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PubMed2004

Step width variability, but not step length variability or step time variability, discriminates gait of healthy young and older adults during treadmill locomotion.

The variability of spatial and temporal step kinematics have separately been shown to prospectively predict falls by older adults. However, the published literature has not addressed the relative importance of the information related to locomotion control contributed by variability of spatial variables, temporal variables, or both. We conducted a post hoc analysis to determine the extent to which the variability of spatial and temporal step kinematics are independent descriptors of locomotion control in healthy young and older adults. A second purpose of the analysis was to establish the extent to which treadmill walking mimics overground walking using a benchmark for step kinematics. Eighteen young adults and 12 older adults walked at a self-selected velocity on an instrumented treadmill from which step length variability, step width variability and step time variability were computed. Stepwise discriminant analysis correctly classified group membership of 70 percent of the 30 subjects (i.e., young or older adult) using only step width variability (p=0.037, Wilk's lamda=0.854). Step width variability was 70+/-57 percent larger than step length variability (p<0.001). This relationship was similar to that of the benchmark established for overground locomotion. The results suggest that for healthy younger and older adults step width variability is a more meaningful descriptor of locomotion control than step length variability and step time variability. Given the potential clinical impact, further systematic study and improvement of the methods and technology for acquiring step kinematic data are warranted.

Adult↗

PubMed2006

Process economics of industrial monoclonal antibody manufacture.

Pressures for cost-effective manufacture of antibodies are growing given their high doses and increasing market potential that have resulted in significant increases in total site capacities of up to 200,000 L. This paper focuses on the process economic issues associated with manufacturing antibodies and reviews the cost studies published in the literature; many of the issues highlighted are not only specific to antibodies but also apply to recombinant proteins. Data collated at UCL suggest current benchmark investment costs of $660-$1580/ft2 ($7130-$17,000/m2) and $1765-$4220/L for antibody manufacturing facilities with total site capacities in the range of 20,000-200,000 L; the limitations of the data are highlighted. The complications with deriving benchmark cost of goods per gram (COG/g) values are discussed, stressing the importance of stating the annual production rate and either titre or fermentation capacity with the cost so as to allow comparisons. The uses and limitations of the methods for cost analysis and the available software tools for process economics are presented. Specific examples found in the literature of process economic studies related to antibody manufacture for different expression systems are reviewed. The key economic drivers are identified; factors such as fermentation titre and overall yield are critical determinants of economic success. Future trends in antibody manufacture that are driven by economic pressures are discussed, such as the use of alternative expression systems (e.g. transgenics, E. coli and yeast), disposables, and improvements to downstream technology. The hidden costs and the challenges in each case are highlighted.

Animals↗

PubMed2004

Protein flexibility in ligand docking and virtual screening to protein kinases.

The main complicating factor in structure-based drug design is receptor rearrangement upon ligand binding (induced fit). It is the induced fit that complicates cross-docking of ligands from different ligand-receptor complexes. Previous studies have shown the necessity to include protein flexibility in ligand docking and virtual screening. Very few docking methods have been developed to predict the induced fit reliably and, at the same time, to improve on discriminating between binders and non-binders in the virtual screening process. We present an algorithm called the ICM-flexible receptor docking algorithm (IFREDA) to account for protein flexibility in virtual screening. By docking flexible ligands to a flexible receptor, IFREDA generates a discrete set of receptor conformations, which are then used to perform flexible ligand-rigid receptor docking and scoring. This is followed by a merging and shrinking step, where the results of the multiple virtual screenings are condensed to improve the enrichment factor. In the IFREDA approach, both side-chain rearrangements and essential backbone movements are taken into consideration, thus sampling adequately the conformational space of the receptor, even in cases of large loop movements. As a preliminary step, to show the importance of incorporating protein flexibility in ligand docking and virtual screening, and to validate the merging and shrinking procedure, we compiled an extensive small-scale virtual screening benchmark of 33 crystal structures of four different protein kinases sub-families (cAPK, CDK-2, P38 and LCK), where we obtained an enrichment factor fold-increase of 1.85+/-0.65 using two or three multiple experimental conformations. IFREDA was used in eight protein kinase complexes and was able to find the correct ligand conformation and discriminate the correct conformations from the "misdocked" conformations solely on the basis of energy calculation. Five of the generated structures were used in the small-scale virtual screening stage and, by merging and shrinking the results with those of the original structure, we show an enrichment factor fold increase of 1.89+/-0.60, comparable to that obtained using multiple experimental conformations. Our cross-docking tests on the protein kinase benchmark underscore the necessity of incorporating protein flexibility in both ligand docking and virtual screening. The methodology presented here will be extremely useful in cases where few or no experimental structures of complexes are available, while some binders are known.

Algorithms↗

PubMed2005

Mimicking cellular sorting improves prediction of subcellular localization.

Predicting the native subcellular compartment of a protein is an important step toward elucidating its function. Here we introduce LOCtree, a hierarchical system combining support vector machines (SVMs) and other prediction methods. LOCtree predicts the subcellular compartment of a protein by mimicking the mechanism of cellular sorting and exploiting a variety of sequence and predicted structural features in its input. Currently LOCtree does not predict localization for membrane proteins, since the compositional properties of membrane proteins significantly differ from those of non-membrane proteins. While any information about function can be used by the system, we present estimates of performance that are valid when only the amino acid sequence of a protein is known. When evaluated on a non-redundant test set, LOCtree achieved sustained levels of 74% accuracy for non-plant eukaryotes, 70% for plants, and 84% for prokaryotes. We rigorously benchmarked LOCtree in comparison to the best alternative methods for localization prediction. LOCtree outperformed all other methods in nearly all benchmarks. Localization assignments using LOCtree agreed quite well with data from recent large-scale experiments. Our preliminary analysis of a few entirely sequenced organisms, namely human (Homo sapiens), yeast (Saccharomyces cerevisiae), and weed (Arabidopsis thaliana) suggested that over 35% of all non-membrane proteins are nuclear, about 20% are retained in the cytosol, and that every fifth protein in the weed resides in the chloroplast.

Animals↗

PubMed2006

Partitioning protein structures into domains: why is it so difficult?

This analysis takes an in-depth look into the difficulties encountered by automatic methods for domain decomposition from three-dimensional structure. The analysis involves a multi-faceted set of criteria including the integrity of secondary structure elements, the tendency toward fragmentation of domains, domain boundary consistency and topology. The strength of the analysis comes from the use of a new comprehensive benchmark dataset, which is based on consensus among experts (CATH, SCOP and AUTHORS of the 3D structures) and covers 30 distinct architectures and 211 distinct topologies as defined by CATH. Furthermore, over 66% of the structures are multi-domain proteins; each domain combination occurring once per dataset. The performance of four automatic domain assignment methods, DomainParser, NCBI, PDP and PUU, is carefully analyzed using this broad spectrum of topology combinations and knowledge of rules and assumptions built into each algorithm. We conclude that it is practically impossible for an automatic method to achieve the level of performance of human experts. However, we propose specific improvements to automatic methods as well as broadening the concept of a structural domain. Such work is prerequisite for establishing improved approaches to domain recognition. (The benchmark dataset is available from http://pdomains.sdsc.edu).

Computational Biology↗

PubMed2026

Proteomics at scale: Bottlenecks and opportunities for early-career researchers in a fast developing field.

The field of proteomics has rapidly evolved over the last five years enabled by rapid advances in instrumentation and computation. At the same time, the proteomics community is also growing. This is reflected by the increasing participation in international conferences such as those organized by the European Proteomics Association and the Human Proteome Organization. These events provide early-career researchers with unique opportunities to exchange ideas, develop collaborations, and build networks that support professional development. One such network is the Young Proteomics Investigators Club, a European initiative supported by European Proteomics Association and led by early-career researchers. In this Community-Driven project, we investigate recent trends in proteomics by screening conference abstracts and evaluating the session attendance at Human Proteome Organization Congresses and European Proteomics Association conferences. Based on these analyses, we identified five areas that, from our perspective, are shaping the current trends in proteomics: clinical proteomics, proteomics of post-translational modifications, single-cell proteomics, systems biology and multi-omics, and computational proteomics. For each area, we highlight both unique challenges and identify a common theme: a shift from exploratory studies with manageable sample numbers towards large screenings and cohorts and the generation of big data, which often comes with the lack of computational support, organizational networks, and infrastructure. In this light, we describe the unique challenges and opportunities faced by early-career researchers. We point to actionable directions for enabling reproducible and transparent proteomics as well as community-driven projects and initiatives, which are often providing training and support. SIGNIFICANCE: In this perspective, the Young Proteomics Investigators Club (YPIC) discusses advances in analytical developments and computational approaches in proteomics research. Based on empirical analysis of recent European Proteomics Association conference and Human Proteome Organization congresses contributions, we identify clinical, single-cell, post-translational and systems-level proteomics as the research areas that have gained most momentum in the last three to five years. What makes this work distinctive is that it is written by and for early-career researchers, thereby uniquely identifying where momentum, challenges, and unmet needs converge for the newest generation of proteomics researchers. Rather than cataloguing advances, we examine the widening gap between what modern proteomics can generate and what individual researchers can realistically process, validate, and interpret. We describe specific structural barriers including access to high performance computing, limited formal training in scalable data analysis, the need for unified benchmarking standards and navigating clinical collaboration frameworks. We then highlight opportunities for the field, such as community-curated benchmarks, interdisciplinary mentorship models, and shared computational infrastructure. By making these challenges explicit from an early-career researchers standpoint, we aim to inform how training, funding, and community initiatives can be shaped to support the next generation of proteomics researchers.

Proteomics↗

PubMed2005

Structural characterization of components of protein assemblies by comparative modeling and electron cryo-microscopy.

We explore structural characterization of protein assemblies by a combination of electron cryo-microscopy (cryoEM) and comparative protein structure modeling. Specifically, our method finds an optimal atomic model of a given assembly subunit and its position within an assembly by fitting alternative comparative models into a cryoEM map. The alternative models are calculated by MODELLER [J. Mol. Biol. 234 (1993) 313] from different sequence alignments between the modeled protein and its template structures. The fitting of these models into a cryoEM density map is performed either by FOLDHUNTER [J. Mol. Biol. 308 (2001) 1033] or by a new density fitting module of MODELLER (Mod-EM). Identification of the most accurate model is based on the correlation between the model accuracy and the quality of fit into the cryoEM density map. To quantify this correlation, we created a benchmark consisting of eight proteins of different structural folds with corresponding density maps simulated at five resolutions from 5 to 15 angstroms, with three noise levels each. Each of the proteins in the set was modeled based on 300 different alignments to their remotely related templates (12-32% sequence identity), spanning the range from entirely inaccurate to essentially accurate alignments. The benchmark revealed that one of the most accurate models can usually be identified by the quality of its fit into the cryoEM density map, even for noisy maps at 15 angstroms resolution. Therefore, a cryoEM density map can be helpful in improving the accuracy of a comparative model. Moreover, a pseudo-atomic model of a component in an assembly may be built better with comparative models of the native subunit sequences than with experimentally determined structures of their homologs.

Cryoelectron Microscopy↗

PubMed2026

Assessing perinatal depression identifying abilities among maternal and child health workers in rural China using smartphone-based virtual patients: a multi-center cross-sectional study.

OBJECTIVE: To assess rural maternal and child health (MCH) workers' virtual patients (VPs)-assessed performance in identifying perinatal depression (PND) using smartphone-based VPs, and to identify factors associated with this performance in rural Hunan, China. METHODS: A multicentre cross-sectional study was conducted in Hunan Province, China. A standardized questionnaire collected demographic and work-related characteristics of rural MCH workers. Smartphone-based VPs were used to assess PND identification performance in a simulated clinical scenario. An overall score ≥60 was used as a prespecified operational benchmark across consultation, ancillary assessment, diagnosis, management, and health education domains. Data were analyzed using SPSS 26.0. RESULTS: A total of 375 rural MCH workers participated, yielding an effective response rate of 90.4%. Only 25.9% met the prespecified operational benchmark for VP-assessed PND identification performance. The mean accuracy scores for consultation, ancillary assessment, diagnosis, management, and health education were 94%, 48%, 64%, 58%, and 74%, respectively. Complete consultation accuracy was higher among MCH workers from township health centers than among those from county-level MCH hospitals. MCH workers aged 18-39 years showed higher odds of complete diagnostic accuracy for PND than those aged ≥40 years. CONCLUSIONS: Smartphone-based VP assessment was feasible in rural MCH settings and revealed suboptimal PND identification performance. Mobile VPs may help identify frontline performance gaps and inform targeted training, but further validation against real-world clinical performance, or standardized patient encounters is needed before large-scale implementation. These findings may support targeted capacity-building for rural MCH workers and more equitable perinatal mental health care.

Humans↗

PubMed2026

Investigating cross-organism prediction of prokaryotic essential proteins using unsupervised language model and ensemble strategy.

Cross-organism prediction of essential proteins is a critical task for drug discovery and microbial engineering, yet the generalizability of existing machine learning models across diverse species remains a significant challenge. In this study, we propose DeepPEP, a large language model-based framework designed to reliably transfer essential protein annotations between distantly related organisms. Utilizing 66 curated prokaryotic datasets, we systematically evaluated DeepPEP's cross-organism performance under various conditions. Initial pairwise predictions revealed a correlation between performance and evolutionary distance; however, further investigation demonstrated that integrating training data from multiple organisms yields superior predictive power. In a benchmark scenario designed to simulate real-world applications, DeepPEP outperformed the state-of-the-art tool Geptop 2.0, showcasing a robust ability to identify species-specific essential proteins. Finally, a case study on novel genomes confirmed the model's practical effectiveness. Our results suggest that DeepPEP is a powerful strategy for prokaryotic essential protein prediction, and the rigorous evaluation framework established in this study provides a new benchmark for the field.

Large Language Models↗

PubMed2026

Sequence optimization targeting mRNA stability enhances monoclonal antibody titers in CHO cells.

This study presents a DNA sequence optimization approach that integrates mRNA stability as a tunable design parameter to enhance monoclonal antibody expression in Chinese hamster ovary (CHO) cells. A comprehensive combinatorial library of synonymous coding-sequence variants of an IgG1 light chain was integrated as single copies at a defined genomic locus in CHO cells with identical regulatory elements. Steady-state mRNA abundance, quantified by deep sequencing of gDNA and mRNA, served as a proxy for mRNA stability. These data were used to train a machine learning model that predicts mRNA abundance from coding sequence using embeddings from a pre-trained nucleotide transformer. This abundance predictor, together with established translational metrics, was incorporated into a genetic algorithm for multi-objective codon optimization. As proof-of-concept, we optimized sequences encoding Trastuzumab to either maximize or minimize the abundance criterion and obtained benchmark sequences from two commercial providers. Using targeted integration, we generated CHO cell lines and measured protein titer and cell-specific productivity. Sequences optimized for high abundance significantly increased intracellular mRNA levels (+41%), protein titer (+59%), and cell-specific productivity (+85%) relative to low-abundance designs, while viable cell densities remained comparable. Compared to commercial benchmarks, high-abundance sequences achieved significantly higher titer (+70%) and cell-specific productivity (+98%). These findings establish mRNA stability as a practical and complementary design parameter for codon optimization in monoclonal antibody production, with potential applicability to other proteins and expression systems.

CHO↗

PubMed2006

Evolutionary product unit based neural networks for regression.

This paper presents a new method for regression based on the evolution of a type of feed-forward neural networks whose basis function units are products of the inputs raised to real number power. These nodes are usually called product units. The main advantage of product units is their capacity for implementing higher order functions. Nevertheless, the training of product unit based networks poses several problems, since local learning algorithms are not suitable for these networks due to the existence of many local minima on the error surface. Moreover, it is unclear how to establish the structure of the network since, hitherto, all learning methods described in the literature deal only with parameter adjustment. In this paper, we propose a model of evolution of product unit based networks to overcome these difficulties. The proposed model evolves both the weights and the structure of these networks by means of an evolutionary programming algorithm. The performance of the model is evaluated in five widely used benchmark functions and a hard real-world problem of microbial growth modeling. Our evolutionary model is compared to a multistart technique combined with a Levenberg-Marquardt algorithm and shows better overall performance in the benchmark functions as well as the real-world problem.

Algorithms↗

PubMed2006

Intraocular lens power calculation after myopic refractive surgery: theoretical comparison of different methods.

OBJECTIVE: To evaluate the reliability of different methods developed to calculate intraocular lens (IOL) power after corneal refractive surgery. DESIGN: Retrospective observational case series. PARTICIPANTS: Preoperative and postoperative data of all eyes that underwent myopic excimer laser surgery in a private practice (Centro Salus, Bologna, Italy) between 1999 and 2004 were reviewed. INTERVENTION: The following methods were analyzed: videokeratography, clinical history, Shammas' refraction-derived and clinically derived methods, Rosa's correcting factor, Ferrara's variable refractive index, separate consideration of anterior and posterior corneal curvature (with and without preoperative data), Feiz-Mannis' formula and nomogram, and Latkany's regression formulas (based on both average and flattest postrefractive surgery keratometry). The Holladay 1 formula was used for eyes with an axial length between 22 and 24.49 mm and the SRK-T for eyes longer than 24.49 mm. Double-K formulas were also evaluated, when applicable. Each IOL power determined with these methods was compared to a benchmark value, calculated using the preoperative axial length and corneal power and aiming for the preoperative spherical equivalent. MAIN OUTCOME MEASURE: Mean error in IOL power prediction. RESULTS: Ninety-eight eyes of 98 patients were analyzed. The double-K clinical history method, Feiz-Mannis' formula, double-K method based on separate consideration of anterior and posterior corneal curvature (with and without preoperative data), and both Latkany's regression formulas were the only methods resulting in a mean IOL power not statistically different (P>0.05) from the benchmark used for comparative purposes. CONCLUSIONS: When prerefractive surgery data are available, IOL power should be calculated using the double-K clinical history method. Alternative choices may be represented by the Feiz-Mannis' formula, Latkany's regression formulas based on average and flattest postrefractive surgery keratometry, and the double-K method based on separate consideration of anterior and posterior corneal curvatures. A variant of the latter can be used to calculate IOL power when prerefractive surgery data are not available. Further prospective studies based on patients undergoing phacoemulsification after refractive surgery are needed to validate the results of this theoretical comparison.

Adult↗

PubMed2005

Motivational interviewing to support antiretroviral therapy adherence: the role of quality counseling.

OBJECTIVE: Although research linking motivational interviewing (MI) to behavior change exists, few studies report on MI's quality or explore how it may influence effectiveness. We studied MI quality and adherence to antiretroviral therapy (ART) in the context of a randomized, controlled trial. METHODS: We used a structured instrument to code MI sessions and then correlated ART adherence (measured by electronic bottle cap monitor and pill count data at study exit) with specific counseling behaviors and the proportion of interactions that achieved quality benchmarks. RESULTS: The sample (n = 47) was predominantly male (79%), minority (90%), had a mean age of 40, and averaged 79% adherence at exit. On three of five benchmarks, most MI sessions achieved the targeted quality level: 100% achieved them for MI-consistent statements; 85% for complex reflections; 63% for reflections to questions ratio; 44% for global therapist rating; 19% for using open-ended questions. ART adherence was positively associated with the ratio of reflections to questions (r = .39, p = .02), affirming statements (r = .38, p = .02), and negatively associated with closed-ended questions (r = -.33, p = .04). DISCUSSION: Good quality MI can be conducted within the structure of a controlled trial but was generally not associated with ART adherence. CONCLUSION: Documenting treatment fidelity is critical to judging the efficacy of MI-based interventions. PRACTICE IMPLICATIONS: Regular feedback and close monitoring are needed to maintain MI quality.

Adult↗

PubMed2005

Assessment of the welfare of working horses, mules and donkeys, using health and behaviour parameters.

Working animals provide an essential transport resource in developing countries worldwide. Many of these animals are owned by poor people and work in harsh environments, so their welfare is a cause for concern. A protocol was developed to assess the welfare of working horses, mules and donkeys in urban and peri-urban areas, using direct observation of health and behaviour parameters. In this study, 4903 animals used for draught, pack and ridden work in Afghanistan, Egypt, India, Jordan and Pakistan were assessed between December 2002 and April 2003. The data showed that donkeys were more likely than mules or horses to demonstrate avoidance or aggressive behaviour towards an observer, while horses were most likely to make a friendly approach. Fewer than 8% of working equines had abnormal mucous membranes, ectoparasites or poor coat condition. Body lesions occurred predominantly in the areas of the breast/shoulder, withers and girth in all three species, with mules having the highest prevalence of lesions in these areas (22.5, 21.3 and 28.4%, respectively). Among horses and donkeys, the prevalence of these lesions was influenced by the type of work carried out. Lesions on the head, neck, ribs, flank and tail base were seen in less than 10% of animals. Across all three species approximately 70% of animals were thin, having a body condition score (BCS) of 2 or less on a scale of 1-5 (1, very thin; 5, very fat) and more horses were in very thin condition (BCS 1) than mules or donkeys. Over 75% of animals demonstrated limb deformities and abnormalities of gait. The results of this study are being used as the initial stage of a long-term strategy to inform priorities for welfare interventions in working equines and to establish a welfare benchmark. Subsequent stages will rank the welfare concerns identified, assess the contributing risk factors and implement specific interventions to address these risks. Following intervention, success in improving welfare will be measured by repetition of this protocol and comparison with the benchmark.

Animal Welfare↗

PubMed2026

Targeting the F17-A Fimbrial gene: An efficient method for the quantitative detection of Escherichia coli F17.

Escherichia coli (E. coli) F17 is one of the leading bacterial causes of diarrhea in farm livestock, which cause huge economic losses and could also pose potential risks to public health. Generally, the monitoring the E. coli F17 is based on the polymerase chain reaction (PCR) and bacteria plate counting method, which were largely limited by the time-consuming nature and susceptibility to detection errors. Hence, there is an urgent need to develop a rapid and quantitative detection method for E. coli F17. In the present study, an E. coli F17 challenge experiment in ovine intestinal epithelial cells (IECs) was employed as an in vitro model. At different post-challenge time points (1 h, 2 h, and 3 h), two conventional methods (bacteria plate counting and microplate method) were conducted as benchmarks to estimate the number of E. coli F17 adhering to the IECs. Additionally, total genomic DNA was extracted and quantitative Real-time PCR (qPCR) was performed to detect the relative abundance of E. coli F17 fimbrial pilin (F17-A) and adhesion (F17-G) genes. Subsequently, statistical analyses, including Pearson's correlation coefficient (PCC) method and linear curve-fitting, were performed to evaluate the correlation between the abundance of F17-A/G genes and the results of the benchmark methods. The results showed that the relative abundances of both genes were highly correlated with the number of E. coli F17 that adhered to the IECs, among them, the F17-A gene showed a stronger correlation with the bacterial counts, exhibiting a correlation coefficient > 0.85. Furthermore, standard curves analyses further confirmed the out-performed quantitative performance of F17-A gene and a significantly stronger correlation with bacterial counts which exhibited an outstanding linear correlation (r = -0.9534, R2 = 0.9252) with amplification efficiency of 101.4%, The results of the present study indicate that targeting fimbrial genetic hallmarks via qPCR is an effective and promising method for E. coli F17 quantification, which could potentially contribute to epidemiological studies and pathogen monitoring in the livestock industry.

Detection↗

PubMed2004

Inter-comparison of multimedia modeling approaches: modes of transport, measures of long range transport potential and the spatial remote state.

Several evaluative multi-media models have been developed during the recent years to determine the long-range transport potential, LRTP, of non-polar organic chemicals. Here, these models are categorized and compared with respect to the modes of transport and the measures used to compute LRTP. Differences concerning the mode of transport include the transport mechanism (advective vs. dispersive transport) and the number and coupling of transport media (transport in a single moving medium vs. coupled transport in air and water). Measures used include the characteristic travel distance and the spatial range. The spatial remote state is defined as a benchmark for the comparison of the different measures. This is the state of the model system far-off the source that is independent of the release pattern. With the expected value in the spatial remote state as a benchmark, the maximum of the spatial ranges in air and water and the maximum of the characteristic travel distances in air and water as well as the spatial range in air in combination with release into water prove to be reliable measures of the LRTP. The framework developed allows one to overview the features of the different models used in the ranking and assessment of chemicals.

Air Movements↗

PubMed2006

Hierarchical models for probabilistic dose-response assessment.

Probabilistic risk assessment is gaining acceptance as the most appropriate way to characterize and communicate uncertainties in estimates of human health risk and/or reference levels of exposure such as benchmark doses. Although probabilistic techniques are well established in the exposure-assessment component of the National Research Council's risk-assessment paradigm, they are less well developed in the dose-response-assessment component. This paper proposes the use of hierarchical statistical models as tools for implementing probabilistic dose-response assessments, in that such models provide a natural connection between the pharmacokinetic (PK) and pharmacodynamic (PD) components of dose-response models. The results show that incorporating internal dose information into dose-response assessments via the coupling of PK and PD models in a hierarchical structure can reduce the uncertainty in the dose-response assessment of risk. However, information on the mean of the internal dose distribution is sufficient; having information on the variance of internal dose does not affect the uncertainty in the resulting estimates of excess risks or benchmark doses. In addition, the complexity of a PK model of internal dose does not affect how the variability in risk is measured via the ultimate endpoint.

Dose-Response Relationship, Drug↗

PubMed2006

Biomonitoring equivalents: a screening approach for interpreting biomonitoring results from a public health risk perspective.

Advances in both sensitivity and specificity of analytical chemistry have made it possible to quantify substances in human biological specimens, such as blood, urine, and breast milk, in specimen volumes that are practical for collection from individuals. Research laboratories led by the Centers for Disease Control and Prevention (CDC) in its series National Report on Human Exposure to Environmental Chemicals [Centers for Disease Control and Prevention (CDC), 2005. Third National Report on Human Exposure to Environmental Chemicals. NCEH Pub. No. 05-0570.] are dedicating substantial resources to designing and conducting human biomonitoring studies and compiling biomonitoring data for the general population. However, the ability to quantitatively interpret the results of human biomonitoring in the context of a health risk assessment currently lags behind the analytical chemist's ability to make such measurements. The traditional paradigm for human health risk assessment of environmental chemicals involves comparing estimated daily doses to health-based criteria for acceptable, safe, or tolerable daily intakes (for example, reference doses [RfDs], tolerable daily intakes [TDIs], or minimal risk levels [MRLs]) to assess whether estimated doses exceed such health screening levels. However, biomonitoring efforts result in measured chemical concentrations in biological specimens (the result of absorption, distribution, metabolism and excretion of administered doses) rather than estimated intake doses. Quantitative benchmarks of acceptable or safe concentrations in biological specimens (analogous to RfDs, TDIs, or MRLs) needed to interpret these levels exist for very few chemicals of environmental interest. This paper discusses issues inherent in converting existing health screening benchmarks based on intake doses to screening levels for evaluating biomonitoring data, and presents methods and approaches that can be used to derive such screening levels (termed "Biomonitoring Equivalents," or BEs) for a range of chemicals and biological media.

Animals↗