Research and exploration of quality control indicators for nutritional therapy in critically ill patients-a multicenter before-and-after controlled study.

Objective: To evaluate and explore the feasibility of using quality control indicators for nutritional therapy in critically ill patients as quality evaluation criteria. Methods: This study focused on intensive care unit (ICU) critically ill patients and conducted a cross-sectional investigation of nutritional therapy quality control indicators (the proportion of patients with application of enteral nutrition pump, nutritional risk assessment rate, the proportion of patients start enteral nutrition within 48 hours, and caloric and protein target achievement rate on 7th day) in 13 hospitals in Jilin Province. After training according to the critical patients nutrition related guidelines and the latest literatures, a second cross-sectional investigation was conducted. Then, analyze the improvement of quality control indicators of the nutritional therapy before and after the training, thus evaluating the feasibility of using these quality control indicators as nutritional therapy quality evaluation criteria in critical patients. Results: (1) A total of 631 patients were included before and after training, with a data acquisition rate of 97.3% for enteral nutrition pumps usage and complete data collection for the remaining nutritional risk assessment rate, start enteral nutrition proportion of patients within 48 h, and caloric and protein target achievement rate on 7th day. (2) The nutritional risk assessment rate before and after training was 88.2% vs. 94.8%, with a P-value of 0.003. The proportion of patients start enteral nutrition within 48 h before and after training was 65.1% vs. 75.4%, with a P-value of 0.039; and protein target achievement rate on 7th day before and after training was 64.6% vs. 79.6%, with a p-value of 0.015. These five indicators as quality evaluation criteria are relevant to the current developments in nutritional therapy and consistent with the national conditions of China. The proportion of patients with application of enteral nutrition pump before and after training was 70.1% vs. 79.4%, with a p-value of 0.065, and the caloric target achievement rate on 7th day before and after training was 73.4% vs. 83.9%, with a p-value of 0.062, and there was no statistical difference between the two groups. Conclusion: The five quality control indicators for nutritional therapy in critically ill patients are clinically feasible and can be used as quality evaluation criteria for nutritional therapy in critically ill patients.

Identification of Euphorbiae pekinensis Radix and its counterfeit and adulterated products based on DNA barcode, UPLC-Q-TOF-MS, UPLC fingerprint, and chemometrics.

Euphorbiae pekinensis Radix (EPR) is a traditional Chinese herb commonly used to treat edema, pleural effusion, and ascites. However, counterfeit and adulterated products often appear in the market because of the homonym phenomenon, similar appearance, and artificial forgery of Chinese herbs. This study comprehensively evaluated the quality of EPR using multiple methods. The DNA barcode technique was used to identify EPR, while the UPLC-Q-TOF-MS technique was utilized to analyze the chemical composition of EPR. A total of 15 tannin and phenolic acid components were identified. Furthermore, UPLC fingerprints of EPR and its common counterfeit products were established, and unsupervised and supervised pattern recognition models were developed using these fingerprints. The backpropagation artificial neural network and counter-propagation artificial neural network models accurately identified counterfeit and adulterated products, with a counterfeit ratio of more than 25%. Finally, the contents of the chemical markers 3,3'-di-O-methyl ellagic acid-4'-O-ß-D-glucopyranoside, ellagic acid, 3,3'-di-O-methyl ellagic acid-4'-O-ß-d-xylopyranoside, and 3,3'-di-O-methyl ellagic acid were determined to range from 0.05% to 0.11%, 1.95% to 8.52%, 0.27% to 0.86%, and 0.10% to 0.42%, respectively. This proposed strategy offers a general procedure for identifying Chinese herbs and distinguishing between counterfeit and adulterated products.

Evaluation of treatment information quality on hypertension and diabetes on WeChat and TikTok: A cross-sectional content analysis.

Objective: This study aimed to assess the quality of the information in WeChat and TikTok videos related to hypertension and diabetes treatment. Methods: A sample of 120 Chinese videos was collected based on specific inclusion and exclusion criteria. The quality was evaluated using DISCERN, JAMA and the latest edition of Chinese guidelines for hypertension and diabetes prevention and treatment, and two observers independently scored each video using the three assessment tools. Results: Among all 120 videos, only 10 scored above 38 points in DISCERN, with 45 videos rated as "very poor". None of the video met all JAMA criteria simultaneously, and there were gaps in accuracy and completeness compared to the two guidelines. Furthermore, there was no significant correlation between information quality and the number of likes and comments. Conclusion: The current quality of information on the treatment of hypertension and diabetes on WeChat and TikTok was unsatisfactory. Consequently, the government should strengthen oversight of information quality, and social media platforms should actively review health-related content to prevent inaccurate information dissemination. Individuals should enhance their digital and health literacy.

Research on Traditional Chinese Medicine: Domain Knowledge Graph Completion and Quality Evaluation.

BACKGROUND: Knowledge graphs (KGs) can integrate domain knowledge into a traditional Chinese medicine (TCM) intelligent syndrome differentiation model. However, the quality of current KGs in the TCM domain varies greatly, related to the lack of knowledge graph completion (KGC) and evaluation methods. OBJECTIVE: This study aims to investigate KGC and evaluation methods tailored for TCM domain knowledge. METHODS: In the KGC phase, according to the characteristics of TCM domain knowledge, we proposed a 3-step "entity-ontology-path" completion approach. This approach uses path reasoning, ontology rule reasoning, and association rules. In the KGC quality evaluation phase, we proposed a 3-dimensional evaluation framework that encompasses completeness, accuracy, and usability, using quantitative metrics such as complex network analysis, ontology reasoning, and graph representation. Furthermore, we compared the impact of different graph representation models on KG usability. RESULTS: In the KGC phase, 52, 107, 27, and 479 triples were added by outlier analysis, rule-based reasoning, association rules, and path-based reasoning, respectively. In addition, rule-based reasoning identified 14 contradictory triples. In the KGC quality evaluation phase, in terms of completeness, KG had higher density and lower sparsity after completion, and there were no contradictory rules within the KG. In terms of accuracy, KG after completion was more consistent with prior knowledge. In terms of usability, the mean reciprocal ranking, mean rank, and hit rate of the first N tail entities predicted by the model (Hits@N) of the TransE, RotatE, DistMult, and ComplEx graph representation models all showed improvement after KGC. Among them, the RotatE model achieved the best representation. CONCLUSIONS: The 3-step completion approach can effectively improve the completeness, accuracy, and availability of KGs, and the 3-dimensional evaluation framework can be used for comprehensive KGC evaluation. In the TCM field, the RotatE model performed better at KG representation.

Establishment of an antiplatelet aggregation efficacy-oriented effect-constituent index for quality evaluation of Curcumae Rhizoma from different species (Curcuma phaeocaulis Val, Curcuma kwangsiensis S. G. Lee et C. F. Liang and Curcuma wenyujin Y. H. Chen et C. Ling).

Curcumae rhizoma (CR) is the dried rhizoma of Curcuma phaeocaulis Val (CP), Curcuma kwangsiensis S. G. Lee et C. F. Liang (CK) and Curcuma wenyujin Y. H. Chen et C. Ling (CW), used widely to treat blood stagnation in China. Currently, quality control indicators for CR are limited to chemical composition analysis. It is unclear whether the current quality standard of the multicomponent content of CR can reflect clinical effects, due to the lack of the evaluation of biological effects. A method of evaluating quality was developed called the effect-constituent index (ECI). By meticulously measuring and calibrating the key active components, the ECI offers a comprehensive assessment of the CR's biological effects, establishing a crucial link to clinical efficacy and safety. An analytical protocol employing high-performance liquid chromatography (HPLC) was devised to ascertain the presence and measure ten principal constituents within CR sourced from various species and the content of total volatile oil was also measured. An In vitro antiplatelet aggregation assay was developed to measure the antiplatelet aggregation biopotencies of thirty batches of CR and ten main components. Then, the calibration weights for each constituent in the ECI were determined based on the antiplatelet aggregation biopotency values of eight components with notable efficacy. The ECI calculation involved summing the products obtained by multiplying the content (Ci) of each component by its corresponding biopotency weight (Wi). Correlation analysis unveiled a the most robust correlation (R = 0.8579, p < 0.001) between ECI and antiplatelet aggregation biopotency of CR, when compared to individual components or volatile oil content. The devised ECI, synthesizing chemical and biological data pertinent to clinical effectiveness, facilitates a nuanced assessment of CR quality across various species in its efficacy in treating blood stagnation. This method addresses the challenge of guaranteeing effectiveness through chemical analysis alone. This study offers substantiation for the applicability of the ECI as a tool for assessing the quality of traditional Chinese medicine (TCM).

Quality evaluation of Qiangli Tianma Duzhong (QLTMDZ) employing UHPLC-MS: A multivariate statistical analysis across multiple dosage forms and manufacturers.

Traditional Chinese medicine (TCM) and its preparations have become increasingly popular in recent years. Nonetheless, due to the high complexity of the compounds in Traditional Chinese Patent Medicine (TCPM), the quality differences between different dosage forms and products from various manufacturers pose numerous challenges and difficulties in quality evaluation. The Qiangli Tianma Duzhong (QLTMDZ) prescription, comprising twelve TCM, is widely used in China. Despite its prevalence, current research on QLTMDZ is limited and lacks in-depth and systematic analysis of the chemical composition of the prescription. In this study, a comprehensive strategy was proposed for characterizing the chemical profile of QLTMDZ based on UHPLC-Q-TOF-MS. A total of 122 compounds were identified in QLTMDZ under both positive and negative ion modes. Subsequently, multivariate statistical methods such as principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were conducted in the MS-DIAL software to further elucidate quality differences among 55 batches of QLTMDZ samples from seven manufacturers. Lastly, multiple reaction monitoring (MRM) mode was utilized in conjunction with UHPLC-QQQ-MS, for the precise quantification of the identified 24 compounds within the QLTMDZ preparation and providing supplementary information in quality evaluation. The established analytical method in this study is sensitive and efficient, enabling qualitative and quantitative analysis of the chemical constituents within QLTMDZ. The application of multivariate statistical analyses effectively discriminates samples based on different dosage forms and manufacturers, thereby providing new research directions and scientific support for further studies on the quality control of the prescription.

A comprehensive quality evaluation strategy for ReDuNing injection by integrating UPLC-Orbitrap MS/MS profile and biological potency combined with multivariate statistical analysis.

Reduning injection (RDN) is a traditional chinese medicine injection widely used in clinical practice. In this study, qualitative and quantitative analysis of RDN were conducted by UPLC-Orbitrap MS/MS simultaneously. Totally 118 compounds were identified and 34 compounds were quantified in RDN. The method with completed method validation proved the high sensitivity and efficiency of the method and it was applied to quantify compounds in RDN. Multivariate statistical analysis method selected 11 key variables that affect the content consistency of RDN. 20 batches with high biological potency were screened by cox-2 enzyme activity assay. Spectrum-effect relationship analysis and multivariate statistical analysis showed that 7 batches were high-quality selected after comprehensive quality evaluation and 9 compounds were key indicators for screening it. This strategy including fingerprint, qualitative analysis and multiple-component quantification could be well applied to modern quality evaluation of RDN, which could be valuable for the further quality control of more other traditional Chinese medicines.

[Methodological and reporting quality of randomized controlled trials on the treatment of benign prostatic hyperplasia with traditional Chinese medicine].

OBJECTIVE: To systematically evaluate the methodological quality and reporting quality of randomized controlled trials (RCT) on the treatment of BPH with traditional Chinese medicine (TCM), in order to provide some methodological reference for clinical practice and research. METHODS: We searched CNKI, VIP, Wanfang Data and PubMed for RCTs on the treatment of BPH with TCM published in China from January 2013 to November 2023. Two researchers screened the literature separately, and evaluated the methodological and reporting quality of the RCTs based on the Cochrane bias risk assessment tool and CONSORT TCM compound. RESULTS: Totally, 88 RCTs were included in this study. In terms of methodological quality, according to the Cochrane bias risk assessment tool, 27 biases in the process of randomization were identified as of low-risk and the other 61 of a certain risk. Among the allocation-related biases deviating from the established interventions, 76 were of low risk, 10 of a certain risk and 2 of high risk; among the compliance-related biases deviating from the established interventions, 76 were of low risk and 12 of a certain risk; among the biases due to missing outcome data, 86 were of low risk and 2 of a certain risk, while all the biases due to outcome measurement were of low risk; and among the biases from selective reporting, 65 were of low-risk, 2 of a certain risk and 21 of high-risk. In terms of reporting quality, according to the evaluation criteria of consort TCM compound, appropriate key words were used in 1 RCT (0.01%), the random assignment sequence method described in 27 (30.68%), the details of assignment limitation given in 5 (5.68%), assignment concealment mentioned in 3 (3.41%), the blind method and assignment concealment employed in 3 (3.41%), fall-offs recorded in 10 (11.36%), adverse events reported in 38 (43.18%), and limitations of the trials analyzed in 18 (20.45%). All the RCTs lacked complete intervention measures, subject flow chart, clinical trial registration and research schemes. CONCLUSION: At present, the methodological quality and reporting quality of RCTs on the treatment of BPH with TCM are generally low, with the main problems of incomplete experimental designs, lack of detailed description of randomized and blind methods, and insufficient TCM symptom evaluation of outcome indicators. Researchers should be cautious in adopting and applying the results reported, follow the CONSORT statement in design, registration, implement and reporting of the scheme, fully consider the clinical characteristics of TCM in the treatment of BPH, and reasonably design and report the evaluation indicators.

Evaluating the impact of ecological factors on the quality and habitat distribution of Lonicera japonica Flos using HPLC and the MaxEnt model.

Introduction: The quality of traditional Chinese medicine is based on the content of their secondary metabolites, which vary with habitat adaptation and ecological factors. This study focuses on Lonicera japonica Flos (LJF), a key traditional herbal medicine, and aims to evaluate how ecological factors impact its quality. Methods: We developed a new evaluation method combining high-performance liquid chromatography (HPLC) fingerprinting technology and MaxEnt models to assess the effects of ecological factors on LJF quality. The MaxEnt model was used to predict suitable habitats for current and future scenarios, while HPLC was employed to analyze the contents of key compounds. We also used ArcGIS for spatial analysis to create a quality zoning map. Results: The analysis identified 21 common chromatographic peaks, with significant variations in the contents of Hyperoside, Rutin, Chlorogenic acid, Cynaroside, and Isochlorogenic acid A across different habitats. Key environmental variables influencing LJF distribution were identified, including temperature, precipitation, and elevation. The current suitable habitats primarily include regions south of the Yangtze River. Under future climate scenarios, suitable areas are expected to shift, with notable expansions in southern Gansu, southeastern Tibet, and southern Liaoning. The spatial distribution maps revealed that high-quality LJF is predominantly found in central and southern Hebei, northern Henan, central Shandong, central Sichuan, southern Guangdong, and Taiwan. Discussion: The study indicates that suitable growth areas can promote the accumulation of certain secondary metabolites in plants, as the accumulation of these metabolites varies. The results underscore the necessity of optimizing quality based on cultivation practices. The integration of HPLC fingerprinting technology and the MaxEnt model provides valuable insights for the conservation and cultivation of herbal resources, offering a new perspective on evaluating the impact of ecological factors on the quality of traditional Chinese medicines.

Study on chemical characterization and sleep-improvement function of Prunella vulgaris L. based on the functional components.

Prunella vulgaris L. (P. vulgaris) has great application value and development prospects in improving sleep. In this study, we continued to evaluate the sleep-improvement function and mechanism of P. vulgaris from both chemical characterization and function based on sleep-improvement functional ingredients, rosmarinic acid and salviaflaside, screened out in the previous stage as the index components. The chemical constituents of P. vulgaris and its phenolic acid fraction were characterized by the UPLC-MSn technology. The quality of the sleep-improvement phenolic acid fraction of P. vulgaris was scientifically evaluated by fingerprints combined with quantitative analysis of rosmarinic acid and salviaflaside. The function of phenolic acid parts of P. vulgaris in improving sleep was verified by different insomnia models including the PCPA-induced insomnia model and surface platform sleep deprivation model. HE staining was used to observe the effect of P. vulgaris on the morphology of nerve cells in different brain regions. In vivo experiments and molecular docking explored the sedative-hypnotic effects of functional ingredients of P. vulgaris. All these results investigated the material basis and mechanism of P. vulgaris to improve sleep from multiple perspectives, which contribute to providing a basis for the development of functional food to improve sleep.

Corrigendum: Assimilation of socially assistive robots by older adults: an interplay of uses, constraints and outcomes.

[This corrects the article DOI: 10.3389/frobt.2024.1337380.].

Chemical constituents, pharmacological activities and quality evaluation methods of genus Hippocampus: A comprehensive review.

The genus Hippocampus is a multi-origin animal species with high medicinal and healthcare values. About 57 species of Hippocampus spread worldwide, of which about 14 species can be used as medicine, showing anti-oxidation, anti-inflammation, anti-depressant, anti-hypertension, anti-prostatic hyperplasia, antivirus, anti-apoptotic, antifatigue, and so on. And those pharmacological effects are mainly related to their active ingredients, including amino acids, abundant proteins (peptides and oligopeptides), fatty acids, nucleosides, steroids, and other small molecular compounds. The main means of authentication of Hippocampus species are morphological identification, microscopic identification, thin layer chromatography method, fingerprint method and genomics method. This review will provide useful insight for exploration, further study and precise medication of Hippocampus in the future.

[Quality evaluation and grading standard discussion on Cinnamomi Ramulus].

This study explored the relationship between the appearance traits and internal components of Cinnamomi Ramulus pieces, so as to provide a reference for the quality evaluation and the formulation of grade standards. This study determined the appearance traits and index component contents of 41 batches of Cinnamomi Ramulus pieces in the core producing areas of Guangxi and Guangdongand established the HPLC characteristic map method. The weight of the pieces, the narrowest diameter, and the widest diameter of the tr ansverse section were used as the indices of appearance traits. The content of index components(cinnamic acid and cinnamalde hyde)was determined by the established content determination method. The chromatographic characteristics were determinedon a Waters XBridge C_(18)(4. 6 mm×250 mm, 5 µm) column with a mobile phase consisting of 0. 1% phosphoric acidacetonitrile and gradient elution at the flow rate of 1 mL ·min~(-1). The column temperature was 30 ℃, and the detection wavelength was 254 nm. Cluster analysis, principal component analysis, and other stoichiometric methods were used to analyze the correlation between theap pearance traits and the index/characteristic components of Cinnamomi Ramulus pieces and compare the qu ality differences of the piecesfrom different batches and plac es. The results showed that the larger weight, the narrowest diameter, andthe widest diameter of the tra nsverse section indicated lowercontent of main indexes/characteristic components, and there was a synergistic decreasing trend amongd ifferent components. The overall quality of Cinnamomi Ramulus pieces in Guangdong Province and Guangxi Province was similar, but there were still differences between different origins and different batches of the same origin. It is scientific and feasible to evaluatethe quality of Cinnamomi Ramulus pieces and establish grading standards based on the appearance traits and index/character istic components. The research provides a more scientific and comprehensive basis for the quality control evaluation and standardformulation of Cinnamomi Ramulus.

Evaluation of the environmental factors influencing the quality of Astragalus membranaceus var. mongholicus based on HPLC and the Maxent model.

BACKGROUND: In recent years, global climate change in tandem with increased human activity has resulted in habitat degradation or the migration of rare medicinal plants, potentially impacting the quality of medicinal herbs. Astragalus membranaceus var. mongholicus is a valuable bulk medicinal material in Northwest China. As the demand for this medicinal herb continues to increase in both domestic and international markets, ensuring the sustainable development of high-quality Astragali Radix is important. In this study, the maximum entropy (Maxent) model was applied, thereby incorporating 136 distribution records, along with 39 environmental factors of A. membranaceus var. mongholicus, to assess the quality zonation and potential distribution of this species in China under climate change. RESULTS: The results showed that the elevation, annual mean temperature, precipitation of wettest month, solar radiation in June, and mean temperature of warmest quarter were the critical environmental factors influencing the accumulation of astragaloside IV and Astragalus polysaccharide in A. membranaceus var. mongholicus. Among the twelve main environmental variables, annual mean temperature, elevation, precipitation of the wettest month, and solar radiation in November were the four most important factors influencing the distribution of A. membranaceus var. mongholicus. In addition, ecological niche modelling revealed that highly suitable habitats were mainly located in central and western Gansu, eastern Qinghai, northern Shaanxi, southern Ningxia, central Inner Mongolia, central Shanxi, and northern Hebei. However, the future projections under climate change suggested a contraction of these suitable areas, shifting towards northeastern high-latitude and high-elevation mountains. CONCLUSIONS: The findings provide essential insights for developing adaptive strategies for A. membranaceus var. mongholicus cultivation in response to climate change and can inform future research on this species. By considering the identified environmental factors and the potential impacts of the predicted climate changes, we can visualize the regional distribution of high-quality Radix Astragali and develop conservation strategies to protect and restore its suitable habitats.

nnSegNeXt: A 3D Convolutional Network for Brain Tissue Segmentation Based on Quality Evaluation.

Accurate and automated segmentation of brain tissue images can significantly streamline clinical diagnosis and analysis. Manual delineation needs improvement due to its laborious and repetitive nature, while automated techniques encounter challenges stemming from disparities in magnetic resonance imaging (MRI) acquisition equipment and accurate labeling. Existing software packages, such as FSL and FreeSurfer, do not fully replace ground truth segmentation, highlighting the need for an efficient segmentation tool. To better capture the essence of cerebral tissue, we introduce nnSegNeXt, an innovative segmentation architecture built upon the foundations of quality assessment. This pioneering framework effectively addresses the challenges posed by missing and inaccurate annotations. To enhance the model's discriminative capacity, we integrate a 3D convolutional attention mechanism instead of conventional convolutional blocks, enabling simultaneous encoding of contextual information through the incorporation of multiscale convolutional features. Our methodology was evaluated on four multi-site T1-weighted MRI datasets from diverse sources, magnetic field strengths, scanning parameters, temporal instances, and neuropsychiatric conditions. Empirical evaluations on the HCP, SALD, and IXI datasets reveal that nnSegNeXt surpasses the esteemed nnUNet, achieving Dice coefficients of 0.992, 0.987, and 0.989, respectively, and demonstrating superior generalizability across four distinct projects with Dice coefficients ranging from 0.967 to 0.983. Additionally, extensive ablation studies have been implemented to corroborate the effectiveness of the proposed model. These findings represent a notable advancement in brain tissue analysis, suggesting that nnSegNeXt holds the promise to significantly refine clinical workflows.

Evaluating Machine Learning-Based MRI Reconstruction Using Digital Image Quality Phantoms.

Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI) reconstruction methods. However, the commonly used fidelity metrics, such as mean squared error (MSE), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), often fail to capture fundamental and clinically relevant MR image quality aspects. To address this, we propose evaluation of ML-based MRI reconstruction using digital image quality phantoms and automated evaluation methods. Our phantoms are based upon the American College of Radiology (ACR) large physical phantom but created in k-space to simulate their MR images, and they can vary in object size, signal-to-noise ratio, resolution, and image contrast. Our evaluation pipeline incorporates evaluation metrics of geometric accuracy, intensity uniformity, percentage ghosting, sharpness, signal-to-noise ratio, resolution, and low-contrast detectability. We demonstrate the utility of our proposed pipeline by assessing an example ML-based reconstruction model across various training and testing scenarios. The performance results indicate that training data acquired with a lower undersampling factor and coils of larger anatomical coverage yield a better performing model. The comprehensive and standardized pipeline introduced in this study can help to facilitate a better understanding of the performance and guide future development and advancement of ML-based reconstruction algorithms.

Component analysis using UPLC-Q-TOF/MS and quality evaluation using fingerprinting and chemometrics for hops.

Hops, extensively cultivated in China for their food and medicinal applications, currently lack well-defined chemical markers to evaluate variations in their quality. The study aimed to explore variations in the quality of Chinese hops by the chemical characteristics of hops, employing UPLC-Q-TOF/MS, integrated with chemical fingerprinting and chemometrics. The results indicated that Chinese hops are abundant in polyphenols and bitter acids. The integration of UPLC-Q-TOF/MS, Chemical fingerprinting, and chemometrics revealed to be an accurate and effective approach for assessing the quality of Chinese hops. In this study, ten important chemical markers were found to be useful in differentiating various hop varieties. Moreover, the support vector machine showed a prediction accuracy of 92.3077% in identifying Chinese hop varieties. The strategy of the study lays the groundwork for classifying Chinese hop varieties and serves as a prerequisite for future quality control studies, particularly focusing on chemical compositions.

Rapid and comprehensive quality evaluation of Huang-qin from different origins by FT-IR and NIR spectroscopy combined with chemometrics.

INTRODUCTION: Quality evaluation of Huang-qin is significant to ensure its clinical efficacy. OBJECTIVE: This study aims to establish an accurate, rapid and comprehensive Huang-qin quality evaluation method to overcome the time-consuming and laborious shortcomings of traditional herbal medicine quality assessment methods. METHODS: The contents of baicalin, baicalein and scutellarin in Huang-qin from five different origins were analyzed by FT-IR and NIR spectra combined with multivariate data technology. The quality of Huang-qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored. RESULTS: Satisfactory prediction results of PLS models were obtained. Relatively, the model based on FT-IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang-qin from different geographical origins was significantly different. The results showed that the quality of Huang-qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang-qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins. CONCLUSION: This study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them.

Quality Evaluation of Lonicerae Flos Produced in Southwest China Based on HPLC Analysis and Antioxidant Activity.

Lonicera macranthoides, the main source of traditional Chinese medicine Lonicerae Flos, is extensively cultivated in Southwest China. However, the quality of L. macranthoides produced in this region significantly varies due to its wide distribution and various cultivation breeds. Herein, 50 Lonicerae Flos samples derived from different breeds of L. macranthoides cultivated in Southwest China were collected for quality evaluation. Six organic acids and three saponin compounds were quantitatively analyzed using HPLC. Furthermore, the antioxidant activity of a portion of samples was conducted with 2,2'-Azinobis-(3-ethylbenzthiazoline-6-sulphonate) (ABTS) and 1,1-diphenyl-2-picryl-hydrazyl (DPPH) radical scavenging experiments. According to the quantitative results, all samples met the quality standards outlined in the Chinese Pharmacopoeia. The samples from Guizhou, whether derived from unopened or open wild-type breeds, exhibited high quality, while the wild-type samples showed relatively significant fluctuation in quality. The samples from Chongqing and Hunan demonstrated similar quality, whereas those from Sichuan exhibited relatively lower quality. These samples demonstrated significant abilities in clearing ABTS and DPPH radicals. The relationship between HPLC chromatograms and antioxidant activity, as elucidated by multivariate analysis, indicated that chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, and isochlorogenic acid C are active components and can serve as Q-markers for quality evaluation.

The future of patient education: A study on AI-driven responses to urinary incontinence inquiries.

OBJECTIVE: To evaluate the effectiveness of ChatGPT in providing insights into common urinary incontinence concerns within urogynecology. By analyzing the model's responses against established benchmarks of accuracy, completeness, and safety, the study aimed to quantify its usefulness for informing patients and aiding healthcare providers. METHODS: An expert-driven questionnaire was developed, inviting urogynecologists worldwide to assess ChatGPT's answers to 10 carefully selected questions on urinary incontinence (UI). These assessments focused on the accuracy of the responses, their comprehensiveness, and whether they raised any safety issues. Subsequent statistical analyses determined the average consensus among experts and identified the proportion of responses receiving favorable evaluations (a score of 4 or higher). RESULTS: Of 50 urogynecologists that were approached worldwide, 37 responded, offering insights into ChatGPT's responses on UI. The overall feedback averaged a score of 4.0, indicating a positive acceptance. Accuracy scores averaged 3.9 with 71% rated favorably, whereas comprehensiveness scored slightly higher at 4 with 74% favorable ratings. Safety assessments also averaged 4 with 74% favorable responses. CONCLUSION: This investigation underlines ChatGPT's favorable performance across the evaluated domains of accuracy, comprehensiveness, and safety within the context of UI queries. However, despite this broadly positive reception, the study also signals a clear avenue for improvement, particularly in the precision of the provided information. Refining ChatGPT's accuracy and ensuring the delivery of more pinpointed responses are essential steps forward, aiming to bolster its utility as a comprehensive educational resource for patients and a supportive tool for healthcare practitioners.