Amsterdam, Netherlands
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 0-443-22395-5 ; 0-443-22394-7 ; 978-0-443-22395-2 ; 978-0-443-22394-5
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Article ; Online: Structural basis for rice starch multi-digestible fractions revealed by consecutive reaction kinetics model.

    Li, Cheng

    Journal of the science of food and agriculture

    2023  Volume 103, Issue 8, Page(s) 4203–4210

    Abstract: Background: Starch-based foods (e.g. rice) usually contain multiple starch fractions with distinct digestion rate constants, although their nature is currently unknown. The present study applied the recently developed consecutive reaction kinetics model ...

    Abstract Background: Starch-based foods (e.g. rice) usually contain multiple starch fractions with distinct digestion rate constants, although their nature is currently unknown. The present study applied the recently developed consecutive reaction kinetics model to fit the in vitro digestion curves for starch fractions deconvoluted from the overall digestograms to differentiate their binding and catalysis rates to starch digestive enzymes. The fitting parameters were then correlated with starch molecular structures obtained from published data to understand starch structural features determining the binding and catalytic rate constants.
    Results: Binding and catalysis rates for the rapidly (RDF) and slowly digestible starch fraction (SDF) were controlled by distinct starch structural features. Typically, (i) the binding rate constant for RDF was negatively correlated with the amount of amylose short to intermediate chains, whereas it was positively correlated with the relative length of amylopectin intermediate chains; (ii) the catalysis rate constant for RDF was negatively correlated with the amount of amylose short to intermediate chains, relative length of amylose intermediate chains and amount of amylopectin long chains, whereas it was positively correlated with starch molecular size as well as relative length of amylopectin intermediate chains; (iii) and the catalysis rate constant for SDF was negatively correlated with the amount of amylopectin long chains, whereas it was positively correlated with starch molecular size.
    Conclusion: These results provide a better understanding of the nature of different starch digestible fractions and the development of foods such as rice with slow starch digestibility. © 2023 Society of Chemical Industry.
    MeSH term(s) Oryza/chemistry ; Starch/chemistry ; Digestion ; Kinetics ; Catalysis ; Amylose/chemistry
    Chemical Substances Starch (9005-25-8) ; Amylose (9005-82-7)
    Language English
    Publishing date 2023-01-24
    Publishing country England
    Document type Journal Article
    ZDB-ID 184116-6
    ISSN 1097-0010 ; 0022-5142
    ISSN (online) 1097-0010
    ISSN 0022-5142
    DOI 10.1002/jsfa.12451
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Preface.

    Li, Cheng-Ta

    Progress in brain research

    2023  Volume 278, Page(s) xi

    Language English
    Publishing date 2023-06-05
    Publishing country Netherlands
    Document type Editorial
    ISSN 1875-7855 ; 0079-6123
    ISSN (online) 1875-7855
    ISSN 0079-6123
    DOI 10.1016/S0079-6123(23)00065-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Overview of treatment-resistant depression.

    Li, Cheng-Ta

    Progress in brain research

    2023  Volume 278, Page(s) 1–23

    Abstract: Patients with major depressive disorder (MDD) often exhibit an inadequate treatment response or failure to achieve remission following treatment with antidepressant drugs. Treatment-resistant depression (TRD) is proposed to identify this clinical ... ...

    Abstract Patients with major depressive disorder (MDD) often exhibit an inadequate treatment response or failure to achieve remission following treatment with antidepressant drugs. Treatment-resistant depression (TRD) is proposed to identify this clinical scenario. Compared to those without TRD, patients with TRD have significantly lower health-related quality of life in mental and physical dimensions, more functional impairment and productivity loss, and higher healthcare costs. TRD imposes a massive burden on the individual, family, and society. However, a lack of consensus on the TRD definition limits the comparison and interpretation of TRD treatment efficacy across trials. Furthermore, because of the various TRD definitions, there is scarce treatment guideline specifically for TRD, in contrast to the rich treatment guidelines for MDD. In this chapter, common issues related to TRD, such as proper definitions of an adequate antidepressant trial and TRD, were carefully reviewed. Prevalence of and clinical outcomes related to TRD were summarized. We also summarized the staging models ever proposed for the diagnosis of TRD. Furthermore, we highlighted variations in the definition regarding the lack of or an inadequate response in treatment guidelines for depression. Up-to-date treatment options for TRD, including pharmacological strategies, psychotherapeutic interventions, neurostimulation techniques, glutamatergic compounds, and even experimental agents were reviewed.
    MeSH term(s) Humans ; Antidepressive Agents/therapeutic use ; Depression ; Depressive Disorder, Major/drug therapy ; Depressive Disorder, Treatment-Resistant/drug therapy ; Depressive Disorder, Treatment-Resistant/diagnosis ; Quality of Life
    Chemical Substances Antidepressive Agents
    Language English
    Publishing date 2023-05-15
    Publishing country Netherlands
    Document type Comparative Study ; Journal Article
    ISSN 1875-7855 ; 0079-6123
    ISSN (online) 1875-7855
    ISSN 0079-6123
    DOI 10.1016/bs.pbr.2023.03.007
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Preface.

    Li, Cheng-Ta

    Progress in brain research

    2023  Volume 281, Page(s) xiii

    Language English
    Publishing date 2023-08-07
    Publishing country Netherlands
    Document type Editorial
    ISSN 1875-7855 ; 0079-6123
    ISSN (online) 1875-7855
    ISSN 0079-6123
    DOI 10.1016/S0079-6123(23)00104-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Empirical selection of referent variables: Comparing multiple-indicator multiple-cause-interaction modeling and moderated nonlinear factor analysis.

    Li, Cheng-Hsien

    Psychological methods

    2023  

    Abstract: The fulfillment of measurement invariance/equivalence is considered a prerequisite for meaningfully proceeding with substantive cross-group comparisons. In the multiple-group confirmatory factor analysis approach, one model identification issue has ... ...

    Abstract The fulfillment of measurement invariance/equivalence is considered a prerequisite for meaningfully proceeding with substantive cross-group comparisons. In the multiple-group confirmatory factor analysis approach, one model identification issue has unfortunately received little attention: the specification of a referent variable in the test of measurement invariance. A multiple-indicator multiple-cause (MIMIC) model with moderated effects (i.e., MIMIC-interaction modeling; Woods & Grimm, 2011) and a moderated nonlinear factor analysis (MNLFA; Bauer, 2017) model for detecting uniform and nonuniform measurement inequivalences in tandem were proposed to identify credible referent variables. The performance of two search strategies, constrained and free baseline models, and MIMIC-interaction and MNLFA methodologies were evaluated in a Monte Carlo simulation. Effects of different configurations of the number of inequivalent variables, type and magnitude of inequivalence, magnitude of group differences in factor means and variances, and sample size in combination with each search strategy were determined. Results showed that the constrained baseline model strategy generally outperformed the free baseline model strategy for identifying credible referent variables, functioning well when up to one-third of the observed variables were noninvariant. Moreover, MNLFA performed better than MIMIC-interaction modeling for the selection of referent variables across nearly all conditions investigated in the study. The superiority of MNLFA over MIMIC-interaction modeling was specifically evident in the models with relatively small samples, large between-group latent variance differences, or a combination of both. An empirical example was presented to demonstrate the applicability of MNLFA with the constrained baseline model strategy for referent variable selection. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
    Language English
    Publishing date 2023-11-13
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2103345-6
    ISSN 1939-1463 ; 1082-989X
    ISSN (online) 1939-1463
    ISSN 1082-989X
    DOI 10.1037/met0000613
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Starch fine molecular structures: The basis for designer rice with slower digestibility and desirable texture properties.

    Li, Cheng

    Carbohydrate polymers

    2022  Volume 299, Page(s) 120217

    Abstract: Development of whole rice with low glycaemic index has been achieved, however, these rices are frequently associated with a poor texture property. Recent advances in terms of understanding the importance of starch fine molecular structures on the starch ... ...

    Abstract Development of whole rice with low glycaemic index has been achieved, however, these rices are frequently associated with a poor texture property. Recent advances in terms of understanding the importance of starch fine molecular structures on the starch digestibility/texture of cooked whole rice have shed new insights on mechanisms of starch digestibility and texture from molecular levels. With an extensive discussion on the correlative and causal relationships among starch molecular structure, texture and starch digestibility of cooked whole rice, this review identified desirable starch fine molecular structures contributing to both slow starch digestibility and preferable textures. For instance, the selection of rice variety having more amylopectin intermediate chains while less amylopectin long chains might help develop cooked whole rice with both slower starch digestibility and softer texture. The information could help rice industry transform cooked whole rice into a healthier food product with slow starch digestibility and desirable texture.
    MeSH term(s) Starch ; Oryza ; Amylopectin ; Molecular Structure ; Cooking
    Chemical Substances Starch (9005-25-8) ; Amylopectin (9037-22-3)
    Language English
    Publishing date 2022-10-13
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 1501516-6
    ISSN 1879-1344 ; 0144-8617
    ISSN (online) 1879-1344
    ISSN 0144-8617
    DOI 10.1016/j.carbpol.2022.120217
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Recent progress in understanding starch gelatinization - An important property determining food quality.

    Li, Cheng

    Carbohydrate polymers

    2022  Volume 293, Page(s) 119735

    Abstract: Starch gelatinization is a crucial process in determining both texture and nutrition properties of starch-based foods, while its complex nature is still not fully understood. Kinetics modeling has been recently developed for understanding starch ... ...

    Abstract Starch gelatinization is a crucial process in determining both texture and nutrition properties of starch-based foods, while its complex nature is still not fully understood. Kinetics modeling has been recently developed for understanding starch gelatinization under both limited and excessive water content. Amylose with different chain lengths has distinct effects on starch gelatinization temperatures and enthalpy by interacting with amylopectin chains in semi-crystalline lamella. Moisture is a crucial factor in determining starch gelatinization property, with new evidence suggesting that different groups of amylopectin-amylopectin or amylose-amylopectin double helices are involved for multi-endothermic gelatinization peaks under limited moisture content. The presence of salts, sugars, protein, lipids and non-starch polysaccharides can affect starch gelatinization through various mechanisms. All these new insights and future directions in terms of better understanding starch gelatinization property were summarized. This information could help develop new generations of foods with desirable properties through a better understanding of starch gelatinization process.
    MeSH term(s) Amylopectin/chemistry ; Amylose/chemistry ; Food Quality ; Starch/chemistry ; Temperature
    Chemical Substances Starch (9005-25-8) ; Amylose (9005-82-7) ; Amylopectin (9037-22-3)
    Language English
    Publishing date 2022-06-15
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 1501516-6
    ISSN 1879-1344 ; 0144-8617
    ISSN (online) 1879-1344
    ISSN 0144-8617
    DOI 10.1016/j.carbpol.2022.119735
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Understanding interactions among diet, host and gut microbiota for personalized nutrition.

    Li, Cheng

    Life sciences

    2022  Volume 312, Page(s) 121265

    Abstract: Human responses to the same diets may vary to a large extent, depending on the complex diet-host-microbiota interactions. Recent scientific advance has indicated that this diet-host-microbiota interaction could be quantified to develop strategies for ... ...

    Abstract Human responses to the same diets may vary to a large extent, depending on the complex diet-host-microbiota interactions. Recent scientific advance has indicated that this diet-host-microbiota interaction could be quantified to develop strategies for improving individual health (personalized nutrition). Compared to the host related factors (which are difficult to manipulate), the gut microbiome is more readily modulated by dietary exposures and has important roles in affecting human health via the synthesis of various bioactive compounds and participating in the digestion and absorption process of macro- and micronutrients. Therefore, gut microbiota alterations induced by diets could possibly be utilized to improve human health in a targeted manner. However, limitations in the processing and analysis of 'big-data' concerning human microbiome still restrict the translational capacity of diet-host-microbiota interactions into tools to improve personalized human health. In the current review, recent advances in terms of understanding the specific diet-host-microbiota interactions were summarized, aiming to help the development of strategies for personalized nutrition.
    Language English
    Publishing date 2022-12-05
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 3378-9
    ISSN 1879-0631 ; 0024-3205
    ISSN (online) 1879-0631
    ISSN 0024-3205
    DOI 10.1016/j.lfs.2022.121265
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Uc I Zs.368: Show issues Location:
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