Management Science Research Articles

Identification and analysis of JHBP/TO family genes and their roles in the reproductive fitness cost of resistance in Frankliniella occidentalis (Pergande)

The juvenile hormone binding protein (JHBP) and takeout (TO) genes, mediated by the juvenile hormone (JH), play a crucial role in regulating the reproductive physiology of insects. Our previous study revealed that spinosad-resistant Frankliniella occidentalis (NIL-R) exhibited reduced fecundity and significant changes in JHBP/TO family gene expression. We hypothesized that these genes were involved in regulating the fitness costs associated with resistance. In this study, 45 JHBP/TO genes were identified in F. occidentalis, among which FoTO2 and FoTO10 were duplicates. Additionally, eight genes exhibited significant down-regulation in the NIL-R population. Two genes (FoTO6 and FoTO24) that exhibited the most significant differential expression between the spinosad-susceptible (Ivf03) and NIL-R populations were selected to investigate their roles in resistance fitness using RNA interference (RNAi). Following interference with FoTO6, FoTO24, and their combination, the expression levels of vitellogenin (Vg) were downregulated by 3%–30%, 13%–28%, and 14%–32% from the 2nd day to the 5th day, respectively; Krüppel-homolog 1 (Kr-h1) expression was down-regulated by 3%–65%, 11%–34%, and 11%–39% from the 2nd day to the 5th day, respectively; ovariole length was shortened by approximately 18%, 21%, and 24%, respectively; and the average number of eggs decreased from 407 to 260, 148, and 106, respectively. Additionally, a JH supplementation experiment on the NIL-R population revealed that the expression levels of both FoTO6, FoTO24, Vg and Kr-h1 were significantly upregulated compared with those observed in the Ivf03 population, resulting in increased fecundity. These results suggest that FoTO6 and FoTO24 are involved in JH-mediated regulation of the reproductive fitness cost of resistance to spinosad. Further, FoTO6 and FoTO24 can be considered potential target genes for applying RNAi technology in the scientific management of F. occidentalis.

Developing ecological protection redline policy for land use pattern optimization in the typical black soil region of Northeastern China

Typical black soil regions in Northeastern China (TBSN) are facing problems of degradation of ecosystem services (ESs) and spatial conflicts between cropland and ecological land. Ecological Protection Redline (EPR) policy is one of the first national policies to utilizing multiple ESs. However, there is no standardized framework of delineation and validation for TBSN. In this study, the framework of Ecological Protection Redline delineation was further improved in three aspects of the ecosystem, namely, service function, ecological sensitivity, and biodiversity. Specifically, the framework considered the conflict between high-quality cropland and ecological land in the TBSN. We examined EPR effectiveness by comparing ESs and trade-off/synergistic relationships of different land use scenarios for 2035. The results show that 1) the EPR delineation threshold for each key indicator was determined to be 15%, considering the quality level of cropland. The ecological redline area of 89,593.63 km2 was identified, which was concentrated in the southwestern part of the Mengdong typical black soil subzone and Songnen typical black soil subzone. 2) Compared to the current ecological protection scenario and current ecological protection redline scenario, the optimized EPR scenario was the best solution to guarantee the sustainable development of the TBSN, maximizing ESs, weakening trade-offs, and strengthening synergistic relationships between them. The results of the study provided a theoretical basis for land use planning and the scientific management of ecosystems in the TBSN.

Overall and subgroup prevalence of self-reported asthma in US adults: a nationally representative cross-sectional study

Background The purpose of this study is to determine the variations in the prevalence of self-reported asthma among the adult population in the United States of America (USA), analyzing demographic characteristics, physical indicators, living habits, and sarcopenia. Methods 10,566 participants from the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) of the USA who were 20 years of age or older and not pregnant were included in the study. Results The prevalence of patients with asthma varies by age, gender, and race. The weighted prevalence is 15.5%, estimated to represent 19.36 million people in the USA (95% CI, 14.5% to 16.6%). The prevalence of self-reported asthma decreases with age, with the highest prevalence among young adults aged 20–25 for both males and females. Females were also more susceptible to asthma compared to males. The increase in asthma prevalence attributed to smoking was most pronounced among African American and Caucasian participants (p < 0.05), while its effect on Mexican American and Asian participants was relatively minor. Notably, the prevalence of asthma was significantly higher in African American and Caucasian participants with sarcopenia compared to those without sarcopenia. Conclusions The prevalence of asthma is associated to varying degrees with factors such as age, gender, smoking, and the presence of sarcopenia. The elevated prevalence of asthma among young people and females warrants attention. Intensifying efforts toward smoking cessation and the scientific management of sarcopenia could be instrumental in reducing the incidence of asthma.

Resilient riverine social–ecological systems: A new paradigm to meet global conservation targets

AbstractThe United Nations' Convention on Biological Diversity set forth the 30 × 30 target, an agenda for countries to protect at least 30% of their terrestrial, inland water, and coastal and marine areas by 2030. With &lt;6 years to reach that goal, riverine conservation professionals are faced with the difficult decision of prioritizing which rivers or river segments should be conserved (protected and/or restored). While incorporating resilience into conservation planning is essential for enhancing, restoring, and maintaining the vital riverine ecosystem services (ES) most threatened by climate change and other environmental and human stresses, this paradigm is at odds with traditional conservation approaches that are either opportunistic or reactionary, where only unique and highly visible ecosystems have been prioritized. Barriers to implementing resilience‐based riverine conservation planning include: (1) difficulties in conceptualizing and quantifying resilience; (2) insufficient consideration of the social components of riverine systems; (3) the inapplicability of terrestrial‐only conservation models to aquatic systems; and (4) the traditional ad hoc and opportunistic approach to conservation. To overcome these barriers, we propose a resilience‐based riverine conservation framework that includes: (1) assessing riverine resilience using indicator frameworks; (2) considering rivers as dynamically coupled social–ecological systems; (3) explicitly incorporating terrestrial–aquatic network connectivity into conservation decision‐making; and (4) strategic systems planning using a novel resilience–conservation matrix as a tool. This framework has the potential to transform conservation practices around the globe to more effectively protect river systems and enhance their resilience to climate change and human development.This article is categorized under: Water and Life &gt; Conservation, Management, and Awareness Science of Water &gt; Water and Environmental Change Human Water &gt; Water Governance

Analyzing the spatiotemporal habitat colonization dynamics of the common vole (Microtus arvalis Pallas) in Castilla y León, northwest Spain, using a hotspot-based approach†.

The common vole is an agricultural pest and population outbreaks have caused significant crop damage in the agricultural areas of the west-central part of the Iberian Peninsula (Spain) during the last few decades. Thus, monitoring is imperative to gain a comprehensive insight on its spatiotemporal habitat colonization dynamics. This work was performed on a long-term database with the primary objective of establishing an operational framework for understanding the spatial and temporal distribution of the common vole, all of it based on the Getis-Ord statistics. The temporal evolution of the vole abundance index (VAI) was consistent for the three studied habitats, that is, crops, reservoirs and paths. Furthermore, the majority of common vole abundance peaks coincide with summer periods, especially in annual herbaceous crops. The spatial distribution of vole abundance exhibited a non-random pattern, characterized by spatial clustering. Particularly, the areas with higher significance of this clustering were located at the so-called 'Tierra de Campos' county, covering northern Valladolid, southern Palencia and north-eastern Zamora provinces. Periods of major incidence and concentration were 2013-2014, 2016-2017 and 2019. Common vole temporal occupancy patterns demonstrate that colonization occurred simultaneously in alfalfa reservoirs and dispersion paths, both preceding settlement in annual herbaceous crop plots. The geographic information system (GIS)-hotspots-based methodology proposed here can be valuable for stakeholders involved in integrated management of the common vole, serving as a detector of pest-prone areas in both space and time. These hotspots are useful for predicting future surveillance areas that accurately reflect pest colonization patterns. It was found that common vole abundance along dispersal paths acts as a source of dissemination, preceding the risk of colonization in annual herbaceous crop plots. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Estimating evapotranspiration and drought dynamics of winter wheat under climate change: A case study in Huang-Huai-Hai region, China

Drought is one of the vital meteorological disasters that influence crop growth. Timely and accurately estimating the drought dynamics of crops is valuable for decision-maker to formulate scientific management measures of agricultural drought risk. In this study, the evapotranspiration and drought dynamics of winter wheat from 1981 to 2020 in the Huang-Huai-Hai (HHH) region of China were evaluated based on long-term multi-source observation data. Four key developmental stages of winter wheat were given attentions: growth before winter stage, overwintering stage, stage of greening-heading, and stage of filling-maturity. The crop water deficit index (CWDI) on a daily scale was established for quantitatively appraising the impacts of drought on winter wheat. Our results indicated that interannual variation in reference crop evapotranspiration (ET0) during the growth season of winter wheat from 1981 to 2020 in the HHH region showed a slight increase trend, with an average of 602.4 mm and obvious spatial differences of decreasing from the Northeast to the Southwest. Over the past forty years, the winter wheat in the HHH region was most severely affected by severe drought, followed by moderate drought, and finally mild drought. In addition, the impacts of drought on winter wheat at different critical growth stages varied greatly. For the growth before winter stage, the winter wheat was mainly threatened by mild, moderate, and severe droughts. For the overwintering stage, the winter wheat was mainly threatened by moderate, severe, and extreme droughts. For the greening-heading stage, the winter wheat was mainly threatened by mild, moderate, severe, and extreme droughts. For the filling-maturity stage, the winter wheat was mainly threatened by mild and moderate droughts. Finally, the impacts of drought on winter wheat during 1981–2020 in the HHH region were revealed to differ extraordinarily in space. In particular, the areas of winter wheat affected by severe drought significantly decreased. However, the areas of winter wheat affected by moderate drought clearly expanded. Our findings provide new insights for further improving climate change impact studies and agricultural drought defense capabilities adapting to continuous environmental change.

A detection method of Auricularia auricula mycelium storage period based on near-infrared spectral characteristics and deep learning model

The storage time of Auricularia auricula mycelium was an important factor influencing its growth activity. The rapid detection of storage time had important theoretical significance and practical value for evaluating, cultivating, and scientifically managing Auricularia auricula germplasm resources. Due to the problem of mapping the relationship between the complex near-infrared (NIR) spectral characteristics of Auricularia auricula mycelium and its storage period, it was difficult to characterize using mathematical models accurately. In this paper, a method for detecting the storage period of Auricularia auricula mycelium based on NIR spectral characteristics and deep learning was proposed. First, five different storage periods of Auricularia auricula mycelium were taken as the research object, and the de-trending (DT) algorithm was used to pre-process the spectral data. Then, the Competitive Adaptive Reweighted Sampling (CARS) algorithm was applied to extract the NIR spectral characteristics of the mycelium. The reduction rate of the spectral variables reached 94.64 %. Further, a one-dimensional convolutional neural network (T-CNN) was constructed, and the SGD-Adam algorithm was used to calculate the optimal network parameters. Finally, a method for detecting the storage period of Auricularia auricula mycelium was implemented, achieving a simulation accuracy of 98.33 %. The experimental results revealed that this method outperformed traditional machine learning models such as partial least squares-discriminant analysis (PLS-DA), back propagation (BP), support vector machine (SVM), and k-nearest neighbors (KNN) by an average of 19.56 % in detection accuracy. Additionally, the detection speed was only 0.07 s. This achievement enabled rapid and accurate detection of the storage time of Auricularia auricula mycelium, providing a dependable foundation for identifying the growth activity of Auricularia auricula mycelium. It provided technical support for the scientific management of the edible fungus mycelium, including quality monitoring, evaluation, and screening.

AI’s effect on innovation capacity in the context of industry 5.0: a scoping review

The classic literature about innovation conveys innovation strategy the leading and starting role to generate business growth due to technology development and more effective managerial practices. The advent of Artificial Intelligence (AI) however reverts this paradigm in the context of Industry 5.0. The focus is moving from “how innovation fosters AI” to “how AI fosters innovation”. Therefore, our research question can be stated as follows: What factors influence the effect of AI on Innovation Capacity in the context of Industry 5.0? To address this question we conduct a scoping review of a vast body of literature spanning engineering, human sciences, and management science. We conduct a keyword-based literature search completed by bibliographic analysis, then classify the resulting 333 works into 3 classes and 15 clusters which we critically analyze. We extract 3 hypotheses setting associations between 4 factors: company age, AI maturity, manufacturing strategy, and innovation capacity. The review uncovers several debates and research gaps left unsolved by the existing literature. In particular, it raises the debate whether the Industry5.0 promise can be achieved while Artificial General Intelligence (AGI) remains out of reach. It explores diverging possible futures driven toward social manufacturing or mass customization. Finally, it discusses alternative AI policies and their incidence on open and internal innovation. We conclude that the effect of AI on innovation capacity can be synergic, deceptive, or substitutive depending on the alignment of the uncovered factors. Moreover, we identify a set of 12 indicators enabling us to measure these factors to predict AI’s effect on innovation capacity. These findings provide researchers with a new understanding of the interplay between artificial intelligence and human intelligence. They provide practitioners with decision metrics for a successful transition to Industry 5.0.

Concept analysis of patient journey disruptions: the obstacle of integrated care

PurposeThis article aims to clarify the concepts used to understand, analyze and improve a patient’s progress through a health service system. A patient pathway describes plans and intentions. Within it, we distinguish between the clinical pathway of decisions and interventions and the care pathway of supportive activities. As a patient pathway is implemented, it turns into a patient journey of what is done, what happens to a patient’s medical condition and what is experienced and felt. We introduce “patient journey disruption” (PJD) as a concept describing the events that need to be prevented from happening to accomplish integrated, coordinated and seamless care.Design/methodology/approachThe method used in this paper is concept analysis. First, an expert steering group worked to refine the concept of PJDs; second, an analysis of similar concepts from related fields was done to root the concept into existing theories, and third, semi-structured interviews with professionals and patients were done to test the concept of PJDs in the home care context.FindingsPJDs are agency-based harmful events in the execution of the care pathway that deviate the patient journey from what can be reasonably expected. PJDs are management failures, which is why they should be studied by healthcare operations management (HOM) and service science scholars with the intention to find ways to prevent them from happening.Research limitations/implicationsThis study has limitations, including presenting conceptual ideas and preliminary results that are only indicative.Practical implicationsWe believe that the introduction of the concept of PJDs into the literature provides a new, systematic way of approaching the different shortcomings in our healthcare production systems. Moreover, by systematically identifying different PJDs, interventions can be designed and targeted more appropriately.Originality/valueManagerial challenges regarding healthcare processes have been studied but have not been well defined. The concept of PJDs is an original, well-thought-out definition.

Exploring SDHI fungicide resistance in Botrytis cinerea through genetic transformation system and AlphaFold model-based molecular docking.

Gray mold caused by Botrytis cinerea is one of the most serious diseases affecting strawberry. Succinate dehydrogenase inhibitor (SDHI) fungicides have been used for more than a decade to control the disease. Monitoring resistance and improving in-depth understanding of resistance mechanisms are essential for the control of B. cinerea. In this study, resistance monitoring of a SDHI fungicide boscalid was conducted on B. cinerea isolated from strawberries in Korea during 2020 and 2021, with resistance rates of 76.92% and 72.25%, respectively. In resistant strains, mutations P225F/H and H272R were found in SdhB, with P225F representing the dominant mutation type. Simultaneous mutations G85A, I93V, M158V, and V168I in SdhC were detected in 54.84% of sensitive strains. Sensitivity profiles of different Sdh genotypes of B. cinerea strains to six SDHIs were determined in vitro and in vivo. In addition, the mutation(s) were genetically validated through in situ SdhB (SdhC) expression. Docking assays between SDHIs and AlphaFold model-based Sdh complexes revealed generally consistent patterns with their in vitro phenotypes. Resistance of B. cinerea to SDHI fungicide on strawberry was systematically investigated in this study. Deciphering of SDHI resistance through the genetic transformation system and AlphaFold model-based molecular docking will provide valuable insights into other target site-based fungicide resistance in fungal pathogens. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The sublethal impacts of five insecticidal formulations on Oryzaephilus surinamensis behavioral traits.

Mortality caused by various pyrethroids, and neonicotinoids has been studied for stored-product insects in the past, yet limited information exists on the sublethal effects they can induce to Oryzaephilus surinamensis. In the current study, the sublethal effects of deltamethrin, λ-cyhalothrin, α-cypermethrin, etofenprox, and the mixture of acetamiprid with d-tetramethrin and piperonyl butoxide on the mobility of O. surinamensis in the presence or the absence of a food source was investigated. Lethal concentrations (LCs) were lower for deltamethrin, α-cypermethrin, and λ-cyhalothrin (LC10 = 0.000233, 0.000211, and 0.000271 mg active ingredient (a.i.) cm-2, LC30 = 0.000413, 0.000398, and 0.000447 mg a.i. cm-2, respectively), followed by etofenprox, and the mixture of acetamiprid with d-tetramethrin and piperonyl butoxide (LC10 = 0.00228 and 0.003267 mg a.i. cm-2, LC30 = 0.00437 and 0.01188 mg a.i. cm-2, respectively). Deltamethrin and λ-cyhalothrin negatively impacted adult walking behavior, increasing stop durations compared to controls. Adults exposed to LC10 and LC30 of λ-cyhalothrin, and LC30 of deltamethrin exhibited prolonged periods on their backs compared to the remaining treatments and the controls. The α-cypermethrin LC30-exposed adults exhibited significantly shorter walking and stopping durations than controls but demonstrated prolonged climbing on the arena walls compared to adults exposed to the remaining a.i. and the control. A similar trend was observed for etofenprox. Under sublethal concentrations, λ-cyhalothrin and deltamethrin increased stop intervals and reduced the duration of climbing attempts of O. surinamensis versus α-cypermethrin. These findings advance comprehension of the underexplored sublethal impacts of the tested a.i. on O. surinamensis adults, holding potential for leveraging insecticide-induced behavioral effects to enhance warehouse pest management. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Association between preconception body mass index and fertility in adult female: A systematic review and meta-analysis.

Obesity potentially reduces fertility, but systematic reviews are lacking to summarize the existing literature. Therefore, we systematically summarized the association between preconception body mass index (BMI) and fertility in adult female based on existing reports. Up to September 2023, we conducted literature retrievals in different databases, including Web of Science, PubMed, Wiley, and ScienceDirect. Finally, 18 studies were included. Female with overweight/obesity (FOR = 0.85; 95% CI: 0.80, 0.90), obesity (FOR = 0.76; 95% CI: 0.69, 0.83), and overweight (FOR = 0.93; 95% CI: 0.88, 0.99) was associated with the significant time-to-pregnancy (TTP) prolongation (reduced fecundability). Interestingly, underweight was moderately associated with prolonged TTP in females (FOR = 0.95; 95% CI: 0.91, 0.99). Female overweight/obesity was associated with an increased risk of subfecundity (OR = 1.44; 95% CI: 1.20, 1.72) and infertility (OR = 1.60, 95% CI: 1.31-1.94). The findings emphasize the importance of considering appropriate preconception BMI at the population level for female fertility outcomes. In particular, prepregnancy obesity in females is strongly associated with prolonged TTP and increased risk of subfecundity. Scientific management of preconception BMI may improve fertility.

Metrology for sensor networks: metrological traceability and measurement uncertainties for air quality monitoring

Abstract In situ calibration of sensors delivering SI traceable measurement results still provides an open question to the design and operation of sensor networks. Particularly when addressing low-cost sensors, currently, the use of sensor networks for air quality monitoring is limited by the low or unknown accuracy of measurements that they can achieve, while the data quality of individual sensor networks is mainly derived by algorithms. Standardization bodies like DIN and CEN therefore announced the need for investigations of validation methods on gas phase species and particulate matter on the one hand side, and for the development of fully digitized quality assurance/quality control and calibration techniques for sensor networks on the other (CEN/CENELEC, Opportunity for Standardisation to Contribute to the European Partnership on Metrology EPM under Horizon Europe). This contribution concentrates on the metrological traceability of sensor networks for air quality monitoring to the international system of units (SI) based on FAIRified intra-network communications (M. Wilkinson, et al., “The FAIR guiding principles for scientific data management and stewardship,” Sci. Data, vol. 3, 2016, Art. no. 160018) and including delocalized Optical Gas Standards operated according to the digital TILSAM method (O. Werhahn, et al., The TILSAM Method Adapted into Optical Gas Standards – Complementing Gaseous Reference Materials, PTB Open Access Repository, 2021). Informed by related activities in EURAMET (Partnership project FunSNM, EMNs COO &amp; POLMO, TC-IM 1551) (European Metrology Network Climate and Ocean Observation (COO), European Metrology Network Pollution Monitoring (POLMO), EURAMET Project TC-IM 1551, Project Database) this contribution discusses the importance of measurement uncertainties in the context of sensor networks, comprising different sensor principles and promoting an efficient uptake of state-of-the-art methods. We discuss how the sensor network case can be addressed with sensors individually using the GUM principles (Joint Committee for Guides in Metrology, Guide to the Expression of Uncertainty in Measurement (GUM), JCGM 100: 2008 (E)). For sensor network measurements becoming metrologically traceable to the SI, documented and unbroken chains of calibrations need to be implemented each contributing to the measurement uncertainty. This applies to each individual sensor of the network including the potential gold standard among them, but also to the network’s output viewed as a single entity. The contribution provides first approaches to be tested and validated that are underpinned by fundamental design strategies for sensor networks. It follows on practical applications in real world scenarios aside from model uncertainties discussed in artificial intelligence prospects.

Endophytic entomopathogenic fungi as biological control agents of insect pests.

Entomopathogenic fungi capable of establishing mutualistic endophytic relationships with plants have a tremendous potential as biocontrol agents of insect pests. While fungi have long played an important and highly effective role in pest suppression, the utility of endophytic entomopathogenic fungi in pest management is a relatively new and emerging topic of biocontrol. Here we discuss the relevance of endophytic fungi to plant health in general, synthesize the current knowledge of the effectiveness of endophytic entomopathogenic fungi against diverse insect pests, discuss the indirect plant-mediated effects of endophytic entomopathogenic fungi on arthropods, and describe the diverse benefits of endophytic fungi to plants that are likely to affect herbivores and plant pathogens as well. Lastly, we consider major challenges to incorporating endophytic entomopathogenic fungi in biocontrol, such as their non-target effects and field efficacy, which can be variable and influenced by environmental factors. Continued research on endophyte-insect-plant-environment interactions is critical to advancing our knowledge of these fungi as a sustainable pest management tactic. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Koszmar menedżera? Wstępne uwagi dotyczące możliwości zarządzania fandomami

Management more and more often turns to the organization as the subjects of its activities in their functional aspect, not the material one. One of such spaces are virtual communities, including fandoms. However, the achievements of fan studies dealing with them have relatively rarely appeared in management sciences so far. In order to determine the state of scientific considerations related to the management of fandoms, a study of the available literature was carried out, covering the leading scientific journals from the list prepared by the Polish Ministry of Education and Science in the field of management sciences, as well as cultural and religious studies, which deal with topics related to management, and thirdly from the Scopus database. Therefore, the article is of a review nature and its main purpose is to indicate the research gap for the issue of fandom management. Therefore, it constitutes a preliminary diagnosis of the current state of research and seeks an answer to the question: does the issue of fandom management appear in the researched scientific journals? The answer to this question remains essentially negative – although some of the topics discussed in the journals are related to the selected issue, the leading titles included in the list of the Ministry of Education and Science so far lack a comprehensive analysis of it. They appear in journals indexed in the Scopus database and in other publications (e.g. monographs). This situation means a specific lack of systemic support for the entry of texts dealing with fandom management into the mainstream of Polish scientific research.

Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities.

In an environment, microbes often work in communities to achieve most of their essential functions, including the production of essential nutrients. Microbial biofilms are communities of microbes that attach to a nonliving or living surface by embedding themselves into a self-secreted matrix of extracellular polymeric substances. These communities work together to enhance their colonization of surfaces, produce essential nutrients, and achieve their essential functions for growth and survival. They often consist of diverse microbes including bacteria, viruses, and fungi. Biofilms play a critical role in influencing plant phenotypes and human microbial infections. Understanding how these biofilms impact plant health, human health, and the environment is important for analyzing genotype-phenotype-driven rule-of-life functions. Such fundamental knowledge can be used to precisely control the growth of biofilms on a given surface. Metagenomics is a powerful tool for analyzing biofilm genomes through function-based gene and protein sequence identification (functional metagenomics) and sequence-based function identification (sequence metagenomics). Metagenomic sequencing enables a comprehensive sampling of all genes in all organisms present within a biofilm sample. However, the complexity of biofilm metagenomic study warrants the increasing need to follow the Findability, Accessibility, Interoperability, and Reusable (FAIR) Guiding Principles for scientific data management. This will ensure that scientific findings can be more easily validated by the research community. This study proposes a dockerized, self-learning bioinformatics workflow to increase the community adoption of metagenomics toolkits in a metagenomics and meta-transcriptomics investigation. Our biofilm metagenomics workflow self-learning module includes integrated learning resources with an interactive dockerized workflow. This module will allow learners to analyze resources that are beneficial for aggregating knowledge about biofilm marker genes, proteins, and metabolic pathways as they define the composition of specific microbial communities. Cloud and dockerized technology can allow novice learners-even those with minimal knowledge in computer science-to use complicated bioinformatics tools. Our cloud-based, dockerized workflow splits biofilm microbiome metagenomics analyses into four easy-to-follow submodules. A variety of tools are built into each submodule. As students navigate these submodules, they learn about each tool used to accomplish the task. The downstream analysis is conducted using processed data obtained from online resources or raw data processed via Nextflow pipelines. This analysis takes place within Vertex AI's Jupyter notebook instance with R and Python kernels. Subsequently, results are stored and visualized in Google Cloud storage buckets, alleviating the computational burden on local resources. The result is a comprehensive tutorial that guides bioinformaticians of any skill level through the entire workflow. It enables them to comprehend and implement the necessary processes involved in this integrated workflow from start to finish. This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

Myzus persicae resistance to neonicotinoids-unravelling the contribution of different mechanisms to phenotype.

Deciphering the mechanisms underlying insecticide resistance is key to devising appropriate strategies against this economically important trait. Myzus persicae, the green peach-potato aphid, is a major pest that has evolved resistance to many insecticide classes, including neonicotinoids. M. persicae resistance to neonicotinoids has previously been shown to result from two main mechanisms: metabolic resistance resulting from P450 overexpression and a targetsite mutation, R81T. However, their respective contribution to resistant phenotypes remains unclear. By combining extensive insecticide bioassays with and without addition of the synergist PBO, and gene copy number and expression quantification of two key P450 enzymes (CYP6CY3 and CYP6CY4) in a 23 clone collection, we, (i) confirmed that metabolic resistance is correlated with P450 expression level, up to a threshold, (ii) demonstrated that the R81T mutation, in the homozygous state and in combination with P450 overexpression, leads to high levels of resistance to neonicotinoids, and, (iii) showed that there is a synergistic interaction between the P450 and R81T mechanisms, and that this interaction has the strongest impact on the strength of resistance phenotypes. However, even though the R81T mutation has a great effect on the resistance phenotype, different R81T genotypes can exhibit variation in the level of resistance, explained only partially by P450 overexpression. To comprehend resistance phenotypes, it is important to take into account every mechanism at play, as well as the way these mechanisms interact. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

„Sternicy mediów”. Opis projektu, kwestie metodologiczne

This article describes the “Media Helmsmen” research project, which primary goal was the analysis of the influence of leaders of media organizations on shaping the media market in Poland after 1989. The project began in 2013 during the “Humanistic Management” conference at Jagiellonian University, and was inspired by the idea presented by the late professor Barbara Czarniawska. Even though professor Czarniawska did not conduct her study in Sweden as it was planned, in Poland extensive research material was collected. It allowed the identification of key dilemmas in organizational management media organizations. The article presents the basic research assumptions of the project, including the main research questions: how is the leadership viewed in relation to media organizations? Who exactly is the media helmsman? What are its features? The authors point to the multi-paradigmatic nature of management sciences and emphasize the importance of both theoretical and practical aspects of research. The article includes a brief description of the research process, which is presented in detail in the monograph titled “Media Helmsmen”.

At War with the Machine: Canadian Workers' Resistance to Taylorism in the Early 20th Century

This essay looks at the ways Frederick Winslow Taylor’s modern theories of scientific management (Taylorism) transformed Canadian workplaces in the early 20th century. In particular, it shows how Taylorism negatively impacted Canadian workers’ lives,and examines the various ways that workers consequently resisted Taylorist methods. The essay argues that although workers were unable to stop the widespread implementation of Taylorism in Canadian workplaces, their resistance to Taylorism still played an important role in unionist and radical political movements that gradually gained important concessions for Canadian workers during the first half of the 20th century. Additionally, the essay argues that resistance was significant as an outlet for workers to retain bodily autonomy in work environments that increasingly aimed to make workers more automated. Ultimately, the essay highlights important ways that the Canadian working classes have exercised agency via solidarity and perseverance.

Interactions between the context of a health-care organisation and failure: the situational impact of failure on organisational learning

PurposeThis study aims to explore how health-care organisations learn from failures, challenging the common view in management science that learning is a continuous cycle. It focuses on understanding how the context of a health-care organisation and the characteristics of failure interact.Design/methodology/approachSystematically collected empirical studies that examine how health-care organisations react to failures, both in terms of learning and non-learning, were reviewed and analysed. The key characteristics of failures and contextual factors are categorised at the individual, team, organisational and global level.FindingsSeveral factors across four distinct levels are identified as being susceptible to the situational impact of failure. In addition, these factors can be used in the design and development of innovations. Taking these factors into account is expected to stimulate learning responses when an innovation does not succeed. This enhances the understanding of how health-care organisations learn from failure, showing that learning behaviour is not solely dependent on whether a health-care organisation possesses the traits of a learning organisation or not.Originality/valueThis review offers a new perspective on organisational learning, emphasising the situational impact of failure and how learning occurs across different levels. It distinguishes between good and bad failures and their effects on a health-care organisation’s ability to learn. Future research could use these findings to study how failures influence organisational performance over time, using longitudinal data to track changes in learning capacity.