Lack Of Fit Research Articles

Identification of novel DNA Gyrase inhibitor by combined Pharmacophore modeling, QSAR analysis, Molecular docking, Molecular dynamics, ADMET and DFT approaches

DNA gyrase, an ATP-dependent enzyme, plays a critical role in DNA replication, transcription, and recombination in Mycobacterium tuberculosis (MTB). While fluoroquinolones are effective antibacterial agents targeting DNA gyrase, their clinical use is often limited due to side effects and the emergence of bacterial resistance. In this study, we developed a quantitative structure-activity relationship (QSAR) model to predict the anti-tubercular activity of Quinoline-Aminopiperidine derivatives targeting the DNA gyrase enzyme, using a dataset of 48 compounds obtained from the literature. The QSAR model was validated using both internal and external validation metrics. Model 4, the best predictive model, demonstrated a strong fit with an R² of 0.8393, an adjusted R² (R²adj) of 0.8010, and a lack of fit (LOF) parameter of 0.0626. The QSAR results revealed that DNA gyrase inhibition is significantly influenced by factors such as partition coefficient, molecular flexibility, hydrogen bonding potential, and the presence of fluorine atoms. Twelve quinoline-aminopiperidine derivatives were designed, and their anti-tubercular activity was predicted using QSAR model-4. These compounds were further assessed for pharmacokinetic properties, toxicity, and binding affinity to DNA gyrase. Pharmacophore modeling was also performed and validated using MOE software. The final pharmacophore model includes the features of two aromatic hydrophobic features, one hydrogen bond acceptor, and one hydrogen bond donor. The results indicated that designed compounds QA-3 and dataset compounds C-34 exhibit favorable drug-likeness properties. Molecular dynamics simulations confirmed the stable binding of compounds QA-3 and C-34 to the DNA gyrase protein, highlighting their potential as promising anti-tubercular agents. The developed QSAR Model-4 will facilitate the prediction of anti-tubercular activity in Quinoline-Aminopiperidine derivatives.

The effects of mechanical imperfections on the stability behavior of double-layer Scallop domes

Mechanical imperfections are almost inevitable in large-span spatial domes with hundreds of members and joints. The lack of fit in members is the most common form of imperfections in double-layer domes which influences the behavior of these structures under gravitational or seismic loads. In this study, the probabilistic effect of mechanical imperfections (lack of fit) on the stability behavior of double-layer Scallop domes with sinusoidal arching style under symmetric and asymmetric snow-loading is investigated. On some double-layer scallop domes, nonlinear static and dynamic analyses are carried out using Abaqus/CAE and MATLAB. The behavior of the structures with randomly distributed imperfect members is compared with those of the ideally perfect structures. A Monte Carlo simulation approach is used to statistically assess the effects of uncertainties on the response parameters and the ultimate capacity of the structures. In the first approach, named here as the “rigorous probabilistic approach”, the amount and the distribution of imperfect members are all treated as random variables, and in the second approach, named as “concise approach”, a fixed amount of imperfections are applied to a number of randomly selected critical members. No simplification method is used in the rigorous probabilistic approach to achieve a reliable assessment of the effect of uncertain parameters. Results show that the collapse behavior of double-layer Scallop domes is sensitive to random imperfections and a considerable decrease is seen in their load-bearing capacity.

Enhanced bioavailability and efficacy in antimalarial treatment through QbD approach enteric encased inclusion delivery.

Aim: In this study, we aimed to prepare enteric encapsulated spheroids containing inclusion complex using quality by design approach.Methods: A Box-Behnken design was employed to determine effects of variables on selected responses. Risk assessment was conducted using Ishikawa fishbone diagram. A model with a p-value was less than 0.5 for being a significant error of model was determined based on significance 'lack of fit' value. Spheroids were formulated using the extrusion spheronization technique and were characterized using analytical techniques.Results: In vitro release was performed in both acidic (pH 1.2) and simulated intestinal (pH 6.8) conditions. Permeability studies demonstrated tenfold enhancement compared with arteether. In vivo studies further validated increase of 51.8% oral bioavailability. Exvivo studies revealed 3.4-fold enhancement in antimalarial activity compared with arteether.Conclusion: These findings highlight effectiveness of inclusion complexation technique as a viable approach to enhance solubility and bioavailability for drugs with low aqueous solubility.

Predicting recurrent gestational diabetes mellitus using artificial intelligence models: a retrospective cohort study.

We aimed to develop novel artificial intelligence (AI) models based on early pregnancy features to forecast the likelihood of recurrent gestational diabetes mellitus (GDM) before 14weeks of gestation in subsequent pregnancies. This study involved a cohort of 588 women who had two consecutive singleton deliveries and were diagnosed with GDM during the index pregnancy. The least absolute shrinkage and selection operator (LASSO) regression analysis were used for feature selection. 5 AI algorithms, namely support vector machine (SVM), extreme gradient boosting (XGB), light gradient boosting (LGB), decision tree classifier (DTC), and random forest (RF) classifier, and traditional multivariate logistic regression (LR) model, were employed to construct predictive models for recurrent GDM. 326 (55.4%) experienced GDM recurrence in subsequent pregnancy. In the training set (67% of the study sample), 13 features were selected for AI models construction. In the testing set (33% of the study sample), the AI models (LGB, RF, and XGB) exhibited outstanding discrimination, with AUROC values of 0.942, 0.936, and 0.924, respectively. The traditional LR model showed moderate discrimination (AUROC = 0.696). LGB, RF, and XGB models also demonstrated excellent calibration, while other models indicated a lack of fit. All AI models showed superior overall net benefits, with LGB, RF, and XGB outperforming the others. The proposed LGB model demonstrated exceptional accuracy, excellent calibration, and superior overall net benefits. These advancements have the potential to assist healthcare professionals in advising women with a history of GDM and in developing preventive strategies to mitigate the adverse effects on maternal and fetal well-being.

Multicenter external validation of prediction models for clinical outcomes after spinal fusion for lumbar degenerative disease

BackgroundClinical prediction models (CPM), such as the SCOAP-CERTAIN tool, can be utilized to enhance decision-making for lumbar spinal fusion surgery by providing quantitative estimates of outcomes, aiding surgeons in assessing potential benefits and risks for each individual patient. External validation is crucial in CPM to assess generalizability beyond the initial dataset. This ensures performance in diverse populations, reliability and real-world applicability of the results. Therefore, we externally validated the tool for predictability of improvement in oswestry disability index (ODI), back and leg pain (BP, LP).MethodsProspective and retrospective data from multicenter registry was obtained. As outcome measure minimum clinically important change was chosen for ODI with ≥ 15-point and ≥ 2-point reduction for numeric rating scales (NRS) for BP and LP 12 months after lumbar fusion for degenerative disease. We externally validate this tool by calculating discrimination and calibration metrics such as intercept, slope, Brier Score, expected/observed ratio, Hosmer–Lemeshow (HL), AUC, sensitivity and specificity.ResultsWe included 1115 patients, average age 60.8 ± 12.5 years. For 12-month ODI, area-under-the-curve (AUC) was 0.70, the calibration intercept and slope were 1.01 and 0.84, respectively. For NRS BP, AUC was 0.72, with calibration intercept of 0.97 and slope of 0.87. For NRS LP, AUC was 0.70, with calibration intercept of 0.04 and slope of 0.72. Sensitivity ranged from 0.63 to 0.96, while specificity ranged from 0.15 to 0.68. Lack of fit was found for all three models based on HL testing.ConclusionsUtilizing data from a multinational registry, we externally validate the SCOAP-CERTAIN prediction tool. The model demonstrated fair discrimination and calibration of predicted probabilities, necessitating caution in applying it in clinical practice. We suggest that future CPMs focus on predicting longer-term prognosis for this patient population, emphasizing the significance of robust calibration and thorough reporting.

Developing an Emotional Labor Scale for Employees in the Service Industry

Purpose: This research aims to develop an emotional labor scale and examine the consistency of the emotional labor measurement model with empirical data. The study focuses on individuals with long-term work experience and incorporates cross-cultural perspectives to address gaps in current research. Additionally, it seeks to create a standardized model for measuring and evaluating emotional labor that is applicable to contemporary work environments. Methodology: The population is front-service employees of hotels in Chonburi Province, and the sample consists of 280 front-service employees of hotels in Pattaya City, Chonburi Province. The research methodology for developing the emotional labor scale in this phase is quantitative research, using confirmatory factor analysis to examine the consistency of the emotional labor measurement model. Findings: The results of the model fit analysis and quality assessment of the CFA model found that the RMSEA (Root Mean Square Error of Approximation) was 0.217, indicating a lack of fit between the model and data. The CFI (Comparative Fit Index) was 0.591. The TLI (Tucker-Lewis Index) was 0.442. Finally, the IFI (Incremental Fit Index) was 0.595. Based on the presented indices, this model has a poor fit with the data. The RMSEA, CFI, TLI, and IFI values are lower than the recommended criteria, indicating a discrepancy between the model and data. Unique Contribution to Theory, Policy and Practice: These findings suggest that current emotional labor measurement models may not accurately capture the experiences of workers across different cultures and with varying lengths of work experience. Policymakers and organizations should consider developing more nuanced and culturally sensitive approaches to assess and manage emotional labor in the workplace. This could involve creating tailored training programs, revising performance evaluation metrics, and implementing supportive policies that acknowledge the complexity of emotional labor across diverse work environments.

Experimental Analysis of Effect of Machined Material on Cutting Forces during Drilling.

Current research studies devoted to cutting forces in drilling are oriented toward predictive model development, however, in the case of mechanistic models, the material effect on the drilling process itself is mostly not considered. This research study aims to experimentally analyze how the machined material affects the feed force (Ff) during drilling, alongside developing predictive mathematical-statistical models to understand the main effects and interactions of the considered technological and tool factors on Ff. By conducting experiments involving six factors (feed, cutting speed, drill diameter, point angle, lip relief angle, and helix angle) at five levels, the drilling process of stainless steel AISI1045 and case-hardened steel 16MnCr5 is executed to validate the numerical accuracy of the established prediction models (AdjR = 99.600% for C45 and AdjR = 97.912% for 16MnCr5). The statistical evaluation (ANOVA, RSM, and Lack of Fit) of the data proves that the drilled material affects the Ff value at the level of 17.600% (p < 0.000). The effect of feed represents 44.867% in C45 and 34.087% in 16MnCr5; the cutting speed is significant when machining C45 steel only (9.109%). When machining 16MnCr5 compared to C45 steel, the influence of the point angle (lip relief angle) is lower by 49.198% (by 22.509%). The effect of the helix angle is 163.060% higher when machining 16MnCr5.

Facilitators of and barriers to County Behavioral Health System Transformation and Innovation: an interview study

BackgroundInadequate and inequitable access to quality behavioral health services and high costs within the mental health systems are long-standing problems. System-level (e.g., fee-for-service payment model, lack of a universal payor) and individual factors (e.g., lack of knowledge of existing resources) contribute to difficulties in accessing resources and services. Patients are underserved in County behavioral health systems in the United States. Orange County’s (California) Behavioral Health System Transformation project sought to improve access by addressing two parts of their system: developing a template for value-based contracts that promote payor-agnostic care (Part 1); developing a digital platform to support resource navigation (Part 2). Our aim was to evaluate facilitators of and barriers to each of these system changes.MethodsWe collected interview data from County or health care agency leaders, contracted partners, and community stakeholders. Themes were informed by the Consolidated Framework for Implementation Research.ResultsFive themes were identified related to behavioral health system transformation, including 1) aligning goals and values, 2) addressing fit, 3) fostering engagement and partnership, 4) being aware of implementation contexts, and 5) promoting communication. A lack of fit into incentive structures and changing state guidelines and priorities were barriers to contract development. Involving diverse communities to inform design and content facilitated the process of developing digital tools.ConclusionsThe study highlights the multifaceted factors that help facilitate or hinder behavioral health system transformation, such as the need for addressing systematic and process behaviors, leveraging the knowledge of leadership and community stakeholders, fostering collaboration, and adapting to implementation contexts.

Officer Perceptions of Mandatory Annual Physical Fitness Standards

One of the most important topics regarding law enforcement is officer fitness, or the larger concern, a lack thereof. Lack of fitness can be correlated to instances of inappropriate use of force and the public outcry of police brutality. Physical conditioning can directly assist an officer in achieving their main objective of every shift which is to go home healthy and safe. Increased fitness increases confidence and provides officers with a greater window of opportunity to de-escalate, showing the public that less drastic measures may be taken in handling stressful confrontations. Failure to set or maintain standards of fitness has in some cases, opened the door to civil litigation such as in Parker v District of Columbia where the proceedings showed that the District of Columbia was deliberately indifferent to physical standards resulting in significant financial compensation. Agencies should consider that an officer’s shift and work environment may indirectly lead to a lack of attention to health and fitness. A “complacency kills” approach may be able to outline the dangers of these lapses in standards but if a pathway cannot be created for these officers, then it may only reinforce the negative thought that they may not go home.

Optimization of the QuEChERS Extraction of Mycotoxins in Maize Using Response Surface Methodology (RSM)

Several methods have been developed for the analysis and detection of mycotoxins in food; however, most do not make use of critical statistics and mathematical tools for precise optimization. This study developed, optimized, and validated a modified quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction procedure for the extraction of multiple mycotoxins in maize and subsequent validation using liquid chromatography tandem mass spectrometry (LC–MS/MS). Central composite design (CCD) was used to optimize extraction conditions. Data analysis of full factorial screening experiments revealed that MeCN (%), FA (%), and extraction time significantly affected the mycotoxins recovery. Assessment of the statistical significance of the generated model using analysis of variance (ANOVA), coefficient tables, and surface plots showed the relative interactions of factors and the adequacy of the model. Thus, P values from the lack of fit (LOF) test ranged from 0.137– 0.467 and a composite desirability function of 0.91 was obtained. Using the optimum extraction conditions of 0.1% (v/v) FA in 80.2% MeCN for 74 min, 10 mycotoxins were effectively extracted with satisfactory recoveries (85–114%), coefficients of regression (R2 > 0.98), coefficients of variation (CVs < 15%), limit of quantifications (LOQs) (0.33–60.45 µg/kg), and other associated method validation parameters. The method validation was carried out according to Commission Implementing Regulation 2021/808 and Commission Regulation (EC) No 401/2006 of 23 February 2006. Application of this method to 20 maize samples collected from markets in Botswana showed detectable mycotoxins in 13 samples, with 2 exceeding the European Union (EU) maximum aflatoxin B1 (AFB1) limit, suggesting potential exposure to high levels of toxic mycotoxins in Botswana.

Food Systems Interventions for Nutrition: Lessons from 6 Program Evaluations in Africa and South Asia

Although there is growing global momentum behind food systems strategies to improve planetary and human health—including nutrition—there is limited evidence of what types of food systems interventions work. Evaluating these types of interventions is challenging due to their complex and dynamic nature and lack of fit with standard evaluation methods. In this article, we draw on a portfolio of 6 evaluations of food systems interventions in Africa and South Asia that were intended to improve nutrition. We identify key methodological challenges and formulate recommendations to improve the quality of such studies. We highlight 5 challenges: a lack of evidence base to justify the intervention, the dynamic and multifaceted nature of the interventions, addressing attribution, collecting or accessing accurate and timely data, and defining and measuring appropriate outcomes. In addition to more specific guidance, we identify 6 cross-cutting recommendations, including a need to use multiple and diverse methods and flexible designs. We also note that these evaluation challenges present opportunities to develop new methods and highlight several specific needs in this space.

Opioid Use Disorder Treatment Prescribers’ Views of Implementing an Electronic System to Collect Patient-Reported Outcomes Measures

Use of patient-reported outcomes measures (PROMs) may improve addiction treatment outcomes. This qualitative study investigated barriers and facilitators for PROMs implementation among prescribers of medications for opioid use disorder (MOUD) participating in AMNet, an addiction medicine practice-based research network. Semi-structured interviews were conducted with seven qualitative research participants of 57 AMNet providers. Interview data were analyzed thematically and coded using ATLAS.ti. Barriers included lack of electronic health record (EHR) integration; user interface issues; insufficient administrative support; challenges with patient engagement; and lack of fit with clinical practice. Facilitators included perceptions that PROMs use would improve outcomes and increase accountability while advancing addiction medicine. Patient-reported outcomes measures implementation is feasible in small outpatient MOUD practices, although resource constraints and technological barriers may reduce potential reach.

“I’m Just so Used to Seeing Men Succeeding”: Gender Inequality and the Glass Slipper of Success in the Events Industry

This mixed methods study investigated differences in men’s and women’s career success in the events industry. A “glass slipper” of success was identified that aligns more readily with some bodies/people than others. An online survey tested the extent to which this glass slipper “fits” men and women. Results illustrate that men are more successful than women on all measures, indicating that the glass slipper of success is gendered. Interviews were used to explore experiences of success (or otherwise) and to investigate the workings of the glass slipper. Women were often aware of their lack of fit, whereas men did not recognize the gendered norms that make it easier for them to have their merit acknowledged and rewarded. The gendered glass slipper contributes to ongoing gender inequality in the events industry, making it harder for women to be recognized???by themselves and others???as successful in their careers.

Exploring Volunteer Turnover Reasons, Intentions, and Behavior

Volunteer involving organizations (VIOs) play a vital role in many societies. Yet, turnover among volunteers remains a persistent struggle and VIOs still do not have a good understanding of why volunteers leave. In response, we employed a mixed-methods approach to explore why volunteers consider leaving. By coding textual responses of Australian State Emergency Services and Scouting volunteers ( n = 252 and 2235) on an annual engagement survey, we found seven overarching reasons to consider leaving these VIOs: Conflict, high demands and/or low resources, lack of fit, lack of inclusion, personal commitments and circumstances, poor communication and organizational practices, and poor leadership. When contrasted to the reasons that employees leave organizations for, the lack of inclusion and poor communication and organizational practices seem to be uniquely salient reasons that volunteers consider leaving for. Subsequently, guided by the Proximal Withdrawal States theory and using quantitative data from the Scouts sample, we investigated how reasons to consider turnover can predict turnover intentions and turnover behavior. First, volunteers in different withdrawal states cited different potential turnover reasons. For example, volunteers who ‘wanted to stay, but felt they had to leave’ cited personal commitments and circumstances more frequently than those in different withdrawal states. Second, we found that reasons to consider turnover explained little variance in turnover behavior one year later.

Prolific application of green synthesised CdS nanoparticles for the sequestration of cationic dyes from aqueous solution

Synthesis of cadmium sulfide (CdS) nanoparticles using watermelon rind aqueous extract was explored for its effectiveness in eliminating Methylene Blue (MB) and Crystal Violet (CV) dyes from water. The synthesised CdS nanoparticles were characterised with XRD, TEM and EDX and found to be around 10 nm in size with spherical shape. A central composite design was developed to optimise independent variables such as pH, contact time and initial concentrations. The developed quadratic model was found to be significant with p-value &lt;0.0001 and lack of fit &gt;0.005 suggesting the reliability of the model. Isotherm modelling analysis revealed that Langmuir and Freundlich's isotherms provided better explanation for the equilibrium data. The loading capacities of the CdS nanoparticles were found be 227.3 and 185.1 mg g-1, respectively for MB and CV. The experimental data showed a good fit with the pseudo-second-order kinetic model, indicating that chemical reactions were the determining factor in controlling the rate-limiting step. Thermodynamic analyses indicated that the process was spontaneous and exothermic. Desorption and regeneration investigations demonstrated that CdS nanoparticles could be successfully regenerated up to 5 times and reused in the adsorption process. The results conclude that the CdS nanoparticles are capable of remediating water containing cationic dyes.&#x0D; KEY WORDS: Watermelon rind, CdS nanoparticles, Synthetic dyes, Adsorption, RSM&#x0D; Bull. Chem. Soc. Ethiop. 2024, 38(3), 631-645. &#x0D; DOI: https://dx.doi.org/10.4314/bcse.v38i3.7

Comparing Designed Training Sets to Optimize Multivariate Regression Models for Pr, Nd, and Nitric Acid Using Spectrophotometry

Chemometric regression models were developed for the quantification of praseodymium (Pr, 0–1000 µg/mL), neodymium (Nd, 0–1000 µg/mL), and nitric acid (HNO3, 0.1–5 M) using spectrophotometry. Designed calibration sets were composed of 20 samples each: 10 model points and 10 lack-of-fit (LOF) points. The D-optimal designs effectively minimized the number of samples required to build models, and each design resulted in similar prediction performance, suggesting that statistical design of experiments can provide a reliable framework for selecting training set samples in three-variable systems. Partial least squares regression (PLSR) models were validated against a one-factor-at-a-time validation set composed of 125 samples (three variables, five levels). The top PLS-1 models resulted in average percent root mean square error of prediction error values of 3.5%, 1.7%, and 1.2% for Pr(III), Nd(III), and HNO3, respectively. Power set augmentations of the model and LOF samples were investigated to optimize the number of training set samples. PLSR models built using just required model points (10) had similar predictive capabilities as models including the LOF points (20) but with fewer samples. The number of validation samples was also varied systematically to learn how many samples are needed to validate regression models. This work addresses long-standing questions in the field of chemometrics to help make this approach amenable to the near-real-time quantification of hazardous species in remote settings.

The Futility of Language as a Means of Communication in Edward Albee’s Who’s Afraid of Virginia Woolf?, Fam and Yam, and The Sandbox

The three plays Who’s Afraid of Virginia Woolf? (1962) The Sandbox (1959) and Fam and Yam (1959) all display the absurdist tendencies to dispel the traditional view of language as the rational means of communication amongst mankind. In absurdist drama the world is portrayed as one that is meaningless and incomprehensible to the human mind. Language, which is confined to faulty human perception and subjectivity, is inefficient in the face of an unfathomable universe. A gap persists between the meanings in language and the world it purports to describe. In addition, the lack of fit between what language permits man to say and what he actually wants to say leads to a breakdown in communication and ultimately to the alienation of the individual. In absurdist works this chaotic sphere of existence is reflected in the dispensing of traditional elements in drama as well as in the illogical usage of language by the characters. Thus, absurdist drama acts as a counter-discourse to the previously dominant, essentialist discourse of realist drama. In this article a brief overview of the absurdist depiction of language’s insufficiency in communication is presented to serve as a backdrop for the analysis of certain segments in Albee’s aforementioned plays in order to assess the extent to which Albee’s plays demonstrate the absurdist’s notion of language’s deficiencies. Thus, the sections chosen for discussion are those that showcase language’s apparent shortcomings in generating human contact.

Generating optimal designs with user‐specified pure replication structure

AbstractOver recent decades, optimal experimental design has surged in popularity due to affordable computing and efficient algorithms. However, some researchers highlight that this focus has often side‐lined the importance of including pure experimental replication in designs, as many optimality criteria do not inherently suggest designs with replicates. In this study, we introduce an approach that allows the designer to input a desired replication structure into the optimal design search. We list all potential replication structures, indicate the corresponding budget for pure‐error (PE) and lack‐of‐fit (LOF) degrees‐of‐freedom, and use particle swarm optimization to search for the optimal design in each scenario. We demonstrate our approach on various unexplored ‐optimal design scenarios and several scenarios recently discussed in literature. Our findings reveal the existence of highly‐efficient ‐optimal designs with unique replication structures, offering designers informed choices on allocating a limited budget for PE and LOF degrees‐of‐freedom. This method is versatile and compatible with other optimizers, such as the coordinate exchange.

Advances in statistical methods for cancer surveillance research: an age-period-cohort perspective.

Analysis of Lexis diagrams (population-based cancer incidence and mortality rates indexed by age group and calendar period) requires specialized statistical methods. However, existing methods have limitations that can now be overcome using new approaches. We assembled a "toolbox" of novel methods to identify trends and patterns by age group, calendar period, and birth cohort. We evaluated operating characteristics across 152 cancer incidence Lexis diagrams compiled from United States (US) Surveillance, Epidemiology and End Results Program data for 21 leading cancers in men and women in four race and ethnicity groups (the "cancer incidence panel"). Nonparametric singular values adaptive kernel filtration (SIFT) decreased the estimated root mean squared error by 90% across the cancer incidence panel. A novel method for semi-parametric age-period-cohort analysis (SAGE) provided optimally smoothed estimates of age-period-cohort (APC) estimable functions and stabilized estimates of lack-of-fit (LOF). SAGE identified statistically significant birth cohort effects across the entire cancer panel; LOF had little impact. As illustrated for colon cancer, newly developed methods for comparative age-period-cohort analysis can elucidate cancer heterogeneity that would otherwise be difficult or impossible to discern using standard methods. Cancer surveillance researchers can now identify fine-scale temporal signals with unprecedented accuracy and elucidate cancer heterogeneity with unprecedented specificity. Birth cohort effects are ubiquitous modulators of cancer incidence in the US. The novel methods described here can advance cancer surveillance research.

Does the Practice of the European Convention on Human Rights Fit the Practical Conception of Human Rights?

Abstract This article investigates how the practice of European human rights, organised around the European Convention on Human Rights, can be brought into conversation with the practice conception of human rights advanced by Charles Beitz in the Idea of Human Rights. The article argues that this is a challenging task. Following Beitz’s construction of the human rights practice composed of (a) a global practice, (b) political discursive practice, (c) triggering a range of international action for corrective concern, (d) when states fail to protect urgent individual interests, the article identifies two main challenges: (1) the regional and legal-political character of the European human rights practice and (2) the lack of fit between the heuristic of urgency of individual interests and the European human rights practice. Having identified these challenges, however, I conclude that putting European human rights practice and the practice conception into a conversation reveals new knowledge at the intersection of moral and legal accounts of human rights. A closer engagement with the practice conception enables a better understanding of the key abstract features of European human rights practice. A closer engagement with this practice accentuates the normative case for making sense of predominantly legal and regional practices of human rights.