Fatty acid binding protein 5 inhibition attenuates pronociceptive cytokine/chemokine expression and suppresses osteoarthritis pain: A comparative human and rat study

OBJECTIVE

Osteoarthritis (OA) is often accompanied by debilitating pain that is refractory to available analgesics due in part to the complexity of signaling molecules that drive OA pain and our inability to target these in parallel. Fatty acid binding protein 5 (FABP5) is a lipid chaperone that regulates inflammatory pain; however, its contribution to OA pain has not been characterized.

DESIGN

This combined clinical and pre-clinical study utilized synovial tissues obtained from subjects with end-stage OA and rats with monoiodoacetate-induced OA. Cytokine and chemokine release from human synovia incubated with a selective FABP5 inhibitor was profiled with cytokine arrays and ELISA. Immunohistochemical analyses were conducted for FABP5 in human and rat synovium. The efficacy of FABP5 inhibitors on pain was assessed in OA rats using incapacitance as an outcome. RNA-seq was then performed to characterize the transcriptomic landscape of synovial gene expression in OA rats treated with FABP5 inhibitor or vehicle.

RESULTS

FABP5 was expressed in human synovium and FABP5 inhibition reduced the secretion of pronociceptive cytokines (interleukin-6 [IL6], IL8) and chemokines (CCL2, CXCL1). In rats, FABP5 was upregulated in the OA synovium and its inhibition alleviated incapacitance. The transcriptome of the rat OA synovium exhibited >6000 differentially expressed genes, including the upregulation of numerous pronociceptive cytokines and chemokines. FABP5 inhibition blunted the upregulation of the majority of these pronociceptive mediators.

CONCLUSIONS

FABP5 is expressed in the OA synovium and its inhibition suppresses pronociceptive signaling and pain, indicating that FABP5 inhibitors may constitute a novel class of analgesics to treat OA.

Computer-Aided Detection of Respiratory Sounds in Bronchial Asthma Patients Based on Machine Learning Method

The aim of the study is to develop a method for detection of pathological respiratory sound, caused by bronchial asthma, with the aid of machine learning techniques.

Materials and Methods

To build and train neural networks, we used the records of respiratory sounds of bronchial asthma patients at different stages of the disease (n=951) aged from several months to 47 years old and healthy volunteers (n=167). The sounds were recorded with calm breathing at four points: at the oral cavity, above the trachea, on the chest (second intercostal space on the right side), and at a point on the back.

Results

The method developed for computer-aided detection of respiratory sounds allows to diagnose sounds typical for bronchial asthma in 89.4% of cases with 89.3% sensitivity and 86.0% specificity regardless of sex and age of the patients, stage of the disease, and the point of sound recording.

A simple explanation for declining temperature sensitivity with warming

Recently, multiple studies have reported declining phenological sensitivities (∆ days per ℃) with higher temperatures. Such observations have been used to suggest climate change is reshaping biological processes, with major implications for forecasts of future change. Here, we show that these results may simply be the outcome of using linear models to estimate nonlinear temperature responses, specifically for events that occur after a cumulative thermal threshold is met-a common model for many biological events. Corrections for the nonlinearity of temperature responses consistently remove the apparent decline. Our results show that rising temperatures combined with linear estimates based on calendar time produce the observations of declining sensitivity-without any shift in the underlying biology. Current methods may thus undermine efforts to identify when and how warming will reshape biological processes.

A child with resistant Kawasaki disease successfully treated with anakinra: a case report

Background

Kawasaki disease (KD) is an acute self-limited systemic vasculitis of unknown etiology. Intravenous immunoglobulin (IVIG) is an effective treatment and decreases the risk of cardiac complications to less than 5%. In spite of its effectiveness, some children do not respond to this therapy and still develop coronary aneurysms (CAA). The optimal treatment for IVIG non-responsive patients remains controversial although corticoids have been suggested to be an effective treatment in some patients. For those patients still resistant to IVIG and corticoids, interleukin-1 receptor antagonists (IL-1RA) such anakinra could be an alternative.

Case presentation

We present a 3 year-old Caucasian patient with KD without cardiac complications but with important resistance to treatment. After becoming resistant to IVIG and corticoids, anakinra proved to be an effective treatment.

Conclusions

To our knowledge, this is the first report of the utility of IL-1RA in refractory KD without coronary impairment. The patient fulfilled the classical criteria for KD and, after becoming resistant to first and second line treatments, anakinra proved to be an effective treatment. Further studies are required to determine if this is an effective treatment option for other cases of resistant Kawasaki disease.

B Cell-Activating Transcription Factor Plays a Critical Role in the Pathogenesis of Anti-Major Histocompatibility Complex-Induced Obliterative Airway Disease

Antibodies (Abs) against major histocompatibility complex (MHC) results in T helper-17 (Th17)-mediated immunity against lung self-antigens (SAgs), K-α1 tubulin and collagen V and obliterative airway disease (OAD). Because B cell-activating transcription factor (BATF) controls Th17 and autoimmunity, we proposed that BATF may play a critical role in OAD. Anti-H2K(b) was administered intrabronchially into Batf (-/-) and C57BL/6 mice. Histopathology of the lungs on days 30 and 45 after Ab administration to Batf (-/-) mice resulted in decreased cellular infiltration, epithelial metaplasia, fibrosis, and obstruction. There was lack of Abs to SAgs, reduction of Sag-specific interleukin (IL)-17 T cells, IL-6, IL-23, IL-17, IL-1β, fibroblast growth factor-6, and CXCL12 and decreased Janus kinase 2, signal transducer and activator of transcription 3 (STAT3), and retinoid-related orphan receptor γT. Further, micro-RNA (miR)-301a, a regulator of Th17, was reduced in Batf (-/-) mice in contrast to upregulation of miR-301a and downregulation of protein inhibitor of activated STAT3 (PIAS3) in anti-MHC-induced OAD animals. We also demonstrate an increase in miR-301a in the bronchoalveolar lavage cells from lung transplant recipients with Abs to human leukocyte antigen. This was accompanied by reduction in PIAS3 mRNA. Therefore, we conclude that BATF plays a critical role in the immune responses to SAgs and pathogenesis of anti-MHC-induced rejection. Targeting BATF should be considered for preventing chronic rejection after human lung transplantation.

Targeting low-arsenic groundwater with mobile-phone technology in Araihazar, Bangladesh

The Bangladesh Arsenic Mitigation and Water Supply Program (BAMWSP) has compiled field-kit measurements of the arsenic content of groundwater for nearly five million wells. By comparing the spatial distribution of arsenic inferred from these field-kit measurements with geo-referenced laboratory data in a portion of Araihazar upazila, it is shown here that the BAMWSP data could be used for targeting safe aquifers for the installation of community wells in many villages of Bangladesh. Recent experiences with mobile-phone technology to access and update the BAMWSP data in the field are also described. It is shown that the technology, without guaranteeing success, could optimize interventions by guiding the choice of the drilling method that is likely to reach a safe aquifer and identifying those villages where exploratory drilling is needed.

Effect of ozone pretreatment on fish storage life at low temperatures

The purpose of the present study was to determine the effect of ozone pretreatment of live fish on their shelf life and storage characteristics during storage at 0 and 5 degrees C. The evaluation included sensory, chemical, physical, and bacteriological tests at set intervals throughout a storage period of 30 days under two temperature regimes (0 and 5 degrees C). The results of the sensory tests showed that ozone pretreatment of live tilapia prolonged their shelf life by 12 days and improved their quality characteristics during storage at 0 degrees C for 30 days. These results were corroborated by the bacteriological tests. The sensory qualities of ozone-treated tilapia stored at 5 degrees C became unacceptable 3 days later than those of control fish. Although the most important factor affecting the fish shelf life is storage temperature, the combination of ozone pretreatment with storage at 0 degrees C appears to be a promising means of prolonging the shelf life.

Reliability of a commercial kit to test groundwater for arsenic in Bangladesh

A comparison of field and laboratory measurements of arsenic in groundwater of Araihazar, Bangladesh, indicates that the most widely used field kit correctly determined the status of 88% of 799 wells relative to the local standard of 50 microg/L As. Additional tests showthatthe inconsistencies, mainly underestimates in the 50-100 microg/L As range, can be avoided by increasing the reaction time from 20 to 40 min. Despite this limitation, the field data already compiled for millions of wells by the Bangladesh Arsenic Mitigation and Water Supply Project, in combination with information on well location and depth, should prove to be extremely useful to prioritize interventions in thousands of affected villages.

Temperature dependent characteristics of intestinal glycyl-l-leucine dipeptidase in boreal zone fish

Three kinds of boreal zone fish were investigated for gastrointestinal glycyl-L-leucine (GL) dipeptide cleaving activity as a function of feeding stage and seasonal changes. The enzyme activity tested in the perch (Perca fluviatilis L.) intestine increased steadily during digestion and rapidly disappeared after completion. The temperature characteristics and the seasonal changes in dipeptide cleaving activity in pike perch (Stizostedion lucioperca L.) and bream (Abramis brama L.) were studied. In summer, the maximal activities in the pike perch and the bream were found at temperatures of 40 and 30 degrees C, respectively. In winter, the temperature of maximal activity in pike perch fell to only 30 degrees C, whereas no changes were observed in bream. The activation energies in bream and pike perch were several times lower in winter than in summer. Seasonal changes in the dipeptide cleaving activity at low temperature relative to that at the temperature of maximal activity were found. At high temperatures, the stability of the enzyme decreases in winter and increases in summer, but in the presence of a substrate the thermal stability of the enzyme increases both in winter and in summer. In our experiments, we found that in these fish, GL dipeptidase was unstable at 0 and -10 degrees C.

Reducing waste contamination from animal-processing plants by anaerobic thermophilic fermentation and by flesh fly digestion

There is currently no market in Israel for the large amounts of waste from fish- and poultry-processing plants. Therefore, this waste is incinerated, as part of the measures to prevent the spread of pathogens. Anaerobic methanogenic thermophilic fermentation (AMTF) of wastes from the cattle-slaughtering industry was examined previously, as an effective system to treat pathogenic bacteria, and in this article, we discuss a combined method of digestion by thermophilic anaerobic bacteria and by flesh flies, as a means of waste treatment. The AMTF process was applied to the wastes on a laboratory scale, and digestion by rearing of flesh fly (Phaenicia sericata) and housefly (Musca domestica) larvae on the untreated raw material was done on a small scale and showed remarkable weight conversion to larvae. The yield from degradation of poultry waste by flesh fly was 22.47% (SD = 3.89) and that from fish waste degradation was 35.34% (SD = 12.42), which is significantly higher than that from rearing houseflies on a regular rearing medium. Bacterial contents before and after thermophilic anaerobic digestion, as well as the changes in the chemical composition of the components during the rearing of larvae, were also examined.

Amylolytic activity in fish intestinal mucosa: temperature effects

The activity, temperature characteristics and energy of activation of amylolytic enzymes in the intestinal mucosa were studied in six species of fish living in a boreal zone [burbot (Lota lota L.), northern pike (Exos lucius L.), perch (Perca fluviatilis L.), bream (Abramis brama L.), roach (Rutilis rutilis L.), and carp (Cyprinus carpio L.)] and in three species from tropical and subtropical areas [pilchard (Sardina pilchardus W.), jack mackerel (Trachurus trecae C.) and round sardinella (Sardinella aurita V.)]. The amylolytic activity correlated with the feeding habits: it was essentially lower in predators. The enzyme activity at low temperature, relative to the maximal activity, was correlated with the natural environmental temperature where the species lived. At low temperature the relative activity was higher in boreal fish than in tropical and subtropical fish. We found a breakpoint in the Arrhenius plots in all fish species, except for jack mackerel. The energy of activation in predators decreased below the breakpoint in the low-temperature region. The energy of activation in benthophages of the Aral-Ponto-Caspian area was lower at higher temperatures above the breakpoint. A reduction in activation energy in the range of physiological temperatures might indicate adaptation to the environmental temperature.

Effects of herbal essential oils used to extend the shelf life of freshwater-reared Asian sea bass fish (Lates calcarifer)

Sensory and microbiological characteristics of Asian sea bass (Lates calcarifer) fish raised in a freshwater pond were evaluated during cold storage for 33 days. Whole fish (averaging 400 g each) were stored in a cold storage room at 0 to 2 degrees C. Essential oils of herbs--thyme (Thymus vulgaris) and oregano (Origanum vulgare)--added at 0.05% (vol/vol) were used as preservatives. On the basis of the sensory test results as well as the bacteriological tests, the addition of oregano and thyme essential oils can considerably slow the process of spoilage. The fish treated with these oils were still fit for human consumption after 33 days of storage. The results obtained through sensory tests are corroborated to a great extent by the chemical (hypoxanthine) tests and to a lesser extent by the physical (Cosmos units) tests. The initial total bacteriological counts were 1.7 x 10(3) CFU/cm2 on the fish surface and <10(2) CFU/g in the fish flesh, and in the control treatment (without preservatives), these counts rose continuously, reaching around 10(7) CFU/cm2 on the fish surface and 10(3) CFU/g in the flesh after 33 days of storage at 0 to 2 degrees C. The use of herbal essential oils as preservatives, on the other hand, resulted in a maximal count of 10(5) CFU/cm2 on the fish surface, while the bacterial count in the flesh remained <10(2) CFU/g by the end of the 33-day storage period at 0 to 2 degrees C.

A case study on the choice, interpretation and checking of multilevel models for longitudinal binary outcomes

Recent advances in statistical software have led to the rapid diffusion of new methods for modelling longitudinal data. Multilevel (also known as hierarchical or random effects) models for binary outcomes have generally been based on a logistic-normal specification, by analogy with earlier work for normally distributed data. The appropriate application and interpretation of these models remains somewhat unclear, especially when compared with the computationally more straightforward semiparametric or 'marginal' modelling (GEE) approaches. In this paper we pose two interrelated questions. First, what limits should be placed on the interpretation of the coefficients and inferences derived from random-effect models involving binary outcomes? Second, what diagnostic checks are appropriate for evaluating whether such random-effect models provide adequate fits to the data? We address these questions by means of an extended case study using data on adolescent smoking from a large cohort study. Bayesian estimation methods are used to fit a discrete-mixture alternative to the standard logistic-normal model, and posterior predictive checking is used to assess model fit. Surprising parallels in the parameter estimates from the logistic-normal and mixture models are described and used to question the interpretability of the so-called 'subject-specific' regression coefficients from the standard multilevel approach. Posterior predictive checks suggest a serious lack of fit of both multilevel models. The results do not provide final answers to the two questions posed, but we expect that lessons learned from the case study will provide general guidance for further investigation of these important issues.

Effects of storage temperature and preservative treatment on shelf life of the pond-raised freshwater fish, silver perch (Bidyanus bidyanus)

Sensory and microbiological characteristics of pond-raised freshwater silver perch (Bidyanus bidyanus) fish, during cold storage over a period of 25 days were evaluated. Whole fish (averaging 400 g each) were stored in cold storage rooms at either 0 to 2 degrees C, 5 degrees C, or 5 degrees C + potassium sorbate as a preservative. The organoleptic and hypoxanthine test results show that the treatment of potassium sorbate can slow the process of spoilage by about 5 days. Yet, the most important factor affecting the shelf life of these fish is the storage temperature. Keeping the fish at 0 to 2 degrees C can prolong the storage prior to spoilage by 10 days compared with those kept at 5 degrees C. These results obtained through organoleptic tests are corroborated by both the chemical (hypoxanthine and total volatile basic nitrogen) and to some extent by the physical (cosmos) tests. The initial total bacteriological counts were 5 x 10(2) CFU/cm2 for fish surface and <10(2) CFU/g for fish flesh, and these counts rose continuously, reaching about 106 CFU/g (0 to 2 degrees C) and 10(7) CFU/g (5 degrees C) in flesh and 10(7) to 10(8) CFU/cm2 on the surface by the end of the storage period. The addition of potassium sorbate led to a smaller increase in bacterial numbers, especially during the first 15 days. Bacterial composition fluctuated during storage. The initial load on the fish surface was predominantly mesophilic and gram positive and consisted mostly (80%) of Micrococci, Bacillus, and Corynebacterium. During the next 10 days, these bacteria were practically replaced by gram-negative flora comprised mostly of Pseudomonas fluorescens that rapidly increased with storage time and accounted for 95% after 15 days.

A method for quantifying artefacts in mapping methods illustrated by application to headbanging

Maps of disease rates (and other quantities) often must contend with variance associated with variable population sizes and low incidence within spatial units. These characteristics can lead to substantial statistical noise that can mask underlying spatial variation. As Gelman and Price illustrated, most conventional mapping methods fail to address this problem, and in fact can introduce statistical artefacts; mapped quantities can show spatial patterns even when there are no spatial patterns in the underlying parameter of interest. Kafadar evaluated the performance of the headbanging algorithm for spatial smoothing (Tukey and Tukey, Hansen) for eliminating small scale variation and preserving edge structure. Here we perform a simulation study to investigate the artefacts of maps smoothed by unweighted and weighted headbanging. We find substantial artefacts that depend on the spatial structure of the statistical variation (for example, the spatial pattern of sample sizes) and on the details of the spatial distribution of geographic units. The methods used here could readily be adapted to study other spatial smoothers; we choose headbanging because (i) it is an important method used in practice, and (ii) its heavily computational nature is naturally studied using simulation (in contrast to the analytical methods used by Gelman and Price).

Should we take measurements at an intermediate design point?

It is well known that, for estimating a linear treatment effect with constant variance, the optimal design divides the units equally between the two extremes of the design space. If the dose-response relation may be nonlinear, however, intermediate measurements may be useful in order to estimate the effects of partial treatments. We consider the decision of whether to gather data at an intermediate design point: do the gains from learning about nonlinearity outweigh the loss in efficiency in estimating the linear effect? Under reasonable assumptions about nonlinearity, we find that, unless sample size is very large, the design with no interior measurements is best, because with moderate total sample sizes, any nonlinearity in the dose-response will be difficult to detect. We discuss in the context of a simplified version of the problem that motivated this work-a study of pest-control treatments intended to reduce asthma symptoms in children.

All maps of parameter estimates are misleading

Maps are frequently used to display spatial distributions of parameters of interest, such as cancer rates or average pollutant concentrations by county. It is well known that plotting observed rates can have serious drawbacks when sample sizes vary by area, since very high (and low) observed rates are found disproportionately in poorly-sampled areas. Unfortunately, adjusting the observed rates to account for the effects of small-sample noise can introduce an opposite effect, in which the highest adjusted rates tend to be found disproportionately in well-sampled areas. In either case, the maps can be difficult to interpret because the display of spatial variation in the underlying parameters of interest is confounded with spatial variation in sample sizes. As a result, spatial patterns occur in adjusted rates even if there is no spatial structure in the underlying parameters of interest, and adjusted rates tend to look too uniform in areas with little data. We introduce two models (normal and Poisson) in which parameters of interest have no spatial patterns, and demonstrate the existence of spatial artefacts in inference from these models. We also discuss spatial models and the extent to which they are subject to the same artefacts. We present examples from Bayesian modelling, but, as we explain, the artefacts occur generally.

Optimal design for a study of butadiene toxicokinetics in humans

The derivation of the optimal design for an upcoming toxicokinetic study of butadiene in humans is presented. The specific goal of the planned study is to obtain a precise estimate of butadiene metabolic clearance for each study subject, together with a good characterization of its population variance. We used a two-compartment toxicokinetic model, imbedded in a hierarchical population model of variability, in conjunction with a preliminary set of butadiene kinetic data in humans, as a basis for design optimization. Optimization was performed using Monte Carlo simulations. Candidate designs differed in the number and timing of exhaled air samples to be collected. Simulations indicated that only 10 air samples should be necessary to obtain a coefficient of variation of 15% for the estimated clearance rate, if the timing of those samples is properly chosen. Optimal sampling times were found to closely bracket the end of exposure. This efficient design will allow the recruitment of more subjects in the study, in particular to match prescribed levels of accuracy in the estimate of the population variance of the butadiene metabolic rate constant. The techniques presented here have general applicability to the design of human and animal toxicology studies.

A nondenaturing solid phase pharmaceutical carrier comprised of surface-modified nanocrystalline materials

Numerous carrier systems have been developed for the controlled delivery of biologically active molecules such as drugs and diagnostic agents. The biophysical interactions between the biologically active molecules and their carriers, however, may denature the former and lead to reduced biological activity. In this study, a model nondenaturing carrier comprised of a nanocrystalline (10 -7 m) tin oxide core and a surface-charge-reducing organic bonding layer (GF292) was synthesized. A subsequently bound protein (human transferrin) showed significant retained conformation by immunoelectron microscopy. In the synthesis of targeted drug systems and vaccines, nanocrystalline cores treated with appropriate surface-modifying agents may be suitable carriers.

Nanocrystalline Epstein-Barr virus decoys

A novel biotechnology is introduced by way of the successful synthesis of nanocrystalline Epstein-Barr virus (EBV) decoys having specific in vivo immunogenic activity. Assembled from ultrafine surface modified tin oxide and purified DNA-free isolated EBV envelope proteins, the decoys consisted of less than 150 nm units whose electrophoretic mobilities were similar to whole EBV; whose outer coats were strongly immunoreactive with murine monoclonal anti-EBV antibodies; and which elicited immunospecific neutralizing anti-EBV antibodies in the rabbit. The development of this carrier technology for vaccine preparations is suggested.

Walking to school and traffic exposure in Australian children

Daily patterns of pedestrian activity in young children have important health implications, primarily because of the risk of road traffic injury, but also because they may reflect the commencement of exercise habits with long-term consequences. A cross-sectional survey in two Australian cities, Melbourne and Perth, aimed to collect, by parent self-administered questionnaire, population-based data on modes of travel, numbers of street crossings (both accompanied and unaccompanied by an adult), and sociodemographic factors for six- and nine-year-old children. Results indicate that 35 per cent (95 per cent confidence interval (CI) 31 to 39 per cent) and 31 per cent (CI 28 to 34 per cent) walk to school in Melbourne and Perth respectively, while over 60 per cent are driven to school by car, with very small proportions riding bicycles or taking public transport. A higher level of walking was associated with lower levels of several indicators of socioeconomic status. Logistic regression analysis showed that the strongest predictor of walking activity was school type (government versus independent), and after adjusting for this, lesser car ownership, non-English-speaking background and lower occupational category were associated with walking to school, while a different set of predictors--age, sex and maternal education--was associated with the unaccompanied crossing of streets. There was little difference in overall walking levels between boys and girls, but boys were significantly more likely to cross streets unaccompanied (adjusted odds ratio 1.41, CI 1.14 to 1.72), providing a partial explanation of documented sex differences in injury rates.

Bayesian prediction of mean indoor radon concentrations for Minnesota counties

Past efforts to identify areas with higher than average indoor radon concentrations by examining the statistical relationship between local mean concentrations and physical parameters such as the soil radium concentration have been hampered by the variation in local means caused by the small number of homes monitored in most areas. In this paper, indoor radon data from a survey in Minnesota are analyzed to minimize the effect of finite sample size within counties, to determine the true county-to-county variation of indoor radon concentrations in the state, and to find the extent to which this variation is explained by the variation in surficial radium concentration among counties. The analysis uses hierarchical modeling, in which some parameters of interest (such as county geometric mean radon concentrations) are assumed to be drawn from a single population, for which the distributional parameters are estimated from the data. Extensions of this technique, known as random effects regression and mixed effects regression, are used to determine the relationship between predictive variables and indoor radon concentrations; the results are used to refine the predictions of each county's radon levels, resulting in a great decrease in uncertainty. The true county-to-county variation of geometric mean radon levels is found to be substantially less than the county-to-county variation of the observed geometric means, much of which is due to the small sample size in each county. The variation in the logarithm of surficial radium content is shown to explain approximately 80% of the variation of the logarithm of geometric mean radon concentration among counties. The influences of housing and measurement factors, such as whether the monitored home has a basement and whether the measurement was made in a basement, are also discussed. The statistical method can be used to predict mean radon concentrations, or applied to other geographically distributed environmental parameters.

Markov chain Monte Carlo methods in biostatistics

Appropriate models in biostatistics are often quite complicated. Such models are typically most easily fit using Bayesian methods, which can often be implemented using simulation techniques. Markov chain Monte Carlo (MCMC) methods are an important set of tools for such simulations. We give an overview and references of this rapidly emerging technology along with a relatively simple example. MCMC techniques can be viewed as extensions of iterative maximization techniques, but with random jumps rather than maximizations at each step. Special care is needed when implementing iterative maximization procedures rather than closed-form methods, and even more care is needed with iterative simulation procedures: it is substantially more difficult to monitor convergence to a distribution than to a point. The most reliable implementations of MCMC build upon results from simpler models fit using combinations of maximization algorithms and noniterative simulations, so that the user has a rough idea of the location and scale of the posterior distribution of the quantities of interest under the more complicated model. These concerns with implementation, however, should not deter the biostatistician from using MCMC methods, but rather help to ensure wise use of these powerful techniques.