Specific Questions Of Interest Research Articles

ACORN (A Clinically-Oriented Antimicrobial Resistance Surveillance Network) II: protocol for case based antimicrobial resistance surveillance.

Background: Antimicrobial resistance surveillance is essential for empiric antibiotic prescribing, infection prevention and control policies and to drive novel antibiotic discovery. However, most existing surveillance systems are isolate-based without supporting patient-based clinical data, and not widely implemented especially in low- and middle-income countries (LMICs). Methods: A Clinically-Oriented Antimicrobial Resistance Surveillance Network (ACORN) II is a large-scale multicentre protocol which builds on the WHO Global Antimicrobial Resistance and Use Surveillance System to estimate syndromic and pathogen outcomes along with associated health economic costs. ACORN-healthcare associated infection (ACORN-HAI) is an extension study which focuses on healthcare-associated bloodstream infections and ventilator-associated pneumonia. Our main aim is to implement an efficient clinically-oriented antimicrobial resistance surveillance system, which can be incorporated as part of routine workflow in hospitals in LMICs. These surveillance systems include hospitalised patients of any age with clinically compatible acute community-acquired or healthcare-associated bacterial infection syndromes, and who were prescribed parenteral antibiotics. Diagnostic stewardship activities will be implemented to optimise microbiology culture specimen collection practices. Basic patient characteristics, clinician diagnosis, empiric treatment, infection severity and risk factors for HAI are recorded on enrolment and during 28-day follow-up. An R Shiny application can be used offline and online for merging clinical and microbiology data, and generating collated reports to inform local antibiotic stewardship and infection control policies. Discussion: ACORN II is a comprehensive antimicrobial resistance surveillance activity which advocates pragmatic implementation and prioritises improving local diagnostic and antibiotic prescribing practices through patient-centred data collection. These data can be rapidly communicated to local physicians and infection prevention and control teams. Relative ease of data collection promotes sustainability and maximises participation and scalability. With ACORN-HAI as an example, ACORN II has the capacity to accommodate extensions to investigate further specific questions of interest.

ACORN (A Clinically-Oriented Antimicrobial Resistance Surveillance Network) II: protocol for case based antimicrobial resistance surveillance

Background: Antimicrobial resistance surveillance is essential for empiric antibiotic prescribing, infection prevention and control policies and to drive novel antibiotic discovery. However, most existing surveillance systems are isolate-based without supporting patient-based clinical data, and not widely implemented especially in low- and middle-income countries (LMICs). Methods: A Clinically-Oriented Antimicrobial Resistance Surveillance Network (ACORN) II is a large-scale multicentre protocol which builds on the WHO Global Antimicrobial Resistance and Use Surveillance System to estimate syndromic and pathogen outcomes along with associated health economic costs. ACORN-healthcare associated infection (ACORN-HAI) is an extension study which focuses on healthcare-associated bloodstream infections and ventilator-associated pneumonia. Our main aim is to implement an efficient clinically-oriented antimicrobial resistance surveillance system, which can be incorporated as part of routine workflow in hospitals in LMICs. These surveillance systems include hospitalised patients of any age with clinically compatible acute community-acquired or healthcare-associated bacterial infection syndromes, and who were prescribed parenteral antibiotics. Diagnostic stewardship activities will be implemented to optimise microbiology culture specimen collection practices. Basic patient characteristics, clinician diagnosis, empiric treatment, infection severity and risk factors for HAI are recorded on enrolment and during 28-day follow-up. An R Shiny application can be used offline and online for merging clinical and microbiology data, and generating collated reports to inform local antibiotic stewardship and infection control policies. Discussion: ACORN II is a comprehensive antimicrobial resistance surveillance activity which advocates pragmatic implementation and prioritises improving local diagnostic and antibiotic prescribing practices through patient-centred data collection. These data can be rapidly communicated to local physicians and infection prevention and control teams. Relative ease of data collection promotes sustainability and maximises participation and scalability. With ACORN-HAI as an example, ACORN II has the capacity to accommodate extensions to investigate further specific questions of interest.

118 The Use of Meta-analysis in Companion Animal Research

Abstract In a world of the “Three Rs” (replace, reduce and refine), combined with more research published via open access research journals, there is increasing interest in the statistical analysis of existing literature. Meta-analysis – the combination of multiple studies, can be used to get better oversight into a specific question of interest. Additionally, it can be used to identify gaps in knowledge. For example, while there are a number of publications investigating energy requirements in adult cat and dog, few studies assess older animals. Similarly, in the dog, there is a lack of literature around dogs at the extremes of body size (i.e. giant and toy breeds). Herein, we describe several published examples that have been used to determine energy requirements of cats and dogs, and more recently, the impacts of diet on the microbiome of the cat and dog. This includes the use of Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, research findings and general findings related to research design and quality.

Seasonal storage of carbon, nitrogen, and phosphorus in two perennial forest herbaceous plants

Herbaceous perennials in a forest ecosystem play a role in seasonal nutrient cycling. Asarum canadense L. (wild ginger) and Hydrophyllum virginianum L. (Virginia waterleaf) are perennial herbaceous plants with different seasonal growth patterns native to mesic hardwood forests. Both flower early, but A. canadense leaves persist after flowering while H. virginianum senesces and produces a second flush of leaves by late summer. Our specific question of interest was whether there is a difference in nutrient storage in leaves and roots seasonally in these two species. We excavated plants in spring, summer, and fall to determine carbon (C), nitrogen (N), and phosphorus (P) concentration and content in above and below ground tissues, as well as C:N and N:P ratios. Our findings indicate complex patterns in the location of nutrients in A. canadense and H. virginianum across the growing season. Asarum canadense exhibits relatively consistent above ground growth, with seasonal nutrient accumulation focused below ground for C, N, and P. Patterns are more varied in H. virginianum as a result of the second flush of leaves, notably, the C:N ratio of H. virginianum decreases across the growing season while the N:P ratio increases, but to different degrees in above/below ground tissues. We suggest these patterns are linked to changing photosynthetic capacity across the seasons and a prioritization of vegetative growth over reproductive investment.

Abstract 4353: The Fibrolamellar Registry: A patient-based medical registry can address medical care

Abstract Advances in genomics and proteomics have enabled more precise characterizations of tumors with the consequence that many cancers are being segregated into smaller categories. With this larger number of categories, more cancers are being categorized as rare. The downside to such categorizations is that the reduced numbers of patients in each category makes it difficult to gather enough information about each cancer. We are a group of patients and caregivers who have joined together to form a repository for patient-shared data and reports in an IRB-approved, non-profit medical registry for the rare and usually lethal childhood liver cancer fibrolamellar hepatocellular carcinoma (FLC). Since the Fibrolamellar Registry is patient-run and patient-owned, we have the trust of the patient community that the records will not be sold for profit. This has enabled us, in our first 3 years, to gather detailed medical records, scans and tests from over 170 patients. With input from scientists and clinicians who study FLC, we have written 600 questions of specific interest to this disease. Most of our patients have also opted to allow these medical records to be shared with a tissue FLC repository that already has samples from 110 patients. Many of patients with FLC get hyperammonenic encephalopathy. These patients do not respond to lactulose and, unfortunately, often enter a coma and die from the condition. From evaluation of our medical records the results indicate that patients do not have hyperammonenic encephalopathy as a result of liver failure. Instead, it is the result of an alteration of the expression of ornithine transcarbamylase, as a consequence of the expression of oncokinase that drives fibrolamellar. These alterations of ornithine transcarbamylase shift the urea acid cycle, resulting in the buildup of ammonia. This suggests that hyperammonemic encephalopathy should be treated with agents that modulate the urea acid cycle rather than lactulose. These results are an example of the power of a patient-run medical registry. Citation Format: Julie Latone Newcomb, Siobhan Lett, Rachael D. Migler, Elana P. Simon, Sanford M. Simon. The Fibrolamellar Registry: A patient-based medical registry can address medical care [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4353.

Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.

Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs in vivo. Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.

A causal inference perspective on the analysis of compositional data.

BackgroundCompositional data comprise the parts of some whole, for which all parts sum to that whole. They are prevalent in many epidemiological contexts. Although many of the challenges associated with analysing compositional data have been discussed previously, we do so within a formal causal framework by utilizing directed acyclic graphs (DAGs).MethodsWe depict compositional data using DAGs and identify two distinct effect estimands in the generic case: (i) the total effect, and (ii) the relative effect. We consider each in the context of three specific example scenarios involving compositional data: (1) the relationship between the economically active population and area-level gross domestic product; (2) the relationship between fat consumption and body weight; and (3) the relationship between time spent sedentary and body weight. For each, we consider the distinct interpretation of each effect, and the resulting implications for related analyses.ResultsFor scenarios (1) and (2), both the total and relative effects may be identifiable and causally meaningful, depending upon the specific question of interest. For scenario (3), only the relative effect is identifiable. In all scenarios, the relative effect represents a joint effect, and thus requires careful interpretation.ConclusionsDAGs are useful for considering causal effects for compositional data. In all analyses involving compositional data, researchers should explicitly consider and declare which causal effect is sought and how it should be interpreted.

Commentary on Boslett et al. (2020): Towards better measurement of drug involvement in fatal overdoses.

Commentary on Boslett et al. (2020): Towards better measurement of drug involvement in fatal overdoses.

Abstract 3357: The fibrolamellar registry: A model for the study of rare diseases

Abstract Advances in genomics and proteomics have enabled more precise characterizations of tumors with the consequence that many cancers are being segregated into smaller categories. With this larger number of categories, more cancers are being categorized as rare. The downside to such categorizations is that the reduced numbers of patients in each category makes it difficult to gather enough information about each cancer. We are a group of patients and caregivers who have joined together to form a repository for patient-shared data and reports in an IRB-approved, non-profit medical registry for the rare and usually lethal childhood liver cancer, fibrolamellar hepatocellular carcinoma (FLC). Since the Fibrolamellar Registry is patient-run and patient-owned, we have the trust of the patient community that the records will not be sold for profit. This has enabled us, in our first two years, to gather detailed medical records, scans and tests from over 140 patients. With input from scientists and clinicians who study FLC, we have written 600 questions of specific interest to this disease. Most of our patients have also opted to allow these medical records to be shared with a tissue FLC repository that already has samples from 110 patients. We have initiated two different collaborations with the clinical-research community to explore the records and our patients have been answering additional questions when pertinent to a particular study. Our ability to gather so many records for what is a rare cancer comes from our ability to involve patients from across institutions and across the globe. We are working with other patient groups and we feel that the Fibrolamellar Registry could be a model for gathering and organizing data for many rare diseases. Citation Format: Michelle Desmond, Julie Latone, Siobhan Lett, Rachael D. Migler, Elana P. Simon, Sanford M. Simon. The fibrolamellar registry: A model for the study of rare diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3357.

Multiplicative noise is beneficial for the transmission of sensory signals in simple neuron models

We study simple integrate-and-fire type models with multiplicative noise and consider the transmission of a weak and slow signal, i.e. a signal that evokes a small modulation of the instantaneous firing rate on time scales that are much larger than the membrane time scale and the mean interspike interval. The specific question of interest is whether and how the state-dependence of the noise can be optimized with respect to information transmission. First, in a simple model in which the noise intensity varies linearly with the state variable, we show analytically that multiplicative fluctuations may benefit the signal transfer and we elucidate the mechanism for this improvement. In a conductance-based integrate-and-fire model with synaptically filtered shot-noise input, we show by means of extended numerical simulations that also in a biophysically more relevant situation, multiplicative noise can enhance the signal-to-noise ratio. Our results shed light on a so far unexplored aspect of stochastic signal transmission in neural systems.

Use of direct behavior ratings to collect functional assessment data.

The purpose of this investigation was to evaluate the utility of Direct Behavior Rating Single Item Scale (DBR-SIS) methodology in collecting functional behavior assessment data. Specific questions of interest pertained to the evaluation of the accuracy of brief DBR-SIS ratings of behavioral consequences and determination of the type of training necessary to support such accuracy. Undergraduate student participants (N = 213; 62.0% male; 62.4% White) viewed video clips of students in a classroom setting, and then rated both disruptive behavior and 4 consequences of that behavior (i.e., adult attention, peer attention, escape/avoidance, and access to tangibles/activities). Results indicated training with performance feedback was necessary to support the generation of accurate disruptive behavior and consequence ratings. Participants receiving such support outperformed students in training-only, pretest-posttest, and posttest-only groups for disruptive behavior and all 4 DBR-SIS consequence targets. Future directions for research and implications for practice are discussed, including how teacher ratings may be collected along with other forms of assessment (e.g., progress monitoring) within an efficient Tier 2 assessment model. (PsycINFO Database Record

B02 Systems Modelling And Network-based Approaches For Basic And Translational Research In Huntington's Disease

<h3>Background</h3> As a growing and more diverse amount of genetic and molecular profile data are generated in several models of Huntington’s disease (HD), the potential of these datasets for enhancing HD research has significantly increased. Network-based analysis has the capacity to identify robust HD-associated rules and signatures from complex datasets. These rules and signatures can in turn be exploited for better understanding HD biology on a global scale as well as for prioritising models and genes around questions of specific interest, thereby supporting decision making and biomedical intelligence in HD research. <h3>Aim and method</h3> To support biomedical intelligence in HD, and as part of the project and activities of the EHDN’s working group ‘Biological modifiers’, we have developed Biogemix, a network-based data integration framework for precise rule/pattern extraction across models and species. We used this framework for integrating greater than 16 publically available datasets including transcriptomic and gene perturbation data. <h3>Outcome</h3> We found previously suspected as well as novel HD-associated features, the latter providing new insights into the global effects of mutant huntingtin pathogenicity. Additionally, we managed to determine the functional distances between experimental models of HD and assess the biological relevance of individual models of HD, functional profiles of biological modifiers and shared/unshared properties between pathological and compensatory/survival genes. <h3>Conclusion</h3> Our results validate the value and precision of the Biogemix framework for actionable knowledge in HD. As larger HD datasets become available, our results suggest that applying the Biogemix approach to the analysis of these datasets will provide deep insights into the essential features of mutant huntingtin pathogenicity while providing strong guidance to translational and pharmacological research in HD. <h3>Support</h3> CHDI Foundation, ANR, EHDN, ANRT/GSK.

The Use and Interpretation of Competing Risks Regression Models

Competing risks observations, in which patients are subject to a number of potential failure events, are a feature of most clinical cancer studies. With competing risks, several modeling approaches are available to evaluate the relationship of covariates to cause-specific failures. We discuss the use and interpretation of commonly used competing risks regression models. For competing risks analysis, the influence of covariate can be evaluated in relation to cause-specific hazard or on the cumulative incidence of the failure types. We present simulation studies to illustrate how covariate effects differ between these approaches. We then show the implications of model choice in an example from a Radiation Therapy Oncology Group (RTOG) clinical trial for prostate cancer. The simulation studies illustrate that, depending on the relationship of a covariate to both the failure type of principal interest and the competing failure type, different models can result in substantially different effects. For example, a covariate that has no direct influence on the hazard of a primary event can still be significantly associated with the cumulative probability of that event, if the covariate influences the hazard of a competing event. This is a logical consequence of a fundamental difference between the model formulations. The example from RTOG similarly shows differences in the influence of age and tumor grade depending on the endpoint and the model type used. Competing risks regression modeling requires that one considers the specific question of interest and subsequent choice of the best model to address it.

Suicidality and Risk of Suicide—Definition, Drug Safety Concerns, and a Necessary Target for Drug Development

To address issues concerning potential treatment-emergent "suicidality," a consensus conference was convened March 23-24, 2009. This gathering of participants from academia, government, and industry brought together experts in suicide prevention, clinical trial design, psychometrics, pharmacoepidemiology, and genetics, as well as research psychiatrists involved in studies in studies of psychiatric disorders associated with elevated suicide risk across the life cycle. The process involved reviews of the relevant literature, and a series of 6 breakout sessions focused on specific questions of interest. Each of the participants at the meeting received references relevant to the formal presentations (as well as the slides for the presentations) for their review prior to the meeting. In addition, the assessment instruments of suicidal ideation/behavior were reviewed in relationship to standard measures of validity, reliability, and clinical utility, and these findings were discussed at length in relevant breakout groups, in the final plenary session, and in the preparation of the article. Consensus and dissenting views were noted. Discussion and questions followed each formal presentation during the plenary sessions. Approximately 6 questions per breakout group were prepared in advance by members of the Steering Committee and each breakout group chair. Consensus in the breakout groups was achieved by nominal group process. Consensus recommendations and any dissent were reviewed for each breakout group at the final plenary session. All plenary sessions were recorded and transcribed by a court stenographer. Following the transcript, with input by each of the authors, the final paper went through 14 drafts. The output of the meeting was organized into this brief report and the accompanying full article from which it is distilled. The full article was developed by the authors with feedback from all participants at the meeting and represents a consensus view. Any areas of disagreement at the conference have been noted in the text. The term suicidality is not as clinically useful as more specific terminology (ideation, behavior, attempts, and suicide). Most participants applauded the FDA's encouragement of standard definitions and definable expectations for investigators and industry sponsors. Further research of available assessment instruments is needed to verify their utility, reliability, and validity in identifying suicide-associated treatment-emergent adverse effects and/or a signal of efficacy in suicide prevention trials. The FDA needs to systematically monitor postmarketing events by encouraging the development of a validated instrument for postmarketing surveillance of suicidal ideation, behavior, and risk. Over time, the FDA, industry, and clinical researchers should evaluate the impact of the requirement that all central nervous system clinical drug trials must include a Columbia Classification Algorithm of Suicide Assessment (C-CASA)-compatible screening instrument for assessing and documenting the occurrence of treatment-emergent suicidal ideation and behavior. Finally, patients at high risk for suicide can safely be included in clinical trials, if proper precautions are followed.

The Case-Crossover Study: A Novel Design in Evaluating Transient Fatigue as a Risk Factor for Road Traffic Accidents

The Case-Crossover Study: A Novel Design in Evaluating Transient Fatigue as a Risk Factor for Road Traffic Accidents

Effective hydraulic properties of layered soils at the lysimeter scale determined by inverse modelling

SummaryThe transferability of soil hydraulic properties measured in the laboratory to the field or catchment scale is a key problem in soil hydrology. To narrow the gap between laboratory and field scale we investigated soil water movement at the lysimeter scale. Specific questions of interest are the existence and uniqueness of effective hydraulic properties for lysimeters that are internally heterogeneous. To answer these questions, synthetic measurements of water contents, pressure heads, and fluxes across the system boundaries were generated by forward modelling of water flow, based on the Richards equation, for a variety of homogeneous and layered soils and under varying types of boundary conditions (multistep outflow, evaporation, transient atmospheric). We evaluated the measurements by inverse modelling assuming a homogeneous system. The globally convergent shuffled complex evolution algorithm was applied to avoid parameter estimation problems caused by a rough topology of the objective function. The hydraulic properties of homogeneous soils were always uniquely identified, not only for the classic multistep outflow and evaporation experiments but also under natural atmospheric boundary conditions. Moreover, for the weakly heterogeneous layered soils, the soil water dynamics could be well described with effective homogeneous properties. For highly heterogeneous, layered soils, it was still possible to match the boundary fluxes for all types of experiments. Internal system states could not be matched, however, and the properties identified depended on the type of experiment. For these soils no unique effective soil hydraulic properties exist. We found that for strongly layered soils the simultaneous determination of the hydraulic properties of multiple soil layers by inverse modelling is a practicable alternative to the description with effective parameters.

Writing place: a comparison of nursing research and health geography

The concept of 'place', and general references to 'geographies of ...' are making gradual incursions into nursing literature. Although the idea of place in nursing is not new, this recent spatial turn seems to be influenced by the increasing profile of the discipline of health geography, and the broadening of its scope to incorporate smaller and more intimate spatial scales. A wider emphasis within the social sciences on place from a social and cultural perspective, and a wider turn to 'place' across disciplines are probably equally important factors. This trend is raising some interesting questions for nurses, but at the same time contributes some confusion with regard to imputed meanings of 'place'. While it is clear that most nurse clinicians and researchers certainly understand that place of care matters to their practices and patients, many diverse uses of 'place' are found within nursing literature, and contemporary understandings of the term 'place' within nursing are not immediately clear. It is in this context that this article plans to advance the discussion of place. More specifically, the aims of this paper are threefold: to critique 'place' as it appears in nursing literature, to explore the use of 'place' within health geography, whence notions of place and 'geographies of' have originated and, finally, to compare and contrast the use of 'place' in both disciplines. This critique intends to address a deficit in the literature, in this era of growing spatialization in nursing research. The specific questions of interest here are: 'what is "place" in nursing?' and 'how do concepts of place in nursing compare to concepts of place in health geography?'

Illustrations and guidelines for selecting statistical methods for quantifying spatial pattern in ecological data

This paper aims to provide guidance to ecologists with limited experience in spatial analysis to help in their choice of techniques. It uses examples to compare methods of spatial analysis for ecological field data. A taxonomy of different data types is presented, including point‐ and area‐referenced data, with and without attributes. Spatially and non‐spatially explicit data are distinguished. The effects of sampling and other transformations that convert one data type to another are discussed; the possible loss of spatial information is considered. Techniques for analyzing spatial pattern, developed in plant ecology, animal ecology, landscape ecology, geostatistics and applied statistics are reviewed briefly and their overlap in methodology and philosophy noted. The techniques are categorized according to their output and the inferences that may be drawn from them, in a discursive style without formulae. Methods are compared for four case studies with field data covering a range of types. These are: 1) percentage cover of three shrubs along a line transect; 2) locations and volume of a desert plant in a 1 ha area; 3) a remotely‐sensed spectral index and elevation from 105 km2 of a mountainous region; and 4) land cover from three rangeland types within 800 km2 of a coastal region. Initial approaches utilize mapping, frequency distributions and variance‐mean indices. Analysis techniques we compare include: local quadrat variance, block quadrat variance, correlograms, variograms, angular correlation, directional variograms, wavelets, SADIE, nearest neighbour methods, Ripley's (t), and various landscape ecology metrics. Our advice to ecologists is to use simple visualization techniques for initial analysis, and subsequently to select methods that are appropriate for the data type and that answer their specific questions of interest. It is usually prudent to employ several different techniques.

Telemedicine and Patient Satisfaction: Current Status and Future Directions

One of the most researched areas in telemedicine concerns the issue of satisfaction. However, most of this research lacks any consistent methodological approach. As a result, it is difficult to conclude whether patients and providers are satisfied with telemedicine. However, this paper postulates that there is a bigger problem within the satisfaction literature than the quality of the research to date. Instead, the bigger question is whether the results from a specific telemedicine project can actually be generalized across all telemedicine contexts. This paper argues that research should focus on specific questions of interest rather than continue the tradition of generic satisfaction research if we hope to gain specific knowledge that will inform the field of telemedicine as a whole.

The Excess Burden of Monetary Policy; A Discussion of the Hodgman and Mayer Papers

The papers by Donald Hodgman and Thomas Mayer are concerned with two general questions: (1) The differential effects of monetary policy on different sectors of the economy, and (2) the use of selective credit controls to implement both general monetary policy and to alter the allocation of credit. Both Hodgman and Mayer pay particular attention to specific questions of interest to them. Mayer concentrates on the alleged discriminatory impact of tight money on housing. Hodgman devotes much of his paper to the use of selective credit controls as a tool for altering the allocation of credit in the market. Implicit in both analyses is some theory of optimal policy execution in a setting where the free market allegedly fails to produce socially acceptable results. Much theory has been put forth in this setting as far as tax and expenditure policies are concerned. Very little general theory has been developed as far as monetary policy is concerned. Both Mayer and Hodgman present theoretical discussions of specific issues but do not relate this theory to an overall approach to monetary policy execution. This is an ideal opportunity to initiate a discussion along such lines. There are, really, two topics for consideration. The first topic concerns the optimal execution of an overall policy of monetary ease or restraint, while the second issue concerns the optimal execution of a policy to alter the allocation of credit. Each will be discussed in turn. Let us assume for the moment that in all segments of the economy social costs equal private costs and social benefits equal private benefits. The imposition of monetary ease or restraint (in order to maintain full employment without inflation) must, therefore, take place without altering the efficiency of the free market's allocation of resources.1 In other words, we must minimize the welfare costs of a given monetary (or stabilization) policy. Assuming that some stabilization policy is