Individual-specific postural discomfort prediction using decision tree models

The objective of the current study was to explore the utilization of the decision tree (DT) algorithm to model posture-discomfort relationships at the individual level. The DT algorithm has the advantage that it makes no assumptions about the distribution of data, is robust in representing non-linear data with noise, and produces white-box models that are interpretable. Individual-level modelling is essential for examining individual-specific postural discomfort perception processes and understanding the inter-individual variability. It also has practical applications, including the development of individual-specific digital human models and more precise and informative population accommodation analysis. Individual-specific DT models were generated using postural discomfort rating data for various seated upper body postures to predict discomfort based on postural and task variables. The individual-specific DT models accurately predicted postural discomfort and revealed large inter-individual variability in the modelling results. DT modelling is expected to greatly facilitate investigating the human discomfort perception process.

Bioavailability and excretion profile of betacyanins - Variability and correlations between different excretion routes

The present study addresses the knowledge gap in betalain bioavailability, transformation and excretion. Analysis of renal and fecal excretion profiles in humans after consumption of beetroot revealed very low bioavailability (renal recovery of 0.13 %) and fast elimination of pigments (renal elimination rate constant of 0.16 h-1), while the majority of betalains underwent severe depletion during GI transit, evidenced by decarboxylation, deglucosidation and dehydrogenation. Betacyanin metabolite levels in human urine were positively associated with those in stools (p < 0.05), indicating significant impact of pigment metabolism in the gut on their bioavailability. In addition, the current study revealed large inter-individual and compositional variabilities of pigment after colonic fermentation compared with systemic metabolism, likely attributed to the increasing complexity of intestinal environment with diverse gut microbiota. To conclude, intestinal uptake and systemic metabolism of betacyanins are intimately associated with their intestinal biotransformation, with gut microbiota serving as a crucial factor.

Towards a qualitative theory of the interruption of eating behavior change

The poor maintenance of eating behavior change is one of the main obstacles to minimizing weight regain after weight loss during diets for non-surgical care of obese or overweight patients. We start with a known informal explanation of interruption in eating behavior change during severe restriction and formalize it as a causal network involving psychological variables, which we extend with energetic variables governed by principles of thermodynamics. The three core phenomena of dietary behavior change, i.e., non-initiation, initiation followed by discontinuation and initiation followed by non-discontinuation, are expressed in terms of the value of the key variable representing mood or psychological energy, the fluctuation of which is the result of three causal relationships. Based on our experimental knowledge of the time evolution profile of the three causal input variables, we then proceed to a qualitative analysis of the resulting theory, i.e., we consider an over-approximation of it which, after discretization, can be expressed in the form of a finite integer-based model. Using Answer Set Programming, we show that our formal model faithfully reproduces the three phenomena and, under a certain assumption, is minimal. We generalize this result by providing all the minimal models reproducing these phenomena when the possible causal relationships exerted on mood are extended to all the other variables (not just those assumed in the informal explanation), with arbitrary causality signs. Finally, by a direct analytical resolution of an under-approximation of our theory, obtained by assuming linear causalities, as a system of linear ODEs, we find exactly the same minimal models, proving that they are also equal to the actual minimal models of our theory since these are framed below and above by the models of the under-approximation and the over-approximation. We determine which parameters need to be person-specific and which can be considered invariant, i.e., we explain inter-individual variability. Our approach could pave the way for universally accepted theories in the field of behavior change and, more broadly, in other areas of psychology.

Dimensionality and optimal combination of autonomic fear-conditioning measures in humans

Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.

CSF protein ratios with enhanced potential to reflect Alzheimer's disease pathology and neurodegeneration

BACKGROUND

Amyloid and tau aggregates are considered to cause neurodegeneration and consequently cognitive decline in individuals with Alzheimer's disease (AD). Here, we explore the potential of cerebrospinal fluid (CSF) proteins to reflect AD pathology and cognitive decline, aiming to identify potential biomarkers for monitoring outcomes of disease-modifying therapies targeting these aggregates.

METHOD

We used a multiplex antibody-based suspension bead array to measure the levels of 49 proteins in CSF from the Swedish GEDOC memory clinic cohort at the Karolinska University Hospital. The cohort comprised 148 amyloid- and tau-negative individuals (A-T-) and 65 amyloid- and tau-positive individuals (A+T+). An independent sample set of 26 A-T- and 26 A+T+ individuals from the Amsterdam Dementia Cohort was used for validation. The measured proteins were clustered based on their correlation to CSF amyloid beta peptides, tau and NfL levels. Further, we used support vector machine modelling to identify protein pairs, matched based on their cluster origin, that reflect AD pathology and cognitive decline with improved performance compared to single proteins.

RESULTS

The protein-clustering revealed 11 proteins strongly correlated to t-tau and p-tau (tau-associated group), including mainly synaptic proteins previously found elevated in AD such as NRGN, GAP43 and SNCB. Another 16 proteins showed predominant correlation with Aβ42 (amyloid-associated group), including PTPRN2, NCAN and CHL1. Support vector machine modelling revealed that proteins from the two groups combined in pairs discriminated A-T- from A+T+ individuals with higher accuracy compared to single proteins, as well as compared to protein pairs composed of proteins originating from the same group. Moreover, combining the proteins from different groups in ratios (tau-associated protein/amyloid-associated protein) significantly increased their correlation to cognitive decline measured with cognitive scores. The results were validated in an independent cohort.

CONCLUSIONS

Combining brain-derived proteins in pairs largely enhanced their capacity to discriminate between AD pathology-affected and unaffected individuals and increased their correlation to cognitive decline, potentially due to adjustment of inter-individual variability. With these results, we highlight the potential of protein pairs to monitor neurodegeneration and thereby possibly the efficacy of AD disease-modifying therapies.

A strategy for deciphering the bioactive metabolites of Farfarae Flos by the inter-individual variability of the antitussive effect

Farfarae Flos is a commonly used traditional herb for the treatment of respiratory disorders. In this study, ultra-high-performance liquid chromatography coupled with time-of-flight mass spectrometry combined with the mass defect filter method was used for the qualitative analysis of Farfarae Flos metabolites in the lung tissues. Then a method for the simultaneous determination of 14 Farfarae Flos metabolites was developed and validated in terms of specificity, linearity, precision and accuracy, matrix effect and recovery. The method was applied to compare the lung tissue of Farfarae Flos treated mice, and 10 caffeoylquinic acid metabolites were higher in the mice with better antitussive effect. Further network pharmacology analysis and molecular docking results showed that these metabolites played an important role in the antitussive effect of Farfarae Flos. This study presented a novel strategy for deciphering the active compounds of herbal medicine by inter-individual variability of bioactivities.

How far are we from reliable metabolomics-based biomarkers? The often-overlooked importance of addressing inter-individual variability factors

Metabolomics has proven great potential to unravel the molecular basis of diseases. However, most attempts aimed at identifying reliable metabolomics-based biomarkers for diagnosis, prediction, and prognosis of diseases have repeatedly failed because of inconsistent results and unsatisfactory replication in independent cohorts. This review article explores the possible causes behind this reproducibility crisis, with special focus on the role that inter-individual variability factors play in modulating the susceptibility to disease development. Furthermore, we provide future perspectives on the applicability of metabolomics in biomedical research and its translatability into clinical practice.

Personalized redox biology: Designs and concepts

Personalized interventions are regarded as a next-generation approach in almost all fields of biomedicine, such as clinical medicine, exercise, nutrition and pharmacology. At the same time, an increasing body of evidence indicates that redox processes regulate, at least in part, multiple aspects of human physiology and pathology. As a result, the idea of applying personalized redox treatments to improve their efficacy has gained popularity among researchers in recent years. The aim of the present primer-style review was to highlight some crucial yet underappreciated methodological, statistical, and interpretative concepts within the redox biology literature, while also providing a physiology-oriented perspective on personalized redox biology. The topics addressed are: (i) the critical issue of investigating the potential existence of inter-individual variability; (ii) the importance of distinguishing a genuine and consistent response of a subject from a chance finding; (iii) the challenge of accurately quantifying the effect of a redox treatment when dealing with 'extreme' groups due to mathematical coupling and regression to the mean; and (iv) research designs and analyses that have been implemented in other fields, and can be reframed and exploited in a redox biology context.

Importance of cytochrome 3A4 and 2D6-mediated drug-drug interactions in oxycodone consumption among older adults hospitalized for hip fracture: a cross-sectional study

Hip fracture is a common injury and represents a major health problem with an increasing incidence. In older adults, opioids such as oxycodone are often preferred to other analgesics such as tramadol because of a lower risk of delirium. Different parameters, such as inhibition of cytochrome P450 (CYP450) 2D6 and/or 3A4, can potentially lead to pharmacokinetic variations of oxycodone representing a risk of adverse drugs effects or lack of drug response. There is a risk of drug-drug interactions involving CYP450 in older adults due to the high prevalence of polypharmacy. This study sought to identify patient characteristics that influence oxycodone administration. A single-center observational study included 355 patients with a hip fracture hospitalized in a geriatric postoperative unit. Composite endpoint based on form, duration, and timing to intake separated patients into three groups: "no oxycodone", "low oxycodone ", and "high oxycodone ". CYP450 interactions were studied based on a composite variable defining the most involved CYP450 pathways between CYP2D6 and CYP3A4. CYP450 interactions with CYP2D6 pathway involved were associated with the risk of "high oxycodone" [odds ratio adjusted on age and the type of hip fracture (OR*) 4.52, 95% confidence interval (CI) 1.39-16.83, p = 0.02)], as well as serum albumin levels (OR* 1.09, 95% CI 1.02-1.17, p = 0.01). Cognitive impairment was negatively associated with the risk of "high oxycodone" (OR* 0.38, 95% CI 0.18-0.77, p = 0.02). This study showed an association between CYP2D6 interactions and higher oxycodone consumption indirectly reflecting the existence of uncontrolled postoperative pain.

Unravelling phenolic metabotypes in the frame of the COMBAT study, a randomized, controlled trial with cranberry supplementation

Cranberry (poly)phenols may have potential health benefits. Circulating (poly)phenol metabolites can act as mediators of these effects, but they are subjected to an extensive inter-individual variability. This study aimed to quantify both plasma and urine (poly)phenol metabolites following a 12-week intake of a cranberry powder in healthy older adults, and to investigate inter-individual differences by considering the existence of urinary metabotypes related to dietary (poly)phenols. Up to 13 and 67 metabolites were quantified in plasma and urine respectively. Cranberry consumption led to changes in plasma metabolites, mainly hydroxycinnamates and hippuric acid. Individual variability in urinary metabolites was assessed using different data sets and a combination of statistical models. Three phenolic metabotypes were identified, colonic metabolism being the main driver for subject clustering. Metabotypes were characterized by quali-quantitative differences in the excretion of some metabolites such as phenyl-γ-valerolactones, hydroxycinnamic acids, and phenylpropanoic acids. Metabotypes were further confirmed when applying a model only focused on flavan-3-ol colonic metabolites. 5-(3',4'-dihydroxyphenyl)-γ-valerolactone derivatives were the most relevant metabolites for metabotyping. Metabotype allocation was well preserved after 12-week intervention. This metabotyping approach for cranberry metabolites represents an innovative step to handle the complexity of (poly)phenol metabolism in free-living conditions, deciphering the existence of metabotypes derived from the simultaneous consumption of different classes of (poly)phenols. These results will help contribute to studying the health effects of cranberries and other (poly)phenol-rich foods, mainly considering gut microbiota-driven individual differences.

P1NP and β-CTX-1 Responses to a Prolonged, Continuous Running Bout in Young Healthy Adult Males: A Systematic Review with Individual Participant Data Meta-analysis

BACKGROUND

Circulating biomarkers of bone formation and resorption are widely used in exercise metabolism research, but their responses to exercise are not clear. This study aimed to quantify group responses and inter-individual variability of P1NP and β-CTX-1 after prolonged, continuous running (60-120 min at 65-75% V̇O2max) in young healthy adult males using individual participant data (IPD) meta-analysis.

METHODS

The protocol was designed following PRISMA-IPD guidelines and was pre-registered on the Open Science Framework prior to implementation ( https://osf.io/y69nd ). Changes in P1NP and β-CTX-1 relative to baseline were measured during, immediately after, and in the hours and days following exercise. Typical hourly and daily variations were estimated from P1NP and β-CTX-1 changes relative to baseline in non-exercise (control) conditions. Group responses and inter-individual variability were quantified with estimates of the mean and standard deviation of the difference, and the proportion of participants exhibiting an increased response. Models were conducted within a Bayesian framework with random intercepts to account for systematic variation across studies.

RESULTS

P1NP levels increased during and immediately after running, when the proportion of response was close to 100% (75% CrI: 99 to 100%). P1NP levels returned to baseline levels within 1 h and over the next 4 days, showing comparable mean and standard deviation of the difference with typical hourly (0.1 ± 7.6 ng·mL-1) and daily (- 0.4 ± 5.7 ng·mL-1) variation values. β-CTX-1 levels decreased during and up to 4 h after running with distributions comparable to typical hourly variation (- 0.13 ± 0.11 ng·mL-1). There was no evidence of changes in β-CTX-1 levels during the 4 days after the running bout, when distributions were also similar between the running data and typical daily variation (- 0.03 ± 0.10 ng·mL-1).

CONCLUSION

Transient increases in P1NP were likely biological artefacts (e.g., connective tissue leakage) and not reflective of bone formation. Comparable small decreases in β-CTX-1 identified in both control and running data, suggested that these changes were due to the markers' circadian rhythm and not the running intervention. Hence, prolonged continuous treadmill running did not elicit bone responses, as determined by P1NP and β-CTX-1, in this population.

A systematic review of the neurobiological effects of theta-burst stimulation (TBS) as measured using functional magnetic resonance imaging (fMRI)

Theta burst stimulation (TBS) is associated with the modulation of a range of clinical, cognitive, and behavioural outcomes, but specific neurobiological effects remain somewhat unclear. This systematic literature review investigated resting-state and task-based functional magnetic resonance imaging (fMRI) outcomes post-TBS in healthy human adults. Fifty studies that applied either continuous-or intermittent-(c/i) TBS, and adopted a pretest-posttest or sham-controlled design, were included. For resting-state outcomes following stimulation applied to motor, temporal, parietal, occipital, or cerebellar regions, functional connectivity generally decreased in response to cTBS and increased in response to iTBS, though there were some exceptions to this pattern of response. These findings are mostly consistent with the assumed long-term depression (LTD)/long-term potentiation (LTP)-like plasticity effects of cTBS and iTBS, respectively. Task-related outcomes following TBS were more variable. TBS applied to the prefrontal cortex, irrespective of task or state, also produced more variable responses, with no consistent patterns emerging. Individual participant and methodological factors are likely to contribute to the variability in responses to TBS. Future studies assessing the effects of TBS via fMRI must account for factors known to affect the TBS outcomes, both at the level of individual participants and of research methodology.

Individual consistency in the learning abilities of honey bees: cognitive specialization within sensory and reinforcement modalities

The question of whether individuals perform consistently across a variety of cognitive tasks is relevant for studies of comparative cognition. The honey bee (Apis mellifera) is an appropriate model to study cognitive consistency as its learning can be studied in multiple elemental and non-elemental learning tasks. We took advantage of this possibility and studied if the ability of honey bees to learn a simple discrimination correlates with their ability to solve two tasks of higher complexity, reversal learning and negative patterning. We performed four experiments in which we varied the sensory modality of the stimuli (visual or olfactory) and the type (Pavlovian or operant) and complexity (elemental or non-elemental) of conditioning to examine if stable correlated performances could be observed across experiments. Across all experiments, an individual's proficiency to learn the simple discrimination task was positively and significantly correlated with performance in both reversal learning and negative patterning, while the performances in reversal learning and negative patterning were positively, yet not significantly correlated. These results suggest that correlated performances across learning paradigms represent a distinct cognitive characteristic of bees. Further research is necessary to examine if individual cognitive consistency can be found in other insect species as a common characteristic of insect brains.

Inter-individual variability in current direction for common tDCS montages

The direction of applied electric current relative to the cortical surface is a key determinant of transcranial direct current stimulation (tDCS) effects. Inter-individual differences in anatomy affect the consistency of current direction at a cortical target. However, the degree of this variability remains undetermined. Using current flow modelling (CFM), we quantified the inter-individual variability in tDCS current direction at a cortical target (left primary motor cortex, M1). Three montages targeting M1 using circular electrodes were compared: PA-tDCS directed current perpendicular to the central sulcus in a posterior-anterior direction relative to M1, ML-tDCS directed current parallel to the central sulcus in a medio-lateral direction, and conventional-tDCS applied electrodes over M1 and the contralateral forehead. In 50 healthy brain scans from the Human Connectome Project, we extracted current direction and intensity from the grey matter surface in the sulcal bank (M1BANK) and gyral crown (M1CROWN), and neighbouring primary somatosensory cortex (S1BANK and S1CROWN). Results confirmed substantial inter-individual variability in current direction (50%-150%) across all montages. Radial inward current produced by PA-tDCS was predominantly located in M1BANK, whereas for conventional-tDCS it was clustered in M1CROWN. The difference in radial inward current in functionally distinct subregions of M1 raises the testable hypothesis that PA-tDCS and conventional-tDCS modulate cortical excitability through different mechanisms. We show that electrode locations can be used to closely approximate current direction in M1 and precentral gyrus, providing a landmark-based method for tDCS application to address the hypothesis without the need for MRI. By contrast, ML-tDCS current was more tangentially orientated, which is associated with weaker somatic polarisation. Substantial inter-individual variability in current direction likely contributes to variable neuromodulation effects reported for these protocols, emphasising the need for individualised electrode montages, including the control of current direction.

Comparative transcriptome in large-scale human and cattle populations

BACKGROUND

Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes.

RESULTS

Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues.

CONCLUSIONS

In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

Background and objective

Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect.

Methods

Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2×2×2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change.

Results

In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = –3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis.

Conclusions

Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects.

Investigating the inter-individual variability of Astragali Radix against cisplatin-induced liver injury via 16S rRNA gene sequencing and LC/MS-based metabolomics

BACKGROUND

Cisplatin (CDDP), one of the widely used chemotherapeutic drugs, can induce a series of side effects, such as hepatotoxicity and gastrointestinal toxicity. Astragali Radix (AR) is widely used as the tonic herbal medicine in traditional Chinese medicine (TCM). However, there was no report about the hepatoprotective effect of AR against the cisplatin-induced hepatic damage.

PURPOSE

This study aimed to investigate the protective effect and potential mechanism of AR water extract against the cisplatin-induced liver injury.

METHODS

Cisplatin was utilized to induce the liver injury using ICR mice, and the protective effect of AR was evaluated by serum biochemistry indices and liver histopathology. Then UHPLC Q-TOF-MS/MS-based untargeted serum metabolomics approach combined with 16S rRNA-based microbiota analysis was used to explore the underlying biomarkers and mechanism about the liver-protective effect of AR.

RESULTS

AR could decrease the serum AST and ALT, ameliorate hepatic pathological damages caused by cisplatin. Serum metabolomics indicated AR could regulate the biosynthesis of unsaturated fatty acids, arachidonic acid metabolism, purine metabolism, and fatty acid biosynthesis. In addition, 16S rRNA gene sequencing analysis showed that AR could regulate cisplatin-induced gut microbiota disorder, especially the inflammation-related bacteria (p_Deferribacteres, g_Enterococcus, and g_Alistipes, etc.), and the short chain fatty acids (SCFAs)-producing bacteria (g_Alloprevotella, g_Intestinimoas, and g_Flavonifractor). Moreover, 7 mice (AR-7) showed better liver protective effect than the other 3 mice (AR-3), and their regulatory effect on the gut microbiota and serum metabolites were also different, indicating the presence of inter-individual variability for the liver protective effect of AR.

CONCLUSIONS

This study revealed the protective effect and the potential mechanisms of AR against cisplatin-induced liver injury, and found that inter-individual variability of the liver protective effect of AR was related to the host microbiome and metabolome. These findings provided new insight into the health effect of dietary AR as a functional food for cisplatin-based chemotherapy.

Genetic variants affecting chemical mediated skin immunotoxicity

The skin is an immune-competent organ and this function may be impaired by exposure to chemicals, which may ultimately result in immune-mediated dermal disorders. Interindividual variability to chemical-induced skin immune reactions is associated with intrinsic individual characteristics and their genomes. In the last 30-40 years, several genes influencing susceptibility to skin immune reactions were identified. The aim of this review is to provide information regarding common genetic variations affecting skin immunotoxicity. The polymorphisms selected for this review are related to xenobiotic-metabolizing enzymes (CYPA1 and CYPB1 genes), antioxidant defense (GSTM1, GSTT1, and GSTP1 genes), aryl hydrocarbon receptor signaling pathway (AHR and ARNT genes), skin barrier function transepidermal water loss (FLG, CASP14, and SPINK5 genes), inflammation (TNF, IL10, IL6, IL18, IL31, and TSLP genes), major histocompatibility complex (MHC) and neuroendocrine system peptides (CALCA, TRPV1, ACE genes). These genes present variants associated with skin immune responses and diseases, as well as variants associated with protecting skin immune homeostasis following chemical exposure. The molecular and association studies focusing on these genetic variants may elucidate their functional consequences and contribution in the susceptibility to skin immunotoxicity. Providing information on how genetic variations affect the skin immune system may reduce uncertainties in estimating chemical hazards/risks for human health in the future.

A double-blind randomized controlled trial combining cognitive training (CoRe) and neurostimulation (tDCS) in the early stages of cognitive impairment

BACKGROUND

The prevalence of neurodegenerative diseases is expected to increase over the next years, therefore, new methods able to prevent and delay cognitive decline are needed.

AIMS

To evaluate the effectiveness of a combined treatment protocol associating a computerized cognitive training (CoRe) with anodal transcranial direct current stimulation (tDCS).

METHODS

In this randomized controlled trial, 33 patients in the early stage of cognitive impairment were assigned to the experimental group (CoRE + real tDCS) or control group (CoRE + sham tDCS). In each group, the intervention lasted 3 consecutive weeks (4 sessions/week). A neuropsychological assessment was administered at baseline (T0), post-intervention (T1) and 6-months later (T2).

RESULTS

The CoRE + real tDCS group only improved in working memory and attention/processing speed at both T1 and T2. It reported a stable MMSE score at T2, while the CoRE + sham tDCS group worsened. Age, mood, and T0 MMSE score resulted to play a role in predicting treatment effects.

CONCLUSION

Combined multi-domain interventions may contribute to preventing or delaying disease progression.

TRIAL REGISTRATION

Trial registration number (ClinicalTrials.gov): NCT04118686.

Chronic mild stress paradigm as a rat model of depression: facts, artifacts, and future perspectives

RATIONALE

The chronic mild stress (CMS) paradigm was first described almost 40 years ago and has become a widely used model in the search for antidepressant drugs for major depression disorder (MDD). It has resulted in the publication of almost 1700 studies in rats alone. Under the original CMS procedure, the expression of an anhedonic response, a key symptom of depression, was seen as an essential feature of both the model and a depressive state. The prolonged exposure of rodents to unpredictable/uncontrollable mild stressors leads to a reduction in the intake of palatable liquids, behavioral despair, locomotor inhibition, anxiety-like changes, and vegetative (somatic) abnormalities. Many of the CMS studies do not report these patterns of behaviors, and they often fail to include consistent molecular, neuroanatomical, and physiological phenotypes of CMS-exposed animals.

OBJECTIVES

To critically review the CMS studies in rats so that conceptual and methodological flaws can be avoided in future studies.

RESULTS

Analysis of the literature supports the validity of the CMS model and its impact on the field. However, further improvements could be achieved by (i) the stratification of animals into 'resilient' and 'susceptible' cohorts within the CMS animals, (ii) the use of more refined protocols in the sucrose test to mitigate physiological and physical artifacts, and (iii) the systematic evaluation of the non-specific effects of CMS and implementation of appropriate adjustments within the behavioral tests.

CONCLUSIONS

We propose methodological revisions and the use of more advanced behavioral tests to refine the rat CMS paradigm, which offers a valuable tool for developing new antidepressant medications.

Evidence of cognitive specialization in an insect: proficiency is maintained across elemental and higher-order visual learning but not between sensory modalities in honey bees

Individuals differing in their cognitive abilities and foraging strategies may confer a valuable benefit to their social groups as variability may help responding flexibly in scenarios with different resource availability. Individual learning proficiency may either be absolute or vary with the complexity or the nature of the problem considered. Determining if learning abilities correlate between tasks of different complexity or between sensory modalities has a high interest for research on brain modularity and task-dependent specialisation of neural circuits. The honeybee Apis mellifera constitutes an attractive model to address this question due to its capacity to successfully learn a large range of tasks in various sensory domains. Here we studied whether the performance of individual bees in a simple visual discrimination task (a discrimination between two visual shapes) is stable over time and correlates with their capacity to solve either a higher-order visual task (a conceptual discrimination based on spatial relations between objects) or an elemental olfactory task (a discrimination between two odorants). We found that individual learning proficiency within a given task was maintained over time and that some individuals performed consistently better than others within the visual modality, thus showing consistent aptitude across visual tasks of different complexity. By contrast, performance in the elemental visual-learning task did not predict performance in the equivalent elemental olfactory task. Overall, our results suggest the existence of cognitive specialisation within the hive, which may contribute to ecological social success.

Inter-individual variability in habituation of anxiety-related responses within three mouse inbred strains

Inter-individual variability in behavioral and physiological response has become a well-established phenomenon in animal models of anxiety and other disorders. Such variability is even demonstrated within mouse inbred strains. A recent study showed that adaptive and non-adaptive anxiety phenotypes (measured as habituation and/or sensitization of anxiety responses) may differ within cohorts of 129 mice. This variability was expressed across both anxiety- and activity-related behavioral dimensions. These findings were based however on re-analysis of previously published data. The present study therefore aimed to empirically validate these findings in 129 mice. In addition, we assessed such inter-individuality in two other strains: BALB/c and C57BL/6. Males of three mouse inbred strains (BALB/c, C57BL/6 and 129S2) were behaviorally characterized through repeated exposure to a mild aversive stimulus (modified Hole Board, 4 consecutive trials). Behavioral observations were supplemented with assessment of circulating corticosterone levels. Clustering the individual response trajectories of behavioral and endocrine responses yielded two multidimensional response types of different adaptive value. Interestingly, these response types were displayed by individuals of all three strains. The response types differed significantly on anxiety and activity related behavioral dimensions but not on corticosterone concentrations. This study empirically confirms that adaptive capacities may differ within 129 cohorts. In addition, it extends this inter-individual variability in behavioral profiles to BALB/c and C57BL/6. Whether these two sub-types constitute differential anxiety phenotypes may differ per strain and requires further study.

Impact of inter-individual variability on the estimation of default mode network in temporal concatenation group ICA

Temporal concatenation group ICA (TC-GICA) is a widely used data-driven method to extract common functional brain networks among individuals. TC-GICA concatenates the time series of individual fMRI data and applies dimension reduction and ICA algorithms to decompose the data into group-level components. The default mode network (DMN) estimated using TC-GICA at relatively high model orders (i.e., large numbers of components) is split into multiple components. The split DMNs are topographically different from those estimated using other methods (e.g., seed-based correlation, clustering, graph theoretical analysis, and other ICA methods like gRAICAR and IVA-GL) and are inconsistent with the existing knowledge of DMN. We hypothesize that the "DMN-splitting'' phenomenon reflects the impact of inter-individual variability in data, which is propagated into the ICA decomposition via the data-concatenation step of TC-GICA. By systematically manipulating the amount of variability involved in the temporal concatenation in both simulated and several realistic datasets, we observed that as more variability was involved, the estimated DMN became less similar to the averaged functional connectivity (FC) pattern obtained using seed-based correlation analysis. The performance of the DMN estimation in TC-GICA also exhibited remarkable dependence on the model order settings. Further analyses revealed that the "DMN-splitting" in TC-GICA could be reproduced when involving large variability in the data-concatenation and performing ICA at high model orders. These results were replicated across multiple datasets and various software implementations. When applying ICA approaches that avoid temporal concatenation, such as gRAICAR and IVA-GL, to the same datasets, the estimated group-level DMN was more consistent with the seed-based FC pattern and was more robust to various model order settings. This study calls for caution when applying TC-GICA to datasets expected to have large inter-individual variability, such as pooling different experimental groups of subjects.

Measuring sleep regularity: Theoretical properties and practical usage of existing metrics

STUDY OBJECTIVES

Sleep regularity predicts many health-related outcomes. Currently, however, there is no systematic approach to measuring sleep regularity. Traditionally, metrics have assessed deviations in sleep patterns from an individual's average. Traditional metrics include intra-individual standard deviation (StDev), Interdaily Stability (IS), and Social Jet Lag (SJL). Two metrics were recently proposed that instead measure variability between consecutive days: Composite Phase Deviation (CPD) and Sleep Regularity Index (SRI). Using large-scale simulations, we investigated the theoretical properties of these five metrics.

METHODS

Multiple sleep-wake patterns were systematically simulated, including variability in daily sleep timing and/or duration. Average estimates and 95% confidence intervals were calculated for six scenarios that affect measurement of sleep regularity: 'scrambling' the order of days; daily vs. weekly variation; naps; awakenings; 'all-nighters'; and length of study.

RESULTS

SJL measured weekly but not daily changes. Scrambling did not affect StDev or IS, but did affect CPD and SRI; these metrics, therefore, measure sleep regularity on multi-day and day-to-day timescales, respectively. StDev and CPD did not capture sleep fragmentation. IS and SRI behaved similarly in response to naps and awakenings but differed markedly for all-nighters. StDev and IS required over a week of sleep-wake data for unbiased estimates, whereas CPD and SRI required larger sample sizes to detect group differences.

CONCLUSIONS

Deciding which sleep regularity metric is most appropriate for a given study depends on a combination of the type of data gathered, the study length and sample size, and which aspects of sleep regularity are most pertinent to the research question.

Quantitative assessment of inter-individual variability in fMRI-based human brain atlas

Background

Inter-individual variability is an inherent and ineradicable feature of group-level brain atlases that undermines their reliability for clinical and other applications. To date, there have been no reports quantifying inter-individual variability in brain atlases.

Methods

In the present study, we compared inter-individual variability in nine brain atlases by task-based functional magnetic resonance imaging (MRI) mapping of motor and temporal lobe language regions in both cerebral hemispheres. We analyzed complete motor and language task-based fMRI and T1 data for 893 young, healthy subjects in the Human Connectome Project database. Euclidean distances (EDs) between hotspots in specific brain regions were calculated from task-based fMRI and brain atlas data. General linear model parameters were used to investigate the influence of different brain atlases on signal extraction. Finally, the inter-individual variability of ED and extracted signals and interdependence of relevant indicators were statistically evaluated.

Results

We found that inter-individual variability of ED varied across the nine brain atlases (P<0.0001 for motor regions and P<0.0001 for language regions). There was no correlation between parcel number and inter-individual variability in left to right (LtoR; P=0.7959 for motor regions and P=0.2002 for language regions) and right to left (RtoL; P=0.7654 for motor regions and P=0.3544 for language regions) ED; however, LtoR (P≤0.0001) and RtoL (P≤0.0001) inter-individual variability differed according to brain region: the LtoR (P=0.0008) and RtoL (P=0.0004) inter-individual variability was greater for the right hand than for the left hand, the LtoR (P=0.0019) and RtoL (P=0.0179) inter-individual variability was greater for the right language than for the left language, but there was no such difference between the right foot and left foot (LtoR, P=0.2469 and RtoL, P=0.6140). Inter-individual variability in one motor region was positively correlated with mean values in the other three motor regions (left hand, P=0.0145; left foot, P=0.0103; right hand, P=0.1318; right foot, P=0.3785). Inter-individual variability in language region was positively correlated with mean values in the four motor regions (left language, P=0.0422; right language, P=0.0514). Signal extraction for LtoR (P<0.0001) and RtoL (P<0.0001) varied across the nine brain atlases, which also showed differences in inter-individual variability.

Conclusions

These results underscore the importance of quantitatively assessing the inter-individual variability of a brain atlas prior to use, and demonstrate that mapping motor regions by task-based fMRI is an effective method for quantitatively assessing the inter-individual variability in a brain atlas.

The impact of individual electrical fields and anatomical factors on the neurophysiological outcomes of tDCS: A TMS-MEP and MRI study

BACKGROUND

Transcranial direct current stimulation (tDCS), a neuromodulatory non-invasive brain stimulation technique, has shown promising results in basic and clinical studies. The known interindividual variability of the effects, however, limits the efficacy of the technique. Recently we reported neurophysiological effects of tDCS applied over the primary motor cortex at the group level, based on data from twenty-nine participants who received 15min of either sham, 0.5, 1.0, 1.5 or 2.0 mA anodal, or cathodal tDCS. The neurophysiological effects were evaluated via changes in: 1) transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEP), and 2) cerebral blood flow (CBF) measured by functional magnetic resonance imaging (MRI) via arterial spin labeling (ASL). At the group level, dose-dependent effects of the intervention were obtained, which however displayed interindividual variability.

METHOD

In the present study, we investigated the cause of the observed inter-individual variability. To this end, for each participant, a MRI-based realistic head model was designed to 1) calculate anatomical factors and 2) simulate the tDCS- and TMS-induced electrical fields (EFs). We first investigated at the regional level which individual anatomical factors explained the simulated EFs (magnitude and normal component). Then, we explored which specific anatomical and/or EF factors predicted the neurophysiological outcomes of tDCS.

RESULTS

The results highlight a significant negative correlation between regional electrode-to-cortex distance (rECD) as well as regional CSF (rCSF) thickness, and the individual EF characteristics. In addition, while both rCSF thickness and rECD anticorrelated with tDCS-induced physiological changes, EFs positively correlated with the effects.

CONCLUSION

These results provide novel insights into the dependency of the neuromodulatory effects of tDCS on individual physical factors.

Gross motor development of Thai healthy full-term infants aged from birth to 14 months using the Alberta Infant Motor Scale: Inter individual variability

BACKGROUND

The gross motor percentiles of the Alberta Infants Motor Scale (AIMS) have been commonly referenced in research. Cross-cultural assessment of gross motor development during the first year of life is suggested as diverse child-rearing practices can cause inter-variability. The main aim of this study was to develop an AIMS percentile curve for typically developing home-raised infants in the northeastern part of Thailand. The AIMS scores of these infants were also compared with the standard Canadian norms.

METHODS

The gross motor development of 574 full-term infants aged 15 days to 14 months was assessed using the Thai version of the AIMS. Percentile curves of their gross motor ability were developed. The Thai infants' mean AIMS scores were compared with the Canadian norm using the one-sample t-test.

RESULTS

The percentile curve of gross motor development of healthy Thai infants showed that mean AIMS scores increased with age. Large inter-variability was present from the 7th to 10th months. The mean AIMS scores of Thai infants were significantly lower than the standard Canadian means during the first three months (P < 0.05), but significantly higher in three age groups: 7-<8 months, 11-<12 months, and 13-14 months.

CONCLUSION

The developed percentile curve of gross motor development is applicable for infants from the same demographic and environmental context. According to the study, infants from diverse cultures display a natural inter-variability in gross motor development between the 7th and 10th months.

Inter-phenotypic differences in CYP2C9 and CYP2C19 metabolism: Bayesian meta-regression of human population variability in kinetics and application in chemical risk assessment

Quantifying variability in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. In this context, genetic polymorphisms in cytochromes P450 (CYPs) drive inter-phenotypic differences and may result in reduction or increase in metabolism of drugs or other xenobiotics. Here, an extensive literature search was performed to identify PK data for probe substrates of the human polymorphic isoforms CYP2C9 and CYP2C19. Relevant data from 158 publications were extracted for markers of chronic exposure (clearance and area under the plasma concentration-time curve) and analysed using a Bayesian meta-regression model. Enzyme function (EF), driven by inter-phenotypic differences across a range of allozymes present in extensive and poor metabolisers (EMs and PMs), and fraction metabolised (Fm), were identified as exhibiting the highest impact on the metabolism. The Bayesian meta-regression model provided good predictions for such inter-phenotypic differences. Integration of population distributions for inter-phenotypic differences and estimates for EF and Fm allowed the derivation of CYP2C9- and CYP2C19-related UFs which ranged from 2.7 to 12.7, and were above the default factor for human variability in TK (3.16) for PMs and major substrates (Fm >60%). These results provide population distributions and pathway-related UFs as conservative in silico options to integrate variability in CYP2C9 and CYP2C19 metabolism using in vitro kinetic evidence and in the absence of human data. The future development of quantitative extrapolation models is discussed with particular attention to integrating human in vitro and in vivo PK or TK data with pathway-related variability for chemical risk assessment.

Human variability in glutathione-S-transferase activities, tissue distribution and major polymorphic variants: Meta-analysis and implication for chemical risk assessment

The input into the QIVIVE and Physiologically-Based kinetic and dynamic models of drug metabolising enzymes performance and their inter-individual differences significantly improve the modelling performance, supporting the development and integration of alternative approaches to animal testing. Bayesian meta-analyses allow generating and integrating statistical distributions with human in vitro metabolism data for quantitative in vitro-in vivo extrapolation. Such data are lacking on glutathione-S-transferases (GSTs). This paper reports for the first time results on the human variability of GST activities in healthy individuals, their tissue localisation and the frequencies of their major polymorphic variants by means of extensive literature search, data collection, data base creation and meta-analysis. A limited number of papers focussed on in vivo GST inter-individual differences in humans. Ex-vivo total GST activity without discriminating amongst isozymes is generally reported, resulting in a high inter-individual variability. The highest levels of cytosolic GSTs in humans are measured in the kidney, liver, adrenal glands and blood. The frequencies of GST polymorphisms for cytosolic isozymes in populations of different geographical ancestry were also presented. Bayesian meta-analyses to derive GST-related uncertainty factors provided uncertain estimates, due to the limited database. Considering the relevance of GST activities and their pivotal role in cellular adaptive response mechanisms to chemical stressors, further studies are needed to identify GST probe substrates for specific isozymes and quantify inter-individual differences.

Systematic dose-response of environmental epidemiologic studies: Dose and response pre-analysis

Meta-analysis approaches can be used to assess the human risks due to exposure to environmental chemicals when there are numerous high-quality epidemiologic studies of priority outcomes in a database. However, methodological issues related to how different studies report effect measures and incorporate exposure into their analyses arise that complicate the pooled analysis of multiple studies. As such, there are "pre-analysis" steps that are often necessary to prepare summary data reported in epidemiologic studies for dose-response analysis. This paper uses epidemiologic studies of arsenic-induced health effects as a case example and addresses the issues surrounding the estimation of mean doses from censored dose- or exposure-intervals reported in the literature (e.g., estimation of mean doses from high exposures that are only reported as an open-ended interval), calculation of a common dose metric for use in a dose-response meta-analysis (one that takes into consideration inter-individual variability), and calculation of response "effective counts" that inherently account for confounders. The methods herein may be generalizable to 1) the analysis of other environmental contaminants with a suitable database of epidemiologic studies, and 2) any meta-analytic approach used to pool information across studies. A second companion paper detailing the use of "pre-analyzed" data in a hierarchical Bayesian dose-response model and techniques for extrapolating risks to target populations follows.

Imprinting statistically sound conclusions for gut microbiota in comparative animal studies: A case study with diet and teleost fishes

Despite the technical progress in high-throughput sequencing technologies, defining the sample size which is capable of yielding representative inferences in metabarcoding analysis still remains debatable. The present study addresses the influence of individual variability in assessing dietary effects on fish gut microbiota parameters and estimates the biological sample size that is sufficient to imprint a statistically secure outcome. European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata) were fed three alternative animal protein diets and a fishmeal control diet. Gut microbiota data from 12 individuals per diet, derived from Illumina sequencing of the V3-V4 region of the 16S rRNA gene, were randomized in all possible combinations of n-1 individuals. Results in this study showcased that increasing the sample size can limit the prevalence of individuals with high microbial load on the outcome and can ensure the statistical confidence required for an accurate validation of dietary-induced microbe shifts. Inter-individual variability was evident in the four dietary treatments where consequently misleading inferences arose from insufficient biological replication. These findings have critical implications for the design of future metabarcoding studies and highlight the urgency in selecting an adequate sample size able to safely elucidate the dietary effects on fish gut microbial communities.

Gut microbiota modulation with long-chain corn bran arabinoxylan in adults with overweight and obesity is linked to an individualized temporal increase in fecal propionate

BACKGROUND

Variability in the health effects of dietary fiber might arise from inter-individual differences in the gut microbiota's ability to ferment these substrates into beneficial metabolites. Our understanding of what drives this individuality is vastly incomplete and will require an ecological perspective as microbiomes function as complex inter-connected communities. Here, we performed a parallel two-arm, exploratory randomized controlled trial in 31 adults with overweight and class-I obesity to characterize the effects of long-chain, complex arabinoxylan (n = 15) at high supplementation doses (female: 25 g/day; male: 35 g/day) on gut microbiota composition and short-chain fatty acid production as compared to microcrystalline cellulose (n = 16, non-fermentable control), and integrated the findings using an ecological framework.

RESULTS

Arabinoxylan resulted in a global shift in fecal bacterial community composition, reduced α-diversity, and the promotion of specific taxa, including operational taxonomic units related to Bifidobacterium longum, Blautia obeum, and Prevotella copri. Arabinoxylan further increased fecal propionate concentrations (p = 0.012, Friedman's test), an effect that showed two distinct groupings of temporal responses in participants. The two groups showed differences in compositional shifts of the microbiota (p ≤ 0.025, PERMANOVA), and multiple linear regression (MLR) analyses revealed that the propionate response was predictable through shifts and, to a lesser degree, baseline composition of the microbiota. Principal components (PCs) derived from community data were better predictors in MLR models as compared to single taxa, indicating that arabinoxylan fermentation is the result of multi-species interactions within microbiomes.

CONCLUSION

This study showed that long-chain arabinoxylan modulates both microbiota composition and the output of health-relevant SCFAs, providing information for a more targeted application of this fiber. Variation in propionate production was linked to both compositional shifts and baseline composition, with PCs derived from shifts of the global microbial community showing the strongest associations. These findings constitute a proof-of-concept for the merit of an ecological framework that considers features of the wider gut microbial community for the prediction of metabolic outcomes of dietary fiber fermentation. This provides a basis to personalize the use of dietary fiber in nutritional application and to stratify human populations by relevant gut microbiota features to account for the inconsistent health effects in human intervention studies.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT02322112 , registered on July 3, 2015. Video Abstract.

Exploring the effects of Transcranial Direct Current Stimulation over the prefrontal cortex on working memory: A cluster analysis approach

BACKGROUND

The interest in the use of anodal transcranial direct current stimulation (tDCS) for the enhancement of cognitive functioning has increased significantly in recent years. However, the efficacy of this technique remains to be established.

OBJECTIVE

The current study explored the effects of anodal vs. sham tDCS over the left dorsolateral prefrontal cortex (DLPFC) during the performance of the digit span backwards task.

METHODS

30 healthy participants received 'offline' anodal tDCS (1.5 mA, 15 min) to the left DLPFC in an intra-individual, cross-over, sham-controlled experimental design. Memory span performance was assessed before (baseline), immediately after tDCS administration (T1) and 10 min post-T1 (T2). We applied cluster analysis in order to characterize individual responses to tDCS, and in order to identify naturally occurring subgroups that may be present.

RESULTS

Analysis of all the subjects showed that anodal tDCS failed to improve memory span performance. Cluster analysis revealed the presence of a subgroup of 'responders' that significantly improved their performance after anodal (vs. sham) tDCS in T1 (47%) and T2 (46%). However, there was no significant improvement in performance after anodal tDCS compared to the best baseline performance.

CONCLUSION

Our findings suggest that tDCS does not improve memory span performance and highlights the need for better ways to optimize methodological approaches in order to account for inter-individual variability and accurately assess the evidential value of tDCS-linked cognitive outcomes.

Systematic review of artesunate pharmacokinetics: Implication for treatment of resistant malaria

BACKGROUND

Artesunate (ART) is an artemisinin derivative used as monotherapy for the treatment of severe malaria and in combination with a partner drug for non-severe malaria. Resistance of malaria parasites to artemisinins have emerged in Southeast Asia. Adjustment of drug regimen may be an option to prevent therapeutic failures considering the relative favourable safety profile of ART high doses.

METHODS

For that purpose, a systematic review was done using PubMed, Scopus and Web of Science databases. All studies on ART and DHA pharmacokinetic post-administration of artesunate in human patients or volunteers were included. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist 2009 was used.

FINDINGS

Fifty studies exploring oral, intravenous, rectal, and intramuscular route (1470 persons, volunteers and patients) were included. Correlations between artesunate doses and C_max or AUC_0-∞ of dihydroartemisinin (DHA) and DHA+ART were evaluated. This correlation was good (R²>0.9) using intravenous (IV) route. DHA and ART+DHA average concentrations (Cav) were well above estimated in vivo half-maximal effective concentration (EC₅₀) for intravenous route, but this was not the case for oral route.

INTERPRETATION

The favorable Cav/EC₅₀ ratio for IV route provides evidence that IV ART will remain efficient even in the case of increased resistance level, whereas for the oral route, a two-fold increase in EC₅₀ may lead to therapeutic failures, thus providing a rationale for oral dose escalation. Considering the inter-individual variability of ART pharmacokinetic, Therapeutic Drug Monitoring through antimalarial stewardship activities is needed to optimize drug exposure and avoid resistance development.

Variation of human salivary alpha-amylase proteoforms in three stimulation models

OBJECTIVES

To evaluate the sAA proteoforms' expression during different stimulation situations.

MATERIALS AND METHODS

This study evaluated the salivary alpha-amylase (sAA) proteoforms' behavior by western blot (WB) analysis and high-resolution mass spectrometry (LC-MS/MS) in different situations that produce increases in sAA activity. For this purpose, six healthy women with a similar body mass index, age, and fit, underwent different sAA stimulation tests, such as acetic acid stimulation, psychological stress using the standardized Trier social stress test, and physical effort using the Cooper treadmill test.

RESULTS

The three models showed an increase in sAA activity. The WB demonstrated seven common bands observed in the six women (band one at 59 kDa, two at 56 kDa, three at 48 kDa, four at 45 kDa, five at 41 kDa, six at 36 kDa, and seven at 14 kDa), in which sAA protein was identified. The individual WB analysis showed that band two, which corresponded to the native non-glycosylated sAA proteoform, had a higher increase after the three sAA stimulation inducers, and this band was also the only proteoform correlated with sAA activity (r = 0.56, P = 0.001). In addition, when the label-free quantification analysis was performed, the different proteoforms showed different responses depending on the type of stimulation.

CONCLUSIONS

This preliminary study showed that the diverse sAA proteoforms' expression depends on the different stimulation models.

CLINICAL RELEVANCE

This study opens new perspectives and challenges for the use of the different alpha-amylase proteoforms as possible biomarkers in addition to the sAA activity.

Identifying inter-individual differences in pain threshold using brain connectome: a test-retest reproducible study

Individuals are unique in terms of brain and behavior. Some are very sensitive to pain, while others have a high tolerance. However, how inter-individual intrinsic differences in the brain are related to pain is unknown. Here, we performed longitudinal test-retest analyses to investigate pain threshold variability among individuals using a resting-state fMRI brain connectome. Twenty-four healthy subjects who received four MRI sessions separated by at least 7 days were included in the data analysis. Subjects' pain thresholds were measured using two modalities of experimental pain (heat and pressure) on two different locations (heat pain: leg and arm; pressure pain: leg and thumbnail). Behavioral results showed strong inter-individual variability and strong within-individual stability in pain threshold. Resting state fMRI data analyses showed that functional connectivity profiles can accurately identify subjects across four sessions, indicating that an individual's connectivity profile may be intrinsic and unique. By using multivariate pattern analyses, we found that connectivity profiles could be used to predict an individual's pain threshold at both within-session and between-session levels, with the most predictive contribution from medial-frontal and frontal-parietal networks. These results demonstrate the potential of using a resting-state fMRI brain connectome to build a 'neural trait' for characterizing an individual's pain-related behavior, and such a 'neural trait' may eventually be used to personalize clinical assessments.

Modelling of oscillatory cortisol response in horses using a Bayesian population approach for evaluation of dexamethasone suppression test protocols

Cortisol is a steroid hormone relevant to immune function in horses and other species and shows a circadian rhythm. The glucocorticoid dexamethasone suppresses cortisol in horses. Pituitary pars intermedia dysfunction (PPID) is a disease in which the cortisol suppression mechanism through dexamethasone is challenged. Overnight dexamethasone suppression test (DST) protocols are used to test the functioning of this mechanism and to establish a diagnosis for PPID. However, existing DST protocols have been recognized to perform poorly in previous experimental studies, often indicating presence of PPID in healthy horses. This study uses a pharmacokinetic/pharmacodynamic (PK/PD) modelling approach to analyse the oscillatory cortisol response and its interaction with dexamethasone. Two existing DST protocols were then scrutinized using model simulations with particular focus on their ability to avoid false positive outcomes. Using a Bayesian population approach allowed for quantification of uncertainty and enabled predictions for a broader population of horses than the underlying sample. Dose selection and sampling time point were both determined to have large influence on the number of false positives. Advice on pitfalls in test protocols and directions for possible improvement of DST protocols were given. The presented methodology is also easily extended to other clinical test protocols.

Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness

Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performance of machine learning models (Artificial Neural Networks: ANNs) by training a model with a group of drivers and then adapting it to a new individual. Twenty-one participants drove a car simulator for 110 min in a monotonous environment. We measured physiological and behavioral indicators and recorded driving behavior. These measurements, in addition to driving time and personal information, served as the ANN inputs. Two ANN-based models were used, one to detect the level of drowsiness every minute, and the other to predict, every minute, how long it would take the driver to reach a specific drowsiness level (moderately drowsy). The ANNs were trained with 20 participants and subsequently adapted using the earliest part of the data recorded from a 21st participant. Then the adapted ANNs were tested with the remaining data from this 21st participant. The same procedure was run for all 21 participants. Varying amounts of data were used to adapt the ANNs, from 1 to 30 min, Model performance was enhanced for each participant. The overall drowsiness monitoring performance of the models was enhanced by roughly 40% for prediction and 80% for detection.

Can intrinsic foraging efficiency explain dominance status? A test with functional response experiments

The functional response describes how food abundance affects the intake rate of foraging individuals, and as such, it can influence a wide range of ecological processes. In social species, dominance status can affect the functional response of competing individuals, but studies conducted in an interference-free context have provided contrasting results on the extent of between-individual variability in functional response. We tested the prediction that individuals intrinsically differ in their functional response, and that these differences could predict body weight and dominance status in social species. We used goats as a model species and performed foraging experiments to assess the functional response of these goats in an interference-free context. Our results show that some individuals are consistently better foragers than others, and these individuals were more likely to be heavier and dominant. Parameters of the functional response are, however, more strongly associated with dominance status than with body weight. We conclude that interference while foraging is not needed to explain body weight differences between dominant and subordinate individuals. We suggest that these differences can emerge from intrinsic differences in foraging efficiency between individuals, which could also allow better foragers to demonstrate greater tenacity during agonistic interactions.

Inter-individual Variability in Activity of the Major Drug Metabolizing Enzymes in Liver Homogenates of 20 Individuals

BACKGROUND

Inter-individual variability in hepatic drug metabolizing enzyme (DME) activity is a major contributor to heterogeneity in drug clearance and safety. Accurate data on expression levels and activities of DMEs is an important prerequisite for in vitro-in vivo extrapolation and in silico based predictions. Characterization and assessment of inter-correlations of the major DMEs cytochrome P450s (CYPs) and UDP-glucuronosyltransferases (UGTs) have been extensively documented, but simultaneous quantification including other major DMEs has been lacking.

OBJECTIVE

Assessment of inter-donor variability and inter-correlations of CYPs, UGTs, sulfotransferases (SULTs), glutathione S-transferases (GSTs), NAD(P)H:quinone oxidoreductase 1 (NQO1) and NRH: quinone oxidoreductase 2 (NQO2) in a set of 20 individual liver homogenates.

METHOD

The main drug metabolizing isoforms of CYP and UGT have been reaction phenotype in individual liver microsomes and NQO1, NQO2, GSTT1 and GSTT2 in corresponding cytosol. In addition, we assessed overall SULT activity in liver cytosol using acetaminophen and 7-hydroxycoumarin as non-selective substrates and cytosolic GST activity using the non-selective substrate 1-chloro-2,4-dinitrobenzene (CDNB). Expression of GST isoforms was also assessed.

RESULTS AND CONCLUSION

While hepatic NQO1 activity was highly variable, NQO2 activity was more conserved. In addition, we found that of the hepatic GST isoforms, the variation in GSTM3 levels, which is poorly studied, was highest. The majority of significant correlations were found amongst CYP and UGT enzyme activities. The dataset presented provides the absolute quantification of the largest number of hepatic DME activities so far and constitute an essential resource for in silico toxicokinetic and metabolic modelling studies.

Quantitative characterization of UDP-glucuronosyltransferase 2B17 in human liver and intestine and its role in testosterone first-pass metabolism

Protein abundance and activity of UGT2B17, a highly variable drug- and androgen-metabolizing enzyme, were quantified in microsomes, S9 fractions, and primary cells isolated from human liver and intestine by validated LC-MS/MS methods. UGT2B17 protein abundance showed >160-fold variation (mean ± SD, 1.7 ± 2.7 pmol/mg microsomal protein) in adult human liver microsomes (n = 26) and significant correlation (r2 = 0.77, p < 0.001) with testosterone glucuronide (TG) formation. Primary role of UGT2B17 in TG formation compared to UGT2B15 was confirmed by performing activity assays in UGT2B17 gene deletion samples and with a selective UGT2B17 inhibitor, imatinib. Human intestinal microsomes isolated from small intestine (n = 6) showed on average significantly higher protein abundance (7.4 ± 6.6 pmol/mg microsomal protein, p = 0.016) compared to liver microsomes, with an increasing trend towards distal segments of the gastrointestinal (GI) tract. Commercially available pooled microsomes and S9 fractions confirmed greater abundance and activity of UGT2B17 in intestinal fractions compared to liver fractions. To further investigate the quantitative role of UGT2B17 in testosterone metabolism in whole cell system, a targeted metabolomics study was performed in hepatocytes (n = 5) and enterocytes (n = 16). TG was the second most abundant metabolite after androstenedione in both cell systems. Reasonable correlation between UGT2B17 abundance and activity were observed in enterocytes (r2 = 0.69, p = 0.003), but not in hepatocytes. These observational and mechanistic data will be useful in developing physiologically-based pharmacokinetic (PBPK) models for predicting highly-variable first-pass metabolism of testosterone and other UGT2B17 substrates.

Inter-individual and inter-organ variability in the bioactivation of paracetamol by human liver and kidney tissues

Paracetamol (PAR) overdose is associated with massive hepatic injury; it may induce kidney toxicity as well. It is essential to measure organ-specific activities of related CYPs for evaluating the overdose cases. Available HPLC-based methods require high amounts of tissue samples. In order to develop liquid chromatography mass spectrometry (LC-MS)-based methods to process small amounts of human tissues, liver and kidney samples were obtained. Individual microsomes were prepared and incubated with PAR (for quantifying bioactivation), with nifedipine (for measuring CYP3A4 activity) and with p-nitrophenol (for measuring CYP2E1 activity). The small amount of tissue microsomes was sufficient to measure both the formation of NAPQI and the activities of CYP enzymes. Although the sample size in group was relatively low, both NAPQI formation and activity of CYP2E1 were significantly higher in males compared to females in kidney. Considerable variations in the metabolic capacity of individuals were observed for both organs.

Beyond the mean: A comparison of trace- and macroelement correlation profiles of two lacustrine populations of the crayfish Procambarus clarkii

In invertebrate biomonitors of chemical pollution, emphasis has been generally given to mean accumulation patterns and how they reflect varying environmental levels of contamination. Intra-population variability, and how it relates with individual phenotypic traits, has received less attention. Here, a set of analytes including trace elements (B, Ba, Cd, Cr, Cu, Fe, Li, Mn, Ni, Pb, Sr, V, and Zn), macroelements (C, Ca, K, Mg, N, Na), and carbon and nitrogen stable isotopes (δ¹³C and δ¹⁵N) was measured in two populations of the crayfish Procambarus clarkii from Lake Trasimeno and Lake Bolsena (Central Italy). The influence of location, sex, body size, and condition factor was assessed; in addition, the analyte correlation profiles of the two populations were compared to verify their congruence. In general, significant inter-lake differences were observed in the concentration of both trace- and macroelements in crayfish tissues, generally mirroring the local chemistry of water and of benthic non-living matrices (sediment and plant detritus). Crayfish CN isotopic signatures excluded the occurrence of inter-lake variations in their omnivorous trophic habits. Correlation profiles varied considerably between the two populations in the nature and strength of bivariate relationships. However, Mantel tests and procrustean analyses indicated a general, significant congruence; C, N, and, to a lesser extent K, Li, Ni, Pb, and δ¹³C showed the highest procrustean residuals, suggesting that their associations with other analytes may be partially influenced by inter-population differences in growing phases. Our study indicates that the local geochemistry of the lacustrine environment influences the elemental fingerprint of Procambarus clarkii; the considerable inter-individual variability in the concentration of analytes, however, does not significantly reflect on their association, thus corroborating its effectiveness as an indicator species.

Histone H4 acetylation regulates behavioral inter-individual variability in zebrafish

BACKGROUND

Animals can show very different behaviors even in isogenic populations, but the underlying mechanisms to generate this variability remain elusive. We use the zebrafish (Danio rerio) as a model to test the influence of histone modifications on behavior.

RESULTS

We find that laboratory and isogenic zebrafish larvae show consistent individual behaviors when swimming freely in identical wells or in reaction to stimuli. This behavioral inter-individual variability is reduced when we impair the histone deacetylation pathway. Individuals with high levels of histone H4 acetylation, and specifically H4K12, behave similarly to the average of the population, but those with low levels deviate from it. More precisely, we find a set of genomic regions whose histone H4 acetylation is reduced with the distance between the individual and the average population behavior. We find evidence that this modulation depends on a complex of Yin-yang 1 (YY1) and histone deacetylase 1 (HDAC1) that binds to and deacetylates these regions. These changes are not only maintained at the transcriptional level but also amplified, as most target regions are located near genes encoding transcription factors.

CONCLUSIONS

We suggest that stochasticity in the histone deacetylation pathway participates in the generation of genetic-independent behavioral inter-individual variability.

The urinary phenolic acid profile varies between younger and older adults after a polyphenol-rich meal despite limited differences in in vitro colonic catabolism

PURPOSE

To investigate whether age influences colonic polyphenol metabolism.

METHODS

Healthy participants, younger (n = 8; 23-43 years) and older (n = 13; 51-76 years), followed a 3-day low-polyphenol diet (LPD) and a 3-day high-polyphenol diet (HPD). Urinary phenolic acids (PA), short chain fatty acids (SCFA), pH and gas were monitored, alongside selected colonic bacteria. Human faecal in vitro fermentations of rutin with or without raftiline were used to evaluate the gut microbiota capacity in a subset of both groups.

RESULTS

Total urinary PA were higher in the older group after HPD compared to the younger group (1.5-fold; p = 0.04), with no difference between groups in terms of a change between diets (Δ high-low diet). While 17 PA were detected in all younger participants after HPD, a narrower range (n = 8 to 16 PA) was detected in most (n = 9/13) older participants, with lower level of benzoic acid (19-fold; p = 0.03), vanillic acid (4.5-fold; p = 0.04) but higher hippuric acid (2.7-fold; p = 0.03). Faecal SCFA concentration did not change after HPD within group, with similar differential excretion (Δ high-low diet) between groups. There were no differences between groups for faecal pH, total, faecal bacteria including Flavonifractor plautii, bifidobacteria, and bacteroides. In human in vitro faecal fermentations, seven PAs were detected in both groups after 24 h of rutin fermentation, with no quantitative and modest qualitative differences between groups. Total SCFA in faecal fermentation did not differ between groups, except for butyric acid (twofold higher in the older group; p = 0.009) when rutin was fermented with raftiline over 24 h.

CONCLUSIONS

Urinary phenolic acids were less diverse in older participants despite limited difference in functional capacity of in vitro faecal fermentations.

Enhancing the effectiveness of human-robot teaming with a closed-loop system

With technological developments in robotics and their increasing deployment, human-robot teams are set to be a mainstay in the future. To develop robots that possess teaming capabilities, such as being able to communicate implicitly, the present study implemented a closed-loop system. This system enabled the robot to provide adaptive aid without the need for explicit commands from the human teammate, through the use of multiple physiological workload measures. Such measures of workload vary in sensitivity and there is large inter-individual variability in physiological responses to imposed taskload. Workload models enacted via closed-loop system should accommodate such individual variability. The present research investigated the effects of the adaptive robot aid vs. imposed aid on performance and workload. Results showed that adaptive robot aid driven by an individualized workload model for physiological response resulted in greater improvements in performance compared to aid that was simply imposed by the system.

Thrombodynamics, a new global coagulation test: Measurement of heparin efficiency

The actual coagulation status may be reliably measured using only highly sensitive global functional tests; however, they are not numerous and all of them have disadvantages. Thrombodynamics (TD), a novel global coagulation test, is sensitive to hypo- and hypercoagulable states. The main properties of this test were investigated, and its capabilities for hemostasis analysis were verified through pharmacodynamic monitoring of the most widely used anticoagulants, heparins. The anticoagulant effects in the plasma of donors (n = 20) and patients after hip replacement (n = 20) spiked with unfractionated heparin or enoxaparin were measured in vitro to eliminate the influence of pharmacokinetic factors. Sensitivity for heparins was compared for activated partial thromboplastin time, thrombin generation tests and TD. TD was shown to reliably characterize the pharmacodynamics of any heparin in the entire range of its prophylactic and therapeutic concentrations. Inter-individual variability for the anticoagulant action of heparins was also calculated using the TD data. This variability did not differ between the investigated groups and did not exceed 12% and 20% for the stationary clot growth rate in the presence of unfractionated heparin and enoxaparin, respectively. That finding was in accordance with the values determined earlier using the thrombin generation test. The study results showed that TD has advantages over the other global methods of coagulation analysis. These advantages are good standardization, high reproducibility, independence of the parameter values from patient age and gender, and a narrower parameter distribution in a normal population. These results indicate that TD is a promising universal assessment method that improves the quality of hemostasis analysis because it more reliably detects deviations from the parameters' reference values.

Ionized and total serum magnesium in hemodialysis: predictors and variability. A longitudinal cross-sectional study

Background

Ionized Magnesium (ion-Mg) represents the active biological fraction of the serum magnesium content. The assessment of total serum Mg (tot-Mg) might not accurately identify patients with hypo-or hyper-magnesaemie. In hemodialysis, serum tot-Mg levels in the upper part of the distribution, have been associated with reduced mortality and fewer vascular calcifications; thus, resulting in the tendency to increase the Mg concentration in the dialysate, traditionally set at 0.5 mmol/L.

Methods

Single-center study in chronic hemodialysis patients, designed in two phases, cross-sectional and longitudinal, aimed to investigate: (1) the sensitivity for pathological values of ion-Mg compared to tot-Mg (2) the predictors of ion-Mg developing ad hoc equations; (3) the inter- and intra-individual variabilities of ion-Mg; and (4) the risk factors for hypermagnesemia. Tot-Mg, ion-Mg, and covariates of 42 hemodialysis sessions, in 42 patients during the cross-sectional phase and of 270 sessions in 27 patients in the longitudinal one were analysed.

Results

Ion-Mg significantly correlates with tot-Mg: β = 0.52; r = 0.88, p < 0.001. Multiple linear regressions in normo- and hypo-albuminemic patients gave the following results: ion-Mg = tot-Mg/2-K⁺/50 + Ca²⁺/5-HCO³⁻/100 and ion-Mg = tot-Mg/2 + albumin/100. Ion-Mg showed a high temporal variability in the longitudinal phase (between months p < 0.001; winter vs. summer, p < 0.027). A high intra-individual variability was also found: coefficient of variation 0.116. Comparing patients with high and low intra-individual variability, we found: age 67 vs. 77 years; p < 0.001; urea 26.3 ± 0.5 vs. 21.2 ± 0.4 mmol/L, p < 0.001; nPCR 0.92 ± 0.1 vs. 0.77 ± 0.1 g/kg day, p < 0.001; PTH 46.3 ± 4 vs. 28.5 ± 3 pmol/L, p < 0.001.

Conclusions

Ion-Mg can be useful in unmasking unrecognized hyper- and hypo-magnesemic and false hyper-magnesemic patients. Ion-Mg is characterized by high intra- and inter-individual variabilities particularly in younger women and those with better nutrition. Patients with greater variability could potentially be at risk if exposed to higher concentrations of magnesium in the dialysate. An interventional study, with controlled increase of magnesium concentrations in the dialysate has been planned.

Ancestors' dietary patterns and environments could drive positive selection in genes involved in micronutrient metabolism-the case of cofactor transporters

Background

During evolution, humans colonized different ecological niches and adopted a variety of subsistence strategies that gave rise to diverse selective pressures acting across the genome. Environmentally induced selection of vitamin, mineral, or other cofactor transporters could influence micronutrient-requiring molecular reactions and contribute to inter-individual variability in response to foods and nutritional interventions.

Methods

A comprehensive list of genes coding for transporters of cofactors or their precursors was built using data mining procedures from the HGDP dataset and then explored to detect evidence of positive genetic selection. This dataset was chosen since it comprises several genetically diverse worldwide populations whom ancestries have evolved in different environments and thus lived following various nutritional habits and lifestyles.

Results

We identified 312 cofactor transporter (CT) genes involved in between-cell or sub-cellular compartment distribution of 28 cofactors derived from dietary intake. Twenty-four SNPs distributed across 14 CT genes separated populations into continental and intra-continental groups such as African hunter-gatherers and farmers, and between Native American sub-populations. Notably, four SNPs were located in SLC24A3 with one being a known eQTL of the NCKX3 protein.

Conclusions

These findings could support the importance of considering individual’s genetic makeup along with their metabolic profile when tailoring personalized dietary interventions for optimizing health.

Electronic supplementary material

The online version of this article (10.1186/s12263-017-0579-x) contains supplementary material, which is available to authorized users.

Prediction of inter-individual variability on the pharmacokinetics of CYP2C8 substrates in human

Inter-individual variability in pharmacokinetics can lead to unexpected side effects and treatment failure, and is therefore an important factor in drug development. CYP2C8 is a major drug-metabolizing enzyme known to be involved in the metabolism of over 100 drugs. In this study, we predicted the inter-individual variability in AUC/Dose of CYP2C8 substrates in healthy volunteers using the Monte Carlo simulation. Inter-individual variability in the hepatic intrinsic clearance of CYP2C8 substrates (CL_int,h,2C8) was estimated from the inter-individual variability in pharmacokinetics of pioglitazone, which is a major CYP2C8 substrate. The coefficient of variation (CV) of CL_int,h,2C8 was estimated to be 40%. Using this value, the CVs of AUC/Dose of other major CYP2C8 substrates, rosiglitazone and amodiaquine, were predicted to validate the estimated CV of CL_int,h,2C8. As a result, the reported CVs of both substrates were within the 2.5-97.5 percentile range of the predicted CVs. Furthermore, the CVs of AUC/Dose of the CYP2C8 substrates loperamide and chloroquine, which are affected by renal clearance, were also successfully predicted. Combining this value with previously reported CVs of other CYPs, we were able to successfully predict the inter-individual variability in pharmacokinetics of various drugs in clinical.