Excellent Model Research Articles

Activity-dependent dendrite patterning in the postnatal barrel cortex.

For neural circuit construction in the brain, coarse neuronal connections are assembled prenatally following genetic programs, being reorganized postnatally by activity-dependent mechanisms to implement area-specific computational functions. Activity-dependent dendrite patterning is a critical component of neural circuit reorganization, whereby individual neurons rearrange and optimize their presynaptic partners. In the rodent primary somatosensory cortex (barrel cortex), driven by thalamocortical inputs, layer 4 (L4) excitatory neurons extensively remodel their basal dendrites at neonatal stages to ensure specific responses of barrels to the corresponding individual whiskers. This feature of barrel cortex L4 neurons makes them an excellent model, significantly contributing to unveiling the activity-dependent nature of dendrite patterning and circuit reorganization. In this review, we summarize recent advances in our understanding of the activity-dependent mechanisms underlying dendrite patterning. Our focus lays on the mechanisms revealed by in vivo time-lapse imaging, and the role of activity-dependent Golgi apparatus polarity regulation in dendrite patterning. We also discuss the type of neuronal activity that could contribute to dendrite patterning and hence connectivity.

O12 Macrophages enhance angiogenesis in an induced pluripotent stem cell-derived skin organoid model

Abstract Introduction and aims Hair-bearing skin organoids (SkOs) are a complex three-dimensional (3D) model that faithfully recapitulates human skin as a multicellular organ with appendage structures. The development of such models provides unique potential for investigating human skin development and translational dermatology. Although this model answers many demands of an investigative tool, one obvious limitation is the absence of immune cells in SkOs. Our aim is to generate coculture systems of SkOs with macrophages to investigate how macrophages influence skin development. Methods Our group, and others, generated single-cell (sc)RNA-Seq and spatial transcriptomic datasets to thoroughly characterize human skin cell populations across the human lifespan. We used these datasets to compare the dynamic tempo of induced pluripotent stem cell (iPSC)-derived SkO (n = 84) differentiation with human prenatal (n = 15) and adult skin. For functional assays, we generated 2D angiogenesis coculture assays with macrophages and endothelial cells (n = 3) and 3D coculture of SkOs with macrophages (n = 3). Macrophages, endothelial cells and SkOs were all derived from the same iPSC line following established protocols. SkO vasculature was analysed after immunowholemount staining of CD31+ endothelial cells. Results Analysis of scRNA-Seq data highlighted a paucity in endothelial cell heterogeneity in SkOs compared with prenatal skin. We hypothesized that this could be explained by the absence of immune cells, as spatial transcriptomics microenvironment analysis of prenatal skin demonstrated that endothelial cells collocate with macrophages. With this in mind, we generated functional assays to investigate interactions of macrophages and endothelial cells in skin development. The 2D and 3D assays revealed that presence of macrophages significantly increased endothelial cell sprouting and network formation. Conclusions Our findings suggest a vital role of macrophages in skin morphogenesis, specifically in relation to the guidance of tip cells during angiogenesis. In addition, we present the SkO as an excellent complex model for investigating skin development, cell–cell interactions, and disease modelling for translational research in regenerative medicine and beyond.

Female proportion has a stronger influence on dispersal than body size in nematodes of mountain lakes.

Nematodes disperse passively and are amongst the smallest invertebrates on Earth. Free-living nematodes in mountain lakes are highly tolerant of environmental variations and are thus excellent model organisms in dispersal studies, since species-environment relationships are unlikely to interfere. In this study, we investigated how population or organism traits influence the stochastic physical nature of passive dispersal in a topologically complex environment. Specifically, we analyzed the influence of female proportion and body size on the geographical distribution of nematode species in the mountain lakes of the Pyrenees. We hypothesized that dispersal is facilitated by (i) a smaller body size, which would increase the rate of wind transport, and (ii) a higher female proportion within a population, which could increase colonization success because many nematode species are capable of parthenogenetic reproduction. The results showed that nematode species with a low proportion of females tend to have clustered spatial distributions that are not associated with patchy environmental conditions, suggesting greater barriers to dispersal. When all species were pooled, the overall proportion of females tended to increase at the highest elevations, where dispersal between lakes is arguably more difficult. The influence of body size was barely relevant for nematode distributions. Our study highlights the relevance of female proportion as a mechanism that enhances the dispersal success of parthenogenetic species, and that female sex is a determining factor in metacommunity connectivity.

A Study on Working Capital Management in Automotive chassis Manufacturing Pvt Ltd

The effective management of working capital is crucial for all companies. Key elements of working capital management include days sales outstanding (DSO), days inventory outstanding (DIO), days payable outstanding (DPO), and cash conversion cycle (CCC). A study conducted on 332 Czech companies, 20 of which were certified by the EFQM (European Foundation for Quality Management) Model, investigated how these components of working capital management impact a company's profitability. Two regression models were utilized for testing - pooled regression and maximum likelihood estimation (MLE). The results indicated that all components of working capital management have a negative effect on profitability. Interestingly, the interaction between EFQM certified companies and working capital components had a positive impact on profitability, suggesting a beneficial relationship between these components and profitability for certified firms. However, it was found that receiving a quality certificate/award from the EFQM Excellence Model actually decreased a company's profitability. Keywords Working capital, Firm profitability CCC, EFQM, Czech firms

Privacy-Preserving Breast Cancer Prediction Based on Logistic Regression

Abstract With the increasing strain on today’s healthcare resources, there is a growing demand for pre-diagnosis testing. In response, researchers have suggested diverse machine learning models for disease prediction, among which logistic regression stands out as one of the most effective models. Its objective is to enhance the accuracy and efficiency of pre-diagnosis testing, thereby alleviating the burden on healthcare resources. However, when multiple medical institutions collaborate to train models, the untrusted cloud server may pose a risk of private data leakage, enabling participants to steal data from one another. Existing privacy-preserving methods often suffer from drawbacks such as high communication costs, long training times and lack of security proofs. Therefore, it is imperative to jointly train an excellent model collaboratively and uphold data privacy. In this paper, we develop a highly optimized two-party logistic regression algorithm based on CKKS scheme. The algorithm optimizes ciphertext operations by employing ciphertext segmentation and minimizing the multiplication depth, resulting in time savings. Furthermore, it utilizes least squares to approximate sigmoid functions within specific intervals that cannot be handled by homomorphic encryption. Finally, the proposed algorithm is evaluated on a breast cancer dataset, and simulation experiments demonstrate that the model’s prediction accuracy, after machine learning training, exceeds 96% for two-sided encrypted data.

The development of an organizational excellence architecture model to support the implementation of business excellence

PurposeThe purpose of this study is to address a critical gap in the existing literature on business excellence implementation. While various studies have examined different aspects of business excellence, there is still a lack of comprehensive research on the optimal organizational excellence architecture (OEA) for an award-winning business excellence journey. The absence of a unified framework has led to inconsistent practices across organizations. The aim of this research based on data collected from 50 organizations across 17 countries is to address this gap and present a refined OEA model.Design/methodology/approachThis study employed quantitative and qualitative data collection methods. Member organizations from the Global Excellence Model (GEM) Council participated through an online survey administered via the Qualtrics software platform. Quantitative data were analyzed using the SPSS and Microsoft Excel software tools, while content analysis techniques were applied to the qualitative data to gain detailed insights.FindingsThe findings refine and extend the OEA model. These contributions lead to a refined OEA definition and open avenues for future research, enriching the current understanding of BE implementation.Originality/valueThis study introduces a novel concept of OEA to the literature on business excellence implementation. The refined OEA model provides a fresh perspective on the critical components necessary for an award-winning business excellence journey. This research offers significant value to both practitioners and academics by presenting a unified approach to BE implementation, effectively addressing the previously identified gap in BE research.

Pathogenic mechanisms and etiologic aspects of Mycobacterium avium subspecies paratuberculosis as an infectious cause of cutaneous melanoma.

Infectious etiologies have previously been proposed as causes of both melanoma and non-melanoma skin cancer. This exploratory overview explains and presents the evidence for the hypothesis that a microorganism excreted in infected ruminant animal feces, Mycobacterium avium subspecies paratuberculosis (MAP), is the cause of some cases of cutaneous melanoma (CM). Occupational, residential, and recreational contact with MAP-contaminated feces, soil, sand, and natural bodies of water may confer a higher rate of CM. Included in our hypothesis are possible reasons for the differing rates and locations of CM in persons with white versus nonwhite skin, why CM develops underneath nails and in vulvar skin, why canine melanoma is an excellent model for human melanoma, and why the Bacille Calmette-Guérin (BCG) vaccine has demonstrated efficacy in the prevention and treatment of CM. The pathogenic mechanisms and etiologic aspects of MAP, as a transmittable agent underlying CM risk, are carefully deliberated in this paper. Imbalances in gut and skin bacteria, genetic risk factors, and vaccine prevention/therapy are also discussed, while acknowledging that the evidence for a causal association between MAP exposure and CM remains circumstantial.

Classification of cervical lesions based on multimodal features fusion

Cervical cancer is a severe threat to women's health worldwide with a long cancerous cycle and a clear etiology, making early screening vital for the prevention and treatment. Based on the dataset provided by the Obstetrics and Gynecology Hospital of Fudan University, a four-category classification model for cervical lesions including Normal, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL) and cancer (Ca) is developed. Considering the dataset characteristics, to fully utilize the research data and ensure the dataset size, the model inputs include original and acetic colposcopy images, lesion segmentation masks, human papillomavirus (HPV), thinprep cytologic test (TCT) and age, but exclude iodine images that have a significant overlap with lesions under acetic images. Firstly, the change information between original and acetic images is introduced by calculating the acetowhite opacity to mine the correlation between the acetowhite thickness and lesion grades. Secondly, the lesion segmentation masks are utilized to introduce prior knowledge of lesion location and shape into the classification model. Lastly, a cross-modal feature fusion module based on the self-attention mechanism is utilized to fuse image information with clinical text information, revealing the features correlation. Based on the dataset used in this study, the proposed model is comprehensively compared with five excellent models over the past three years, demonstrating that the proposed model has superior classification performance and a better balance between performance and complexity. The modules ablation experiments further prove that each proposed improved module can independently improve the model performance.

Acceptability and Feasibility of Survivorship Group Medical Visits for Breast Cancer Survivors in a Safety Net Hospital.

Providing cost-effective, comprehensive survivorship care remains a significant challenge. Breast cancer survivors (BCS) who have limited income and are from marginalized racial and ethnic groups experience a worse quality of life and report higher distress. Thus, innovative care models are required to address the needs of BCSin low resource settings. Group medical visits (GMV), utilized in chronic disease management, are an excellent model for education and building skills. This single-arm intervention study was conducted at a public hospital in California. GMVs consisted of five 2-h weekly sessions focused on survivorship care planning, side effects of treatment and prevention, emotional health, sexual health, physical activity, and diet. The patient navigators recruited three consecutive GMV groups of six English-speaking BCS (N = 17). A multidisciplinary team delivered GMVs, and a patient navigator facilitated all the sessions. We used attendance rates, pre- and post-surveys, and debriefing interviews to assess the feasibility and acceptability of the intervention. We enrolled 18 BCS. One participant dropped out before the intervention started, 17 BCS consistently attended and actively participated in the GMV, and 76% (13) attended all planned sessions. Participants rated GMVs in the post-survey and shared their support for GMVs in debriefing interviews. The BCS who completed the post-survey reported that GMVs increased their awareness, confidence, and knowledge of survivorship care. GMVs were explicitly designed to address unmet needs for services necessary for survivorship care but not readily available in safety net settings. Our pilot data suggest that patient-navigator-facilitated GMVs are a feasible and acceptable model for integrating survivorship care in public hospitals.

Operational Reliability Analysis of Turbine Blisk Using an Enhanced Moving Neural Network Framework

As one of the key components of an aeroengine, turbine blisk endures complex coupling loads under a harsh operational environment so that the reliability of turbine blisk directly influences the safe operation of aeroengine. It is urgent to precisely perform the reliability estimation of a complex blisk structure. To address this issue, an enhanced Moving Neural Network Framework (MNNF) is proposed by integrating compact support region theory, improve sooty tern optimization algorithm (ISTOA), and Bayesian regularization strategy into artificial neural network. The compact support region theory is applied to select the efficient samples for modeling from the training samples set, the ISTOA is to determine the optimal compact support region, and Bayesian regularization thought is utilized to improve the generalization ability of neural network model. The operational reliability assessment of aeroengine blisk is performed with the consideration of transient loads to verify the proposed MNNF method. It is shown that the reliability degree of turbine blisk stain is 0.9984 when the allowable value is 5.2862 × 10−3 m. In line with the comparison of methods, the developed MNNF approach has 0.99738 in root means square error, 3.1634 × 10−4 m in goodness of fit, 0.423 s in modeling time, 99.99% in simulation precision, and 0.496 s in simulation time under 10,000 simulations, which are superior to all other methods (i.e., 99.96%, 99.91%, 99.93%, 99.97%, and 99.97% in simulation precision and 16.27%, 4.82%, 30.07%, 39.87%, and 23.59% in simulation efficiency, for the response surface method (RSM), Kriging, support vector machine (SVM), back propagation-artificial neural network (BP-NN), and BP-NN based on particle swarm optimization (BP-PSO) methods, respectively). It is demonstrated that the MNNF method holds excellent modeling and simulation performances. The efforts of this study provide promising tools and insights into the reliability design of complex structures, and enrich and develop reliability theory.

The Brilliance, Attitude, Leadership and Materials (BALM) framework of clinical excellence: an adoptable model for sub-Saharan Africa

Clinical excellence is the ability to provide rigorous, evidence-based, and rewarding care to the right patients. The BALM (brilliance, attitude, leadership, and materials) framework is a novel model for adjudicating clinical excellence. There are a few models and frameworks for evaluating clinical excellence, but each has its flaws and does not consider the peculiarities of economically-challenged regions such as sub-Saharan Africa. Coincidentally, such low-resource areas have an urgent need for a framework to assess clinical excellence because of their low health-related indices. The five-step model of professional excellence is a well-recognised tool and was the model upon which the BALM framework was built. So, the BALM framework determines to what extent, using the five-step stages of novice, advanced beginner, competent, proficient, and expert, a clinician has achieved in each of the four critical domains, namely brilliance, attitude, leadership, and materials. Therefore, a clinician, who strives for excellence, aims to be an “expert” in each of the domains of the BALM framework. The framework is concise, practical, easy to use, and multidimensional, although it still needs to be applied widely to assess its reproducibility.

An Introduction to ‘Agile for HR’ Through the Development of an Agile Operating Mindset

An understanding of Agile principles and a readiness mindset for human resources professionals play a crucial role in determining the application of Agile for HR in an organisational context. With the rise in extended and non-linear workforce configurations and geo-neutral team arrangements, Agile organisations necessitate that the nature of the HR function evolve from working through traditional architectural models and quickly adopting Agile models of functional excellence. The dearth of literature on understanding and implementing Agile practices in the HR function within enterprises requires a clear examination of the advantages of going Agile for HR. This essay explores the intuitive concept of Agile HR and operating schema, which can develop as a starting point in examining an understanding of how Agile practices in HR can evolve for sustainable enterprises and some challenges that are encountered.

Biomimetic Materials for Skin Tissue Regeneration and Electronic Skin.

Biomimetic materials have become a promising alternative in the field of tissue engineering and regenerative medicine to address critical challenges in wound healing and skin regeneration. Skin-mimetic materials have enormous potential to improve wound healing outcomes and enable innovative diagnostic and sensor applications. Human skin, with its complex structure and diverse functions, serves as an excellent model for designing biomaterials. Creating effective wound coverings requires mimicking the unique extracellular matrix composition, mechanical properties, and biochemical cues. Additionally, integrating electronic functionality into these materials presents exciting possibilities for real-time monitoring, diagnostics, and personalized healthcare. This review examines biomimetic skin materials and their role in regenerative wound healing, as well as their integration with electronic skin technologies. It discusses recent advances, challenges, and future directions in this rapidly evolving field.

Contribution of parasite and host genotype to immunopathology of schistosome infections

BackgroundThe role of pathogen genotype in determining disease severity and immunopathology has been studied intensively in microbial pathogens including bacteria, fungi, protozoa and viruses but is poorly understood in parasitic helminths. The medically important blood fluke Schistosoma mansoni is an excellent model system to study the impact of helminth genetic variation on immunopathology. Our laboratory has demonstrated that laboratory schistosome populations differ in sporocyst growth and cercarial production in the intermediate snail host and worm establishment and fecundity in the vertebrate host. Here, we (i) investigate the hypothesis that schistosome genotype plays a significant role in immunopathology and related parasite life history traits in the vertebrate mouse host and (ii) quantify the relative impact of parasite and host genetics on infection outcomes.MethodsWe infected BALB/c and C57BL/6 mice with four different laboratory schistosome populations from Africa and the Americas. We quantified disease progression in the vertebrate host by measuring body weight and complete blood count (CBC) with differential over a 12-week infection period. On sacrifice, we assessed parasitological (egg and worm counts, fecundity), immunopathological (organ measurements and histopathology) and immunological (CBC with differential and cytokine profiles) characteristics to determine the impact of parasite and host genetics.ResultsWe found significant variation between parasite populations in worm numbers, fecundity, liver and intestine egg counts, liver and spleen weight, and fibrotic area but not in granuloma size. Variation in organ weight was explained by egg burden and intrinsic parasite factors independent of egg burden. We found significant variation between infected mouse lines in cytokine levels (IFN-γ, TNF-α), eosinophils, lymphocytes and monocyte counts.ConclusionsThis study showed that both parasite and host genotype impact the outcome of infection. While host genotype explains most of the variation in immunological traits, parasite genotype explains most of the variation in parasitological traits, and both host and parasite genotypes impact immunopathology outcomes.Graphical

Chiral Self-Sorting, Spontaneous Resolution, and Hierarchical Self-Assembly in Metal-Organic Cages.

The ability to collectively program chiral recognition and the hierarchical self-assembly of molecular and supramolecular building blocks into complex higher-order superstructures is a significant goal in supramolecular chemistry. Metal-organic cages are excellent model systems to examine chiral self-sorting and build hierarchical self-assembly. Herein, details on how limiting the conformational flexibility and incorporating hydrogen bonding functional groups in the ligands can influence chiral self-sorting and hierarchical self-assembly of metal-organic cages are reported. The urea-functionalized axially chiral bis-pyridyl ligands afford high-fidelity in chiral self-sorting in Pd2L4 cages, when they have fewer conformations. Ligand L1, with more conformations, affords mixture of heterochiral and homochiral cages (≈70:30). Among them, the heterochiral cage adopts unusual twisted conformation and self-assembles into 2D sheets, linked by anion coordination between urea and nitrate. Ligand L2, with fewer conformations, affords homochiral cages via high-fidelity chiral self-sorting. The choice of counter anions influences further self-sorting in the solid state: racemate with PF6 - and spontaneously resolves conglomerate with BF4 -. Urea-BF4 hydrogen bonding directs hierarchical self-assembly of the Pd2L4 metal-organic cages into super-cubic networks. The study introduces a new approach in hierarchical self-assembly of metal-organic cages into higher-order networks aided by hydrogen bonding anion coordination with functional ligands.

Isolation and Structure Determination of New Pyrones from Dictyostelium spp. Cellular Slime Molds Coincubated with Pseudomonas spp.

Cellular slime molds are excellent model organisms in the field of cell and developmental biology because of their simple developmental patterns. During our studies on the identification of bioactive molecules from secondary metabolites of cellular slime molds toward the development of novel pharmaceuticals, we revealed the structural diversity of secondary metabolites. Cellular slime molds grow by feeding on bacteria, such as Klebsiella aerogenes and Escherichia coli, without using medium components. Although changing the feeding bacteria is expected to affect dramatically the secondary metabolite production, the effect of the feeding bacteria on the production of secondary metabolites is not known. Herein, we report the isolation and structure elucidation of clavapyrone (1) from Dictyostelium clavatum, intermedipyrone (2) from D. magnum, and magnumiol (3) from D. intermedium. These compounds are not obtained from usual cultural conditions with Klebsiella aerogenes but obtained from coincubated conditions with Pseudomonas spp. The results demonstrate the diversity of the secondary metabolites of cellular slime molds and suggest that widening the range of feeding bacteria for cellular slime molds would increase their application potential in drug discovery.

212 Growth and behavior of Yorkshire gilts exhibiting physiological resilience to weaning stress

Abstract Weaning is an acute early-life stressor and therefore, an excellent model for examining lasting impacts of stress resilience. Our objective was to identify gilts exhibiting physiological resilience or vulnerability to weaning stress and characterize long-term impact on growth and behavior. Purebred Yorkshire litters born to multiparous sows from a single farrowing group were used. At weaning (26 ± 1 d of age), blood samples were collected from all gilt piglets of 13 litters (n = 101) at -1 d, 0 d, and +4 d pre- and post-weaning. Serum cortisol concentrations were quantified by the Michigan State University Veterinary Diagnostic Laboratory. For each litter, serum cortisol was used to identify the gilt most capable of returning to baseline concentrations by +4 d as stress resilient (SR, n = 13) and the gilt least capable as stress vulnerable (SV, n = 13). Skin lesions were recorded at -1 d, +1 d, and +4 d at weaning and when gilts were mixed into grow-finish cohorts. Body weights were recorded at birth, 4 wk, 8 wk, and 12 wk and used to calculate average daily gain (ADG) for the farrowing, nursery, and early grow-finish stages. To assess behavior, focal gilts underwent a social dyad test in a novel arena at 7 wk, a handling test at 8 wk, and novel object test at 12 wk. We observed no differences in skin lesions at weaning, but at 8 wk SR gilts had significantly more rear lesions -1 d pre-mixing (P = 0.031) and middle lesions 4 d post-mixing (P = 0.049). No differences in body weight or ADG were observed at any stage. We did not observe differences between SR and SV pigs during the social dyad or handling tests. During the novel object test, SR gilts exhibited a tendency towards increased activity as demonstrated by a greater number of total zone crosses, 1 m line crosses, and 0.5 m line crosses (P = 0.062, 0.091, and 0.103, respectively). In conclusion, we found gilts resilient to weaning stress were involved in more agonistic behavior at mixing and exhibited increased activity levels in a novel situation. The absence of growth differences supports the potential to select for resilience without negatively impacting growth performance, and the observed behavioral differences could suggest implications for ease of handling and adaptability if females are retained for breeding.

Exploring the dynamic three-dimensional chromatin architecture and transcriptional landscape in goose liver tissues underlying metabolic adaptations induced by a high-fat diet

BackgroundGoose, descendants of migratory ancestors, have undergone extensive selective breeding, resulting in their remarkable ability to accumulate fat in the liver and exhibit a high tolerance for significant energy intake. As a result, goose offers an excellent model for studying obesity, metabolic disorders, and liver diseases in mammals. Although the impact of the three-dimensional arrangement of chromatin within the cell nucleus on gene expression and transcriptional regulation is widely acknowledged, the precise functions of chromatin architecture reorganization during fat deposition in goose liver tissues still need to be fully comprehended.ResultsIn this study, geese exhibited more pronounced changes in the liver index and triglyceride (TG) content following the consumption of the high-fat diet (HFD) than mice without significant signs of inflammation. Additionally, we performed comprehensive analyses on 10 goose liver tissues (5 HFD, 5 normal), including generating high-resolution maps of chromatin architecture, conducting whole-genome gene expression profiling, and identifying H3K27ac peaks in the livers of geese and mice subjected to the HFD. Our results unveiled a multiscale restructuring of chromatin architecture, encompassing Compartment A/B, topologically associated domains, and interactions between promoters and enhancers. The dynamism of the three-dimensional genome architecture, prompted by the HFD, assumed a pivotal role in the transcriptional regulation of crucial genes. Furthermore, we identified genes that regulate chromatin conformation changes, contributing to the metabolic adaptation process of lipid deposition and hepatic fat changes in geese in response to excessive energy intake. Moreover, we conducted a cross-species analysis comparing geese and mice exposed to the HFD, revealing unique characteristics specific to the goose liver compared to a mouse. These chromatin conformation changes help elucidate the observed characteristics of fat deposition and hepatic fat regulation in geese under conditions of excessive energy intake.ConclusionsWe examined the dynamic modifications in three-dimensional chromatin architecture and gene expression induced by an HFD in goose liver tissues. We conducted a cross-species analysis comparing that of mice. Our results contribute significant insights into the chromatin architecture of goose liver tissues, offering a novel perspective for investigating mammal liver diseases.

Human Capital Efficiency and Firm Performance of Quality-Certified Firms from EFQM Excellence Model: A Dynamic Panel Data Study

Abstract Purpose The study’s main purpose is to investigate the impacts of human capital efficiency (HCE) on the firm performance of non-certified and quality-certified firms from the European Foundation for Quality Management (EFQM) Excellence Model. The study also examines the relationship between firm performance and quality-certificates from the European Foundation. Design/methodology/approach By using a sample of 282 non-certified and 22 quality-certified firms from 2017 to 2021, the current study employed a two-step system generalized method of moments (GMM) estimation to analyse the empirical data. The dummy variable is used to examine the relationship between quality-certificates and firm performance. The dummy interaction term is employed to quantify the impacts of HCE on the firm’s performance for quality-certified firms. Findings The results revealed that quality-certificates and firm performance have a positive relationship. Quality-certified firms perform better and earn more profits than non-certified firms. HCE has a positive impact on firm performance for both types of firms. Moreover, the quality-certified firms utilize HCE in an efficient way to earn more profits compared to the non-certified firms. Originality This is the first study to use a comprehensive analysis to emphasize the HCE for non-certified and quality-certified firms separately. The effects of quality-certificates on firm performance in the context of HCE are also being highlighted for the first time in this research. Practical implications The current study’s findings are fruitful for academics, managers, researchers, policymakers, and other firm management. The findings will encourage the management of the firms to implement the total quality management (TQM) approach within their firms.

Automating Polysomnography in an Under-Explored Animal Model: Preliminary Results from Hibernating Bears

Animal hibernation is a hypometabolic state that may inform translational research to improve clinical outcomes for hypoxic patients whose oxygen supply does not match their demand. Bears are an excellent animal model, as they decrease their body temperature to only 30-35°C during hibernation and suppress their metabolism down to 25% of normal resting levels while having a more comparable physiology to humans than deep hibernators such as small rodents. As little is known about their sleep patterns during hibernation, we continuously monitored for more than 3500 days via biotelemetry a variety of physiological parameters from 16 captive American black bears in and out of hibernation. We recorded EEG, EOG and EMG signals that are commonly used to determine wake, REM sleep and NREM sleep vigilance states in conventional animal models (polysomnography). Such a data set is too large to fully annotate manually, so we compared two automated approaches. We first manually annotated two one-day recordings at body temperature extremes from each of 6 bears during hibernation when body temperatures were oscillating widely in multiday cycles with intermittent bouts of shivering (Tøien et al. 2011). We also manually scored a one-day, non-hibernating recording at normal (summer) body temperature from these bears. Based on this reference data set, we evaluated two automated scoring applications based on different machine learning classifiers: open source Somnotate (author Paul Brodersen), which is trained on multiple files, and proprietary Somnivore (author Giancarlo Allocca), which is trained on a subset of epochs from each individual recording. Somnotate gave best results during hold-one-out testing when using separate models for hibernating and non-hibernating data, and then performed comparably for both conditions. Somnivore was by design trained on a small subset (100 epochs of each kind) of each file to be tested. Both applications provided typical F-measures against manual reference scores in the 0.90-0.97 range. Outliers in the lower 0.72-0.88 range were highly correlated between the two applications, indicating that specific files are more challenging to annotate — either manually, automatically, or both. We conclude that both applications have accuracies on par with manual scorers when trained on high quality data. Supported by NIH COBRE under grant number [P20GM130443]. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.