Tenofovir-Diphosphate and Emtricitabine-Triphosphate Adherence Benchmarks in Dried Blood Spots for Persons with HIV Receiving Tenofovir Alafenamide and Emtricitabine-based Antiretroviral Therapy (QUANTI-TAF).

BACKGROUND: QUANTI-TAF aimed to establish tenofovir-diphosphate/emtricitabine-triphosphate (TFV-DP/FTC-TP) adherence benchmarks in dried blood spots (DBS) for persons with HIV (PWH) receiving tenofovir alafenamide/emtricitabine (TAF/FTC)-based antiretroviral therapy (ART). METHODS: During a 16-week pharmacokinetic study, PWH received TAF/FTC-based ART co-encapsulated with an ingestible sensor to directly measure cumulative (enrollment to final visit) and 10-day adherence. At monthly visits, intraerythrocytic concentrations of TAF/FTC anabolites (TFV-DP/FTC-TP) in DBS were quantified by LC-MS/MS and summarized at steady-state (week 12 or 16) as median (IQR). Linear mixed-effects models evaluated factors associated with TFV-DP/FTC-TP. RESULTS: 84 participants (86% male, 11% female, and 4% transgender), predominantly receiving bictegravir/TAF/FTC (73%) enrolled. 92% completed week 12 or 16 (94% receiving unboosted ART). TFV-DP for <85% (7/72), ≥85%-<95% (9/72), and ≥95% (56/72) cumulative adherence was 2696 (2039-4108), 3117 (2332-3339), and 3344 (2605-4293) fmol/punches. All participants with ≥85% cumulative adherence had TFV-DP ≥1800 fmol/punches. Adjusting for cumulative adherence, TFV-DP was higher with boosted ART, lower BMI, and in non-Blacks. FTC-TP for <85% (14/77), ≥85%-<95% (6/77), and ≥95% (57/77) 10-day adherence was 3.52 (2.64-4.48), 4.58 (4.39-5.06), and 4.96 (4.21-6.26) pmol/punches. All participants with ≥85% 10-day adherence had FTC-TP ≥2.5 pmol/punches. Low-level viremia (HIV-1 RNA ≥20-<200 copies/mL) occurred at 60/335 (18%) visits in 33/84 (39%) participants (range: 20-149 copies/mL), with similar TFV-DP (3177 [2494-4149] fmol/punches) compared with HIV-1 RNA <20 copies/mL visits (3279 [2580-4407] fmol/punches). CONCLUSIONS: We propose PK-based TFV-DP (≥1800 fmol/punches)/FTC-TP (≥2.5 pmol/punches) benchmarks in DBS for PWH receiving unboosted TAF/FTC-based ART with ≥85% adherence. In the setting of high adherence, low-level viremia was common.

Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data.

Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target not only microorganisms but also viruses and cancer cells. Due to their lower selection for resistance compared with traditional antibiotics, AMPs have been attracting the ever-growing attention from researchers, including bioinformaticians. Machine learning represents the most cost-effective method for novel AMP discovery and consequently many computational tools for AMP prediction have been recently developed. In this article, we investigate the impact of negative data sampling on model performance and benchmarking. We generated 660 predictive models using 12 machine learning architectures, a single positive data set and 11 negative data sampling methods; the architectures and methods were defined on the basis of published AMP prediction software. Our results clearly indicate that similar training and benchmark data set, i.e. produced by the same or a similar negative data sampling method, positively affect model performance. Consequently, all the benchmark analyses that have been performed for AMP prediction models are significantly biased and, moreover, we do not know which model is the most accurate. To provide researchers with reliable information about the performance of AMP predictors, we also created a web server AMPBenchmark for fair model benchmarking. AMPBenchmark is available at http://BioGenies.info/AMPBenchmark.

Performance measurement part II: A guide to developing dermatology performance measures.

Throughout the 21st century, national and local governments, private health sectors, health insurance companies, healthcare professionals, labor unions, and consumers have been striving to develop an effective approach to evaluate, report, and improve the quality of healthcare. As medicine improves and health systems grow to meet patient needs, the performance measurement system of care effectiveness must also evolve. Continual efforts should be undertaken to effectively measure quality of care to create a more informed public, improve health outcomes, and reduce healthcare costs. As such, recent policy reform has necessitated that performance systems be implemented in healthcare, with the "performance measure" being the foundation of the system in which all of healthcare must be actively engaged in to ensure optimal care for patients. The development of performance measures can be highly complex, particularly when creating specialty-specific performance measures. To help dermatologists understand the process of creating dermatology-specific performance measures to engage in creating or implementing performance measures at the local or national levels, this article in the two-part continuing medical education series reviews the types, components, and process of developing, reviewing, and implementing performance measures.

Responding to the workforce crisis: consensus recommendations from the Second Workforce Summit of the American Society of Pediatric Nephrology.

IMPORTANCE: Pediatric patients with complex medical problems benefit from pediatric sub-specialty care; however, a significant proportion of children live greater than 80 mi. away from pediatric sub-specialty care. OBJECTIVE: To identify current knowledge gaps and outline concrete next steps to make progress on issues that have persistently challenged the pediatric nephrology workforce. EVIDENCE REVIEW: Workforce Summit 2.0 employed the round table format and methodology for consensus building using adapted Delphi principles. Content domains were identified via input from the ASPN Workforce Committee, the ASPN's 2023 Strategic Plan survey, the ASPN's Pediatric Nephrology Division Directors survey, and ongoing feedback from ASPN members. Working groups met prior to the Summit to conduct an organized literature review and establish key questions to be addressed. The Summit was held in-person in November 2023. During the Summit, work groups presented their preliminary findings, and the at-large group developed the key action statements and future directions. FINDINGS: A holistic appraisal of the effort required to cover inpatient and outpatient sub-specialty care will help define faculty effort and time distribution. Most pediatric nephrologists practice in academic settings, so work beyond clinical care including education, research, advocacy, and administrative/service tasks may form a substantial amount of a faculty member's time and effort. An academic relative value unit (RVU) may assist in creating a more inclusive assessment of their contributions to their academic practice. Pediatric sub-specialties, such as nephrology, contribute to the clinical mission and care of their institutions beyond their direct billable RVUs. Advocacy throughout the field of pediatrics is necessary in order for reimbursement of pediatric sub-specialist care to accurately reflect the time and effort required to address complex care needs. Flexible, individualized training pathways may improve recruitment into sub-specialty fields such as nephrology. CONCLUSIONS AND RELEVANCE: The workforce crisis facing the pediatric nephrology field is echoed throughout many pediatric sub-specialties. Efforts to improve recruitment, retention, and reimbursement are necessary to improve the care delivered to pediatric patients.

Time to define food salt targets in Italy starting with cereal-based products: A safe and practical way to reduce the heavy burden of cardiovascular disease.

BACKGROUND AND AIMS: Excess salt intake is the leading dietary risk factor for cardiovascular disease in most countries, including Italy. While the cost-effectiveness of interventions aimed to reduce salt intake has been proved, the WHO recommendation to reduce salt intake by 30 % at the global level by 2025 is far from being reached. METHODS AND RESULTS: In Italy, two surveys of the general adult population have established that the average salt intake is still almost twice the WHO recommendation although it was reduced by 1.2 g/day between 2008-12 and 2018-19. Previous investigations had shown that non-discretionary salt added by the industry or by local craft producers represents at least 50 % of the total intake and indicated cereal-based products as the main source of non-discretionary salt. Two recent studies conducted by the Italian Society of Human Nutrition "Young Working Group" have provided updated information on the salt content of almost three thousand cereal-based products currently available on the Italian food market and shown that most of the items evaluated had a sodium content much higher than the sodium benchmarks recently proposed by WHO. CONCLUSIONS: Italy has built the foundations of an effective population strategy for salt intake reduction: it is time however to proceed with full commitment to food reformulation if any substantial further progress has to be made. Salt benchmarks for Italy need to be defined for the food categories most relevant to population salt intake and their implementation should ideally be mandatory after consultation with food producers.

Bridging Requirements, Planning, and Evaluation: A Review of Social Robot Navigation.

Navigation lies at the core of social robotics, enabling robots to navigate and interact seamlessly in human environments. The primary focus of human-aware robot navigation is minimizing discomfort among surrounding humans. Our review explores user studies, examining factors that cause human discomfort, to perform the grounding of social robot navigation requirements and to form a taxonomy of elementary necessities that should be implemented by comprehensive algorithms. This survey also discusses human-aware navigation from an algorithmic perspective, reviewing the perception and motion planning methods integral to social navigation. Additionally, the review investigates different types of studies and tools facilitating the evaluation of social robot navigation approaches, namely datasets, simulators, and benchmarks. Our survey also identifies the main challenges of human-aware navigation, highlighting the essential future work perspectives. This work stands out from other review papers, as it not only investigates the variety of methods for implementing human awareness in robot control systems but also classifies the approaches according to the grounded requirements regarded in their objectives.

Uncertainty in GNN Learning Evaluations: A Comparison between Measures for Quantifying Randomness in GNN Community Detection.

(1) The enhanced capability of graph neural networks (GNNs) in unsupervised community detection of clustered nodes is attributed to their capacity to encode both the connectivity and feature information spaces of graphs. The identification of latent communities holds practical significance in various domains, from social networks to genomics. Current real-world performance benchmarks are perplexing due to the multitude of decisions influencing GNN evaluations for this task. (2) Three metrics are compared to assess the consistency of algorithm rankings in the presence of randomness. The consistency and quality of performance between the results under a hyperparameter optimisation with the default hyperparameters is evaluated. (3) The results compare hyperparameter optimisation with default hyperparameters, revealing a significant performance loss when neglecting hyperparameter investigation. A comparison of metrics indicates that ties in ranks can substantially alter the quantification of randomness. (4) Ensuring adherence to the same evaluation criteria may result in notable differences in the reported performance of methods for this task. The W randomness coefficient, based on the Wasserstein distance, is identified as providing the most robust assessment of randomness.

HyperPUT: generating synthetic faulty programs to challenge bug-finding tools.

As research in automatically detecting bugs grows and produces new techniques, having suitable collections of programs with known bugs becomes crucial to reliably and meaningfully compare the effectiveness of these techniques. Most of the existing approaches rely on benchmarks collecting manually curated real-world bugs, or synthetic bugs seeded into real-world programs. Using real-world programs entails that extending the existing benchmarks or creating new ones remains a complex time-consuming task. In this paper, we propose a complementary approach that automatically generates programs with seeded bugs. Our technique, called HyperPUT, builds C programs from a "seed" bug by incrementally applying program transformations (introducing programming constructs such as conditionals, loops, etc.) until a program of the desired size is generated. In our experimental evaluation, we demonstrate how HyperPUT can generate buggy programs that can challenge in different ways the capabilities of modern bug-finding tools, and some of whose characteristics are comparable to those of bugs in existing benchmarks. These results suggest that HyperPUT can be a useful tool to support further research in bug-finding techniques-in particular their empirical evaluation.

Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionals.

Publicly accessible benchmarks that allow for assessing and comparing model performances are important drivers of progress in artificial intelligence (AI). While recent advances in AI capabilities hold the potential to transform medical practice by assisting and augmenting the cognitive processes of healthcare professionals, the coverage of clinically relevant tasks by AI benchmarks is largely unclear. Furthermore, there is a lack of systematized meta-information that allows clinical AI researchers to quickly determine accessibility, scope, content and other characteristics of datasets and benchmark datasets relevant to the clinical domain. To address these issues, we curated and released a comprehensive catalogue of datasets and benchmarks pertaining to the broad domain of clinical and biomedical natural language processing (NLP), based on a systematic review of literature and. A total of 450 NLP datasets were manually systematized and annotated with rich metadata, such as targeted tasks, clinical applicability, data types, performance metrics, accessibility and licensing information, and availability of data splits. We then compared tasks covered by AI benchmark datasets with relevant tasks that medical practitioners reported as highly desirable targets for automation in a previous empirical study. Our analysis indicates that AI benchmarks of direct clinical relevance are scarce and fail to cover most work activities that clinicians want to see addressed. In particular, tasks associated with routine documentation and patient data administration workflows are not represented despite significant associated workloads. Thus, currently available AI benchmarks are improperly aligned with desired targets for AI automation in clinical settings, and novel benchmarks should be created to fill these gaps.

Expanding the utility of robotics for pancreaticoduodenectomy: a 10-year review and comparison to international benchmarks in pancreatic surgery.

BACKGROUND: Robotic pancreaticoduodenectomy (RPD) is an emerging alternative to open pancreaticoduodenectomy (OPD). Although RPD offers various theoretical advantages, it is used in less than 10% of all pancreaticoduodenectomies. The aim of this study was to report our 10-year experience and compare RPD outcomes with international benchmarks for OPD. METHODS: A retrospective review of a prospectively maintained institutional database was performed of consecutive patients who underwent RPD between January 2011 and December 2021. Patients were categorized into low-risk and high-risk groups according to the selection criteria set by the benchmark study. Their outcomes were compared to the international benchmark cut off values. Outcomes were then evaluated over time to identify improvements in practice and establish a learning curve. RESULTS: Of 201 RPDs, 36 were low-risk and 165 high-risk patients. Compared to the OPD benchmarks, outcomes of low-risk patients were within the cutoff values. High-risk patients were outside the cutoff for blood transfusions (26% vs. ≤ 23%), overall complications (78% vs. ≤ 73%), grade I-II complications (68% vs. ≤ 62%), and readmissions (22% vs ≤ 21%). Oncologic outcomes for high-risk patients were within benchmark cutoffs. Cases at the end of the learning curve included more pancreatic cancer (42% from 17%) and fewer low-risk patients (10% from 24%) than those at the beginning. After 41 RPD there was a decline in conversion rates and operative time. Between 95 and 143 cases operative time, transfusion rates, and LOS declined significantly. Complications did not differ over time. CONCLUSION: RPD yields results comparable to the established benchmarks in OPD in both low- and high-risk patients. Along the learning curve, RPD evolved with the inclusion of more high-risk cases while outcomes remained within benchmarks. Addition of a robotic HPB surgery fellowship did not compromise outcomes. These results suggest that RPD may be an option for high-risk patients at specialized centers.

From eye-blinks to state construction: Diagnostic benchmarks for online representation learning.

We present three new diagnostic prediction problems inspired by classical-conditioning experiments to facilitate research in online prediction learning. Experiments in classical conditioning show that animals such as rabbits, pigeons, and dogs can make long temporal associations that enable multi-step prediction. To replicate this remarkable ability, an agent must construct an internal state representation that summarizes its interaction history. Recurrent neural networks can automatically construct state and learn temporal associations. However, the current training methods are prohibitively expensive for online prediction-continual learning on every time step-which is the focus of this paper. Our proposed problems test the learning capabilities that animals readily exhibit and highlight the limitations of the current recurrent learning methods. While the proposed problems are nontrivial, they are still amenable to extensive testing and analysis in the small-compute regime, thereby enabling researchers to study issues in isolation, ultimately accelerating progress towards scalable online representation learning methods.

Clustering and variable selection evaluation of 13 unsupervised methods for multi-omics data integration.

Recent advances in NGS sequencing, microarrays and mass spectrometry for omics data production have enabled the generation and collection of different modalities of high-dimensional molecular data. The integration of multiple omics datasets is a statistical challenge, due to the limited number of individuals, the high number of variables and the heterogeneity of the datasets to integrate. Recently, a lot of tools have been developed to solve the problem of integrating omics data including canonical correlation analysis, matrix factorization and SM. These commonly used techniques aim to analyze simultaneously two or more types of omics. In this article, we compare a panel of 13 unsupervised methods based on these different approaches to integrate various types of multi-omics datasets: iClusterPlus, regularized generalized canonical correlation analysis, sparse generalized canonical correlation analysis, multiple co-inertia analysis (MCIA), integrative-NMF (intNMF), SNF, MoCluster, mixKernel, CIMLR, LRAcluster, ConsensusClustering, PINSPlus and multi-omics factor analysis (MOFA). We evaluate the ability of the methods to recover the subgroups and the variables that drive the clustering on eight benchmarks of simulation. MOFA does not provide any results on these benchmarks. For clustering, SNF, MoCluster, CIMLR, LRAcluster, ConsensusClustering and intNMF provide the best results. For variable selection, MoCluster outperforms the others. However, the performance of the methods seems to depend on the heterogeneity of the datasets (especially for MCIA, intNMF and iClusterPlus). Finally, we apply the methods on three real studies with heterogeneous data and various phenotypes. We conclude that MoCluster is the best method to analyze these omics data. Availability: An R package named CrIMMix is available on GitHub at https://github.com/CNRGH/crimmix to reproduce all the results of this article.

Racial/ethnic inequalities in cervical cancer screening in the United States: An outcome reclassification to better inform interventions and benchmarks.

In the United states (U.S.), prevailing understanding suggests significant racial/ethnic inequalities in cervical cancer screening exist. However, recent findings elsewhere in North America indicate the magnitude of these inequalities depend on the way screening is defined: lifetime screening versus up-to-date screening. As those who have never been screened are most at risk for invasive cancer, an improved understanding of inequalities in this outcome is necessary to better inform interventions. To describe racial/ethnic inequalities in 1) never screening and 2) not being up-to-date with screening among women who have been screened at least once in their lifetime, three years (2014-2016) of the U.S. Behavioral Risk Factor Surveillance Survey were utilized to estimate cervical cancer screening prevalence ratios via Poisson regression (N = 123,070). The sample was limited to women age 21 to 65 years. Women from racial/ethnic minority groups were more likely to never have been screened in comparison to White women, particularly women of Asian descent (Prevalence Ratio (PR) = 3.8, 95% CI = 3.3-4.3). However, among women who had been screened at least once in their lifetime, an inverse association was observed between being a member of a racial/ethnic minority group and not being up-to-date with screening (e.g. PRasian vs white = 0.7, 95% CI = 0.6-0.9). Physicians and public health institutions concerned with monitoring racial/ethnic inequalities should consider adding lifetime screening as a primary benchmark, as this outcome implies different intervention targets to address inequalities and the differential burden of cervical cancer.

Benchmarking medical laboratory performance: survey validation and results for Europe, Middle East, and Africa.

OBJECTIVES: Medical laboratory performance is a relative concept, as are quality and safety in medicine. Therefore, repetitive benchmarking appears to be essential for sustainable improvement in health care. The general idea in this approach is to establish a reference level, upon which improvement may be strived for and quantified. While the laboratory community traditionally is highly aware of the need for laboratory performance and public scrutiny is more intense than ever due to the SARS-CoV-2 pandemic, few initiatives span the globe. The aim of this study was to establish a good practice approach towards benchmarking on a high abstraction level for three key dimensions of medical laboratory performance, generate a tentative snapshot of the current state of the art in the region of Europe, Middle East, and Africa (EMEA), and thus set the stage for global follow-up studies. METHODS: The questionnaire used and previously published in this initiative consisted of 50 items, roughly half relating to laboratory operations in general with the other half addressing more specific topics. An international sample of laboratories from EMEA was approached to elicit high fidelity responses with the help of trained professionals. Individual item results were analyzed using standard descriptive statistics. Dimensional reduction of specific items was performed using exploratory factor analysis and assessed with confirmatory factor analysis, resulting in individual laboratory scores for the three subscales of "Operational performance", "Integrated clinical care performance", and "Financial sustainability". RESULTS: Altogether, 773 laboratories participated in the survey, of which 484 were government hospital laboratories, 129 private hospital laboratories, 146 commercial laboratories, and 14 were other types of laboratories (e.g. research laboratories). Respondents indicated the need for digitalization (e.g. use of IT for order management, auto-validation), automation (e.g. pre-analytics, automated sample transportation), and establishment of formal quality management systems (e.g. ISO 15189, ISO 9001) as well as sustainably embedding them in the fabric of laboratory operations. Considerable room for growth also exists for services provided to physicians, such as "Diagnostic pathways guidance", "Proactive consultation on complex cases", and "Real time decision support" which were provided by less than two thirds of laboratories. Concordantly, the most important kind of turn-around time (TAT) for clinicians, sample-to-result TAT, was monitored by only 40% of respondents. CONCLUSIONS: Altogether, the need for stronger integration of laboratories into the clinical care process became apparent and should be a main trajectory of future laboratory management. Factor analysis confirmed the theoretical constructs of the questionnaire design phase, resulting in a reasonably valid tool for further benchmarking activities on the three aimed-for key dimensions.

Officer characteristics and racial disparities in fatal officer-involved shootings.

Despite extensive attention to racial disparities in police shootings, two problems have hindered progress on this issue. First, databases of fatal officer-involved shootings (FOIS) lack details about officers, making it difficult to test whether racial disparities vary by officer characteristics. Second, there are conflicting views on which benchmark should be used to determine racial disparities when the outcome is the rate at which members from racial groups are fatally shot. We address these issues by creating a database of FOIS that includes detailed officer information. We test racial disparities using an approach that sidesteps the benchmark debate by directly predicting the race of civilians fatally shot rather than comparing the rate at which racial groups are shot to some benchmark. We report three main findings: 1) As the proportion of Black or Hispanic officers in a FOIS increases, a person shot is more likely to be Black or Hispanic than White, a disparity explained by county demographics; 2) race-specific county-level violent crime strongly predicts the race of the civilian shot; and 3) although we find no overall evidence of anti-Black or anti-Hispanic disparities in fatal shootings, when focusing on different subtypes of shootings (e.g., unarmed shootings or "suicide by cop"), data are too uncertain to draw firm conclusions. We highlight the need to enforce federal policies that record both officer and civilian information in FOIS.

[New assessment recommendations for disability in private accident insurance, part 1 : An interdisciplinary consented approach-Basics]. / Neue Bemessungsempfehlungen zur Invalidität in der PUV, Teil 1 : Ein fachübergreifend konsentierter Ansatz ­ Grundlagen.

The centerpiece of a private accident insurer is the benefit promise in cases of disability, which must be determined by a doctor in due time. The insurer specifies the rates of the compensation scheme for loss or inability to function and the medical expert must then fall back on generally recognized, revised or updated assessment recommendations in order to be able to apply the given framework to the specific, individual situation of the insured person. In four steps (basics, upper and lower extremities [disability within the compensation scheme] and disability outside the compensation scheme) interdisciplinary consensus benchmarks for disability assessment are presented, which should form the basis of a uniform medical assessment of accident-related functional disorders in private accident insurance compensation.

Specialised psychiatric beds and 24-hour residential care in Australia 2018-2019 - Comparative analysis and commentary according to international benchmarking.

OBJECTIVE: A commentary on Australian specialised private and public psychiatric acute and non-acute inpatient care, and 24-hour-staffed community residential care with regard to international benchmarks. METHOD: Descriptive analysis of specialised psychiatric beds from the Australian Institute of Health and Welfare (AIHW) with the WHO Mental Health Atlas 2020, and an international Delphi consensus on optimal and minimal psychiatric beds per capita. RESULTS: Australian private sector beds have shown a 3.8% annual growth rate from 2014-15 to 2018-19, in contrast to relatively static public sector bed numbers. Australia's national combined public and private psychiatric bed number (hospital acute and non-acute, and 24-hour-staffed community residential) of 48.8 per 100,000 population is lower than the WHO European (100.6) and World Bank High Income (69.2) medians, due to fewer community residential and non-acute beds. Australia's 40.9 general and stand-alone psychiatric beds per 100,000 are below the Delphi consensus optimal level of 60 beds per 100,000, but above the bed shortage threshold (30 per 100,000). CONCLUSIONS: Rising bed numbers in private hospitals have contributed to Australian psychiatric inpatient capacity, although the level remains below comparable international medians. Recent initiatives to increase psychiatric bed numbers may signal a policy shift in the public sector, complementary to private and community care.

[Quality value transfer of substance benchmarks in Sanpian Decoction].

According to the polarity of different components in Sanpian Decoction, two fingerprints were established. Then the substance benchmark freeze-dried powder of 15 batches of Sanpian Decoction was prepared, followed by the determination of the fingerprints, index component content, and dry extract rates, the identification of attribution of characteristic peaks, and the calculation of similarities between these fingerprints and the reference(R), the content and transfer rate ranges of ferulic acid, sinapine thiocyanate, liquiritin, and glycyrrhizic acid, and the dry extract rate range. The results showed that the similarities of 15 batches of the substance benchmark fingerprints with R were all greater than 0.900.Further summarization of the characteristic peaks revealed that there were a total of 20 characteristic peaks in fingerprint 1, among which, eight were from Sinapis Semen, four from Paeoniae Radix Alba, six from Chuanxiong Rhizoma, and two from Glycyrrhizae Radix et Rhizoma. A total of 16 characteristic peaks were observed in fingerprint 2, including one from Sinapis Semen, three from Paeoniae Radix Alba, eight from Chuanxiong Rhizoma, and four from Glycyrrhizae Radix et Rhizoma. The average dry extract rate of 15 batches of substance benchmarks was 18.25%, with a dry extract rate range of 16.28%-20.76%. The index component content and transfer rate ranges were listed as follows: 0.15%-0.18% and 38.81%-58.05% for ferulic acid; 0.26%-0.42% and 36.51%-51.02% for sinapine thiocyanate; 0.09%-0.15% and 48.80%-76.61% for liquiritin; 0.13%-0.24% and 23.45%-35.61% for glycyrrhizic acid. The fingerprint, dry extract rate, and index component content determination was combined for analyzing the quality value transfer of substance benchmarks in the classic prescription Sanpian Decoction.The established quality evaluation method for the substance benchmarks was stable and feasible, which has provided a basis for the quality control of Sanpian Decoction and the follow-up development of related preparations.

[Quality value transmitting of substance benchmarks of Zhuru Decoction].

A total of 18 batches of Zhuru Decoction samples were prepared. Chromatographic fingerprints were established for Zhuru Decoction and single decoction pieces, the content of which was then determined. The extraction rate ranges, content, and transfer rate ranges of puerarin, liquiritin, and glycyrrhizic acid, together with the common peaks and the similarity range of the fingerprints, were determined to clarify key quality attributes of Zhuru Decoction. The 18 batches of Zhuru Decoction samples had 25 common peaks and the fingerprint similarity higher than 0.95. Puerariae Lobatae Radix, Glycyrrhizae Radix et Rhizoma, and Zingiberis Rhizoma Recens had 21, 3, and 1 characteristic peaks, respectively. The 18 batches of samples showed the extraction rates within the range of 18.45%-25.29%. Puerarin had the content of 2.20%-3.07% and the transfer rate of 38.5%-45.9%; liquiritin had the content of 0.24%-0.85% and the transfer rate of 15.9%-37.5%; glycyrrhizic acid had the content of 0.39%-1.87% and the transfer rate of 16.2%-32.8%. In this paper, the quality value transmitting of substance benchmarks of Zhuru Decoction was analyzed based on chromatographic fingerprints, extraction rate, and the content of index components. A scientific and stable method was preliminarily established, which provided a scientific basis for the quality control and formulation development of Zhuru Decoction.

[Quality value transmitting of substance benchmarks in Danggui Buxue Decoction].

To clarify the key quality attributes of substance benchmarks in Danggui Buxue Decoction(DBD), this study prepared 21 batches of DBD substance benchmarks, and established two methods for detecting their fingerprints, followed by the identification of peak attribution and similarity range as well as the determination of extract and transfer rate ranges and contents of index components ferulic acid, calycosin-7-O-ß-D-glucoside, and astragaloside Ⅳ. The mass fractions and transfer rates of DBD substance benchmarks from different batches were calculated as follows: ferulic acid(index component in Angelicae Sinensis Radix): 0.037%-0.084% and 31.41%-98.88%; astragaloside Ⅳ(index component in Astragali Radix): 0.021%-0.059% and 32.18%-118.57%; calycosin-7-O-ß-D-glucoside: 0.002%-0.023% and 11.51%-45.65%, with the extract rate being 18.4%-36.1%. The similarity of fingerprints among 21 batches of DBD substance benchmarks was all higher than 0.9. The quality control method for DBD substance benchmarks was preliminarily established based on the HPLC fingerprint analysis and index component determination, which has provided a basis for the subsequent development of DBD and the quality control of novel related preparations.