Complex Approach Research Articles

Determination of endometrial cancer molecular subtypes using a whole exome-sequencing based single-method approach

AimEndometrial cancer (EC) is heterogeneous with respect to epidemiology, clinical course, histopathology and tumor biology. Recently, The Cancer Genome Atlas (TCGA) network has identified four molecular subtypes with distinct clinical courses by an integrated multi-omics approach. These subtypes are of critical importance in the clinical management of EC. However, determination of TCGA molecular subtypes requires a complex methodological approach that is resource intensive and difficult to implement in diagnostic routine procedures. In this context, Talhouk et al. reported the precise determination of modified subtypes based on molecular surrogates obtained by a two-method approach comprising immunohistochemistry and DNA-sequence analysis (Proactive Molecular Risk Classifier for Endometrial Cancer; ProMisE). In this study, we aimed to identify EC molecular subtypes in analogy to TCGA and ProMisE applying an innovative whole exome-sequencing (WES) based single-method approach.MethodsWES was performed in a cohort comprising N = 114 EC patients. WES data were analyzed using the oncology treatment decision support software MH Guide (Molecular Health, Heidelberg, Germany) and EC molecular subtypes in analogy to TCGA and ProMisE were determined. Results from both classifications were compared regarding their prognostic values using overall survival and progression-free survival analyses.ResultsApplying a single-method WES-approach, EC molecular subtypes analogue to TCGA and ProMisE were identified in the study cohort. The surrogate marker-analogue classification precisely identified high-risk and low-risk EC, whereas the TCGA-analogue classification failed to obtain significant prognostic values in this regard.ConclusionOur data demonstrate that determination of EC molecular subtypes analogue to TCGA and ProMisE is feasible by using a single-method WES approach. Within our EC cohort, prognostic implications were only reliably provided by applying the surrogate marker-analogue approach. Designation of molecular subtypes in EC will be increasingly important in routine clinical practice. Thus, the single-method WES approach provides an important simple tool to tailor therapeutic decisions in EC.

МОНИТОРИНГ КАЧЕСТВА АТМОСФЕРНОГО ВОЗДУХА ЗАПАДНО-КАЗАХСТАНСКОГО РЕГИОНА: ПРИНЦИПЫ, МЕТОДЫ, ПОДХОДЫ

The main approaches and methods of studying the characteristics and conditions of atmospheric pollution on the example of Western Kazakhstan are considered. The classification and grouping of applied approaches by topics, methods, time intervals and other relevant criteria was conducted. An analysis of the available information on the sources and volumes of emissions into the atmosphere, as well as on the systems for monitoring the pollution of the air basin, was carried out. It is shown that to increase the effectiveness of the atmospheric air quality management system, it is expedient to use a complex approach taking into account the influence of meteorological factors and synoptic conditions that determine different levels of pollution. An analytical review of modern methods of modeling the spread of pollutants in atmospheric air showed the feasibility of using statistical methods integrated with deep machine learning and the Eulerian continuum model of turbulent diffusion. The obtained conclusions will allow further use of an integrated approach to improve the atmospheric air quality management system of the studied region.

FedGMMAT: Federated generalized linear mixed model association tests.

Increasing genetic and phenotypic data size is critical for understanding the genetic determinants of diseases. Evidently, establishing practical means for collaboration and data sharing among institutions is a fundamental methodological barrier for performing high-powered studies. As the sample sizes become more heterogeneous, complex statistical approaches, such as generalized linear mixed effects models, must be used to correct for the confounders that may bias results. On another front, due to the privacy concerns around Protected Health Information (PHI), genetic information is restrictively protected by sharing according to regulations such as Health Insurance Portability and Accountability Act (HIPAA). This limits data sharing among institutions and hampers efforts around executing high-powered collaborative studies. Federated approaches are promising to alleviate the issues around privacy and performance, since sensitive data never leaves the local sites. Motivated by these, we developed FedGMMAT, a federated genetic association testing tool that utilizes a federated statistical testing approach for efficient association tests that can correct for confounding fixed and additive polygenic random effects among different collaborating sites. Genetic data is never shared among collaborating sites, and the intermediate statistics are protected by encryption. Using simulated and real datasets, we demonstrate FedGMMAT can achieve the virtually same results as pooled analysis under a privacy-preserving framework with practical resource requirements.

Structural analysis of the dynamic response of a shape memory alloy based damper

Shape memory alloys (SMAs) are promising candidates for use in sensors, actuators, or passive dampers. This paper investigates the dynamic response of a superelastic NiTi holed disk to assess its damping performance relative to frequency and temperature for SMA-based damper applications. This study involved several key steps. Initially, the superelastic behavior of the SMA was experimentally characterized through tensile tests. This testing campaign provided the required data to identify material parameters of a thermomechanical constitutive model, already implemented in the finite element code Abaqus. Using the identified parameters, a finite element based structural analysis was conducted to predict the disk’s operational range, ensuring it remained within the superelastic domain without incurring potential damage. Following this static analysis, a dynamic mechanical analysis (DMA) was performed on the disk. By employing a complex stiffness approach, we further examined the disk’s damping effects. This dynamic method enabled a detailed description of the apparent stiffness and damping characteristics based on solicitation frequency, test temperature, vibration amplitude, and a predefined static displacement. The results indicated a clearly predominant structural effect over the phase transformation effect, despite the disk’s substantial damping potential.

Enhancing Physiotherapy Outcomes with Photobiomodulation: A Comprehensive Review

Physiotherapy treatments employ complex approaches tailored to the patient’s diagnosis. Exercise is the primary strategy to enhance rehabilitation processes for most individuals. However, electrophysical agents, such as Photobiomodulation (PBM), that utilize specific wavelengths of light to penetrate tissues and stimulate cellular activity, can modulate various biological processes and may improve physiotherapy outcomes. This non-invasive treatment can reduce pain and inflammation, promote tissue repair, and accelerate tissue healing. Currently, PBM has numerous applications, including pain and inflammation treatment, wound healing (such as diabetic foot ulcers, pressure ulcers, post-surgery wounds, and skin grafts in burn injuries), and the management of musculoskeletal disorders (such as arthritis, tendinopathies, muscle injuries, and spinal disorders). It is also utilized to improve muscle performance and recovery in rehabilitation and sports. Additionally, transcranial PBM has shown promise in enhancing neurorehabilitative processes by facilitating the recovery of cognitive and motor functions in various types of lesions. The safety and efficacy of this treatment allow it to be incorporated alongside regular exercises and manual therapies as an adjunctive treatment, potentially enhancing outcomes in different areas of rehabilitation.

The Complex Approach to Environmental and Technological Project Management to Enhance the Sustainability of Industrial Systems

To achieve sustainability, industrial systems need to be modernized to improve resource efficiency while optimizing environmental and social performance. The implementation of environmental and technological projects is a complex management process and requires sufficient innovative potential and serious investments, which not every company can provide. Network integration of companies, providing synergy of resources and potentials, is an effective tool for the development and implementation of innovative technologies that allow achieving optimal resource efficiency indicators. An integrated complex approach to the formation of a cross- industrial system on the principles of network integration and partnerships ensures technological interaction between companies, optimizes the methods and forms of their economic activities, allows integration participants to achieve strategic goals and ensure environmental and social effects for the territory of presence. The sustainability of such a system is expressed in its ability to withstand internal threats and external challenges. Approaches to balancing environmental and technological effects while simultaneously analysing social efficiency have not received sufficient development in scientific research. This article discusses an approach to the selection of environmental-technological projects based on criteria for assessing the sustainability and resilience of industrial systems. The authors’ approach has been tested using two industrial symbioses of advanced socio-economic development territories in the city of Novotroitsk (Orenburg region, Russian Federation). The authors presented calculated indicators of resource efficiency before and after the formation of a cross-sectoral industrial system in order to identify social and environmental effects in Novotroitsk. This approach to the assessment of environmental and technological projects allows to concentrate government support measures on the general priorities of the implementation of regional economic and industrial policies.

Transformation of the Cultural Landscape in the Central Part of the Historical Region of Warmia in Poland

The study analyzed the cultural landscape of Dobre Miasto municipality, which is situated in north-eastern Poland, in the heart of the Warmia region. Cultural traditions that have been passed down from generation to generation and are presently being revived constitute the backbone of Warmia’s cultural heritage. The Warmian landscape comprises several distinctive components, including traditional settlement patterns dating back to the 13th and 14th centuries, as well as cultural values (historical and architectural values, and the level of their preservation) that are being increasingly recognized and contribute to the region’s tourism potential. The growing awareness that the cultural landscape must be preserved for the future generations implies that landscape protection is no longer regarded as a niche problem that is of interest only to experts in the field, and that activities should also be initiated at the local level. The study aimed to specify measures that should be undertaken to protect the components of the cultural landscape and to propose strategies that will not only contribute to the appreciation of cultural values, but will also facilitate the promotion and preservation of cultural landscape components that are gradually disappearing from the rural fabric. This complex approach to the rational management of environmental resources can set an example for other lake regions with clearly defined historical roots and well-preserved cultural values. The resulting guidelines and conclusions can be useful for developing new planning documents and updating and validating the existing legal regulations on planning, development, land use, and protection of the cultural landscape.

Streamflow Prediction Using Complex Networks.

The reliable prediction of streamflow is crucial for various water resources, environmental, and ecosystem applications. The current study employs a complex networks-based approach for the prediction of streamflow. The approach consists of three major steps: (1) the formation of a network using streamflow time series; (2) the calculation of the clustering coefficient (CC) as a network measure; and (3) the use of a clustering coefficient-based nearest neighbor search procedure for streamflow prediction. For network construction, each timestep is considered as a node and the existence of link between any node pair is identified based on the difference (distance) between the streamflow values of the nodes. Different distance threshold values are used to identify the critical distance threshold to form the network. The complex networks-based approach is implemented for the prediction of daily streamflow at 142 stations in the contiguous United States. The prediction accuracy is quantified using three statistical measures: correlation coefficient (R), normalized root mean square error (NRMSE), and Nash-Sutcliffe efficiency (NSE). The influence of the number of neighbors on the prediction accuracy is also investigated. The results, obtained with the critical distance threshold, reveal that the clustering coefficients for the 142 stations range from 0.799 to 0.999. Overall, the prediction approach yields reasonably good results for all 142 stations, with R values ranging from 0.05 to 0.99, NRMSE values ranging from 0.1 to 12.3, and the NSE values ranging from -0.89 to 0.99. An attempt is also made to examine the relationship between prediction accuracy and the catchment characteristics/streamflow statistical properties (drainage area, mean flow, coefficient of variation of flow). The results suggest that the prediction accuracy does not have much of a relationship with the drainage area and the mean streamflow values, but with the coefficient of variation of flow. The outcomes from this study are certainly promising regarding the application of complex networks-based concepts for the prediction of streamflow (and other hydrologic) time series.

Panorama de pesquisas sobre ecossistemas de inovação:

Innovation ecosystems are composed of interconnected and interdependent network actors that shape scientific, technological and political-economic dynamics with high transformative capacity related to information and innovation. The study analyzes the panorama of research on “innovation ecosystems”, as a theme produced and communicated in scientific literature. As an exploratory and descriptive research, it uses the Dimensions database and VOSviewer network analysis software, for the collection, representation and inferential analysis of production and connection indicators on this topic. It demonstrates the exponential growth of publications on innovation ecosystems, its thematic coverage and its scope of emerging research highlighting themes such as technological transfer, digital transformation, internet, regional ecosystem and open innovation. Innovation ecosystems are configured as a transversal theme that allows for multilateral and complex theoretical approaches due to the broad and profound possibility of connecting other themes, concepts, contents and contexts of social production.

Exploring the journey: A comprehensive review of vaccine development against Klebsiella pneumoniae

Klebsiella pneumoniae, a prominent nosocomial pathogen, poses a critical global health threat due to its multidrug-resistant (MDR) and hypervirulent strains. This comprehensive review focuses into the complex approaches undertaken in the development of vaccines against K. pneumoniae. Traditional methods, such as whole-cell and ribosomal-based vaccines, are compared with modern strategies, including DNA and mRNA vaccines, and extracellular vesicles (EVs), among others. Each method presents unique advantages and challenges, emphasising the complexity of developing an effective vaccine against this pathogen. Significant advancements in computational tools and artificial intelligence (AI) have revolutionised antigen identification and vaccine design, enhancing the precision and efficiency of developing multiepitope-based vaccines. The review also highlights the potential of glycomics and immunoinformatics in identifying key antigenic components and elucidating immune evasion mechanisms employed by K. pneumoniae. Despite progress, challenges remain in ensuring the safety, efficacy, and manufacturability of these vaccines. Notably, EVs demonstrate promise due to their intrinsic adjuvant properties and ability to elicit robust immune responses, although concerns regarding inflammation and antigen variability persist. This review provides a critical overview of the current landscape of K. pneumoniae vaccine development, stressing the need for continued innovation and interdisciplinary collaboration to address this pressing public health issue. The integration of advanced computational methods and AI holds the potential to accelerate the development of effective immunotherapies, paving the way for novel vaccines against MDR K. pneumoniae.

Complex optical systems for individualized correction of presbyopia

Amultitude of available intraocular lens (IOL) models enable apersonalized approach to presbyopia correction in order to meet each patient's needs. This review article discusses more complex approaches which can be useful in selected cases. The concept of reversible trifocality enables correction of presbyopia using asupplementary intraocular lens (IOL), which can be removed if necessary (e.g., intolerance to multifocal optics). The use of capsulotomy-fixated IOLs enables high precision for positioning of the lens and better stability compared to conventional capsular bag-fixated IOLs, which can be particularly advantageous in multifocal optics. The mix and match concept enables acombination of different IOLs with various optical principles to achieve the desired binocular effect. Binocular IOL systems, which consist of two complementary IOLs, can be seen as afurther development of the mix and match concept. Knowledge of the available options and their application can further improve correction of presbyopia.

Management of alcohol withdrawal syndrome (AWS)

Alcohol withdrawal syndrome (AWS) is a complex set of symptoms that occur in alcohol-dependent individuals after sudden withdrawal or a significant reduction in alcohol consumption. AWS symptoms occur in about 50% of alcohol abusers. These symptoms may include restlessness, tremor, nausea, nervousness, tachycardia, elevated blood pressure, hyperhidrosis, insomnia, hyperactivity, and hallucinations. In some cases, seizures may occur and delirium tremens may develop, which is life-threatening and an absolute indication for hospitalization of the patient. Effective treatment of AWS is the key to prevent complications and to reduce the risk of death. Treatment of alcohol withdrawal syndrome requires a complex approach that combines properly performed diagnosis, careful monitoring of the patient's condition, pharmacotherapy, equalization of electrolyte disorders, adequate hydration of the patient, supplementation of thiamine deficiencies and, in the case of symptoms of alcoholic delirium, intensive medical care. Pharmacological treatment plays a key role, with the first line of treatment being benzodiazepines, which reduce the risk of epileptic seizures and delirium tremens, and reduce mortality in the course of AWS. Individualized therapy adjustment and patient monitoring are crucial to ensure effective and safe treatment.

Performance enhancement of reactive foam dyeing for cotton fabric through different foaming agents and stabilizers

Purpose In the textile dyeing industry, the foam dyeing has been recognized as a significantly sustainable alternative for the cotton fabrics. However, this efficient technology undergoes the many issues related to the foam generation, foam optimization and the required performance of the resultant fabrics. The purpose of this paper is to address these issues through the development and optimization of the novel reactive foam dyeing recipes for the cotton fabrics. Design/methodology/approach The foam dyeing recipes were generated and optimized using the different stabilizers, foaming agents and three primary colors of reactive dyes. The different recipes were applied onto the cotton fabric using laboratory scale foam coating machine. The performance of the foam coated and padded fabrics was evaluated using different criteria including the shade depth, rubbing fastness, air permeability, washing fastness, perspiration fastness, light fastness and tear strength. Then, a complex decision-making approach, namely, analytic hierarchy process (AHP), was applied for the ranking of the key recipes based on the main criteria. Findings The newly optimized foam dyeing recipes were found very competitive with the conventional pad dyeing process with respect to the shade-depth and the other performance properties. The optimization of foaming parameters and addition of stabilizers have advanced the foam dyeing process, which would accelerate the implementation of foam dyeing methods in the textile industry. Furthermore, significant water and energy savings would be achieved as compared to the conventional foam dyeing. AHP model offered a comprehensive and rational way to identify the most important recipes amongst the selected recipes. Originality/value In this research, novel foam dyeing recipes have been developed for the cotton fabrics through the optimization of the different stabilizers, foaming agents and the three primary colors of reactive dyes. Until now, the exiting literature has not reported the combination of these stabilizers with the different foaming agents and three primary reactive dyes for the improvement of sustainable foam cotton dyeing process.

Isaiah 56:9–59:21 and the Pursuit of שלום

Abstract Isaiah 56:9–59:21 is a carefully constructed unit with a coherent rhetorical agenda. By reinvigorating traditional prophetic literary materials, it aims to reform some traditional practices, revitalize social structures, and point toward a conception of שלום as the product of Yhwh’s action. The unit serves the larger construction of Isaiah 56–66 as a whole. It may be read as an attempt to reimagine the world without Persian rule while not identifying that rule as a sort of given against which it must define itself. That complex approach to persuasion and audience agency shows a level of creativity not always associated with this text.

On the prediction of rare events when sampling from large data

When modeling rare events using logistic regression, independent samples of event occurrence (ones) and nonoccurrence (zeros) are commonly taken from large datasets in order to fit models efficiently. A deterministic offset may then be included in the model to compensate for that sampling method. We propose a more complex sampling approach using stratified sampling within the sets of ones and zeros to ensure that we may sample more zeros from strata of interest. This design may avoid situations in which a random sample of zeros fails to capture the range of a key covariate. We employ sampling weights along with stratum-specific intercepts to obtain unbiased estimates of the logistic regression coefficients (including the intercept) and their standard errors. We use simulation to show that this method provides unbiased parameter estimates comparable with those of maximum likelihood. We also illustrate an application of this method to wildland fire occurrence prediction in a study area in northwestern Ontario, Canada.

Short communication: Five ways UK European Capitals and cities of culture have connected cultural activities with nature and their impacts on health and wellbeing, wider determinants of health and inequality

ObjectiveTo rapidly synthesise evidence for local practice on what initiatives UK European Capitals and Cities of Culture (UKEUCoCs) have implemented connecting cultural activities with green, blue, or outdoor space (culture-nature initiatives) and their impacts on planetary health outcomes: personal health and wellbeing, wider determinants of health particularly the environment, and existing inequality. Study designRapid evidence review. MethodsA rapid review of published articles and evaluation reports. Published articles were identified through database searches (Proquest, OVID, Scopus, Web of Science, MEDLINE) in January–February 2024. Data was extracted directly into a table and findings synthesised narratively by theme. ResultsPublished evidence about UKEUCoC culture-nature initiatives was limited but five initiative types were identified: 1) growing-focused activities; 2) activities exploring human-nature relationships; 3) targeted nature-based wellbeing activities; 4) activities connecting cultural engagement with environmental activism; and 5) use of outdoor spaces for artworks, performances and festivals. UKEUCoC culture-nature initiatives may contribute to short-term improvements in mental health and wellbeing (confidence, self-esteem, subjective wellbeing), community health (community relations, civic pride), cultural participation, and local environmental quality and use, but risk widening existing inequalities. Co-creating initiatives at hyper-local levels with marginalised groups and trusted Community Champions, active involvement, and creating equitable access to livelihood opportunities may mitigate inequality risks. ConclusionsEvidence is limited but suggests UKEUCoC culture-nature initiatives could positively support planetary health outcomes in the short-term. Equity in these outcomes appears to rely however, on action to ensure the involvement of and sustainable livelihood creation for marginalised groups. It is unclear how outcomes are generated across the initiative types identified, including through interactions between them, where they are implemented. The five initiative types identified in this work could be targeted for further investigation in research and practice on culture-nature initiatives for health more generally, using a complex systems approach to evaluation.

Double tracheoesophageal fistula after prolonged intubation during COVID-19: surgical treatment by colonic transposition in the retrosternal space

This is a patient with 2 tracheoesophageal fistulas following prolonged intubation due to COVID-19 with severe evolution and indication for surgical treatment due to failure of endoscopic treatment. Patient in a long hospital stay, unable to eat an oral diet, malnourished, chronic cough, developing persistent pneumonia due to recurrent salivary bronchoaspiration. The case was treated by complex surgical intervention consisting of proximal and distal partial esophagectomy with reconstruction of food transit by colonic bypass in the anterior mediastinum, resection and tracheal reanastomosis. The final result was good, with the patient being discharged from the hospital on a restored oral diet and free spontaneous breathing. The resolution of an extremely serious case through a complex and exceptional surgical approach, which imposed enormous challenges in pre-operative preparation and detailed therapeutic planning, with single-stage surgical action by two surgical teams (Digestive System Surgery and Thoracic Surgery).

A complex network analysis approach to bankruptcy prediction using company relational information-based drivers

Corporate bankruptcy prediction is a long-standing topic of interest for a variety of stakeholders. Various prediction methodologies have been proposed to achieve more accurate predictions. So far, most studies have focused on making predictions using artificial intelligence models fed with accounting information only or a combination of accounting information and other category or categories of information. This study proposes new corporate governance drivers that exploit company relational information using board of directors’ networks of companies and the concept of node embeddings obtained by mapping large directors’ networks to lower-dimensional spaces. The contribution of these new drivers to the overall prediction performance is assessed using data on UK companies listed on the London Stock Exchange. The proposed two-stage methodology consists of devising new drivers in the first stage followed by risk class prediction in the second stage. We examine different complex network structures that capture the diversity of connectivity patterns observed in directors’ networks. Empirical results suggest that the proposed network-based drivers that use company relational corporate governance information significantly improve the performance of bankruptcy prediction.

Conceptual frameworks for the integration of genetic and social epidemiology in complex diseases

Uncovering the root causes of complex diseases requires complex approaches, yet many studies continue to isolate the effects of genetic and social determinants of disease. Epidemiologic efforts that under-utilize genetic epidemiology methods and findings may lead to incomplete understanding of disease. Meanwhile, genetic epidemiology studies are often conducted without consideration of social and environmental context, limiting the public health impact of genomic discoveries. This divide endures despite shared goals and increases in interdisciplinary data due to a lack of shared theoretical frameworks and differing language. Here, we demonstrate that bridging epidemiological divides does not require entirely new ways of thinking. Existing social epidemiology frameworks including Ecosocial theory and Fundamental Cause Theory, can both be extended to incorporate principles from genetic epidemiology. We show that genetic epidemiology can strengthen, rather than detract from, efforts to understand the impact of social determinants of health. In addition to presenting theoretical synergies, we offer practical examples of how genetics can improve the public health impact of epidemiology studies across the field. Ultimately, we aim to provide a guiding framework for trainees and established epidemiologists to think about diseases and complex systems and foster more fruitful collaboration between genetic and traditional epidemiological disciplines.

The Use of Project Management to Provide Technological Sovereig

The most important factors, which stipulate the development of any state, are the level of technological independence and availability of sustainable competitive advantages in innovation sphere. Achievement of technological sovereignty in the Russian Federation is a priority task, whose topicality in conditions of unprecedented sanctions pressure is self-evident. In the research the authors analyzed works by home and overseas experts in the field of technological sovereignty and described the problem of possible damage to ecology and human life in the process of developing the technological sphere. Proceed from it the authors put forward an assumption about the necessity of complex approach to reaching the level of critical and end-to-end technologies with regard to goals of sustainable development on the basis of project management. Findings of the research show that there is a certain mutual conformity of goals of sustainable development and national projects being implemented. However, today we have not got projects, whose goals combine achievements of technological independence and principles of sustainable development of the country. The article provides a conceptual scheme of project management use elaborated by the authors. Academic novelty of the scheme is demonstrated by complementarity of specific goals of technological sovereignty and principles of sustainable development.